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Week 6/Programming Assignment 3 - Functions.py
joe733/Joy-Of-Computing-Using-Python-2019
0
12790051
<filename>Week 6/Programming Assignment 3 - Functions.py ''' Given an integer number n, define a function named printDict() which can print a dictionary where the keys are numbers between 1 and n (both included) and the values are square of keys. The function printDict() doesn't take any argument. >>Input Format: The first line contains the number n. >>Output Format: Print the dictionary in one line. >>Example: Input: 5 Output: {1: 1, 2: 4, 3: 9, 4: 16, 5: 25} NOTE: You are supposed to write the code for the function printDict() only. The function has already been called in the main part of the code. ''' def printDict(): print(dict([(i,i**2) for i in range (1,x+1)]), end="") x=int(input()) printDict()
4.65625
5
setup.py
CrawlerCode/PythonTools
0
12790052
<gh_stars>0 from setuptools import setup def readme(): with open("README.rst") as f: README = f.read() return README TYPE = "CORE" packages = [] install_requires = [] if TYPE == "CORE": packages = ['pythontools.core', 'pythontools.identity', 'pythontools.sockets', 'pythontools.dev', 'pythontools.telegram'] install_requires.extend(['requests', 'colorama', 'getmac', 'stdiomask', 'cryptography']) if TYPE == "GUI": packages.append('pythontools.gui') install_requires.append('PyQt5') if TYPE == "WEBBOT": packages.append('pythontools.webbot') install_requires.append('selenium') setup( name='CrawlerCodePythonTools' + ('-Gui' if TYPE == "GUI" else '-WebBot' if TYPE == "WEBBOT" else ''), version='1.5.2', packages=packages, url='https://github.com/CrawlerCode', license='MIT', author='CrawlerCode', author_email='', description='Tools for Python', long_description=readme(), long_description_content_type="text/x-rst", include_package_data=True, install_requires=install_requires )
1.609375
2
study/spMap.py
Suryavf/SelfDrivingCar
11
12790053
<filename>study/spMap.py import os import glob import h5py import numpy as np import cv2 as cv from matplotlib import pyplot as plt # Parameters path = '/media/victor/Documentos/' outpath = '/media/victor/Documentos/Thesis/AttentionMap/Resume10' dimImage = ( 96,192) dimEncode = ( 12, 24) n_head = 2 n_task = 2 n_sample = 120*20 def getint(name): basename = name.partition('.') _, num = basename[0].split('resume') return int(num) filesname = glob.glob(os.path.join(path,'*.sy')) filesname.sort() filename = '/media/victor/Documentos/resume10.sy' # Getting data with h5py.File(filename, 'r') as h5_file: image = np.array(h5_file['image']) alpha = np.array(h5_file['alpha']) print('Load data done\n') t = 0 # Genera mapas de atencion en video alpha = alpha.reshape([n_sample,n_head,dimEncode[0],dimEncode[1],n_task]) alpha = alpha/alpha.max() """ for attmap,sample in zip(alpha,image): # a: [n_head,h,w,n_task] # s: [3,H,W] tasks = list() for n in range(n_task): heads = list() for h in range(n_head): # Up-sampling att = attmap[h,:,:,n] att = cv.resize(att,None,fx=8,fy=8, interpolation = cv.INTER_AREA) att = cv.GaussianBlur(att,(11,11),0) #att = np.expand_dims(att,axis=0) # [1,H,W] # Apply sample = att #sample*att heads.append( sample ) #np.moveaxis(sample,0,2) ) tasks.append( cv.vconcat(heads) ) plt.figure(1); plt.clf() plt.imshow(cv.hconcat(tasks)) plt.title('Frame ' + str(t)) plt.pause(0.1) t += 1 """ n_up = 8 for attmap,sample in zip(alpha,image): # a: [n_head,h,w,n_task] # s: [3,H,W] sample = np.moveaxis(sample,0,2) maps = list() for n in range(n_task): map = np.zeros([ dimEncode[0]*n_up,dimEncode[1]*n_up ,3]) for h in range(n_head): # Up-sampling att = attmap[h,:,:,n] att = cv.resize(att,None,fx=n_up,fy=n_up, interpolation = cv.INTER_AREA) att = cv.GaussianBlur(att,(11,11),0) map[:,:,h] = att maps.append( (0.5*sample+0.5*map) ) img = cv.hconcat(maps)*255 img = img.astype('float32') img = cv.cvtColor(img,cv.COLOR_RGB2BGR) fileout = os.path.join(outpath,'sample%i.png'%t) cv.imwrite(fileout,img) #plt.imshow(cv.hconcat(maps)) #fileout = os.path.join(outpath,'sample%i.png'%t) #plt.savefig(fileout) #print('Create %s'%fileout) #plt.title('Frame ' + str(t)) #plt.pause(0.1) t += 1
2.375
2
.github/workflows/get_version_and_update.py
gdt050579/GView
7
12790054
import sys import os import shutil if len(sys.argv) < 2: print("Failed to obtain GView.hpp location") exit(1) header_location = sys.argv[1] if not os.path.exists(header_location): print("Path {} does not exists!".format(header_location)) exit(1) default_version_to_update = 1 # major=0, minor=1, patch=2 if len(sys.argv) > 2: version_to_update = sys.argv[2] defined_versions = { "major": 0, "minor": 1, "patch": 2 } default_version_to_update = defined_versions[version_to_update] reset_lower_versions = True header_output_location = header_location+'.new' found_version = False with open(header_location, 'r') as f: with open(header_output_location, 'w') as g: for line in f: if line.startswith('#define GVIEW_VERSION '): version = line.split('#define GVIEW_VERSION ')[ 1].strip(' \r\n\t\"') version_array = version.split('.') value = int(version_array[default_version_to_update])+1 version_array[default_version_to_update] = value for i in range(default_version_to_update+1, 3): version_array[i] = 0 version = "{}.{}.{}".format( version_array[0], version_array[1], version_array[2]) line = '#define GVIEW_VERSION "{}"\n'.format(version) found_version = True os.putenv('GVIEW_VERSION', version) g.write(line) if not found_version: print("Failed to find GVIEW_VERSION") exit(1) shutil.move(header_output_location, header_location) exit(0)
2.484375
2
utils/redis_utils.py
sdgdsffdsfff/qtalk_search
1
12790055
<reponame>sdgdsffdsfff/qtalk_search #!/usr/bin/env python # -*- coding:utf-8 -*- __author__ = 'jingyu.he' import redis from redis import sentinel import json from conf.cache_params_define import * # from utils.logger_conf import configure_logger # log_path = get_logger_file(name='reids.log') # redis_log = configure_logger('redis', log_path) try: if if_redis_sentinel: _hosts = [hp.split(':') for hp in pre_rs_hosts] hosts = [(hp[0].strip(), int(hp[1].strip())) for hp in _hosts] r_sentinel = sentinel.Sentinel(hosts, socket_timeout=r_timeout) redis_cli = r_sentinel.master_for(r_master, socket_timeout=r_timeout, password=<PASSWORD>, db=r_database, decode_responses=True) else: redis_cli = redis.StrictRedis(host=r_host, port=r_port, db=r_database, password=r_password, decode_responses=True) except (KeyError, ValueError, IndexError) as e: raise TypeError('wrong configure pattern') # redis_log.exception('wrong configure pattern') # exit(0) class RedisUtil: def __init__(self): self.redis = redis_cli self.single_key = SINGLE_KEY self.muc_key = MUC_KEY self.single_trace_key = SINGLE_TRACE_KEY self.muc_trace_key = MUC_TRACE_KEY self.user_registed_mucs = USER_MUCS self.all_user_key = ALL_USER_DATA_CACHE # self.router = [self.single_key, self.muc_key, self.single_trace_key, self.muc_trace_key] def get_user_habit(self, user_id): """ 获取redis中用户的缓存 包括个人、群组聊天顺序 个人、群组聊天频率 :param user_id: :return: """ router = [self.single_key, self.muc_key, self.single_trace_key, self.muc_trace_key, self.user_registed_mucs] habit = {} for key in router: _k = key + '_' + user_id if key in [self.single_key, self.muc_key, self.user_registed_mucs]: habit[key] = self.redis.lrange(name=_k, start=0, end=-1) else: habit[key] = self.redis.zrevrangebyscore(name=_k, max='+inf', min=10, start=0, num=10) # TODO 这个num可能应该走limit 和 offset return habit def get_all_user_data(self, domain=''): if domain: __k = self.all_user_key + '_' + domain else: __k = self.all_user_key user_data = self.redis.get(name=__k) try: if not user_data: return [] user_data = json.loads(user_data) return user_data except json.JSONDecodeError: return [] def set_all_user_data(self, data, domain=''): data = json.dumps(data, ensure_ascii=False) if domain: __k = self.all_user_key + '_' + domain else: __k = self.all_user_key self.redis.set(name=__k, value=data, ex=86400) def get_single_lookback(self, user, term): res = self.redis.get(LOOKBACK_SINGLE_CACHE + '_' + user + '_' + term) if res: try: if not res: return None res = json.loads(res) except Exception as e: print('LOAD SINGLE LOOKBACK ERROR {}'.format(e)) return None return res def set_single_lookback(self, user, term, data): self.redis.set(name=LOOKBACK_SINGLE_CACHE + '_' + user + '_' + term, value=json.dumps(data, ensure_ascii=False), ex=300) def get_muc_lookback(self, user, term): res = self.redis.get(LOOKBACK_MUC_CACHE + '_' + user + '_' + term) if res: try: if not res: return None res = json.loads(res) except Exception as e: print('LOAD SINGLE LOOKBACK ERROR {}'.format(e)) res = None return res def set_muc_lookback(self, user, term, data): self.redis.set(name=LOOKBACK_MUC_CACHE + '_' + user + '_' + term, value=json.dumps(data, ensure_ascii=False), ex=300) def get_agg_cache(self, user, term): """ 结构: user - { 'key' : term, 'data': _info } :param user: :param term: :return: """ name = LOOKBACK_AGG_CACHE + '_' + user res = self.redis.get(name=name) try: if not res: return [] res = json.loads(res) except Exception as __e: print(__e) return [] if res.get('term', '') != term: self.redis.delete(name) return [] return res['data'] def set_agg_cache(self, user, term, data): name = LOOKBACK_AGG_CACHE + '_' + user info = {'term': term, 'data': data} self.redis.set(name=name, value=json.dumps(info, ensure_ascii=False), ex=300)
1.789063
2
agilife/api/views.py
michellydsalves/agilife-api
0
12790056
<filename>agilife/api/views.py from rest_framework import viewsets from rest_framework import mixins from rest_framework import generics from rest_framework.views import APIView from rest_framework.authentication import TokenAuthentication from rest_framework.permissions import IsAuthenticated from rest_framework.decorators import authentication_classes, permission_classes from api.serializers import ( UserModelSerializer, PartnerModelSerializer, HomeworkModelSerializer, UserHomeworkModelSerializer, HomeworkVoucherTypeModelSerializer, HomeworkVoucherModelSerializer, UserHomeworkVoucherModelSerializer, ForumTypeModelSerializer, ForumModelSerializer, ForumCommentModelSerializer, UserForumFavoriteModelSerializer, ContentTypeModelSerializer, ContentModelSerializer, UserContentModelSerializer, PaymentModelSerializer ) from api.models import ( Partner, User, Homework, UserHomework, HomeworkVoucherType, HomeworkVoucher, UserHomeworkVoucher, ForumType, Forum, ForumComment, UserForumFavorite, ContentType, Content, UserContent, Payment ) @authentication_classes([]) @permission_classes([]) class UserApiViewSet(viewsets.ModelViewSet): queryset = User.objects.all() serializer_class = UserModelSerializer class PartnerApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = Partner.objects.all() serializer_class = PartnerModelSerializer class HomeworkApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = Homework.objects.all() serializer_class = HomeworkModelSerializer class UserHomeworkApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = UserHomework.objects.all() serializer_class = UserHomeworkModelSerializer class HomeworkVoucherTypeListOnlyAPIView(mixins.ListModelMixin, generics.GenericAPIView): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = HomeworkVoucherType.objects.all() serializer_class = HomeworkVoucherTypeModelSerializer def get(self, request, *args, **kwargs): return self.list(request, *args, **kwargs) class HomeworkVoucherListOnlyAPIView(mixins.ListModelMixin, generics.GenericAPIView): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = HomeworkVoucher.objects.all() serializer_class = HomeworkVoucherModelSerializer def get(self, request, *args, **kwargs): return self.list(request, *args, **kwargs) class UserHomeworkVoucherApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = UserHomeworkVoucher.objects.all() serializer_class = UserHomeworkVoucherModelSerializer class ForumTypeListOnlyAPIView(mixins.ListModelMixin, generics.GenericAPIView): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = ForumType.objects.all() serializer_class = ForumTypeModelSerializer def get(self, request, *args, **kwargs): return self.list(request, *args, **kwargs) class ForumApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = Forum.objects.all() serializer_class = ForumModelSerializer class ForumCommentApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = ForumComment.objects.all() serializer_class = ForumCommentModelSerializer class UserForumFavoriteApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = UserForumFavorite.objects.all() serializer_class = UserForumFavoriteModelSerializer class ContentTypeListOnlyAPIView(mixins.ListModelMixin, generics.GenericAPIView): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = ContentType.objects.all() serializer_class = ContentTypeModelSerializer def get(self, request, *args, **kwargs): return self.list(request, *args, **kwargs) class ContentListOnlyAPIView(mixins.ListModelMixin, generics.GenericAPIView): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = Content.objects.all() serializer_class = ContentModelSerializer def get(self, request, *args, **kwargs): return self.list(request, *args, **kwargs) class UserContentApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = UserContent.objects.all() serializer_class = UserContentModelSerializer class PaymentApiViewSet(viewsets.ModelViewSet): authentication_classes = [TokenAuthentication] permission_classes = [IsAuthenticated] queryset = Payment.objects.all() serializer_class = PaymentModelSerializer
1.921875
2
Python/Nearly Lucky Number.py
bic-potato/codeforces_learning
0
12790057
<filename>Python/Nearly Lucky Number.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Oct 19 21:11:16 2020 @author: zuoxichen """ import sys def main_args(): a=list(input()) k=0 n=0 for i in a: n+=1 if (i=='4' or i=='7'): k+=1 else: k+=0 return [n,k] list1=main_args() k=str(list1[1]) n=list1[0] if n==int(k) and n!=1: print('YES') sys.exit(0) else: for i in k : if i!='4' or i!='7': print('NO') sys.exit(0) print('YES')
3.515625
4
server/etes/migrations/0024_auto_20181119_1213.py
ethanmnrd/TicketXchnge
0
12790058
<gh_stars>0 # Generated by Django 2.1.3 on 2018-11-19 20:13 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('etes', '0023_auto_20181119_1203'), ] operations = [ migrations.AddField( model_name='ticket', name='ticket_address', field=models.CharField(default='San José State University, Washington Sq, San Jose, CA, United States', max_length=200), preserve_default=False, ), migrations.AlterField( model_name='ticket', name='ticket_price', field=models.DecimalField(decimal_places=2, max_digits=10), ), ]
1.617188
2
taschenrechner.py
it-moerike/python
0
12790059
<gh_stars>0 from tkinter import * def rechnen(): if operator.curselection() == (0,): ausgabe["text"] = float(zahl1.get()) + float(zahl2.get()) elif operator.curselection() == (1,): ausgabe["text"] = float(zahl1.get()) - float(zahl2.get()) elif operator.curselection() == (2,): ausgabe["text"] = float(zahl1.get()) * float(zahl2.get()) elif operator.curselection() == (3,): ausgabe["text"] = float(zahl1.get()) / float(zahl2.get()) window = Tk() window.title("Taschenrechner") zahl1 = Entry(window) operator = Listbox(window) operator.insert(0, "+") operator.insert(1, "-") operator.insert(2, "*") operator.insert(3, "/") zahl2 = Entry(window) button = Button(window, command=rechnen, text="Los", bg='#FBD975') ausgabe = Label(window) zahl1.grid(row=0, column=0) operator.grid(row=0, column=1) zahl2.grid(row=0, column=2) button.grid(row=1, column=2, sticky=E) ausgabe.grid(row=2) window.mainloop()
3.21875
3
scripts/mongodb_store.py
coastrock/CEBD1261-2019-fall-group-project
1
12790060
try: from pyspark import SparkContext, SparkConf from pyspark.sql import SparkSession import pyspark.sql.functions as f # from operator import add except Exception as e: print(e) ## http://www.hongyusu.com/imt/technology/spark-via-python-basic-setup-count-lines-and-word-counts.html def push_mongo(): spark = SparkSession \ .builder \ .appName("Push to MongoDB") \ .master("spark://master:7077") \ .config("spark.mongodb.input.uri", "mongodb://root:password@mongo/test.coll?authSource=admin") \ .config("spark.mongodb.output.uri", "mongodb://root:password@mongo/test.coll?authSource=admin") \ .config('spark.jars.packages', 'org.mongodb.spark:mongo-spark-connector_2.11:2.4.0')\ .getOrCreate() sc = spark.sparkContext sc.setLogLevel('WARN') # Reading Data from volume acc_mongo=spark.read.csv("/volume/data") #Show Mongo data acc_mongo.show() # Store data in MongoDB acc_mongo.write.format("com.mongodb.spark.sql.DefaultSource").mode("append").save() # End the Spark Context spark.stop() if __name__ == "__main__": push_mongo()
2.421875
2
UVa 231 - Testing the Catcher/sample/main.py
tadvi/uva
1
12790061
''' Created on Jul 20, 2013 @author: <NAME> ''' import sys INF = 1 << 31 def LDS(array): N = len(array) longest = [0] * N longest[0] = 1 for i in range(1, N): currMax = 1 for j in range(i): if array[i] <= array[j] and longest[j] + 1 > currMax: currMax = longest[j] + 1 longest[i] = currMax return max(longest) if __name__ == '__main__': sys.stdin = open('input.txt', 'r') array = [] while True: n = int(input()) if n == -1: print('maximum possible interceptions: %d' % LDS(array)) array = [] n1 = int(input()) if n1 == -1: break else: array.append(n1) else: array.append(n)
3.125
3
lib/config/default.py
yaopengUSTC/mbit-skin-cancer
3
12790062
<reponame>yaopengUSTC/mbit-skin-cancer<gh_stars>1-10 from __future__ import absolute_import from __future__ import division from __future__ import print_function from yacs.config import CfgNode as CN _C = CN() # ----- BASIC SETTINGS ----- _C.NAME = "default" _C.OUTPUT_DIR = "./output/derm_7pt" _C.VALID_STEP = 5 _C.SAVE_STEP = 5 _C.SHOW_STEP = 20 _C.PIN_MEMORY = True _C.INPUT_SIZE = (224, 224) # (h, w) _C.COLOR_SPACE = "RGB" _C.RESUME_MODEL = "" _C.RESUME_MODE = "all" _C.CPU_MODE = False _C.EVAL_MODE = False _C.GPUS = [0, 1] # ----- DATASET BUILDER ----- _C.DATASET = CN() _C.DATASET.DATASET = "" _C.DATASET.ROOT = "" _C.DATASET.DATA_TYPE = "jpg" _C.DATASET.TRAIN_JSON = "" _C.DATASET.VALID_JSON = "" _C.DATASET.TEST_JSON = "" _C.DATASET.CLASS_NAME = ['BCC', 'NV', 'MEL', 'MISC', 'SK'] _C.DATASET.VALID_ADD_ONE_CLASS = False # for ISIC_2019 valid and test, the number of class is increased from 8 to 9. _C.DATASET.ADD_CLASS_NAME = "UNK" _C.DATASET.IMBALANCECIFAR = CN() _C.DATASET.IMBALANCECIFAR.RATIO = 0.01 _C.DATASET.IMBALANCECIFAR.RANDOM_SEED = 0 # ----- BACKBONE BUILDER ----- _C.BACKBONE = CN() _C.BACKBONE.TYPE = "RegNetY_800MF" # refer to lib/backbone/all_models.py _C.BACKBONE.BBN = False _C.BACKBONE.FREEZE = False _C.BACKBONE.PRE_FREEZE = False _C.BACKBONE.PRE_FREEZE_EPOCH = 5 _C.BACKBONE.PRETRAINED = True _C.BACKBONE.PRETRAINED_MODEL = "" # if using drop block, below are drop block parameter _C.BACKBONE.DROP = CN() _C.BACKBONE.DROP.BLOCK_PROB = 0.1 _C.BACKBONE.DROP.BLOCK_SIZE = 5 _C.BACKBONE.DROP.NR_STEPS = 50000 # dropout parameter to the last FC layer _C.BACKBONE.DROP.OUT_PROB = 0.1 # ----- MODULE BUILDER ----- _C.MODULE = CN() _C.MODULE.TYPE = "GAP" # "GAP", "Identity" # ----- CLASSIFIER BUILDER ----- _C.CLASSIFIER = CN() _C.CLASSIFIER.TYPE = "FC" # "FC", "FCNorm" _C.CLASSIFIER.BIAS = True # ----- LOSS BUILDER ----- _C.LOSS = CN() _C.LOSS.WEIGHT_POWER = 1.1 _C.LOSS.EXTRA_WEIGHT = [1.0, 1.0, 1.0, 1.0, 1.0] _C.LOSS.LOSS_TYPE = "CrossEntropy" # "CrossEntropy", "LDAMLoss", "FocalLoss", "LOWLoss", "GHMCLoss", "CCELoss", "MWNLoss" _C.LOSS.SCHEDULER = "default" # "default"--the weights of all classes are "1.0", # "re_weight"--re-weighting by the power of inverse class frequency at all train stage, # "drw"--two-stage strategy using re-weighting at the second stage, # "cls"--cumulative learning strategy to set loss weight. # For drw scheduler _C.LOSS.DRW_EPOCH = 50 # For cls scheduler _C.LOSS.CLS_EPOCH_MIN = 20 _C.LOSS.CLS_EPOCH_MAX = 60 # For LDAMLoss _C.LOSS.LDAM = CN() _C.LOSS.LDAM.MAX_MARGIN = 0.5 # For FocalLoss _C.LOSS.FOCAL = CN() _C.LOSS.FOCAL.GAMMA = 2.0 _C.LOSS.FOCAL.TYPE = "sigmoid" # "cross_entropy", "sigmoid", "ldam" _C.LOSS.FOCAL.SIGMOID = "normal" # "normal", "enlarge" # For LOWLoss _C.LOSS.LOW = CN() _C.LOSS.LOW.LAMB = 0.01 # For GHMCLoss _C.LOSS.GHMC = CN() _C.LOSS.GHMC.BINS = 10 _C.LOSS.GHMC.MOMENTUM = 0.0 # For MWNLoss _C.LOSS.MWNL = CN() _C.LOSS.MWNL.GAMMA = 2.0 _C.LOSS.MWNL.BETA = 0.1 _C.LOSS.MWNL.TYPE = "fix" # "zero", "fix", "decrease" _C.LOSS.MWNL.SIGMOID = "normal" # "normal", "enlarge" # ----- TRAIN BUILDER ----- _C.TRAIN = CN() _C.TRAIN.BATCH_SIZE = 32 # for every gpu _C.TRAIN.MAX_EPOCH = 70 _C.TRAIN.SHUFFLE = True _C.TRAIN.NUM_WORKERS = 8 _C.TRAIN.TENSORBOARD = CN() _C.TRAIN.TENSORBOARD.ENABLE = True # ----- SAMPLER BUILDER ----- _C.TRAIN.SAMPLER = CN() _C.TRAIN.SAMPLER.TYPE = "default" # "default", "weighted sampler", "oversample" _C.TRAIN.SAMPLER.IMAGE_TYPE = "derm" # "derm", "clinic". For derm_7pt dataset used. _C.TRAIN.SAMPLER.BORDER_CROP = "pixel" # "pixel", "ratio" _C.TRAIN.SAMPLER.BORDER_CROP_PIXEL = 0 # An integer specifying how many pixels to crop at the image border. Useful if images contain a black boundary. _C.TRAIN.SAMPLER.BORDER_CROP_RATIO = 0.0 # the ratio of edge of the image to be cropped. _C.TRAIN.SAMPLER.IMAGE_RESIZE = True # whether the input image needs to be resized to a fix size _C.TRAIN.SAMPLER.IMAGE_RESIZE_SHORT = 450 # the need size of the short side of the input image _C.TRAIN.SAMPLER.COLOR_CONSTANCY = False _C.TRAIN.SAMPLER.CONSTANCY_POWER = 6.0 _C.TRAIN.SAMPLER.CONSTANCY_GAMMA = 0.0 # For Modified RandAugment _C.TRAIN.SAMPLER.AUGMENT = CN() _C.TRAIN.SAMPLER.AUGMENT.NEED_AUGMENT = False _C.TRAIN.SAMPLER.AUGMENT.AUG_METHOD = "v1_0" # the method of Modified RandAugment ('v0_0' to 'v3_1') or RandAugment ('rand') (refer to: lib/data_transform/modified_randaugment.py) _C.TRAIN.SAMPLER.AUGMENT.AUG_PROB = 0.7 # the probability parameter 'P' of Modified RandAugment (0.1 -- 0.9) _C.TRAIN.SAMPLER.AUGMENT.AUG_MAG = 10 # the magnitude parameter 'M' of Modified RandAugment (1 -- 20) _C.TRAIN.SAMPLER.AUGMENT.AUG_LAYER_NUM = 1 # the number of transformations applied to a training image if AUG_METHOD = 'rand' # for BBN sampler _C.TRAIN.SAMPLER.DUAL_SAMPLER = CN() _C.TRAIN.SAMPLER.DUAL_SAMPLER.TYPE = "reversed" # "balance", "reverse", "uniform" # for other sampler _C.TRAIN.SAMPLER.WEIGHTED_SAMPLER = CN() _C.TRAIN.SAMPLER.WEIGHTED_SAMPLER.TYPE = "balance" # "balance", "reverse" # for multi crop _C.TRAIN.SAMPLER.MULTI_CROP = CN() _C.TRAIN.SAMPLER.MULTI_CROP.ENABLE = False # Should the crops be order or random for evaluation _C.TRAIN.SAMPLER.MULTI_CROP.CROP_NUM = 16 # Number of crops to use during evaluation (must be N^2) _C.TRAIN.SAMPLER.MULTI_CROP.L_REGION = 1.0 # Only crop within a certain range of the central area (along the long side of the image) _C.TRAIN.SAMPLER.MULTI_CROP.S_REGION = 1.0 # Only crop within a certain range of the central area (along the short side of the image) _C.TRAIN.SAMPLER.MULTI_CROP.SCHEME = 'average' # Averaging or voting over the crop predictions ("vote", "average") # for multi transformation of the center crop _C.TRAIN.SAMPLER.MULTI_SCALE = CN() _C.TRAIN.SAMPLER.MULTI_SCALE.ENABLE = False # whether to perform multi transformation on the central crop _C.TRAIN.SAMPLER.MULTI_SCALE.SCALE_NUM = 12 # Number of scales to use during evaluation (must be less than or equal to the length of SCALE_NAME) _C.TRAIN.SAMPLER.MULTI_SCALE.SCALE_NAME = ["scale_+00", "flip_x_+00", "rotate_90_+00", "rotate_270_+00", "scale_+10", "flip_x_+10", "rotate_90_+10", "rotate_270_+10", "scale_+20", "flip_x_+20", "rotate_90_+20", "rotate_270_+20", "scale_+30", "flip_x_+30", "rotate_90_+30", "rotate_270_+30", "scale_-10", "flip_x_-10", "rotate_90_-10", "rotate_270_-10", "flip_y_+00", "flip_y_+10", "flip_y_-10", "flip_y_+20"] _C.TRAIN.SAMPLER.FIX_MEAN_VAR = CN() _C.TRAIN.SAMPLER.FIX_MEAN_VAR.ENABLE = True # Normalize using the mean and variance of each image, or using fixed values # A fixed set mean (input image will be subtracted from the mean, processing variance) _C.TRAIN.SAMPLER.FIX_MEAN_VAR.SET_MEAN = [0.485, 0.456, 0.406] # A fixed set variance _C.TRAIN.SAMPLER.FIX_MEAN_VAR.SET_VAR = [0.229, 0.224, 0.225] # ----- OPTIMIZER ----- _C.TRAIN.OPTIMIZER = CN() _C.TRAIN.OPTIMIZER.TYPE = "SGD" # 'SGD', 'ADAM', 'NADAM', 'RMSPROP' _C.TRAIN.OPTIMIZER.BASE_LR = 0.001 _C.TRAIN.OPTIMIZER.MOMENTUM = 0.9 _C.TRAIN.OPTIMIZER.WEIGHT_DECAY = 1e-4 # ----- LR_SCHEDULER ----- _C.TRAIN.LR_SCHEDULER = CN() _C.TRAIN.LR_SCHEDULER.TYPE = "multistep" # "steplr", "multistep", "cosine", "warmup" _C.TRAIN.LR_SCHEDULER.LR_LOWER_STEP = 20 # for 'steplr' _C.TRAIN.LR_SCHEDULER.LR_STEP = [40, 50] # for 'multistep' _C.TRAIN.LR_SCHEDULER.LR_FACTOR = 0.1 _C.TRAIN.LR_SCHEDULER.WARM_EPOCH = 5 # for 'warmup' _C.TRAIN.LR_SCHEDULER.COSINE_DECAY_END = 0 # For valid or test _C.TEST = CN() _C.TEST.BATCH_SIZE = 128 # for every gpu _C.TEST.NUM_WORKERS = 8 _C.TEST.MODEL_FILE = "best_model.pth" def update_config(cfg, args): cfg.defrost() cfg.merge_from_file(args.cfg) cfg.merge_from_list(args.opts) cfg.freeze() def update_cfg_name(cfg): ''' modify the cfg.NAME :param cfg: :return: ''' cfg.defrost() cfg_name = cfg.DATASET.DATASET + "." + cfg.BACKBONE.TYPE + ( "_BBN." if cfg.BACKBONE.BBN else ".") + cfg.LOSS.LOSS_TYPE + cfg.NAME cfg.merge_from_list(['NAME', cfg_name]) cfg.freeze()
1.609375
2
wirexfers/__init__.py
plaes/wirexfers
1
12790063
<reponame>plaes/wirexfers # -*- coding: utf-8 -*- """ wirexfers - an online payment library ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ WireXfers is an online payments library, written in Python, providing a simple common API for various online payment protocols (IPizza, Solo/TUPAS). :copyright: (c) 2012-2014 <NAME> :license: ISC, see LICENSE for more details. """ __title__ = 'wirexfers' __version__ = '2014.06-dev' __author__ = '<NAME>' __license__ = 'ISC' __copyright__ = 'Copyright 2012-2014 Priit Laes' from .request import PaymentInfo, PaymentRequest from .response import PaymentResponse
0.855469
1
thualign/utils/hook.py
bryant1410/Mask-Align
27
12790064
<filename>thualign/utils/hook.py # coding=utf-8 # Copyright 2021-Present The THUAlign Authors import torch import numpy as np from .summary import scalar from .misc import get_global_step def print_grad(x, name="x"): if type(x) == torch.Tensor: x.register_hook(lambda x: print("Norm - {} {}:{}\n {}".format(name, list(x.shape), torch.norm(x), x))) elif type(x) == torch.nn.Module: pass # TODO def print_grad_norm(x, name="x", summary=True, verbose=True): if type(x) == torch.Tensor: if verbose: x.register_hook(lambda x: print("Norm - {} {}: {}".format(name, list(x.shape), torch.norm(x)))) if summary: scalar('grad_norm/' + name + '/max', torch.max(x), get_global_step(), write_every_n_steps=1) scalar('grad_norm/' + name + '/min', torch.min(x), get_global_step(), write_every_n_steps=1) scalar('grad_norm/' + name + '/mean', torch.mean(x), get_global_step(), write_every_n_steps=1) scalar('grad_norm/' + name + '/normavg', torch.norm(x)/x.nelement(), get_global_step(), write_every_n_steps=1) elif type(x) == torch.nn.Module: pass # TODO def print_grad_max(x, name="x"): if type(x) == torch.Tensor: x.register_hook(lambda x: print("Grad max - {} {}:\n {}".format(name, list(x.shape), torch.max(x).item()))) elif type(x) == torch.nn.Module: pass # TODO global_collection = {} collection_on = False def start_global_collection(): global collection_on collection_on = True def stop_global_collection(): global collection_on collection_on = False def add_global_collection(v, name="var"): global global_collection if not collection_on: return if name in global_collection: global_collection[name].append(v) else: global_collection[name] = [v] def get_global_collection(name): global global_collection if name in global_collection: return global_collection[name] return None def clear_global_collection(): global global_collection global_collection = {}
2.3125
2
src/negotiating_agent/venv/lib/python3.8/site-packages/geniusweb/protocol/session/mopac/MOPACSettings.py
HahaBill/CollaborativeAI
1
12790065
from typing import List from tudelft_utilities_logging.Reporter import Reporter from geniusweb.deadline.Deadline import Deadline from geniusweb.protocol.session.SessionProtocol import SessionProtocol from geniusweb.protocol.session.SessionSettings import SessionSettings from geniusweb.protocol.session.TeamInfo import TeamInfo from geniusweb.protocol.tournament.Team import Team from geniusweb.references.PartyWithProfile import PartyWithProfile from geniusweb.voting.VotingEvaluator import VotingEvaluator class MOPACSettings (SessionSettings): ''' Settings for MOPAC negotiation. in MOPAC, each party may get a "power" parameter containing an natural number &le;1. ''' def __init__(self, participants:List[TeamInfo] , deadline:Deadline , votingevaluator:VotingEvaluator): ''' @param participants the list of {@link PartyWithProfile} in clockwise order. There must be at least 2 to run the MOPAC protocol. This is not tested in the constructor because this can be initialized with less, for use in TournamentSettings. @param deadline the {@link Deadline} for the negotiation @param votingeval the {@link VotingEvaluator} to use. ''' self._participants = participants; self._deadline = deadline; if participants == None or deadline == None or votingevaluator == None: raise ValueError( "participants, deadline and votingeval must be not none") self._votingevaluator = votingevaluator self._checkTeams(); def getMaxRunTime(self)->float: return self._deadline.getDuration() / 1000. def getProtocol(self, logger:Reporter) -> SessionProtocol : from geniusweb.protocol.session.mopac.MOPACState import MOPACState from geniusweb.protocol.session.mopac.MOPAC import MOPAC return MOPAC(MOPACState(None, [], None, self, {}), logger) def getTeams(self ) -> List[TeamInfo] : return list(self._participants) def getParticipants(self ) -> List[TeamInfo] : ''' bit hacky, same as getTeams, for deserialization... ''' return list(self._participants) def getDeadline(self)-> Deadline : ''' @return the deadline for this negotiation ''' return self._deadline def getAllParties(self)->List[PartyWithProfile] : return [ particip.getParties()[0] for particip in self._participants] def getVotingEvaluator(self)->VotingEvaluator : ''' @return a class that allows us to evaluate the voting results in different ways, selectable by the user. ''' return self._votingevaluator def With(self, team:TeamInfo ) -> "MOPACSettings" : if team.getSize() != 1: raise ValueError( "Added party must have one party but got " + str(team)) newparts:List[TeamInfo] = list(self._participants) newparts.append(team) return MOPACSettings(newparts, self._deadline, self._votingevaluator) def __repr__(self)->str: return "MOPACSettings[" + str(self._participants) + "," +\ str(self._deadline) + "," + \ type(self._votingevaluator).__name__ + "]"; def getTeamSize(self)->int: return 1; def __hash__(self): return hash((tuple(self._participants), self._deadline, self._votingevaluator)) def __eq__(self, other): return isinstance(other, self.__class__)\ and self._participants == other._participants \ and self._deadline == other._deadline \ and self._votingevaluator == other._votingevaluator def _checkTeams(self): ''' @throws IllegalArgumentException if teams have improper power settings. ''' for team in self._participants: if team.getSize() != 1: raise ValueError("All teams must be size 1 but found " + str(team)) party = team.getParties()[0] if 'power' in party.getParty().getParameters().getParameters(): power = party.getParty().getParameters().get("power") if not isinstance(power, int): raise ValueError( "parameter 'power' for party" + str(party) + " must be integer but found " + str(power)) if power < 1: raise ValueError( "parameter 'power' for party" + str(party) + " must be >=1 but found " + str(power))
2.109375
2
data_visualization_app.py
vishwas1234567/Streamlit_tutorials
5
12790066
import streamlit as st import plotly_express as px import pandas as pd # configuration st.set_option('deprecation.showfileUploaderEncoding', False) # title of the app st.title("Data Visualization App") # Add a sidebar st.sidebar.subheader("Visualization Settings") # Setup file upload uploaded_file = st.sidebar.file_uploader( label="Upload your CSV or Excel file. (200MB max)", type=['csv', 'xlsx']) global df if uploaded_file is not None: print(uploaded_file) print("hello") try: df = pd.read_csv(uploaded_file) except Exception as e: print(e) df = pd.read_excel(uploaded_file) global numeric_columns global non_numeric_columns try: st.write(df) numeric_columns = list(df.select_dtypes(['float', 'int']).columns) non_numeric_columns = list(df.select_dtypes(['object']).columns) non_numeric_columns.append(None) print(non_numeric_columns) except Exception as e: print(e) st.write("Please upload file to the application.") # add a select widget to the side bar chart_select = st.sidebar.selectbox( label="Select the chart type", options=['Scatterplots', 'Lineplots', 'Histogram', 'Boxplot'] ) if chart_select == 'Scatterplots': st.sidebar.subheader("Scatterplot Settings") try: x_values = st.sidebar.selectbox('X axis', options=numeric_columns) y_values = st.sidebar.selectbox('Y axis', options=numeric_columns) color_value = st.sidebar.selectbox("Color", options=non_numeric_columns) plot = px.scatter(data_frame=df, x=x_values, y=y_values, color=color_value) # display the chart st.plotly_chart(plot) except Exception as e: print(e) if chart_select == 'Lineplots': st.sidebar.subheader("Line Plot Settings") try: x_values = st.sidebar.selectbox('X axis', options=numeric_columns) y_values = st.sidebar.selectbox('Y axis', options=numeric_columns) color_value = st.sidebar.selectbox("Color", options=non_numeric_columns) plot = px.line(data_frame=df, x=x_values, y=y_values, color=color_value) st.plotly_chart(plot) except Exception as e: print(e) if chart_select == 'Histogram': st.sidebar.subheader("Histogram Settings") try: x = st.sidebar.selectbox('Feature', options=numeric_columns) bin_size = st.sidebar.slider("Number of Bins", min_value=10, max_value=100, value=40) color_value = st.sidebar.selectbox("Color", options=non_numeric_columns) plot = px.histogram(x=x, data_frame=df, color=color_value) st.plotly_chart(plot) except Exception as e: print(e) if chart_select == 'Boxplot': st.sidebar.subheader("Boxplot Settings") try: y = st.sidebar.selectbox("Y axis", options=numeric_columns) x = st.sidebar.selectbox("X axis", options=non_numeric_columns) color_value = st.sidebar.selectbox("Color", options=non_numeric_columns) plot = px.box(data_frame=df, y=y, x=x, color=color_value) st.plotly_chart(plot) except Exception as e: print(e)
3.234375
3
rigidsearch/cli.py
robopsi/rigidsearch
9
12790067
# coding: utf-8 import os import shutil import json import click from werkzeug.utils import cached_property class Context(object): def __init__(self): self.config_filename = os.environ.get('RIGIDSEARCH_CONFIG') @cached_property def app(self): from rigidsearch.app import create_app return create_app(self.config_filename) pass_ctx = click.make_pass_decorator(Context, ensure=True) @click.group() @click.option('--config', type=click.Path(), help='Path to the config file.') @pass_ctx def cli(ctx, config): if config is not None: ctx.config_filename = os.path.abspath(config) @cli.command('index-folder') @click.argument('config', type=click.File('rb')) @click.option('--index-path', type=click.Path(), help='Where to write the index to other than config default.') @click.option('--save-zip', type=click.File('wb'), help='Optional a zip file the index should be stored at ' 'instead of modifying the index in-place.') @pass_ctx def index_folder_cmd(ctx, config, index_path, save_zip): """Indexes a path.""" from rigidsearch.search import index_tree, get_index_path index_path = get_index_path(index_path=index_path, app=ctx.app) try: shutil.rmtree(index_path) except (OSError, IOError): pass for event in index_tree(json.load(config), index_zip=save_zip, index_path=index_path): click.echo(event) @cli.command('search') @click.argument('query') @click.option('--section', default='generic') @click.option('--index-path', help='Path to the search index.') @pass_ctx def search_cmd(ctx, query, section, index_path): """Triggers a search from the command line.""" from rigidsearch.search import get_index, get_index_path index_path = get_index_path(app=ctx.app) index = get_index(index_path) results = index.search(query, section=section) for result in results['items']: click.echo('%s (%s)' % ( result['path'], result['title'] )) @cli.command('devserver') @click.option('--bind', '-b', default='127.0.0.1:5001') @pass_ctx def devserver_cmd(ctx, bind): """Runs a local development server.""" parts = bind.split(':', 1) if len(parts) == 2: addr, port = parts elif len(parts) == 1: addr, port = bind, '5001' if addr == '': addr = '127.0.0.1' ctx.app.run(addr, int(port), debug=True) @cli.command('run') @click.option('--bind', '-b', default='127.0.0.1:5001') @click.option('--workers', '-w', default=1) @click.option('--timeout', '-t', default=30) @click.option('--loglevel', default='info') @click.option('--accesslog', default='-') @click.option('--errorlog', default='-') @pass_ctx def run_cmd(ctx, **options): """Runs the http web server.""" from rigidsearch.app import make_production_server make_production_server(app=ctx.app, options=options).run() def main(): cli(auto_envvar_prefix='RIGIDSEARCH')
2.15625
2
src/sion.py
kamimura/py-sion
1
12790068
# Created by kamimura on 2018/07/21. # Copyright © 2018 kamimura. All rights reserved. import sys import datetime from antlr4 import * from SIONLexer import SIONLexer from SIONParser import SIONParser from SIONVisitor import SIONVisitor def load(file, encoding: str='utf-8', errors: str='strict') -> object: data = file.read() if isinstance(data, (bytes, bytearray)): data = data.decode(encoding, errors) stream = InputStream(data) lexer = SIONLexer(stream) tokens = CommonTokenStream(lexer) parser = SIONParser(tokens) tree = parser.si_self() visitor = SIONVisitor() return visitor.visit(tree) def loads(s): if isinstance(s, (bytes, bytearray)): s = s.decode() stream = InputStream(s) lexer = SIONLexer(stream) tokens = CommonTokenStream(lexer) parser = SIONParser(tokens) tree = parser.si_self() visitor = SIONVisitor() return visitor.visit(tree) def str_esc(s): for o, n in [('"', '\\"'), ('\n', '\\n'), ('\r', '\\r'), ('\\', '\\\\')]: s = s.replace(o, n) return s def dump(obj, file): if obj is None: print('nil', file=file, end='') elif isinstance(obj, bool): if obj: print('ture', file=file, end='') else: print('false', file=file, end='') elif isinstance(obj, (int, float)): print(obj, file=file, end='') elif isinstance(obj, str): print(f'"{str_esc(obj)}"', file=file, end='') elif isinstance(obj, (bytes, bytearray)): print(f'.Data("{str(obj)[2:-1]}")', file=file, end='') elif isinstance(obj, datetime.datetime): print(f'.Date({obj.timestamp()})', file=file, end='') elif isinstance(obj, (list, tuple)): print(f'[', file=file, end='') if len(obj) > 0: for o in obj[:-1]: dump(o, file) print(',', file=file, end='') dump(obj[-1], file) print(']', file=file, end='') elif isinstance(obj, dict): print('[', file=file, end='') ks = list(obj.keys()) if len(ks) == 0: print(':', file=file, end='') elif len(ks) == 1: dump(ks[0], file) print(':', file=file, end='') dump(obj[ks[0]], file) else: for k in ks[:-1]: dump(k, file) print(':', file=file, end='') dump(obj[k], file) print(',', file=file, end='') dump(ks[-1], file) print(':', file=file, end='') dump(obj[ks[-1]], file) print(']', file=file, end='') else: raise TypeError( f"Object of type '{obj.__class__.__name__}' is not SION serializable") def dumps(obj: object): if obj is None: return 'nil' if isinstance(obj, bool): if obj: return 'true' return 'false' if isinstance(obj, (int, float)): return str(obj) if isinstance(obj, str): return f'"{str_esc(obj)}"' if isinstance(obj, (bytes, bytearray)): return f'.Data("{str(obj)[2:-1]}")' if isinstance(obj, datetime.datetime): return f'.Date({obj.timestamp(obj)})' if isinstance(obj, (list, tuple)): res = '[' if len(obj) > 0: for o in obj[:-1]: res += dumps(o) + ',' res += dumps(obj[-1]) res += ']' return res if isinstance(obj, dict): res = '[' ks = list(obj.keys()) if len(ks) == 0: res += ':' elif len(ks) == 1: res += dumps(ks[0]) + ':' + dumps(obj[ks[0]]) else: for k in ks[:-1]: res += dumps(k) + ':' + str(obj[k]) + ',' res += dumps(ks[-1]) + ':' + dumps(obj[ks[-1]]) res += ']' return res raise TypeError( f"Object of type '{obj.__class__.__name__}' is not SION serializable") if __name__ == '__main__': import pprint if len(sys.argv) > 1: filename = sys.argv[1] else: filename = '../test/t.sion' with open(filename) as f: obj = load(f) pprint.pprint(obj) with open('../test/output.sion', 'w') as f: dump(obj, f) s = ''' [ "array" : [ nil, true, 1, // Int in decimal 1.0, // Double in decimal "one", [1], ["one" : 1.0] ], "bool" : true, "data" : .Data("R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"), "date" : .Date(0x0p+0), "dictionary" : [ "array" : [], "bool" : false, "double" : 0x0p+0, "int" : 0, "nil" : nil, "object" : [:], "string" : "" ], "double" : 0x1.518f5c28f5c29p+5, // Double in hexadecimal "int" : -0x2a, // Int in hexadecimal "nil" : nil, "string" : "漢字、カタカナ、ひらがなの入ったstring😇", "url" : "https://github.com/dankogai/", nil : "Unlike JSON and Property Lists,", true : "Yes, SION", 1 : "does accept", 1.0 : "non-String keys.", [] : "like", [:] : "Map of ECMAScript." ] ''' obj = loads(s) pprint.pprint(obj) s = dumps(obj) print(s)
2.203125
2
src/project/urls.py
kottenator/code.kottenator.com
0
12790069
<reponame>kottenator/code.kottenator.com from django.contrib import admin from django.urls import path, include import project.auth.urls import project.core.urls from project.core.views import bad_request, permission_denied, page_not_found, server_error import project.projects.urls urlpatterns = [ path('admin/', admin.site.urls), path('projects/', include(project.projects.urls)), path('', include(project.auth.urls)), path('', include(project.core.urls)) ] handler400 = bad_request handler403 = permission_denied handler404 = page_not_found handler500 = server_error
1.898438
2
code/matplotlib/test.py
qiudebo/13learn
1
12790070
# *-* coding:utf-8 *-* import numpy as np import matplotlib.pyplot as plt import matplotlib from matplotlib import style import os from os import path from matplotlib.font_manager import fontManager # 图表坐标系
1.382813
1
rdfframework/processors/__init__.py
KnowledgeLinks/rdfframework
7
12790071
""" RDF Proccessors =============== Processors are used to manipulate rdf date within the framework. :copyright: Copyright (c) 2016 by <NAME> and <NAME>. :license: To be determined, see LICENSE.txt for details. """ from .propertyprocessors import PropertyProcessor from .classprocessors import ClassProcessor __author__ = "<NAME>, <NAME>" __version__ = '0.0.1'
1.328125
1
atlas/foundations_rest_api/src/foundations_rest_api/filters/null_filter.py
DeepLearnI/atlas
296
12790072
<reponame>DeepLearnI/atlas from foundations_rest_api.filters.api_filter_mixin import APIFilterMixin class NullFilter(APIFilterMixin): def __call__(self, result, params): if result and isinstance(result, list): new_params = {key: value for key, value in params.items() if key.endswith('_isnull')} if new_params: self._filter(result, new_params) return result def _filter(self, result, params): for key, param_value in params.items(): column_name = key.split('_isnull', 1)[0] value = self._parse_value(param_value) if value is not None: self._filter_column(result, column_name, value) def _parse_value(self, param_value): from foundations_rest_api.filters.parsers import BoolParser parser = BoolParser() return parser.parse(param_value) def _filter_column(self, result, column_name, value): # Explicit is better than implicit [Zen of Python, 1] # This is because "value" can also be None and in that case filtering is discarded if value is True: self._filter_by_null_values(result, column_name) elif value is False: self._filter_by_not_null_values(result, column_name) def _is_none(self, value): return value is None or self._is_nan(value) def _is_nan(self, value): import math return isinstance(value, float) and math.isnan(value) def _filter_by_null_values(self, result, column_name): def column_value_is_null(item): value, item_parser = self._get_item_property_value_and_parser(item, column_name, parse=False) return item_parser is not None and self._is_none(value) return self._in_place_filter(column_value_is_null, result) def _filter_by_not_null_values(self, result, column_name): def column_value_is_not_null(item): value, item_parser = self._get_item_property_value_and_parser(item, column_name, parse=False) return item_parser is not None and not self._is_none(value) return self._in_place_filter(column_value_is_not_null, result)
2.75
3
problems/interleaving_str.py
apoorvkk/LeetCodeSolutions
1
12790073
class Solution: def isInterleave(self, s1, s2, s3): """ :type s1: str :type s2: str :type s3: str :rtype: bool """ return self._is_interleave(s1, s2, s3, set(), 0, 0, 0) def _is_interleave(self, s1, s2, s3, memo, s1_start, s2_start, s3_start): if s3_start >= len(s3): return s1_start >= len(s1) and s2_start >= len(s2) encoding = str(s1_start) + '|' + str(s2_start) + '|' + str(s3_start) if encoding in memo: return False s1_counter = s1_start if s1_start < len(s1) else None s2_counter = s2_start if s2_start < len(s2) else None def _find_prefix(counter, p, other_start): for i in range(s3_start, len(s3)): if counter is not None: if s3[i] == p[counter]: if s1 == p: if self._is_interleave(s1, s2, s3, memo, counter+1, other_start, i+1): return True else: if self._is_interleave(s1, s2, s3, memo, other_start, counter+1, i+1): return True counter += 1 else: counter = None if counter is not None and counter >= len(p): counter = None if _find_prefix(s1_counter, s1, s2_start): return True if _find_prefix(s2_counter, s2, s1_start): return True memo.add(encoding) return False
3.53125
4
pyDLib/GUI/fields.py
benoitkugler/abstractDataLibrary
0
12790074
"""Implements widgets to visualize and modify basic fields. (french language) ASSOCIATION should be updated with custom widgets, since common.abstractDetails will use it. """ import datetime import re from collections import defaultdict from typing import List, Any from PyQt5.QtCore import pyqtSignal, Qt, QPoint from PyQt5.QtGui import QColor, QPen, QBrush, QIcon from PyQt5.QtWidgets import (QFrame, QHBoxLayout, QPushButton, QLineEdit, QLabel, QComboBox, QSpinBox, QDoubleSpinBox, QCheckBox, QCompleter, QGridLayout, QVBoxLayout, QPlainTextEdit, QStyledItemDelegate, QToolTip) from . import list_views, clear_layout, Icons from ..Core import formats class NouveauTelephone(list_views.abstractNewButton): LABEL = "Ajouter un numéro" @staticmethod def IS_TELEPHONE(s: str): r = re.compile(r'[0-9]{9,10}') m = r.search(s.replace(' ', '')) return (m is not None) def _clear(self): clear_layout(self.layout()) def enter_edit(self): self._clear() line_layout = self.layout() self.entree = QLineEdit() self.entree.setObjectName("nouveau-numero-tel") self.entree.setAlignment(Qt.AlignCenter) self.entree.setPlaceholderText("Ajouter...") add = QPushButton() add.setIcon(QIcon(Icons.Valid)) add.clicked.connect(self.on_add) self.entree.editingFinished.connect(self.on_add) line_layout.addWidget(self.entree) line_layout.addWidget(add) line_layout.setStretch(0, 3) line_layout.setStretch(1, 1) def on_add(self): num = self.entree.text() if self.IS_TELEPHONE(num): self.entree.setPlaceholderText("Ajouter...") self.data_changed.emit(num) self._clear() self.set_button() else: self.entree.selectAll() QToolTip.showText(self.entree.mapToGlobal( QPoint(0, 10)), "Numéro invalide") class Tels(list_views.abstractMutableList): LIST_PLACEHOLDER = "Aucun numéro." LIST_HEADER = None BOUTON = NouveauTelephone def __init__(self, collection: list, is_editable): collection = self.from_list(collection) super().__init__(collection, is_editable) def on_add(self, item): """Convert to pseuso acces""" super(Tels, self).on_add(list_views.PseudoAccesCategorie(item)) def set_data(self, collection): collection = self.from_list(collection) super(Tels, self).set_data(collection) def get_data(self): col = super(Tels, self).get_data() return [tel.Id for tel in col] class Duree(QLabel): """Display the numbers of day between two date widgets. These widgets have to implement a get_data method, which return a date.date""" def __init__(self, begining, end): super().__init__() self.begining = begining self.end = end self.begining.data_changed.connect(self.set_data) self.end.data_changed.connect(self.set_data) self.set_data() def set_data(self, *args): """we cant to call set_data to manually update""" db = self.begining.get_data() or formats.DATE_DEFAULT df = self.end.get_data() or formats.DATE_DEFAULT jours = max((df - db).days + 1, 0) self.setText(str(jours) + (jours >= 2 and " jours" or " jour")) # -------------- Enumerations vizualisation -------------- class abstractEnum(QLabel): VALUE_TO_LABEL = {} """Dict. giving label from raw value""" def set_data(self, value): self.value = value self.setText(self.VALUE_TO_LABEL.get(self.value, "")) def get_data(self): return self.value class abstractEnumEditable(QComboBox): data_changed = pyqtSignal(object) VALEURS_LABELS = [] """List of tuples (value, label) or None to add a separator""" def __init__(self, parent=None): super().__init__(parent) self.set_choix(self.VALEURS_LABELS) self.currentIndexChanged.connect( lambda i: self.data_changed.emit(self.currentData())) def set_choix(self, choix): self.places = {} for t in choix: if t: self.places[t[0]] = self.count() self.addItem(t[1], userData=t[0]) else: self.insertSeparator(self.count()) def set_data(self, value): if value is None: self.setCurrentIndex(-1) else: self.setCurrentIndex(self.places[value]) self.data_changed.emit(self.get_data()) def get_data(self): return self.currentData() # -------------------- Commons types -------------------- class DepartementFixe(abstractEnum): VALUE_TO_LABEL = formats.DEPARTEMENTS class DepartementEditable(abstractEnumEditable): VALEURS_LABELS = sorted((i, i + " " + v) for i, v in formats.DEPARTEMENTS.items()) class SexeFixe(abstractEnum): VALUE_TO_LABEL = formats.SEXES class SexeEditable(abstractEnumEditable): VALEURS_LABELS = sorted((k, v) for k, v in formats.SEXES.items()) class ModePaiementFixe(abstractEnum): VALUE_TO_LABEL = formats.MODE_PAIEMENT class ModePaiementEditable(abstractEnumEditable): VALEURS_LABELS = sorted([(k, v) for k, v in formats.MODE_PAIEMENT.items()]) # ------------- Simple string-like field ------------- class abstractSimpleField(QLabel): FONCTION_AFF = None TOOLTIP = None data_changed = pyqtSignal() # dummy signal def __init__(self, *args, **kwargs): super(abstractSimpleField, self).__init__(*args, **kwargs) if self.TOOLTIP: self.setToolTip(self.TOOLTIP) def set_data(self, value): self.value = value label = self.FONCTION_AFF(value) self.setText(label) def get_data(self): return self.value class BoolFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.boolen) class EurosFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.euros) class PourcentFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.pourcent) class DefaultFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.default) class DateFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.date) class DateHeureFixe(abstractSimpleField): FONCTION_AFF = staticmethod(formats.abstractRender.dateheure) # --------------- Numeric fields --------------- class abstractEntierEditable(QSpinBox): UNITE = "" MAX = None MIN = 0 DEFAULT = 0 data_changed = pyqtSignal(int) def __init__(self, parent=None): super().__init__(parent) self.setMaximum(self.MAX) self.setMinimum(self.MIN) self.setSuffix(self.UNITE) self.valueChanged.connect(self.data_changed.emit) self.setSpecialValueText(" ") def set_data(self, somme): somme = somme if somme is not None else (self.MIN - 1) self.setValue(somme) def get_data(self): return self.value() class EntierEditable(abstractEntierEditable): MAX = 10000 class PourcentEditable(abstractEntierEditable): UNITE = "%" MAX = 100 DEFAULT = 0 class EurosEditable(QDoubleSpinBox): data_changed = pyqtSignal(float) def __init__(self, parent=None): super().__init__(parent) self.setMaximum(100000) self.setMinimum(-1) self.setSpecialValueText(" ") self.setSuffix("€") self.valueChanged.connect(self.data_changed.emit) def set_data(self, somme): somme = somme if somme is not None else -1 self.setValue(somme) def get_data(self): v = self.value() return v if v != -1 else None class BoolEditable(QFrame): data_changed = pyqtSignal(bool) def __init__(self, parent=None): super().__init__(parent) cb = QCheckBox() l = QLabel() self.setAutoFillBackground(True) # Pour éviter la transparence layout = QHBoxLayout(self) layout.addWidget(cb) layout.addWidget(l) def callback(b): l.setText(b and "Oui" or "Non") self.data_changed.emit(b) cb.clicked.connect(callback) self.cb = cb self.l = l def set_data(self, b): b = b or False self.cb.setChecked(b) self.l.setText(b and "Oui" or "Non") def get_data(self): return self.cb.isChecked() class DefaultEditable(QLineEdit): data_changed = pyqtSignal(str) MAX_LENGTH = None def __init__(self, parent=None, completion=[]): super().__init__(parent) self.textChanged.connect(self.data_changed.emit) if completion: c = QCompleter(completion) c.setCaseSensitivity(Qt.CaseInsensitive) self.setCompleter(c) if self.MAX_LENGTH: self.setMaxLength(self.MAX_LENGTH) def set_data(self, value): self.setText(str(value or "")) def get_data(self): return self.text() def LimitedDefaultEditable(max_length): return type("LDefaultEditable", (DefaultEditable,), {"MAX_LENGTH": max_length}) class OptionnalTextEditable(QFrame): """QCheckbox + QLineEdit""" data_changed = pyqtSignal(object) def __init__(self, parent=None): super(OptionnalTextEditable, self).__init__(parent=parent) self.active = QCheckBox() self.text = QLineEdit() self.active.clicked.connect(self.on_click) self.text.textChanged.connect(self.on_text_changed) layout = QHBoxLayout(self) layout.addWidget(self.active) layout.addWidget(self.text) def on_click(self): self.text.setEnabled(self.active.isChecked()) self.data_changed.emit(self.get_data()) def on_text_changed(self, text): is_active = bool(text.strip()) self.active.setChecked(is_active) self.text.setEnabled(is_active) self.data_changed.emit(self.get_data()) def get_data(self): text = self.text.text().strip() active = self.active.isChecked() and bool(text) return text if active else None def set_data(self, text: str): text = text or "" is_active = bool(text.strip()) self.active.setChecked(is_active) self.text.setEnabled(is_active) self.text.setText(text) self.data_changed.emit(self.get_data()) class DateEditable(QFrame): data_changed = pyqtSignal(object) def __init__(self, parent=None): super().__init__(parent) layout = QGridLayout(self) layout.setContentsMargins(0, 0, 0, 0) j = QSpinBox() j.setMinimum(0) j.setMaximum(31) j.setToolTip("Jour") m = QSpinBox() m.setMinimum(0) m.setMaximum(12) m.setToolTip("Mois") a = QSpinBox() a.setMinimum(0) a.setMaximum(2500) a.setToolTip("Année") j.setAlignment(Qt.AlignCenter) m.setAlignment(Qt.AlignCenter) a.setAlignment(Qt.AlignCenter) j.setSpecialValueText("-") m.setSpecialValueText("-") a.setSpecialValueText("-") layout.addWidget(j, 0, 0) layout.addWidget(m, 0, 1) layout.addWidget(a, 0, 2, 1, 2) j.valueChanged.connect( lambda v: self.data_changed.emit(self.get_data())) m.valueChanged.connect( lambda v: self.data_changed.emit(self.get_data())) a.valueChanged.connect( lambda v: self.data_changed.emit(self.get_data())) a.editingFinished.connect(self.on_editing) self.ws = (a, m, j) def _change_year_text_color(self, is_ok): color = "black" if is_ok else "red" self.ws[0].setStyleSheet(f"color : {color}") def on_editing(self): current_year = self.ws[0].value() if not current_year: return self._change_year_text_color(not current_year < 100) self.ws[0].setValue(current_year) def get_data(self): d = [self.ws[0].value(), self.ws[1].value(), self.ws[2].value()] try: return datetime.date(*d) except ValueError: return def set_data(self, d): if d is None: self.ws[0].clear() self.ws[1].clear() self.ws[2].clear() else: self.ws[0].setValue(d.year) self.ws[1].setValue(d.month) self.ws[2].setValue(d.day) self.on_editing() class MontantEditable(QFrame): def __init__(self, parent=None): super().__init__(parent) self.setAutoFillBackground(True) self.val = QDoubleSpinBox() self.val.setMaximum(100000) self.par_jour = QCheckBox("Par jour") layout = QVBoxLayout(self) layout.addWidget(self.val) layout.addWidget(self.par_jour) def set_data(self, value): self.val.setValue(value[0]) self.par_jour.setChecked(value[1]) def get_data(self): return [self.val.value(), self.par_jour.isChecked()] class DateRange(QFrame): data_changed = pyqtSignal(object, object) def __init__(self): super().__init__() self.debut = DateEditable() self.fin = DateEditable() self.debut.data_changed.connect(self.on_change) self.fin.data_changed.connect(self.on_change) layout = QHBoxLayout(self) layout.setContentsMargins(0, 0, 0, 0) layout.addWidget(QLabel("Du ")) layout.addWidget(self.debut) layout.addWidget(QLabel(" au ")) layout.addWidget(self.fin) def on_change(self): self.data_changed.emit(*self.get_data()) def get_data(self): return self.debut.get_data(), self.fin.get_data() def set_data(self, v): v = v or [None, None] self.debut.set_data(v[0]) self.fin.set_data(v[1]) class Texte(QPlainTextEdit): data_changed = pyqtSignal(str) def __init__(self, text, is_editable, placeholder="Informations complémentaires"): super().__init__(text) self.setSizeAdjustPolicy(QPlainTextEdit.AdjustToContents) self.setMinimumHeight(50) self.setMinimumWidth(150) self.setPlaceholderText(placeholder) self.setReadOnly(not is_editable) self.textChanged.connect( lambda: self.data_changed.emit(self.toPlainText())) def get_data(self): return self.toPlainText() def set_data(self, text): self.setPlainText(text) class OptionsButton(QPushButton): """Bouton to open window to acces advanced options. CLASS_PANEL_OPTIONS is responsible for doing the actual modification""" TITLE = "Advanced options" CLASS_PANEL_OPTIONS:Any = None options_changed = pyqtSignal() def __init__(self, acces, is_editable): super(OptionsButton, self).__init__(self.TITLE) self.clicked.connect(self.show_options) self.acces = acces self.is_editable = is_editable def show_options(self): f = self.CLASS_PANEL_OPTIONS(self.acces, self.is_editable) if f.exec_(): self.options_changed.emit() def set_data(self, *args): pass ###---------------------------- Wrappers---------------------------- ### def _get_widget(classe, value): w = classe() w.set_data(value) return w def Default(value, is_editable): return _get_widget(is_editable and DefaultEditable or DefaultFixe, value) def Booleen(value, is_editable): return _get_widget(is_editable and BoolEditable or BoolFixe, value) def Entier(entier, is_editable): return _get_widget(is_editable and EntierEditable or DefaultFixe, entier) def Euros(value, is_editable): return _get_widget(is_editable and EurosEditable or EurosFixe, value) def Pourcent(value, is_editable): return _get_widget(is_editable and PourcentEditable or PourcentFixe, value) def Date(value, is_editable): return _get_widget(is_editable and DateEditable or DateFixe, value) def Departement(value, is_editable): return _get_widget(is_editable and DepartementEditable or DepartementFixe, value) def Sexe(value, is_editable): return _get_widget(is_editable and SexeEditable or SexeFixe, value) def Adresse(value, is_editable): return Texte(value, is_editable, placeholder="Adresse...") def ModePaiement(value, is_editable): return _get_widget(is_editable and ModePaiementEditable or ModePaiementFixe, value) def DateHeure(value, is_editable): if is_editable: raise NotImplementedError("No editable datetime widget !") w = DateHeureFixe() w.set_data(value) return w def OptionnalText(value, is_editable): return _get_widget(is_editable and OptionnalTextEditable or DefaultFixe, value) """Correspondance field -> widget (callable)""" TYPES_WIDGETS = defaultdict( lambda: Default, date_naissance=Date, departement_naissance=Departement, sexe=Sexe, tels=Tels, adresse=Adresse, date=Date, date_debut=Date, date_fin=Date, date_arrivee=Date, date_depart=Date, date_emission=Date, date_reception=Date, nb_places=Entier, nb_places_reservees=Entier, age_min=Entier, age_max=Entier, acquite=Booleen, is_acompte=Booleen, is_remboursement=Booleen, reduc_speciale=Euros, acompte_recu=Euros, valeur=Euros, total=Euros, prix=Euros, date_heure_modif=DateHeure, date_reglement=Date, date_encaissement=Date, info=Texte, message=Texte, mode_paiement=ModePaiement, ) ASSOCIATION = {} def add_widgets_type(type_widgets, abstract_ASSOCIATION): TYPES_WIDGETS.update(type_widgets) for k, v in abstract_ASSOCIATION.items(): t = TYPES_WIDGETS[k] ASSOCIATION[k] = (v[0], v[1], v[2], t, v[3]) add_widgets_type({}, formats.ASSOCIATION) ## ------------------Custom delegate ------------------ ## class delegateAttributs(QStyledItemDelegate): CORRES = {"montant": MontantEditable, "mode_paiement": ModePaiementEditable, "valeur": EurosEditable, "description": DefaultEditable, "quantite": EntierEditable, "obligatoire": BoolEditable} """Correspondance between fields and widget classes""" size_hint_: tuple def __init__(self, parent): QStyledItemDelegate.__init__(self, parent) self.size_hint_ = None self.row_done_ = None @staticmethod def paint_filling_rect(option, painter, proportion): rect = option.rect painter.save() proportion = min(proportion, 100) rs, vs, bs = (30,64,55) # start re, ve, be = (153,242,200) # end t = proportion / 100 color = QColor( rs + t*(re - rs), vs + t*(ve - vs), bs + t*(be - bs)) painter.setPen(QPen(color, 0.5, Qt.SolidLine, Qt.RoundCap, Qt.RoundJoin)) painter.setBackgroundMode(Qt.OpaqueMode) painter.setBackground(QBrush(color)) painter.setBrush(QBrush(color)) rect.setWidth(rect.width() * proportion / 100) painter.drawRoundedRect(rect, 5, 5) painter.restore() @staticmethod def _get_field(index): return index.model().header[index.column()] def sizeHint(self, option, index): if self.size_hint_ and self.size_hint_[0] == index: return self.size_hint_[1] return super().sizeHint(option, index) def setEditorData(self, editor, index): value = index.data(role=Qt.EditRole) editor.set_data(value) self.sizeHintChanged.emit(index) def createEditor(self, parent, option, index): field = self._get_field(index) other = index.data(role=Qt.UserRole) classe = self.CORRES[field] w = classe(parent, other) if other else classe(parent) self.size_hint_ = (index, w.sizeHint()) self.row_done_ = index.row() return w def destroyEditor(self, editor, index): self.size_hint_ = None super().destroyEditor(editor, index) def setModelData(self, editor, model, index): value = editor.get_data() model.set_data(index, value)
2.359375
2
charts.py
TurtleOld/budget_interface_flask
0
12790075
<gh_stars>0 from flask import Blueprint, render_template import matplotlib.pyplot as plt import datetime from settings_database import cursor from functions import get_total_amount, get_number_month charts_route = Blueprint("charts", __name__) # Выделяем число месяца из даты чека def get_name_month_from_date(date_time): date_without_dash = date_time.replace("-", "") number_month = datetime.datetime.strptime(date_without_dash, "%Y%m%d").date().month if number_month == 1: return "Январь" if number_month == 2: return "Февраль" if number_month == 3: return "Март" if number_month == 4: return "Апрель" if number_month == 5: return "Май" if number_month == 6: return "Июнь" if number_month == 7: return "Июль" if number_month == 8: return "Август" if number_month == 9: return "Сентябрь" if number_month == 10: return "Октябрь" if number_month == 11: return "Ноябрь" if number_month == 12: return "Декабрь" @charts_route.route("/charts") def charts(): title = "Графики" cursor.execute("SELECT * FROM receipt ORDER BY date_receipt") product_information = cursor.fetchall() listing_name_months = [] month_listing = [] number_month = [] amount_total = [] for date in product_information: name_month = (get_name_month_from_date(str(date[0]))) listing_name_months.append(name_month) number_month.append(get_number_month(str(date[0]))) for number in set(number_month): cursor.execute( "SELECT total_sum FROM receipt WHERE (extract (month from date_receipt)=%s) GROUP BY total_sum", (number,)) product_total_sum = cursor.fetchall() amount_total.append(get_total_amount(product_total_sum)) for item in set(listing_name_months): month_listing.append(item) month_listing.sort(reverse=True) dict_name_months = list(set(listing_name_months)) dict_name_months.sort(reverse=True) index = dict_name_months values = amount_total plt.bar(index, values) plt.title("Расходы по месяцам") plt.savefig("static/img/plot_monthly_expenses.png") return render_template("charts.html", plot_monthly_expenses="static/img/plot_monthly_expenses.png", title=title)
2.703125
3
src/bbbr/wsgi.py
zgoda/bbbrating-server
0
12790076
<reponame>zgoda/bbbrating-server from .app import make_app application = make_app()
1.25
1
proxysql_tools/galera/galera_node.py
akuzminsky/proxysql-tools
26
12790077
"""Module describes GaleraNode class""" from contextlib import contextmanager import pymysql from pymysql.cursors import DictCursor from proxysql_tools import execute class GaleraNodeState(object): # pylint: disable=too-few-public-methods """State of Galera node http://bit.ly/2r1tUGB """ PRIMARY = 1 JOINER = 2 JOINED = 3 SYNCED = 4 DONOR = 5 class GaleraNode(object): """ GaleraNode class describes a single node in Galera Cluster. :param host: hostname of the node. :param port: port to connect to. :param user: MySQL username to connect to the node. :param password: <PASSWORD>. """ def __init__(self, host, port=3306, user='root', password=<PASSWORD>): self.host = host self.port = port self.user = user self.password = password @property def wsrep_cluster_state_uuid(self): """Provides the current State UUID. This is a unique identifier for the current state of the cluster and the sequence of changes it undergoes. """ return self._status('wsrep_cluster_state_uuid') @property def wsrep_cluster_status(self): """Status of this cluster component. That is, whether the node is part of a ``PRIMARY`` or ``NON_PRIMARY`` component.""" return self._status('wsrep_cluster_status') @property def wsrep_local_state(self): """Internal Galera Cluster FSM state number.""" return int(self._status('wsrep_local_state')) @property def wsrep_cluster_name(self): """The logical cluster name for the node.""" result = self.execute("SELECT @@wsrep_cluster_name") return result[0]['@@wsrep_cluster_name'] def execute(self, query, *args): """Execute query in Galera Node. :param query: Query to execute. :type query: str :return: Query result or None if the query is not supposed to return result. :rtype: dict """ with self._connect() as conn: return execute(conn, query, *args) @contextmanager def _connect(self): """Connect to Galera node :return: MySQL connection to the Galera node :rtype: Connection """ connection = pymysql.connect( # pylint: disable=duplicate-code host=self.host, port=self.port, user=self.user, passwd=<PASSWORD>, cursorclass=DictCursor ) yield connection connection.close() def _status(self, status_variable): """Return value of a variable from SHOW GLOBAL STATUS""" result = self.execute('SHOW GLOBAL STATUS LIKE %s', status_variable) return result[0]['Value'] def __eq__(self, other): return self.host == other.host and self.port == self.port def __ne__(self, other): return not self.__eq__(other) def __str__(self): return "%s:%d" % (self.host, self.port)
2.5
2
src/comment_analysis/parsing_utils.py
peppocola/DeClutter-Challenge-2020
5
12790078
import json from sklearn.preprocessing import LabelEncoder from src.comment_analysis.url_utils import get_text_by_url from src.csv.csv_utils import get_link_line_type, get_keywords from src.keys import line, serialize_outpath from nltk.stem.porter import * from spacy.lang.en.stop_words import STOP_WORDS from src.comment_analysis.java_re import * def get_line(code, comment_line, comment_type): code = code.splitlines() try: if comment_type == line: if not re.match(r"^[\s]*//.*", code[ comment_line - 1]): # if the line doesn't start as a comment, the comment refers to this line if not re.match(r"^[\s]*}?[\s]*(else|try|finally)?[\s]*{?[\s]*//.*[\s]*$", code[ comment_line - 1]): # if the line isnt just brackets and some keywords, the foucs line is the comment_line return code[comment_line - 1] i = 0 while re.match(r"^[\s]*//.*", code[comment_line + i]) or re.match(r"^[\s]*$", code[comment_line + i]) or re.match(r"[\s]*[^}{](try|else|finally)[\s]*{?", code[comment_line + i]): # while the line starts as a comment, ignore it. I do this because they use multiple line comment to simulate a block i += 1 if re.match(r"^[\s]*}.*", code[comment_line + i]) or re.match(r"[\s]*(try|else|finally)[\s]*{?", code[ comment_line + i]): # if this matches, the block is empty so i take the first non comment non empty line before the comment. i = -2 while re.match(r"^[\s]*//.*", code[comment_line + i]) or re.match(r"^[\s]*$", code[comment_line + i]) or re.match( r"^[\s]*/\*.*", code[comment_line + i]) or re.match(r"^\*", code[comment_line + i]) or re.match( r"^[\s]*\*/.*", code[comment_line + i]): # while the line is a comment or is blank, ignore it i -= 1 return code[comment_line + i] # comment refers to that # r"^[\s]*}?[\s]*(else|try|finally)?[\s]*{?[\s]*.*$" else: # block or javadoc # if the line doesn't start as a comment, the comment refers to this line if not re.match(r"^[\s]*/\*.*", code[comment_line - 1]): return code[comment_line - 1] if comment_line >= len(code) - 1: return code[comment_line - 2] i = 0 if not re.match(r"^[\s]*.*\*/", code[comment_line - 1]): while not re.match(r"^[\s]*\*/", code[comment_line + i]): i += 1 i += 1 # while the line starts as a comment or is blank, or is an annotation, ignore it while re.match(r"^[\s]*$", code[comment_line + i]) or re.match(r"^[\s]*@[^\s]*[\s]*$", code[comment_line + i]) or re.match(r"^[\s]*//.*", code[comment_line + i]) or re.match(r"[\s]*[^}{](try|else|finally)[\s]*{?", code[comment_line + i]): i += 1 # if this matches, probabily the comment refers to the line before if re.match(r"^[\s]*}[\s]*.*", code[comment_line + i]) or re.match(r"[\s]*(try|else|finally)[\s]*{?", code[comment_line + i]): i = -2 # while the line is a comment or is blank, ignore it while re.match(r"^[\s]*//.*", code[comment_line + i]) or re.match(r"^[\s]*$", code[comment_line + i]) or re.match(r"^[\s]*/\*.*", code[comment_line + i]) or re.match(r"^\*", code[comment_line + i]) or re.match(r"^[\s]*\*/.*", code[comment_line + i]): i -= 1 return code[comment_line + i] except IndexError: return "" def get_positions(lines=None, set='train'): comment_type = 0 text_link = 1 comment_line = 2 positions = [] data = get_link_line_type(set=set) if lines is None: lines = get_lines(set=set) i = 0 for row in data: #print(row[comment_line], row[comment_type], row[text_link] + "#L" + str(row[comment_line])) focus_line = lines[i] #print(focus_line) p = get_position(focus_line) positions.append(p) #print(p) i += 1 return positions def get_positions_encoded(lines=None, set='train'): if lines is None: positions = get_positions(set=set) else: positions = get_positions(lines, set=set) le = LabelEncoder() return le.fit_transform(positions) def get_lines(serialized=True, serialize=False, set='train'): if serialized: x = open(serialize_outpath + 'serialized_' + set +'.json', 'r').read() return json.loads(x) comment_type = 0 text_link = 1 comment_line = 2 data = get_link_line_type(set=set) lines = [] for row in data: code = get_text_by_url(row[text_link]) focus_line = get_line(code, row[comment_line], row[comment_type]) lines.append(focus_line) if serialize: x = open(serialize_outpath + 'serialized_' + set +'.json', 'w') x.write(json.dumps(lines)) return lines def get_code_words(stemming=True, rem_keyws=True, lines=None, set='train'): if lines is None: lines = get_lines(set=set, serialized=False, serialize=True) words = [] for line in lines: words.append(word_extractor(line, stemming, rem_keyws)) return words def word_extractor(string, stemming=True, rem_keyws=True): string = remove_line_comment(string) string = remove_block_comment(string) splitted = code_split(string) words = [] for part in splitted: camel_case_parts = camel_case_split(part) for camel in camel_case_parts: words.append(camel.lower()) if stemming and rem_keyws: return stem(remove_keywords(words)) elif stemming: return stem(words) else: return remove_keywords(words) def remove_keywords(words): keywords = get_keywords() non_keywords = [] for word in words: if word not in keywords: non_keywords.append(word) return non_keywords def stem(words): stemmer = PorterStemmer() stemmed = [] for token in words: stemmed.append(stemmer.stem(token)) return stemmed def camel_case_split(string): if not string: return string words = [[string[0]]] for c in string[1:]: if words[-1][-1].islower() and c.isupper(): words.append(list(c)) else: words[-1].append(c) return [''.join(word) for word in words] def remove_line_comment(string): in_string = False escape = False comment = False i = 0 for char in string: if char == '"': if in_string is True: if escape is False: in_string = False else: escape = False else: in_string = True elif char == '\\': if in_string is True: escape = True elif char == '/': if comment is False: comment = True else: return string[:i] elif comment is True: i += 1 comment = False elif escape is True: escape = False if comment is False: i += 1 return string def remove_block_comment(string): in_string = False escape = False block = False maybe_block = False found = False init_index = 0 end_index = 0 i = 0 for char in string: if char == '*': if not in_string: if maybe_block is False: if block is True: maybe_block = True else: block = True if char == '"': if in_string is True: if escape is False: in_string = False else: escape = False else: in_string = True elif char == '\\': if in_string is True: escape = True elif char == '/': if not in_string: if maybe_block is True: if block is True: found = True end_index = i break else: maybe_block = True init_index = i i += 1 if found is True: return string[:init_index] + string[end_index + 1:] return string def code_split(string): words = re.split(r'\\n|\?|&|\\|;|,|\*|\(|\)|\{|\s|\.|/|_|:|=|<|>|\||!|"|\+|-|\[|\]|\'|\}|\^|#|%', string) words = list(filter(lambda a: a != "", words)) return words def remove_stopwords(tokens): stop_words = STOP_WORDS relevant_words = [] for token in tokens: if token not in stop_words: relevant_words.append(token) return relevant_words def tokenizer(string, rem_stop=False, stemming=False, rem_kws=False): tokens = code_split(string) new_tokens = [] for token in tokens: for t in camel_case_split(token): new_tokens.append(t.lower()) if rem_stop: new_tokens = remove_stopwords(new_tokens) if rem_kws: new_tokens = remove_keywords(new_tokens) if stemming: new_tokens = stem(new_tokens) return new_tokens if __name__ == '__main__': # code = open('../testers/test.txt', 'r').read() # code_parser(code, 151, javadoc) print(get_lines(serialized=False, serialize=True)) print('first') print(get_lines(serialized=True, serialize=False)) # get_positions() # line_type_identifier("ciao") # code_parser3() # print(word_extractor("ciao mamma /*css rff*/")) # print(tokenizer("t<EMAIL>@<EMAIL> @param")) # print(camel_case_split("tuaMadre@QuellaTroia @param")) # print(code_split("tuaMadre@QuellaTroia @param"))
2.8125
3
2020/01/part_1.py
anders-wind/advent_of_code
0
12790079
from typing import List def read_input(file_path) -> List[int]: res = set({}) with open(file_path, 'r') as file_handle: for line in file_handle: res.add(int(line)) return res def calculate_result(numbers: List[int]) -> int: for number in numbers: opposite = 2020 - number if opposite in numbers: return number * opposite raise Exception("Could not find combi") def main(): print(calculate_result(read_input("sample.txt"))) print(calculate_result(read_input("input.txt"))) if __name__ == "__main__": main()
3.765625
4
tests/unit/test_user.py
gnott/h
0
12790080
from unittest import TestCase from h.models import User from . import AppTestCase class UserTest(AppTestCase): def test_password_encrypt(self): """make sure user passwords are stored encrypted """ u1 = User(username=u'test', password=u'<PASSWORD>', email=u'<EMAIL>') assert u1.password != '<PASSWORD>' self.db.add(u1) self.db.flush() assert u1.password != '<PASSWORD>'
3.3125
3
tagannotator/base/migrations/0005_auto_20200113_0518.py
kixlab/suggestbot-instagram-context-annotator
0
12790081
<filename>tagannotator/base/migrations/0005_auto_20200113_0518.py # Generated by Django 2.2.7 on 2020-01-13 05:18 import base.models from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('base', '0004_auto_20200113_0232'), ] operations = [ migrations.RemoveField( model_name='photo', name='title', ), migrations.RemoveField( model_name='post', name='user', ), migrations.RemoveField( model_name='tag', name='madeat', ), migrations.AddField( model_name='post', name='source', field=models.CharField(blank=True, choices=[('instagram', 'instagram'), ('upload', 'upload')], max_length=20, null=True), ), migrations.AddField( model_name='tag', name='madeby', field=models.CharField(blank=True, choices=[('user', 'user'), ('post', 'post')], max_length=20, null=True), ), migrations.AlterField( model_name='photo', name='file', field=models.ImageField(upload_to=base.models.user_directory_path), ), migrations.CreateModel( name='Session', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('starttime', models.DateTimeField(auto_now_add=True)), ('endtime', models.DateTimeField(auto_now_add=True)), ('status', models.BooleanField(blank=True, default=False)), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]
1.523438
2
get_model.py
dev-05/google_lens_clone
1
12790082
<filename>get_model.py # -*- coding: utf-8 -*- """ Created on Tue Feb 16 17:14:38 2021 @author: dev """ from tensorflow.keras.applications.vgg16 import VGG16 model=VGG16() model.save('mymodel.h5') print("VGG16 model downloaded and saved successfully")
2.40625
2
src/architecture/encoder/stacked_mnist_encoder.py
gmum/lcw-generator
4
12790083
<reponame>gmum/lcw-generator from architecture.encoder.cnn_encoder_block import CnnEncoderBlock import torch import torch.nn as nn from architecture.generator.linear_generator_block import LinearGeneratorBlock class Encoder(nn.Module): def __init__(self, latent_size: int): super().__init__() self.__sequential_blocks = [ CnnEncoderBlock(3, 128), CnnEncoderBlock(128, 256), nn.Flatten(start_dim=1), LinearGeneratorBlock(7 * 7 * 256, 256), nn.Linear(256, latent_size) ] self.main = nn.Sequential(*self.__sequential_blocks) def forward(self, input_images: torch.Tensor): assert input_images.size(1) == 3 and input_images.size(2) == 28 and input_images.size(3) == 28 encoded_latent = self.main(input_images) return encoded_latent
2.703125
3
scraper/scraper/main_page.py
tomirendo/BenYehuda
0
12790084
""" Class for parsing the main Ben Yehuda site page """ from urllib import request from urllib import parse as urlparse from bs4 import BeautifulSoup from .helpers import NamedLink, clean_text class MainPage(object): """ Parses and gets information from the main index page. Mostly used to get links for all of the artist pages """ def __init__(self, url="http://benyehuda.org"): self.main_url = url self.soup = BeautifulSoup(request.urlopen(url)) @staticmethod def artist_a_filter(tag): """ Finds all the links in the index page that points to an artist's page """ if tag.name != "a": return False href = tag.get("href").lower() # Artist links are supposed to be internal if href.startswith("http"): return False # Remove unrelated crap if href.startswith("javascript"): return False # Artist pages are one branch below the main page and their links # usually end with / - Need to verify if href.count("/") == 1 and href[-1] == "/": return True return False def get_artist_links(self): """ :return: A set of unique artist page urls and names :rtype: set[NamedLink] """ anchors = self.soup.find_all(self.artist_a_filter) links = set() for anchor in anchors: url = urlparse.urljoin(self.main_url, anchor.get("href").lower()) links.add(NamedLink(url, clean_text(anchor))) return links
3.734375
4
Eye-Tracking-System/tony/com.tonybeltramelli.eyetracker/Eye.py
tonybeltramelli/Graphics-And-Vision
12
12790085
<gh_stars>10-100 __author__ = 'tbeltramelli' from scipy.cluster.vq import * from UMedia import * from Filtering import * from RegionProps import * from UMath import * from UGraphics import * import operator class Eye: _result = None _right_template = None _left_template = None def __init__(self, right_corner_path, left_corner_path): self._right_template = Filtering.apply_box_filter(Filtering.get_gray_scale_image(UMedia.get_image(right_corner_path)), 5) self._left_template = Filtering.apply_box_filter(Filtering.get_gray_scale_image(UMedia.get_image(left_corner_path)), 5) def process(self, img): self._result = img img = Filtering.apply_box_filter(Filtering.get_gray_scale_image(img), 5) pupil_position, pupil_radius = self.get_pupil(img, 40) iris_radius = self.get_iris(img, pupil_position, pupil_radius) glints_position = self.get_glints(img, 180, pupil_position, iris_radius) corners_position = self.get_eye_corners(img) UMedia.show(self._result) def get_pupil(self, img, threshold): img = cv2.threshold(img, threshold, 255, cv2.THRESH_BINARY_INV)[1] height, width = img.shape side = (width * height) / 8 st = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5)) img = cv2.morphologyEx(img, cv2.MORPH_ERODE, st, iterations=1) img = cv2.morphologyEx(img, cv2.MORPH_DILATE, st, iterations=1) c, contours, hierarchy = cv2.findContours(img, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) props = RegionProps() radius = 0.0 for cnt in contours: properties = props.CalcContourProperties(cnt, ['Area', 'Length', 'Centroid', 'Extend', 'ConvexHull']) perimeter = cv2.arcLength(cnt, True) radius = np.sqrt(properties['Area'] / np.pi) radius = 1.0 if radius == 0.0 else radius circularity = perimeter / (radius * 2 * np.pi) if ((circularity >= 0.0) and (circularity <= 1.5)) and ((properties['Area'] > 900) and (properties['Area'] < side)): for i, centroid in enumerate(properties['Centroid']): if i == 0: center = int(centroid), int(properties['Centroid'][i+1]) if UMath.is_in_area(center[0], center[1], width, height): if len(cnt) >= 5: ellipse = cv2.fitEllipse(cnt) cv2.ellipse(self._result, ellipse, (0, 0, 255), 1) cv2.circle(self._result, center, int(radius), (0, 0, 255), 1) return center, radius return (int(width / 2), int(height / 2)), radius def get_glints(self, img, threshold, pupil_position, iris_radius): img = cv2.threshold(img, threshold, 255, cv2.THRESH_BINARY)[1] height, width = img.shape max_dist = iris_radius if iris_radius > 0 else (width + height) / 16 c, contours, hierarchy = cv2.findContours(img, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) props = RegionProps() coordinates = [] for cnt in contours: properties = props.CalcContourProperties(cnt, ['Area', 'Length', 'Centroid', 'Extend', 'ConvexHull']) if properties['Extend'] > 0 and properties['Area'] < 100: for i, centroid in enumerate(properties['Centroid']): if i == 0: center = int(centroid), int(properties['Centroid'][i+1]) distance = np.sqrt(np.power(pupil_position[0] - center[0], 2) + np.power(pupil_position[1] - center[1], 2)) if distance < max_dist: coordinates.append(center) cv2.circle(self._result, center, 2, (0, 255, 0), 3) return coordinates def get_eye_corners(self, img): right = self._match(img, self._right_template) left = self._match(img, self._left_template) return [right, left] def _match(self, img, template): matching = cv2.matchTemplate(img, template, cv2.TM_CCOEFF_NORMED) height, width = template.shape min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(matching) cv2.rectangle(self._result, (max_loc[0] - width/2, max_loc[1] - height/2), (max_loc[0] + width/2, max_loc[1] + height/2), 2) return max_loc[0], max_loc[1] def get_iris(self, img, pupil_position, pupil_radius, angle_tolerance=3, min_magnitude=15, max_magnitude=20): if pupil_radius <= 1.0: return 0.0 orientation, magnitude = self._get_gradient(img) max_iris_radius = pupil_radius * 5 pupil_samples = UMath.get_circle_samples(pupil_position, pupil_radius) iris_samples = UMath.get_circle_samples(pupil_position, max_iris_radius) iris_radius_vote = dict() for sample in range(len(pupil_samples)): pupil_sample = (int(pupil_samples[sample][0]), int(pupil_samples[sample][1])) iris_sample = (int(iris_samples[sample][0]), int(iris_samples[sample][1])) normal = UMath.get_line_coordinates(pupil_sample, iris_sample) normal_angle = cv2.fastAtan2(pupil_sample[1] - pupil_position[1], pupil_sample[0] - pupil_position[0]) for point in normal: i = point[1] - 1 j = point[0] - 1 if (i >= 0 and j >= 0) and (len(magnitude) > i and len(magnitude[i]) > j): mag = magnitude[i][j] if min_magnitude < mag < max_magnitude: angle = normal_angle + orientation[i][j] - 90 angle = angle - 360 if angle > 360 else angle if angle < angle_tolerance: radius = np.sqrt(np.power(point[0] - pupil_position[0], 2) + np.power(point[1] - pupil_position[1], 2)) radius = int(radius) if radius not in iris_radius_vote: iris_radius_vote[radius] = 0 iris_radius_vote[radius] += 1 cv2.line(self._result, pupil_sample, iris_sample, UGraphics.hex_color_to_bgr(0xf2f378), 1) iris_radius = max(iris_radius_vote.iteritems(), key=operator.itemgetter(1))[0] if len(iris_radius_vote) > 0 else 0 cv2.circle(self._result, pupil_position, iris_radius, (255, 0, 0), 1) return iris_radius def _get_gradient(self, img, granularity=10): height, width = img.shape sobel_horizontal = cv2.Sobel(img, cv2.CV_32F, 1, 0) sobel_vertical = cv2.Sobel(img, cv2.CV_32F, 0, 1) orientation = np.empty(img.shape) magnitude = np.empty(img.shape) for y in range(height): for x in range(width): orientation[y][x] = cv2.fastAtan2(sobel_horizontal[y][x], sobel_vertical[y][x]) magnitude[y][x] = np.sqrt(np.power(sobel_horizontal[y][x], 2) + np.power(sobel_vertical[y][x], 2)) if (x % granularity == 0) and (y % granularity == 0): UGraphics.draw_vector(self._result, x, y, magnitude[y][x] / granularity, orientation[y][x]) return orientation, magnitude
2.234375
2
tinylinks/urls.py
gosuai/django-tinylinks
11
12790086
<gh_stars>10-100 """URLs for the ``django-tinylinks`` app.""" from django.conf.urls import url from django.views.generic import TemplateView from .views import ( StatisticsView, TinylinkCreateView, TinylinkDeleteView, TinylinkListView, TinylinkRedirectView, TinylinkUpdateView, ) urlpatterns = [ url( r'^$', TinylinkListView.as_view(), name='tinylink_list' ), url( r'^create/$', TinylinkCreateView.as_view(), name='tinylink_create' ), url( r'^update/(?P<pk>\d+)/(?P<mode>[a-z-]+)/$', TinylinkUpdateView.as_view(), name='tinylink_update', ), url( r'^delete/(?P<pk>\d+)/$', TinylinkDeleteView.as_view(), name='tinylink_delete', ), url( r'^404/$', TemplateView.as_view(template_name='tinylinks/notfound.html'), name='tinylink_notfound', ), url( r'^statistics/?$', StatisticsView.as_view(), name='tinylink_statistics', ), url( r'^(?P<short_url>[a-zA-Z0-9-]+)/?$', TinylinkRedirectView.as_view(), name='tinylink_redirect', ), ]
1.820313
2
rainy_project/mainpage/migrations/0018_survey.py
osamhack2020/WEB_HeavyReading_Rainy
2
12790087
<gh_stars>1-10 # Generated by Django 2.1 on 2020-10-29 14:45 from django.conf import settings from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('mainpage', '0017_auto_20201025_2232'), ] operations = [ migrations.CreateModel( name='Survey', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=200)), ('author', models.CharField(max_length=50)), ('count', models.SmallIntegerField(default=0)), ('user', models.ManyToManyField(to=settings.AUTH_USER_MODEL)), ], ), ]
1.859375
2
naive_bayes.py
xiecong/Simple-Implementation-of-ML-Algorithms
16
12790088
<filename>naive_bayes.py import numpy as np from sklearn.datasets import fetch_20newsgroups import re def tokenize(documents, stop_words): text = [] for doc in documents: letters_only = re.sub("[^a-zA-Z]", " ", doc) words = letters_only.lower().split() text.append([w for w in words if not w in stop_words]) return np.array(text) class NaiveBayes(object): # multinominal NB model with laplace smoothing # guassian can be used for numerical def __init__(self): self.p_w = {} self.p_c = {} self.vocabulary = [] self.v_num = 0 def fit(self, x, y): n_data = len(y) self.label, p_c = np.unique(y, return_counts=True) self.p_c = dict(zip(self.label, np.log(p_c / n_data))) indexes = np.c_[np.array(y), np.arange(n_data)] self.vocabulary = np.unique( [item for sublist in x for item in sublist]) self.v_num = len(self.vocabulary) print("vocabulary length {}".format(self.v_num)) self.v_idx = dict(zip(self.vocabulary, np.arange(self.v_num))) print("start fitting") for l in self.label: idxes = indexes[indexes[:, 0] == l][:, 1].astype(int) corpus = [x[idx] for idx in idxes] flatten = [item for sublist in corpus for item in sublist] self.p_w[l] = [ np.log(1 / (len(flatten) + self.v_num))] * self.v_num words, pwl = np.unique(flatten, return_counts=True) for w, p in zip(words, pwl): self.p_w[l][self.v_idx[w]] = np.log( (p + 1) / (len(flatten) + self.v_num)) def predict(self, x): return np.array([self.predict_sample(xi) for xi in x]) def predict_sample(self, x): eps = 1 / self.v_num p = [self.p_c[i] + sum(self.p_w[i][self.v_idx[w]] if w in self.v_idx.keys() else eps for w in x) for i in range(len(self.label))] return self.label[np.argmax(p)] def main(): stop_words = set(["i", "me", "my", "myself", "we", "our", "ours", "ourselves", "you", "your", "yours", "yourself", "yourselves", "he", "him", "his", "himself", "she", "her", "hers", "herself", "it", "its", "itself", "they", "them", "their", "theirs", "themselves", "what", "which", "who", "whom", "this", "that", "these", "those", "am", "is", "are", "was", "were", "be", "been", "being", "have", "has", "had", "having", "do", "does", "did", "doing", "a", "an", "the", "and", "but", "if", "or", "because", "as", "until", "while", "of", "at", "by", "for", "with", "about", "against", "between", "into", "through", "during", "before", "after", "above", "below", "to", "from", "up", "down", "in", "out", "on", "off", "over", "under", "again", "further", "then", "once", "here", "there", "when", "where", "why", "how", "all", "any", "both", "each", "few", "more", "most", "other", "some", "such", "no", "nor", "not", "only", "own", "same", "so", "than", "too", "very", "s", "t", "can", "will", "just", "don", "should", "now"]) data = fetch_20newsgroups() x = tokenize(data.data, stop_words) y = data.target test_ratio = 0.2 test_split = np.random.uniform(0, 1, len(x)) train_x = x[test_split >= test_ratio] test_x = x[test_split < test_ratio] train_y = y[test_split >= test_ratio] test_y = y[test_split < test_ratio] nb = NaiveBayes() nb.fit(train_x, train_y) print("predicting") print(sum(nb.predict(train_x) == train_y) / train_x.shape[0]) print(sum(nb.predict(test_x) == test_y) / test_y.shape[0]) if __name__ == "__main__": main()
2.515625
3
code.py
priyanshnama/Hackerrank-Automation-Prototype
0
12790089
<filename>code.py<gh_stars>0 import string import urllib3 import random import json # log file log = open("log.txt", "a+") Head = ["firstname\t", "lastname\t", "email\t\t\t", "college\t", "city\t", "phone\t\t", "password\t", "refral\t"] log.writelines(Head) code = input("Enter Your Refral code: ") points = int((int(input("how much point you want to generate: ")))/10) point = int(points/10) # fields for i in range(point): firstname = ''.join(random.choices(string.ascii_uppercase + string.digits, k=5)) email = firstname + "@gmail.com" lastname = 'Jr' college = 'IIITDMJ' city = 'Dumna' phone = '1234567890' password = '<PASSWORD>' refral = code data = { "firstname": firstname, "lastname": lastname, "email": email, "college": college, "city": city, "phone": phone, "password": password, "refral": refral, } L = [v for k, v in data.items()] L[0] = " " + L[0] L[1] = " " + L[1] for index in range(len(L)): L[index] = L[index] + "\t" log.writelines("\n") log.writelines(L) http = urllib3.PoolManager() try: r = http.request('GET', 'https://invicta20.org/register', retries=False) encoded_data = json.dumps(data).encode('utf-8') r = http.request('POST', 'https://invicta20.org/register', body=encoded_data, headers={'Content-Type': 'application/json'}) json.loads(r.data.decode('utf-8'))['json'] var = {'attribute': 'value'} except urllib3.exceptions.NewConnectionError: print('Connection failed.') except json.decoder.JSONDecodeError: var = {'attribute': 'value'}
2.9375
3
nygame/_quietload.py
nfearnley/nygame
1
12790090
import os os.environ["PYGAME_HIDE_SUPPORT_PROMPT"] = "1"
1.367188
1
_unittests/ut_rss/test_rss_compile.py
sdpython/pyrsslocal
2
12790091
<gh_stars>1-10 # coding: utf-8 """ @brief test log(time=2s) """ import os import unittest from pyquickhelper.loghelper import fLOG from pyquickhelper.pycode import get_temp_folder, ExtTestCase from pyrsslocal.cli import compile_rss_blogs class TestRSSCompile(ExtTestCase): def test_rss_compile(self): fLOG( __file__, self._testMethodName, OutputPrint=__name__ == "__main__") temp = get_temp_folder(__file__, "temp_rss_compile") out_html = os.path.join(temp, 'index.html') out_rss = os.path.join(temp, 'rssfile.xml') links = ['http://www.xavierdupre.fr/blog/xdbrss.xml', 'http://www.xavierdupre.fr/app/ensae_projects/helpsphinx/_downloads/rss.xml'] compile_rss_blogs(links, "http://www.xavierdupre.fr/blogagg.html", 'Aggregation of blog posts published on <a href=' '"http://www.xavierdupre.fr.">xavierdupre.fr</a>', title="Recent posts", author="<NAME>", out_html=out_html, out_rss=out_rss, fLOG=fLOG) self.assertExists(out_html) self.assertExists(out_rss) if __name__ == "__main__": unittest.main()
2.34375
2
plantpredict/helpers.py
plantpredict/python-sdk
2
12790092
import pandas as pd def load_from_excel(file_path, sheet_name=None): """ Loads the data from an Excel file into a list of dictionaries, where each dictionary represents a row in the Excel file and the keys of each dictionary represent each column header in the Excel file. The method creates this list of dictionaries via a Pandas dataframe. :param file_path: The full file path (appended with .xlsx) of the Excel file to be loaded. :type file_path: str :param sheet_name: Name of a particular sheet in the file to load (optional, defaults to the first sheet in the Excel file). :type sheet_name: str :return: List of dictionaries, each dictionary representing a row in the Excel file. :rtype: list of dict """ xl = pd.ExcelFile(file_path) sheet_name = sheet_name if sheet_name else xl.sheet_names[0] return xl.parse(sheet_name, index_col=None).to_dict('records') def export_to_excel(data, file_path, sheet_name="Sheet1", field_order=None, sorting_fields=None): """ Writes data from a list of dictionaries to an Excel file, where each dictionary represents a row in the Excel file and the keys of each dictionary represent each column header in the Excel file. :param data: List of dictionaries, each dictionary representing a row in the Excel file. :type data: list of dict :param file_path: The full file path (appended with .xlsx) of the Excel file to be written to. This will overwrite data if both file_path and sheet_name already exist. :type file_path: str :param sheet_name: Name of a particular sheet in the file to write to (optional, defaults to "Sheet1"). :type sheet_name: str :param field_order: List of keys from data ordered to match the intended Excel column ordering (left to right). Must include all keys/columns. Any keys omitted from the list will not be written as columns. (optional) :type field_order: list of str :param sorting_fields: List of keys from data to be used as sorting columns (small to large) in Excel. Can be any length from 1 column to every column. The order of the list will dictate the sorting order. :type sorting_fields: list of str :return: None """ writer = pd.ExcelWriter(file_path, engine='openpyxl') df = pd.DataFrame(data) if field_order: df = df[field_order] if sorting_fields: df = df.sort_values(sorting_fields) df.to_excel(writer, sheet_name=sheet_name, index=False) writer.save()
4.21875
4
ulm/settings/local.py
dupuy/ulm
1
12790093
<reponame>dupuy/ulm<gh_stars>1-10 # pylint: disable=W0401,W0614,C0111 from .base import * # noqa ADMINS = ( ('<NAME>', '<EMAIL>'), ) MANAGERS = ADMINS # Make this unique, and don't share it with anybody. SECRET_KEY = '<KEY>'
1.296875
1
examples/1827402009.py
lobo0616/bysj
1
12790094
<filename>examples/1827402009.py # 学号:1827402009 # 姓名:肖鹏 # IP:192.168.157.232 # 上传时间:2018/11/12 15:22:55 import math def func1(a,b): if a>=b or int(a)!=a or int(b)!=b : return None else: d=1 for i in range(a,b): d=d*i c=len(str(d)) x=1 for j in range(1,x+1): if c%10**j==0: x=x+1 else: break return(x) def func2(a,b): if int(a)!=a or int(b)!=b: return None else: n=0 for i in range(a,b+1): m=str(i) h=list(m) if list(reversed(m))==h: n+=1 else: break return(n) def func3(lst): for i in lst[:]: if int(i)!=i: return None elif i<0 or i%3==0: lst.remove(i) lst.sort(reverse=True) return (lst) if __name__=="__main__": pass
3.734375
4
dynatrace-scripts/checkforproblems.py
nikhilgoenkatech/Jekins
0
12790095
<filename>dynatrace-scripts/checkforproblems.py import sys import json import requests def main(): DT_URL = sys.argv[1] DT_TOKEN = sys.argv[2] endpoint = DT_URL + "api/v1/problem/status" get_param = {'Accept':'application/json; charset=utf-8', 'Authorization':'Api-Token {}'.format(DT_TOKEN)} config_post = requests.get(endpoint, headers = get_param) jsonObj = applications = json.loads(config_post.text) problem = jsonObj["result"]["totalOpenProblemsCount"] return problem if __name__=="__main__": val = main() exit(val)
2.59375
3
WIP/urls.py
kodi-sk/CSI-WIP
0
12790096
"""WIP URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.10/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import url from django.contrib import admin from complaint.views import show_complaints from complaint.views import reject, signup from django.contrib.auth import views as auth_views from complaint.views import reject from complaint.views import index from complaint.views import resolved from complaint.views import detail urlpatterns = [ url(r'^admin/', admin.site.urls), url(r'^show/$',show_complaints), url(r'^reject/complaint/(\d{1,2})/$',reject), url(r'^register/$',signup), url(r'^$', auth_views.login, name='login'), url(r'^logout/$', auth_views.logout, name='logout'), url(r'^complaint/$',index), url(r'^resolved/complaint/(\d{1,2})/$',resolved), url(r'^complaint/(\d{1,2})/',detail), ]
2.53125
3
src/Honeybee_EnergyPlus Window Shade Generator.py
rdzeldenrust/Honeybee
1
12790097
<reponame>rdzeldenrust/Honeybee # This component creates shades for Honeybee Zones # By <NAME> # <EMAIL> # Ladybug started by <NAME> is licensed # under a Creative Commons Attribution-ShareAlike 3.0 Unported License. """ Use this component to generate shades for Honeybee zone windows. The component has two main uses: _ The first is that it can be used to assign blind objects to HBZones prior to simulation. These blinds can be dynamically controlled via a schedule. Note that shades created this way will automatically be assigned to the zone and the windowBreps and shadeBreps outputs are just for visualization. _ The second way to use the component is to create test shade areas for shade benefit evaluation after an energy simulation has already been run. In this case, the component helps keep the data tree paths of heating, cooling and beam gain synced with that of the zones and windows. For this, you would take imported EnergyPlus results and hook them up to the "zoneData" inputs and use the output "zoneDataTree" in the shade benefit evaluation. - Provided by Honeybee 0.0.55 Args: _HBObjects: The HBZones out of any of the HB components that generate or alter zones. Note that these should ideally be the zones that are fed into the Run Energy Simulation component. Zones read back into Grasshopper from the Import idf component will not align correctly with the EP Result data. blindsMaterial_: An optional blind material from the blind material component. If no material is connected here, the component will automatically assign a material of 0.65 solar reflectance, 0 transmittance, 0.9 emittance, 0.25 mm thickness, 221 W/mK conductivity. blindsSchedule_: An optional schedule to raise and lower the blinds. If no value is connected here, the blinds will assume the "ALWAYS ON" shcedule. north_: Input a vector to be used as a true North direction or a number between 0 and 360 that represents the degrees off from the y-axis to make North. The default North direction is set to the Y-axis (0 degrees). _depth: A number representing the depth of the shade to be generated on each window. You can also input lists of depths, which will assign different depths based on cardinal direction. For example, inputing 4 values for depths will assign each value of the list as follows: item 0 = north depth, item 1 = west depth, item 2 = south depth, item 3 = east depth. Lists of vectors to be shaded can also be input and shades can be joined together with the mergeVectors_ input. _numOfShds: The number of shades to generated for each glazed surface. _distBetween: An alternate option to _numOfShds where the input here is the distance in Rhino units between each shade. horOrVertical_: Set to "True" to generate horizontal shades or "False" to generate vertical shades. You can also input lists of horOrVertical_ input, which will assign different orientations based on cardinal direction. shdAngle_: A number between -90 and 90 that represents an angle in degrees to rotate the shades. The default is set to "0" for no rotation. If you have vertical shades, use this to rotate them towards the South by a certain value in degrees. If applied to windows facing East or West, tilting the shades like this will let in more winter sun than summer sun. If you have horizontal shades, use this input to angle shades downward. You can also put in lists of angles to assign different shade angles to different cardinal directions. interiorOrExter_: Set to "True" to generate Shades on the interior and set to "False" to generate shades on the exterior. The default is set to "False" to generate exterior shades. distToGlass_: A number representing the offset distance from the glass to make the shades. _runIt: Set boolean to "True" to run the component and generate shades. ---------------: ... zoneData1_: Optional zone data for the HBZones_ that will be aligned with the generated windows. Use this to align data like heating load, cooling load or beam gain for a shade benefit simulation with the generated shades. zoneData2_: Optional zone data for the HBZones_ that will be aligned with the generated windows. Use this to align data like heating load, cooling load or beam gain for a shade benefit simulation with the generated shades. zoneData3_: Optional zone data for the HBZones_ that will be aligned with the generated windows. Use this to align data like heating load, cooling load or beam gain for a shade benefit simulation with the generated shades. Returns: readMe!: ... ---------------: ... HBZones: The HBZones with the assigned shading (ready to be simulated). ---------------: ... windowBreps: Breps representing each window of the zone. These can be plugged into a shade benefit evaulation as each window is its own branch of a grasshopper data tree. shadeBreps: Breps representing each shade of the window. These can be plugged into a shade benefit evaulation as each window is its own branch of a grasshopper data tree. Alternatively, they can be plugged into an EnergyPlus simulation with the "Honeybee_EP Context Surfaces" component. ---------------: ... zoneData1Tree: Data trees of the zoneData1_, which align with the branches for each window above. zoneData2Tree: Data trees of the zoneData2_, which align with the branches for each window above. zoneData3Tree: Data trees of the izoneData3_, which align with the branches for each window above. """ ghenv.Component.Name = "Honeybee_EnergyPlus Window Shade Generator" ghenv.Component.NickName = 'EPWindowShades' ghenv.Component.Message = 'VER 0.0.55\nSEP_11_2014' ghenv.Component.Category = "Honeybee" ghenv.Component.SubCategory = "09 | Energy | Energy" #compatibleHBVersion = VER 0.0.55\nAUG_25_2014 #compatibleLBVersion = VER 0.0.58\nAUG_20_2014 try: ghenv.Component.AdditionalHelpFromDocStrings = "1" except: pass from System import Object from System import Drawing from clr import AddReference AddReference('Grasshopper') import Grasshopper.Kernel as gh from Grasshopper import DataTree from Grasshopper.Kernel.Data import GH_Path import Rhino as rc import rhinoscriptsyntax as rs import scriptcontext as sc import uuid import math import os w = gh.GH_RuntimeMessageLevel.Warning tol = sc.doc.ModelAbsoluteTolerance def checkTheInputs(zoneNames, windowNames, windowSrfs, isZone): #Check if the user has hooked up a distBetwee or numOfShds. if _distBetween == [] and _numOfShds == []: numOfShd = [1] print "No value is connected for number of shades. The component will be run with one shade per window." else: numOfShd = _numOfShds #Check the depths. checkData2 = True if _depth == []: checkData2 = False print "You must provide a depth for the shades." ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Warning, "You must provide a depth for the shades.") #Check if there is a blinds material connected and, if not, set a default. checkData5 = True if blindsMaterial_ == None: print "No blinds material has been connected. A material will be used with 0.65 solar reflectance, 0 transmittance, 0.9 emittance, 0.25 mm thickness, 221 W/mK conductivity." blindsMaterial = ['DEFAULTBLINDSMATERIAL', 0.65, 0, 0.9, 0.00025, 221] else: try: blindsMaterial = deconstructBlindMaterial(blindsMaterial_) except: checkData5 = False warning = 'Blinds material is not a valid blinds material from the "Honeybee_EnergyPlus Blinds Material" component.' print warning ghenv.Component.AddRuntimeMessage(w, warning) #Check if there is a blinds schedule connected and, if not, set a default. checkData4 = True if blindsSchedule_ == None: schedule = "ALWAYSON" print "No blinds schedule has been connected. It will be assumed that the blinds are always drawn" else: schedule= blindsSchedule_.upper() if schedule!=None and not schedule.lower().endswith(".csv") and schedule not in HBScheduleList: msg = "Cannot find " + schedule + " in Honeybee schedule library." print msg ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Warning, msg) checkData4 = False elif schedule!=None and schedule.lower().endswith(".csv"): # check if csv file is existed if not os.path.isfile(schedule): msg = "Cannot find the shchedule file: " + schedule print msg ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Warning, msg) checkData4 = False #Create a Python list from the input data trees. def makePyTree(zoneData): dataPyList = [] for i in range(zoneData.BranchCount): branchList = zoneData.Branch(i) dataVal = [] for item in branchList: dataVal.append(item) dataPyList.append(dataVal) return dataPyList allData = [] allData.append(makePyTree(zoneData1_)) allData.append(makePyTree(zoneData2_)) allData.append(makePyTree(zoneData3_)) #Test to see if the data lists have a headers on them, which is necessary to match the data to a zone or window. If there's no header, the data cannot be coordinated with this component. checkData3 = True checkBranches = [] allHeaders = [] allNumbers = [] for branch in allData: checkHeader = [] dataHeaders = [] dataNumbers = [] for list in branch: if str(list[0]) == "key:location/dataType/units/frequency/startsAt/endsAt": checkHeader.append(1) dataHeaders.append(list[:7]) dataNumbers.append(list[7:]) allHeaders.append(dataHeaders) allNumbers.append(dataNumbers) if sum(checkHeader) == len(branch):pass else: checkData3 = False warning = "Not all of the connected zoneData has a Ladybug/Honeybee header on it. This header is necessary for data input to this component." print warning ghenv.Component.AddRuntimeMessage(w, warning) #Align all of the lists to each window. windowNamesFinal = [] windowBrepsFinal = [] alignedDataTree = [] for item in allData: alignedDataTree.append([]) for zoneCount, windowList in enumerate(windowSrfs): if isZone == True: zoneName = zoneNames[zoneCount] for windowCount, window in enumerate(windowList): windowBrepsFinal.append(window) windowName = windowNames[zoneCount][windowCount] windowNamesFinal.append(windowName) for inputDataTreeCount, branch in enumerate(allHeaders): #Test to see if the data is for the zone level. zoneData = False if isZone == True: for listCount, header in enumerate(branch): if header[2].split(' for ')[-1] == zoneName.upper(): alignedDataTree[inputDataTreeCount].append(allData[inputDataTreeCount][listCount]) zoneData = True #Test to see if the data is for the window level. srfData = False if zoneData == False: for listCount, header in enumerate(branch): try: winNm = header[2].split(' for ')[-1].split(': ')[0] except: winNm = header[2].split(' for ')[-1] if str(winNm) == str(windowName.upper()): alignedDataTree[inputDataTreeCount].append(allData[inputDataTreeCount][listCount]) srfData = True if zoneData == False and srfData == False and alignedDataTree != [[], [], []]: print "A window was not matched with its respective zone/surface data." if checkData2 == True and checkData3 == True and checkData4 == True and checkData5 == True: checkData = True else: checkData = False return checkData, windowNamesFinal, windowBrepsFinal, _depth, alignedDataTree, numOfShd, blindsMaterial, schedule def analyzeGlz(glzSrf, distBetween, numOfShds, horOrVertical, lb_visualization, normalVector): # find the bounding box bbox = glzSrf.GetBoundingBox(True) if horOrVertical == None: horOrVertical = True if numOfShds == None and distBetween == None: numOfShds = 1 if numOfShds == 0 or distBetween == 0: sortedPlanes = [] elif horOrVertical == True: # Horizontal #Define a bounding box for use in calculating the number of shades to generate minZPt = bbox.Corner(False, True, True) minZPt = rc.Geometry.Point3d(minZPt.X, minZPt.Y, minZPt.Z) maxZPt = bbox.Corner(False, True, False) maxZPt = rc.Geometry.Point3d(maxZPt.X, maxZPt.Y, maxZPt.Z - sc.doc.ModelAbsoluteTolerance) centerPt = bbox.Center #glazing hieghts glzHeight = minZPt.DistanceTo(maxZPt) # find number of shadings try: numOfShd = int(numOfShds) shadingHeight = glzHeight/numOfShd shadingRemainder = shadingHeight except: shadingHeight = distBetween shadingRemainder = (((glzHeight/distBetween) - math.floor(glzHeight/distBetween))*distBetween) if shadingRemainder == 0: shadingRemainder = shadingHeight # find shading base planes planeOrigins = [] planes = [] X, Y, z = minZPt.X, minZPt.Y, minZPt.Z zHeights = rs.frange(minZPt.Z + shadingRemainder, maxZPt.Z + 0.5*sc.doc.ModelAbsoluteTolerance, shadingHeight) try: for Z in zHeights: planes.append(rc.Geometry.Plane(rc.Geometry.Point3d(X, Y, Z), rc.Geometry.Vector3d.ZAxis)) except: # single shading planes.append(rc.Geometry.Plane(rc.Geometry.Point3d(maxZPt), rc.Geometry.Vector3d.ZAxis)) # sort the planes sortedPlanes = sorted(planes, key=lambda a: a.Origin.Z) elif horOrVertical == False: # Vertical # Define a vector to be used to generate the planes planeVec = rc.Geometry.Vector3d(normalVector.X, normalVector.Y, 0) planeVec.Rotate(1.570796, rc.Geometry.Vector3d.ZAxis) #Define a bounding box for use in calculating the number of shades to generate minXYPt = bbox.Corner(True, True, True) minXYPt = rc.Geometry.Point3d(minXYPt.X, minXYPt.Y, minXYPt.Z) maxXYPt = bbox.Corner(False, False, True) maxXYPt = rc.Geometry.Point3d(maxXYPt.X, maxXYPt.Y, maxXYPt.Z) centerPt = bbox.Center #Test to be sure that the values are parallel to the correct vector. testVec = rc.Geometry.Vector3d.Subtract(rc.Geometry.Vector3d(minXYPt.X, minXYPt.Y, minXYPt.Z), rc.Geometry.Vector3d(maxXYPt.X, maxXYPt.Y, maxXYPt.Z)) if testVec.IsParallelTo(planeVec) == 0: minXYPt = bbox.Corner(False, True, True) minXYPt = rc.Geometry.Point3d(minXYPt.X, minXYPt.Y, minXYPt.Z) maxXYPt = bbox.Corner(True, False, True) maxXYPt = rc.Geometry.Point3d(maxXYPt.X, maxXYPt.Y, maxXYPt.Z) #Adjust the points to ensure the creation of the correct number of shades starting from the northernmost side of the window. tolVec = rc.Geometry.Vector3d.Subtract(rc.Geometry.Vector3d(minXYPt.X, minXYPt.Y, minXYPt.Z), rc.Geometry.Vector3d(maxXYPt.X, maxXYPt.Y, maxXYPt.Z)) tolVec.Unitize() tolVec = rc.Geometry.Vector3d.Multiply(sc.doc.ModelAbsoluteTolerance*2, tolVec) if tolVec.X > 0 and tolVec.Y > 0: tolVec = rc.Geometry.Vector3d.Multiply(1, tolVec) norOrient = False if tolVec.X < 0 and tolVec.Y > 0: tolVec = rc.Geometry.Vector3d.Multiply(1, tolVec) norOrient = False if tolVec.X < 0 and tolVec.Y < 0: tolVec = rc.Geometry.Vector3d.Multiply(-1, tolVec) norOrient = True else: tolVec = rc.Geometry.Vector3d.Multiply(-1, tolVec) norOrient = True maxXYPt = rc.Geometry.Point3d.Subtract(maxXYPt, tolVec) minXYPt = rc.Geometry.Point3d.Subtract(minXYPt, tolVec) #glazing distance glzHeight = minXYPt.DistanceTo(maxXYPt) # find number of shadings try: numOfShd = int(numOfShds) shadingHeight = glzHeight/numOfShd shadingRemainder = shadingHeight except: shadingHeight = distBetween shadingRemainder = (((glzHeight/distBetween) - math.floor(glzHeight/distBetween))*distBetween) if shadingRemainder == 0: shadingRemainder = shadingHeight # find shading base planes planeOrigins = [] planes = [] pointCurve = rc.Geometry.Curve.CreateControlPointCurve([maxXYPt, minXYPt]) divisionParams = pointCurve.DivideByLength(shadingHeight, True) divisionPoints = [] for param in divisionParams: divisionPoints.append(pointCurve.PointAt(param)) planePoints = divisionPoints try: for point in planePoints: planes.append(rc.Geometry.Plane(point, planeVec)) except: # single shading planes.append(rc.Geometry.Plane(rc.Geometry.Point3d(minXYPt), planeVec)) sortedPlanes = planes return sortedPlanes, shadingHeight def makeShade(_glzSrf, depth, numShds, distBtwn): rotationAngle_ = 0 # import the classes lb_preparation = sc.sticky["ladybug_Preparation"]() lb_mesh = sc.sticky["ladybug_Mesh"]() lb_visualization = sc.sticky["ladybug_ResultVisualization"]() # find the normal of the surface in the center # note2developer: there might be cases that the surface is not planar and # the normal is changing from point to point, then I should sample the test surface # and test the normal direction for more point baseSrfCenPt = rc.Geometry.AreaMassProperties.Compute(_glzSrf).Centroid # sometimes the center point is not located on the surface baseSrfCenPt = _glzSrf.ClosestPoint(baseSrfCenPt) bool, centerPtU, centerPtV = _glzSrf.Faces[0].ClosestPoint(baseSrfCenPt) if bool: normalVector = _glzSrf.Faces[0].NormalAt(centerPtU, centerPtV) #return rc.Geometry.Plane(baseSrfCenPt,normalVector) else: print "Couldn't find the normal of the shading surface." + \ "\nRebuild the surface and try again!" return -1 shadingSurfaces =[] #Define a function that can get the angle to North of any surface. def getAngle2North(normalVector): if north_ != None and north_.IsValid(): northVector = north_ else:northVector = rc.Geometry.Vector3d.YAxis angle = rc.Geometry.Vector3d.VectorAngle(northVector, normalVector, rc.Geometry.Plane.WorldXY) finalAngle = math.degrees(angle) return finalAngle # Define a function that can split up a list of values and assign it to different cardinal directions. def getValueBasedOnOrientation(valueList): angles = [] if valueList == None or len(valueList) == 0: value = None if len(valueList) == 1: value = valueList[0] elif len(valueList) > 1: initAngles = rs.frange(0, 360, 360/len(valueList)) for an in initAngles: angles.append(an-(360/(2*len(valueList)))) angles.append(360) for angleCount in range(len(angles)-1): if angles[angleCount] <= (getAngle2North(normalVector))%360 <= angles[angleCount +1]: targetValue = valueList[angleCount%len(valueList)] value = targetValue return value # If multiple shading depths are given, use it to split up the glazing by cardinal direction and assign different depths to different directions. depth = getValueBasedOnOrientation(depth) # If multiple number of shade inputs are given, use it to split up the glazing by cardinal direction and assign different numbers of shades to different directions. numShds = getValueBasedOnOrientation(numShds) # If multiple distances between shade inputs are given, use it to split up the glazing by cardinal direction and assign different distances of shades to different directions. distBtwn = getValueBasedOnOrientation(distBtwn) # If multiple horizontal or vertical inputs are given, use it to split up the glazing by cardinal direction and assign different horizontal or vertical to different directions. horOrVertical = getValueBasedOnOrientation(horOrVertical_) # If multiple shdAngle_ inputs are given, use it to split up the glazing by cardinal direction and assign different shdAngle_ to different directions. shdAngle = getValueBasedOnOrientation(shdAngle_) #If multiple interiorOrExter_ inputs are given, use it to split up the glazing by cardinal direction and assign different interiorOrExterior_ to different directions. interiorOrExter = getValueBasedOnOrientation(interiorOrExter_) #If multiple distToGlass_ inputs are given, use it to split up the glazing by cardinal direction and assign different distToGlass_ to different directions. distToGlass = getValueBasedOnOrientation(distToGlass_) # generate the planes planes, shadingHeight = analyzeGlz(_glzSrf, distBtwn, numShds, horOrVertical, lb_visualization, normalVector) # find the intersection crvs as the base for shadings intCrvs =[] for plane in planes: try: intCrvs.append(rc.Geometry.Brep.CreateContourCurves(_glzSrf, plane)[0]) except: print "One intersection failed." if normalVector != rc.Geometry.Vector3d.ZAxis: normalVectorPerp = rc.Geometry.Vector3d(normalVector.X, normalVector.Y, 0) angleFromNorm = math.degrees(rc.Geometry.Vector3d.VectorAngle(normalVectorPerp, normalVector)) if normalVector.Z < 0: angleFromNorm = angleFromNorm*(-1) #If the user has set the shades to generate on the interior, flip the normal vector. if interiorOrExter == True: normalVectorPerp.Reverse() else: interiorOrExter = False #If a shdAngle is provided, use it to rotate the planes by that angle if shdAngle != None: if horOrVertical == True or horOrVertical == None: horOrVertical = True planeVec = rc.Geometry.Vector3d(normalVector.X, normalVector.Y, 0) planeVec.Rotate(1.570796, rc.Geometry.Vector3d.ZAxis) normalVectorPerp.Rotate((shdAngle*0.01745329), planeVec) elif horOrVertical == False: planeVec = rc.Geometry.Vector3d.ZAxis if getAngle2North(normalVectorPerp) < 180: normalVectorPerp.Rotate((shdAngle*0.01745329), planeVec) else: normalVectorPerp.Rotate((shdAngle*-0.01745329), planeVec) else: shdAngle = 0 #Make EP versions of some of the outputs. EPshdAngleInint = angleFromNorm+shdAngle if EPshdAngleInint >= 0: EPshdAngle = 90 - EPshdAngleInint else: EPshdAngle = 90 + (EPshdAngleInint)*-1 if EPshdAngle > 180 or EPshdAngle < 0: warning = "The input shdAngle_ value will cause EnergyPlus to crash." print warning ghenv.Component.AddRuntimeMessage(w, warning) if horOrVertical == True: EPSlatOrient = 'Horizontal' else: EPSlatOrient = 'Vertical' if interiorOrExter == True: EPinteriorOrExter = 'InteriorBlind' else: EPinteriorOrExter = 'ExteriorBlind' #Generate the shade curves based on the planes and extrusion vectors if intCrvs !=[]: for c in intCrvs: try: shdSrf = rc.Geometry.Surface.CreateExtrusion(c, float(depth) * normalVectorPerp).ToBrep() shadingSurfaces.append(shdSrf) except: pass #If the user has specified a distance to move the shades, move them along the normal vector. if distToGlass != None: transVec = normalVectorPerp transVec.Unitize() finalTransVec = rc.Geometry.Vector3d.Multiply(distToGlass, transVec) blindsTransform = rc.Geometry.Transform.Translation(finalTransVec) for shdSrf in shadingSurfaces: shdSrf.Transform(blindsTransform) else: distToGlass = 0 #Get the EnergyPlus distance to glass. EPDistToGlass = distToGlass + (depth)*(0.5)*math.cos(math.radians(EPshdAngle)) if EPDistToGlass < 0.01: EPDistToGlass = 0.01 elif EPDistToGlass > 1: warning = "The input distToGlass_ value is so large that it will cause EnergyPlus to crash." print warning ghenv.Component.AddRuntimeMessage(w, warning) #Check the depth and the shadingHeight to see if E+ will crash. assignEPCheckInit = True if depth > 1: assignEPCheckInit = False warning = "Note that E+ does not like shading depths greater than 1. HBObjWShades will not be generated. shadeBreps will still be produced and you can account for these shades using a 'Honeybee_EP Context Surfaces' component." print warning ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Remark, warning) if shadingHeight > 1: assignEPCheckInit = False warning = "Note that E+ does not like distances between shades that are greater than 1. HBObjWShades will not be generated. shadeBreps will still be produced and you can account for these shades using a 'Honeybee_EP Context Surfaces' component." print warning ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Remark, warning) return shadingSurfaces, EPSlatOrient, depth, shadingHeight, EPshdAngle, EPDistToGlass, EPinteriorOrExter, assignEPCheckInit def deconstructBlindMaterial(material): matLines = material.split('\n') name = matLines[1].split(',')[0] reflect = float(matLines[2].split(',')[0]) transmit = float(matLines[3].split(',')[0]) emiss = float(matLines[4].split(',')[0]) thickness = float(matLines[5].split(',')[0]) conduct = float(matLines[6].split(';')[0]) return [name, reflect, transmit, emiss, thickness, conduct] def createEPBlindMat(blindsMaterial, EPSlatOrient, depth, shadingHeight, EPshdAngle, distToGlass, name): EPBlindMat = "WindowMaterial:Blind,\n" + \ '\t' + blindsMaterial[0] + "_" + name + ', !- Name\n' + \ '\t' + EPSlatOrient + ', !- Slat Orientation\n' + \ '\t' + str(depth) + ', !- Slat Width {m}\n' + \ '\t' + str(shadingHeight) +', !- Slat Separation {m}\n' + \ '\t' + str(blindsMaterial[4]) + ', !- Slat Thickness {m}\n' + \ '\t' + str(EPshdAngle) + ', !- Slat Angle {deg}\n' + \ '\t' + str(blindsMaterial[5]) + ', !- Slat Conductivity {W/m-K}\n' + \ '\t' + str(blindsMaterial[2]) + ', !- Slat Beam Solar Transmittance\n' + \ '\t' + str(blindsMaterial[1]) + ', !- Front Side Slat Beam Solar Reflectance\n' + \ '\t' + str(blindsMaterial[1]) + ', !- Back Side Slat Beam Solar Reflectance\n' + \ '\t' + ', !- Slat Diffuse Solar Transmittance\n' + \ '\t' + str(blindsMaterial[1]) + ', !- Front Side Slat Diffuse Solar Reflectance\n' + \ '\t' + str(blindsMaterial[1]) + ', !- Back Side Slat Diffuse Solar Reflectance\n' + \ '\t' + str(blindsMaterial[2]) + ', !- Slat Beam Visible Transmittance\n' + \ '\t' + ', !- Front Side Slat Beam Visible Reflectance\n' + \ '\t' + ', !- Back Side Slat Beam Visible Reflectance\n' + \ '\t' + ', !- Slat Diffuse Visible Transmittance\n' + \ '\t' + ', !- Front Side Slat Diffuse Visible Reflectance\n' + \ '\t' + ', !- Back Side Slat Diffuse Visible Reflectance\n' + \ '\t' + ', !- Slat Infrared Hemispherical Transmittance\n' + \ '\t' + str(blindsMaterial[3]) + ', !- Front Side Slat Infrared Hemispherical Emissivity\n' + \ '\t' + str(blindsMaterial[3]) + ', !- Back Side Slat Infrared Hemispherical Emissivity\n' + \ '\t' + str(distToGlass) + ', !- Blind to Glass Distance {m}\n' + \ '\t' + '0.5, !- Blind Top Opening Multiplier\n' + \ '\t' + ', !- Blind Bottom Opening Multiplier\n' + \ '\t' + '0.5, !- Blind Left Side Opening Multiplier\n' + \ '\t' + '0.5, !- Blind Right Side Opening Multiplier\n' + \ '\t' + ', !- Minimum Slat Angle {deg}\n' + \ '\t' + '180; !- Maximum Slat Angle {deg}\n' return EPBlindMat def createEPBlindControl(blindsMaterial, schedule, EPinteriorOrExter, name): if schedule == 'ALWAYSON': schedCntrlType = 'ALWAYSON' schedCntrl = 'No' schedName = '' else: schedName = schedule schedCntrlType = 'OnIfScheduleAllows' schedCntrl = 'Yes' EPBlindControl = 'WindowProperty:ShadingControl,\n' + \ '\t' + 'BlindCntrlFor_' + name +', !- Name\n' + \ '\t' + EPinteriorOrExter + ', !- Shading Type\n' + \ '\t' + ', !- Construction with Shading Name\n' + \ '\t' + schedCntrlType + ', !- Shading Control Type\n' + \ '\t' + schedName + ', !- Schedule Name\n' + \ '\t' + ', !- Setpoint {W/m2, W or deg C}\n' + \ '\t' + schedCntrl + ', !- Shading Control Is Scheduled\n' + \ '\t' + 'No, !- Glare Control Is Active\n' + \ '\t' + blindsMaterial[0] + "_" + name + ', !- Shading Device Material Name\n' + \ '\t' + 'FixedSlatAngle, !- Type of Slat Angle Control for Blinds\n' + \ '\t' + '; !- Slat Angle Schedule Name\n' return EPBlindControl def main(): if _HBObjects != [] and sc.sticky.has_key('honeybee_release') == True and sc.sticky.has_key('ladybug_release') == True: #Import the classes hb_EPZone = sc.sticky["honeybee_EPZone"] hb_EPSrf = sc.sticky["honeybee_EPSurface"] hb_EPFenSurface = sc.sticky["honeybee_EPFenSurface"] hb_hive = sc.sticky["honeybee_Hive"]() #Make the lists that will be filled up zoneNames = [] windowNames = [] windowSrfs = [] windowObjects = [] isZoneList = [] assignEPCheck = True HBObjWShades = [] EPSlatOrientList = [] depthList = [] shadingHeightList = [] EPshdAngleList = [] distToGlassList = [] EPinteriorOrExterList = [] #Call the objects from the hive. HBZoneObjects = hb_hive.callFromHoneybeeHive(_HBObjects) #Find out what the object is and make sure that we can run it through this component's functions. for object in HBZoneObjects: if object.objectType == "HBZone": isZoneList.append(1) zoneNames.append(object.name) winBreps = [] winNames = [] for srf in object.surfaces: if srf.hasChild: if srf.BC == 'OUTDOORS' or srf.BC == 'Outdoors': if srf.isPlanar == True: for childSrf in srf.childSrfs: windowObjects.append(childSrf) winNames.append(childSrf.name) winBreps.append(childSrf.geometry) else: print "One surface with a window is not planar. EenergyPlus shades will not be assigned to this window." else: print "One surface with a window does not have an outdoor boundary condition. EenergyPlus shades will not be assigned to this window." windowNames.append(winNames) windowSrfs.append(winBreps) elif object.objectType == "HBSurface": isZoneList.append(0) warning = "Note that, when using this component for individual surfaces, you should make sure that the direction of the surface is facing the outdoors in order to be sure that your shades are previewing correctly." print warning ghenv.Component.AddRuntimeMessage(gh.GH_RuntimeMessageLevel.Remark, warning) if not hasattr(object, 'type'): # find the type based on object.type = object.getTypeByNormalAngle() if not hasattr(object, 'angle2North'): # find the type based on object.getAngle2North() if not hasattr(object, "BC"): object.BC = 'OUTDOORS' if object.hasChild: if object.BC != 'OUTDOORS' and object.BC != 'Outdoors': assignEPCheck = False warning = "The boundary condition of the input object must be outdoors. E+ cannot create shades for intdoor windows." print warning ghenv.Component.AddRuntimeMessage(w, warning) elif object.isPlanar == False: assignEPCheck = False warning = "The surface must not be curved. With the way that we mesh curved surfaces for E+, the program would just freak out with blinds." print warning ghenv.Component.AddRuntimeMessage(w, warning) else: for childSrf in object.childSrfs: windowObjects.append(childSrf) windowNames.append([childSrf.name]) windowSrfs.append([childSrf.geometry]) #Make sure that all HBObjects are of the same type. checkSameType = True if sum(isZoneList) == len(_HBObjects): isZone = True elif sum(isZoneList) == 0: isZone = False else: checkSameType = False warning = "This component currently only supports inputs that are all HBZones or all HBSrfs but not both. For now, just grab another component for each of these inputs." print warning ghenv.Component.AddRuntimeMessage(w, warning) isZone = False #Check the inputs and make sure that we have everything that we need to generate the shades. Set defaults on things that are not connected. if checkSameType == True: checkData, windowNames, windowSrfsInit, depths, alignedDataTree, numOfShd, blindsMaterial, schedule = checkTheInputs(zoneNames, windowNames, windowSrfs, isZone) else: checkData == False #Generate the shades. if checkData == True: shadings = [] for window in windowSrfsInit: shadeBreps, EPSlatOrient, depth, shadingHeight, EPshdAngle, distToGlass, EPinteriorOrExter, assignEPCheckInit = makeShade(window, depths, numOfShd, _distBetween) shadings.append(shadeBreps) EPSlatOrientList.append(EPSlatOrient) depthList.append(depth) shadingHeightList.append(shadingHeight) EPshdAngleList.append(EPshdAngle) distToGlassList.append(distToGlass) EPinteriorOrExterList.append(EPinteriorOrExter) if assignEPCheckInit == False: assignEPCheck = False #Create the EnergyPlus blinds material and assign it to the windows with shades. if assignEPCheck == True: for count, windowObj in enumerate(windowObjects): windowObj.blindsMaterial = createEPBlindMat(blindsMaterial, EPSlatOrientList[count], depthList[count], shadingHeightList[count], EPshdAngleList[count], distToGlassList[count], windowObj.name) windowObj.shadingControl = createEPBlindControl(blindsMaterial, schedule, EPinteriorOrExterList[count], windowObj.name) windowObj.shadingControlName = 'BlindCntrlFor_' + windowObj.name windowObj.shadingSchName = schedule ModifiedHBZones = hb_hive.addToHoneybeeHive(HBZoneObjects, ghenv.Component.InstanceGuid.ToString() + str(uuid.uuid4())) else: ModifiedHBZones = [] return checkData, windowSrfsInit, shadings, alignedDataTree, ModifiedHBZones else: return False, [], [], [], [] else: print "You should first let both Honeybee and Ladybug fly..." ghenv.Component.AddRuntimeMessage(w, "You should first let both Honeybee and Ladybug fly...") return False, [], [], [], [] #Run the main functions. checkData = False if _HBObjects != [] and _runIt == True: checkData, windowSrfsInit, shadings, alignedDataTree, HBObjWShades = main() #Unpack the data trees. if checkData == True: windowBreps = DataTree[Object]() shadeBreps = DataTree[Object]() zoneData1Tree = DataTree[Object]() zoneData2Tree = DataTree[Object]() zoneData3Tree = DataTree[Object]() for count, brep in enumerate(windowSrfsInit): windowBreps.Add(brep, GH_Path(count)) for count, brepList in enumerate(shadings): for brep in brepList: shadeBreps.Add(brep, GH_Path(count)) for treeCount, finalTree in enumerate(alignedDataTree): if treeCount == 0: for bCount, branch in enumerate(finalTree): for twig in branch: zoneData1Tree.Add(twig, GH_Path(bCount)) elif treeCount == 1: for bCount, branch in enumerate(finalTree): for twig in branch: zoneData2Tree.Add(twig, GH_Path(bCount)) elif treeCount == 2: for bCount, branch in enumerate(finalTree): for twig in branch: zoneData3Tree.Add(twig, GH_Path(bCount))
2.28125
2
devserver/modules/profile.py
leture/django-devserver
467
12790098
from devserver.modules import DevServerModule from devserver.utils.time import ms_from_timedelta from devserver.settings import DEVSERVER_AUTO_PROFILE from datetime import datetime import functools import gc class ProfileSummaryModule(DevServerModule): """ Outputs a summary of cache events once a response is ready. """ logger_name = 'profile' def process_init(self, request): self.start = datetime.now() def process_complete(self, request): duration = datetime.now() - self.start self.logger.info('Total time to render was %.2fs', ms_from_timedelta(duration) / 1000) class LeftOversModule(DevServerModule): """ Outputs a summary of events the garbage collector couldn't handle. """ # TODO: Not even sure this is correct, but the its a general idea logger_name = 'profile' def process_init(self, request): gc.enable() gc.set_debug(gc.DEBUG_SAVEALL) def process_complete(self, request): gc.collect() self.logger.info('%s objects left in garbage', len(gc.garbage)) from django.template.defaultfilters import filesizeformat try: from guppy import hpy except ImportError: import warnings class MemoryUseModule(DevServerModule): def __new__(cls, *args, **kwargs): warnings.warn('MemoryUseModule requires guppy to be installed.') return super(MemoryUseModule, cls).__new__(cls) else: class MemoryUseModule(DevServerModule): """ Outputs a summary of memory usage of the course of a request. """ logger_name = 'profile' def __init__(self, request): super(MemoryUseModule, self).__init__(request) self.hpy = hpy() self.oldh = self.hpy.heap() self.logger.info('heap size is %s', filesizeformat(self.oldh.size)) def process_complete(self, request): newh = self.hpy.heap() alloch = newh - self.oldh dealloch = self.oldh - newh self.oldh = newh self.logger.info('%s allocated, %s deallocated, heap size is %s', *map(filesizeformat, [alloch.size, dealloch.size, newh.size])) try: from line_profiler import LineProfiler except ImportError: import warnings class LineProfilerModule(DevServerModule): def __new__(cls, *args, **kwargs): warnings.warn('LineProfilerModule requires line_profiler to be installed.') return super(LineProfilerModule, cls).__new__(cls) class devserver_profile(object): def __init__(self, follow=[]): pass def __call__(self, func): return func else: class LineProfilerModule(DevServerModule): """ Outputs a Line by Line profile of any @devserver_profile'd functions that were run """ logger_name = 'profile' def process_view(self, request, view_func, view_args, view_kwargs): request.devserver_profiler = LineProfiler() request.devserver_profiler_run = False if (DEVSERVER_AUTO_PROFILE): _unwrap_closure_and_profile(request.devserver_profiler, view_func) request.devserver_profiler.enable_by_count() def process_complete(self, request): if hasattr(request, 'devserver_profiler_run') and (DEVSERVER_AUTO_PROFILE or request.devserver_profiler_run): from cStringIO import StringIO out = StringIO() if (DEVSERVER_AUTO_PROFILE): request.devserver_profiler.disable_by_count() request.devserver_profiler.print_stats(stream=out) self.logger.info(out.getvalue()) def _unwrap_closure_and_profile(profiler, func): if not hasattr(func, 'func_code'): return profiler.add_function(func) if func.func_closure: for cell in func.func_closure: if hasattr(cell.cell_contents, 'func_code'): _unwrap_closure_and_profile(profiler, cell.cell_contents) class devserver_profile(object): def __init__(self, follow=[]): self.follow = follow def __call__(self, func): def profiled_func(*args, **kwargs): request = args[0] if hasattr(request, 'request'): # We're decorating a Django class-based-view and the first argument is actually self: request = args[1] try: request.devserver_profiler.add_function(func) request.devserver_profiler_run = True for f in self.follow: request.devserver_profiler.add_function(f) request.devserver_profiler.enable_by_count() return func(*args, **kwargs) finally: request.devserver_profiler.disable_by_count() return functools.wraps(func)(profiled_func)
2.25
2
editor/readsave/test.py
Atrosha/APOC-Editor
4
12790099
x1=10 y1=10 x2=9 y2=10 x=(x1*x1+y1*y1) y=(x2*x2+y2*y2) xyz=(x+y)//2 average_x=(x1+x2)//2 average_y=(y1+y2)//2 average_x_2=average_x*average_x average_y_2=average_y*average_y average=average_x_2+average_y_2 new_x=(x1+x2)-average_x new_y=(y1+y2)-average_y new_2=new_x*new_x+new_y*new_y disp=new_2 print(xyz-average,disp)
3.703125
4
hyperion/helpers/__init__.py
hyperion-ml/hyperion
14
12790100
<filename>hyperion/helpers/__init__.py """ Copyright 2018 Johns Hopkins University (Author: <NAME>) Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0) """ from .vector_reader import VectorReader from .vector_class_reader import VectorClassReader from .trial_data_reader import TrialDataReader from .multi_test_trial_data_reader import MultiTestTrialDataReader from .multi_test_trial_data_reader_v2 import MultiTestTrialDataReaderV2 from .classif_trial_data_reader import ClassifTrialDataReader # from .sequence_reader import SequenceReader # from .sequence_class_reader import SequenceClassReader # from .sequence_post_reader import SequencePostReader # from .sequence_post_class_reader import SequencePostClassReader from .plda_factory import PLDAFactory
1.515625
2
src/plot_AGs_results.py
syhw/contextual_word_segmentation
2
12790101
import numpy as np import pylab as pl import matplotlib import matplotlib.pyplot as plt from collections import defaultdict import glob import readline # otherwise the wrong readline is imported by rpy2 SAGE_XPS = 11 SAGE = 12 EAGE = 31 N_MONTHS = EAGE-SAGE+1 #TYPES = ["basic", "single-context", "topics"] #TYPES = ["basic", "topics"] TYPES = ["basic", "single-context"] TEST = False # if True, just use the values evaluated on a test test ITERS = range(499, 520) + range(1000,1005) #ITERS = range(1000,1005) #ITERS = range(600, 620) PREFIX = "" #PREFIX = "old_naima_XPs/" TAKE_MAX_SCORE = False # in case of several results, otherwise do the mean+std SORTED = True # sort the histograms by score, disable at your own risk! FACTOR_STD = 1. # 1.96 for 95% confidence interval OLDVERSION = False # version before March 10 LAST_ITERS = 10 # take the last XX iterations as results (considering converged) # USED ONLY FOR TEST currently if LAST_ITERS > 1 and TEST: TAKE_MAX_SCORE = False DO_ONLY = {'colloc_syll': 'baseline', 't_colloc_syll': 'split vocab', 't_readapt_colloc_syll': 'share vocab', 't_colloc_syll_wth_common': 'with common', #'t_permuted_colloc_syll': 'permuted split vocab', ### 't_permuted_colloc_syll_wth_common': 'permuted with common', #'t_random_colloc_syll': 'random split vocab', ### 't_random_colloc_syll_wth_common': 'random with common', 'colloc3_syll': 'colloc3 syll', 't_colloc3_syll_collocs_common': 'colloc3 syll collocs common'} #'syll': 'syll', #'t_syll': 'syll split vocab', #'t_readapt_syll': 'syll share vocab'} #'unigram': 'unigram', 't_readapt_unigram': 'unigram share vocab', #'t_unigram': 'unigram split vocab'} #'t_readapt_colloc_syll_wth_common': 'share vocab with common', #'t_readapt_colloc_syll_wth_common2': 'share vocab with common 2'} if OLDVERSION: DO_ONLY = {'syll': 'syll', 'colloc': 'colloc', 't_readapt_colloc': 't_colloc_shr_vocab', 't_syll': 't_syll_spl_vocab', 't_readapt_colloc_wth_common': 't_colloc_wth_common', 'colloc_syll': 'colloc_syll', 't_colloc_syll': 't_colloc_syll_spl_vocab', 't_readapt_colloc_syll': 't_colloc_syll_shr_vocab', 't_colloc_syll_wth_common': 't_colloc_syll_wth_common'} if TEST: DO_ONLY = {'t_nopfx_colloc_syll_wth_common': 'with common no prefix', 't_test_colloc_syll_wth_common': 'with common test', 't_nopfx_colloc_syll': 'split vocab no prefix', 'test_coll_syll': 'baseline test', 't_test_colloc_syll': 'split vocab test'} if OLDVERSION: DO_ONLY = {'t_nopfx_coll_syll_wth_common': 't_colloc_syll_wth_common_nopfx', 't_test_coll_syll_wth_common': 't_colloc_syll_wth_common_test', 't_nopfx_coll_syll': 't_colloc_syll_spl_vocab_nopfx', 'test_coll_syll': 'colloc_syll_test', 't_test_coll_syll': 't_colloc_syll_spl_vocab_test'} #DO_ONLY = {} # for cosmetics when preparing figures for papers # e.g. DO_ONLY = {'t_colloc': 'colloc with topics'} scores_order = "token_f-score token_precision token_recall boundary_f-score boundary_precision boundary_recall".split() results = defaultdict(lambda: [dict(zip(scores_order, [[] for i in range(len(scores_order))])) for tmp_i in range(N_MONTHS)]) if TAKE_MAX_SCORE: results = defaultdict(lambda: [dict(zip(scores_order, [0 for i in range(len(scores_order))])) for tmp_i in range(N_MONTHS)]) for month in xrange(SAGE, EAGE+1): for fname in glob.iglob(PREFIX+'naima_' + str(SAGE_XPS) + 'to' + str(month) + 'm/nai*-' + str(SAGE_XPS) + '-' + str(month) + '*.o*'): if TEST and (not "test" in fname and not "nopfx" in fname): continue elif not TEST and ("test" in fname or "nopfx" in fname): continue if "-sc" in fname and not "single-context" in TYPES: continue if "docs" in fname and not "topics" in TYPES: continue # always plots basic results currently doit = False with open (fname.replace(".o", ".e")) as f: line = "" for line in f: for iternumber in ITERS: striter = str(iternumber) if striter + " iterations" in line or "Iteration " + striter in line: doit = True break if not doit: print "NOT DOING:", fname else: print fname scores = [] s_dict = {} with open(fname) as f: last_lines = [] for line in f: last_lines.append(line) try: if TEST and LAST_ITERS > 1 and len(last_lines) > LAST_ITERS+1: for iter_to_take in range(1,LAST_ITERS+1): scores = [float(last_lines[-iter_to_take].split('\t')[i]) for i in range(6)] if not len(s_dict): s_dict = [dict(zip(scores_order, scores))] else: s_dict.append(dict(zip(scores_order, scores))) else: scores = [float(last_lines[-1].split('\t')[i]) for i in range(6)] s_dict = dict(zip(scores_order, scores)) except: print "PARSE ERROR: parse went wrongly for", fname fname = '/'.join(fname.split('/')[1:]) fname = fname.replace('coll-', 'colloc-') # old names if 'docs' in fname: condname = '_'.join(fname.split('/')[-1].split('-')[-1].split('.')[0].split('_')[2:]) if condname == '': # topics-based unigram condname = 'uni' condname = 'd_' + condname elif '-sc' in fname: fname = fname.replace('-sc', '') condname = 't' if '-r+' in fname or '-r.' in fname: condname = 't_readapt' fname = fname.replace('-r', '') if '-w+' in fname: fname = fname.replace('-w+', '_words_common') elif '-c+' in fname: fname = fname.replace('-c+', '_collocs_common') elif '+' in fname: fname = fname.replace('+', '_wth_common') condname = '_'.join([condname] + fname.split('/')[-1].split('-')[3:]).split('.')[0] else: condname = '_'.join(fname.split('/')[-1].split('-')[3:]).split('.')[0] ########## cosmetic (for legends) ########## if len(DO_ONLY): if condname in DO_ONLY: condname = DO_ONLY[condname] else: continue ########## /cosmetic (for legends) ########## if type(s_dict) == type({}) and len(s_dict) == 6: if TAKE_MAX_SCORE: if results[condname][month-SAGE]['token_f-score'] == 0 or s_dict['token_f-score'] > results[condname][month-SAGE]['token_f-score']: results[condname][month-SAGE] = s_dict else: for k, v in s_dict.iteritems(): results[condname][month-SAGE][k].append(v) elif type(s_dict) == type([]): for e in s_dict: for k, v in e.iteritems(): results[condname][month-SAGE][k].append(v) print results fig = plt.figure(figsize=(12, 9), dpi=1200) plt.xticks(xrange(N_MONTHS)) ax = plt.gca() ax.set_ylim([0.55, 0.90]) ax.set_xlim([-0.1, N_MONTHS - 0.9]) ax.set_xticklabels(map(str, range(SAGE, EAGE+1))) for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] + ax.get_xticklabels() + ax.get_yticklabels()): item.set_fontsize(24) for cond, a in results.iteritems(): linetype = '' if "syll" in cond: linetype = '^-.' else: linetype = 'v-.' if "d_" or "t_" in cond: linetype = linetype[0] + '--' vals = None stddevs = None if TAKE_MAX_SCORE: vals = [x['token_f-score'] for x in a] else: vals = [np.mean(x['token_f-score']) for x in a] stddevs = [FACTOR_STD*np.std(x['token_f-score']) for x in a] # TODO (gaussian process or some smoothing) plt.plot(map(lambda x: 'NaN' if x <= 0.0 else x, vals), linetype, linewidth=3.5, alpha=0.8) plt.xlabel('months') plt.ylabel('token f-score') plt.legend([l for l in results.iterkeys()], loc='best', ncol=4) plt.setp(ax.get_legend().get_texts(), fontsize=20) plt.savefig('progress_ages.png') matplotlib.rcParams.update({'font.size': 20}) matplotlib.rcParams.update({'text.color': "black"}) matplotlib.rcParams.update({'axes.labelcolor': "black"}) matplotlib.rcParams.update({'xtick.color': "black"}) matplotlib.rcParams.update({'ytick.color': "black"}) plotted_results = {} # plotted_results[month][cond][score_type] = mean for month in xrange(SAGE, EAGE+1): y_pos = [0.5] scores = [] stddevs = [] conds = [] s_dicts = [] for cond, a in results.iteritems(): score = 0 stddev = 0 if TAKE_MAX_SCORE: score = a[month-SAGE]['token_f-score'] else: score = np.mean(a[month-SAGE]['token_f-score']) stddev = FACTOR_STD*np.std(a[month-SAGE]['token_f-score']) if score > 0: y_pos.append(y_pos[-1] + 1) scores.append(score) stddevs.append(stddev) conds.append(cond) s_dicts.append({'token_f-score': score, 'token_precision': np.mean(a[month-SAGE]['token_precision']), 'token_recall': np.mean(a[month-SAGE]['token_recall']), 'boundary_f-score': np.mean(a[month-SAGE]['boundary_f-score']), 'boundary_precision': np.mean(a[month-SAGE]['boundary_precision']), 'boundary_recall': np.mean(a[month-SAGE]['boundary_recall'])}) plotted_results[month] = dict(zip(conds, s_dicts)) if len(conds) == 0: continue y_pos = y_pos[:-1] fig = plt.figure(figsize=(9, len(y_pos)), dpi=1200) ax = plt.gca() ax.set_ylim([0, len(y_pos)+1]) ax.set_xlim([0.6, 0.86]) if TEST: ax.set_xlim([0.7, 0.86]) tmp = () if TAKE_MAX_SCORE: tmp = zip(y_pos, scores, conds, ['g' for tmp_i in range(len(y_pos))]) if OLDVERSION: tmp = map(lambda (y, s, cond, color): (y, s, cond, 'b') if 't' == cond[0] or 'd' == cond[0] else (y, s, cond, color), tmp) else: tmp = map(lambda (y, s, cond, color): (y, s, cond, 'b') if 'b' != cond[0] or 'd' == cond[0] else (y, s, cond, color), tmp) # cond[0]=='b' for cond=='baseline' else: tmp = zip(y_pos, scores, stddevs, conds, ['g' for tmp_i in range(len(y_pos))]) if OLDVERSION: tmp = map(lambda (y, s, sd, cond, color): (y, s, sd, cond, 'b') if 't' == cond[0] or 'd' == cond[0] else (y, s, sd, cond, color), tmp) else: if TEST: tmp = map(lambda (y, s, sd, cond, color): (y, s, sd, cond, 'b') if 'no prefix' in cond else (y, s, sd, cond, color), tmp) # "no prefix" cond => different color tmp = map(lambda (y, s, sd, cond, color): (y, s, sd, cond, 'grey') if 'b' == cond[0] else (y, s, sd, cond, color), tmp) # cond[0]=='b' for cond=='baseline' else: tmp = map(lambda (y, s, sd, cond, color): (y, s, sd, cond, 'b') if 'b' != cond[0] else (y, s, sd, cond, color), tmp) # cond[0]=='b' for cond=='baseline' if SORTED: ys = map(lambda x: x[0], tmp) tmp = sorted(tmp, key=lambda x: x[1]) tmp = map(lambda y,t: sum(((y,), t[1:]), ()), ys, tmp) if TAKE_MAX_SCORE: y_pos, scores, conds, colors = zip(*tmp) plt.barh(y_pos, scores, color=colors, ecolor='r', alpha=0.8) else: y_pos, scores, stddev, conds, colors = zip(*tmp) plt.barh(y_pos, scores, xerr=stddev, color=colors, ecolor='r', alpha=0.8) plt.yticks(map(lambda x: x+0.5, y_pos), conds) plt.xlabel('token f-score') #plt.title('') plt.savefig('histogram_' + str(SAGE_XPS) + 'to' + str(month) + 'm.png', bbox_inches='tight') from pandas import DataFrame from copy import deepcopy import pandas as pd mydata = defaultdict(lambda: []) ages_max_points = [0 for i in xrange(SAGE, EAGE+1)] results_m = deepcopy(results) for cond, a in results_m.iteritems(): for i, x in enumerate(a): if len(x['token_f-score']) > ages_max_points[i]: ages_max_points[i] = len(x['token_f-score']) mydata[cond].append(x['token_f-score']) mydata['months'] = [[m for i in range(ages_max_points[m-SAGE])] for m in xrange(SAGE, EAGE+1)] #mydata['months'] = [[str(m) for i in range(ages_max_points[m-SAGE])] for m in xrange(SAGE, EAGE+1)] # TODO if we don't want the stat_smooth to know about X (months) for key, value in mydata.iteritems(): for i, l in enumerate(value): value[i] = l + [np.nan for j in range(ages_max_points[i] - len(l))] mydata[key] = [j for i in value for j in i] if np.all(map(np.isnan, mydata[key])): # remove data that is only nan mydata.pop(key) print mydata print ">>> conditions that will be plotted" print mydata.keys() mydataframe = DataFrame(mydata) my_lng = pd.melt(mydataframe[['months'] + [k for k in mydata.keys() if k != 'months']], id_vars='months') #my_lng = pd.melt(mydataframe[['months', 'share vocab', 'baseline', 'with common', 'split vocab']], id_vars='months') #my_lng = pd.melt(mydataframe[['months', 't_permuted_colloc_syll', 't_permuted_colloc_syll_wth_common', 'unigram', 't_unigram', 't_readapt_unigram', 'colloc_syll', 't_colloc_syll', 't_colloc_syll_wth_common']], id_vars='months') if OLDVERSION: my_lng = pd.melt(mydataframe[['months', 't_colloc_syll_shr_vocab', 'colloc_syll', 't_colloc_syll_wth_common', 't_colloc_syll_spl_vocab']], id_vars='months') # from ggplot_import_* # #p = ggplot(aes(x='months', y='colloc'), data=mydataframe) + geom_point(color='lightgreen') + stat_smooth(se=True) + xlab('age in months') + ylab('token f-score') # my_lng = pd.melt(mydataframe[['months', 't_colloc syll shr vocab', 'colloc syll', 't_colloc_syll_wth_common', 't_colloc_syll_spl_vocab', 'colloc', 'syll', 't_syll_spl_vocab']], id_vars='months') # #p = ggplot(aes(x='months', y='value', color='variable'), data=my_lng) + stat_smooth(se=True, method='lm', level=0.95) + xlab('age in months') + ylab('token f-score') # p = ggplot(aes(x='months', y='value', color='variable'), data=my_lng) + stat_smooth(se=False) + xlab('age in months') + ylab('token f-score') # ggsave(p, 'ggplot_progress.png') import rpy2.robjects as robj import rpy2.robjects.pandas2ri # for dataframe conversion from rpy2.robjects.packages import importr from rpy2.robjects import globalenv import pandas.rpy.common as com #grdevices = importr('grDevices') #robj.pandas2ri.activate() #data_r = robj.conversion.py2ri(mydata) lng_r = com.convert_to_r_dataframe(my_lng) data_r = com.convert_to_r_dataframe(mydataframe) globalenv['lng_r'] = lng_r globalenv['data_r'] = data_r globalenv['eage'] = EAGE globalenv['sage'] = SAGE print "===================" print "and now for the R part" print "===================" rstring = """ library("ggplot2") library("grid") #print(lng_r) #print(factor(lng_r$months)) #print(factor(lng_r$variable)) cLevels <- levels(lng_r$variable) p <- ggplot(data=lng_r, aes(x=months, y=value, group=variable, colour=variable, fill=variable, shape=variable, linetype=variable))\ + scale_y_continuous(name='token f-score')\ + scale_x_discrete('age in months', breaks=seq(eage,sage), labels=seq(eage,sage))\ + coord_cartesian(xlim = c(eage, sage))\ + theme_bw()\ + scale_colour_discrete("model", drop=TRUE, limits=cLevels)\ + scale_fill_discrete("model", drop=TRUE, limits=cLevels)\ + scale_shape_discrete("model", drop=TRUE, limits=cLevels)\ + scale_linetype_discrete("model", drop=TRUE, limits=cLevels)\ + stat_smooth(level=0.68, size=1.8)\ + theme(text = element_text(size=44))\ """ #+ geom_point()\ #+ xlab('age in months')\ #+ ylab('token f-score')\ #+ scale_x_continuous('age in months', breaks=seq(eage,sage), limits=c(eage,sage))\ # + scale_x_discrete('age in months') if len(DO_ONLY) and len(DO_ONLY) < 5: rstring += """+ opts(legend.position = c(0.96, 0.5), legend.justification = c(1, 0.5), legend.background = element_rect(colour = "grey70", fill = "white"), legend.text=element_text(size=44), legend.title=element_text(size=44), legend.key.size=unit(2, "cm"), plot.margin=unit(c(1,1,1,1), "cm")) """ else: rstring += """+ opts(legend.background = element_rect(colour = "grey70", fill = "white"), legend.text=element_text(size=44), legend.title=element_text(size=44), legend.key.size=unit(2, "cm"), plot.margin=unit(c(1,1,1,1), "cm")) """ rstring += """ ggsave('ggplot2_progress.pdf', plot=p, width=22, height=16) """ plotFunc_2 = robj.r(rstring) print "===================" print "and now for the LaTeX tables" print "===================" header_table = """ \\begin{table*}[ht] \caption{Mean f-scores (f), precisions (p), and recalls (r) for different models depending on the size of dataset} \\vspace{-0.5cm} \\begin{center} \\begin{scriptsize} \\begin{tabular}{|c|ccc|ccc|ccc|ccc|ccc|ccc|ccc|ccc|} \hline & \multicolumn{3}{|c|}{syll} & \multicolumn{3}{|c|}{t\_syll} & \multicolumn{3}{|c|}{colloc} & \multicolumn{3}{|c|}{t\_coll\_wth\_common} & \multicolumn{3}{|c|}{coll\_syll} & \multicolumn{3}{|c|}{t\_coll\_syll\_shr\_voc} & \multicolumn{3}{|c|}{t\_coll\_syll\_spl\_voc} & \multicolumn{3}{|c|}{t\_coll\_syll\_wth\_com}\\\\ """ print header_table for typ in ['token', 'boundary']: print typ + """ & f & p & r & f & p & r & f & p & r & f & p & r & f & p & r & f & p & r & f & p & r & f & p & r \\\\ \hline """ for month, d in plotted_results.iteritems(): print str(SAGE_XPS) + "-" + str(month), if OLDVERSION: listmodels = ['syll', 't_syll_spl_vocab', 'colloc', 't_colloc_wth_common', 'colloc_syll', 't_colloc_syll_shr_vocab', 't_colloc_syll_spl_vocab', 't_colloc_syll_wth_common'] listmodels = ['unigram', 'unigram share vocab', 'unigram split vocab', 'baseline', 'share vocab', 'split vocab', 'with common'] for cond in listmodels: s_dict = d[cond] f = s_dict[typ+'_f-score'] p = s_dict[typ+'_precision'] r = s_dict[typ+'_recall'] print " & ", print "%.3f" % f, print " & ", print "%.3f" % p, print " & ", print "%.3f" % r, print "\\\\" print "\hline" footer_table = """ \end{tabular} \label{results} \end{scriptsize} \end{center} \end{table*} """ print footer_table
2.078125
2
supports/pyload/src/pyload/plugins/accounts/LinkifierCom.py
LuckyNicky/pycrawler
1
12790102
# -*- coding: utf-8 -*- import hashlib import json import pycurl from ..base.multi_account import MultiAccount class LinkifierCom(MultiAccount): __name__ = "LinkifierCom" __type__ = "account" __version__ = "0.01" __status__ = "testing" __pyload_version__ = "0.5" __description__ = """Linkifier.com account plugin""" __license__ = "GPLv3" __authors__ = [("GammaC0de", "nitzo2001[AT]yahoo[DOT]com")] __config__ = [ ("mh_mode", "all;listed;unlisted", "Filter hosters to use", "all"), ("mh_list", "str", "Hoster list (comma separated)", ""), ("mh_interval", "int", "Reload interval in hours", 12), ] API_KEY = "<KEY>" API_URL = "https://api.linkifier.com/downloadapi.svc/" def api_response(self, method, user, password, **kwargs): post = { "login": user, "md5Pass": hashlib.md5(password.encode()).hexdigest(), "apiKey": self.API_KEY, } post.update(kwargs) self.req.http.c.setopt( pycurl.HTTPHEADER, ["Content-Type: application/json; charset=utf-8"] ) res = json.loads(self.load(self.API_URL + method, post=json.dumps(post))) self.req.http.c.setopt( pycurl.HTTPHEADER, ["Content-Type: text/html; charset=utf-8"] ) return res def grab_hosters(self, user, password, data): json_data = self.api_response("hosters", user, password) if json_data["hasErrors"]: self.log_warning(json_data["ErrorMSG"] or "Unknown error") return [] return [ x["hostername"] for x in json_data["hosters"] if x["hostername"] and x["isActive"] ] def grab_info(self, user, password, data): json_data = self.api_response("user", user, password) trafficleft = json_data["extraTraffic"] validuntil = float(json_data["expirydate"]) // 1000 return { "validuntil": validuntil, "trafficleft": -1 if trafficleft.lower() == "unlimited" else int(trafficleft), "premium": True, } def signin(self, user, password, data): json_data = self.api_response("user", user, password) if json_data.get("hasErrors", True) or not json_data.get("isActive", True): self.log_warning(json_data["ErrorMSG"] or "Unknown error") self.fail_login()
2.0625
2
temp.py
Hrishabh-B/Basic_codes
0
12790103
#This code is written for dynamic step-size. step size c0 gets smaller when it achieves the number 200. #Author: <NAME>, Senior Research Fellow, University of Delhi #Date: 5-07-2021 from math import * import numpy as np c0=50.0 for x in np.arange(c0,580,10): t=10*(abs(200.1-c0)/200.1)*abs(np.log(0.3/abs(c0-200.1))) y=1.0/(c0-200.0**2)**2 print(str(c0)+" "+str(y)) c0+=t if c0> 198 and c0<202: c0+=1
3.203125
3
src/OTLMOW/OTLModel/Classes/Grasland.py
davidvlaminck/OTLClassPython
2
12790104
<gh_stars>1-10 # coding=utf-8 from OTLMOW.OTLModel.BaseClasses.OTLAttribuut import OTLAttribuut from OTLMOW.OTLModel.Classes.GrazigeVegetatie import GrazigeVegetatie from OTLMOW.OTLModel.Datatypes.KlNSB import KlNSB from OTLMOW.GeometrieArtefact.VlakGeometrie import VlakGeometrie # Generated with OTLClassCreator. To modify: extend, do not edit class Grasland(GrazigeVegetatie, VlakGeometrie): """Grazige vegetatie met daarin kruidachtigen die jaarlijks één of meerdere malen per jaar gemaaid of begraasd wordt.""" typeURI = 'https://wegenenverkeer.data.vlaanderen.be/ns/onderdeel#Grasland' """De URI van het object volgens https://www.w3.org/2001/XMLSchema#anyURI.""" def __init__(self): GrazigeVegetatie.__init__(self) VlakGeometrie.__init__(self) self._natuurstreefbeeld = OTLAttribuut(field=KlNSB, naam='natuurstreefbeeld', label='natuurstreefbeeld', objectUri='https://wegenenverkeer.data.vlaanderen.be/ns/onderdeel#Grasland.natuurstreefbeeld', definition='Een natuurstreefbeeld is een nagestreefd biotoop, mozaïek van biotopen of een leefgebied van een soort dat je wil behouden of verkrijgen via een goed natuurbeheer.In het definitief plan van type twee, drie of vier wordt het ecologisch einddoel vastgesteld aan de hand van natuurstreefbeelden.', owner=self) @property def natuurstreefbeeld(self): """Een natuurstreefbeeld is een nagestreefd biotoop, mozaïek van biotopen of een leefgebied van een soort dat je wil behouden of verkrijgen via een goed natuurbeheer. In het definitief plan van type twee, drie of vier wordt het ecologisch einddoel vastgesteld aan de hand van natuurstreefbeelden.""" return self._natuurstreefbeeld.get_waarde() @natuurstreefbeeld.setter def natuurstreefbeeld(self, value): self._natuurstreefbeeld.set_waarde(value, owner=self)
2.015625
2
build_html/preprocess_xml.py
DCCouncil/dc-law-tools
3
12790105
<reponame>DCCouncil/dc-law-tools import lxml.etree as et from .preprocessors import preprocessors from .preprocessors.utils import index_docs import os DIR = os.path.abspath(os.path.dirname(__file__)) out_dir = os.path.join(DIR, '../../dc-law-html') bld_file = os.path.join(DIR, '../working_files/dccode-html-bld.xml') def preprocess_xml(): print('preprocessing...') parser = et.XMLParser(remove_blank_text=True) with open(bld_file) as f: dom = et.parse(f, parser) index_docs(dom) for preprocessor in preprocessors: preprocess(dom, *preprocessor) with open(bld_file, 'wb') as f: f.write(et.tostring(dom, pretty_print=True, encoding="utf-8")) def preprocess(dom, xpath, *preprocessors): roots = dom.xpath(xpath) if not roots: raise BaseException('no valid roots for xpath:', xpath) for root in roots: for preprocessor in preprocessors: preprocessor(root) def pdfs(dom): pdf_dir = os.path.join(DIR, 'dc_laws') pdf_out_path = os.path.join(DIR, '../../dc-law-docs-laws/{}.pdf') pdfs = os.listdir(pdf_dir) law_root = dom.find('//collection[@name="dclaws"]') skip_laws = law_root.xpath('./collection/document[cites/law/@url]/num/text()') for pdf in pdfs: if not pdf.startswith('dc-law-docs-laws'): print('skipping', pdf) continue pdf_path = os.path.join(pdf_dir, pdf) law_num = pdf.replace('dc-law-docs-laws', '')[:-4] if law_num in skip_laws: continue os.rename(pdf_path, pdf_out_path.format(law_num)) import ipdb ipdb.set_trace()
2.421875
2
code/config.py
SimonSuster/rc-cnn-dailymail
325
12790106
import theano import argparse _floatX = theano.config.floatX def str2bool(v): return v.lower() in ('yes', 'true', 't', '1', 'y') def get_args(): parser = argparse.ArgumentParser() parser.register('type', 'bool', str2bool) # Basics parser.add_argument('--debug', type='bool', default=False, help='whether it is debug mode') parser.add_argument('--test_only', type='bool', default=False, help='test_only: no need to run training process') parser.add_argument('--random_seed', type=int, default=1013, help='Random seed') # Data file parser.add_argument('--train_file', type=str, default=None, help='Training file') parser.add_argument('--dev_file', type=str, default=None, help='Development file') parser.add_argument('--pre_trained', type=str, default=None, help='Pre-trained model.') parser.add_argument('--model_file', type=str, default='model.pkl.gz', help='Model file to save') parser.add_argument('--log_file', type=str, default=None, help='Log file') parser.add_argument('--embedding_file', type=str, default=None, help='Word embedding file') parser.add_argument('--max_dev', type=int, default=None, help='Maximum number of dev examples to evaluate on') parser.add_argument('--relabeling', type='bool', default=True, help='Whether to relabel the entities when loading the data') # Model details parser.add_argument('--embedding_size', type=int, default=None, help='Default embedding size if embedding_file is not given') parser.add_argument('--hidden_size', type=int, default=128, help='Hidden size of RNN units') parser.add_argument('--bidir', type='bool', default=True, help='bidir: whether to use a bidirectional RNN') parser.add_argument('--num_layers', type=int, default=1, help='Number of RNN layers') parser.add_argument('--rnn_type', type=str, default='gru', help='RNN type: lstm or gru (default)') parser.add_argument('--att_func', type=str, default='bilinear', help='Attention function: bilinear (default) or mlp or avg or last or dot') # Optimization details parser.add_argument('--batch_size', type=int, default=32, help='Batch size') parser.add_argument('--num_epoches', type=int, default=100, help='Number of epoches') parser.add_argument('--eval_iter', type=int, default=100, help='Evaluation on dev set after K updates') parser.add_argument('--dropout_rate', type=float, default=0.2, help='Dropout rate') parser.add_argument('--optimizer', type=str, default='sgd', help='Optimizer: sgd (default) or adam or rmsprop') parser.add_argument('--learning_rate', '-lr', type=float, default=0.1, help='Learning rate for SGD') parser.add_argument('--grad_clipping', type=float, default=10.0, help='Gradient clipping') return parser.parse_args()
2.4375
2
modules/evaluation.py
hrayrhar/limit-label-memorization
37
12790107
<reponame>hrayrhar/limit-label-memorization from tqdm import tqdm import numpy as np def compute_accuracy_with_bootstrapping(pred, target, n_iters=1000): """ Expects numpy arrays. pred should have shape (n_samples, n_classes), while target should have shape (n_samples,). """ assert pred.shape[0] == target.shape[0] all_accuracies = [] for _ in tqdm(range(n_iters), desc='bootstrapping') : indices = np.random.choice(pred.shape[0], size=pred.shape[0], replace=True) cur_pred = pred[indices] cur_target = target[indices] cur_accuracy = np.mean((cur_pred.argmax(axis=1) == cur_target).astype(np.float)) all_accuracies.append(cur_accuracy) return { 'mean': np.mean(all_accuracies), 'std': np.std(all_accuracies) }
2.90625
3
hmm_for_baxter_using_only_success_trials/anomaly_identification.py
HongminWu/HMM
3
12790108
<reponame>HongminWu/HMM #!/usr/bin/env python import os import numpy as np from sklearn.externals import joblib from matplotlib import pyplot as plt import util import training_config import pandas as pd import random import ipdb def run(anomaly_data_path_for_testing, model_save_path, figure_save_path,): ''' 1. load all the anomalous trained models 2. load testing anomaly data 3. plot the log-likelihood wrt each model and plot in a same figure ''' # load trained anomaly models anomaly_model_group_by_label = {} folders = os.listdir(training_config.anomaly_model_save_path) for fo in folders: path = os.path.join(training_config.anomaly_data_path, fo) if not os.path.isdir(path): continue anomaly_model_path = os.path.join(training_config.anomaly_model_save_path, fo, training_config.config_by_user['data_type_chosen'], training_config.config_by_user['model_type_chosen'], training_config.model_id) try: anomaly_model_group_by_label[fo] = joblib.load(anomaly_model_path + "/model_s%s.pkl"%(1,)) except IOError: print 'anomaly model of %s not found'%(fo,) continue # one-folder confuse_matrix = {} folders = os.listdir(anomaly_data_path_for_testing) for fo in folders: predict_class = [] data_path = os.path.join(anomaly_data_path_for_testing, fo) if not os.path.isdir(path): continue anomaly_testing_group_by_folder_name = util.get_anomaly_data_for_labelled_case(training_config, data_path) # one-file for trial_name in anomaly_testing_group_by_folder_name: ''' #plot fig = plt.figure() ax = fig.add_subplot(111) from matplotlib.pyplot import cm color = iter(cm.rainbow(np.linspace(0, 1, len(anomaly_model_group_by_label)))) ''' calc_cofidence_resourse = [] for model_label in anomaly_model_group_by_label: one_log_curve_of_this_model = util.fast_log_curve_calculation( anomaly_testing_group_by_folder_name[trial_name][1], anomaly_model_group_by_label[model_label]) # one_predict_proba_of_this_state = anomaly_model_group_by_label[model_label].predict_proba(anomaly_testing_group_by_folder_name[trial_name][1]) # HDPHSMM haven't implemented this # one_hidden_stateSeq_of_this_state = anomaly_model_group_by_label[model_label].decode(anomaly_testing_group_by_folder_name[trial_name][1],len(anomaly_testing_group_by_folder_name[trial_name][1])-1) calc_cofidence_resourse.append({ 'model_label' : model_label, 'culmulative_loglik': one_log_curve_of_this_model[-1], 'loglik_curve' : one_log_curve_of_this_model, # 'predict_proba' : one_predict_proba_of_this_state, # 'hidden_stateSeq' : one_hidden_stateSeq_of_this_state }) ''' #--plot c = next(color) plot_line, = ax.plot(one_log_curve_of_this_model, linestyle="solid", color = c) plot_line.set_label(model_label) title = ('Anomaly_identification for ' + fo) ax.set_title(title) ''' sorted_list = sorted(calc_cofidence_resourse, key=lambda x:x['culmulative_loglik']) # from small to large optimal_result = sorted_list[-1] classified_model = optimal_result['model_label'] predict_class.append(classified_model) all_log_curves_of_this_state, threshold, confidence = get_confidence_of_identification(optimal_result) ''' if confidence < 0.0: df = pd.DataFrame(anomaly_testing_group_by_folder_name[trial_name][1], columns=training_config.interested_data_fields) id = random.randint(1000,10000) _name = 'unknown_anomaly_' + str(id) unknown_anomaly_path = os.path.join(training_config.anomaly_data_path, _name) os.makedirs(unknown_anomaly_path) print 'generated a new anomaly:' + _name print '*\n'*5 print 'synthetic data generation' import generate_synthetic_data generate_synthetic_data.run_finite_differece_matrix(df=df, num_data = 5, csv_save_path=unknown_anomaly_path, trial_name) ''' #--plot ''' for no_trial in range(len(all_log_curves_of_this_state)): ax.plot(all_log_curves_of_this_state[no_trial], linestyle= '--', color = 'gray', label = 'trials') ax.plot(threshold.tolist()[0], linestyle='--', color='gold', label='threshold') ax.legend(loc='upper left') ax.text(20,optimal_result['culmulative_loglik']/2, optimal_result['model_label'] + ': ' + str(confidence), ha = 'center', va = 'baseline', bbox=dict(boxstyle="round", ec=(1., 0.6, 0.6), fc=(1., 0.9, 0.9),) ) if not os.path.isdir(figure_save_path + '/anomaly_identification_plot'): os.makedirs(figure_save_path + '/anomaly_identification_plot') fig.savefig(os.path.join(figure_save_path, 'anomaly_identification_plot', fo + ":" + trial_name + ".jpg"), format="jpg") # fig.show(1) # raw_input('testing another trial?? Please any key to continue') ''' print 'Finish testing: '+ fo + '\n' confuse_matrix[fo] = predict_class _items = confuse_matrix.keys() _matrix = np.identity(len(_items)) for row in _items: for col in _items: r = _items.index(row) c = _items.index(col) _matrix[r, c] = confuse_matrix[row].count(col) print 'print the confusion matrix...' print _items print _matrix def get_confidence_of_identification(optimal_result): confidence_metric = ['culmulative_loglik_divide_by_the_culmulative_mean_loglik', 'posterior_of_gmm_model', 'calc_kullback_leibler_divergence_of_predict_proba', 'hamming_distance_of_hidden_state_sequence', ] CONF_TYPE = confidence_metric[0] anomaly_model_path = os.path.join(training_config.anomaly_model_save_path, optimal_result['model_label'], training_config.config_by_user['data_type_chosen'], training_config.config_by_user['model_type_chosen'], training_config.model_id) if CONF_TYPE == 'culmulative_loglik_divide_by_the_culmulative_mean_loglik': c_value = 5 all_log_curves_of_this_state = joblib.load(os.path.join(anomaly_model_path, 'all_log_curves_of_this_state.pkl')) std_of_log_likelihood = joblib.load(os.path.join(anomaly_model_path, 'std_of_log_likelihood.pkl')) np_matrix_traj_by_time = np.matrix(all_log_curves_of_this_state) mean_of_log_curve = np_matrix_traj_by_time.mean(0) threshold = mean_of_log_curve - std_of_log_likelihood[1] confidence = optimal_result['culmulative_loglik'] - threshold.tolist()[0][-1] return all_log_curves_of_this_state, threshold, confidence elif CONF_TYPE == 'posterior_of_gmm_model': #load -> build a hmm model -> calculate the probability of testing sequence all_log_curves_of_this_state = joblib.load(os.path.join(anomaly_model_path, 'all_log_curves_of_this_state.pkl')) data = np.ndarray([]) for icurve in range(len(all_log_curves_of_this_state)): tVal = range(len(all_log_curves_of_this_state[icurve])) feature = all_log_curves_of_this_state[icurve] data_points = np.vstack([np.array(tVal), feature]).T if icurve == 0: data = data_points else: data = np.vstack([data, data_points]) # fit a gmm model from sklearn import mixture gmm = mixture.GaussianMixture(n_components = 5, covariance_type = 'diag').fit(data) tVal = range(optimal_result['loglik_curve'].shape[0]) testing_data = np.vstack([np.array(tVal), optimal_result['loglik_curve']]).T confidence = gmm.score(testing_data) return all_log_curves_of_this_state, None, confidence elif CONF_TYPE == 'calc_kullback_leibler_divergence_of_predict_proba': print 'obsoleted' pass from scipy.stats import entropy # average_predict_proba average_predict_proba = joblib.load(os.path.join(anomaly_model_path, 'average_predict_proba.pkl')) testing_predict_proba = optimal_result['predict_proba'] confidence = 0.0 for iObs in range(len(testing_predict_proba)): confidence += entropy(testing_predict_proba[iObs,:], average_predict_proba[1][iObs,:]) return None, None, confidence elif CONF_TYPE == 'hamming_distance_of_hidden_state_sequence': # hidden_state_sequence_of_training_trials hidden_stateSeq = joblib.load(os.path.join(anomaly_model_path, 'hidden_stateSeq.pkl')) hidden_stateSeq = np.append(hidden_stateSeq, [hidden_stateSeq[-1]]) # add one item, because for autoregressive model, I had deleted one data point totalLen = len(hidden_stateSeq) testing_stateSeq = optimal_result['hidden_stateSeq'] testing_stateSeq = np.append(testing_stateSeq, [testing_stateSeq[-1]]) tLen = len(testing_stateSeq) hidden_stateSeq = hidden_stateSeq.reshape(totalLen/tLen, tLen) from scipy.spatial.distance import hamming confidence = 0 for iTrial in range(totalLen/tLen): confidence += hamming(testing_stateSeq, hidden_stateSeq[iTrial,:]) return None, None, confidence else: print ("without the confidence_metric as: " + CONF_TYPE) pass
2.390625
2
matador/orm/__init__.py
dquigley-warwick/matador
24
12790109
<filename>matador/orm/__init__.py # coding: utf-8 # Distributed under the terms of the MIT License. __all__ = ["DataContainer"] __author__ = '<NAME>' __maintainer__ = '<NAME>' from .orm import DataContainer
1.265625
1
lib/Model.py
calumcorrie/Meraki-Crowd-Interface
0
12790110
<reponame>calumcorrie/Meraki-Crowd-Interface<gh_stars>0 import os import sys import numpy as np from PIL import Image, ImageFilter import bz2 import pickle import datetime import requests import hashlib parentddir = os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)) sys.path.append(parentddir) from lib.APIQuery import APIQuery, FloorPlan from lib.BoundaryDetector import BoundaryDetector # As per Scanning API v3 SECRET_K = "secret" class Floor: "Wrapper class for the floorplan object including model data" def __init__(self,floorplan:FloorPlan): self.floorplan = floorplan # Dimentions should default to (height, width) self.floorplan_dimensions = (self.floorplan.height,self.floorplan.width) self.overlay_dimensions = ( int(self.floorplan_dimensions[0]//Model.CELL_SIZE_M)+1, int(self.floorplan_dimensions[1]//Model.CELL_SIZE_M)+1 ) # Determine the distance between the end of the floorplan and the data overlay, in metres and px self.margin_m = ( Model.CELL_SIZE_M - (self.floorplan_dimensions[0] % Model.CELL_SIZE_M), Model.CELL_SIZE_M - (self.floorplan_dimensions[1] % Model.CELL_SIZE_M) ) self.margin_px = ( self.margin_m[0] * self.floorplan.px_per_m_h, self.margin_m[1] * self.floorplan.px_per_m_w ) self.mask_enabled = False self.pixelmask = None self.mask = np.ones(self.overlay_dimensions,dtype=np.bool_) self.aps = {} self.bm_boxes = [] def set_bounds_mask(self,blindspots=None,wallthreshold:float=None) -> None: """" Generate a mask from BoundaryDetector for areas of the floor that people cannot possibly be or are to be ignored eg outside high floors. Blindspots should be a Numpy array, tuple or nested list of the form [[x1,x2,y1,y2],...] """ self.bm_boxes = blindspots if wallthreshold == None: bd = BoundaryDetector( self.floorplan.get_image() ) else: # pragma: no cover # Not covered as only parameter passing bd = BoundaryDetector( self.floorplan.get_image(), threshold=wallthreshold ) if blindspots != None: for spot in blindspots: bd.add_blindspot(*tuple(spot)) bd.run() self.pixelmask = bd.getBoundaryMask() #Downsample from pixel level to mask level #Assuming cell >> pixel #Mask (1msq-scale, small-dims) dims mx = self.mask.shape[0] my = self.mask.shape[1] #Image-scale pixel mask (mini-scale, big-dims) dims ix = self.pixelmask.shape[0] iy = self.pixelmask.shape[1] #Image-scale chunk divisions (what coords do we get laying one mask over the other) # Account for margin between edge of floorplan and overlay ix_divs = np.floor(np.linspace( 0, ix+self.margin_px[0], mx+1 )).astype("int32") iy_divs = np.floor(np.linspace( 0, iy+self.margin_px[1], my+1 )).astype("int32") for x in range(mx): #Top, bottom it = ix_divs[x] ib = ix_divs[x+1] for y in range(my): #Left, right il = iy_divs[y] ir = iy_divs[y+1] # As array is binary, mean gives ratio of elems 1 to elems total self.mask[x][y] = self.pixelmask[it:ib,il:ir].mean() < Model.DOWNSAMPLE_THRESHOLD def calc_bounds_mask(self,blindspots=None,wallthreshold:float=None) -> Image.Image: """ Generate a preview of a bounds mask with given parameters. For more info see Floor.set_bounds_mask """ if wallthreshold == None: bd = BoundaryDetector( self.floorplan.get_image() ) else: # pragma: no cover # Not covered as only parameter passing bd = BoundaryDetector( self.floorplan.get_image(), threshold=wallthreshold ) if blindspots != None: for spot in blindspots: bd.add_blindspot(*tuple(spot)) bd.run() return bd.generate_graphic() def render_overlay(self,overlay:np.ndarray,pixelmask:bool=True): """ Render overlay onto the floorplan image in heatmap form. If pixelmask and image has bounds mask set, will mask final image to keep overlay heatmap within bounds. """ POS = np.array([255,0,0,180],dtype=np.uint8) NEG = np.array([0,255,0,180],dtype=np.uint8) BLUR_CELLS = 0.35 destination = self.floorplan.get_image().convert("RGBA") # Overlay scaling absmax = max(overlay.max(), overlay.min(), key=abs) #m_max, m_min = absmax, -absmax imarr = np.zeros((destination.size[1],destination.size[0],4),dtype="uint8") # Account for margin between edge of floorplan and overlay ix_points = np.floor(np.linspace( 0, imarr.shape[0] + self.margin_px[0], overlay.shape[0] + 1 )).astype("int32") iy_points = np.floor(np.linspace( 0,imarr.shape[1] + self.margin_px[1], overlay.shape[1] + 1 )).astype("int32") for mx in range(overlay.shape[0]): # Top, bottom ixs = ix_points[mx] ixe = ix_points[mx+1] for my in range(overlay.shape[1]): val = overlay[mx,my] if val==0: continue #Colour by sign, scale alpha by magnitude pos = val > 0 alpha = abs(val / absmax) #Left, right iys = iy_points[my] iye = iy_points[my+1] imarr[ixs:ixe,iys:iye] = POS if pos else NEG imarr[ixs:ixe,iys:iye,3] = ( imarr[ixs:ixe,iys:iye,3].astype(np.float64) * alpha ).astype(np.uint8) imarr = Image.fromarray(imarr,"RGBA").filter( ImageFilter.BoxBlur( BLUR_CELLS * destination.size[0] / overlay.shape[1] ) ) if isinstance(self.pixelmask, np.ndarray) and pixelmask: # Tidy the edges # Make the mask an Image, mode=L mask = Image.fromarray(255*self.pixelmask.astype(np.uint8),"L") # Paste alpha on masked region imarr.paste((0,0,0,0),mask) elif pixelmask: print("Error: Could not filter by pixel mask as no mask exists") destination.putalpha(255) return Image.alpha_composite(destination,imarr) class Layer: "Class representing a data layer: a series of overlays covering all floorplans with data from a single source type" def __init__(self,floorplans:dict,exposure:int): self.exposure = exposure self.overlays = { _id : Overlay(_id, floor.overlay_dimensions, floor.floorplan_dimensions, floor.mask, exposure) for _id,floor in floorplans.items() } def set_observations(self,observations:dict): "Set the layer to contain passed observations, clearing any previous. Pass floor object dictionary" bins = { id : dict() for id in self.overlays.keys() } for id, placeable in observations.items(): bins[placeable.floorPlanId][id] = placeable for fid, overlay in self.overlays.items(): overlay.roll() obs = bins.get(fid) if obs != None: overlay.add(obs) def get_deltas(self, masked:bool=True, exposure:int=0) -> dict: """ Return the delta data for each overlay in the layer. If exposure 0 (default), will provide all available exposures squashed. For more info, see Overlay.get_delta """ return { _id : over.get_delta(masked, exposure) for _id, over in self.overlays.items() } def get_full(self, masked:bool=True, exposure:int=0) -> dict: #pragma: no cover """ Return the full data for each overlay in the layer. If exposure 0 (default), will provide all available exposures squashed. See Overlay.get_full """ # Not covered as not required for current scope return { _id : over.get_full(masked, exposure) for _id, over in self.overlays.items() } def copy(self,flatten:bool=True): """ Return a copy of the layer. Flatten squashes exposures into 1 frame For more info, see Overlay.copy() """ ly = Layer({}, 1 if flatten else self.exposure ) ly.overlays = { _id : over.copy(flatten) for _id, over in self.overlays.items() } return ly def clear(self)->None: "Clear all member overlays of observation data" for over in self.overlays.values(): over.clear() def verify_and_update(self, floorplans:dict): """ Ensure overlays are compatible with current floorplans (Floor objects). Throws ModelException in case of dimention mismatch. If mask is outdated, update - note this does not effect existing data, only new observations If an overlay missing, print info, create new If an overlay is extra, do nothing """ for fpid in set(floorplans).difference(self.overlays.keys()): # A floorplan not represented in the floorplans but not in the overlays print("Info: Creating new overlay for FPID:{}".format(fpid)) fp = floorplans[fpid] self.overlays[fpid] = Overlay(fpid, fp.overlay_dimensions, fp.floorplan_dimensions, fp.mask, self.exposure) for fpid, floor in floorplans.items(): self.overlays[fpid].verify_and_update(floor) class Overlay: "Represents an data overlay of a single floorplan" def __init__(self, floorid:str, overlay_dimensions:tuple, real_dimensions:tuple, floormask:np.ndarray, exposure:int): self.floorid = floorid #self.observations = dict() self.overlay_dimensions = overlay_dimensions self.real_dimensions = real_dimensions self.mask = floormask assert exposure > 0 self.exposure = exposure # Exposure queue, shape (exp,x,y) self.__unfixed_observations = np.zeros(exposure) self.__masked_dataoverlay = np.zeros( (exposure,)+overlay_dimensions, dtype="float32" ) self.__unmasked_dataoverlay = np.zeros( (exposure,)+overlay_dimensions, dtype="float32" ) def set(self, unfixed_count:np.ndarray, masked_overlay:np.ndarray, unmasked_overlay:np.ndarray): "Sets internal observation data. Not for general use, instead use Overlay.add" assert len(self.__unfixed_observations.shape) == len(unfixed_count.shape) assert len(self.__masked_dataoverlay.shape) == len(masked_overlay.shape) assert len(self.__unmasked_dataoverlay.shape) == len(unmasked_overlay.shape) self.__unfixed_observations = unfixed_count self.__masked_dataoverlay = masked_overlay self.__unmasked_dataoverlay = unmasked_overlay def roll(self) -> None: "Roll the exposure, preparing for a new frame of data" self.__masked_dataoverlay = np.roll(self.__masked_dataoverlay, 1, axis=0) self.__unmasked_dataoverlay = np.roll(self.__unmasked_dataoverlay, 1, axis=0) self.__unfixed_observations = np.roll(self.__unfixed_observations, 1, axis=0) self.__masked_dataoverlay[0] = 0 self.__unmasked_dataoverlay[0] = 0 self.__unfixed_observations[0] = 0 def clear(self) -> None: "Clear accumulated observation data including exposure" self.__unfixed_observations[:] = 0 self.__masked_dataoverlay[:] = 0 self.__unmasked_dataoverlay[:] = 0 def copy(self,flatten:bool=False): """ Return a copy of the overlay. If flatten, squash (mean) exposure window into 1 frame. """ if flatten: cp = Overlay(self.floorid, self.overlay_dimensions, self.real_dimensions, self.mask, 1) cp.__unfixed_observations[0] = self.__unfixed_observations.mean(axis=0) cp.__masked_dataoverlay[0] = self.__masked_dataoverlay.mean(axis=0) cp.__unmasked_dataoverlay[0] = self.__unmasked_dataoverlay.mean(axis=0) else: cp = Overlay(self.floorid, self.overlay_dimensions, self.real_dimensions, self.mask, self.exposure) cp.__unfixed_observations = self.__unfixed_observations.copy() cp.__masked_dataoverlay = self.__masked_dataoverlay.copy() cp.__unmasked_dataoverlay = self.__unmasked_dataoverlay.copy() return cp def add(self,observations:dict) -> None: fixed = {} unfixed = {} for id, placeable in observations.items(): if ( placeable.x != None and placeable.y != None ) or placeable.has_mask_override: fixed[id] = placeable else: unfixed[id] = placeable self.__add_fixed_locations(fixed) self.__add_unfixed_locations(unfixed) def __add_fixed_locations(self,fixed:dict) -> None: for placeable in fixed.values(): # We store both a copy of the m(asked)_possible locations and the u(n)m(asked)_possible locations um_possible = np.zeros(self.overlay_dimensions, dtype=np.bool_) if placeable.has_mask_override: # Even if a floorplan mask is in place, mask override takes precident um_possible = placeable.mask_override m_possible = placeable.mask_override else: if placeable.variance < Model.VARIANCE_THRESHOLD: # Calculated minimum reach # Account for change of axis um_possible[-int(placeable.y/Model.CELL_SIZE_M),int(placeable.x/Model.CELL_SIZE_M)] = 1 else: # Store parsed location in x,y tuple, in m, with change of axis client_loc = np.array( [self.real_dimensions[0] - placeable.y, placeable.x ] ) for x in range(um_possible.shape[0]): for y in range(um_possible.shape[1]): # For each square, see if it's centre is close enough to be within variance metres d = np.linalg.norm( (np.array([x,y]) + 0.5) * Model.CELL_SIZE_M - client_loc ) um_possible[x,y] = d <= placeable.variance # m(asked)_possible is a copy of the u(n)m(asked)_possible's with the floor mask applied m_possible = np.logical_and( um_possible, self.mask, dtype=np.bool_ ) # If theres a DIV0 here, the search hasn't found any near enough to call near # Ignore floor mask self.__unmasked_dataoverlay[0][um_possible] += 1.0 / um_possible.sum() # Include floor mask self.__masked_dataoverlay[0][m_possible] += 1.0 / m_possible.sum() def __add_unfixed_locations(self,unfixed:dict) -> None: self.__unfixed_observations[0] += len(unfixed) def get_delta(self, masked:bool=True, exposure:int=0)->np.ndarray: """ Returns a copy of the delta overlay (only fixed observations). If masked, will select data masked at input, else unmasked data. Set exposure to specify mean smoothing on the first n frames of stored exposure, default (0) combines all available frames, 1 gives only the latest frame (no smoothing). """ window = self.exposure if exposure == 0 else exposure if masked: return self.__masked_dataoverlay[:window].mean(axis=0) else: return self.__unmasked_dataoverlay[:window].mean(axis=0) def get_unfixed_observations(self, exposure:int=0)->float: """ Return how many unfixed observations were passed. For more details on exposure, see Overlay.get_delta """ window = self.exposure if exposure == 0 else exposure return self.__unfixed_observations[:window].mean(axis=0) def get_full(self, masked:bool=True, exposure:int=0)->np.ndarray: #pragma: no cover """ Returns a copy of the full client overlay (including distributed unfixed observations) For exposure, see Overlay.get_delta """ data = self.get_delta(masked,exposure) window = self.exposure if exposure == 0 else exposure # Distribute unfixed observations evenly across the floorplan (or mask) mask = self.mask if masked else np.ones(self.overlay_dimensions,dtype=np.bool_) data[mask] += self.__unfixed_observations[:window].mean(axis=0) / mask.sum() return data def verify_and_update(self,floor:Floor)->None: "Verifies overlay is compatible with passed floor, updates mask" if self.overlay_dimensions != floor.overlay_dimensions or self.real_dimensions != floor.floorplan_dimensions: raise Model.ModelException("Error: Overlay and Floorplan dimension mismatch for FPID={}".format(floor.floorplan.id)) # Update mask in case of change # Note this does not change existing data, only new observations self.mask == floor.mask class Model: LAYER_SNAP_WIFI = 1 LAYER_SNAP_BT = 2 LAYER_MVSENSE = 3 LAYERS_ALL = {LAYER_SNAP_WIFI, LAYER_SNAP_BT, LAYER_MVSENSE} CONFIG_PATH = os.path.join('model.conf') CELL_SIZE_M = 1 DOWNSAMPLE_THRESHOLD = 0.5 VARIANCE_THRESHOLD = np.hypot( *( 2*(CELL_SIZE_M / 2,) ) ) # This means let x = cell_s_m / 2; V_T = sqrt(x^2+x^2) # I wish I was kidding # This is 0.707 iff cell_s_m = 1 DEFAULT_EXPOSURE = 3 DEFAULT_PASSWORD = '<PASSWORD>' __BAD_LAYER = "Layer {} not defined. Use internally defined layer (eg Model.LAYER_*)" class ModelException(Exception): pass class BadRequest(Exception): pass def __init__(self,network_id:str=None,layers:set={}): "Initialise model. API key must be defined in enviroment variable \"MERAKI_DASHBOARD_API_KEY\"" self.read_config_data() self.write_config_data() def populate(self,layers:set): assert isinstance(self.query_obj, APIQuery) self.network_id = self.query_obj.network_id self.plans = self.pullFloors() self.getAPs() self.query_obj.pullCameras() self.data_layers = dict() self.webhook_threshold = 0.35 for layer in layers: if layer not in Model.LAYERS_ALL: raise Model.ModelException(Model.__BAD_LAYER.format(layer)) self.data_layers[layer] = Layer(self.plans, Model.DEFAULT_EXPOSURE) self.timeslot = TimeSlotAvg.load(self.data_layers,self.plans) self.webhook_addresses = [] ### Floorplans def pullFloors(self) -> dict: "Pull floorplans from the network, construct blank floor layer for each" floorplans = self.query_obj.pullFloorPlans() self.plans = { id : Floor(fp) for id,fp in floorplans.items() } return self.plans def getFloorplanSummary(self) -> dict: "Get a dict of retreived floor plan IDs and names" return { k : v.floorplan.name for k,v in self.plans.items() } def findFloorplanByName(self,name) -> str: "Find a floorPlanId from the floor name" for k in self.plans: if self.plans[k].floorplan.name == name: return k return None def setBoundsMask(self,floor_id:str,on:bool,blindspots=None,wallthreshold:float=None) -> None: "Generate a mask from BoundaryDetector for areas that people cannot possibly be on the given floor eg outside high floors. Blindspots should be a Numpy array, tuple or nested list of the form [[x1,x2,y1,y2],...]" if blindspots==None: pass elif not (isinstance(blindspots,(np.ndarray,list,tuple))): raise TypeError("Invalid type for blindspots parameter. Should be of type np.array, list or tuple") elif False in [ len(spot) == 4 for spot in blindspots ]: raise ValueError("Invalid format for blindspots parameter. Should be of shape (n,4), got {}".format(str(blindspots))) if wallthreshold == None: pass elif not isinstance(wallthreshold,(int,float)): raise TypeError("Invalid type for wallthreshold parameter. Should be of type int or float, got {}".format(str(type(wallthreshold)))) if floor_id not in self.plans.keys(): raise Model.ModelException("No such floor: ",floor_id) floor = self.plans[floor_id] if on: floor.set_bounds_mask(blindspots,wallthreshold) else: floor.bm_boxes = blindspots floor.mask[:] = 1 floor.mask_enabled = on self.update_layers() ### Layers def update_layers(self)->None: """ Must be called when a Floor is added, removed, or altered, including by set_bounds_mask This will update the Overlay objects to reflect this change May throw error if dimensions do not equate and historical data would be invalidated """ for layer in self.data_layers.values(): layer.verify_and_update(self.plans) ### Access Points def getAPs(self) -> None: "Get APs and store internally in relevent floor objects" aps = self.query_obj.pullAPs() for mac,ap in aps.items(): if ap.floorPlanId in self.plans.keys(): self.plans[ap.floorPlanId].aps[mac] = ap ### Scanning API (SAPI) def __validate_scanning(self,SAPI_packet:dict) -> None: if type(SAPI_packet) != dict: raise TypeError("JSON parsed a {}, expected a dict".format(str(type(SAPI_packet)))) try: source_net_id = SAPI_packet["data"]["networkId"] if SAPI_packet[SECRET_K] != self.secret: raise Model.BadRequest("Request has bad authentication secret - rejecting data") except KeyError as ke: raise Model.BadRequest("Request is missing data: " + str(ke) ) if source_net_id != self.network_id: raise Model.BadRequest("Request has data from wrong network: expected {} got {}".format(self.network_id,source_net_id)) def get_type(SAPI_packet:dict) -> int: "Get the Model layer constant for a given SAPI packet" api_layer_val = APIQuery.get_SAPI_type(SAPI_packet) if api_layer_val == "WiFi": return Model.LAYER_SNAP_WIFI elif api_layer_val == "Bluetooth": return Model.LAYER_SNAP_BT else: raise Model.ModelException(Model.__BAD_LAYER.format(api_layer_val)) def __generate_person_obs(self) -> dict: "Indexes observed person objects with an arbitrary key" obs = self.query_obj.get_camera_observations() # Zip [0,n) with n obs objects, converting to dictionary return dict(zip(range(len(obs)),obs)) def provide_scanning(self,SAPI_packet:dict) -> None: "Update model with SAPI data" # Raise a racket if theres something wrong self.__validate_scanning(SAPI_packet) dest_layer = Model.get_type(SAPI_packet) observations = self.query_obj.extract_SAPI_observations(SAPI_packet) self.data_layers[dest_layer].set_observations(observations) ### Camera and MVSense def setFOVs(self,mac:str,coords:set)->None: """ Set the FOV coords from given camera (by mac). Coords should be iterable of shape (n,2). Coords pertain to sqm pixels on internal datamap. Pass len(iterable)==0 to unset mask """ #Check if Layer exists if Model.LAYER_MVSENSE in self.data_layers.keys(): #Check camera with mac exists if mac in self.query_obj.getCameras().keys(): #Check coords of correct shape and iterable, or of len 0 to unset try: if len(coords) == 0 or False not in [ len(coord)==2 for coord in coords ]: cam = self.query_obj.cameras[mac] shape = self.plans[cam.floorPlanId].overlay_dimensions cam.set_FOV(shape,coords) else: raise ValueError except (ValueError, TypeError) as err: raise err.__class__("Coordinates supplied of incorrect shape or type, should be iterable shape (n,2)") else: raise Model.ModelException("Camera with mac {} not found".format(mac)) else: raise Model.ModelException("Model not configured for LAYER_MVSENSE") def pull_mvsense_data(self): "Pull live MVSense data from cameras and feed into data layer" self.query_obj.updateCameraMVSenseData() observations = self.__generate_person_obs() self.data_layers[Model.LAYER_MVSENSE].set_observations(observations) def spike(self, layer, threshhold)->dict: #add floorplan ID into params, camera/wifi/bluetoothall into params? threshold into params? dims = ( (len(layer)//3)+1, (len(layer[0])//3)+1 ) #splits floorplan into 3m^2 areas clusters = np.zeros(dims, dtype="float32") for x in range(len(clusters)): for y in range(len(clusters[0])): clusters[x,y] = layer[3*x:3*(x+1),3*y:3*(y+1)].sum() busiest = 0 busiest_location=None for x in range(len(clusters)): for y in range(len(clusters[0])): if clusters[x][y] > busiest: busiest = clusters[x][y] busiest_location = (3*(x+0.5), 3*(y+0.5)) return {'spike':busiest > threshhold, 'location':busiest_location} def nearestCameras(self, n:int, floor:Floor,spikeDict:dict)->tuple: #returns a list of camera objects # They call me the comprehension king # Maybe after we spend 30 minutes fixing it ;) event = spikeDict["location"] event_root = tuple([ int(d) for d in event ]) cameras = { cam for cam in self.query_obj.getCameras().values() if cam.floorPlanId == floor.floorplan.id } FOVcams = { cam for cam in cameras if cam.has_FOV() } nonFOVcams = cameras - FOVcams hasView = { cam for cam in FOVcams if cam.get_FOV()[event_root]==True } if len(hasView)>0: return ("Covered", list(hasView) ) distances = dict() for cam in FOVcams: fov = cam.get_FOV() mindist = 9999999 for x,row in enumerate(fov): for y, cell in enumerate(row): if cell: dist = np.hypot( (x+0.5)-event[0], (y+0.5)-event[1] ) if dist < mindist: mindist = dist distances[cam] = mindist for cam in nonFOVcams: distances[cam] = np.hypot( cam.x-event[0], cam.y-event[1] ) top_n = [ cam[0] for cam in sorted(distances.items(),key=lambda x: x[1])[:n] ] return ("Best Effort", top_n) def getCameraImage(self, camera) -> dict: #returns a dictionary containing a link to the image response = self.query_obj.getCameraSnap(camera) return response def snapshotWebhook(self, snapshot:dict): for address in self.webhook_addresses: response = requests.post(address, json = snapshot) print(response) def addWebhookAddress(self, webhookAddress:str): self.webhook_addresses.append(webhookAddress) ### Historical def put_historical(self) -> None: "Updates the average data for the current TimeSlotAvg object" self.update_timeslot() # Get the current timeslot object self.timeslot.update_avg_data( self.data_layers ) def comp_historical(self, floorPlanId:str): "Get the relative busyness of a floorplan using all layers" self.update_timeslot() # Get the current timeslot object hist_fp_data = self.timeslot.get_floor_avgs(floorPlanId) collective = np.zeros( self.plans[floorPlanId].overlay_dimensions ) for lid in self.data_layers.keys(): mask_enabled = self.plans[floorPlanId].mask_enabled current = self.data_layers[lid].overlays[floorPlanId].get_delta(masked=mask_enabled) historical = hist_fp_data[lid].get_delta(masked=mask_enabled,exposure=1) collective += (current - historical) collective /= len(self.data_layers) return collective def update_timeslot(self): "Calls the factory if the current TimeSlotAvg object is not current" if not (self.timeslot.is_current_time()): self.timeslot.write() self.timeslot = TimeSlotAvg.load( self.data_layers, self.plans ) self.timeslot.verify_and_update_struct( self.data_layers, self.plans ) ### Providers def poll_layer(self,layer:int,exposure:int) -> dict: return self.data_layers[layer].get_full(exposure=exposure) def render_delta(self,floorPlanId:str)->Image: "Get the current datamap in terms of absolute delta from mean" datamap = self.comp_historical(floorPlanId) return self.plans[floorPlanId].render_overlay(datamap) def render_abs(self,floorPlanId:str)->Image: "Get latest frame of WiFi layer rendered on the floor plan" return self.plans[floorPlanId].render_overlay(self.data_layers[Model.LAYER_SNAP_WIFI].overlays[floorPlanId].get_delta(exposure=1)) def debug_render(self,fpid)->Image: import datetime dm = self.plans[fpid] dims = dm.overlay_dimensions testarr = np.zeros(dims).ravel() n = (datetime.datetime.now().second / 60) * len(testarr) testarr[:int(n)] = 1 return dm.render_overlay(testarr.reshape(dims)) def update(self)->None: "Update non-webhook (non-SAPI) layers, write history" self.pull_mvsense_data() self.put_historical() #spike detect POST_data = {} for fpid, floor in self.plans.items(): spikedict = self.spike(self.comp_historical(fpid), self.webhook_threshold) if spikedict['spike'] == True: idealality, cameras = self.nearestCameras(2, floor, spikedict) #need to get relevant floor obj POST_data[fpid] = {"type" : "SnapshotData", "is_ideal" : idealality} for i, cam in enumerate(cameras): response = self.getCameraImage(cam) POST_data[fpid]["camera_data_" + str(i)] = response if POST_data != {}: self.snapshotWebhook(POST_data) ### Configuration STORE_WEBHOOK = "webhooklist" STORE_SELECTED = "selectednet" STORE_LAYERS = "layers" STORE_FOVCOORDS = "fov_coords" STORE_FOVMASK = "fov_mask" STORE_BMBOXES = "bm_boxes" STORE_BDENABLED = "bd_enabled" STORE_SECRET = "sapisecret" STORE_TOKEN = "<PASSWORD>_token" STORE_PASSWORD = "<PASSWORD>" STORE_WHTHRESHOLD = "webhook_threshold" def update_model_config(self, netid, conf_dict): layers = conf_dict.get(Model.STORE_LAYERS,set()) try: if netid != self.network_id: raise AttributeError except AttributeError: self.query_obj = APIQuery(netid) self.populate(layers) self.secret = conf_dict.get(Model.STORE_SECRET) self.validator_token = conf_dict.get(Model.STORE_TOKEN) self.webhook_addresses = conf_dict.get(Model.STORE_WEBHOOK,list()) self.password = conf_dict.get(Model.STORE_PASSWORD,Model.DEFAULT_PASSWORD) self.webhook_threshold = conf_dict.get(Model.STORE_WHTHRESHOLD,self.webhook_threshold) for mac, coords in conf_dict.get(Model.STORE_FOVCOORDS,dict()).items(): self.setFOVs( mac, coords ) for fpid, boxes in conf_dict.get(Model.STORE_BMBOXES, dict()).items(): on = conf_dict.get(Model.STORE_BDENABLED,{fpid:False})[fpid] self.setBoundsMask(fpid, on, boxes) def serialize(self): conf = dict() conf[Model.STORE_SECRET] = self.secret conf[Model.STORE_TOKEN] = self.validator_token conf[Model.STORE_LAYERS] = set(self.data_layers.keys()) conf[Model.STORE_WEBHOOK] = self.webhook_addresses conf[Model.STORE_WHTHRESHOLD] = self.webhook_threshold conf[Model.STORE_PASSWORD] = self.password conf[Model.STORE_FOVCOORDS] = { cam.mac: cam.get_fov_coords() for cam in self.query_obj.cameras.values() } conf[Model.STORE_BMBOXES] = { fpid: fp.bm_boxes for fpid,fp in self.plans.items() } conf[Model.STORE_BDENABLED] = { fpid: fp.mask_enabled for fpid,fp in self.plans.items() } return conf def write_config_data(self): config_data = {Model.STORE_SELECTED:self.network_id} config_data[self.network_id] = self.serialize() with open( self.CONFIG_PATH, 'wb' ) as f: pickle.dump(config_data, f) def read_config_data(self): if os.path.isfile(Model.CONFIG_PATH): with open( Model.CONFIG_PATH, 'rb' ) as f: config_data = pickle.load(f) selected_id = config_data[Model.STORE_SELECTED] select_data = config_data[selected_id] self.update_model_config(selected_id,select_data) else: print("Warning: config file not found") try: self.update_model_config(None, {Model.STORE_LAYERS: Model.LAYERS_ALL} ) except APIQuery.APIException: raise Model.ModelException("Could not get network from config file") class TimeSlotAvg: class TimeSlotAvgException( Exception ): pass DATA_DIR = "historical_data" def __init__(self, data_layers:dict, day:int, hour:int): self.day = day self.hour = hour self.data_layers = dict() self.count = dict() for l_id, layer in data_layers.items(): # Copy the layer structure but clear the transient data # Also we only need 1 frame to store average so flatten self.data_layers[l_id] = layer.copy(flatten=True) self.data_layers[l_id].clear() # Set a count for each overlay in each layer stored self.count[l_id] = { fpid:0 for fpid in layer.overlays.keys() } @staticmethod def load( data_layers:dict, floors:dict, day=None, hour=None ): "Static factory method; Load TimeSlotAvg object from compressed pickle file or create new" #TODO remove day hour params - used for unit tests if day==None or hour==None: day, hour = TimeSlotAvg.get_time() try: tsa = bz2.BZ2File(os.path.join(TimeSlotAvg.DATA_DIR,'{}_{}.pbz2'.format(day, hour)), 'rb') tsa = pickle.load(tsa) except FileNotFoundError: tsa = TimeSlotAvg( data_layers, day, hour ) tsa.verify_and_update_struct(data_layers, floors) tsa.write() else: if __name__!="__main__": assert isinstance(tsa,TimeSlotAvg) tsa.verify_and_update_struct(data_layers, floors) return tsa def is_current_time(self, debug=None) -> bool: "Returns True iff timeslot is for current time" if debug != None: return debug curr_day, curr_hour = TimeSlotAvg.get_time() return curr_day == self.day and curr_hour == self.hour def update_avg_data(self, current_data:dict, debug:bool=None) -> None: "Updates an average model for a timeslot using the current model data, if valid time" if self.is_current_time(debug): # it is valid to update with the current model # For each layer in the new data for l_key, layer in current_data.items(): # Get the respective average layer avg_layer = self.data_layers[l_key] # For each overlay in the respective new data layer for o_key, over in layer.overlays.items(): # Get masked and unmasked deltas, and unfixed count from new data # Get full available exposure by default new_um_overlay = over.get_delta(masked=False) new_m_overlay = over.get_delta(masked=True) new_unfixed_obs = over.get_unfixed_observations() # Similar from averages # avg layers are already flat so exposure of 1 avg_um_overlay = avg_layer.overlays[o_key].get_delta(masked=False,exposure=1) avg_m_overlay = avg_layer.overlays[o_key].get_delta(masked=True,exposure=1) avg_unfixed_obs = over.get_unfixed_observations() # Count c = self.count[l_key][o_key] # update the average by adding current values to sum total and dividing by new count upd_um_overlay = ( avg_um_overlay * c + new_um_overlay ) / (c+1) upd_m_overlay = ( avg_m_overlay * c + new_m_overlay ) / (c+1) upd_unfixed_obs = ( avg_unfixed_obs * c + new_unfixed_obs ) / (c+1) # save the new data overlay to the timeslots model, promoting as exposure of historicals = 1 self.data_layers[l_key].overlays[o_key].set( upd_unfixed_obs[None,], upd_m_overlay[None,], upd_um_overlay[None,] ) # Update the count self.count[l_key][o_key] += 1 #self.write() else: raise TimeSlotAvg.TimeSlotAvgException(f"Cannot update with current model as it is not currently day:{self.day}, hour:{self.hour}") def write(self): "Save TimeSlotAvg object to a compressed file" filepath = os.path.join(TimeSlotAvg.DATA_DIR,'{}_{}.pbz2'.format(self.day, self.hour)) if not os.path.exists(TimeSlotAvg.DATA_DIR): os.makedirs(TimeSlotAvg.DATA_DIR) with bz2.BZ2File(filepath, 'wb') as f: pickle.dump(self, f) def get_floor_avgs(self, fpid:str)->dict: "Return the flat average Overlay object indexed by each layer stored" return { layer_id: layer.overlays[fpid] for layer_id, layer in self.data_layers.items() } @staticmethod def get_time()->tuple: "Get the current time values needed for reading and writing data files" curr_dt = datetime.datetime.now( datetime.timezone( offset=datetime.timedelta(hours=0) ) ) curr_day = curr_dt.weekday() curr_hour = curr_dt.hour return curr_day, curr_hour def verify_and_update_struct(self, data_layers:dict, floors:dict)->None: """ Verifies that the data in the TimeSlotAvg is compatible with the current Model. If layers or overlays are not represented in TSA, those are created, infos are printed Throws ModelException if dimensions do not match """ for l_id in set(data_layers.keys()).difference(self.data_layers.keys()): # For layers in data_layers not in self self.data_layers[l_id] = data_layers[l_id].copy() self.count[l_id] = dict() print("Info: Layer implicitly created for Layer ID {}".format(l_id)) for l_id, layer in self.data_layers.items(): # Add any missing overlays layer.verify_and_update(floors) for l_id in data_layers.keys(): # Get count if exists, else set to 1 self.count[l_id] = { ov_id:self.count[l_id].get(ov_id,1) for ov_id in data_layers[l_id].overlays.keys() } def sha256(inpt:str) -> str: m = hashlib.sha256() m.update(inpt.encode()) return m.hexdigest()
2.09375
2
53. Maximum Subarray/main.py
Competitive-Programmers-Community/LeetCode
2
12790111
<filename>53. Maximum Subarray/main.py class Solution: def maxSubArray(self, A): if not A: return 0 curSum = maxSum = A[0] for num in A[1:]: curSum = max(num, curSum + num) maxSum = max(maxSum, curSum) return maxSum
3.65625
4
esociallib/v2_04/evtCdBenPrRP.py
akretion/esociallib
6
12790112
<filename>esociallib/v2_04/evtCdBenPrRP.py #!/usr/bin/env python # -*- coding: utf-8 -*- # # Generated Tue Oct 10 00:42:21 2017 by generateDS.py version 2.28b. # Python 2.7.12 (default, Nov 19 2016, 06:48:10) [GCC 5.4.0 20160609] # # Command line options: # ('--no-process-includes', '') # ('-o', 'esociallib/v2_04/evtCdBenPrRP.py') # # Command line arguments: # schemas/v2_04/evtCdBenPrRP.xsd # # Command line: # /usr/local/bin/generateDS --no-process-includes -o "esociallib/v2_04/evtCdBenPrRP.py" schemas/v2_04/evtCdBenPrRP.xsd # # Current working directory (os.getcwd()): # esociallib # import sys import re as re_ import base64 import datetime as datetime_ import warnings as warnings_ try: from lxml import etree as etree_ except ImportError: from xml.etree import ElementTree as etree_ Validate_simpletypes_ = True if sys.version_info.major == 2: BaseStrType_ = basestring else: BaseStrType_ = str def parsexml_(infile, parser=None, **kwargs): if parser is None: # Use the lxml ElementTree compatible parser so that, e.g., # we ignore comments. try: parser = etree_.ETCompatXMLParser() except AttributeError: # fallback to xml.etree parser = etree_.XMLParser() doc = etree_.parse(infile, parser=parser, **kwargs) return doc # # Namespace prefix definition table (and other attributes, too) # # The module generatedsnamespaces, if it is importable, must contain # a dictionary named GeneratedsNamespaceDefs. This Python dictionary # should map element type names (strings) to XML schema namespace prefix # definitions. The export method for any class for which there is # a namespace prefix definition, will export that definition in the # XML representation of that element. See the export method of # any generated element type class for a example of the use of this # table. # A sample table is: # # # File: generatedsnamespaces.py # # GenerateDSNamespaceDefs = { # "ElementtypeA": "http://www.xxx.com/namespaceA", # "ElementtypeB": "http://www.xxx.com/namespaceB", # } # try: from generatedsnamespaces import GenerateDSNamespaceDefs as GenerateDSNamespaceDefs_ except ImportError: GenerateDSNamespaceDefs_ = {} # # The root super-class for element type classes # # Calls to the methods in these classes are generated by generateDS.py. # You can replace these methods by re-implementing the following class # in a module named generatedssuper.py. try: from generatedssuper import GeneratedsSuper except ImportError as exp: class GeneratedsSuper(object): tzoff_pattern = re_.compile(r'(\+|-)((0\d|1[0-3]):[0-5]\d|14:00)$') class _FixedOffsetTZ(datetime_.tzinfo): def __init__(self, offset, name): self.__offset = datetime_.timedelta(minutes=offset) self.__name = name def utcoffset(self, dt): return self.__offset def tzname(self, dt): return self.__name def dst(self, dt): return None def gds_format_string(self, input_data, input_name=''): return input_data def gds_validate_string(self, input_data, node=None, input_name=''): if not input_data: return '' else: return input_data def gds_format_base64(self, input_data, input_name=''): return base64.b64encode(input_data) def gds_validate_base64(self, input_data, node=None, input_name=''): return input_data def gds_format_integer(self, input_data, input_name=''): return '%d' % input_data def gds_validate_integer(self, input_data, node=None, input_name=''): return input_data def gds_format_integer_list(self, input_data, input_name=''): return '%s' % ' '.join(input_data) def gds_validate_integer_list( self, input_data, node=None, input_name=''): values = input_data.split() for value in values: try: int(value) except (TypeError, ValueError): raise_parse_error(node, 'Requires sequence of integers') return values def gds_format_float(self, input_data, input_name=''): return ('%.15f' % input_data).rstrip('0') def gds_validate_float(self, input_data, node=None, input_name=''): return input_data def gds_format_float_list(self, input_data, input_name=''): return '%s' % ' '.join(input_data) def gds_validate_float_list( self, input_data, node=None, input_name=''): values = input_data.split() for value in values: try: float(value) except (TypeError, ValueError): raise_parse_error(node, 'Requires sequence of floats') return values def gds_format_double(self, input_data, input_name=''): return '%e' % input_data def gds_validate_double(self, input_data, node=None, input_name=''): return input_data def gds_format_double_list(self, input_data, input_name=''): return '%s' % ' '.join(input_data) def gds_validate_double_list( self, input_data, node=None, input_name=''): values = input_data.split() for value in values: try: float(value) except (TypeError, ValueError): raise_parse_error(node, 'Requires sequence of doubles') return values def gds_format_boolean(self, input_data, input_name=''): return ('%s' % input_data).lower() def gds_validate_boolean(self, input_data, node=None, input_name=''): return input_data def gds_format_boolean_list(self, input_data, input_name=''): return '%s' % ' '.join(input_data) def gds_validate_boolean_list( self, input_data, node=None, input_name=''): values = input_data.split() for value in values: if value not in ('true', '1', 'false', '0', ): raise_parse_error( node, 'Requires sequence of booleans ' '("true", "1", "false", "0")') return values def gds_validate_datetime(self, input_data, node=None, input_name=''): return input_data def gds_format_datetime(self, input_data, input_name=''): if input_data.microsecond == 0: _svalue = '%04d-%02d-%02dT%02d:%02d:%02d' % ( input_data.year, input_data.month, input_data.day, input_data.hour, input_data.minute, input_data.second, ) else: _svalue = '%04d-%02d-%02dT%02d:%02d:%02d.%s' % ( input_data.year, input_data.month, input_data.day, input_data.hour, input_data.minute, input_data.second, ('%f' % (float(input_data.microsecond) / 1000000))[2:], ) if input_data.tzinfo is not None: tzoff = input_data.tzinfo.utcoffset(input_data) if tzoff is not None: total_seconds = tzoff.seconds + (86400 * tzoff.days) if total_seconds == 0: _svalue += 'Z' else: if total_seconds < 0: _svalue += '-' total_seconds *= -1 else: _svalue += '+' hours = total_seconds // 3600 minutes = (total_seconds - (hours * 3600)) // 60 _svalue += '{0:02d}:{1:02d}'.format(hours, minutes) return _svalue @classmethod def gds_parse_datetime(cls, input_data): tz = None if input_data[-1] == 'Z': tz = GeneratedsSuper._FixedOffsetTZ(0, 'UTC') input_data = input_data[:-1] else: results = GeneratedsSuper.tzoff_pattern.search(input_data) if results is not None: tzoff_parts = results.group(2).split(':') tzoff = int(tzoff_parts[0]) * 60 + int(tzoff_parts[1]) if results.group(1) == '-': tzoff *= -1 tz = GeneratedsSuper._FixedOffsetTZ( tzoff, results.group(0)) input_data = input_data[:-6] time_parts = input_data.split('.') if len(time_parts) > 1: micro_seconds = int(float('0.' + time_parts[1]) * 1000000) input_data = '%s.%s' % (time_parts[0], micro_seconds, ) dt = datetime_.datetime.strptime( input_data, '%Y-%m-%dT%H:%M:%S.%f') else: dt = datetime_.datetime.strptime( input_data, '%Y-%m-%dT%H:%M:%S') dt = dt.replace(tzinfo=tz) return dt def gds_validate_date(self, input_data, node=None, input_name=''): return input_data def gds_format_date(self, input_data, input_name=''): _svalue = '%04d-%02d-%02d' % ( input_data.year, input_data.month, input_data.day, ) try: if input_data.tzinfo is not None: tzoff = input_data.tzinfo.utcoffset(input_data) if tzoff is not None: total_seconds = tzoff.seconds + (86400 * tzoff.days) if total_seconds == 0: _svalue += 'Z' else: if total_seconds < 0: _svalue += '-' total_seconds *= -1 else: _svalue += '+' hours = total_seconds // 3600 minutes = (total_seconds - (hours * 3600)) // 60 _svalue += '{0:02d}:{1:02d}'.format( hours, minutes) except AttributeError: pass return _svalue @classmethod def gds_parse_date(cls, input_data): tz = None if input_data[-1] == 'Z': tz = GeneratedsSuper._FixedOffsetTZ(0, 'UTC') input_data = input_data[:-1] else: results = GeneratedsSuper.tzoff_pattern.search(input_data) if results is not None: tzoff_parts = results.group(2).split(':') tzoff = int(tzoff_parts[0]) * 60 + int(tzoff_parts[1]) if results.group(1) == '-': tzoff *= -1 tz = GeneratedsSuper._FixedOffsetTZ( tzoff, results.group(0)) input_data = input_data[:-6] dt = datetime_.datetime.strptime(input_data, '%Y-%m-%d') dt = dt.replace(tzinfo=tz) return dt.date() def gds_validate_time(self, input_data, node=None, input_name=''): return input_data def gds_format_time(self, input_data, input_name=''): if input_data.microsecond == 0: _svalue = '%02d:%02d:%02d' % ( input_data.hour, input_data.minute, input_data.second, ) else: _svalue = '%02d:%02d:%02d.%s' % ( input_data.hour, input_data.minute, input_data.second, ('%f' % (float(input_data.microsecond) / 1000000))[2:], ) if input_data.tzinfo is not None: tzoff = input_data.tzinfo.utcoffset(input_data) if tzoff is not None: total_seconds = tzoff.seconds + (86400 * tzoff.days) if total_seconds == 0: _svalue += 'Z' else: if total_seconds < 0: _svalue += '-' total_seconds *= -1 else: _svalue += '+' hours = total_seconds // 3600 minutes = (total_seconds - (hours * 3600)) // 60 _svalue += '{0:02d}:{1:02d}'.format(hours, minutes) return _svalue def gds_validate_simple_patterns(self, patterns, target): # pat is a list of lists of strings/patterns. We should: # - AND the outer elements # - OR the inner elements found1 = True for patterns1 in patterns: found2 = False for patterns2 in patterns1: if re_.search(patterns2, target) is not None: found2 = True break if not found2: found1 = False break return found1 @classmethod def gds_parse_time(cls, input_data): tz = None if input_data[-1] == 'Z': tz = GeneratedsSuper._FixedOffsetTZ(0, 'UTC') input_data = input_data[:-1] else: results = GeneratedsSuper.tzoff_pattern.search(input_data) if results is not None: tzoff_parts = results.group(2).split(':') tzoff = int(tzoff_parts[0]) * 60 + int(tzoff_parts[1]) if results.group(1) == '-': tzoff *= -1 tz = GeneratedsSuper._FixedOffsetTZ( tzoff, results.group(0)) input_data = input_data[:-6] if len(input_data.split('.')) > 1: dt = datetime_.datetime.strptime(input_data, '%H:%M:%S.%f') else: dt = datetime_.datetime.strptime(input_data, '%H:%M:%S') dt = dt.replace(tzinfo=tz) return dt.time() def gds_str_lower(self, instring): return instring.lower() def get_path_(self, node): path_list = [] self.get_path_list_(node, path_list) path_list.reverse() path = '/'.join(path_list) return path Tag_strip_pattern_ = re_.compile(r'\{.*\}') def get_path_list_(self, node, path_list): if node is None: return tag = GeneratedsSuper.Tag_strip_pattern_.sub('', node.tag) if tag: path_list.append(tag) self.get_path_list_(node.getparent(), path_list) def get_class_obj_(self, node, default_class=None): class_obj1 = default_class if 'xsi' in node.nsmap: classname = node.get('{%s}type' % node.nsmap['xsi']) if classname is not None: names = classname.split(':') if len(names) == 2: classname = names[1] class_obj2 = globals().get(classname) if class_obj2 is not None: class_obj1 = class_obj2 return class_obj1 def gds_build_any(self, node, type_name=None): return None @classmethod def gds_reverse_node_mapping(cls, mapping): return dict(((v, k) for k, v in mapping.iteritems())) @staticmethod def gds_encode(instring): if sys.version_info.major == 2: return instring.encode(ExternalEncoding) else: return instring @staticmethod def convert_unicode(instring): if isinstance(instring, str): result = quote_xml(instring) elif sys.version_info.major == 2 and isinstance(instring, unicode): result = quote_xml(instring).encode('utf8') else: result = GeneratedsSuper.gds_encode(str(instring)) return result def __eq__(self, other): if type(self) != type(other): return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not self.__eq__(other) def getSubclassFromModule_(module, class_): '''Get the subclass of a class from a specific module.''' name = class_.__name__ + 'Sub' if hasattr(module, name): return getattr(module, name) else: return None # # If you have installed IPython you can uncomment and use the following. # IPython is available from http://ipython.scipy.org/. # ## from IPython.Shell import IPShellEmbed ## args = '' ## ipshell = IPShellEmbed(args, ## banner = 'Dropping into IPython', ## exit_msg = 'Leaving Interpreter, back to program.') # Then use the following line where and when you want to drop into the # IPython shell: # ipshell('<some message> -- Entering ipshell.\nHit Ctrl-D to exit') # # Globals # ExternalEncoding = 'ascii' Tag_pattern_ = re_.compile(r'({.*})?(.*)') String_cleanup_pat_ = re_.compile(r"[\n\r\s]+") Namespace_extract_pat_ = re_.compile(r'{(.*)}(.*)') CDATA_pattern_ = re_.compile(r"<!\[CDATA\[.*?\]\]>", re_.DOTALL) # Change this to redirect the generated superclass module to use a # specific subclass module. CurrentSubclassModule_ = None # # Support/utility functions. # def showIndent(outfile, level, pretty_print=True): if pretty_print: for idx in range(level): outfile.write(' ') def quote_xml(inStr): "Escape markup chars, but do not modify CDATA sections." if not inStr: return '' s1 = (isinstance(inStr, BaseStrType_) and inStr or '%s' % inStr) s2 = '' pos = 0 matchobjects = CDATA_pattern_.finditer(s1) for mo in matchobjects: s3 = s1[pos:mo.start()] s2 += quote_xml_aux(s3) s2 += s1[mo.start():mo.end()] pos = mo.end() s3 = s1[pos:] s2 += quote_xml_aux(s3) return s2 def quote_xml_aux(inStr): s1 = inStr.replace('&', '&amp;') s1 = s1.replace('<', '&lt;') s1 = s1.replace('>', '&gt;') return s1 def quote_attrib(inStr): s1 = (isinstance(inStr, BaseStrType_) and inStr or '%s' % inStr) s1 = s1.replace('&', '&amp;') s1 = s1.replace('<', '&lt;') s1 = s1.replace('>', '&gt;') if '"' in s1: if "'" in s1: s1 = '"%s"' % s1.replace('"', "&quot;") else: s1 = "'%s'" % s1 else: s1 = '"%s"' % s1 return s1 def quote_python(inStr): s1 = inStr if s1.find("'") == -1: if s1.find('\n') == -1: return "'%s'" % s1 else: return "'''%s'''" % s1 else: if s1.find('"') != -1: s1 = s1.replace('"', '\\"') if s1.find('\n') == -1: return '"%s"' % s1 else: return '"""%s"""' % s1 def get_all_text_(node): if node.text is not None: text = node.text else: text = '' for child in node: if child.tail is not None: text += child.tail return text def find_attr_value_(attr_name, node): attrs = node.attrib attr_parts = attr_name.split(':') value = None if len(attr_parts) == 1: value = attrs.get(attr_name) elif len(attr_parts) == 2: prefix, name = attr_parts namespace = node.nsmap.get(prefix) if namespace is not None: value = attrs.get('{%s}%s' % (namespace, name, )) return value class GDSParseError(Exception): pass def raise_parse_error(node, msg): msg = '%s (element %s/line %d)' % (msg, node.tag, node.sourceline, ) raise GDSParseError(msg) class MixedContainer: # Constants for category: CategoryNone = 0 CategoryText = 1 CategorySimple = 2 CategoryComplex = 3 # Constants for content_type: TypeNone = 0 TypeText = 1 TypeString = 2 TypeInteger = 3 TypeFloat = 4 TypeDecimal = 5 TypeDouble = 6 TypeBoolean = 7 TypeBase64 = 8 def __init__(self, category, content_type, name, value): self.category = category self.content_type = content_type self.name = name self.value = value def getCategory(self): return self.category def getContenttype(self, content_type): return self.content_type def getValue(self): return self.value def getName(self): return self.name def export(self, outfile, level, name, namespace, pretty_print=True): if self.category == MixedContainer.CategoryText: # Prevent exporting empty content as empty lines. if self.value.strip(): outfile.write(self.value) elif self.category == MixedContainer.CategorySimple: self.exportSimple(outfile, level, name) else: # category == MixedContainer.CategoryComplex self.value.export( outfile, level, namespace, name, pretty_print=pretty_print) def exportSimple(self, outfile, level, name): if self.content_type == MixedContainer.TypeString: outfile.write('<%s>%s</%s>' % ( self.name, self.value, self.name)) elif self.content_type == MixedContainer.TypeInteger or \ self.content_type == MixedContainer.TypeBoolean: outfile.write('<%s>%d</%s>' % ( self.name, self.value, self.name)) elif self.content_type == MixedContainer.TypeFloat or \ self.content_type == MixedContainer.TypeDecimal: outfile.write('<%s>%f</%s>' % ( self.name, self.value, self.name)) elif self.content_type == MixedContainer.TypeDouble: outfile.write('<%s>%g</%s>' % ( self.name, self.value, self.name)) elif self.content_type == MixedContainer.TypeBase64: outfile.write('<%s>%s</%s>' % ( self.name, base64.b64encode(self.value), self.name)) def to_etree(self, element): if self.category == MixedContainer.CategoryText: # Prevent exporting empty content as empty lines. if self.value.strip(): if len(element) > 0: if element[-1].tail is None: element[-1].tail = self.value else: element[-1].tail += self.value else: if element.text is None: element.text = self.value else: element.text += self.value elif self.category == MixedContainer.CategorySimple: subelement = etree_.SubElement( element, '%s' % self.name) subelement.text = self.to_etree_simple() else: # category == MixedContainer.CategoryComplex self.value.to_etree(element) def to_etree_simple(self): if self.content_type == MixedContainer.TypeString: text = self.value elif (self.content_type == MixedContainer.TypeInteger or self.content_type == MixedContainer.TypeBoolean): text = '%d' % self.value elif (self.content_type == MixedContainer.TypeFloat or self.content_type == MixedContainer.TypeDecimal): text = '%f' % self.value elif self.content_type == MixedContainer.TypeDouble: text = '%g' % self.value elif self.content_type == MixedContainer.TypeBase64: text = '%s' % base64.b64encode(self.value) return text def exportLiteral(self, outfile, level, name): if self.category == MixedContainer.CategoryText: showIndent(outfile, level) outfile.write( 'model_.MixedContainer(%d, %d, "%s", "%s"),\n' % ( self.category, self.content_type, self.name, self.value)) elif self.category == MixedContainer.CategorySimple: showIndent(outfile, level) outfile.write( 'model_.MixedContainer(%d, %d, "%s", "%s"),\n' % ( self.category, self.content_type, self.name, self.value)) else: # category == MixedContainer.CategoryComplex showIndent(outfile, level) outfile.write( 'model_.MixedContainer(%d, %d, "%s",\n' % ( self.category, self.content_type, self.name,)) self.value.exportLiteral(outfile, level + 1) showIndent(outfile, level) outfile.write(')\n') class MemberSpec_(object): def __init__(self, name='', data_type='', container=0, optional=0, child_attrs=None, choice=None): self.name = name self.data_type = data_type self.container = container self.child_attrs = child_attrs self.choice = choice self.optional = optional def set_name(self, name): self.name = name def get_name(self): return self.name def set_data_type(self, data_type): self.data_type = data_type def get_data_type_chain(self): return self.data_type def get_data_type(self): if isinstance(self.data_type, list): if len(self.data_type) > 0: return self.data_type[-1] else: return 'xs:string' else: return self.data_type def set_container(self, container): self.container = container def get_container(self): return self.container def set_child_attrs(self, child_attrs): self.child_attrs = child_attrs def get_child_attrs(self): return self.child_attrs def set_choice(self, choice): self.choice = choice def get_choice(self): return self.choice def set_optional(self, optional): self.optional = optional def get_optional(self): return self.optional def _cast(typ, value): if typ is None or value is None: return value return typ(value) # # Data representation classes. # class eSocial(GeneratedsSuper): subclass = None superclass = None def __init__(self, evtCdBenPrRP=None, Signature=None): self.original_tagname_ = None self.evtCdBenPrRP = evtCdBenPrRP self.Signature = Signature def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, eSocial) if subclass is not None: return subclass(*args_, **kwargs_) if eSocial.subclass: return eSocial.subclass(*args_, **kwargs_) else: return eSocial(*args_, **kwargs_) factory = staticmethod(factory) def get_evtCdBenPrRP(self): return self.evtCdBenPrRP def set_evtCdBenPrRP(self, evtCdBenPrRP): self.evtCdBenPrRP = evtCdBenPrRP def get_Signature(self): return self.Signature def set_Signature(self, Signature): self.Signature = Signature def hasContent_(self): if ( self.evtCdBenPrRP is not None or self.Signature is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='eSocial', namespacedef_=' xmlns:ds="http://www.w3.org/2000/09/xmldsig#" ', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('eSocial') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='eSocial') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='eSocial', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='eSocial'): pass def exportChildren(self, outfile, level, namespace_='', name_='eSocial', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.evtCdBenPrRP is not None: self.evtCdBenPrRP.export(outfile, level, namespace_, name_='evtCdBenPrRP', pretty_print=pretty_print) if self.Signature is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sSignature>%s</%sSignature>%s' % ('ds:', self.gds_encode(self.gds_format_string(quote_xml(self.Signature), input_name='Signature')), 'ds:', eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'evtCdBenPrRP': obj_ = evtCdBenPrRP.factory() obj_.build(child_) self.evtCdBenPrRP = obj_ obj_.original_tagname_ = 'evtCdBenPrRP' elif nodeName_ == 'Signature': Signature_ = child_.text Signature_ = self.gds_validate_string(Signature_, node, 'Signature') self.Signature = Signature_ # end class eSocial class evtCdBenPrRP(GeneratedsSuper): """Evento de cadastro de benefícios previdenciários de Regimes Próprios""" subclass = None superclass = None def __init__(self, Id=None, ideEvento=None, ideEmpregador=None, ideBenef=None, infoBeneficio=None): self.original_tagname_ = None self.Id = _cast(None, Id) self.ideEvento = ideEvento self.ideEmpregador = ideEmpregador self.ideBenef = ideBenef self.infoBeneficio = infoBeneficio def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, evtCdBenPrRP) if subclass is not None: return subclass(*args_, **kwargs_) if evtCdBenPrRP.subclass: return evtCdBenPrRP.subclass(*args_, **kwargs_) else: return evtCdBenPrRP(*args_, **kwargs_) factory = staticmethod(factory) def get_ideEvento(self): return self.ideEvento def set_ideEvento(self, ideEvento): self.ideEvento = ideEvento def get_ideEmpregador(self): return self.ideEmpregador def set_ideEmpregador(self, ideEmpregador): self.ideEmpregador = ideEmpregador def get_ideBenef(self): return self.ideBenef def set_ideBenef(self, ideBenef): self.ideBenef = ideBenef def get_infoBeneficio(self): return self.infoBeneficio def set_infoBeneficio(self, infoBeneficio): self.infoBeneficio = infoBeneficio def get_Id(self): return self.Id def set_Id(self, Id): self.Id = Id def hasContent_(self): if ( self.ideEvento is not None or self.ideEmpregador is not None or self.ideBenef is not None or self.infoBeneficio is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='evtCdBenPrRP', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('evtCdBenPrRP') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='evtCdBenPrRP') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='evtCdBenPrRP', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='evtCdBenPrRP'): if self.Id is not None and 'Id' not in already_processed: already_processed.add('Id') outfile.write(' Id=%s' % (self.gds_encode(self.gds_format_string(quote_attrib(self.Id), input_name='Id')), )) def exportChildren(self, outfile, level, namespace_='', name_='evtCdBenPrRP', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.ideEvento is not None: self.ideEvento.export(outfile, level, namespace_, name_='ideEvento', pretty_print=pretty_print) if self.ideEmpregador is not None: self.ideEmpregador.export(outfile, level, namespace_, name_='ideEmpregador', pretty_print=pretty_print) if self.ideBenef is not None: self.ideBenef.export(outfile, level, namespace_, name_='ideBenef', pretty_print=pretty_print) if self.infoBeneficio is not None: self.infoBeneficio.export(outfile, level, namespace_, name_='infoBeneficio', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): value = find_attr_value_('Id', node) if value is not None and 'Id' not in already_processed: already_processed.add('Id') self.Id = value def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'ideEvento': obj_ = TIdeEveTrab.factory() obj_.build(child_) self.ideEvento = obj_ obj_.original_tagname_ = 'ideEvento' elif nodeName_ == 'ideEmpregador': obj_ = TEmprPJ.factory() obj_.build(child_) self.ideEmpregador = obj_ obj_.original_tagname_ = 'ideEmpregador' elif nodeName_ == 'ideBenef': obj_ = ideBenef.factory() obj_.build(child_) self.ideBenef = obj_ obj_.original_tagname_ = 'ideBenef' elif nodeName_ == 'infoBeneficio': obj_ = infoBeneficio.factory() obj_.build(child_) self.infoBeneficio = obj_ obj_.original_tagname_ = 'infoBeneficio' # end class evtCdBenPrRP class ideBenef(GeneratedsSuper): """Identificação do beneficiário""" subclass = None superclass = None def __init__(self, cpfBenef=None, nmBenefic=None, dadosBenef=None): self.original_tagname_ = None self.cpfBenef = cpfBenef self.nmBenefic = nmBenefic self.dadosBenef = dadosBenef def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, ideBenef) if subclass is not None: return subclass(*args_, **kwargs_) if ideBenef.subclass: return ideBenef.subclass(*args_, **kwargs_) else: return ideBenef(*args_, **kwargs_) factory = staticmethod(factory) def get_cpfBenef(self): return self.cpfBenef def set_cpfBenef(self, cpfBenef): self.cpfBenef = cpfBenef def get_nmBenefic(self): return self.nmBenefic def set_nmBenefic(self, nmBenefic): self.nmBenefic = nmBenefic def get_dadosBenef(self): return self.dadosBenef def set_dadosBenef(self, dadosBenef): self.dadosBenef = dadosBenef def hasContent_(self): if ( self.cpfBenef is not None or self.nmBenefic is not None or self.dadosBenef is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='ideBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('ideBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='ideBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='ideBenef', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='ideBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='ideBenef', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.cpfBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scpfBenef>%s</%scpfBenef>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.cpfBenef), input_name='cpfBenef')), namespace_, eol_)) if self.nmBenefic is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snmBenefic>%s</%snmBenefic>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nmBenefic), input_name='nmBenefic')), namespace_, eol_)) if self.dadosBenef is not None: self.dadosBenef.export(outfile, level, namespace_, name_='dadosBenef', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'cpfBenef': cpfBenef_ = child_.text cpfBenef_ = self.gds_validate_string(cpfBenef_, node, 'cpfBenef') self.cpfBenef = cpfBenef_ elif nodeName_ == 'nmBenefic': nmBenefic_ = child_.text nmBenefic_ = self.gds_validate_string(nmBenefic_, node, 'nmBenefic') self.nmBenefic = nmBenefic_ elif nodeName_ == 'dadosBenef': obj_ = TDadosBenef.factory() obj_.build(child_) self.dadosBenef = obj_ obj_.original_tagname_ = 'dadosBenef' # end class ideBenef class cpfBenef(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, cpfBenef) if subclass is not None: return subclass(*args_, **kwargs_) if cpfBenef.subclass: return cpfBenef.subclass(*args_, **kwargs_) else: return cpfBenef(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='cpfBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('cpfBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='cpfBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='cpfBenef', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='cpfBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='cpfBenef', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class cpfBenef class nmBenefic(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nmBenefic) if subclass is not None: return subclass(*args_, **kwargs_) if nmBenefic.subclass: return nmBenefic.subclass(*args_, **kwargs_) else: return nmBenefic(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nmBenefic', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nmBenefic') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nmBenefic') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nmBenefic', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nmBenefic'): pass def exportChildren(self, outfile, level, namespace_='', name_='nmBenefic', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nmBenefic class infoBeneficio(GeneratedsSuper): """Informações relacionadas ao benefício previdenciário concedido ao servidor""" subclass = None superclass = None def __init__(self, tpPlanRP=None, iniBeneficio=None, altBeneficio=None, fimBeneficio=None): self.original_tagname_ = None self.tpPlanRP = tpPlanRP self.iniBeneficio = iniBeneficio self.altBeneficio = altBeneficio self.fimBeneficio = fimBeneficio def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, infoBeneficio) if subclass is not None: return subclass(*args_, **kwargs_) if infoBeneficio.subclass: return infoBeneficio.subclass(*args_, **kwargs_) else: return infoBeneficio(*args_, **kwargs_) factory = staticmethod(factory) def get_tpPlanRP(self): return self.tpPlanRP def set_tpPlanRP(self, tpPlanRP): self.tpPlanRP = tpPlanRP def get_iniBeneficio(self): return self.iniBeneficio def set_iniBeneficio(self, iniBeneficio): self.iniBeneficio = iniBeneficio def get_altBeneficio(self): return self.altBeneficio def set_altBeneficio(self, altBeneficio): self.altBeneficio = altBeneficio def get_fimBeneficio(self): return self.fimBeneficio def set_fimBeneficio(self, fimBeneficio): self.fimBeneficio = fimBeneficio def hasContent_(self): if ( self.tpPlanRP is not None or self.iniBeneficio is not None or self.altBeneficio is not None or self.fimBeneficio is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='infoBeneficio', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('infoBeneficio') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='infoBeneficio') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='infoBeneficio', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='infoBeneficio'): pass def exportChildren(self, outfile, level, namespace_='', name_='infoBeneficio', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.tpPlanRP is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpPlanRP>%s</%stpPlanRP>%s' % (namespace_, self.gds_format_integer(self.tpPlanRP, input_name='tpPlanRP'), namespace_, eol_)) if self.iniBeneficio is not None: self.iniBeneficio.export(outfile, level, namespace_, name_='iniBeneficio', pretty_print=pretty_print) if self.altBeneficio is not None: self.altBeneficio.export(outfile, level, namespace_, name_='altBeneficio', pretty_print=pretty_print) if self.fimBeneficio is not None: self.fimBeneficio.export(outfile, level, namespace_, name_='fimBeneficio', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'tpPlanRP': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'tpPlanRP') self.tpPlanRP = ival_ elif nodeName_ == 'iniBeneficio': obj_ = TDadosBeneficio.factory() obj_.build(child_) self.iniBeneficio = obj_ obj_.original_tagname_ = 'iniBeneficio' elif nodeName_ == 'altBeneficio': obj_ = TDadosBeneficio.factory() obj_.build(child_) self.altBeneficio = obj_ obj_.original_tagname_ = 'altBeneficio' elif nodeName_ == 'fimBeneficio': obj_ = fimBeneficio.factory() obj_.build(child_) self.fimBeneficio = obj_ obj_.original_tagname_ = 'fimBeneficio' # end class infoBeneficio class tpPlanRP(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, tpPlanRP) if subclass is not None: return subclass(*args_, **kwargs_) if tpPlanRP.subclass: return tpPlanRP.subclass(*args_, **kwargs_) else: return tpPlanRP(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='tpPlanRP', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('tpPlanRP') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='tpPlanRP') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='tpPlanRP', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='tpPlanRP'): pass def exportChildren(self, outfile, level, namespace_='', name_='tpPlanRP', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class tpPlanRP class fimBeneficio(GeneratedsSuper): """Informações relativas a benefícios previdenciários - Término. Validação: Só pode ser informado se já houver informação anterior de benefícios para o beneficiário identificado em {ideBenef} e para o qual não tenha havido ainda informação de término de benefícios.""" subclass = None superclass = None def __init__(self, tpBenef=None, nrBenefic=None, dtFimBenef=None, mtvFim=None): self.original_tagname_ = None self.tpBenef = tpBenef self.nrBenefic = nrBenefic if isinstance(dtFimBenef, BaseStrType_): initvalue_ = datetime_.datetime.strptime(dtFimBenef, '%Y-%m-%d').date() else: initvalue_ = dtFimBenef self.dtFimBenef = initvalue_ self.mtvFim = mtvFim def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, fimBeneficio) if subclass is not None: return subclass(*args_, **kwargs_) if fimBeneficio.subclass: return fimBeneficio.subclass(*args_, **kwargs_) else: return fimBeneficio(*args_, **kwargs_) factory = staticmethod(factory) def get_tpBenef(self): return self.tpBenef def set_tpBenef(self, tpBenef): self.tpBenef = tpBenef def get_nrBenefic(self): return self.nrBenefic def set_nrBenefic(self, nrBenefic): self.nrBenefic = nrBenefic def get_dtFimBenef(self): return self.dtFimBenef def set_dtFimBenef(self, dtFimBenef): self.dtFimBenef = dtFimBenef def get_mtvFim(self): return self.mtvFim def set_mtvFim(self, mtvFim): self.mtvFim = mtvFim def hasContent_(self): if ( self.tpBenef is not None or self.nrBenefic is not None or self.dtFimBenef is not None or self.mtvFim is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='fimBeneficio', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('fimBeneficio') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='fimBeneficio') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='fimBeneficio', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='fimBeneficio'): pass def exportChildren(self, outfile, level, namespace_='', name_='fimBeneficio', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.tpBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpBenef>%s</%stpBenef>%s' % (namespace_, self.gds_format_integer(self.tpBenef, input_name='tpBenef'), namespace_, eol_)) if self.nrBenefic is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrBenefic>%s</%snrBenefic>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrBenefic), input_name='nrBenefic')), namespace_, eol_)) if self.dtFimBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sdtFimBenef>%s</%sdtFimBenef>%s' % (namespace_, self.gds_format_date(self.dtFimBenef, input_name='dtFimBenef'), namespace_, eol_)) if self.mtvFim is not None: showIndent(outfile, level, pretty_print) outfile.write('<%smtvFim>%s</%smtvFim>%s' % (namespace_, self.gds_format_integer(self.mtvFim, input_name='mtvFim'), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'tpBenef': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'tpBenef') self.tpBenef = ival_ elif nodeName_ == 'nrBenefic': nrBenefic_ = child_.text nrBenefic_ = self.gds_validate_string(nrBenefic_, node, 'nrBenefic') self.nrBenefic = nrBenefic_ elif nodeName_ == 'dtFimBenef': sval_ = child_.text dval_ = self.gds_parse_date(sval_) self.dtFimBenef = dval_ elif nodeName_ == 'mtvFim': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'mtvFim') self.mtvFim = ival_ # end class fimBeneficio class tpBenef(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, tpBenef) if subclass is not None: return subclass(*args_, **kwargs_) if tpBenef.subclass: return tpBenef.subclass(*args_, **kwargs_) else: return tpBenef(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='tpBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('tpBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='tpBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='tpBenef', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='tpBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='tpBenef', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class tpBenef class nrBenefic(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nrBenefic) if subclass is not None: return subclass(*args_, **kwargs_) if nrBenefic.subclass: return nrBenefic.subclass(*args_, **kwargs_) else: return nrBenefic(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nrBenefic', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nrBenefic') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nrBenefic') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nrBenefic', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nrBenefic'): pass def exportChildren(self, outfile, level, namespace_='', name_='nrBenefic', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nrBenefic class dtFimBenef(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, dtFimBenef) if subclass is not None: return subclass(*args_, **kwargs_) if dtFimBenef.subclass: return dtFimBenef.subclass(*args_, **kwargs_) else: return dtFimBenef(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='dtFimBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('dtFimBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='dtFimBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='dtFimBenef', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='dtFimBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='dtFimBenef', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class dtFimBenef class mtvFim(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, mtvFim) if subclass is not None: return subclass(*args_, **kwargs_) if mtvFim.subclass: return mtvFim.subclass(*args_, **kwargs_) else: return mtvFim(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='mtvFim', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('mtvFim') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='mtvFim') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='mtvFim', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='mtvFim'): pass def exportChildren(self, outfile, level, namespace_='', name_='mtvFim', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class mtvFim class TIdeEveTrab(GeneratedsSuper): """Identificação do evento""" subclass = None superclass = None def __init__(self, indRetif=None, nrRecibo=None, tpAmb=None, procEmi=None, verProc=None): self.original_tagname_ = None self.indRetif = indRetif self.nrRecibo = nrRecibo self.tpAmb = tpAmb self.procEmi = procEmi self.verProc = verProc def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TIdeEveTrab) if subclass is not None: return subclass(*args_, **kwargs_) if TIdeEveTrab.subclass: return TIdeEveTrab.subclass(*args_, **kwargs_) else: return TIdeEveTrab(*args_, **kwargs_) factory = staticmethod(factory) def get_indRetif(self): return self.indRetif def set_indRetif(self, indRetif): self.indRetif = indRetif def get_nrRecibo(self): return self.nrRecibo def set_nrRecibo(self, nrRecibo): self.nrRecibo = nrRecibo def get_tpAmb(self): return self.tpAmb def set_tpAmb(self, tpAmb): self.tpAmb = tpAmb def get_procEmi(self): return self.procEmi def set_procEmi(self, procEmi): self.procEmi = procEmi def get_verProc(self): return self.verProc def set_verProc(self, verProc): self.verProc = verProc def hasContent_(self): if ( self.indRetif is not None or self.nrRecibo is not None or self.tpAmb is not None or self.procEmi is not None or self.verProc is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TIdeEveTrab', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TIdeEveTrab') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TIdeEveTrab') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TIdeEveTrab', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TIdeEveTrab'): pass def exportChildren(self, outfile, level, namespace_='', name_='TIdeEveTrab', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.indRetif is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sindRetif>%s</%sindRetif>%s' % (namespace_, self.gds_format_integer(self.indRetif, input_name='indRetif'), namespace_, eol_)) if self.nrRecibo is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrRecibo>%s</%snrRecibo>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrRecibo), input_name='nrRecibo')), namespace_, eol_)) if self.tpAmb is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpAmb>%s</%stpAmb>%s' % (namespace_, self.gds_format_integer(self.tpAmb, input_name='tpAmb'), namespace_, eol_)) if self.procEmi is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sprocEmi>%s</%sprocEmi>%s' % (namespace_, self.gds_format_integer(self.procEmi, input_name='procEmi'), namespace_, eol_)) if self.verProc is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sverProc>%s</%sverProc>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.verProc), input_name='verProc')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'indRetif': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'indRetif') self.indRetif = ival_ elif nodeName_ == 'nrRecibo': nrRecibo_ = child_.text nrRecibo_ = self.gds_validate_string(nrRecibo_, node, 'nrRecibo') self.nrRecibo = nrRecibo_ elif nodeName_ == 'tpAmb': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'tpAmb') self.tpAmb = ival_ elif nodeName_ == 'procEmi': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'procEmi') self.procEmi = ival_ elif nodeName_ == 'verProc': verProc_ = child_.text verProc_ = self.gds_validate_string(verProc_, node, 'verProc') self.verProc = verProc_ # end class TIdeEveTrab class indRetif(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, indRetif) if subclass is not None: return subclass(*args_, **kwargs_) if indRetif.subclass: return indRetif.subclass(*args_, **kwargs_) else: return indRetif(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='indRetif', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('indRetif') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='indRetif') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='indRetif', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='indRetif'): pass def exportChildren(self, outfile, level, namespace_='', name_='indRetif', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class indRetif class nrRecibo(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nrRecibo) if subclass is not None: return subclass(*args_, **kwargs_) if nrRecibo.subclass: return nrRecibo.subclass(*args_, **kwargs_) else: return nrRecibo(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nrRecibo', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nrRecibo') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nrRecibo') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nrRecibo', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nrRecibo'): pass def exportChildren(self, outfile, level, namespace_='', name_='nrRecibo', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nrRecibo class tpAmb(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, tpAmb) if subclass is not None: return subclass(*args_, **kwargs_) if tpAmb.subclass: return tpAmb.subclass(*args_, **kwargs_) else: return tpAmb(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='tpAmb', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('tpAmb') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='tpAmb') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='tpAmb', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='tpAmb'): pass def exportChildren(self, outfile, level, namespace_='', name_='tpAmb', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class tpAmb class procEmi(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, procEmi) if subclass is not None: return subclass(*args_, **kwargs_) if procEmi.subclass: return procEmi.subclass(*args_, **kwargs_) else: return procEmi(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='procEmi', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('procEmi') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='procEmi') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='procEmi', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='procEmi'): pass def exportChildren(self, outfile, level, namespace_='', name_='procEmi', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class procEmi class verProc(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, verProc) if subclass is not None: return subclass(*args_, **kwargs_) if verProc.subclass: return verProc.subclass(*args_, **kwargs_) else: return verProc(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='verProc', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('verProc') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='verProc') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='verProc', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='verProc'): pass def exportChildren(self, outfile, level, namespace_='', name_='verProc', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class verProc class TEmprPJ(GeneratedsSuper): """Informações do Empregador PJ""" subclass = None superclass = None def __init__(self, tpInsc=None, nrInsc=None): self.original_tagname_ = None self.tpInsc = tpInsc self.nrInsc = nrInsc def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TEmprPJ) if subclass is not None: return subclass(*args_, **kwargs_) if TEmprPJ.subclass: return TEmprPJ.subclass(*args_, **kwargs_) else: return TEmprPJ(*args_, **kwargs_) factory = staticmethod(factory) def get_tpInsc(self): return self.tpInsc def set_tpInsc(self, tpInsc): self.tpInsc = tpInsc def get_nrInsc(self): return self.nrInsc def set_nrInsc(self, nrInsc): self.nrInsc = nrInsc def hasContent_(self): if ( self.tpInsc is not None or self.nrInsc is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TEmprPJ', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TEmprPJ') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TEmprPJ') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TEmprPJ', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TEmprPJ'): pass def exportChildren(self, outfile, level, namespace_='', name_='TEmprPJ', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.tpInsc is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpInsc>%s</%stpInsc>%s' % (namespace_, self.gds_format_integer(self.tpInsc, input_name='tpInsc'), namespace_, eol_)) if self.nrInsc is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrInsc>%s</%snrInsc>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrInsc), input_name='nrInsc')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'tpInsc': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'tpInsc') self.tpInsc = ival_ elif nodeName_ == 'nrInsc': nrInsc_ = child_.text nrInsc_ = self.gds_validate_string(nrInsc_, node, 'nrInsc') self.nrInsc = nrInsc_ # end class TEmprPJ class tpInsc(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, tpInsc) if subclass is not None: return subclass(*args_, **kwargs_) if tpInsc.subclass: return tpInsc.subclass(*args_, **kwargs_) else: return tpInsc(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='tpInsc', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('tpInsc') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='tpInsc') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='tpInsc', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='tpInsc'): pass def exportChildren(self, outfile, level, namespace_='', name_='tpInsc', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class tpInsc class nrInsc(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nrInsc) if subclass is not None: return subclass(*args_, **kwargs_) if nrInsc.subclass: return nrInsc.subclass(*args_, **kwargs_) else: return nrInsc(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nrInsc', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nrInsc') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nrInsc') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nrInsc', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nrInsc'): pass def exportChildren(self, outfile, level, namespace_='', name_='nrInsc', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nrInsc class TDadosBenef(GeneratedsSuper): """Dados de beneficiário""" subclass = None superclass = None def __init__(self, dadosNasc=None, endereco=None): self.original_tagname_ = None self.dadosNasc = dadosNasc self.endereco = endereco def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TDadosBenef) if subclass is not None: return subclass(*args_, **kwargs_) if TDadosBenef.subclass: return TDadosBenef.subclass(*args_, **kwargs_) else: return TDadosBenef(*args_, **kwargs_) factory = staticmethod(factory) def get_dadosNasc(self): return self.dadosNasc def set_dadosNasc(self, dadosNasc): self.dadosNasc = dadosNasc def get_endereco(self): return self.endereco def set_endereco(self, endereco): self.endereco = endereco def hasContent_(self): if ( self.dadosNasc is not None or self.endereco is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TDadosBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TDadosBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TDadosBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TDadosBenef', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TDadosBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='TDadosBenef', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.dadosNasc is not None: self.dadosNasc.export(outfile, level, namespace_, name_='dadosNasc', pretty_print=pretty_print) if self.endereco is not None: self.endereco.export(outfile, level, namespace_, name_='endereco', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'dadosNasc': obj_ = dadosNasc.factory() obj_.build(child_) self.dadosNasc = obj_ obj_.original_tagname_ = 'dadosNasc' elif nodeName_ == 'endereco': obj_ = endereco.factory() obj_.build(child_) self.endereco = obj_ obj_.original_tagname_ = 'endereco' # end class TDadosBenef class dadosNasc(GeneratedsSuper): """Informações de nascimento do beneficiário""" subclass = None superclass = None def __init__(self, dtNascto=None, codMunic=None, uf=None, paisNascto=None, paisNac=None, nmMae=None, nmPai=None): self.original_tagname_ = None if isinstance(dtNascto, BaseStrType_): initvalue_ = datetime_.datetime.strptime(dtNascto, '%Y-%m-%d').date() else: initvalue_ = dtNascto self.dtNascto = initvalue_ self.codMunic = codMunic self.uf = uf self.paisNascto = paisNascto self.paisNac = paisNac self.nmMae = nmMae self.nmPai = nmPai def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, dadosNasc) if subclass is not None: return subclass(*args_, **kwargs_) if dadosNasc.subclass: return dadosNasc.subclass(*args_, **kwargs_) else: return dadosNasc(*args_, **kwargs_) factory = staticmethod(factory) def get_dtNascto(self): return self.dtNascto def set_dtNascto(self, dtNascto): self.dtNascto = dtNascto def get_codMunic(self): return self.codMunic def set_codMunic(self, codMunic): self.codMunic = codMunic def get_uf(self): return self.uf def set_uf(self, uf): self.uf = uf def get_paisNascto(self): return self.paisNascto def set_paisNascto(self, paisNascto): self.paisNascto = paisNascto def get_paisNac(self): return self.paisNac def set_paisNac(self, paisNac): self.paisNac = paisNac def get_nmMae(self): return self.nmMae def set_nmMae(self, nmMae): self.nmMae = nmMae def get_nmPai(self): return self.nmPai def set_nmPai(self, nmPai): self.nmPai = nmPai def hasContent_(self): if ( self.dtNascto is not None or self.codMunic is not None or self.uf is not None or self.paisNascto is not None or self.paisNac is not None or self.nmMae is not None or self.nmPai is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='dadosNasc', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('dadosNasc') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='dadosNasc') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='dadosNasc', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='dadosNasc'): pass def exportChildren(self, outfile, level, namespace_='', name_='dadosNasc', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.dtNascto is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sdtNascto>%s</%sdtNascto>%s' % (namespace_, self.gds_format_date(self.dtNascto, input_name='dtNascto'), namespace_, eol_)) if self.codMunic is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scodMunic>%s</%scodMunic>%s' % (namespace_, self.gds_format_integer(self.codMunic, input_name='codMunic'), namespace_, eol_)) if self.uf is not None: showIndent(outfile, level, pretty_print) outfile.write('<%suf>%s</%suf>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.uf), input_name='uf')), namespace_, eol_)) if self.paisNascto is not None: showIndent(outfile, level, pretty_print) outfile.write('<%spaisNascto>%s</%spaisNascto>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.paisNascto), input_name='paisNascto')), namespace_, eol_)) if self.paisNac is not None: showIndent(outfile, level, pretty_print) outfile.write('<%spaisNac>%s</%spaisNac>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.paisNac), input_name='paisNac')), namespace_, eol_)) if self.nmMae is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snmMae>%s</%snmMae>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nmMae), input_name='nmMae')), namespace_, eol_)) if self.nmPai is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snmPai>%s</%snmPai>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nmPai), input_name='nmPai')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'dtNascto': sval_ = child_.text dval_ = self.gds_parse_date(sval_) self.dtNascto = dval_ elif nodeName_ == 'codMunic': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'codMunic') self.codMunic = ival_ elif nodeName_ == 'uf': uf_ = child_.text uf_ = self.gds_validate_string(uf_, node, 'uf') self.uf = uf_ elif nodeName_ == 'paisNascto': paisNascto_ = child_.text paisNascto_ = self.gds_validate_string(paisNascto_, node, 'paisNascto') self.paisNascto = paisNascto_ elif nodeName_ == 'paisNac': paisNac_ = child_.text paisNac_ = self.gds_validate_string(paisNac_, node, 'paisNac') self.paisNac = paisNac_ elif nodeName_ == 'nmMae': nmMae_ = child_.text nmMae_ = self.gds_validate_string(nmMae_, node, 'nmMae') self.nmMae = nmMae_ elif nodeName_ == 'nmPai': nmPai_ = child_.text nmPai_ = self.gds_validate_string(nmPai_, node, 'nmPai') self.nmPai = nmPai_ # end class dadosNasc class dtNascto(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, dtNascto) if subclass is not None: return subclass(*args_, **kwargs_) if dtNascto.subclass: return dtNascto.subclass(*args_, **kwargs_) else: return dtNascto(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='dtNascto', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('dtNascto') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='dtNascto') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='dtNascto', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='dtNascto'): pass def exportChildren(self, outfile, level, namespace_='', name_='dtNascto', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class dtNascto class codMunic(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, codMunic) if subclass is not None: return subclass(*args_, **kwargs_) if codMunic.subclass: return codMunic.subclass(*args_, **kwargs_) else: return codMunic(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='codMunic', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('codMunic') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='codMunic') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='codMunic', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='codMunic'): pass def exportChildren(self, outfile, level, namespace_='', name_='codMunic', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class codMunic class uf(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, uf) if subclass is not None: return subclass(*args_, **kwargs_) if uf.subclass: return uf.subclass(*args_, **kwargs_) else: return uf(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='uf', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('uf') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='uf') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='uf', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='uf'): pass def exportChildren(self, outfile, level, namespace_='', name_='uf', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class uf class paisNascto(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, paisNascto) if subclass is not None: return subclass(*args_, **kwargs_) if paisNascto.subclass: return paisNascto.subclass(*args_, **kwargs_) else: return paisNascto(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='paisNascto', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('paisNascto') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='paisNascto') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='paisNascto', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='paisNascto'): pass def exportChildren(self, outfile, level, namespace_='', name_='paisNascto', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class paisNascto class paisNac(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, paisNac) if subclass is not None: return subclass(*args_, **kwargs_) if paisNac.subclass: return paisNac.subclass(*args_, **kwargs_) else: return paisNac(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='paisNac', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('paisNac') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='paisNac') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='paisNac', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='paisNac'): pass def exportChildren(self, outfile, level, namespace_='', name_='paisNac', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class paisNac class nmMae(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nmMae) if subclass is not None: return subclass(*args_, **kwargs_) if nmMae.subclass: return nmMae.subclass(*args_, **kwargs_) else: return nmMae(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nmMae', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nmMae') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nmMae') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nmMae', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nmMae'): pass def exportChildren(self, outfile, level, namespace_='', name_='nmMae', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nmMae class nmPai(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nmPai) if subclass is not None: return subclass(*args_, **kwargs_) if nmPai.subclass: return nmPai.subclass(*args_, **kwargs_) else: return nmPai(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nmPai', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nmPai') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nmPai') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nmPai', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nmPai'): pass def exportChildren(self, outfile, level, namespace_='', name_='nmPai', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nmPai class endereco(GeneratedsSuper): """Grupo de informações do endereço do Trabalhador""" subclass = None superclass = None def __init__(self, brasil=None, exterior=None): self.original_tagname_ = None self.brasil = brasil self.exterior = exterior def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, endereco) if subclass is not None: return subclass(*args_, **kwargs_) if endereco.subclass: return endereco.subclass(*args_, **kwargs_) else: return endereco(*args_, **kwargs_) factory = staticmethod(factory) def get_brasil(self): return self.brasil def set_brasil(self, brasil): self.brasil = brasil def get_exterior(self): return self.exterior def set_exterior(self, exterior): self.exterior = exterior def hasContent_(self): if ( self.brasil is not None or self.exterior is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='endereco', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('endereco') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='endereco') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='endereco', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='endereco'): pass def exportChildren(self, outfile, level, namespace_='', name_='endereco', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.brasil is not None: self.brasil.export(outfile, level, namespace_, name_='brasil', pretty_print=pretty_print) if self.exterior is not None: self.exterior.export(outfile, level, namespace_, name_='exterior', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'brasil': obj_ = TEnderecoBrasil.factory() obj_.build(child_) self.brasil = obj_ obj_.original_tagname_ = 'brasil' elif nodeName_ == 'exterior': obj_ = TEnderecoExterior.factory() obj_.build(child_) self.exterior = obj_ obj_.original_tagname_ = 'exterior' # end class endereco class TEnderecoBrasil(GeneratedsSuper): """Informações do Endereço no Brasil""" subclass = None superclass = None def __init__(self, tpLograd=None, dscLograd=None, nrLograd=None, complemento=None, bairro=None, cep=None, codMunic=None, uf=None): self.original_tagname_ = None self.tpLograd = tpLograd self.dscLograd = dscLograd self.nrLograd = nrLograd self.complemento = complemento self.bairro = bairro self.cep = cep self.codMunic = codMunic self.uf = uf def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TEnderecoBrasil) if subclass is not None: return subclass(*args_, **kwargs_) if TEnderecoBrasil.subclass: return TEnderecoBrasil.subclass(*args_, **kwargs_) else: return TEnderecoBrasil(*args_, **kwargs_) factory = staticmethod(factory) def get_tpLograd(self): return self.tpLograd def set_tpLograd(self, tpLograd): self.tpLograd = tpLograd def get_dscLograd(self): return self.dscLograd def set_dscLograd(self, dscLograd): self.dscLograd = dscLograd def get_nrLograd(self): return self.nrLograd def set_nrLograd(self, nrLograd): self.nrLograd = nrLograd def get_complemento(self): return self.complemento def set_complemento(self, complemento): self.complemento = complemento def get_bairro(self): return self.bairro def set_bairro(self, bairro): self.bairro = bairro def get_cep(self): return self.cep def set_cep(self, cep): self.cep = cep def get_codMunic(self): return self.codMunic def set_codMunic(self, codMunic): self.codMunic = codMunic def get_uf(self): return self.uf def set_uf(self, uf): self.uf = uf def hasContent_(self): if ( self.tpLograd is not None or self.dscLograd is not None or self.nrLograd is not None or self.complemento is not None or self.bairro is not None or self.cep is not None or self.codMunic is not None or self.uf is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TEnderecoBrasil', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TEnderecoBrasil') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TEnderecoBrasil') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TEnderecoBrasil', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TEnderecoBrasil'): pass def exportChildren(self, outfile, level, namespace_='', name_='TEnderecoBrasil', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.tpLograd is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpLograd>%s</%stpLograd>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.tpLograd), input_name='tpLograd')), namespace_, eol_)) if self.dscLograd is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sdscLograd>%s</%sdscLograd>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.dscLograd), input_name='dscLograd')), namespace_, eol_)) if self.nrLograd is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrLograd>%s</%snrLograd>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrLograd), input_name='nrLograd')), namespace_, eol_)) if self.complemento is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scomplemento>%s</%scomplemento>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.complemento), input_name='complemento')), namespace_, eol_)) if self.bairro is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sbairro>%s</%sbairro>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.bairro), input_name='bairro')), namespace_, eol_)) if self.cep is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scep>%s</%scep>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.cep), input_name='cep')), namespace_, eol_)) if self.codMunic is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scodMunic>%s</%scodMunic>%s' % (namespace_, self.gds_format_integer(self.codMunic, input_name='codMunic'), namespace_, eol_)) if self.uf is not None: showIndent(outfile, level, pretty_print) outfile.write('<%suf>%s</%suf>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.uf), input_name='uf')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'tpLograd': tpLograd_ = child_.text tpLograd_ = self.gds_validate_string(tpLograd_, node, 'tpLograd') self.tpLograd = tpLograd_ elif nodeName_ == 'dscLograd': dscLograd_ = child_.text dscLograd_ = self.gds_validate_string(dscLograd_, node, 'dscLograd') self.dscLograd = dscLograd_ elif nodeName_ == 'nrLograd': nrLograd_ = child_.text nrLograd_ = self.gds_validate_string(nrLograd_, node, 'nrLograd') self.nrLograd = nrLograd_ elif nodeName_ == 'complemento': complemento_ = child_.text complemento_ = self.gds_validate_string(complemento_, node, 'complemento') self.complemento = complemento_ elif nodeName_ == 'bairro': bairro_ = child_.text bairro_ = self.gds_validate_string(bairro_, node, 'bairro') self.bairro = bairro_ elif nodeName_ == 'cep': cep_ = child_.text cep_ = self.gds_validate_string(cep_, node, 'cep') self.cep = cep_ elif nodeName_ == 'codMunic': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'codMunic') self.codMunic = ival_ elif nodeName_ == 'uf': uf_ = child_.text uf_ = self.gds_validate_string(uf_, node, 'uf') self.uf = uf_ # end class TEnderecoBrasil class tpLograd(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, tpLograd) if subclass is not None: return subclass(*args_, **kwargs_) if tpLograd.subclass: return tpLograd.subclass(*args_, **kwargs_) else: return tpLograd(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='tpLograd', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('tpLograd') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='tpLograd') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='tpLograd', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='tpLograd'): pass def exportChildren(self, outfile, level, namespace_='', name_='tpLograd', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class tpLograd class dscLograd(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, dscLograd) if subclass is not None: return subclass(*args_, **kwargs_) if dscLograd.subclass: return dscLograd.subclass(*args_, **kwargs_) else: return dscLograd(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='dscLograd', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('dscLograd') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='dscLograd') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='dscLograd', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='dscLograd'): pass def exportChildren(self, outfile, level, namespace_='', name_='dscLograd', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class dscLograd class nrLograd(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nrLograd) if subclass is not None: return subclass(*args_, **kwargs_) if nrLograd.subclass: return nrLograd.subclass(*args_, **kwargs_) else: return nrLograd(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nrLograd', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nrLograd') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nrLograd') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nrLograd', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nrLograd'): pass def exportChildren(self, outfile, level, namespace_='', name_='nrLograd', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nrLograd class complemento(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, complemento) if subclass is not None: return subclass(*args_, **kwargs_) if complemento.subclass: return complemento.subclass(*args_, **kwargs_) else: return complemento(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='complemento', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('complemento') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='complemento') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='complemento', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='complemento'): pass def exportChildren(self, outfile, level, namespace_='', name_='complemento', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class complemento class bairro(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, bairro) if subclass is not None: return subclass(*args_, **kwargs_) if bairro.subclass: return bairro.subclass(*args_, **kwargs_) else: return bairro(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='bairro', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('bairro') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='bairro') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='bairro', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='bairro'): pass def exportChildren(self, outfile, level, namespace_='', name_='bairro', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class bairro class cep(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, cep) if subclass is not None: return subclass(*args_, **kwargs_) if cep.subclass: return cep.subclass(*args_, **kwargs_) else: return cep(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='cep', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('cep') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='cep') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='cep', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='cep'): pass def exportChildren(self, outfile, level, namespace_='', name_='cep', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class cep class TEnderecoExterior(GeneratedsSuper): """Informações do Endereço no Exterior""" subclass = None superclass = None def __init__(self, paisResid=None, dscLograd=None, nrLograd=None, complemento=None, bairro=None, nmCid=None, codPostal=None): self.original_tagname_ = None self.paisResid = paisResid self.dscLograd = dscLograd self.nrLograd = nrLograd self.complemento = complemento self.bairro = bairro self.nmCid = nmCid self.codPostal = codPostal def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TEnderecoExterior) if subclass is not None: return subclass(*args_, **kwargs_) if TEnderecoExterior.subclass: return TEnderecoExterior.subclass(*args_, **kwargs_) else: return TEnderecoExterior(*args_, **kwargs_) factory = staticmethod(factory) def get_paisResid(self): return self.paisResid def set_paisResid(self, paisResid): self.paisResid = paisResid def get_dscLograd(self): return self.dscLograd def set_dscLograd(self, dscLograd): self.dscLograd = dscLograd def get_nrLograd(self): return self.nrLograd def set_nrLograd(self, nrLograd): self.nrLograd = nrLograd def get_complemento(self): return self.complemento def set_complemento(self, complemento): self.complemento = complemento def get_bairro(self): return self.bairro def set_bairro(self, bairro): self.bairro = bairro def get_nmCid(self): return self.nmCid def set_nmCid(self, nmCid): self.nmCid = nmCid def get_codPostal(self): return self.codPostal def set_codPostal(self, codPostal): self.codPostal = codPostal def hasContent_(self): if ( self.paisResid is not None or self.dscLograd is not None or self.nrLograd is not None or self.complemento is not None or self.bairro is not None or self.nmCid is not None or self.codPostal is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TEnderecoExterior', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TEnderecoExterior') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TEnderecoExterior') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TEnderecoExterior', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TEnderecoExterior'): pass def exportChildren(self, outfile, level, namespace_='', name_='TEnderecoExterior', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.paisResid is not None: showIndent(outfile, level, pretty_print) outfile.write('<%spaisResid>%s</%spaisResid>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.paisResid), input_name='paisResid')), namespace_, eol_)) if self.dscLograd is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sdscLograd>%s</%sdscLograd>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.dscLograd), input_name='dscLograd')), namespace_, eol_)) if self.nrLograd is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrLograd>%s</%snrLograd>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrLograd), input_name='nrLograd')), namespace_, eol_)) if self.complemento is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scomplemento>%s</%scomplemento>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.complemento), input_name='complemento')), namespace_, eol_)) if self.bairro is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sbairro>%s</%sbairro>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.bairro), input_name='bairro')), namespace_, eol_)) if self.nmCid is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snmCid>%s</%snmCid>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nmCid), input_name='nmCid')), namespace_, eol_)) if self.codPostal is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scodPostal>%s</%scodPostal>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.codPostal), input_name='codPostal')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'paisResid': paisResid_ = child_.text paisResid_ = self.gds_validate_string(paisResid_, node, 'paisResid') self.paisResid = paisResid_ elif nodeName_ == 'dscLograd': dscLograd_ = child_.text dscLograd_ = self.gds_validate_string(dscLograd_, node, 'dscLograd') self.dscLograd = dscLograd_ elif nodeName_ == 'nrLograd': nrLograd_ = child_.text nrLograd_ = self.gds_validate_string(nrLograd_, node, 'nrLograd') self.nrLograd = nrLograd_ elif nodeName_ == 'complemento': complemento_ = child_.text complemento_ = self.gds_validate_string(complemento_, node, 'complemento') self.complemento = complemento_ elif nodeName_ == 'bairro': bairro_ = child_.text bairro_ = self.gds_validate_string(bairro_, node, 'bairro') self.bairro = bairro_ elif nodeName_ == 'nmCid': nmCid_ = child_.text nmCid_ = self.gds_validate_string(nmCid_, node, 'nmCid') self.nmCid = nmCid_ elif nodeName_ == 'codPostal': codPostal_ = child_.text codPostal_ = self.gds_validate_string(codPostal_, node, 'codPostal') self.codPostal = codPostal_ # end class TEnderecoExterior class paisResid(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, paisResid) if subclass is not None: return subclass(*args_, **kwargs_) if paisResid.subclass: return paisResid.subclass(*args_, **kwargs_) else: return paisResid(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='paisResid', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('paisResid') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='paisResid') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='paisResid', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='paisResid'): pass def exportChildren(self, outfile, level, namespace_='', name_='paisResid', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class paisResid class nmCid(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, nmCid) if subclass is not None: return subclass(*args_, **kwargs_) if nmCid.subclass: return nmCid.subclass(*args_, **kwargs_) else: return nmCid(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='nmCid', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('nmCid') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='nmCid') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='nmCid', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='nmCid'): pass def exportChildren(self, outfile, level, namespace_='', name_='nmCid', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class nmCid class codPostal(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, codPostal) if subclass is not None: return subclass(*args_, **kwargs_) if codPostal.subclass: return codPostal.subclass(*args_, **kwargs_) else: return codPostal(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='codPostal', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('codPostal') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='codPostal') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='codPostal', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='codPostal'): pass def exportChildren(self, outfile, level, namespace_='', name_='codPostal', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class codPostal class TDadosBeneficio(GeneratedsSuper): """Dados do benefício previdenciário""" subclass = None superclass = None def __init__(self, tpBenef=None, nrBenefic=None, dtIniBenef=None, vrBenef=None, infoPenMorte=None): self.original_tagname_ = None self.tpBenef = tpBenef self.nrBenefic = nrBenefic if isinstance(dtIniBenef, BaseStrType_): initvalue_ = datetime_.datetime.strptime(dtIniBenef, '%Y-%m-%d').date() else: initvalue_ = dtIniBenef self.dtIniBenef = initvalue_ self.vrBenef = vrBenef self.infoPenMorte = infoPenMorte def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, TDadosBeneficio) if subclass is not None: return subclass(*args_, **kwargs_) if TDadosBeneficio.subclass: return TDadosBeneficio.subclass(*args_, **kwargs_) else: return TDadosBeneficio(*args_, **kwargs_) factory = staticmethod(factory) def get_tpBenef(self): return self.tpBenef def set_tpBenef(self, tpBenef): self.tpBenef = tpBenef def get_nrBenefic(self): return self.nrBenefic def set_nrBenefic(self, nrBenefic): self.nrBenefic = nrBenefic def get_dtIniBenef(self): return self.dtIniBenef def set_dtIniBenef(self, dtIniBenef): self.dtIniBenef = dtIniBenef def get_vrBenef(self): return self.vrBenef def set_vrBenef(self, vrBenef): self.vrBenef = vrBenef def get_infoPenMorte(self): return self.infoPenMorte def set_infoPenMorte(self, infoPenMorte): self.infoPenMorte = infoPenMorte def hasContent_(self): if ( self.tpBenef is not None or self.nrBenefic is not None or self.dtIniBenef is not None or self.vrBenef is not None or self.infoPenMorte is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='TDadosBeneficio', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('TDadosBeneficio') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='TDadosBeneficio') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='TDadosBeneficio', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='TDadosBeneficio'): pass def exportChildren(self, outfile, level, namespace_='', name_='TDadosBeneficio', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.tpBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%stpBenef>%s</%stpBenef>%s' % (namespace_, self.gds_format_integer(self.tpBenef, input_name='tpBenef'), namespace_, eol_)) if self.nrBenefic is not None: showIndent(outfile, level, pretty_print) outfile.write('<%snrBenefic>%s</%snrBenefic>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.nrBenefic), input_name='nrBenefic')), namespace_, eol_)) if self.dtIniBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sdtIniBenef>%s</%sdtIniBenef>%s' % (namespace_, self.gds_format_date(self.dtIniBenef, input_name='dtIniBenef'), namespace_, eol_)) if self.vrBenef is not None: showIndent(outfile, level, pretty_print) outfile.write('<%svrBenef>%s</%svrBenef>%s' % (namespace_, self.gds_format_float(self.vrBenef, input_name='vrBenef'), namespace_, eol_)) if self.infoPenMorte is not None: self.infoPenMorte.export(outfile, level, namespace_, name_='infoPenMorte', pretty_print=pretty_print) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'tpBenef': sval_ = child_.text try: ival_ = int(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires integer: %s' % exp) ival_ = self.gds_validate_integer(ival_, node, 'tpBenef') self.tpBenef = ival_ elif nodeName_ == 'nrBenefic': nrBenefic_ = child_.text nrBenefic_ = self.gds_validate_string(nrBenefic_, node, 'nrBenefic') self.nrBenefic = nrBenefic_ elif nodeName_ == 'dtIniBenef': sval_ = child_.text dval_ = self.gds_parse_date(sval_) self.dtIniBenef = dval_ elif nodeName_ == 'vrBenef': sval_ = child_.text try: fval_ = float(sval_) except (TypeError, ValueError) as exp: raise_parse_error(child_, 'requires float or double: %s' % exp) fval_ = self.gds_validate_float(fval_, node, 'vrBenef') self.vrBenef = fval_ elif nodeName_ == 'infoPenMorte': obj_ = infoPenMorte.factory() obj_.build(child_) self.infoPenMorte = obj_ obj_.original_tagname_ = 'infoPenMorte' # end class TDadosBeneficio class dtIniBenef(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, dtIniBenef) if subclass is not None: return subclass(*args_, **kwargs_) if dtIniBenef.subclass: return dtIniBenef.subclass(*args_, **kwargs_) else: return dtIniBenef(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='dtIniBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('dtIniBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='dtIniBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='dtIniBenef', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='dtIniBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='dtIniBenef', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class dtIniBenef class vrBenef(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, vrBenef) if subclass is not None: return subclass(*args_, **kwargs_) if vrBenef.subclass: return vrBenef.subclass(*args_, **kwargs_) else: return vrBenef(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='vrBenef', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('vrBenef') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='vrBenef') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='vrBenef', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='vrBenef'): pass def exportChildren(self, outfile, level, namespace_='', name_='vrBenef', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class vrBenef class infoPenMorte(GeneratedsSuper): """Informações relativas a pensão por morte""" subclass = None superclass = None def __init__(self, idQuota=None, cpfInst=None): self.original_tagname_ = None self.idQuota = idQuota self.cpfInst = cpfInst def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, infoPenMorte) if subclass is not None: return subclass(*args_, **kwargs_) if infoPenMorte.subclass: return infoPenMorte.subclass(*args_, **kwargs_) else: return infoPenMorte(*args_, **kwargs_) factory = staticmethod(factory) def get_idQuota(self): return self.idQuota def set_idQuota(self, idQuota): self.idQuota = idQuota def get_cpfInst(self): return self.cpfInst def set_cpfInst(self, cpfInst): self.cpfInst = cpfInst def hasContent_(self): if ( self.idQuota is not None or self.cpfInst is not None ): return True else: return False def export(self, outfile, level, namespace_='', name_='infoPenMorte', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('infoPenMorte') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='infoPenMorte') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='infoPenMorte', pretty_print=pretty_print) showIndent(outfile, level, pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='infoPenMorte'): pass def exportChildren(self, outfile, level, namespace_='', name_='infoPenMorte', fromsubclass_=False, pretty_print=True): if pretty_print: eol_ = '\n' else: eol_ = '' if self.idQuota is not None: showIndent(outfile, level, pretty_print) outfile.write('<%sidQuota>%s</%sidQuota>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.idQuota), input_name='idQuota')), namespace_, eol_)) if self.cpfInst is not None: showIndent(outfile, level, pretty_print) outfile.write('<%scpfInst>%s</%scpfInst>%s' % (namespace_, self.gds_encode(self.gds_format_string(quote_xml(self.cpfInst), input_name='cpfInst')), namespace_, eol_)) def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): if nodeName_ == 'idQuota': idQuota_ = child_.text idQuota_ = self.gds_validate_string(idQuota_, node, 'idQuota') self.idQuota = idQuota_ elif nodeName_ == 'cpfInst': cpfInst_ = child_.text cpfInst_ = self.gds_validate_string(cpfInst_, node, 'cpfInst') self.cpfInst = cpfInst_ # end class infoPenMorte class idQuota(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, idQuota) if subclass is not None: return subclass(*args_, **kwargs_) if idQuota.subclass: return idQuota.subclass(*args_, **kwargs_) else: return idQuota(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='idQuota', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('idQuota') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='idQuota') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='idQuota', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='idQuota'): pass def exportChildren(self, outfile, level, namespace_='', name_='idQuota', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class idQuota class cpfInst(GeneratedsSuper): subclass = None superclass = None def __init__(self): self.original_tagname_ = None def factory(*args_, **kwargs_): if CurrentSubclassModule_ is not None: subclass = getSubclassFromModule_( CurrentSubclassModule_, cpfInst) if subclass is not None: return subclass(*args_, **kwargs_) if cpfInst.subclass: return cpfInst.subclass(*args_, **kwargs_) else: return cpfInst(*args_, **kwargs_) factory = staticmethod(factory) def hasContent_(self): if ( ): return True else: return False def export(self, outfile, level, namespace_='', name_='cpfInst', namespacedef_='', pretty_print=True): imported_ns_def_ = GenerateDSNamespaceDefs_.get('cpfInst') if imported_ns_def_ is not None: namespacedef_ = imported_ns_def_ if pretty_print: eol_ = '\n' else: eol_ = '' if self.original_tagname_ is not None: name_ = self.original_tagname_ showIndent(outfile, level, pretty_print) outfile.write('<%s%s%s' % (namespace_, name_, namespacedef_ and ' ' + namespacedef_ or '', )) already_processed = set() self.exportAttributes(outfile, level, already_processed, namespace_, name_='cpfInst') if self.hasContent_(): outfile.write('>%s' % (eol_, )) self.exportChildren(outfile, level + 1, namespace_='', name_='cpfInst', pretty_print=pretty_print) outfile.write('</%s%s>%s' % (namespace_, name_, eol_)) else: outfile.write('/>%s' % (eol_, )) def exportAttributes(self, outfile, level, already_processed, namespace_='', name_='cpfInst'): pass def exportChildren(self, outfile, level, namespace_='', name_='cpfInst', fromsubclass_=False, pretty_print=True): pass def build(self, node): already_processed = set() self.buildAttributes(node, node.attrib, already_processed) for child in node: nodeName_ = Tag_pattern_.match(child.tag).groups()[-1] self.buildChildren(child, node, nodeName_) return self def buildAttributes(self, node, attrs, already_processed): pass def buildChildren(self, child_, node, nodeName_, fromsubclass_=False): pass # end class cpfInst GDSClassesMapping = { 'altBeneficio': TDadosBeneficio, 'brasil': TEnderecoBrasil, 'dadosBenef': TDadosBenef, 'exterior': TEnderecoExterior, 'ideEmpregador': TEmprPJ, 'ideEvento': TIdeEveTrab, 'iniBeneficio': TDadosBeneficio, } USAGE_TEXT = """ Usage: python <Parser>.py [ -s ] <in_xml_file> """ def usage(): print(USAGE_TEXT) sys.exit(1) def get_root_tag(node): tag = Tag_pattern_.match(node.tag).groups()[-1] rootClass = GDSClassesMapping.get(tag) if rootClass is None: rootClass = globals().get(tag) return tag, rootClass def parse(inFileName, silence=False): parser = None doc = parsexml_(inFileName, parser) rootNode = doc.getroot() rootTag, rootClass = get_root_tag(rootNode) if rootClass is None: rootTag = 'eSocial' rootClass = eSocial rootObj = rootClass.factory() rootObj.build(rootNode) # Enable Python to collect the space used by the DOM. doc = None if not silence: sys.stdout.write('<?xml version="1.0" ?>\n') rootObj.export( sys.stdout, 0, name_=rootTag, namespacedef_='', pretty_print=True) return rootObj def parseEtree(inFileName, silence=False): parser = None doc = parsexml_(inFileName, parser) rootNode = doc.getroot() rootTag, rootClass = get_root_tag(rootNode) if rootClass is None: rootTag = 'eSocial' rootClass = eSocial rootObj = rootClass.factory() rootObj.build(rootNode) # Enable Python to collect the space used by the DOM. doc = None mapping = {} rootElement = rootObj.to_etree(None, name_=rootTag, mapping_=mapping) reverse_mapping = rootObj.gds_reverse_node_mapping(mapping) if not silence: content = etree_.tostring( rootElement, pretty_print=True, xml_declaration=True, encoding="utf-8") sys.stdout.write(content) sys.stdout.write('\n') return rootObj, rootElement, mapping, reverse_mapping def parseString(inString, silence=False): if sys.version_info.major == 2: from StringIO import StringIO as IOBuffer else: from io import BytesIO as IOBuffer parser = None doc = parsexml_(IOBuffer(inString), parser) rootNode = doc.getroot() rootTag, rootClass = get_root_tag(rootNode) if rootClass is None: rootTag = 'eSocial' rootClass = eSocial rootObj = rootClass.factory() rootObj.build(rootNode) # Enable Python to collect the space used by the DOM. doc = None if not silence: sys.stdout.write('<?xml version="1.0" ?>\n') rootObj.export( sys.stdout, 0, name_=rootTag, namespacedef_='') return rootObj def parseLiteral(inFileName, silence=False): parser = None doc = parsexml_(inFileName, parser) rootNode = doc.getroot() rootTag, rootClass = get_root_tag(rootNode) if rootClass is None: rootTag = 'eSocial' rootClass = eSocial rootObj = rootClass.factory() rootObj.build(rootNode) # Enable Python to collect the space used by the DOM. doc = None if not silence: sys.stdout.write('#from evtCdBenPrRP import *\n\n') sys.stdout.write('import evtCdBenPrRP as model_\n\n') sys.stdout.write('rootObj = model_.rootClass(\n') rootObj.exportLiteral(sys.stdout, 0, name_=rootTag) sys.stdout.write(')\n') return rootObj def main(): args = sys.argv[1:] if len(args) == 1: parse(args[0]) else: usage() if __name__ == '__main__': #import pdb; pdb.set_trace() main() __all__ = [ "TDadosBenef", "TDadosBeneficio", "TEmprPJ", "TEnderecoBrasil", "TEnderecoExterior", "TIdeEveTrab", "eSocial" ]
1.984375
2
pointcloudset/diff/__init__.py
hugoledoux/pointcloudset
23
12790113
<reponame>hugoledoux/pointcloudset """ Functions to calculate differences and distances between entities. """ from pointcloudset.diff.origin import calculate_distance_to_origin from pointcloudset.diff.plane import calculate_distance_to_plane from pointcloudset.diff.point import calculate_distance_to_point from pointcloudset.diff.pointcloud import calculate_distance_to_pointcloud ALL_DIFFS = { "pointcloud": calculate_distance_to_pointcloud, "plane": calculate_distance_to_plane, "point": calculate_distance_to_point, "origin": calculate_distance_to_origin, }
2.21875
2
acq4/devices/ThorlabsFilterWheel/__init__.py
aleonlein/acq4
1
12790114
<reponame>aleonlein/acq4 from FilterWheel import *
0.976563
1
sdk/python/pulumi_cloudamqp/get_plugins.py
pulumi/pulumi-cloudamqp
2
12790115
<filename>sdk/python/pulumi_cloudamqp/get_plugins.py<gh_stars>1-10 # coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities from . import outputs __all__ = [ 'GetPluginsResult', 'AwaitableGetPluginsResult', 'get_plugins', ] @pulumi.output_type class GetPluginsResult: """ A collection of values returned by getPlugins. """ def __init__(__self__, id=None, instance_id=None, plugins=None): if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if instance_id and not isinstance(instance_id, int): raise TypeError("Expected argument 'instance_id' to be a int") pulumi.set(__self__, "instance_id", instance_id) if plugins and not isinstance(plugins, list): raise TypeError("Expected argument 'plugins' to be a list") pulumi.set(__self__, "plugins", plugins) @property @pulumi.getter def id(self) -> str: """ The provider-assigned unique ID for this managed resource. """ return pulumi.get(self, "id") @property @pulumi.getter(name="instanceId") def instance_id(self) -> int: return pulumi.get(self, "instance_id") @property @pulumi.getter def plugins(self) -> Sequence['outputs.GetPluginsPluginResult']: return pulumi.get(self, "plugins") class AwaitableGetPluginsResult(GetPluginsResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetPluginsResult( id=self.id, instance_id=self.instance_id, plugins=self.plugins) def get_plugins(instance_id: Optional[int] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetPluginsResult: """ Use this data source to retrieve information about installed and available plugins for the CloudAMQP instance. ## Example Usage ```python import pulumi import pulumi_cloudamqp as cloudamqp plugins = cloudamqp.get_plugins(instance_id=cloudamqp_instance["instance"]["id"]) ``` ## Argument reference * `instance_id` - (Required) The CloudAMQP instance identifier. ## Attributes reference All attributes reference are computed * `id` - The identifier for this resource. * `plugins` - An array of plugins. Each `plugins` block consists of the fields documented below. *** The `plugins` block consist of * `name` - The type of the recipient. * `version` - Rabbit MQ version that the plugins are shipped with. * `description` - Description of what the plugin does. * `enabled` - Enable or disable information for the plugin. ## Dependency This data source depends on CloudAMQP instance identifier, `cloudamqp_instance.instance.id`. """ __args__ = dict() __args__['instanceId'] = instance_id if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('cloudamqp:index/getPlugins:getPlugins', __args__, opts=opts, typ=GetPluginsResult).value return AwaitableGetPluginsResult( id=__ret__.id, instance_id=__ret__.instance_id, plugins=__ret__.plugins)
1.929688
2
mathrepl/evaluator.py
lpozo/mathrepl
3
12790116
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. """MathREPL, a math expression evaluator using Python eval() and the math module.""" from . import ALLOWED_NAMES def evaluate(expression): """Evaluate a math expression.""" # Compile the expression eventually raising a SyntaxError # when the user enters an invalid expression code = compile(expression, "<string>", "eval") # Validate allowed names for name in code.co_names: if name not in ALLOWED_NAMES: raise NameError(f"The use of '{name}' is not allowed") # Evaluate the expression eventually raising a ValueError # when the user uses a math function with a wrong input value # e.g. math.sqrt(-10) return eval(code, {"__builtins__": {}}, ALLOWED_NAMES)
2.625
3
measure_mate/migrations/0010_measurement_target_rating.py
niche-tester/measure-mate
15
12790117
# -*- coding: utf-8 -*- # Generated by Django 1.9.1 on 2016-01-30 00:57 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('measure_mate', '0009_auto_20160124_1245'), ] operations = [ migrations.AddField( model_name='measurement', name='target_rating', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='target_measurements', to='measure_mate.Rating'), ), ]
1.429688
1
jnpr/openclos/tests/unit/test_writer.py
sysbot/OpenClos
1
12790118
''' Created on Aug 26, 2014 @author: preethi ''' import os import sys import shutil sys.path.insert(0,os.path.abspath(os.path.dirname(__file__) + '/' + '../..')) #trick to make it run from CLI import unittest import sqlalchemy from sqlalchemy.orm import sessionmaker import pydot from jnpr.openclos.model import Pod, Device, InterfaceDefinition, InterfaceLogical, Interface, Base from jnpr.openclos.writer import WriterBase, ConfigWriter, CablingPlanWriter from jnpr.openclos.util import configLocation from jnpr.openclos.dao import Dao from test_model import createPod, createPodDevice from flexmock import flexmock class TestWriterBase(unittest.TestCase): def setUp(self): self.conf = {} self.conf['outputDir'] = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'out') self.conf['dbUrl'] = 'sqlite:///' self.conf['DOT'] = {'ranksep' : '5 equally', 'colors': ['red', 'green', 'blue']} self.conf['deviceFamily'] = { "QFX5100-24Q": { "ports": 'et-0/0/[0-23]' }, "QFX5100-48S": { "uplinkPorts": 'et-0/0/[48-53]', "downlinkPorts": 'xe-0/0/[0-47]' } } self.dao = Dao(self.conf) ''' Deletes 'out' folder under test dir''' shutil.rmtree(self.conf['outputDir'], ignore_errors=True) def tearDown(self): ''' Deletes 'out' folder under test dir''' shutil.rmtree(self.conf['outputDir'], ignore_errors=True) class TestConfigWriter(TestWriterBase): def testWrite(self): pod = createPod('pod1', self.dao.Session()) device = Device('test_device', "",'admin', 'admin', 'spine', "", "", pod) configWriter = ConfigWriter(self.conf, pod, self.dao) configWriter.write(device, "dummy config") self.assertTrue(os.path.exists(configWriter.outputDir + '/test_device.conf')) class TestCablingPlanWriter(TestWriterBase): def testInitWithTemplate(self): from jinja2 import TemplateNotFound pod = createPod('pod1', self.dao.Session()) cablingPlanWriter = CablingPlanWriter(self.conf, pod, self.dao) self.assertIsNotNone(cablingPlanWriter.template) with self.assertRaises(TemplateNotFound) as e: cablingPlanWriter.templateEnv.get_template('unknown-template') self.assertTrue('unknown-template' in e.exception.message) def testCreateDeviceInGraph(self): testDeviceTopology = pydot.Dot(graph_type='graph', ) pod = createPod('pod1', self.dao.Session()) cablingPlanWriter = CablingPlanWriter(self.conf, pod, self.dao) device = createPodDevice(self.dao.Session(), 'Preethi', pod) device.id = 'preethi-1' cablingPlanWriter.createDeviceInGraph(device.name, device, testDeviceTopology) path = cablingPlanWriter.outputDir + '/testDevicelabel.dot' testDeviceTopology.write_raw(path) data = open(path, 'r').read() #check the generated label for device self.assertTrue('"preethi-1" [shape=record, label=Preethi];' in data) def testcreateLinksInGraph(self): testLinksInTopology = pydot.Dot(graph_type='graph') pod = createPod('pod1', self.dao.Session()) cablingPlanWriter = CablingPlanWriter(self.conf, pod, self.dao) deviceOne = Device('spine01',"", 'admin', 'admin', 'spine', "", "", pod) deviceOne.id = 'spine01' IF1 = InterfaceDefinition('IF1', deviceOne, 'downlink') IF1.id = 'IF1' deviceTwo = Device('leaf01',"", 'admin', 'admin', 'leaf', "", "", pod) deviceTwo.id = 'leaf01' IF21 = InterfaceDefinition('IF1', deviceTwo, 'uplink') IF21.id = 'IF21' IF1.peer = IF21 IF21.peer = IF1 linkLabel = {deviceOne.id + ':' + IF1.id : deviceTwo.id + ':' + IF21.id} cablingPlanWriter.createLinksInGraph(linkLabel, testLinksInTopology, 'red') path = cablingPlanWriter.outputDir + '/testLinklabel.dot' testLinksInTopology.write_raw(path) data = open(path, 'r').read() #check generated label for links self.assertTrue('spine01:IF1 -- leaf01:IF21 [color=red];' in data) def testcreateDOTFile(self): # create pod # create device #create interface session = self.dao.Session() pod = createPod('pod1', session) cablingPlanWriter = CablingPlanWriter(self.conf, pod, self.dao) deviceOne = Device('spine01',"", 'admin', 'admin', 'spine', "", "", pod) session.add(deviceOne) IF1 = InterfaceDefinition('IF1', deviceOne, 'downlink') session.add(IF1) IF2 = InterfaceDefinition('IF2', deviceOne, 'downlink') session.add(IF2) deviceTwo = Device('leaf01',"", 'admin', 'admin', 'leaf', "", "", pod) session.add(deviceTwo) IF21 = InterfaceDefinition('IF1', deviceTwo, 'uplink') session.add(IF21) IF22 = InterfaceDefinition('IF2', deviceTwo, 'uplink') session.add(IF22) IF23 = InterfaceDefinition('IF3', deviceTwo, 'downlink') session.add(IF23) IF24 = InterfaceDefinition('IF3', deviceTwo, 'downlink') session.add(IF24) deviceThree = Device('Access01', "",'admin', 'admin', 'leaf', "", "", pod) session.add(deviceThree) IF31 = InterfaceDefinition('IF1', deviceThree, 'uplink') session.add(IF31) IF32 = InterfaceDefinition('IF2', deviceThree, 'uplink') session.add(IF32) IF1.peer = IF21 IF2.peer = IF22 IF21.peer = IF1 IF22.peer = IF2 IF23.peer = IF31 IF31.peer = IF23 IF24.peer = IF32 IF32.peer = IF24 session.commit() devices = session.query(Device).all() #check the DOT file is generated cablingPlanWriter.writeDOT() data = open(cablingPlanWriter.outputDir + '/cablingPlan.dot', 'r').read() #check generated label for links self.assertTrue('splines=polyline;' in data)
1.96875
2
py_particle_processor_qt/tools/OrbitTool/__init__.py
DanielWinklehner/py_particle_processor
0
12790119
from py_particle_processor_qt.tools.OrbitTool.OrbitTool import *
1.023438
1
hyquest/verifiers/timemap.py
Edmonton-Public-Library/centennial
0
12790120
from hyquest.verifiers.common import getTaskResultSet, getUserAction from hyquest.constants import TASK_TIMEMAP # This handles matching up TimeMap state to associated TimeMap Tasks def matchingTimeMapTasks(user, timeMapState): tasks = getTaskResultSet(user).filter(type=TASK_TIMEMAP) activeTasks = [] otherTasks = [] for task in tasks: if timeMapMatches(task, timeMapState): action = getUserAction(user, task) if action is None: otherTasks.append(task) elif action.complete != True: activeTasks.append(task) return (activeTasks, otherTasks) def timeMapMatches(task, timeMapState): reqs = task.getInfoReqs() if 'minYear' in reqs and ('year' not in timeMapState or int(timeMapState['year'])+5 < int(reqs['minYear'])): print "year before minYear" return False if 'maxYear' in reqs and ('year' not in timeMapState or int(timeMapState['year'])-5 > int(reqs['maxYear'])): print "year after maxYear" return False if 'branch' in reqs and ('branch' not in timeMapState or reqs['branch'] != str(timeMapState['branch'])): print "incorrect branch" return False if 'story' in reqs and ('story' not in timeMapState or reqs['story'] != str(timeMapState['story'])): print "incorrect story" return False if 'onMap' in reqs and ('onMap' not in timeMapState or reqs['onMap'] != str(timeMapState['onMap'])): print "On Map does not match" return False return True def getTimeMapReqs(task): taskReqs = task.taskinfo.split(';') requirements = {} for req in taskReqs: if '=' in req: reqSplit = req.split('=') requirements[reqSplit[0]] = reqSplit[1] return requirements
2.671875
3
app.py
15281029/translation
0
12790121
# -*- coding: utf-8 -*- from flask import Flask, request, make_response import requests import json from core import Translation, RequestJson, PBMT from bean import log app = Flask(__name__) def buildResponse(code, msg): json_data = dict() json_data['code'] = code json_data['message'] = msg response = make_response(json.dumps(json_data, sort_keys=True)) response.headers['Content-type'] = 'application/json; charset=utf-8' return response ''' =================翻译===================== method: POST headers: Authorization: [your api key] type: json { "text":[text], "taget":[target language] } return: json { "code":[status code], "message":[translation text] } ''' @app.route('/languages/api/translate', methods=['GET', 'POST']) def translate(): ip = request.remote_addr if request.method != 'POST': return buildResponse(403, "Method Not Allowed. ") else: try: token = request.headers['Authorization'] except Exception: return buildResponse(403, "API key not valid. Please pass a valid API key. ") tobj = Translation(token) jsondict = request.get_json() try: rjson = RequestJson(**jsondict) except Exception: log.writelogs(token, ip, '[Failed] Required field error. ') return buildResponse(400, "Required field error. ") rlist = tobj.translate(text=rjson.text, target=rjson.target) if rlist[0] == 200: log.writelogs(token, ip, '[Succeed]') else: log.writelogs(token, ip, '[Failed] '+rlist[1]) return buildResponse(code=rlist[0], msg=rlist[1]) ''' =================日志===================== method: GET headers: Authorization: [your api key] type: NULL return: json { "code":[status code], "message":[calling log] } ''' @app.route('/languages/api/logs', methods=['GET', 'POST']) def getlog(): if request.method != 'GET': return buildResponse(403, "Method Not Allowed. ") else: try: token = request.headers['Authorization'] logs = log.getlogs(token) if logs: logs = [(str(lo[0]), lo[1], lo[2], lo[3]) for lo in logs] return buildResponse(200, logs) elif logs == []: return buildResponse(200, []) elif logs is None: return buildResponse(403, "API key not valid. Please pass a valid API key. ") except Exception: return buildResponse(500, "Query log exception. ") @app.route('/languages/support', methods=['GET', 'POST']) def support_languages(): if request.method != 'GET': return buildResponse(403, "Method Not Allowed. ") else: return buildResponse(200, PBMT) if __name__ == '__main__': app.run('0.0.0.0', 81, debug=True)
2.421875
2
html_parsing/get_price_game/from_gama-gama.py
DazEB2/SimplePyScripts
117
12790122
<gh_stars>100-1000 #!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'ipetrash' # Основа взята из http://stackoverflow.com/a/37755811/5909792 def get_html(url): from PyQt5.QtCore import QUrl from PyQt5.QtWidgets import QApplication from PyQt5.QtWebEngineWidgets import QWebEnginePage class ExtractorHtml: def __init__(self, url): _app = QApplication([]) self._page = QWebEnginePage() self._page.loadFinished.connect(self._load_finished_handler) self.html = None # Небольшой костыль для получения содержимого страницы сайта http://gama-gama.ru # Загрузка страницы проходит 2 раза: сначада кусок хитрого javascript кода, потом страница # сайта с содержимым self._counter_finished = 0 self._page.load(QUrl(url)) # Ожидание загрузки страницы и получения его содержимого # Этот цикл асинхронный код делает синхронным while self.html is None: _app.processEvents() _app.quit() # Чтобы избежать падений скрипта self._page = None def _callable(self, data): self.html = data def _load_finished_handler(self, _): self._counter_finished += 1 if self._counter_finished == 2: self._page.toHtml(self._callable) return ExtractorHtml(url).html text = 'mad' url = 'http://gama-gama.ru/search/?searchField=' + text html = get_html(url) from bs4 import BeautifulSoup root = BeautifulSoup(html, 'lxml') for game in root.select('.catalog-content > a'): name = game['title'].strip() name = name.replace('Купить ', '') price = None price_holder = game.select_one('.catalog_price_holder') price_1 = price_holder.select_one('.price_1') if price_1: price = price_1.text.strip() else: # Содержит описание цены со скидкой. Вытаскиваем цену со скидкой price_2 = price_holder.select_one('.price_2') if price_2: price = price_2.select_one('.price_group > .promo_price').text # Удаление пустых символов пробелом import re price = re.sub(r'\s+', ' ', price) price = price.strip() print(name, price)
2.421875
2
tests/test_kmeans.py
joezuntz/TreeCorr
0
12790123
# Copyright (c) 2003-2019 by <NAME> # # TreeCorr is free software: 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 disclaimer given in the accompanying LICENSE # file. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions, and the disclaimer given in the documentation # and/or other materials provided with the distribution. from __future__ import print_function import numpy as np import os import time import coord import warnings import treecorr from test_helper import get_from_wiki, CaptureLog, assert_raises, profile, timer @timer def test_dessv(): try: import fitsio except ImportError: print('Skipping dessv test, since fitsio is not installed') return #treecorr.set_omp_threads(1); get_from_wiki('des_sv.fits') file_name = os.path.join('data','des_sv.fits') cat = treecorr.Catalog(file_name, ra_col='ra', dec_col='dec', ra_units='deg', dec_units='deg') # Use an odd number to make sure we force some of the shuffle bits in InitializeCenters # to happen. npatch = 43 field = cat.getNField(max_top=5) t0 = time.time() patches, cen = field.run_kmeans(npatch) t1 = time.time() print('patches = ',np.unique(patches)) assert len(patches) == cat.ntot assert min(patches) == 0 assert max(patches) == npatch-1 # Check the returned center to a direct calculation. xyz = np.array([cat.x, cat.y, cat.z]).T direct_cen = np.array([xyz[patches==i].mean(axis=0) for i in range(npatch)]) direct_cen /= np.sqrt(np.sum(direct_cen**2,axis=1)[:,np.newaxis]) np.testing.assert_allclose(cen, direct_cen, atol=1.e-3) # KMeans minimizes the total inertia. # Check this value and the rms size, which should also be quite small. inertia = np.array([np.sum((xyz[patches==i] - cen[i])**2) for i in range(npatch)]) sizes = np.array([np.mean((xyz[patches==i] - cen[i])**2) for i in range(npatch)])**0.5 sizes *= 180. / np.pi * 60. # convert to arcmin counts = np.array([np.sum(patches==i) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) print('mean size = ',np.mean(sizes)) print('rms size = ',np.std(sizes)) assert np.sum(inertia) < 200. # This is specific to this particular field and npatch. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually < 0.2 * mean assert np.std(sizes) < 0.1 * np.mean(sizes) # sizes have even less spread usually. # Should all have similar number of points. Nothing is required here though. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. t0 = time.time() patches, cen = field.run_kmeans(npatch, alt=True) t1 = time.time() assert len(patches) == cat.ntot assert min(patches) == 0 assert max(patches) == npatch-1 inertia = np.array([np.sum((xyz[patches==i] - cen[i])**2) for i in range(npatch)]) sizes = np.array([np.mean((xyz[patches==i] - cen[i])**2) for i in range(npatch)])**0.5 sizes *= 180. / np.pi * 60. # convert to arcmin counts = np.array([np.sum(patches==i) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) print('mean size = ',np.mean(sizes)) print('rms size = ',np.std(sizes)) assert np.sum(inertia) < 200. # Total shouldn't increase much. (And often decreases.) assert np.std(inertia) < 0.15 * np.mean(inertia) # rms should be even smaller here. assert np.std(sizes) < 0.1 * np.mean(sizes) # This is only a little bit smaller. # This doesn't keep the counts as equal as the standard algorithm. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Finally, use a field with lots of top level cells to check the other branch in # InitializeCenters. field = cat.getNField(min_top=10) t0 = time.time() patches, cen = field.run_kmeans(npatch) t1 = time.time() assert len(patches) == cat.ntot assert min(patches) == 0 assert max(patches) == npatch-1 inertia = np.array([np.sum((xyz[patches==i] - cen[i])**2) for i in range(npatch)]) sizes = np.array([np.mean((xyz[patches==i] - cen[i])**2) for i in range(npatch)])**0.5 sizes *= 180. / np.pi * 60. # convert to arcmin counts = np.array([np.sum(patches==i) for i in range(npatch)]) # This doesn't give as good an initialization, so these are a bit worse usually. print('With min_top=10:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) print('mean size = ',np.mean(sizes)) print('rms size = ',np.std(sizes)) assert np.sum(inertia) < 210. assert np.std(inertia) < 0.4 * np.mean(inertia) # I've seen over 0.3 x mean here. assert np.std(sizes) < 0.15 * np.mean(sizes) print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) @timer def test_radec(): # Very similar to the above, but with a random set of points, so it will run even # if the user doesn't have fitsio installed. # In addition, we add weights to make sure that works. ngal = 100000 s = 10. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) + 100 # Put everything at large y, so smallish angle on sky z = rng.normal(0,s, (ngal,) ) w = rng.random_sample(ngal) ra, dec = coord.CelestialCoord.xyz_to_radec(x,y,z) print('minra = ',np.min(ra) * coord.radians / coord.degrees) print('maxra = ',np.max(ra) * coord.radians / coord.degrees) print('mindec = ',np.min(dec) * coord.radians / coord.degrees) print('maxdec = ',np.max(dec) * coord.radians / coord.degrees) cat = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', w=w) npatch = 111 field = cat.getNField() t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 # Check the returned center to a direct calculation. xyz = np.array([cat.x, cat.y, cat.z]).T direct_cen = np.array([np.average(xyz[p==i], axis=0, weights=w[p==i]) for i in range(npatch)]) direct_cen /= np.sqrt(np.sum(direct_cen**2,axis=1)[:,np.newaxis]) np.testing.assert_allclose(cen, direct_cen, atol=2.e-3) inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('inertia = ',inertia) print('counts = ',counts) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # This is specific to this particular field and npatch. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean # With weights, these aren't actually all that similar. The range is more than a # factor of 10. I think because it varies whether high weight points happen to be near the # edges or middles of patches, so the total weight varies when you target having the # inertias be relatively similar. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. t0 = time.time() p, cen = field.run_kmeans(npatch, alt=True) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # Total shouldn't increase much. (And often decreases.) assert np.std(inertia) < 0.15 * np.mean(inertia) # rms should be even smaller here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Finally, use a field with lots of top level cells to check the other branch in # InitializeCenters. field = cat.getNField(min_top=10) t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) # This doesn't give as good an initialization, so these are a bit worse usually. print('With min_top=10:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 210. assert np.std(inertia) < 0.4 * np.mean(inertia) # I've seen over 0.3 x mean here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) @timer def test_3d(): # Like the above, but using x,y,z positions. ngal = 100000 s = 1. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) z = rng.normal(0,s, (ngal,) ) w = rng.random_sample(ngal) + 1 cat = treecorr.Catalog(x=x, y=y, z=z, w=w) npatch = 111 field = cat.getNField() t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 xyz = np.array([x, y, z]).T inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('inertia = ',inertia) print('counts = ',counts) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 33000. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Should be the same thing with ra, dec, ra ra, dec = coord.CelestialCoord.xyz_to_radec(x,y,z) r = (x**2 + y**2 + z**2)**0.5 cat2 = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', r=r, w=w) field = cat2.getNField() t0 = time.time() p2, cen = field.run_kmeans(npatch) t1 = time.time() inertia = np.array([np.sum(w[p2==i][:,None] * (xyz[p2==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p2==i]) for i in range(npatch)]) print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 33000. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. t0 = time.time() p, cen = field.run_kmeans(npatch, alt=True) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 33000. assert np.std(inertia) < 0.1 * np.mean(inertia) # rms should be even smaller here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Finally, use a field with lots of top level cells to check the other branch in # InitializeCenters. field = cat.getNField(min_top=10) t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) # This doesn't give as good an initialization, so these are a bit worse usually. print('With min_top=10:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 33000. assert np.std(inertia) < 0.4 * np.mean(inertia) # I've seen over 0.3 x mean here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) @timer def test_2d(): # Like the above, but using x,y positions. # An additional check here is that this works with other fields besides NField, even though # in practice NField will alsmost always be the kind of Field used. ngal = 100000 s = 1. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) w = rng.random_sample(ngal) + 1 g1 = rng.normal(0,s, (ngal,) ) g2 = rng.normal(0,s, (ngal,) ) k = rng.normal(0,s, (ngal,) ) cat = treecorr.Catalog(x=x, y=y, w=w, g1=g1, g2=g2, k=k) npatch = 111 field = cat.getGField() t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 xy = np.array([x, y]).T inertia = np.array([np.sum(w[p==i][:,None] * (xy[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('inertia = ',inertia) print('counts = ',counts) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 5300. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. t0 = time.time() p, cen = field.run_kmeans(npatch, alt=True) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xy[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 5300. assert np.std(inertia) < 0.1 * np.mean(inertia) # rms should be even smaller here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Finally, use a field with lots of top level cells to check the other branch in # InitializeCenters. field = cat.getKField(min_top=10) t0 = time.time() p, cen = field.run_kmeans(npatch) t1 = time.time() assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xy[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) # This doesn't give as good an initialization, so these are a bit worse usually. print('With min_top=10:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 5300. assert np.std(inertia) < 0.4 * np.mean(inertia) # I've seen over 0.3 x mean here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) @timer def test_init_random(): # Test the init=random option ngal = 100000 s = 1. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) z = rng.normal(0,s, (ngal,) ) cat = treecorr.Catalog(x=x, y=y, z=z) xyz = np.array([x, y, z]).T # Skip the refine_centers step. print('3d with init=random') npatch = 10 field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'random') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way # Use higher max_iter, since random isn't a great initialization. p2, cen2 = field.run_kmeans(npatch, init='random', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Use a field with lots of top level cells print('3d with init=random, min_top=10') field = cat.getNField(min_top=10) cen1 = field.kmeans_initialize_centers(npatch, 'random') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='random', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Repeat in 2d print('2d with init=random') cat = treecorr.Catalog(x=x, y=y) xy = np.array([x, y]).T field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'random') assert cen1.shape == (npatch, 2) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xy[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='random', max_iter=1000) inertia2 = np.array([np.sum((xy[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Repeat in spherical print('spher with init=random') ra, dec = coord.CelestialCoord.xyz_to_radec(x,y,z) cat = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad') xyz = np.array([cat.x, cat.y, cat.z]).T field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'random') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='random', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) with assert_raises(ValueError): field.run_kmeans(npatch, init='invalid') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch, init='invalid') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=ngal*2, init='random') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=ngal+1, init='random') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=0, init='random') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=-100, init='random') # Should be valid to give npatch = 1, although not particularly useful. cen_1 = field.kmeans_initialize_centers(npatch=1, init='random') p_1 = field.kmeans_assign_patches(cen_1) np.testing.assert_equal(p_1, np.zeros(ngal)) # If same number of patches as galaxies, each galaxy gets a patch. # (This is stupid of course, but check that it doesn't fail.) # Do this with fewer points though, since it's not particularly fast with N=10^5. n = 100 cat = treecorr.Catalog(ra=ra[:n], dec=dec[:n], ra_units='rad', dec_units='rad') field = cat.getNField() cen_n = field.kmeans_initialize_centers(npatch=n, init='random') p_n = field.kmeans_assign_patches(cen_n) np.testing.assert_equal(sorted(p_n), list(range(n))) @timer def test_init_kmpp(): # Test the init=random option ngal = 100000 s = 1. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) z = rng.normal(0,s, (ngal,) ) cat = treecorr.Catalog(x=x, y=y, z=z) xyz = np.array([x, y, z]).T # Skip the refine_centers step. print('3d with init=kmeans++') npatch = 10 field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'kmeans++') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way # Use higher max_iter, since random isn't a great initialization. p2, cen2 = field.run_kmeans(npatch, init='kmeans++', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Use a field with lots of top level cells print('3d with init=kmeans++, min_top=10') field = cat.getNField(min_top=10) cen1 = field.kmeans_initialize_centers(npatch, 'kmeans++') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='kmeans++', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Repeat in 2d print('2d with init=kmeans++') cat = treecorr.Catalog(x=x, y=y) xy = np.array([x, y]).T field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'kmeans++') assert cen1.shape == (npatch, 2) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xy[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='kmeans++', max_iter=1000) inertia2 = np.array([np.sum((xy[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) # Repeat in spherical print('spher with init=kmeans++') ra, dec = coord.CelestialCoord.xyz_to_radec(x,y,z) cat = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad') xyz = np.array([cat.x, cat.y, cat.z]).T field = cat.getNField() cen1 = field.kmeans_initialize_centers(npatch, 'kmeans++') assert cen1.shape == (npatch, 3) p1 = field.kmeans_assign_patches(cen1) print('patches = ',np.unique(p1)) assert len(p1) == cat.ntot assert min(p1) == 0 assert max(p1) == npatch-1 inertia1 = np.array([np.sum((xyz[p1==i] - cen1[i])**2) for i in range(npatch)]) counts1 = np.array([np.sum(p1==i) for i in range(npatch)]) print('counts = ',counts1) print('rms counts = ',np.std(counts1)) print('total inertia = ',np.sum(inertia1)) # Now run the normal way p2, cen2 = field.run_kmeans(npatch, init='kmeans++', max_iter=1000) inertia2 = np.array([np.sum((xyz[p2==i] - cen2[i])**2) for i in range(npatch)]) counts2 = np.array([np.sum(p2==i) for i in range(npatch)]) print('rms counts => ',np.std(counts2)) print('total inertia => ',np.sum(inertia2)) assert np.sum(inertia2) < np.sum(inertia1) with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=ngal*2, init='kmeans++') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=ngal+1, init='kmeans++') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=0, init='kmeans++') with assert_raises(ValueError): field.kmeans_initialize_centers(npatch=-100, init='kmeans++') # Should be valid to give npatch = 1, although not particularly useful. cen_1 = field.kmeans_initialize_centers(npatch=1, init='kmeans++') p_1 = field.kmeans_assign_patches(cen_1) np.testing.assert_equal(p_1, np.zeros(ngal)) # If same number of patches as galaxies, each galaxy gets a patch. # (This is stupid of course, but check that it doesn't fail.) # Do this with fewer points though, since it's not particularly fast with N=10^5. n = 100 cat = treecorr.Catalog(ra=ra[:n], dec=dec[:n], ra_units='rad', dec_units='rad') field = cat.getNField() cen_n = field.kmeans_initialize_centers(npatch=n, init='kmeans++') p_n = field.kmeans_assign_patches(cen_n) np.testing.assert_equal(sorted(p_n), list(range(n))) @timer def test_zero_weight(): # Based on test_ra_dec, but where many galaxies have w=0. # There used to be a bug where w=0 objects were not assigned to any patch. ngal = 10000 s = 10. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) + 100 # Put everything at large y, so smallish angle on sky z = rng.normal(0,s, (ngal,) ) w = np.zeros(ngal) w[np.random.choice(range(ngal), ngal//10, replace=False)] = 1.0 ra, dec = coord.CelestialCoord.xyz_to_radec(x,y,z) print('minra = ',np.min(ra) * coord.radians / coord.degrees) print('maxra = ',np.max(ra) * coord.radians / coord.degrees) print('mindec = ',np.min(dec) * coord.radians / coord.degrees) print('maxdec = ',np.max(dec) * coord.radians / coord.degrees) cat = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', w=w, keep_zero_weight=True) treecorr.set_omp_threads(1) npatch = 16 field = cat.getNField() t0 = time.time() p, c = field.run_kmeans(npatch) t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 print('w>0 patches = ',np.unique(p[w>0])) print('w==0 patches = ',np.unique(p[w==0])) assert set(p[w>0]) == set(p[w==0]) @timer def test_catalog_sphere(): # This follows the same path as test_radec, but using the Catalog API to run kmeans. ngal = 100000 s = 10. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) + 100 # Put everything at large y, so smallish angle on sky z = rng.normal(0,s, (ngal,) ) w = rng.random_sample(ngal) ra, dec, r = coord.CelestialCoord.xyz_to_radec(x,y,z, return_r=True) print('minra = ',np.min(ra) * coord.radians / coord.degrees) print('maxra = ',np.max(ra) * coord.radians / coord.degrees) print('mindec = ',np.min(dec) * coord.radians / coord.degrees) print('maxdec = ',np.max(dec) * coord.radians / coord.degrees) npatch = 111 cat = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', w=w, npatch=npatch) t0 = time.time() p = cat.patch cen = cat.patch_centers t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 # Check the returned center to a direct calculation. xyz = np.array([cat.x, cat.y, cat.z]).T direct_cen = np.array([np.average(xyz[p==i], axis=0, weights=w[p==i]) for i in range(npatch)]) direct_cen /= np.sqrt(np.sum(direct_cen**2,axis=1)[:,np.newaxis]) np.testing.assert_allclose(cen, direct_cen, atol=2.e-3) inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('inertia = ',inertia) print('counts = ',counts) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # This is specific to this particular field and npatch. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean # With weights, these aren't actually all that similar. The range is more than a # factor of 10. I think because it varies whether high weight points happen to be near the # edges or middles of patches, so the total weight varies when you target having the # inertias be relatively similar. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. cat2 = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', w=w, npatch=npatch, kmeans_alt=True) t0 = time.time() p = cat2.patch cen = cat2.patch_centers t1 = time.time() assert len(p) == cat2.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # Total shouldn't increase much. (And often decreases.) assert np.std(inertia) < 0.15 * np.mean(inertia) # rms should be even smaller here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check using patch_centers from (ra,dec) -> (ra,dec,r) cat3 = treecorr.Catalog(ra=ra, dec=dec, r=r, ra_units='rad', dec_units='rad', w=w, patch_centers=cat2.patch_centers) np.testing.assert_array_equal(cat2.patch, cat3.patch) np.testing.assert_array_equal(cat2.patch_centers, cat3.patch_centers) @timer def test_catalog_3d(): # With ra, dec, r, the Catalog API should only do patches using RA, Dec. ngal = 100000 s = 10. rng = np.random.RandomState(8675309) x = rng.normal(0,s, (ngal,) ) y = rng.normal(0,s, (ngal,) ) + 100 # Put everything at large y, so smallish angle on sky z = rng.normal(0,s, (ngal,) ) w = rng.random_sample(ngal) ra, dec, r = coord.CelestialCoord.xyz_to_radec(x,y,z, return_r=True) print('minra = ',np.min(ra) * coord.radians / coord.degrees) print('maxra = ',np.max(ra) * coord.radians / coord.degrees) print('mindec = ',np.min(dec) * coord.radians / coord.degrees) print('maxdec = ',np.max(dec) * coord.radians / coord.degrees) npatch = 111 cat = treecorr.Catalog(ra=ra, dec=dec, r=r, ra_units='rad', dec_units='rad', w=w, npatch=npatch) t0 = time.time() p = cat.patch cen = cat.patch_centers t1 = time.time() print('patches = ',np.unique(p)) assert len(p) == cat.ntot assert min(p) == 0 assert max(p) == npatch-1 # Check the returned center to a direct calculation. xyz = np.array([cat.x/cat.r, cat.y/cat.r, cat.z/cat.r]).T print('cen = ',cen) print('xyz = ',xyz) direct_cen = np.array([np.average(xyz[p==i], axis=0, weights=w[p==i]) for i in range(npatch)]) direct_cen /= np.sqrt(np.sum(direct_cen**2,axis=1)[:,np.newaxis]) np.testing.assert_allclose(cen, direct_cen, atol=2.e-3) inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With standard algorithm:') print('time = ',t1-t0) print('inertia = ',inertia) print('counts = ',counts) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # This is specific to this particular field and npatch. assert np.std(inertia) < 0.3 * np.mean(inertia) # rms is usually small mean # With weights, these aren't actually all that similar. The range is more than a # factor of 10. I think because it varies whether high weight points happen to be near the # edges or middles of patches, so the total weight varies when you target having the # inertias be relatively similar. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check the alternate algorithm. rms inertia should be lower. cat2 = treecorr.Catalog(ra=ra, dec=dec, r=r, ra_units='rad', dec_units='rad', w=w, npatch=npatch, kmeans_alt=True) t0 = time.time() p = cat2.patch cen = cat2.patch_centers t1 = time.time() assert len(p) == cat2.ntot assert min(p) == 0 assert max(p) == npatch-1 inertia = np.array([np.sum(w[p==i][:,None] * (xyz[p==i] - cen[i])**2) for i in range(npatch)]) counts = np.array([np.sum(w[p==i]) for i in range(npatch)]) print('With alternate algorithm:') print('time = ',t1-t0) print('total inertia = ',np.sum(inertia)) print('mean inertia = ',np.mean(inertia)) print('rms inertia = ',np.std(inertia)) assert np.sum(inertia) < 200. # Total shouldn't increase much. (And often decreases.) assert np.std(inertia) < 0.15 * np.mean(inertia) # rms should be even smaller here. print('mean counts = ',np.mean(counts)) print('min counts = ',np.min(counts)) print('max counts = ',np.max(counts)) # Check using patch_centers from (ra,dec,r) -> (ra,dec) cat3 = treecorr.Catalog(ra=ra, dec=dec, ra_units='rad', dec_units='rad', w=w, patch_centers=cat2.patch_centers) np.testing.assert_array_equal(cat2.patch, cat3.patch) np.testing.assert_array_equal(cat2.patch_centers, cat3.patch_centers) if __name__ == '__main__': test_dessv() test_radec() test_3d() test_2d() test_init_random() test_init_kmpp() test_zero_weight() test_catalog_sphere() test_catalog_3d()
1.945313
2
ws2122-lspm/Lib/site-packages/pm4py/objects/log/util/sorting.py
Malekhy/ws2122-lspm
1
12790124
''' This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de). PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>. ''' from pm4py.objects.log.obj import EventLog, Trace, EventStream from pm4py.util import xes_constants as xes def sort_timestamp_trace(trace, timestamp_key=xes.DEFAULT_TIMESTAMP_KEY, reverse_sort=False): """ Sort a trace based on timestamp key Parameters ----------- trace Trace timestamp_key Timestamp key reverse_sort If true, reverses the direction in which the sort is done (ascending) Returns ----------- trace Sorted trace """ events = sorted(trace._list, key=lambda x: x[timestamp_key], reverse=reverse_sort) new_trace = Trace(events, attributes=trace.attributes) return new_trace def sort_timestamp_stream(event_log, timestamp_key=xes.DEFAULT_TIMESTAMP_KEY, reverse_sort=False): """ Sort an event log based on timestamp key Parameters ----------- event_log Event log timestamp_key Timestamp key reverse_sort If true, reverses the direction in which the sort is done (ascending) Returns ----------- event_log Sorted event log """ events = sorted(event_log._list, key=lambda x: x[timestamp_key], reverse=reverse_sort) new_stream = EventStream(events, attributes=event_log.attributes, extensions=event_log.extensions, omni_present=event_log.omni_present, classifiers=event_log.classifiers, properties=event_log.properties) return new_stream def sort_timestamp_log(event_log, timestamp_key=xes.DEFAULT_TIMESTAMP_KEY, reverse_sort=False): """ Sort a log based on timestamp key Parameters ----------- event_log Log timestamp_key Timestamp key reverse_sort If true, reverses the direction in which the sort is done (ascending) Returns ----------- log Sorted log """ new_log = EventLog(attributes=event_log.attributes, extensions=event_log.extensions, omni_present=event_log.omni_present, classifiers=event_log.classifiers, properties=event_log.properties) for trace in event_log: if trace: new_log.append(sort_timestamp_trace(trace, timestamp_key=timestamp_key, reverse_sort=reverse_sort)) new_log._list.sort(key=lambda x: x[0][timestamp_key], reverse=reverse_sort) return new_log def sort_timestamp(log, timestamp_key=xes.DEFAULT_TIMESTAMP_KEY, reverse_sort=False): """ Sort a log based on timestamp key Parameters ----------- log Trace/Event log timestamp_key Timestamp key reverse_sort If true, reverses the direction in which the sort is done (ascending) Returns ----------- log Sorted Trace/Event log """ if type(log) is EventLog: return sort_timestamp_log(log, timestamp_key=timestamp_key, reverse_sort=reverse_sort) return sort_timestamp_stream(log, timestamp_key=timestamp_key, reverse_sort=reverse_sort) def sort_lambda_log(event_log, sort_function, reverse=False): """ Sort a log based on a lambda expression Parameters ------------ event_log Log sort_function Sort function reverse Boolean (sort by reverse order) Returns ------------ new_log Sorted log """ traces = sorted(event_log._list, key=sort_function, reverse=reverse) new_log = EventLog(traces, attributes=event_log.attributes, extensions=event_log.extensions, omni_present=event_log.omni_present, classifiers=event_log.classifiers, properties=event_log.properties) return new_log def sort_lambda_stream(event_log, sort_function, reverse=False): """ Sort a stream based on a lambda expression Parameters ------------ event_log Stream sort_function Sort function reverse Boolean (sort by reverse order) Returns ------------ stream Sorted stream """ events = sorted(event_log._list, key=sort_function, reverse=reverse) new_stream = EventStream(events, attributes=event_log.attributes, extensions=event_log.extensions, omni_present=event_log.omni_present, classifiers=event_log.classifiers, properties=event_log.properties) return new_stream def sort_lambda(log, sort_function, reverse=False): """ Sort a log based on lambda expression Parameters ------------- log Log sort_function Sort function reverse Boolean (sort by reverse order) Returns ------------- log Sorted log """ if type(log) is EventLog: return sort_lambda_log(log, sort_function, reverse=reverse) return sort_lambda_stream(log, sort_function, reverse=reverse)
2.25
2
kuconnect/dropout.py
ozanarkancan/KuConnect
0
12790125
import theano from utils import srng def dropout(input, dropout_rate=0): if dropout_rate > 0: retain = 1 - dropout_rate d_output = (input / retain) * srng.binomial(input.shape, p=retain, dtype='int32').astype('float32') else: d_output = input return d_output
2.515625
3
pytglib/api/types/push_message_content_location.py
iTeam-co/pytglib
6
12790126
<filename>pytglib/api/types/push_message_content_location.py<gh_stars>1-10 from ..utils import Object class PushMessageContentLocation(Object): """ A message with a location Attributes: ID (:obj:`str`): ``PushMessageContentLocation`` Args: is_live (:obj:`bool`): True, if the location is live is_pinned (:obj:`bool`): True, if the message is a pinned message with the specified content Returns: PushMessageContent Raises: :class:`telegram.Error` """ ID = "pushMessageContentLocation" def __init__(self, is_live, is_pinned, **kwargs): self.is_live = is_live # bool self.is_pinned = is_pinned # bool @staticmethod def read(q: dict, *args) -> "PushMessageContentLocation": is_live = q.get('is_live') is_pinned = q.get('is_pinned') return PushMessageContentLocation(is_live, is_pinned)
2.859375
3
03. Tuples and Sets - Lab/05_softuni_party.py
elenaborisova/Python-Advanced
2
12790127
def input_to_list(guests_count): return [input() for _ in range(guests_count)] def input_to_list_until_command(command): result = [] line = input() while not line == command: result.append(line) line = input() return result def get_not_arrived_guests(guests, guests_arrived): return set(guests) - set(guests_arrived) def print_result(result): result = sorted(result) print(len(result)) [print(guest) for guest in result if guest[0].isdigit()] [print(guest) for guest in result if not guest[0].isdigit()] guests = input_to_list(int(input())) guests_arrived = input_to_list_until_command("END") print_result( get_not_arrived_guests(guests, guests_arrived) )
3.765625
4
nmtwizard/config.py
OpenNMT/nmt-wizard-docker
44
12790128
<filename>nmtwizard/config.py """Functions to manipulate and validate configurations.""" import collections import jsonschema import copy def merge_config(a, b): """Merges config b in a.""" for key, b_value in b.items(): if not isinstance(b_value, dict): a[key] = b_value else: a_value = a.get(key) if a_value is not None and isinstance(a_value, dict): merge_config(a_value, b_value) else: a[key] = b_value return a def replace_config(a, b): """Updates fields in a by fields in b.""" a.update(b) return a _non_user_fields = {"model", "modelType", "imageTag", "build", "parent_model"} def update_config(a, b, mode="default"): """Update the configuration a with b.""" if not b: return a from_version = get_config_version(a) to_version = get_config_version(b) if from_version == 1 and to_version == 2: # When updating the configuration to a newer version, we clear all user fields. a = {k: v for k, v in a.items() if k in _non_user_fields} return replace_config(a, b) if mode == "default" or mode == "merge": return merge_config(a, b) if mode == "replace": return replace_config(a, b) raise ValueError("Invalid configuration update mode: %s" % mode) def index_config(config, path, index_structure=True): """Index a configuration with a path-like string.""" key = None sections = path.split("/") if not index_structure: key = sections[-1] sections = sections[:-1] for section in sections: if isinstance(config, dict): if section not in config: raise ValueError("Invalid path %s in config" % path) config = config[section] elif isinstance(config, list): section_index = None try: section_index = int(section) except ValueError: for i, block in enumerate(config): if isinstance(block, dict) and block.get("name") == section: section_index = i break if section_index is None: raise ValueError( "Expected an array index in path, but got %s instead" % section ) config = config[section_index] else: raise ValueError( "Paths in config can only represent object and array structures" ) if index_structure: return config else: return config, key def build_override(config, path, value): """Builds a configuration override to update the value at path.""" if not path: return value sections = path.split("/") section = sections[0] inner_path = "/".join(sections[1:]) if isinstance(config, dict): return {section: build_override(config.get(section), inner_path, value)} if isinstance(config, list): index = int(sections[0]) override = build_override(config[index], inner_path, value) # Since lists can't be merged, the override should contain the full list content. config = list(config) if isinstance(override, dict): config[index] = merge_config(copy.deepcopy(config[index]), override) else: config[index] = override return config raise TypeError("Paths in config can only represent object and array structures") def index_schema(schema, path): """Index a JSON schema with a path-like string.""" for section in path.split("/"): if schema["type"] != "object": raise ValueError( "Only object types are supported in the schema structure, " "but saw type %s" % schema["type"] ) properties = schema["properties"] if section not in properties: raise ValueError("Invalid path %s in user options" % path) schema = properties[section] return schema def validate_inference_options(inference_options, config): """Validate the inference options, raising ValueError on error.""" json_schema = inference_options.get("json_schema") if json_schema is None: raise ValueError('Missing "json_schema" in "inference_options"') jsonschema.Draft7Validator.check_schema(json_schema) options = inference_options.get("options") if options is None: raise ValueError('Missing "options" in "inference_options"') validate_mapping(json_schema, options, config) return json_schema def validate_mapping(schema, options, config): """Validate the mapping between inference options and configuration fields, raising ValueError on error. """ for i, mapping in enumerate(options): config_path = mapping.get("config_path") if config_path is None: raise ValueError('Missing "config_path" in option mapping %d' % i) if isinstance(config_path, str): config_path = [config_path] for cp in config_path: dst_config, _ = index_config(config, cp, index_structure=False) if not isinstance(dst_config, dict): raise ValueError("Paths in config can only index object structures") option_path = mapping.get("option_path") if option_path is None: raise ValueError('Missing "option_path" in option mapping %d' % i) _ = index_schema(schema, option_path) def read_options(config, options): """Reads the inference options. For V1 configurations, this function returns a configuration override. For V2 configurations, this function returns a dict mapping operator names to their options. Raises: ValueError: if inference options were not expected or the value is not accepted. """ inference_options = config.get("inference_options") if inference_options is None: raise ValueError("This model does not expect inference options") try: jsonschema.validate(options, inference_options["json_schema"]) except jsonschema.ValidationError as e: raise ValueError("Options validation error: %s" % e.message) v2_config = is_v2_config(config) operators_options = collections.defaultdict(dict) config_override = {} for mapping in inference_options["options"]: try: option_value = index_config(options, mapping["option_path"]) except ValueError: continue # Option not passed for this request. config_path = mapping["config_path"] if isinstance(config_path, str): config_path = [config_path] if v2_config: for cp in config_path: dst_config, dst_key = index_config(config, cp, index_structure=False) operators_options[dst_config["name"]].update({dst_key: option_value}) else: for cp in config_path: merge_config( config_override, build_override(config, cp, option_value), ) if v2_config: return operators_options return config_override def is_v2_config(config): """Returns True if config is a V2 configuration.""" preprocess = config.get("preprocess") return ( "tokenization" not in config and preprocess is not None and isinstance(preprocess, list) ) def is_v1_config(config): """Returns True if config is a V1 configuration.""" return not is_v2_config(config) def get_config_version(config): """Returns the version of the configuration.""" return 2 if is_v2_config(config) else 1 def ensure_operators_name(config): """Make sure all operators in model configuration have a unique name.""" if is_v1_config(config): return i = 1 for process in ["preprocess", "postprocess"]: process_config = config.get(process) if process_config: for op_config in process_config: op_type = op_config.get("op") if op_type: op_config.setdefault("name", "%s_%d" % (op_type, i)) i += 1 def old_to_new_config(config): """Locally update old configuration with 'tokenization' field to include new 'vocabulary' and 'preprocess" fields.""" if not config: return tok_config = config.get("tokenization") new_config = config if tok_config: if "vocabulary" not in config: new_config = copy.deepcopy(config) vocab_src = tok_config["source"].get("vocabulary", None) vocab_tgt = tok_config["target"].get("vocabulary", None) replace_src = tok_config["source"].get("replace_vocab", False) replace_tgt = tok_config["target"].get("replace_vocab", False) prev_vocab_src = tok_config["source"].get("previous_vocabulary", None) prev_vocab_tgt = tok_config["target"].get("previous_vocabulary", None) if vocab_src or vocab_tgt: new_config["vocabulary"] = {} if vocab_src: new_config["vocabulary"]["source"] = { "path": vocab_src, "replace_vocab": replace_src, } if vocab_tgt: new_config["vocabulary"]["target"] = { "path": vocab_tgt, "replace_vocab": replace_tgt, } if prev_vocab_src: new_config["vocabulary"]["source"][ "previous_vocabulary" ] = prev_vocab_src if prev_vocab_tgt: new_config["vocabulary"]["target"][ "previous_vocabulary" ] = prev_vocab_tgt if "preprocess" not in config: new_tok_config = copy.deepcopy(tok_config) new_tok_config["source"].pop("vocabulary", None) new_tok_config["target"].pop("vocabulary", None) new_tok_config["source"].pop("replace_vocab", None) new_tok_config["target"].pop("replace_vocab", None) new_config["preprocess"] = [ { "op": "tokenization", "source": new_tok_config["source"], "target": new_tok_config["target"], } ] return new_config def _ensure_params_order(params): params = collections.OrderedDict(sorted(params.items(), key=lambda x: x[0])) preferred_first = ["op", "name"] preferred_last = ["overrides"] for field in reversed(preferred_first): if field in params: params.move_to_end(field, last=False) for field in preferred_last: if field in params: params.move_to_end(field, last=True) return params def prepare_config_for_save(config): """Prepares the configuration before saving it in the model directory.""" if is_v2_config(config): # In V2 operators, we prefer that some fields appear first (or last) for readability. config = config.copy() for section_name in ("preprocess", "postprocess"): section = config.get(section_name) if section is None: continue config[section_name] = [_ensure_params_order(params) for params in section] return config
2.640625
3
shap/plots/_utils.py
willianfco/shap
16,097
12790129
from .. import Explanation from ..utils import OpChain from . import colors import numpy as np def convert_color(color): try: color = pl.get_cmap(color) except: pass if color == "shap_red": color = colors.red_rgb elif color == "shap_blue": color = colors.blue_rgb return color def convert_ordering(ordering, shap_values): if issubclass(type(ordering), OpChain): ordering = ordering.apply(Explanation(shap_values)) if issubclass(type(ordering), Explanation): if "argsort" in [op["name"] for op in ordering.op_history]: ordering = ordering.values else: ordering = ordering.argsort.flip.values return ordering def get_sort_order(dist, clust_order, cluster_threshold, feature_order): """ Returns a sorted order of the values where we respect the clustering order when dist[i,j] < cluster_threshold """ #feature_imp = np.abs(values) # if partition_tree is not None: # new_tree = fill_internal_max_values(partition_tree, shap_values) # clust_order = sort_inds(new_tree, np.abs(shap_values)) clust_inds = np.argsort(clust_order) feature_order = feature_order.copy()#order.apply(Explanation(shap_values)) # print("feature_order", feature_order) for i in range(len(feature_order)-1): ind1 = feature_order[i] next_ind = feature_order[i+1] next_ind_pos = i + 1 for j in range(i+1,len(feature_order)): ind2 = feature_order[j] #if feature_imp[ind] > # if ind1 == 2: # print(ind1, ind2, dist[ind1,ind2]) if dist[ind1,ind2] <= cluster_threshold: # if ind1 == 2: # print(clust_inds) # print(ind1, ind2, next_ind, dist[ind1,ind2], clust_inds[ind2], clust_inds[next_ind]) if dist[ind1,next_ind] > cluster_threshold or clust_inds[ind2] < clust_inds[next_ind]: next_ind = ind2 next_ind_pos = j # print("next_ind", next_ind) # print("next_ind_pos", next_ind_pos) # insert the next_ind next for j in range(next_ind_pos, i+1, -1): #print("j", j) feature_order[j] = feature_order[j-1] feature_order[i+1] = next_ind #print(feature_order) return feature_order def merge_nodes(values, partition_tree): """ This merges the two clustered leaf nodes with the smallest total value. """ M = partition_tree.shape[0] + 1 ptind = 0 min_val = np.inf for i in range(partition_tree.shape[0]): ind1 = int(partition_tree[i,0]) ind2 = int(partition_tree[i,1]) if ind1 < M and ind2 < M: val = np.abs(values[ind1]) + np.abs(values[ind2]) if val < min_val: min_val = val ptind = i #print("ptind", ptind, min_val) ind1 = int(partition_tree[ptind,0]) ind2 = int(partition_tree[ptind,1]) if ind1 > ind2: tmp = ind1 ind1 = ind2 ind2 = tmp partition_tree_new = partition_tree.copy() for i in range(partition_tree_new.shape[0]): i0 = int(partition_tree_new[i,0]) i1 = int(partition_tree_new[i,1]) if i0 == ind2: partition_tree_new[i,0] = ind1 elif i0 > ind2: partition_tree_new[i,0] -= 1 if i0 == ptind + M: partition_tree_new[i,0] = ind1 elif i0 > ptind + M: partition_tree_new[i,0] -= 1 if i1 == ind2: partition_tree_new[i,1] = ind1 elif i1 > ind2: partition_tree_new[i,1] -= 1 if i1 == ptind + M: partition_tree_new[i,1] = ind1 elif i1 > ptind + M: partition_tree_new[i,1] -= 1 partition_tree_new = np.delete(partition_tree_new, ptind, axis=0) # update the counts to be correct fill_counts(partition_tree_new) return partition_tree_new, ind1, ind2 def dendrogram_coords(leaf_positions, partition_tree): """ Returns the x and y coords of the lines of a dendrogram where the leaf order is given. Note that scipy can compute these coords as well, but it does not allow you to easily specify a specific leaf order, hence this reimplementation. """ xout = [] yout = [] _dendrogram_coords_rec(partition_tree.shape[0]-1, leaf_positions, partition_tree, xout, yout) return np.array(xout), np.array(yout) def _dendrogram_coords_rec(pos, leaf_positions, partition_tree, xout, yout): M = partition_tree.shape[0] + 1 if pos < 0: return leaf_positions[pos + M], 0 left = int(partition_tree[pos, 0]) - M right = int(partition_tree[pos, 1]) - M x_left, y_left = _dendrogram_coords_rec(left, leaf_positions, partition_tree, xout, yout) x_right, y_right = _dendrogram_coords_rec(right, leaf_positions, partition_tree, xout, yout) y_curr = partition_tree[pos, 2] xout.append([x_left, x_left, x_right, x_right]) yout.append([y_left, y_curr, y_curr, y_right]) return (x_left + x_right) / 2, y_curr def fill_internal_max_values(partition_tree, leaf_values): """ This fills the forth column of the partition tree matrix with the max leaf value in that cluster. """ M = partition_tree.shape[0] + 1 new_tree = partition_tree.copy() for i in range(new_tree.shape[0]): val = 0 if new_tree[i,0] < M: ind = int(new_tree[i,0]) val = max(val, np.abs(leaf_values[ind])) else: ind = int(new_tree[i,0])-M val = max(val, np.abs(new_tree[ind,3])) # / partition_tree[ind,2]) if new_tree[i,1] < M: ind = int(new_tree[i,1]) val = max(val, np.abs(leaf_values[ind])) else: ind = int(new_tree[i,1])-M val = max(val, np.abs(new_tree[ind,3])) # / partition_tree[ind,2]) new_tree[i,3] = val return new_tree def fill_counts(partition_tree): """ This updates the """ M = partition_tree.shape[0] + 1 for i in range(partition_tree.shape[0]): val = 0 if partition_tree[i,0] < M: ind = int(partition_tree[i,0]) val += 1 else: ind = int(partition_tree[i,0])-M val += partition_tree[ind,3] if partition_tree[i,1] < M: ind = int(partition_tree[i,1]) val += 1 else: ind = int(partition_tree[i,1])-M val += partition_tree[ind,3] partition_tree[i,3] = val def sort_inds(partition_tree, leaf_values, pos=None, inds=None): if inds is None: inds = [] if pos is None: partition_tree = fill_internal_max_values(partition_tree, leaf_values) pos = partition_tree.shape[0]-1 M = partition_tree.shape[0] + 1 if pos < 0: inds.append(pos + M) return left = int(partition_tree[pos, 0]) - M right = int(partition_tree[pos, 1]) - M left_val = partition_tree[left,3] if left >= 0 else leaf_values[left + M] right_val = partition_tree[right,3] if right >= 0 else leaf_values[right + M] if left_val < right_val: tmp = right right = left left = tmp sort_inds(partition_tree, leaf_values, left, inds) sort_inds(partition_tree, leaf_values, right, inds) return inds
2.75
3
samples/pose_estimation/solver.py
SushmaDG/MaskRCNN
1
12790130
<filename>samples/pose_estimation/solver.py import cv2 import os import trimesh import numpy as np from paz.core import Pose6D from paz.core.ops import Camera import paz.processors as pr from paz.core import ops import matplotlib.pyplot as plt MESH_DIR = '/home/incendio/Documents/Thesis/YCBVideo_detector/color_meshes' GREEN = (0, 255, 0) class PnPSolver(): """ Implements PnP RANSAC algorithm to compute rotation and translation vector for a given RGB mask of an object # Arguments: rgb_mask: RGB mask of object true_id: Int class_name: class name of object. String dimension: (width, height) for draw_cube size: size of the mask """ def __init__(self, rgb_mask, true_id, class_name, color=GREEN, dimension=[.1, .1], size=(320, 320)): self.rgb_mask = rgb_mask self.size = size self.dimension = dimension self.camera = self.compute_camera_matrix() self.id = true_id self.class_name = class_name self.vertex_colors = self.get_vertex_colors() self.color = color self.world_to_camera = np.array([[ 0.70710678, 0., -0.70710678, 0.01674194], [-0.40824829, 0.81649658, -0.40824829, -0.01203142], [ 0.57735027, 0.57735027, 0.57735027, -1.73205081], [ 0., 0., 0., 1.]]) def get_vertex_colors(self): for name in os.listdir(MESH_DIR): class_id = name.split('_')[0] if int(class_id) == self.id: mesh_path = os.path.join(MESH_DIR, name) self.mesh = trimesh.load(mesh_path) vertex_colors = self.mesh.visual.vertex_colors[:, :3] return vertex_colors def solve_PnP(self): points3d, image2D = self.get_points() assert image2D.shape[0] == points3d.shape[0] (_, rotation, translation, inliers) = ops.solve_PNP(points3d, image2D, self.camera, ops.UPNP) pose6D = Pose6D.from_rotation_vector(rotation, translation, self.class_name) return pose6D def visualize_3D_boxes(self, image, pose6D): dimensions = {self.class_name: self.dimension} pose = {'pose6D': pose6D, 'image': image, 'color': self.color} draw = pr.DrawBoxes3D(self.camera, dimensions) args, projected_points = draw(pose) return args, projected_points def get_points(self): points3d, image2d = [], [] rows, cols, channels = np.where(self.rgb_mask > 0) for index in range(len(rows)): x, y = rows[index], cols[index] R, G, B = self.rgb_mask[x, y, :] matches = np.unique(np.array(self.get_matches(x, y))) if len(matches) == 1: image2d.append([y, x]) vertex = self.mesh.vertices[matches[0], :] points3d.append(vertex) # x_index = np.where(self.vertex_colors == np.stack([R, G, B]))[0] # mid_index = int(len(x_index) / 2) # points3d.append(self.mesh.vertices[x_index[mid_index], :]) image2d = np.array(image2d).astype(np.float32) #(N, 2) points3d = np.array(points3d).astype(np.float32) #(N, 3) return points3d, image2d def get_matches(self, x, y): R, G, B = self.rgb_mask[x, y, :] r_index = np.where(self.vertex_colors[:, 0] == R)[0] g_index = np.where(self.vertex_colors[:, 1] == G)[0] b_index = np.where(self.vertex_colors[:, 2] == B)[0] matches = [r_index, g_index, b_index] intersection = list(set(matches[0]).intersection(*matches)) return intersection def get_model_point(self): rows, cols, channels = np.where(self.rgb_mask > 0) x, y = int(np.mean(rows)), int(np.mean(cols)) R, G, B = self.rgb_mask[x, y, 0], self.rgb_mask[x, y, 1], self.rgb_mask[x, y, 2] x_index = np.where(self.vertex_colors == np.stack([R, G, B]))[0] mid_index = int(len(x_index) / 2) return self.mesh.vertices[x_index[mid_index], :] def compute_camera_matrix(self): focal_length = self.size[1] camera_center = (self.size[1] / 2, self.size[0] / 2) camera_matrix = np.array([[focal_length, 0, camera_center[0]], [0, focal_length, camera_center[1]], [0, 0, 1]], dtype='double') camera = Camera(0) camera.intrinsics = camera_matrix camera.distortion = np.zeros((4, 1)) return camera def draw_axis(self, mask, projected_points, thickness=2): rows, cols, channels = np.where(mask > 0) x, y = (int(np.mean(rows)), int(np.mean(cols))) center = (y, x) image = mask.copy() R, G, B = (255, 0, 0), (0, 255, 0), (0, 0, 255) projected_points = projected_points.astype(np.int32) image = cv2.line(image, center, tuple(projected_points[0].ravel()), R, thickness) image = cv2.line(image, center, tuple(projected_points[1].ravel()), G, thickness) image = cv2.line(image, center, tuple(projected_points[2].ravel()), B, thickness) return image def get_neighbors(self, image, row, col, window=1): neighbor = image[row - window : row + window + 1, col - window : col + window + 1] color_values = np.reshape(neighbor, (9, 3)) return color_values
2.3125
2
MLSD/Transformers/Text_Transformers.py
HaoranXue/Machine_Learning_For_Structured_Data
4
12790131
<filename>MLSD/Transformers/Text_Transformers.py import numpy as np import pandas as pd from sklearn.base import TransformerMixin from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer class BasicText(TransformerMixin): def __init__(self, Dreduction= None, *args,**kwargs): self.Dreduction = Dreduction def fit(self, X, y =None): self.trans = CountVectorizer(*args,**kwargs) self.TFid = TfidfTransformer() self.trans.fit(X.values) self.TFid.fit(self.trans.fit_transform(X.values).toarray()) def transform(self,X): self.features = pd.DataFrame(self.TFid.transform(X.values), index=X.index) return self.features
2.90625
3
glycan_profiling/output/annotate_spectra.py
mstim/glycresoft
0
12790132
<gh_stars>0 import os import logging import string import platform from glycan_profiling import serialize from glycan_profiling.serialize import ( Protein, Glycopeptide, IdentifiedGlycopeptide, func, MSScan, GlycopeptideSpectrumMatch) from glycan_profiling.task import TaskBase from glycan_profiling.serialize import DatabaseBoundOperation from glycan_profiling.chromatogram_tree import Unmodified from glycan_profiling.tandem.ref import SpectrumReference from glycan_profiling.tandem.glycopeptide.scoring import CoverageWeightedBinomialModelTree from glycan_profiling.plotting import figure from glycan_profiling.plotting.sequence_fragment_logo import glycopeptide_match_logo from glycan_profiling.plotting.spectral_annotation import TidySpectrumMatchAnnotator from ms_deisotope.output.mzml import ProcessedMzMLDeserializer from matplotlib import pyplot as plt, style from matplotlib import rcParams as mpl_params status_logger = logging.getLogger("glycresoft.status") def format_filename(s): """Take a string and return a valid filename constructed from the string. Uses a whitelist approach: any characters not present in valid_chars are removed. Also spaces are replaced with underscores. """ valid_chars = "-_.() %s%s" % (string.ascii_letters, string.digits) filename = ''.join(c for c in s if c in valid_chars) filename = filename.replace(' ', '_') return filename class SpectrumAnnotatorExport(TaskBase, DatabaseBoundOperation): def __init__(self, database_connection, analysis_id, output_path, mzml_path=None): DatabaseBoundOperation.__init__(self, database_connection) self.analysis_id = analysis_id self.mzml_path = mzml_path self.output_path = output_path self.analysis = self.session.query(serialize.Analysis).get(self.analysis_id) self.scan_loader = None self._mpl_style = { 'figure.facecolor': 'white', 'figure.edgecolor': 'white', 'font.size': 10, 'savefig.dpi': 72, 'figure.subplot.bottom': .125 } def _make_scan_loader(self): if self.mzml_path is not None: if not os.path.exists(self.mzml_path): raise IOError("No such file {}".format(self.mzml_path)) self.scan_loader = ProcessedMzMLDeserializer(self.mzml_path) else: self.mzml_path = self.analysis.parameters['sample_path'] if not os.path.exists(self.mzml_path): raise IOError(( "No such file {}. If {} was relocated, you may need to explicily pass the" " corrected file path.").format( self.mzml_path, self.database_connection._original_connection)) self.scan_loader = ProcessedMzMLDeserializer(self.mzml_path) return self.scan_loader def _load_spectrum_matches(self): query = self.query(GlycopeptideSpectrumMatch).join( GlycopeptideSpectrumMatch.scan).filter( GlycopeptideSpectrumMatch.analysis_id == self.analysis_id).order_by( MSScan.index) return query.all() def run(self): scan_loader = self._make_scan_loader() gpsms = self._load_spectrum_matches() if not os.path.exists(self.output_path): os.makedirs(self.output_path) n = len(gpsms) self.log("%d Spectrum Matches" % (n,)) for i, gpsm in enumerate(gpsms): scan = scan_loader.get_scan_by_id(gpsm.scan.scan_id) gpep = gpsm.structure.convert() if i % 10 == 0: self.log("... %0.2f%%: %s @ %s" % (((i + 1) / float(n) * 100.0), gpep, scan.id)) with style.context(self._mpl_style): fig = figure() grid = plt.GridSpec(nrows=5, ncols=1) ax1 = fig.add_subplot(grid[1, 0]) ax2 = fig.add_subplot(grid[2:, 0]) ax3 = fig.add_subplot(grid[0, 0]) match = CoverageWeightedBinomialModelTree.evaluate(scan, gpep) ax3.text(0, 0.5, ( str(match.target) + '\n' + scan.id + '\nscore=%0.3f q value=%0.3g' % (gpsm.score, gpsm.q_value)), va='center') ax3.axis('off') match.plot(ax=ax2) glycopeptide_match_logo(match, ax=ax1) fname = format_filename("%s_%s.pdf" % (scan.id, gpep)) path = os.path.join(self.output_path, fname) abspath = os.path.abspath(path) if len(abspath) > 259 and platform.system().lower() == 'windows': abspath = '\\\\?\\' + abspath fig.savefig(abspath, bbox_inches='tight') plt.close(fig)
2.203125
2
payloadcode/phototest.py
debragail/n3m0
21
12790133
print "Here we go!" # Import DroneKit-Python from dronekit import connect, VehicleMode, LocationGlobalRelative, LocationGlobal from pymavlink import mavutil # Needed for command message definitions from picamera import PiCamera import time import math import requests # Connect to the Vehicle. print("\nConnecting to vehicle") #vehicle = connect(/dev/ttyACM0, wait_ready=True) # pixhawk usb #vehicle = connect("/dev/ttyUSB0", wait_ready='armed', baud=57600) # telemetry usb #vehicle = connect("/dev/ttyUSB0", baud=57600) # telemetry usb vehicle = connect("/dev/ttyS0", baud=57600) # telemetry usb # Using the ``wait_ready(True)`` waits on :py:attr:`parameters`, :py:attr:`gps_0`, # :py:attr:`armed`, :py:attr:`mode`, and :py:attr:`attitude`. In practice this usually # means that all supported attributes will be populated. # 'parameters' #vehicle.wait_ready('gps_0','armed','mode','attitude') vehicle.wait_ready('gps_0') # Get some vehicle attributes (state) print "Get some vehicle attribute values:" print " GPS: %s" % vehicle.gps_0 print " Battery: %s" % vehicle.battery print " Last Heartbeat: %s" % vehicle.last_heartbeat print " Is Armable?: %s" % vehicle.is_armable print " System status: %s" % vehicle.system_status.state print " Mode: %s" % vehicle.mode.name # settable # class to hold info for courses, states, etc. class PhotoStuff: ## Photo point (where to take photo) point1 = LocationGlobalRelative(38.0, -122.0, 0) ## current location lat = 38.06807841429639 lon = -122.23280310630798 mode='none' message = 'no msg' Photoing = False time_to_quit = False ## picture data getpix = False plat=0 plon=0 pmode='none' pmsg = 'no message' camera = PiCamera() def update_n3m0_location(self): ## update the boat location r=requests.post('http://sailbot.holdentechnology.com/postlatlon.php',data={'b_no':1,'lat':myPhoto.lat,'lon':myPhoto.lon,'mode':myPhoto.mode,'debug':myPhoto.message}) #print(r.text) def get_pic_requests(self): ## get data r2 = requests.get('http://sailbot.holdentechnology.com/getbuoys.php') thedata=r2.text.split(';') myPhoto.plat=float(thedata[8]) myPhoto.plon=float(thedata[9]) myPhoto.pmode = thedata[10] myPhoto.pmsg = thedata[11] if (str(myPhoto.pmode).find("REQUESTED") >= 0): # new request, acknowledge. r=requests.post('http://sailbot.holdentechnology.com/postlatlon.php',data={ 'b_no':2,'lat':myPhoto.plat,'lon':myPhoto.plon,'mode':"n3m0 Received",'debug':"need auth"}) def take_photo(self, w,h, filename): print('taking photo') print filename self.camera.resolution = (w, h) #self.camera.resolution = (1920, 1080) #self.camera.resolution = (640, 480) self.camera.start_preview() #time.sleep(2) self.camera.capture(filename) self.camera.stop_preview() print('photo taken') def post_photo(self,filename, newname): print ('posting photo') url = 'http://sailbot.holdentechnology.com/upload.php' #url = 'http://httpbin.org/post' data={'submit':'Submit','name':'fileToUpload','id':'fileToUpload'} files = {'fileToUpload': (newname, open(filename, 'rb'))} rr = requests.post(url, data=data, files=files) print rr.text print('photo posted') def deliver_photo(self,filename): myPhoto.pmode = "Finished<br>" + time.strftime("%Y-%m-%d %H:%M:%S") #myPhoto.pmsg = "<a href=\"uploads/"+filename+"\"><img src=\"uploads/" + filename + "\" height=50 ></a>" myPhoto.pmsg = "uploads/" + filename r=requests.post('http://sailbot.holdentechnology.com/insertlatlon.php',data={'b_no':2,'lat':myPhoto.plat,'lon':myPhoto.plon,'mode':myPhoto.pmode,'debug':myPhoto.pmsg}) print "should be guided now",myPhoto.get_distance_meters(myPhoto.point1,vehicle.location.global_relative_frame) print myPhoto.pmsg #myPhoto.time_to_quit=True myPhoto.pmode = "DONE" myPhoto.pmsg = "Ready for new request" + time.strftime(" %Y-%m-%d %H:%M:%S") r=requests.post('http://sailbot.holdentechnology.com/postlatlon.php',data={'b_no':2,'lat':myPhoto.plat,'lon':myPhoto.plon,'mode':myPhoto.pmode,'debug':myPhoto.pmsg}) def get_location_meters(self,original_location, dNorth, dEast): """ Returns a LocationGlobal object containing the latitude/longitude `dNorth` and `dEast` metres from the specified `original_location`. The returned LocationGlobal has the same `alt` value as `original_location`. The function is useful when you want to move the vehicle around specifying locations relative to the current vehicle position. The algorithm is relatively accurate over small distances (10m within 1km) except close to the poles. For more information see: http://gis.stackexchange.com/questions/2951/algorithm-for-offsetting-a-latitude-longitude-by-some-amount-of-meters """ earth_radius = 6378137.0 #Radius of "spherical" earth #Coordinate offsets in radians dLat = dNorth/earth_radius dLon = dEast/(earth_radius*math.cos(math.pi*original_location.lat/180)) #New position in decimal degrees newlat = original_location.lat + (dLat * 180/math.pi) newlon = original_location.lon + (dLon * 180/math.pi) print("llatlon" ) if type(original_location) is LocationGlobal: targetlocation=LocationGlobal(newlat, newlon,original_location.alt) elif type(original_location) is LocationGlobalRelative: targetlocation=LocationGlobalRelative(newlat, newlon,original_location.alt) else: raise Exception("Invalid Location object passed") return targetlocation; def get_distance_meters(self, aLocation1, aLocation2): """ Returns the ground distance in metres between two LocationGlobal objects. This method is an approximation, and will not be accurate over large distances and close to the earth's poles. It comes from the ArduPilot test code: https://github.com/diydrones/ardupilot/blob/master/Tools/autotest/common.py """ dlat = aLocation2.lat - aLocation1.lat dlong = aLocation2.lon - aLocation1.lon return math.sqrt((dlat*dlat) + (dlong*dlong)) * 1.113195e5 def get_bearing(self, aLocation1, aLocation2): """ Returns the bearing between the two LocationGlobal objects passed as parameters. This method is an approximation, and may not be accurate over large distances and close to the earth's poles. It comes from the ArduPilot test code: https://github.com/diydrones/ardupilot/blob/master/Tools/autotest/common.py """ off_x = aLocation2.lon - aLocation1.lon off_y = aLocation2.lat - aLocation1.lat bearing = 90.00 + math.atan2(-off_y, off_x) * 57.2957795 if bearing < 0: bearing += 360.00 return bearing; myPhoto = PhotoStuff() # Callback when location has changed. 'value' is the updated value # Mode changing done here. # myPhoto.Photoing is True when we are heading for a picture point # also saves current location into myPhoto variables. def location_callback(self, attr_name, value): #print "Location: ", value ## store data myPhoto.lat = vehicle.location.global_relative_frame.lat myPhoto.lon = vehicle.location.global_relative_frame.lon myPhoto.mode = str(vehicle.mode.name) ## check for reaching picture waypoint dist = myPhoto.get_distance_meters(myPhoto.point1,vehicle.location.global_relative_frame) # if reached photo point: take photo, return to auto mode. if (dist <= 3.0) and (myPhoto.Photoing): # waits until we reach photo point, takes photo #if (myPhoto.Photoing): # use for bench testing, immediately takes photo. print "Picture!", dist # take photo myPhoto.take_photo(1920, 1080,'/home/pi/Desktop/cap.jpg') # exit guided mode myPhoto.Photoing = False # post photo fname='n3m0_' + time.strftime("%Y%m%d-%H%M%S") + '.jpg' myPhoto.post_photo('/home/pi/Desktop/cap.jpg',fname) myPhoto.deliver_photo(fname) # continuously check to see if we need to change modes # if guided flag set but not guided mode: do guided mode. if myPhoto.Photoing: myPhoto.mode = str(dist) if (str(vehicle.mode.name).find("GUIDED") < 0): # not guided myPhoto.point1.lat = myPhoto.plat myPhoto.point1.lon = myPhoto.plon vehicle.mode = VehicleMode("GUIDED") vehicle.simple_goto(myPhoto.point1) print "guided mode again: ", str(vehicle.mode.name) else: # guided flag not set if (str(vehicle.mode.name).find("GUIDED") >= 0): # guided, return to auto mode. vehicle.mode = VehicleMode("AUTO") print "End guided mode ", str(vehicle.mode.name) #Callback to monitor mode changes. 'value' is the updated value # If mode changes to "steering" start autonomous action (picture) # any other mode change cancels autonomous function through this code def mode_callback(self, attr_name, value): print "Mode: ", value if str(value).find("STEERING") >=0: myPhoto.Photoing = True myPhoto.pmode = "UNDERWAY" myPhoto.pmsg = "n3m0 received request" + time.strftime(" %Y-%m-%d %H:%M:%S") r=requests.post('http://sailbot.holdentechnology.com/postlatlon.php',data={'b_no':2,'lat':myPhoto.plat,'lon':myPhoto.plon,'mode':myPhoto.pmode,'debug':myPhoto.pmsg}) print "should be guided now",myPhoto.get_distance_meters(myPhoto.point1,vehicle.location.global_relative_frame) else: if str(value).find("GUIDED") < 0: #not changed to guided mode myPhoto.Photoing = False #let us go back to manual or RTL etc print("new mode set, Photoing off") # Add a callback `location_callback` for the `global_frame` attribute. vehicle.add_attribute_listener('location.global_frame', location_callback) vehicle.add_attribute_listener('mode', mode_callback) # Loop, interrupts are running things now. while not myPhoto.time_to_quit: time.sleep(4) print myPhoto.get_distance_meters(myPhoto.point1,vehicle.location.global_relative_frame) # getting parameters is a little buggy #print "Param: %s" % vehicle.parameters['WP_RADIUS'] myPhoto.message = time.strftime("%Y-%m-%d %H:%M:%S ") + str(vehicle.battery) + " " + str(vehicle.gps_0) myPhoto.mode = str(vehicle.mode.name) myPhoto.update_n3m0_location() myPhoto.message = " " myPhoto.mode = " " myPhoto.take_photo(640,480,'/home/pi/Desktop/testcap.jpg') myPhoto.post_photo('/home/pi/Desktop/testcap.jpg','tphoto.jpg') #fname='Tn3m0_' + time.strftime("%Y%m%d-%H%M%S") + '.jpg' #myPhoto.post_photo('/home/pi/Desktop/testcap.jpg',fname) #myPhoto.time_to_quit=True myPhoto.get_pic_requests() # Remove observer - specifying the attribute and previously registered callback function vehicle.remove_message_listener('location.global_frame', location_callback) vehicle.remove_message_listener('mode', mode_callback) # Close vehicle object before exiting script vehicle.close() print("Completed")
2.953125
3
examples/entities/pdfunderlay.py
jpsantos-mf/ezdxf
1
12790134
# Copyright (c) 2016-2019 <NAME> # License: MIT License import ezdxf dwg = ezdxf.new('R2000') # underlay requires the DXF R2000 format or newer pdf_underlay_def = dwg.add_underlay_def(filename='underlay.pdf', name='1') # name = page to display dwf_underlay_def = dwg.add_underlay_def(filename='underlay.dwf', name="Underlay_R2013-Model") # don't know how to get this name dgn_underlay_def = dwg.add_underlay_def(filename='underlay.dgn', name='default') # name = 'default' just works # The (PDF)DEFINITION entity is like a block definition, it just defines the underlay msp = dwg.modelspace() # add first underlay msp.add_underlay(pdf_underlay_def, insert=(0, 0, 0), scale=1.) # The (PDF)UNDERLAY entity is like the INSERT entity, it creates an underlay reference, # and there can be multiple references to the same underlay in a drawing. msp.add_underlay(pdf_underlay_def, insert=(10, 0, 0), scale=.5, rotation=30) # use dgn format msp.add_underlay(dgn_underlay_def, insert=(0, 30, 0), scale=1.) # use dwf format msp.add_underlay(dwf_underlay_def, insert=(0, 15, 0), scale=1.) # get existing underlay definitions, Important: UNDERLAYDEFs resides in the objects section pdf_defs = dwg.objects.query('PDFDEFINITION') # get all pdf underlay defs in drawing dwg.saveas("underlay.dxf")
2.765625
3
setup.py
krazybean/pybusy
0
12790135
<filename>setup.py """ Cursor glamor prettiness for bash """ from setuptools import setup, find_packages from codecs import open from os import path here = path.abspath(path.dirname(__file__)) with open(path.join(here, 'README.md'), encoding='utf-8') as f: long_description = f.read() setup( name='pybusy', version='0.0.1', description='Bash progress decoration', long_description=long_description, long_description_content_type='text/markdown', url='https://github.com/krazybean/pybusy', author='krazybean', author_email='<EMAIL>', classifiers=[ 'Development Status :: 1 - Pre-Alpha', 'Intended Audience :: Developers', 'Topic :: Software Development :: Build Tools', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ], keywords='python3 bash progress', packages=find_packages(exclude=['contrib', 'docs', 'tests']), install_requires=['cursor', 'ansicolors'] )
1.5625
2
discovery-provider/src/queries/get_remix_track_parents.py
mikedotexe/audius-protocol
1
12790136
<reponame>mikedotexe/audius-protocol<filename>discovery-provider/src/queries/get_remix_track_parents.py from sqlalchemy import desc, and_ from src.models import Track, Remix from src.utils import helpers from src.utils.db_session import get_db_read_replica from src.queries.query_helpers import get_current_user_id, populate_track_metadata, \ paginate_query, add_users_to_tracks def get_remix_track_parents(track_id, args): db = get_db_read_replica() with db.scoped_session() as session: base_query = ( session.query(Track) .join( Remix, and_( Remix.parent_track_id == Track.track_id, Remix.child_track_id == track_id ) ) .filter( Track.is_current == True, Track.is_unlisted == False ) .order_by( desc(Track.created_at), desc(Track.track_id) ) ) tracks = paginate_query(base_query).all() tracks = helpers.query_result_to_list(tracks) track_ids = list(map(lambda track: track["track_id"], tracks)) current_user_id = get_current_user_id(required=False) tracks = populate_track_metadata(session, track_ids, tracks, current_user_id) if args.get("with_users", False): add_users_to_tracks(session, tracks) return tracks
2.125
2
answerer/query.py
apricis/erudite
0
12790137
import re import string class Reformulator(object): def __init__(self, question, qclass, lang='en', stopwords=None): self.__original_question = question punctuation = re.sub(r"[-+/&']", '', string.punctuation) self.__punctuation_re = r'[{}]'.format(punctuation) question = question[0].lower() + question[1:] question = re.sub(r'(?<=[A-Z])\.', 'QQQ', question) question = re.sub(self.__punctuation_re, '', question) self.__question = re.sub(r'QQQ', '.', question) self.__stopwords = stopwords self.__qclass = qclass.split(':')[1] if lang == 'en': question_words = ['what', 'which', 'who', 'whom', 'when', 'where', 'why', 'how'] conj_prep_words = ['of', 'not'] elif lang == 'sv': question_words = ['vilket', 'vilken', 'vem', 'whom', 'när', 'var', 'varför', 'hur'] conj_prep_words = ['av', 'inte', 'ej'] else: raise NotImplemented('This language is not available') self.__exact_stop_words = set(stopwords) - set(conj_prep_words) self.__expansion_rules = { 'dismed': 'disease', 'instru': 'instrument', 'lang': 'language', 'other': '', 'techmeth': 'technique', 'termeq': 'term', 'veh': 'vehicle', 'dist': 'distance', 'ord': 'order', 'perc': 'percentage', 'speed': 'speed', 'temp': 'temperature', 'volsize': 'size' } if qclass == 'ABBR:abb': try: self.__stopwords.append('abbreviation') except: self.__stopwords.add('abbreviation') self.__exact_stop_words.append('abbreviation') def question(self): return self.__question def reformulate(self): without_stopwords = [w for w in self.__question.split() if w not in self.__stopwords] query = without_stopwords query.append(self.__expansion_rules.get(self.__qclass, '')) return " ".join(query) def reformulate_exact(self): without_exact_stopwords = [w for w in self.__question.split() if w not in self.__exact_stop_words] query = without_exact_stopwords query.append(self.__expansion_rules.get(self.__qclass, '')) return " ".join(query)
2.9375
3
example.py
ipconfiger/result2
4
12790138
<filename>example.py #coding=utf8 from result2 import Result, Ok, Err def get_valid_user_by_email(email): """ Return user instance """ user = get_user(email) if user: if user.valid is False: return Err("user not valid") return Ok(user) return Err("user not exists") result = user = get_user_by_email('<EMAIL>') if result == Result.Ok: # do something if user exists ... else: # to create new user page with reason
3.125
3
restApi/helpers/ride_helpers.py
Kitingu/restplus
0
12790139
<reponame>Kitingu/restplus import datetime from flask_restplus import reqparse class RideParser: parser = reqparse.RequestParser() parser.add_argument('start_point', type=str, required=True, location='json', help="Please enter a valid starting point") parser.add_argument('destination', type=str, required=True, location='json', help="This field cannot be blank") parser.add_argument('seats_available', type=int, required=True, location='json', help="This field cannot be blank") parser.add_argument('date', type=lambda x: datetime.datetime.strptime(x, '%d/%m/%Y').strftime('%d/%m/%Y'), required=True, location='json', help="please enter a valid date using format") parser.add_argument('time', type=lambda x: datetime.datetime.strptime(x, '%H:%M').strftime('%H:%M'), required=True, location='json', help="Use 24 hour clock system")
2.953125
3
scapy/scapy-arp_request.py
all3g/pieces
34
12790140
<reponame>all3g/pieces<gh_stars>10-100 #!/usr/bin/env python # -*- coding: utf8 -*- from scapy.all import * import logging import threading import Queue logging.basicConfig(level=logging.DEBUG, format='[*] %(name)s - %(message)s') logger = logging.getLogger('arpscanner') # disable scapy verbose mode conf.verb = 0 # disable scapy warning logging.getLogger("scapy.runtime").setLevel(logging.ERROR) def arpscanner(iplist, lock): """Scan internal mac addresses""" while 1: try: lock.acquire() ip = iplist.get_nowait() lock.release() # create a ether object ether = Ether(type=0x0806) # create a arp object arp = ARP(op=1, hwdst='ff:ff:ff:ff:ff:ff', pdst=ip) # send arp request and receive response arpres = srp1(ether/arp, timeout=0.05) if arpres and arpres.haslayer('ARP'): logger.info('%s \t %s' % (ip, arpres['ARP'].hwsrc)) else: logger.debug('%s \t %s' % (ip, None)) except Queue.Empty: lock.release() break return if __name__ == "__main__": iplist = Queue.Queue() lock = threading.Lock() for i in range(1, 255, 1): ip = "192.168.1.%s" % i iplist.put(ip) for n in range(30): t = threading.Thread(target=arpscanner, args=(iplist, lock)) t.start()
2.328125
2
src/third_party/swiftshader/third_party/subzero/pydir/run-pnacl-sz.py
rhencke/engine
2,151
12790141
#!/usr/bin/env python2 import argparse import itertools import os import re import subprocess import sys import tempfile from utils import FindBaseNaCl, GetObjdumpCmd, shellcmd def TargetAssemblerFlags(target, sandboxed): # TODO(reed kotler). Need to find out exactly we need to # add here for Mips32. flags = { 'x8632': ['-triple=%s' % ('i686-nacl' if sandboxed else 'i686')], 'x8664': ['-triple=%s' % ( 'x86_64-nacl' if sandboxed else 'x86_64')], 'arm32': ['-triple=%s' % ( 'armv7a-nacl' if sandboxed else 'armv7a'), '-mcpu=cortex-a9', '-mattr=+neon'], 'mips32': ['-triple=%s' % ( 'mipsel-nacl' if sandboxed else 'mipsel'), '-mcpu=mips32'] } return flags[target] def TargetDisassemblerFlags(target): flags = { 'x8632': ['-Mintel'], 'x8664': ['-Mintel'], 'arm32': [], 'mips32':[] } return flags[target] def main(): """Run the pnacl-sz compiler on an llvm file. Takes an llvm input file, freezes it into a pexe file, converts it to a Subzero program, and finally compiles it. """ argparser = argparse.ArgumentParser( description=' ' + main.__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter) argparser.add_argument('--input', '-i', required=True, help='LLVM source file to compile') argparser.add_argument('--output', '-o', required=False, help='Output file to write') argparser.add_argument('--insts', required=False, action='store_true', help='Stop after translating to ' + 'Subzero instructions') argparser.add_argument('--no-local-syms', required=False, action='store_true', help="Don't keep local symbols in the pexe file") argparser.add_argument('--llvm', required=False, action='store_true', help='Parse pexe into llvm IR first, then ' + 'convert to Subzero') argparser.add_argument('--llvm-source', required=False, action='store_true', help='Parse source directly into llvm IR ' + '(without generating a pexe), then ' + 'convert to Subzero') argparser.add_argument( '--pnacl-sz', required=False, default='./pnacl-sz', metavar='PNACL-SZ', help="Subzero translator 'pnacl-sz'") argparser.add_argument('--pnacl-bin-path', required=False, default=( '{root}/toolchain/linux_x86/pnacl_newlib_raw/bin' ).format(root=FindBaseNaCl()), metavar='PNACL_BIN_PATH', help='Path to LLVM & Binutils executables ' + '(e.g. for building PEXE files)') argparser.add_argument('--assemble', required=False, action='store_true', help='Assemble the output') argparser.add_argument('--disassemble', required=False, action='store_true', help='Disassemble the assembled output') argparser.add_argument('--dis-flags', required=False, action='append', default=[], help='Add a disassembler flag') argparser.add_argument('--filetype', default='iasm', dest='filetype', choices=['obj', 'asm', 'iasm'], help='Output file type. Default %(default)s') argparser.add_argument('--forceasm', required=False, action='store_true', help='Force --filetype=asm') argparser.add_argument('--target', default='x8632', dest='target', choices=['x8632','x8664','arm32','mips32'], help='Target architecture. Default %(default)s') argparser.add_argument('--echo-cmd', required=False, action='store_true', help='Trace command that generates ICE instructions') argparser.add_argument('--tbc', required=False, action='store_true', help='Input is textual bitcode (not .ll)') argparser.add_argument('--expect-fail', required=False, action='store_true', help='Negate success of run by using LLVM not') argparser.add_argument('--allow-pnacl-reader-error-recovery', action='store_true', help='Continue parsing after first error') argparser.add_argument('--args', '-a', nargs=argparse.REMAINDER, default=[], help='Remaining arguments are passed to pnacl-sz') argparser.add_argument('--sandbox', required=False, action='store_true', help='Sandboxes the generated code') args = argparser.parse_args() pnacl_bin_path = args.pnacl_bin_path llfile = args.input if args.llvm and args.llvm_source: raise RuntimeError("Can't specify both '--llvm' and '--llvm-source'") if args.llvm_source and args.no_local_syms: raise RuntimeError("Can't specify both '--llvm-source' and " + "'--no-local-syms'") if args.llvm_source and args.tbc: raise RuntimeError("Can't specify both '--tbc' and '--llvm-source'") if args.llvm and args.tbc: raise RuntimeError("Can't specify both '--tbc' and '--llvm'") if args.forceasm: if args.expect_fail: args.forceasm = False elif args.filetype == 'asm': pass elif args.filetype == 'iasm': # TODO(sehr) implement forceasm for iasm. pass elif args.filetype == 'obj': args.filetype = 'asm' args.assemble = True cmd = [] if args.tbc: cmd = [os.path.join(pnacl_bin_path, 'pnacl-bcfuzz'), llfile, '-bitcode-as-text', '-output', '-', '|'] elif not args.llvm_source: cmd = [os.path.join(pnacl_bin_path, 'llvm-as'), llfile, '-o', '-', '|', os.path.join(pnacl_bin_path, 'pnacl-freeze')] if not args.no_local_syms: cmd += ['--allow-local-symbol-tables'] cmd += ['|'] if args.expect_fail: cmd += [os.path.join(pnacl_bin_path, 'not')] cmd += [args.pnacl_sz] cmd += ['--target', args.target] if args.sandbox: cmd += ['-sandbox'] if args.insts: # If the tests are based on '-verbose inst' output, force # single-threaded translation because dump output does not get # reassembled into order. cmd += ['-verbose', 'inst,global_init', '-notranslate', '-threads=0'] elif args.allow_pnacl_reader_error_recovery: cmd += ['-allow-pnacl-reader-error-recovery', '-threads=0'] if not args.llvm_source: cmd += ['--bitcode-format=pnacl'] if not args.no_local_syms: cmd += ['--allow-local-symbol-tables'] if args.llvm or args.llvm_source: cmd += ['--build-on-read=0'] else: cmd += ['--build-on-read=1'] cmd += ['--filetype=' + args.filetype] cmd += ['--emit-revision=0'] script_name = os.path.basename(sys.argv[0]) for _, arg in enumerate(args.args): # Redirecting the output file needs to be done through the script # because forceasm may introduce a new temporary file between pnacl-sz # and llvm-mc. Similar issues could occur when setting filetype, target, # or sandbox through --args. Filter and report an error. if re.search('^-?-(o|output|filetype|target|sandbox)(=.+)?$', arg): preferred_option = '--output' if re.search('^-?-o(=.+)?$', arg) else arg print 'Option should be set using:' print ' %s ... %s ... --args' % (script_name, preferred_option) print 'rather than:' print ' %s ... --args %s ...' % (script_name, arg) exit(1) asm_temp = None output_file_name = None keep_output_file = False if args.output: output_file_name = args.output keep_output_file = True cmd += args.args if args.llvm_source: cmd += [llfile] if args.assemble or args.disassemble: if not output_file_name: # On windows we may need to close the file first before it can be # re-opened by the other tools, so don't do delete-on-close, # and instead manually delete. asm_temp = tempfile.NamedTemporaryFile(delete=False) asm_temp.close() output_file_name = asm_temp.name if args.assemble and args.filetype != 'obj': cmd += (['|', os.path.join(pnacl_bin_path, 'llvm-mc')] + TargetAssemblerFlags(args.target, args.sandbox) + ['-filetype=obj', '-o', output_file_name]) elif output_file_name: cmd += ['-o', output_file_name] if args.disassemble: # Show wide instruction encodings, diassemble, show relocs and # dissasemble zeros. cmd += (['&&', os.path.join(pnacl_bin_path, GetObjdumpCmd(args.target))] + args.dis_flags + ['-w', '-d', '-r', '-z'] + TargetDisassemblerFlags(args.target) + [output_file_name]) stdout_result = shellcmd(cmd, echo=args.echo_cmd) if not args.echo_cmd: sys.stdout.write(stdout_result) if asm_temp and not keep_output_file: os.remove(output_file_name) if __name__ == '__main__': main()
2.609375
3
examples/svd.py
ravenSanstete/hako
1
12790142
<reponame>ravenSanstete/hako from .context import monad from .context import tangle from .context import feeder from .context import prototype from .context import magica from .context import hako from connectors import ml_100k_conn as conn ip='10.141.246.29'; port=27017; version='100k'; batch_size=100; connector=conn.MLConnector(ip,port,version); print(connector.feed_train_batch(batch_size)); #
1.585938
2
project_euler/101.py
huangshenno1/project_euler
0
12790143
<reponame>huangshenno1/project_euler from __future__ import division def u(n): ret = 0 for i in xrange(0, 11): ret += (-1)**i * n**i return ret def solve(k): a = [] for n in xrange(1, k+1): x = [n**x for x in xrange(0, k)] x.append(u(n)) a.append(x) for j in xrange(0, k): for i in xrange(0, k): if i == j: continue d = a[i][j] / a[j][j] for l in xrange(j, k+1): a[i][l] -= a[j][l] * d ret = 0 for i in xrange(0, k): ret += (a[i][k] / a[i][i]) * (k+1)**i return ret ans = sum(map(solve, xrange(1, 11))) print ans
2.484375
2
vasp-validator/tests/test_vasp_proxy_hook.py
tanshuai/reference-wallet
14
12790144
<reponame>tanshuai/reference-wallet # Copyright (c) The Diem Core Contributors # SPDX-License-Identifier: Apache-2.0 def test_tautology(): ...
1.070313
1
Part 2/Chapter 02/Programming projects/project_01.py
phuycke/Practice-of-computing-using-Python
1
12790145
<reponame>phuycke/Practice-of-computing-using-Python #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ @author: <NAME> email: <EMAIL> GitHub: phuycke """ #%% total_grains = 0 multiplier = 1 for i in range(1, 65): total_grains += multiplier multiplier *= 2 print('Total amount of wheat: {}'.format(total_grains)) #%% print('Weight of wheat (in tons): {}'.format(total_grains * 0.05 / 1000)) #%% # I don't understand question c
3.890625
4
nova/objects/volume_usage.py
bopopescu/nova-token
0
12790146
<filename>nova/objects/volume_usage.py begin_unit comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may' nl|'\n' comment|'# not use this file except in compliance with the License. You may obtain' nl|'\n' comment|'# a copy of the License at' nl|'\n' comment|'#' nl|'\n' comment|'# http://www.apache.org/licenses/LICENSE-2.0' nl|'\n' comment|'#' nl|'\n' comment|'# Unless required by applicable law or agreed to in writing, software' nl|'\n' comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT' nl|'\n' comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the' nl|'\n' comment|'# License for the specific language governing permissions and limitations' nl|'\n' comment|'# under the License.' nl|'\n' nl|'\n' name|'from' name|'nova' name|'import' name|'db' newline|'\n' name|'from' name|'nova' op|'.' name|'objects' name|'import' name|'base' newline|'\n' name|'from' name|'nova' op|'.' name|'objects' name|'import' name|'fields' newline|'\n' nl|'\n' nl|'\n' op|'@' name|'base' op|'.' name|'NovaObjectRegistry' op|'.' name|'register' newline|'\n' DECL|class|VolumeUsage name|'class' name|'VolumeUsage' op|'(' name|'base' op|'.' name|'NovaPersistentObject' op|',' name|'base' op|'.' name|'NovaObject' op|')' op|':' newline|'\n' comment|'# Version 1.0: Initial version' nl|'\n' DECL|variable|VERSION indent|' ' name|'VERSION' op|'=' string|"'1.0'" newline|'\n' nl|'\n' DECL|variable|fields name|'fields' op|'=' op|'{' nl|'\n' string|"'id'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'volume_id'" op|':' name|'fields' op|'.' name|'UUIDField' op|'(' op|')' op|',' nl|'\n' string|"'instance_uuid'" op|':' name|'fields' op|'.' name|'UUIDField' op|'(' name|'nullable' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'project_id'" op|':' name|'fields' op|'.' name|'StringField' op|'(' name|'nullable' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'user_id'" op|':' name|'fields' op|'.' name|'StringField' op|'(' name|'nullable' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'availability_zone'" op|':' name|'fields' op|'.' name|'StringField' op|'(' name|'nullable' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'tot_last_refreshed'" op|':' name|'fields' op|'.' name|'DateTimeField' op|'(' name|'nullable' op|'=' name|'True' op|',' nl|'\n' DECL|variable|read_only name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'tot_reads'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'tot_read_bytes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'tot_writes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'tot_write_bytes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'curr_last_refreshed'" op|':' name|'fields' op|'.' name|'DateTimeField' op|'(' name|'nullable' op|'=' name|'True' op|',' nl|'\n' DECL|variable|read_only name|'read_only' op|'=' name|'True' op|')' op|',' nl|'\n' string|"'curr_reads'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' op|')' op|',' nl|'\n' string|"'curr_read_bytes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' op|')' op|',' nl|'\n' string|"'curr_writes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' op|')' op|',' nl|'\n' string|"'curr_write_bytes'" op|':' name|'fields' op|'.' name|'IntegerField' op|'(' op|')' nl|'\n' op|'}' newline|'\n' nl|'\n' op|'@' name|'staticmethod' newline|'\n' DECL|member|_from_db_object name|'def' name|'_from_db_object' op|'(' name|'context' op|',' name|'vol_usage' op|',' name|'db_vol_usage' op|')' op|':' newline|'\n' indent|' ' name|'for' name|'field' name|'in' name|'vol_usage' op|'.' name|'fields' op|':' newline|'\n' indent|' ' name|'setattr' op|'(' name|'vol_usage' op|',' name|'field' op|',' name|'db_vol_usage' op|'[' name|'field' op|']' op|')' newline|'\n' dedent|'' name|'vol_usage' op|'.' name|'_context' op|'=' name|'context' newline|'\n' name|'vol_usage' op|'.' name|'obj_reset_changes' op|'(' op|')' newline|'\n' name|'return' name|'vol_usage' newline|'\n' nl|'\n' dedent|'' op|'@' name|'base' op|'.' name|'remotable' newline|'\n' DECL|member|save name|'def' name|'save' op|'(' name|'self' op|',' name|'update_totals' op|'=' name|'False' op|')' op|':' newline|'\n' indent|' ' name|'db_vol_usage' op|'=' name|'db' op|'.' name|'vol_usage_update' op|'(' nl|'\n' name|'self' op|'.' name|'_context' op|',' name|'self' op|'.' name|'volume_id' op|',' name|'self' op|'.' name|'curr_reads' op|',' nl|'\n' name|'self' op|'.' name|'curr_read_bytes' op|',' name|'self' op|'.' name|'curr_writes' op|',' name|'self' op|'.' name|'curr_write_bytes' op|',' nl|'\n' name|'self' op|'.' name|'instance_uuid' op|',' name|'self' op|'.' name|'project_id' op|',' name|'self' op|'.' name|'user_id' op|',' nl|'\n' name|'self' op|'.' name|'availability_zone' op|',' name|'update_totals' op|'=' name|'update_totals' op|')' newline|'\n' name|'self' op|'.' name|'_from_db_object' op|'(' name|'self' op|'.' name|'_context' op|',' name|'self' op|',' name|'db_vol_usage' op|')' newline|'\n' dedent|'' dedent|'' endmarker|'' end_unit
1.804688
2
misc/python/materialize/zippy/source_capabilities.py
bobbyiliev/materialize
1
12790147
# Copyright Materialize, Inc. and contributors. All rights reserved. # # Use of this software is governed by the Business Source License # included in the LICENSE file at the root of this repository. # # As of the Change Date specified in that file, in accordance with # the Business Source License, use of this software will be governed # by the Apache License, Version 2.0. from typing import Optional from materialize.zippy.framework import Capability from materialize.zippy.kafka_capabilities import TopicExists from materialize.zippy.watermarks import Watermarks class SourceExists(Capability): def __init__(self, name: str, topic: Optional[TopicExists] = None) -> None: self.name = name self.topic = topic def get_watermarks(self) -> Watermarks: assert self.topic is not None return self.topic.watermarks
1.867188
2
main.py
gbuenoandrade/Integralization-Simulator---Unicamp
0
12790148
<reponame>gbuenoandrade/Integralization-Simulator---Unicamp import numpy as np import matplotlib.pyplot as plt class Course: def __init__(self): self.name = '' self.type = '' self.credits = 0 self.grade = 0.0 self.sem = '' def __str__(self): return self.name + ' ' + self.type + ' ' + str(self.credits) + ' ' + str(self.grade) def parseFromFile(fname): def parseRevClass(v): c = Course() c.name = v.pop() if len(c.name) == 1: c.name += ' ' + v.pop() crd = v.pop() if len(crd) == 1: crd = v.pop() c.credits = int(crd) c.type = v.pop() if len(c.type) != 1: #it doesn't count for i in range(3): v.pop() if len(v) != 0: return parseRevClass(v) else: return [] try: grd = list(v.pop()) for i in range(len(grd)): if grd[i] == ',': grd[i] = '.' break grd = ''.join(grd) c.grade = float(grd) except ValueError: for i in range(3): v.pop() if len(v) != 0: return parseRevClass(v) else: return [] for i in range(2): v.pop() c.sem = v.pop() if len(v) != 0: return [c] + parseRevClass(v) else: return [c] with open(fname) as f: content = f.readlines() content = [line.strip() for line in content] ans = [] for line in content: ret = parseRevClass(line.split()[::-1]) ans += ret return ans courses = [] def addNewCourse(name, credits, grade, sem): c = Course() c.name = name c.credits = int(credits) c.grade = float(grade) c.sem = sem courses.append(c) def getCR(): return getCRUntil('2S3016') def getCRUntil(sem): num = 0.0 den = 0 pr = int(sem[0]) year = int(sem[2:]) for c in courses: cpr = int(c.sem[0]) cyear = int(c.sem[2:]) if cyear < year or (cyear == year and cpr <= pr): num += c.grade*c.credits den += c.credits cr = num/den/10 return cr def getSemCR(sem): num = 0.0 den = 0 pr = int(sem[0]) year = int(sem[2:]) for c in courses: cpr = int(c.sem[0]) cyear = int(c.sem[2:]) if cyear == year and cpr == pr: num += c.grade*c.credits den += c.credits cr = num/den/10 return cr def plot_charts(): year = 2012 pr = 1 labels = [] acc = [] partial = [] ignored = {'2S2015', '1S2016', '2S2018'} while year <= 2018: sem = str(pr) + 'S' + str(year) if sem not in ignored: cacc = getCRUntil(sem) cpartial = getSemCR(sem) print('%s: %.4f' % (sem, cacc)) labels.append(sem) acc.append(cacc) partial.append(cpartial) pr += 1 if pr == 3: pr = 1 year += 1 print(acc) print(partial) plt.plot(labels, acc) plt.plot(labels, partial) plt.legend(('Accumulated', 'Partial')) plt.xlabel('Semester') plt.ylabel('CR') plt.title('CR evolution') plt.show() def main(): global courses courses += parseFromFile('grades.txt') plot_charts() if __name__ == "__main__": main()
3.25
3
database/test_code/test_scrape_wiki_mysql.py
Coslate/NBA_Win_Predictor
0
12790149
#! /usr/bin/env python3.6 import pymysql import re import random import datetime import sys import argparse import os ######################### # Main-Routine # ######################### def main(): #Initialization print('> Crawler Initialization...') iter_num = 0 crawler_nba.init() #Argument Parser (password, table, max_sql_store_num, unix_socket, database_name) = ArgumentParser() #DB Initialization print('> DB Initialization...') crawler_nba.MySQLDBInitialize(password, table, unix_socket, database_name) #Sideband Setting current_time = datetime.datetime.now() print(f'current_time = {current_time}') random.seed(datetime.datetime.now()) starting_url = "https://en.wikipedia.org/wiki/Kevin_Bacon" print(f'starting_url = {starting_url}') # Scrape articles from Wikipedia and store into MySQl Database choose_link = starting_url skipping = 0 while(iter_num < max_sql_store_num): print('iter_num = {}. Get Wiki Links and store the content to MySQL...'.format(iter_num)) print(f'choose_link = {choose_link}') all_internal_links_loop, skipping = crawler_nba.GetWikiLinksContent(choose_link, crawler_nba.cur, table) total_num_internal_links_loop = len(all_internal_links_loop) if(total_num_internal_links_loop > 0): choose_link = "http://en.wikipedia.org"+all_internal_links_loop[random.randint(0, total_num_internal_links_loop-1)].attrs['href'] if(skipping == 0): iter_num += 1 # Test to read from MySQL Database sql_ex = 'SELECT id, title, created, LEFT(content, 32) FROM {table_name} WHERE id=4;'.format(table_name=table) crawler_nba.cur.execute(sql_ex) results = crawler_nba.cur.fetchall() print(f'-------------------Execution {sql_ex}-------------------') print(f'table = {table}') for row in results: id_name = str(row[0]) title_name = row[1] created_name = str(row[2]) content_name = row[3] print('{x:<2s}, {y:<2s}, {z:<2s}, {k:<2s}'.format(x=id_name, y=title_name, z=created_name, k=content_name)) # Close the connection of MySQL Database crawler_nba.MySQLDBClose(crawler_nba.cur, crawler_nba.conn) ######################### # Sub-Routine # ######################### def ArgumentParser(): password = "" table = "" database_name = "" unix_socket = "" max_sql_store_num = 10 parser = argparse.ArgumentParser() parser.add_argument("--mysql_password", "-sql_p", help="The password to connect to MySQL server.", required=True) parser.add_argument("--mysql_table_name", "-sql_tn", help="The table name that will be used to store data.", required=True) parser.add_argument("--max_sql_store_num", "-sql_mx_sn", help="The maximum number that stores in MySQL table.", required=True) parser.add_argument("--unix_socket", "-sql_un_sock", help="The unix_socket that is used to mypysql connection.", required=True) parser.add_argument("--database_name", "-database_name", help="The unix_socket that is used to mypysql connection.", required=True) args = parser.parse_args() if args.mysql_password: password = args.mysql_password if args.mysql_table_name: table = args.mysql_table_name if args.max_sql_store_num: max_sql_store_num = int(args.max_sql_store_num) if args.unix_socket: unix_socket = args.unix_socket if args.database_name: database_name = args.database_name return(password, table, max_sql_store_num, unix_socket, database_name) #-----------------Execution------------------# if __name__ == '__main__': import sys this_script_path = os.path.realpath(__file__) this_script_folder = os.path.dirname(this_script_path) crawler_nba_pkg_path = this_script_folder+'/../../crawler' print('Add to sys.path : {x}'.format(x=crawler_nba_pkg_path)) sys.path.append(crawler_nba_pkg_path) import package_crawler_nba.crawler_nba as crawler_nba print('Import package_crawler_nba successfully.') main()
2.875
3
reina/iv/__init__.py
SoumilShekdar/Reina
4
12790150
<filename>reina/iv/__init__.py<gh_stars>1-10 from .2sls import SieveTSLS
1.125
1