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{
"code": "def apply_option(self, cmd, option, active=True):\n return re.sub(r'{{{}\\:(?P<option>[^}}]*)}}'.format(option),\n '\\g<option>' if active else '', cmd)"
},
{
"code": "def make_local_static_report_files(self):\n for static, pkgdir in self.STATIC_FILES:\n shutil.copyfile(\n data_filename(static, pkgdir),\n os.path.join(self.directory, static)\n )\n if self.extra_css:\n shutil.copyfile(\n self.config.extra_css,\n os.path.join(self.directory, self.extra_css)\n )"
},
{
"code": "def format_filesize(size):\n for suffix in (\"bytes\", \"KB\", \"MB\", \"GB\", \"TB\"):\n if size < 1024.0:\n if suffix in (\"GB\", \"TB\"):\n return \"{0:3.2f} {1}\".format(size, suffix)\n else:\n return \"{0:3.1f} {1}\".format(size, suffix)\n size /= 1024.0"
},
{
"code": "def add_lexicon_ref(self, lrid, name, lrtype, url, lexicon_id,\n lexicon_name, datcat_id=None, datcat_name=None):\n self.lexicon_refs[lrid] = {\n 'LEX_REF_ID': lrid,\n 'NAME': name,\n 'TYPE': lrtype,\n 'URL': url,\n 'LEXICON_ID': lexicon_id,\n 'LEXICON_NAME': lexicon_name,\n 'DATCAT_ID': datcat_id,\n 'DATCAT_NAME': datcat_name\n }"
},
{
"code": "def invert_hash(self, tok_hash):\n return [tok_encoded.decode('utf8')\n for (_, tok_encoded) in\n self.client.scan_keys(HASH_KEYWORD_INDEX_TABLE,\n ((tok_hash,), (tok_hash,)))]"
},
{
"code": "def find_unique_points(explored_parameters):\n ranges = [param.f_get_range(copy=False) for param in explored_parameters]\n zipped_tuples = list(zip(*ranges))\n try:\n unique_elements = OrderedDict()\n for idx, val_tuple in enumerate(zipped_tuples):\n if val_tuple not in unique_elements:\n unique_elements[val_tuple] = []\n unique_elements[val_tuple].append(idx)\n return list(unique_elements.items())\n except TypeError:\n logger = logging.getLogger('pypet.find_unique')\n logger.error('Your parameter entries could not be hashed, '\n 'now I am sorting slowly in O(N**2).')\n unique_elements = []\n for idx, val_tuple in enumerate(zipped_tuples):\n matches = False\n for added_tuple, pos_list in unique_elements:\n matches = True\n for idx2, val in enumerate(added_tuple):\n if not explored_parameters[idx2]._equal_values(val_tuple[idx2], val):\n matches = False\n break\n if matches:\n pos_list.append(idx)\n break\n if not matches:\n unique_elements.append((val_tuple, [idx]))\n return unique_elements"
},
{
"code": "def unfinished(cls):\n return [\n cls.NONE,\n cls.SCHEDULED,\n cls.QUEUED,\n cls.RUNNING,\n cls.SHUTDOWN,\n cls.UP_FOR_RETRY,\n cls.UP_FOR_RESCHEDULE\n ]"
},
{
"code": "def merge_left(field, local_task, remote_issue, hamming=False):\n local_field = local_task.get(field, [])\n remote_field = remote_issue.get(field, [])\n if field not in local_task:\n local_task[field] = []\n new_count = 0\n for remote in remote_field:\n for local in local_field:\n if (\n (\n hamming\n and get_annotation_hamming_distance(remote, local) == 0\n )\n or (\n remote == local\n )\n ):\n break\n else:\n log.debug(\"%s not found in %r\" % (remote, local_field))\n local_task[field].append(remote)\n new_count += 1\n if new_count > 0:\n log.debug('Added %s new values to %s (total: %s)' % (\n new_count, field, len(local_task[field]),))"
},
{
"code": "def images(self, query=None):\n from sregistry.database.models import Collection, Container\n rows = []\n if query is not None: \n like = \"%\" + query + \"%\"\n containers = Container.query.filter(or_(Container.name == query,\n Container.tag.like(like),\n Container.uri.like(like),\n Container.name.like(like))).all() \n else:\n containers = Container.query.all()\n if len(containers) > 0:\n message = \" [date] [client]\\t[uri]\"\n bot.custom(prefix='Containers:', message=message, color=\"RED\")\n for c in containers:\n uri = c.get_uri()\n created_at = c.created_at.strftime('%B %d, %Y')\n rows.append([created_at, \" [%s]\" %c.client, uri])\n bot.table(rows) \n return containers"
},
{
"code": "def set_max_in_flight(self, max_in_flight):\n assert isinstance(max_in_flight, int)\n self.max_in_flight = max_in_flight\n if max_in_flight == 0:\n for conn in itervalues(self.conns):\n if conn.rdy > 0:\n logger.debug('[%s:%s] rdy: %d -> 0', conn.id, self.name, conn.rdy)\n self._send_rdy(conn, 0)\n self.total_rdy = 0\n else:\n self.need_rdy_redistributed = True\n self._redistribute_rdy_state()"
},
{
"code": "def _store(self, lines, buffer=None, store='source'):\n if buffer is None:\n buffer = self._buffer\n if lines.endswith('\\n'):\n buffer.append(lines)\n else:\n buffer.append(lines+'\\n')\n setattr(self, store, self._set_source(buffer))"
},
{
"code": "def _ast_option_group_to_code(self, option_group, **kwargs):\n lines = [\"option(\"]\n lines.extend(self._indent(self._ast_to_code(option_group.expression)))\n lines.append(\")\")\n return lines"
},
{
"code": "def add(symbol: str, date, value, currency: str):\n symbol = symbol.upper()\n currency = currency.upper()\n app = PriceDbApplication()\n price = PriceModel()\n price.symbol.parse(symbol)\n price.datum.from_iso_date_string(date)\n price.value = Decimal(value)\n price.currency = currency\n app.add_price(price)\n app.save()\n click.echo(\"Price added.\")"
},
{
"code": "def _close(self):\n if self.connection:\n with self.wrap_database_errors:\n self.connection.client.close()"
},
{
"code": "def _get_byte_parser(self):\n if not self._byte_parser:\n self._byte_parser = \\\n ByteParser(text=self.text, filename=self.filename)\n return self._byte_parser"
},
{
"code": "def _configureShortcuts(self):\n self._upShortcut = QtGui.QShortcut(\n QtGui.QKeySequence('Backspace'), self\n )\n self._upShortcut.setAutoRepeat(False)\n self._upShortcut.activated.connect(self._onNavigateUpButtonClicked)"
},
{
"code": "def update_message_dict(message_dict,action):\n global g_ok_java_messages\n allKeys = g_ok_java_messages.keys()\n for key in message_dict.keys():\n if key in allKeys:\n for message in message_dict[key]:\n if action == 1:\n if message not in g_ok_java_messages[key]:\n g_ok_java_messages[key].append(message)\n if action == 2:\n if message in g_ok_java_messages[key]:\n g_ok_java_messages[key].remove(message)\n else:\n if action == 1:\n g_ok_java_messages[key] = message_dict[key]"
},
{
"code": "def _addHdlProcToRun(self, trigger: SimSignal, proc) -> None:\n if not self._applyValPlaned:\n self._scheduleApplyValues()\n if isEvDependentOn(trigger, proc):\n if self.now == 0:\n return\n self._seqProcsToRun.append(proc)\n else:\n self._combProcsToRun.append(proc)"
},
{
"code": "def resolve_backend_name(name, backends, deprecated, aliased):\n available = [backend.name() for backend in backends]\n resolved_name = deprecated.get(name, aliased.get(name, name))\n if isinstance(resolved_name, list):\n resolved_name = next((b for b in resolved_name if b in available), \"\")\n if resolved_name not in available:\n raise LookupError(\"backend '{}' not found.\".format(name))\n if name in deprecated:\n logger.warning(\"WARNING: '%s' is deprecated. Use '%s'.\", name, resolved_name)\n return resolved_name"
},
{
"code": "def _rewrite_insert_nothing(self, sql, params, returning):\n conflict_target = self._build_conflict_target()\n where_clause = ' AND '.join([\n '{0} = %s'.format(self._format_field_name(field_name))\n for field_name in self.query.conflict_target\n ])\n where_clause_params = [\n self._format_field_value(field_name)\n for field_name in self.query.conflict_target\n ]\n params = params + tuple(where_clause_params)\n return (\n (\n 'WITH insdata AS ('\n '{insert} ON CONFLICT {conflict_target} DO UPDATE'\n ' SET {pk_column} = NULL WHERE FALSE RETURNING {returning})'\n ' SELECT * FROM insdata UNION ALL'\n ' SELECT {returning} FROM {table} WHERE {where_clause} LIMIT 1;'\n ).format(\n insert=sql,\n conflict_target=conflict_target,\n pk_column=self.qn(self.query.model._meta.pk.column),\n returning=returning,\n table=self.query.objs[0]._meta.db_table,\n where_clause=where_clause\n ),\n params\n )"
},
{
"code": "def get_stores(self, search_term):\n params = {'SearchText': search_term}\n response = self.__get('/storefindermap/storesearch', params=params)\n return Stores(response.json())"
},
{
"code": "def list_recommendations(\n self, keywords=None, max_domain_recommendations=None, custom_headers=None, raw=False, **operation_config):\n parameters = models.DomainRecommendationSearchParameters(keywords=keywords, max_domain_recommendations=max_domain_recommendations)\n def internal_paging(next_link=None, raw=False):\n if not next_link:\n url = self.list_recommendations.metadata['url']\n path_format_arguments = {\n 'subscriptionId': self._serialize.url(\"self.config.subscription_id\", self.config.subscription_id, 'str')\n }\n url = self._client.format_url(url, **path_format_arguments)\n query_parameters = {}\n query_parameters['api-version'] = self._serialize.query(\"self.api_version\", self.api_version, 'str')\n else:\n url = next_link\n query_parameters = {}\n header_parameters = {}\n header_parameters['Accept'] = 'application/json'\n header_parameters['Content-Type'] = 'application/json; charset=utf-8'\n if self.config.generate_client_request_id:\n header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())\n if custom_headers:\n header_parameters.update(custom_headers)\n if self.config.accept_language is not None:\n header_parameters['accept-language'] = self._serialize.header(\"self.config.accept_language\", self.config.accept_language, 'str')\n body_content = self._serialize.body(parameters, 'DomainRecommendationSearchParameters')\n request = self._client.post(url, query_parameters, header_parameters, body_content)\n response = self._client.send(request, stream=False, **operation_config)\n if response.status_code not in [200]:\n raise models.DefaultErrorResponseException(self._deserialize, response)\n return response\n deserialized = models.NameIdentifierPaged(internal_paging, self._deserialize.dependencies)\n if raw:\n header_dict = {}\n client_raw_response = models.NameIdentifierPaged(internal_paging, self._deserialize.dependencies, header_dict)\n return client_raw_response\n return deserialized"
},
{
"code": "def query_string(self, **params):\n return SearchResult(self, self._api.get(self._href, **params))"
},
{
"code": "def add_bias(self, name, size, mean=0, std=1):\n mean = self.kwargs.get('mean_{}'.format(name), mean)\n std = self.kwargs.get('std_{}'.format(name), std)\n self._params.append(theano.shared(\n util.random_vector(size, mean, std, rng=self.rng),\n name=self._fmt(name)))"
},
{
"code": "def ancestors(self, lhs, rhs):\n def _search(node):\n if node in lhs:\n return True\n if not node.parent:\n return False\n return _search(node.parent)\n return [node for node in rhs if _search(node)]"
},
{
"code": "def get_prices_on(self, on_date: str, namespace: str, symbol: str):\n repo = self.get_price_repository()\n query = (\n repo.query.filter(dal.Price.namespace == namespace)\n .filter(dal.Price.symbol == symbol)\n .filter(dal.Price.date == on_date)\n .order_by(dal.Price.time.desc())\n )\n result = query.first()\n return result"
},
{
"code": "def getEvents(self):\n events = []\n for json in self.conn.endpoints[\"self\"].getEvents():\n events.append(SkypeEvent.fromRaw(self, json))\n return events"
},
{
"code": "def prepare(self):\n self.output_dim = 10\n self.encoder = Chain(self.input_dim).stack(Dense(self.internal_layer_size, 'tanh'))\n self.decoder = Chain(self.internal_layer_size).stack(Dense(self.input_dim))\n self.classifier = Chain(self.internal_layer_size).stack(Dense(50, 'tanh'),\n Dense(self.output_dim),\n Softmax())\n self.register_inner_layers(self.encoder, self.decoder, self.classifier)\n self.target_input = T.ivector('target')\n self.register_external_inputs(self.target_input)"
},
{
"code": "def _set_configurations(self):\n logger.debug(\"======================\")\n logger.debug(\"Setting configurations\")\n logger.debug(\"======================\")\n resources = \"\"\n containers = \"\"\n params = \"\"\n manifest = \"\"\n if self.merge_params:\n params += self._get_merged_params_string()\n help_list = self._get_merged_params_help()\n else:\n params += self._get_params_string()\n help_list = self._get_params_help()\n for p in self.processes:\n if not p.directives:\n continue\n logger.debug(\"[{}] Adding directives: {}\".format(\n p.template, p.directives))\n resources += self._get_resources_string(p.directives, p.pid)\n containers += self._get_container_string(p.directives, p.pid)\n manifest = self._get_manifest_string()\n self.resources = self._render_config(\"resources.config\", {\n \"process_info\": resources\n })\n self.containers = self._render_config(\"containers.config\", {\n \"container_info\": containers\n })\n self.params = self._render_config(\"params.config\", {\n \"params_info\": params\n })\n self.manifest = self._render_config(\"manifest.config\", {\n \"manifest_info\": manifest\n })\n self.help = self._render_config(\"Helper.groovy\", {\n \"nf_file\": basename(self.nf_file),\n \"help_list\": help_list,\n \"version\": __version__,\n \"pipeline_name\": \" \".join([x.upper() for x in self.pipeline_name])\n })\n self.user_config = self._render_config(\"user.config\", {})"
},
{
"code": "def add_range(self, sequence, begin, end):\n sequence.parser_tree = parsing.Range(self.value(begin).strip(\"'\"),\n self.value(end).strip(\"'\"))\n return True"
},
{
"code": "def streams(self):\n result = self.db.read(self.path, {\"q\": \"ls\"})\n if result is None or result.json() is None:\n return []\n streams = []\n for s in result.json():\n strm = self[s[\"name\"]]\n strm.metadata = s\n streams.append(strm)\n return streams"
},
{
"code": "def truncate_string(data, headers, max_field_width=None, **_):\n return (([utils.truncate_string(v, max_field_width) for v in row] for row in data),\n [utils.truncate_string(h, max_field_width) for h in headers])"
},
{
"code": "def login(self):\n if self._session is None:\n self._session = requests.session()\n self._session.headers.update({'User-agent': str(UserAgent().random)})\n return self._post_login_page()"
},
{
"code": "def file_read(filename):\n fobj = open(filename,'r');\n source = fobj.read();\n fobj.close()\n return source"
},
{
"code": "def einsum_vecmul_index(gate_indices, number_of_qubits):\n mat_l, mat_r, tens_lin, tens_lout = _einsum_matmul_index_helper(gate_indices,\n number_of_qubits)\n return \"{mat_l}{mat_r}, \".format(mat_l=mat_l, mat_r=mat_r) + \\\n \"{tens_lin}->{tens_lout}\".format(tens_lin=tens_lin,\n tens_lout=tens_lout)"
},
{
"code": "def validate_widget(widget):\n if not has_valid_id(widget):\n raise InvalidWidget(\"%s must contain a valid 'id' attribute\" % widget.__name__)\n if not has_valid_name(widget):\n raise InvalidWidget(\"%s must contain a valid 'name' attribute\" % widget.__name__)\n if not has_valid_template(widget):\n raise InvalidWidget(\"%s must contain a valid 'template' attribute\" % widget.__name__)\n if not hasattr(widget, 'zones') or not widget.zones:\n raise InvalidWidget(\"%s must be compatible with at least one zone\" % widget.__name__)"
},
{
"code": "def institute(context, institute_id, sanger_recipient, coverage_cutoff, frequency_cutoff, \n display_name, remove_sanger):\n adapter = context.obj['adapter']\n LOG.info(\"Running scout update institute\")\n try:\n adapter.update_institute(\n internal_id=institute_id, \n sanger_recipient=sanger_recipient, \n coverage_cutoff=coverage_cutoff, \n frequency_cutoff=frequency_cutoff, \n display_name=display_name,\n remove_sanger=remove_sanger,\n )\n except Exception as err:\n LOG.warning(err)\n context.abort()"
},
{
"code": "def get_agency_id(relation):\n op = relation.tags.get('operator')\n if op:\n return int(hashlib.sha256(op.encode('utf-8')).hexdigest(), 16) % 10**8\n return -1"
},
{
"code": "def writes(nb, format, **kwargs):\n format = unicode(format)\n if format == u'json' or format == u'ipynb':\n return writes_json(nb, **kwargs)\n elif format == u'py':\n return writes_py(nb, **kwargs)\n else:\n raise NBFormatError('Unsupported format: %s' % format)"
},
{
"code": "def f_add_config_group(self, *args, **kwargs):\n return self._nn_interface._add_generic(self, type_name=CONFIG_GROUP,\n group_type_name=CONFIG_GROUP,\n args=args, kwargs=kwargs)"
},
{
"code": "def _get_authorization(self, request, httpclient):\n return 'WRAP access_token=\"' + \\\n self._get_token(request.host, request.path, httpclient) + '\"'"
},
{
"code": "def evaluate(self, expression, i1=None, i2=None, out=None, selection=None, delay=False):\n expression = _ensure_strings_from_expressions(expression)\n result = self.server._call_dataset(\"evaluate\", self, expression=expression, i1=i1, i2=i2, selection=selection, delay=delay)\n return result"
},
{
"code": "def _get_value(self, key, func=None, split_val=None, as_boolean=False,\n\t\texception_default=None):\n\t\ttry:\n\t\t\tif as_boolean:\n\t\t\t\treturn self.config.getboolean(key[0], key[1])\n\t\t\tvalue = self.config.get(key[0], key[1])\n\t\t\tif split_val is not None:\n\t\t\t\tvalue = value.split(split_val)\n\t\t\tif func is not None:\n\t\t\t\treturn func(value)\n\t\t\treturn value\n\t\texcept (KeyError, configparser.NoSectionError, configparser.NoOptionError) as e:\n\t\t\tif exception_default is not None:\n\t\t\t\treturn exception_default\n\t\t\traise KeyError(e)"
},
{
"code": "def get_system_cpu_times():\n user, system, idle = 0, 0, 0\n for cpu_time in _psutil_mswindows.get_system_cpu_times():\n user += cpu_time[0]\n system += cpu_time[1]\n idle += cpu_time[2]\n return _cputimes_ntuple(user, system, idle)"
},
{
"code": "def _spark_fit(self, cls, Z, *args, **kwargs):\n mapper = lambda X_y: super(cls, self).fit(\n X_y[0], X_y[1], *args, **kwargs\n )\n models = Z.map(mapper)\n avg = models.reduce(operator.add) / models.count()\n self.__dict__.update(avg.__dict__)\n return self"
},
{
"code": "def main(sample_id, assembly_file, coverage_file, coverage_bp_file, bam_file,\n opts, gsize):\n min_assembly_coverage, max_contigs = opts\n logger.info(\"Starting assembly mapping processing\")\n logger.info(\"Parsing coverage table\")\n coverage_info, a_cov = parse_coverage_table(coverage_file)\n a_size, contig_size = get_assembly_size(assembly_file)\n logger.info(\"Assembly processed with a total size of '{}' and coverage\"\n \" of '{}'\".format(a_size, a_cov))\n logger.info(\"Parsing coverage per bp table\")\n coverage_bp_data = get_coverage_from_file(coverage_bp_file)\n min_coverage = evaluate_min_coverage(min_assembly_coverage, a_cov, a_size)\n filtered_assembly = \"{}_filt.fasta\".format(\n os.path.splitext(assembly_file)[0])\n filtered_bam = \"filtered.bam\"\n logger.info(\"Checking filtered assembly\")\n if check_filtered_assembly(coverage_info, coverage_bp_data, min_coverage,\n gsize, contig_size, int(max_contigs),\n sample_id):\n logger.info(\"Filtered assembly passed minimum size threshold\")\n logger.info(\"Writting filtered assembly\")\n filter_assembly(assembly_file, min_coverage, coverage_info,\n filtered_assembly)\n logger.info(\"Filtering BAM file according to saved contigs\")\n filter_bam(coverage_info, bam_file, min_coverage, filtered_bam)\n else:\n shutil.copy(assembly_file, filtered_assembly)\n shutil.copy(bam_file, filtered_bam)\n shutil.copy(bam_file + \".bai\", filtered_bam + \".bai\")\n with open(\".status\", \"w\") as status_fh:\n status_fh.write(\"pass\")"
},
{
"code": "def fetchmany(self, size=None):\n self._check_executed()\n r = self._fetch_row(size or self.arraysize)\n self.rownumber = self.rownumber + len(r)\n if not r:\n self._warning_check()\n return r"
},
{
"code": "def find_source(self, filename):\n source = None\n base, ext = os.path.splitext(filename)\n TRY_EXTS = {\n '.py': ['.py', '.pyw'],\n '.pyw': ['.pyw'],\n }\n try_exts = TRY_EXTS.get(ext)\n if not try_exts:\n return filename, None\n for try_ext in try_exts:\n try_filename = base + try_ext\n if os.path.exists(try_filename):\n return try_filename, None\n source = self.coverage.file_locator.get_zip_data(try_filename)\n if source:\n return try_filename, source\n raise NoSource(\"No source for code: '%s'\" % filename)"
},
{
"code": "def get_document(self, document_id, database_name=None, collection_name=None):\n if document_id is None:\n raise AirflowBadRequest(\"Cannot get a document without an id\")\n try:\n return self.get_conn().ReadItem(\n get_document_link(\n self.__get_database_name(database_name),\n self.__get_collection_name(collection_name),\n document_id))\n except HTTPFailure:\n return None"
},
{
"code": "def execute_actions(self, cwd):\n self._execute_globals(cwd)\n for action in self.actions:\n logger.info(\"executing {}\".format(action))\n p = subprocess.Popen(action, shell=True, cwd=cwd)\n p.wait()"
},
{
"code": "def __var_find_to_py_ast(\n var_name: str, ns_name: str, py_var_ctx: ast.AST\n) -> GeneratedPyAST:\n return GeneratedPyAST(\n node=ast.Attribute(\n value=ast.Call(\n func=_FIND_VAR_FN_NAME,\n args=[\n ast.Call(\n func=_NEW_SYM_FN_NAME,\n args=[ast.Str(var_name)],\n keywords=[ast.keyword(arg=\"ns\", value=ast.Str(ns_name))],\n )\n ],\n keywords=[],\n ),\n attr=\"value\",\n ctx=py_var_ctx,\n )\n )"
},
{
"code": "def create_storage_account(self, service_name, description, label,\n affinity_group=None, location=None,\n geo_replication_enabled=None,\n extended_properties=None,\n account_type='Standard_GRS'):\n _validate_not_none('service_name', service_name)\n _validate_not_none('description', description)\n _validate_not_none('label', label)\n if affinity_group is None and location is None:\n raise ValueError(\n 'location or affinity_group must be specified')\n if affinity_group is not None and location is not None:\n raise ValueError(\n 'Only one of location or affinity_group needs to be specified')\n if geo_replication_enabled == False:\n account_type = 'Standard_LRS'\n return self._perform_post(\n self._get_storage_service_path(),\n _XmlSerializer.create_storage_service_input_to_xml(\n service_name,\n description,\n label,\n affinity_group,\n location,\n account_type,\n extended_properties),\n as_async=True)"
},
{
"code": "def set_selection(self, selection, name=\"default\", executor=None):\n def create(current):\n return selection\n self._selection(create, name, executor=executor, execute_fully=True)"
},
{
"code": "def set_resolved_name(self, ref: dict, type_name2solve: TypeName,\n type_name_ref: TypeName):\n if self.resolution[type_name2solve.value] is None:\n self.resolution[type_name2solve.value] = ref[type_name_ref.value]"
},
{
"code": "def format_data(self, data, scale=True):\n if len(self.analytes) == 1:\n d = nominal_values(data[self.analytes[0]])\n ds = np.array(list(zip(d, np.zeros(len(d)))))\n else:\n d = [nominal_values(data[a]) for a in self.analytes]\n ds = np.vstack(d).T\n finite = np.isfinite(ds).sum(1) == ds.shape[1]\n sampled = np.arange(data[self.analytes[0]].size)[finite]\n ds = ds[finite]\n if scale:\n ds = self.scaler.transform(ds)\n return ds, sampled"
},
{
"code": "def _referer(self, extension):\n iana_record = self.lookup.whois(\n PyFunceble.CONFIGURATION[\"iana_whois_server\"], \"hello.%s\" % extension\n )\n if iana_record and \"refer\" in iana_record:\n regex_referer = r\"(?s)refer\\:\\s+([a-zA-Z0-9._-]+)\\n\"\n matched = Regex(\n iana_record, regex_referer, return_data=True, group=1\n ).match()\n if matched:\n return matched\n if extension in self.manual_server:\n return self.manual_server[extension]\n return None"
},
{
"code": "def shape_rb_data(raw_rb):\n rb_data = []\n rb_data.append(np.mean(raw_rb, 0))\n rb_data.append(np.std(raw_rb, 0))\n return rb_data"
},
{
"code": "def update_function(self, name, body, update_mask):\n response = self.get_conn().projects().locations().functions().patch(\n updateMask=\",\".join(update_mask),\n name=name,\n body=body\n ).execute(num_retries=self.num_retries)\n operation_name = response[\"name\"]\n self._wait_for_operation_to_complete(operation_name=operation_name)"
},
{
"code": "def boolean(ctx, obj):\n if hasattr(obj, 'compute'):\n obj = next(seq.compute(ctx), '')\n else:\n obj = seq\n yield next(to_boolean(obj), '')"
},
{
"code": "def expects_none(options):\n if any(options.get(key) is not None for key in [\"count\", \"maximum\", \"minimum\", \"between\"]):\n return matches_count(0, options)\n else:\n return False"
},
{
"code": "def __early_downsample(y, sr, hop_length, res_type, n_octaves,\n nyquist, filter_cutoff, scale):\n downsample_count = __early_downsample_count(nyquist, filter_cutoff,\n hop_length, n_octaves)\n if downsample_count > 0 and res_type == 'kaiser_fast':\n downsample_factor = 2**(downsample_count)\n hop_length //= downsample_factor\n if len(y) < downsample_factor:\n raise ParameterError('Input signal length={:d} is too short for '\n '{:d}-octave CQT'.format(len(y), n_octaves))\n new_sr = sr / float(downsample_factor)\n y = audio.resample(y, sr, new_sr,\n res_type=res_type,\n scale=True)\n if not scale:\n y *= np.sqrt(downsample_factor)\n sr = new_sr\n return y, sr, hop_length"
},
{
"code": "def log_parser(self):\n size_stamp = os.path.getsize(self.log_file)\n self.log_retry = 0\n if size_stamp and size_stamp == self.log_sizestamp:\n return\n else:\n logger.debug(\"Updating log size stamp to: {}\".format(size_stamp))\n self.log_sizestamp = size_stamp\n r = \".* (.*) \\[.*\\].*\\[(.*)\\].*process > (.*) \\((.*)\\).*\"\n with open(self.log_file) as fh:\n for line in fh:\n if \"Submitted process >\" in line or \\\n \"Re-submitted process >\" in line or \\\n \"Cached process >\" in line:\n m = re.match(r, line)\n if not m:\n continue\n time_start = m.group(1)\n workdir = m.group(2)\n process = m.group(3)\n tag = m.group(4)\n if time_start + tag not in self.stored_log_ids:\n self.stored_log_ids.append(time_start + tag)\n else:\n continue\n if process not in self.processes:\n continue\n p = self.processes[process]\n if tag in list(p[\"finished\"]) + list(p[\"retry\"]):\n continue\n if tag in list(p[\"failed\"]) and \\\n \"Re-submitted process >\" in line:\n p[\"retry\"].add(tag)\n self.send = True\n continue\n p[\"barrier\"] = \"R\"\n if tag not in p[\"submitted\"]:\n p[\"submitted\"].add(tag)\n if tag not in self.process_tags[process]:\n self.process_tags[process][tag] = {\n \"workdir\": self._expand_path(workdir),\n \"start\": time_start\n }\n self.send = True\n elif not self.process_tags[process][tag][\"start\"]:\n self.process_tags[process][tag][\"start\"] = time_start\n self.send = True\n self._update_pipeline_status()"
},
{
"code": "def _remove_exploration(self):\n for param in self._explored_parameters.values():\n if param._stored:\n try:\n self.f_delete_item(param)\n except Exception:\n self._logger.exception('Could not delete expanded parameter `%s` '\n 'from disk.' % param.v_full_name)"
},
{
"code": "def setup_platform(hass, config, add_entities, discovery_info=None):\n host = config.get(CONF_HOST)\n token = config.get(CONF_ACCESS_TOKEN)\n name = config.get(CONF_NAME)\n volume_step = config.get(CONF_VOLUME_STEP)\n device_type = config.get(CONF_DEVICE_CLASS)\n device = VizioDevice(host, token, name, volume_step, device_type)\n if device.validate_setup() is False:\n _LOGGER.error(\"Failed to set up Vizio platform, \"\n \"please check if host and API key are correct\")\n return\n elif (token is None or token == \"\") and device_type == \"tv\":\n _LOGGER.error(\"Failed to set up Vizio platform, \"\n \"if device_class is 'tv' then an auth_token needs \"\n \"to be provided, otherwise if device_class is \"\n \"'soundbar' then add the right device_class to config\")\n return\n if config.get(CONF_SUPPRESS_WARNING):\n from requests.packages import urllib3\n _LOGGER.warning(\"InsecureRequestWarning is disabled \"\n \"because of Vizio platform configuration\")\n urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)\n add_entities([device], True)"
},
{
"code": "def handle_oauth2_response(self, args):\n client = self.make_client()\n remote_args = {\n 'code': args.get('code'),\n 'client_secret': self.consumer_secret,\n 'redirect_uri': session.get('%s_oauthredir' % self.name)\n }\n log.debug('Prepare oauth2 remote args %r', remote_args)\n remote_args.update(self.access_token_params)\n headers = copy(self._access_token_headers)\n if self.access_token_method == 'POST':\n headers.update({'Content-Type': 'application/x-www-form-urlencoded'})\n body = client.prepare_request_body(**remote_args)\n resp, content = self.http_request(\n self.expand_url(self.access_token_url),\n headers=headers,\n data=to_bytes(body, self.encoding),\n method=self.access_token_method,\n )\n elif self.access_token_method == 'GET':\n qs = client.prepare_request_body(**remote_args)\n url = self.expand_url(self.access_token_url)\n url += ('?' in url and '&' or '?') + qs\n resp, content = self.http_request(\n url,\n headers=headers,\n method=self.access_token_method,\n )\n else:\n raise OAuthException(\n 'Unsupported access_token_method: %s' %\n self.access_token_method\n )\n data = parse_response(resp, content, content_type=self.content_type)\n if resp.code not in (200, 201):\n raise OAuthException(\n 'Invalid response from %s' % self.name,\n type='invalid_response', data=data\n )\n return data"
},
{
"code": "def decode(self, val):\n new_val = self.decode_date(val)\n if val != new_val:\n return new_val\n return json.JSONDecoder.decode(self, val)"
},
{
"code": "def extractPrintSaveIntermittens():\n global g_summary_dict_intermittents\n localtz = time.tzname[0]\n for ind in range(len(g_summary_dict_all[\"TestName\"])):\n if g_summary_dict_all[\"TestInfo\"][ind][\"FailureCount\"] >= g_threshold_failure:\n addFailedTests(g_summary_dict_intermittents, g_summary_dict_all, ind)\n if len(g_summary_dict_intermittents[\"TestName\"]) > 0:\n json.dump(g_summary_dict_intermittents, open(g_summary_dict_name, 'w'))\n with open(g_summary_csv_filename, 'w') as summaryFile:\n for ind in range(len(g_summary_dict_intermittents[\"TestName\"])):\n testName = g_summary_dict_intermittents[\"TestName\"][ind]\n numberFailure = g_summary_dict_intermittents[\"TestInfo\"][ind][\"FailureCount\"]\n firstFailedTS = parser.parse(time.ctime(min(g_summary_dict_intermittents[\"TestInfo\"][ind][\"Timestamp\"]))+\n ' '+localtz)\n firstFailedStr = firstFailedTS.strftime(\"%a %b %d %H:%M:%S %Y %Z\")\n recentFail = parser.parse(time.ctime(max(g_summary_dict_intermittents[\"TestInfo\"][ind][\"Timestamp\"]))+\n ' '+localtz)\n recentFailStr = recentFail.strftime(\"%a %b %d %H:%M:%S %Y %Z\")\n eachTest = \"{0}, {1}, {2}, {3}\\n\".format(testName, recentFailStr, numberFailure,\n g_summary_dict_intermittents[\"TestInfo\"][ind][\"TestCategory\"][0])\n summaryFile.write(eachTest)\n print(\"Intermittent: {0}, Last failed: {1}, Failed {2} times since \"\n \"{3}\".format(testName, recentFailStr, numberFailure, firstFailedStr))"
},
{
"code": "def _get_rule_source(self, rule):\n p = len(self.input_source) + rule.position\n source = self.input_source[p:p + rule.consumed].rstrip()\n return self._indent(source, depth=self.indent + \" \", skip_first_line=True)"
},
{
"code": "def _resubscribe(self, soft=False):\n if self.bitfinex_config:\n self.send(**self.bitfinex_config)\n q_list = []\n while True:\n try:\n identifier, q = self.channel_configs.popitem(last=True if soft else False)\n except KeyError:\n break\n q_list.append((identifier, q.copy()))\n if identifier == 'auth':\n self.send(**q, auth=True)\n continue\n if soft:\n q['event'] = 'unsubscribe'\n self.send(**q)\n if soft:\n for identifier, q in reversed(q_list):\n self.channel_configs[identifier] = q\n self.send(**q)\n else:\n for identifier, q in q_list:\n self.channel_configs[identifier] = q"
},
{
"code": "def _receive_data(self):\n while True:\n while len(self._buffer) < self.max_size and self.conn.poll():\n data = self._read_chunks()\n if data is not None:\n self._buffer.append(data)\n if len(self._buffer) > 0:\n return self._buffer.popleft()"
},
{
"code": "def _build_purchase_item(course_id, course_url, cost_in_cents, mode, course_data, sku):\n item = {\n 'id': \"{}-{}\".format(course_id, mode),\n 'url': course_url,\n 'price': cost_in_cents,\n 'qty': 1,\n }\n if 'title' in course_data:\n item['title'] = course_data['title']\n else:\n item['title'] = 'Course {} mode: {}'.format(course_id, mode)\n if 'tags' in course_data:\n item['tags'] = course_data['tags']\n item['vars'] = dict(course_data.get('vars', {}), mode=mode, course_run_id=course_id)\n item['vars']['purchase_sku'] = sku\n return item"
},
{
"code": "def _vector_matrix(vs, ms):\n return tf.reduce_sum(input_tensor=vs[..., tf.newaxis] * ms, axis=-2)"
},
{
"code": "def mix_over_posterior_draws(means, variances):\n with tf.compat.v1.name_scope(\n 'mix_over_posterior_draws', values=[means, variances]):\n num_posterior_draws = dist_util.prefer_static_value(\n tf.shape(input=means))[0]\n component_observations = tfd.Independent(\n distribution=tfd.Normal(\n loc=dist_util.move_dimension(means, 0, -2),\n scale=tf.sqrt(dist_util.move_dimension(variances, 0, -2))),\n reinterpreted_batch_ndims=1)\n return tfd.MixtureSameFamily(\n mixture_distribution=tfd.Categorical(\n logits=tf.zeros([num_posterior_draws],\n dtype=component_observations.dtype)),\n components_distribution=component_observations)"
},
{
"code": "def DeleteItem(self, item):\r\n \"Remove the item from the list and unset the related data\"\r\n wx_data = self.GetItemData(item)\r\n py_data = self._py_data_map[wx_data]\r\n del self._py_data_map[wx_data]\r\n del self._wx_data_map[py_data]\r\n wx.ListCtrl.DeleteItem(self, item)"
},
{
"code": "def add_route(self, command, adapter):\n if not isinstance(adapter, BaseAdapter):\n try:\n adapter = self.adapter_aliases[adapter]\n except KeyError:\n self.adapter_aliases[adapter] = adapter = resolve_adapter(\n adapter\n )\n self.routes[command] = adapter\n return self"
},
{
"code": "def progress(iterator, prefix):\n if terminal_width(prefix) > 25:\n prefix = (\"..\" + get_cut_prefix(prefix, 23))\n speed_updated = start = time()\n speed_written = written = 0\n speed_history = deque(maxlen=5)\n for data in iterator:\n yield data\n now = time()\n elapsed = now - start\n written += len(data)\n speed_elapsed = now - speed_updated\n if speed_elapsed >= 0.5:\n speed_history.appendleft((\n written - speed_written,\n speed_updated,\n ))\n speed_updated = now\n speed_written = written\n speed_history_written = sum(h[0] for h in speed_history)\n speed_history_elapsed = now - speed_history[-1][1]\n speed = speed_history_written / speed_history_elapsed\n status = create_status_line(\n prefix=prefix,\n written=format_filesize(written),\n elapsed=format_time(elapsed),\n speed=format_filesize(speed)\n )\n print_inplace(status)\n sys.stderr.write(\"\\n\")\n sys.stderr.flush()"
},
{
"code": "def get_params(brightness, contrast, saturation, hue):\n transforms = []\n if brightness is not None:\n brightness_factor = random.uniform(brightness[0], brightness[1])\n transforms.append(Lambda(lambda img: F.adjust_brightness(img, brightness_factor)))\n if contrast is not None:\n contrast_factor = random.uniform(contrast[0], contrast[1])\n transforms.append(Lambda(lambda img: F.adjust_contrast(img, contrast_factor)))\n if saturation is not None:\n saturation_factor = random.uniform(saturation[0], saturation[1])\n transforms.append(Lambda(lambda img: F.adjust_saturation(img, saturation_factor)))\n if hue is not None:\n hue_factor = random.uniform(hue[0], hue[1])\n transforms.append(Lambda(lambda img: F.adjust_hue(img, hue_factor)))\n random.shuffle(transforms)\n transform = Compose(transforms)\n return transform"
},
{
"code": "def panel(context, panel, version, update_date, update_version):\n adapter = context.obj['adapter']\n panel_obj = adapter.gene_panel(panel, version=version)\n if not panel_obj:\n LOG.warning(\"Panel %s (version %s) could not be found\" % (panel, version))\n context.abort()\n date_obj = None\n if update_date:\n try:\n date_obj = get_date(update_date)\n except Exception as err:\n LOG.warning(err)\n context.abort()\n update_panel(\n adapter,\n panel,\n panel_version=panel_obj['version'],\n new_version=update_version,\n new_date=date_obj\n )"
},
{
"code": "def random_ports(port, n):\n for i in range(min(5, n)):\n yield port + i\n for i in range(n-5):\n yield port + random.randint(-2*n, 2*n)"
},
{
"code": "def PermissiveDict(fields=None):\n if fields:\n check_user_facing_fields_dict(fields, 'PermissiveDict')\n class _PermissiveDict(_ConfigComposite):\n def __init__(self):\n key = 'PermissiveDict.' + str(DictCounter.get_next_count())\n super(_PermissiveDict, self).__init__(\n name=None,\n key=key,\n fields=fields or dict(),\n description='A configuration dictionary with typed fields',\n type_attributes=ConfigTypeAttributes(is_builtin=True),\n )\n @property\n def is_permissive_composite(self):\n return True\n return _PermissiveDict"
},
{
"code": "def gravatar_url(user_or_email, size=GRAVATAR_DEFAULT_SIZE):\n if hasattr(user_or_email, 'email'):\n email = user_or_email.email\n else:\n email = user_or_email\n try:\n return escape(get_gravatar_url(email=email, size=size))\n except:\n return ''"
},
{
"code": "def run_as_cmd(cmd, user, shell='bash'):\n to_execute = get_shell(shell) + [EXECUTE_SHELL_PARAM, cmd]\n if user == 'root':\n return to_execute\n return ['sudo', '-s', '--set-home', '-u', user] + to_execute"
},
{
"code": "def profile_function(self):\n with _CodeHeatmapCalculator() as prof:\n result = self._run_object(*self._run_args, **self._run_kwargs)\n code_lines, start_line = inspect.getsourcelines(self._run_object)\n source_lines = []\n for line in code_lines:\n source_lines.append(('line', start_line, line))\n start_line += 1\n filename = os.path.abspath(inspect.getsourcefile(self._run_object))\n heatmap = prof.heatmap[filename]\n run_time = sum(time for time in heatmap.values())\n return {\n 'objectName': self._object_name,\n 'runTime': run_time,\n 'result': result,\n 'timestamp': int(time.time()),\n 'heatmaps': [{\n 'name': self._object_name,\n 'heatmap': heatmap,\n 'executionCount': prof.execution_count[filename],\n 'srcCode': source_lines,\n 'runTime': run_time\n }]\n }"
},
{
"code": "def dashboard(request):\n if not isinstance(mc_client, dict):\n cache_stats = _get_cache_stats()\n else:\n cache_stats = None\n if cache_stats:\n data = _context_data({\n 'title': _('Memcache Dashboard'),\n 'cache_stats': cache_stats,\n 'can_get_slabs': hasattr(mc_client, 'get_slabs'),\n 'REFRESH_RATE': SETTINGS['REFRESH_RATE'],\n },\n request)\n template = 'memcache_admin/dashboard.html'\n else:\n data = _context_data({\n 'title': _('Memcache Dashboard - Error'),\n 'error_message': _('Unable to connect to a memcache server.'),\n },\n request)\n template = 'memcache_admin/dashboard_error.html'\n return render_to_response(template, data, RequestContext(request))"
},
{
"code": "def _validate_initial_statevector(self):\n if self._initial_statevector is None:\n return\n length = len(self._initial_statevector)\n required_dim = 2 ** self._number_of_qubits\n if length != required_dim:\n raise BasicAerError('initial statevector is incorrect length: ' +\n '{} != {}'.format(length, required_dim))"
},
{
"code": "def chatToId(url):\n match = re.search(r\"conversations/([0-9]+:[^/]+)\", url)\n return match.group(1) if match else None"
},
{
"code": "def prepare_pids(self):\n self.pids = []\n for fetcher in self.pid_fetchers:\n val = fetcher(None, self.revisions[-1][1])\n if val:\n self.pids.append(val)"
},
{
"code": "def use(network=False):\n global _engine\n __engine = _engine\n activated = __engine.active\n if activated:\n __engine.disable()\n _engine = Engine(network=network)\n _engine.activate()\n yield _engine\n _engine.disable()\n if network:\n _engine.disable_network()\n _engine = __engine\n if activated:\n _engine.activate()"
},
{
"code": "def parse_yaml_linenumbers(data, filename):\n def compose_node(parent, index):\n line = loader.line\n node = Composer.compose_node(loader, parent, index)\n node.__line__ = line + 1\n return node\n def construct_mapping(node, deep=False):\n if ANSIBLE_VERSION < 2:\n mapping = Constructor.construct_mapping(loader, node, deep=deep)\n else:\n mapping = AnsibleConstructor.construct_mapping(loader, node, deep=deep)\n if hasattr(node, '__line__'):\n mapping[LINE_NUMBER_KEY] = node.__line__\n else:\n mapping[LINE_NUMBER_KEY] = mapping._line_number\n mapping[FILENAME_KEY] = filename\n return mapping\n try:\n if ANSIBLE_VERSION < 2:\n loader = yaml.Loader(data)\n else:\n import inspect\n kwargs = {}\n if 'vault_password' in inspect.getargspec(AnsibleLoader.__init__).args:\n kwargs['vault_password'] = DEFAULT_VAULT_PASSWORD\n loader = AnsibleLoader(data, **kwargs)\n loader.compose_node = compose_node\n loader.construct_mapping = construct_mapping\n data = loader.get_single_data()\n except (yaml.parser.ParserError, yaml.scanner.ScannerError) as e:\n raise SystemExit(\"Failed to parse YAML in %s: %s\" % (filename, str(e)))\n return data"
},
{
"code": "def log_cdf_laplace(x, name=\"log_cdf_laplace\"):\n with tf.name_scope(name):\n x = tf.convert_to_tensor(value=x, name=\"x\")\n lower_solution = -np.log(2.) + x\n safe_exp_neg_x = tf.exp(-tf.abs(x))\n upper_solution = tf.math.log1p(-0.5 * safe_exp_neg_x)\n return tf.where(x < 0., lower_solution, upper_solution)"
},
{
"code": "def samefile(path1, path2):\n info1 = fs.getfileinfo(path1)\n info2 = fs.getfileinfo(path2)\n return (info1.dwVolumeSerialNumber == info2.dwVolumeSerialNumber and\n info1.nFileIndexHigh == info2.nFileIndexHigh and\n info1.nFileIndexLow == info2.nFileIndexLow)"
},
{
"code": "def add_netnode_plugin_name(plugin_name):\n current_names = set(get_netnode_plugin_names())\n if plugin_name in current_names:\n return\n current_names.add(plugin_name)\n get_meta_netnode()[PLUGIN_NAMES_KEY] = json.dumps(list(current_names))"
},
{
"code": "def set_serial(self, hex_str):\n bignum_serial = _ffi.gc(_lib.BN_new(), _lib.BN_free)\n bignum_ptr = _ffi.new(\"BIGNUM**\")\n bignum_ptr[0] = bignum_serial\n bn_result = _lib.BN_hex2bn(bignum_ptr, hex_str)\n if not bn_result:\n raise ValueError(\"bad hex string\")\n asn1_serial = _ffi.gc(\n _lib.BN_to_ASN1_INTEGER(bignum_serial, _ffi.NULL),\n _lib.ASN1_INTEGER_free)\n _lib.X509_REVOKED_set_serialNumber(self._revoked, asn1_serial)"
},
{
"code": "def run_samblaster(job, sam):\n work_dir = job.fileStore.getLocalTempDir()\n job.fileStore.readGlobalFile(sam, os.path.join(work_dir, 'input.sam'))\n command = ['/usr/local/bin/samblaster',\n '-i', '/data/input.sam',\n '-o', '/data/output.sam',\n '--ignoreUnmated']\n start_time = time.time()\n dockerCall(job=job, workDir=work_dir,\n parameters=command,\n tool='quay.io/biocontainers/samblaster:0.1.24--0')\n end_time = time.time()\n _log_runtime(job, start_time, end_time, \"SAMBLASTER\")\n return job.fileStore.writeGlobalFile(os.path.join(work_dir, 'output.sam'))"
},
{
"code": "def handle_stranded_tasks(self, engine):\n lost = self.pending[engine]\n for msg_id in lost.keys():\n if msg_id not in self.pending[engine]:\n continue\n raw_msg = lost[msg_id].raw_msg\n idents,msg = self.session.feed_identities(raw_msg, copy=False)\n parent = self.session.unpack(msg[1].bytes)\n idents = [engine, idents[0]]\n try:\n raise error.EngineError(\"Engine %r died while running task %r\"%(engine, msg_id))\n except:\n content = error.wrap_exception()\n header = dict(\n status='error',\n engine=engine,\n date=datetime.now(),\n )\n msg = self.session.msg('apply_reply', content, parent=parent, subheader=header)\n raw_reply = map(zmq.Message, self.session.serialize(msg, ident=idents))\n self.dispatch_result(raw_reply)\n self.completed.pop(engine)\n self.failed.pop(engine)"
},
{
"code": "def get_group_all(group, path=None):\n result = []\n for config, distro in iter_files_distros(path=path):\n if group in config:\n for name, epstr in config[group].items():\n with BadEntryPoint.err_to_warnings():\n result.append(EntryPoint.from_string(epstr, name, distro))\n return result"
},
{
"code": "def build_filters_and_sizers(self, ppoi_value, create_on_demand):\n name = self.name\n if not name and self.field.placeholder_image_name:\n name = self.field.placeholder_image_name\n self.filters = FilterLibrary(\n name,\n self.storage,\n versatileimagefield_registry,\n ppoi_value,\n create_on_demand\n )\n for (\n attr_name,\n sizedimage_cls\n ) in iteritems(versatileimagefield_registry._sizedimage_registry):\n setattr(\n self,\n attr_name,\n sizedimage_cls(\n path_to_image=name,\n storage=self.storage,\n create_on_demand=create_on_demand,\n ppoi=ppoi_value\n )\n )"
},
{
"code": "def predict_logit(self, x, **kwargs):\n return self.feed_forward(x, **kwargs)[self.layers[-1].full_name('pre')]"
},
{
"code": "def get_source_lane(fork_process, pipeline_list):\n fork_source = fork_process[-1]\n fork_sig = [x for x in fork_process if x != \"__init__\"]\n for position, p in enumerate(pipeline_list[::-1]):\n if p[\"output\"][\"process\"] == fork_source:\n lane = p[\"output\"][\"lane\"]\n logger.debug(\"Possible source match found in position {} in lane\"\n \" {}\".format(position, lane))\n lane_sequence = [x[\"output\"][\"process\"] for x in pipeline_list\n if x[\"output\"][\"lane\"] == lane]\n logger.debug(\"Testing lane sequence '{}' against fork signature\"\n \" '{}'\".format(lane_sequence, fork_sig))\n if lane_sequence == fork_sig:\n return p[\"output\"][\"lane\"]\n return 0"
},
{
"code": "def article(self, msgid_article=None, decode=None):\n args = None\n if msgid_article is not None:\n args = utils.unparse_msgid_article(msgid_article)\n code, message = self.command(\"ARTICLE\", args)\n if code != 220:\n raise NNTPReplyError(code, message)\n parts = message.split(None, 1)\n try:\n articleno = int(parts[0])\n except ValueError:\n raise NNTPProtocolError(message)\n headers = utils.parse_headers(self.info_gen(code, message))\n decode = \"yEnc\" in headers.get(\"subject\", \"\")\n escape = 0\n crc32 = 0\n body = []\n for line in self.info_gen(code, message):\n if decode:\n if line.startswith(\"=y\"):\n continue\n line, escape, crc32 = yenc.decode(line, escape, crc32)\n body.append(line)\n return articleno, headers, \"\".join(body)"
},
{
"code": "def wrap_function(func=None, error_threshold=None, reraise_exception=True, save_current_stack_trace=True):\n if func:\n return flawless.client.client._wrap_function_with_error_decorator(\n func=func,\n error_threshold=error_threshold,\n reraise_exception=reraise_exception,\n save_current_stack_trace=save_current_stack_trace)\n else:\n return functools.partial(flawless.client.client._wrap_function_with_error_decorator,\n error_threshold=error_threshold,\n reraise_exception=reraise_exception,\n save_current_stack_trace=save_current_stack_trace)"
},
{
"code": "def post(self, url, params=None, data=None, files=None, **kwargs):\n return self.call_api(\n \"POST\",\n url,\n params=params,\n data=data,\n files=files,\n **kwargs\n )"
},
{
"code": "def is_dark_rgb(r, g, b):\n try:\n midpoint = int(environ.get('TERMINAL_COLOR_MIDPOINT', None))\n except:\n pass\n if not midpoint:\n term = environ.get('TERM', None)\n print(\"midpoint\", midpoint, 'vs', (16*5 + 16*g + 16*b))\n midpoint = 383 if term and term == 'xterm-256color' else 117963\n if ( (16*5 + 16*g + 16*b) < midpoint ):\n return True\n else:\n return False"
},
{
"code": "def stop(self):\n with self.synclock:\n if self.syncthread is not None:\n self.syncthread.cancel()\n self.syncthread = None"
},
{
"code": "def evaluate_marker(cls, text, extra=None):\n return cls.interpret(parser.expr(text).totuple(1)[1])"
},
{
"code": "def _get_job(self, project_id, job_id):\n job_name = 'projects/{}/jobs/{}'.format(project_id, job_id)\n request = self._mlengine.projects().jobs().get(name=job_name)\n while True:\n try:\n return request.execute()\n except HttpError as e:\n if e.resp.status == 429:\n time.sleep(30)\n else:\n self.log.error('Failed to get MLEngine job: {}'.format(e))\n raise"
},
{
"code": "def pause(self):\n for tracer in self.tracers:\n tracer.stop()\n stats = tracer.get_stats()\n if stats:\n print(\"\\nCoverage.py tracer stats:\")\n for k in sorted(stats.keys()):\n print(\"%16s: %s\" % (k, stats[k]))\n threading.settrace(None)"
},
{
"code": "def to_py(o, keyword_fn: Callable[[kw.Keyword], Any] = _kw_name):\n if isinstance(o, ISeq):\n return _to_py_list(o, keyword_fn=keyword_fn)\n elif not isinstance(\n o, (IPersistentList, IPersistentMap, IPersistentSet, IPersistentVector)\n ):\n return o\n else:\n return _to_py_backup(o, keyword_fn=keyword_fn)"
},
{
"code": "def indent(instr,nspaces=4, ntabs=0, flatten=False):\n if instr is None:\n return\n ind = '\\t'*ntabs+' '*nspaces\n if flatten:\n pat = re.compile(r'^\\s*', re.MULTILINE)\n else:\n pat = re.compile(r'^', re.MULTILINE)\n outstr = re.sub(pat, ind, instr)\n if outstr.endswith(os.linesep+ind):\n return outstr[:-len(ind)]\n else:\n return outstr"
},
{
"code": "def handleCONNACK(self, response):\n state = self.__class__.__name__\n log.error(\"Unexpected {packet:7} packet received in {log_source}\", packet=\"CONNACK\")"
},
{
"code": "def filter_bam(coverage_info, bam_file, min_coverage, output_bam):\n contig_list = [x for x, vals in coverage_info.items()\n if vals[\"cov\"] >= min_coverage]\n cli = [\n \"samtools\",\n \"view\",\n \"-bh\",\n \"-F\",\n \"4\",\n \"-o\",\n output_bam,\n \"-@\",\n \"1\",\n bam_file,\n ]\n cli += contig_list\n logger.debug(\"Runnig samtools view subprocess with command: {}\".format(\n cli))\n p = subprocess.Popen(cli, stdout=PIPE, stderr=PIPE)\n stdout, stderr = p.communicate()\n try:\n stderr = stderr.decode(\"utf8\")\n stdout = stdout.decode(\"utf8\")\n except (UnicodeDecodeError, AttributeError):\n stderr = str(stderr)\n stdout = str(stdout)\n logger.info(\"Finished samtools view subprocess with STDOUT:\\\\n\"\n \"======================================\\\\n{}\".format(stdout))\n logger.info(\"Fished samtools view subprocesswith STDERR:\\\\n\"\n \"======================================\\\\n{}\".format(stderr))\n logger.info(\"Finished samtools view with return code: {}\".format(\n p.returncode))\n if not p.returncode:\n cli = [\n \"samtools\",\n \"index\",\n output_bam\n ]\n logger.debug(\"Runnig samtools index subprocess with command: \"\n \"{}\".format(cli))\n p = subprocess.Popen(cli, stdout=PIPE, stderr=PIPE)\n stdout, stderr = p.communicate()\n try:\n stderr = stderr.decode(\"utf8\")\n stdout = stdout.decode(\"utf8\")\n except (UnicodeDecodeError, AttributeError):\n stderr = str(stderr)\n stdout = str(stdout)\n logger.info(\"Finished samtools index subprocess with STDOUT:\\\\n\"\n \"======================================\\\\n{}\".format(\n stdout))\n logger.info(\"Fished samtools index subprocesswith STDERR:\\\\n\"\n \"======================================\\\\n{}\".format(\n stderr))\n logger.info(\"Finished samtools index with return code: {}\".format(\n p.returncode))"
},
{
"code": "def create_tfs_tfvc_client(url, token=None):\n if token is None:\n token = os.environ.get('TFS_API_TOKEN', None)\n tfs_connection = create_tfs_connection(url, token)\n tfs_tfvc_client = tfs_connection.get_client('vsts.tfvc.v4_1.tfvc_client.TfvcClient')\n if tfs_tfvc_client is None:\n msg = 'Unable to create TFS Git Client, failed to connect to TFS Enterprise (%s) with provided token.'\n raise RuntimeError(msg, url)\n return tfs_tfvc_client"
},
{
"code": "def visualize_qualitative_analysis(inputs, model, samples=1, batch_size=3,\n length=8):\n average = lambda dist: tf.reduce_mean(\n input_tensor=dist.mean(), axis=0)\n with tf.compat.v1.name_scope(\"val_reconstruction\"):\n reconstruct = functools.partial(model.reconstruct, inputs=inputs,\n samples=samples)\n visualize_reconstruction(inputs, average(reconstruct()))\n visualize_reconstruction(inputs, average(reconstruct(sample_static=True)),\n name=\"static_prior\")\n visualize_reconstruction(inputs, average(reconstruct(sample_dynamic=True)),\n name=\"dynamic_prior\")\n visualize_reconstruction(inputs, average(reconstruct(swap_static=True)),\n name=\"swap_static\")\n visualize_reconstruction(inputs, average(reconstruct(swap_dynamic=True)),\n name=\"swap_dynamic\")\n with tf.compat.v1.name_scope(\"generation\"):\n generate = functools.partial(model.generate, batch_size=batch_size,\n length=length, samples=samples)\n image_summary(average(generate(fix_static=True)), \"fix_static\")\n image_summary(average(generate(fix_dynamic=True)), \"fix_dynamic\")"
},
{
"code": "def debug_script(src, pm=False, globs=None):\n \"Debug a test script. `src` is the script, as a string.\"\n import pdb\n srcfilename = tempfile.mktemp(\".py\", \"doctestdebug\")\n f = open(srcfilename, 'w')\n f.write(src)\n f.close()\n try:\n if globs:\n globs = globs.copy()\n else:\n globs = {}\n if pm:\n try:\n execfile(srcfilename, globs, globs)\n except:\n print sys.exc_info()[1]\n pdb.post_mortem(sys.exc_info()[2])\n else:\n pdb.run(\"execfile(%r)\" % srcfilename, globs, globs)\n finally:\n os.remove(srcfilename)"
},
{
"code": "def _dot_product(self, imgs_to_decode):\n return np.dot(imgs_to_decode.T, self.feature_images).T"
},
{
"code": "def set_certificate_issuer(\n self, vault_base_url, issuer_name, provider, credentials=None, organization_details=None, attributes=None, custom_headers=None, raw=False, **operation_config):\n parameter = models.CertificateIssuerSetParameters(provider=provider, credentials=credentials, organization_details=organization_details, attributes=attributes)\n url = self.set_certificate_issuer.metadata['url']\n path_format_arguments = {\n 'vaultBaseUrl': self._serialize.url(\"vault_base_url\", vault_base_url, 'str', skip_quote=True),\n 'issuer-name': self._serialize.url(\"issuer_name\", issuer_name, 'str')\n }\n url = self._client.format_url(url, **path_format_arguments)\n query_parameters = {}\n query_parameters['api-version'] = self._serialize.query(\"self.api_version\", self.api_version, 'str')\n header_parameters = {}\n header_parameters['Content-Type'] = 'application/json; charset=utf-8'\n if self.config.generate_client_request_id:\n header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())\n if custom_headers:\n header_parameters.update(custom_headers)\n if self.config.accept_language is not None:\n header_parameters['accept-language'] = self._serialize.header(\"self.config.accept_language\", self.config.accept_language, 'str')\n body_content = self._serialize.body(parameter, 'CertificateIssuerSetParameters')\n request = self._client.put(url, query_parameters)\n response = self._client.send(\n request, header_parameters, body_content, stream=False, **operation_config)\n if response.status_code not in [200]:\n raise models.KeyVaultErrorException(self._deserialize, response)\n deserialized = None\n if response.status_code == 200:\n deserialized = self._deserialize('IssuerBundle', response)\n if raw:\n client_raw_response = ClientRawResponse(deserialized, response)\n return client_raw_response\n return deserialized"
},
{
"code": "def remove_interval(self, time):\n if self.tier_type != 'IntervalTier':\n raise Exception('Tiertype must be IntervalTier.')\n self.intervals = [i for i in self.intervals\n if not(i[0] <= time and i[1] >= time)]"
},
{
"code": "def _run_valid(self, epoch, valid_set, dry_run=False, save_path=None):\n costs = self.valid_step(valid_set)\n _, J = costs[0]\n new_best = False\n if self.best_cost - J > self.best_cost * self.min_improvement:\n self.best_params = self.copy_params()\n new_best = True\n if not dry_run:\n self.best_cost = J\n self.best_epoch = epoch\n self.save_checkpoint(save_path)\n self.report(dict(costs), type=\"valid\", epoch=0 if dry_run else epoch, new_best=new_best)\n self.last_run_costs = costs\n return epoch - self.best_epoch < self.patience"
},
{
"code": "def Bin(self):\n err = _Bin(self.transit, self.limbdark, self.settings, self.arrays)\n if err != _ERR_NONE: RaiseError(err)"
},
{
"code": "def get_namespaces(self, prefix=None):\n params = {\"prefix\": prefix}\n return self.request(method=\"get\", params=params).json()"
},
{
"code": "def geckoboard_rag_widget(request):\n params = get_gecko_params(request)\n print params['uids']\n max_date = datetime.now()-timedelta(days=params['days_back'])\n metrics = Metric.objects.filter(uid__in=params['uids'])\n results = [(metric.latest_count(frequency=params['frequency'], count=not params['cumulative'],\n cumulative=params['cumulative'], max_date=max_date), metric.title) for metric in metrics]\n return tuple(results)"
},
{
"code": "def _read_compressed_points_data(self, laszip_vlr, point_format):\n offset_to_chunk_table = struct.unpack(\"<q\", self.stream.read(8))[0]\n size_of_point_data = offset_to_chunk_table - self.stream.tell()\n if offset_to_chunk_table <= 0:\n logger.warning(\n \"Strange offset to chunk table: {}, ignoring it..\".format(\n offset_to_chunk_table\n )\n )\n size_of_point_data = -1\n points = record.PackedPointRecord.from_compressed_buffer(\n self.stream.read(size_of_point_data),\n point_format,\n self.header.point_count,\n laszip_vlr,\n )\n return points"
},
{
"code": "def get_system_per_cpu_times():\n ret = []\n for cpu_t in _psutil_mswindows.get_system_cpu_times():\n user, system, idle = cpu_t\n item = _cputimes_ntuple(user, system, idle)\n ret.append(item)\n return ret"
},
{
"code": "def _init_from_bool(self, z, x):\n if z is None:\n raise QiskitError(\"z vector must not be None.\")\n if x is None:\n raise QiskitError(\"x vector must not be None.\")\n if len(z) != len(x):\n raise QiskitError(\"length of z and x vectors must be \"\n \"the same. (z: {} vs x: {})\".format(len(z), len(x)))\n z = _make_np_bool(z)\n x = _make_np_bool(x)\n self._z = z\n self._x = x\n return self"
},
{
"code": "def _expand_default(self, option):\n if self.parser is None or not self.default_tag:\n return option.help\n optname = option._long_opts[0][2:]\n try:\n provider = self.parser.options_manager._all_options[optname]\n except KeyError:\n value = None\n else:\n optdict = provider.get_option_def(optname)\n optname = provider.option_attrname(optname, optdict)\n value = getattr(provider.config, optname, optdict)\n value = utils._format_option_value(optdict, value)\n if value is optparse.NO_DEFAULT or not value:\n value = self.NO_DEFAULT_VALUE\n return option.help.replace(self.default_tag, str(value))"
},
{
"code": "def map(self, func, value_shape=None, dtype=None):\n if value_shape is None or dtype is None:\n try:\n mapped = func(random.randn(*self.plan).astype(self.dtype))\n except Exception:\n first = self._rdd.first()\n if first:\n mapped = func(first[1])\n if value_shape is None:\n value_shape = mapped.shape\n if dtype is None:\n dtype = mapped.dtype\n chunked_dims = where(self.plan != self.vshape)[0]\n unchunked_dims = where(self.plan == self.vshape)[0]\n if len(value_shape) != len(self.plan):\n raise NotImplementedError('map on ChunkedArray cannot drop dimensions')\n if any([value_shape[i] != self.plan[i] for i in chunked_dims]):\n raise ValueError('map cannot change the sizes of chunked dimensions')\n def check_and_apply(v):\n new = func(v)\n if len(unchunked_dims) > 0:\n if any([new.shape[i] != value_shape[i] for i in unchunked_dims]):\n raise Exception(\"Map operation did not produce values of uniform shape.\")\n if len(chunked_dims) > 0:\n if any([v.shape[i] != new.shape[i] for i in chunked_dims]):\n raise Exception(\"Map operation changed the size of a chunked dimension\")\n return new\n rdd = self._rdd.mapValues(check_and_apply)\n vshape = [value_shape[i] if i in unchunked_dims else self.vshape[i] for i in range(len(self.vshape))]\n newshape = r_[self.kshape, vshape].astype(int).tolist()\n return self._constructor(rdd, shape=tuple(newshape), dtype=dtype,\n plan=asarray(value_shape)).__finalize__(self)"
},
{
"code": "def get_data(self, cache=True, as_text=False, parse_form_data=False):\n rv = getattr(self, '_cached_data', None)\n if rv is None:\n if parse_form_data:\n self._load_form_data()\n rv = self.stream.read()\n if cache:\n self._cached_data = rv\n if as_text:\n rv = rv.decode(self.charset, self.encoding_errors)\n return rv"
},
{
"code": "def main(mash_output, sample_id):\n logger.info(\"Reading file : {}\".format(mash_output))\n read_mash_output = open(mash_output)\n dic = {}\n median_list = []\n filtered_dic = {}\n logger.info(\"Generating dictionary and list to pre-process the final json\")\n for line in read_mash_output:\n tab_split = line.split(\"\\t\")\n identity = tab_split[0]\n median_multiplicity = tab_split[2]\n query_id = tab_split[4]\n dic[query_id] = [identity, median_multiplicity]\n median_list.append(float(median_multiplicity))\n output_json = open(\" \".join(mash_output.split(\".\")[:-1]) + \".json\", \"w\")\n if len(median_list) > 0:\n median_cutoff = median(median_list)\n logger.info(\"Generating final json to dump to a file\")\n for k, v in dic.items():\n copy_number = int(float(v[1]) / median_cutoff)\n if float(v[1]) > median_cutoff:\n filtered_dic[\"_\".join(k.split(\"_\")[0:3])] = [\n round(float(v[0]),2),\n copy_number\n ]\n logger.info(\n \"Exported dictionary has {} entries\".format(len(filtered_dic)))\n else:\n logger.error(\"No matches were found using mash screen for the queried reads\")\n output_json.write(json.dumps(filtered_dic))\n output_json.close()\n json_dic = {\n \"tableRow\": [{\n \"sample\": sample_id,\n \"data\": [{\n \"header\": \"Mash Screen\",\n \"table\": \"plasmids\",\n \"patlas_mashscreen\": filtered_dic,\n \"value\": len(filtered_dic)\n }]\n }],\n }\n with open(\".report.json\", \"w\") as json_report:\n json_report.write(json.dumps(json_dic, separators=(\",\", \":\")))"
},
{
"code": "def add_import(\n self, sym: sym.Symbol, module: types.ModuleType, *aliases: sym.Symbol\n ) -> None:\n self._imports.swap(lambda m: m.assoc(sym, module))\n if aliases:\n self._import_aliases.swap(\n lambda m: m.assoc(\n *itertools.chain.from_iterable([(alias, sym) for alias in aliases])\n )\n )"
},
{
"code": "def delete_report(self, report):\n url = ACCOUNTS_API.format(report.account_id) + \"/reports/{}/{}\".format(\n report.type, report.report_id)\n response = self._delete_resource(url)\n return True"
},
{
"code": "def delete(self, blocksize=100):\n from .columns import MODELS_REFERENCED\n if not self._model._no_fk or self._model._namespace in MODELS_REFERENCED:\n raise QueryError(\"Can't delete entities of models with foreign key relationships\")\n de = []\n i = 0\n for result in self.iter_result(pagesize=blocksize):\n de.append(result)\n i += 1\n if i >= blocksize:\n session.delete(de)\n del de[:]\n i = 0\n if de:\n session.delete(de)"
},
{
"code": "def _ep_need_close(self):\n LOG.debug(\"Session %s close requested - closing...\",\n self._name)\n links = self._links.copy()\n for link in links:\n link._session_closed()"
},
{
"code": "def users(store):\n user_objs = list(store.users())\n total_events = store.user_events().count()\n for user_obj in user_objs:\n if user_obj.get('institutes'):\n user_obj['institutes'] = [store.institute(inst_id) for inst_id in user_obj.get('institutes')]\n else:\n user_obj['institutes'] = []\n user_obj['events'] = store.user_events(user_obj).count()\n user_obj['events_rank'] = event_rank(user_obj['events'])\n return dict(\n users=sorted(user_objs, key=lambda user: -user['events']),\n total_events=total_events,\n )"
},
{
"code": "def linear_connection(plist, lane):\n logger.debug(\n \"Establishing linear connection with processes: {}\".format(plist))\n res = []\n previous = None\n for p in plist:\n if not previous:\n previous = p\n continue\n res.append({\n \"input\": {\n \"process\": previous,\n \"lane\": lane\n },\n \"output\": {\n \"process\": p,\n \"lane\": lane\n }\n })\n previous = p\n return res"
},
{
"code": "def run_migrations_online():\n connectable = settings.engine\n with connectable.connect() as connection:\n context.configure(\n connection=connection,\n transaction_per_migration=True,\n target_metadata=target_metadata,\n compare_type=COMPARE_TYPE,\n )\n with context.begin_transaction():\n context.run_migrations()"
},
{
"code": "def map_generic(self, func):\n def process_record(val):\n newval = empty(1, dtype=\"object\")\n newval[0] = func(val)\n return newval\n rdd = self._rdd.mapValues(process_record)\n nchunks = self.getnumber(self.plan, self.vshape)\n newshape = tuple([int(s) for s in r_[self.kshape, nchunks]])\n newsplit = len(self.shape)\n return BoltArraySpark(rdd, shape=newshape, split=newsplit, ordered=self._ordered, dtype=\"object\")"
},
{
"code": "def get_conn(self):\n if not self._conn:\n http_authorized = self._authorize()\n self._conn = build('compute', self.api_version,\n http=http_authorized, cache_discovery=False)\n return self._conn"
},
{
"code": "def parse_args(argv):\n global g_new_messages_to_exclude\n global g_old_messages_to_remove\n global g_load_java_message_filename\n global g_save_java_message_filename\n global g_print_java_messages\n if len(argv) < 2:\n usage()\n i = 1\n while (i < len(argv)):\n s = argv[i]\n if (s == \"--inputfileadd\"):\n i += 1\n if (i > len(argv)):\n usage()\n g_new_messages_to_exclude = argv[i]\n elif (s == \"--inputfilerm\"):\n i += 1\n if (i > len(argv)):\n usage()\n g_old_messages_to_remove = argv[i]\n elif (s == \"--loadjavamessage\"):\n i += 1\n if i > len(argv):\n usage()\n g_load_java_message_filename = argv[i]\n elif (s == \"--savejavamessage\"):\n i += 1\n if (i > len(argv)):\n usage()\n g_save_java_message_filename = argv[i]\n elif (s == '--printjavamessage'):\n i += 1\n g_print_java_messages = True\n g_load_java_message_filename = argv[i]\n elif (s == '--help'):\n usage()\n else:\n unknown_arg(s)\n i += 1"
},
{
"code": "def expand_files(self, modules):\n result, errors = utils.expand_modules(\n modules, self.config.black_list, self.config.black_list_re\n )\n for error in errors:\n message = modname = error[\"mod\"]\n key = error[\"key\"]\n self.set_current_module(modname)\n if key == \"fatal\":\n message = str(error[\"ex\"]).replace(os.getcwd() + os.sep, \"\")\n self.add_message(key, args=message)\n return result"
},
{
"code": "def _m(self):\n assert not hasattr(self, \"_interfaces\") or not self._interfaces, \\\n \"Too late to change direction of interface\"\n self._direction = DIRECTION.asIntfDirection(DIRECTION.opposite(self._masterDir))\n return self"
},
{
"code": "def __nn_filter_helper(R_data, R_indices, R_ptr, S, aggregate):\n s_out = np.empty_like(S)\n for i in range(len(R_ptr)-1):\n targets = R_indices[R_ptr[i]:R_ptr[i+1]]\n if not len(targets):\n s_out[i] = S[i]\n continue\n neighbors = np.take(S, targets, axis=0)\n if aggregate is np.average:\n weights = R_data[R_ptr[i]:R_ptr[i+1]]\n s_out[i] = aggregate(neighbors, axis=0, weights=weights)\n else:\n s_out[i] = aggregate(neighbors, axis=0)\n return s_out"
},
{
"code": "def fit(self, Z, **fit_params):\n Zt, fit_params = self._pre_transform(Z, **fit_params)\n self.steps[-1][-1].fit(Zt, **fit_params)\n Zt.unpersist()\n return self"
},
{
"code": "def _make_content_item(node, mime_type=None, alternate_data=None):\n raw = node.data\n if getattr(node, 'encoding', None) == 'zlib':\n try:\n raw = zlib.decompress(node.data)\n except Exception, exc:\n if alternate_data is not None:\n try:\n raw = zlib.decompress(alternate_data)\n except Exception:\n raise exc\n else:\n raise\n if mime_type is None:\n mime_type = node.mime_type\n raw = raw.decode('utf8').encode('utf8')\n return streamcorpus.ContentItem(raw=raw, media_type=mime_type)"
},
{
"code": "def simUnit(self, synthesisedUnit: Unit, until: float, extraProcesses=[]):\n beforeSim = self.config.beforeSim\n if beforeSim is not None:\n beforeSim(self, synthesisedUnit)\n add_proc = self.add_process\n for p in extraProcesses:\n add_proc(p(self))\n self._initUnitSignals(synthesisedUnit)\n self.run(until)"
},
{
"code": "def parse(self, hcl, canonicalize=False):\n return self.request(\"parse\", json={\"JobHCL\": hcl, \"Canonicalize\": canonicalize}, method=\"post\", allow_redirects=True).json()"
},
{
"code": "def has_no_unchecked_field(self, locator, **kwargs):\n kwargs[\"checked\"] = False\n return self.has_no_selector(\"field\", locator, **kwargs)"
},
{
"code": "def reconnect(self):\n self.log.debug(\"reconnect(): Initialzion reconnect sequence..\")\n self.connected.clear()\n self.reconnect_required.set()\n if self.socket:\n self.socket.close()"
},
{
"code": "def lowpass_filter(data, cutoff, fs, order=5):\n nyq = 0.5 * fs\n normal_cutoff = cutoff / nyq\n b, a = signal.butter(order, normal_cutoff, btype='low', analog=False)\n y = signal.lfilter(b, a, data)\n return y"
},
{
"code": "def _add(self, to_add):\n if PyFunceble.CONFIGURATION[\"mining\"]:\n if PyFunceble.INTERN[\"file_to_test\"] not in PyFunceble.INTERN[\"mined\"]:\n PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]] = {}\n for element in to_add:\n if (\n element\n in PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]]\n ):\n PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]][\n element\n ].extend(to_add[element])\n else:\n PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]][\n element\n ] = to_add[element]\n PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]][\n element\n ] = List(\n PyFunceble.INTERN[\"mined\"][PyFunceble.INTERN[\"file_to_test\"]][\n element\n ]\n ).format()\n self._backup()"
},
{
"code": "def square(duration: int, amp: complex, period: float = None,\n phase: float = 0, name: str = None) -> SamplePulse:\n if period is None:\n period = duration\n return _sampled_square_pulse(duration, amp, period, phase=phase, name=name)"
},
{
"code": "def size(self, train=False, valid=False, xval=False):\n tm = ModelBase._get_metrics(self, train, valid, xval)\n m = {}\n for k, v in tm.items():\n m[k] = None if v is None else [v[2] for v in v._metric_json[\"centroid_stats\"].cell_values]\n return list(m.values())[0] if len(m) == 1 else m"
},
{
"code": "def find_files(filenames, recursive, exclude):\n while filenames:\n name = filenames.pop(0)\n if recursive and os.path.isdir(name):\n for root, directories, children in os.walk(name):\n filenames += [os.path.join(root, f) for f in children\n if match_file(os.path.join(root, f),\n exclude)]\n directories[:] = [d for d in directories\n if match_file(os.path.join(root, d),\n exclude)]\n else:\n if not is_exclude_file(name, exclude):\n yield name"
},
{
"code": "def is_literal_or_name(value):\n try:\n ast.literal_eval(value)\n return True\n except (SyntaxError, ValueError):\n pass\n if value.strip() in ['dict()', 'list()', 'set()']:\n return True\n return re.match(r'^\\w+\\s*$', value)"
},
{
"code": "def complete_restore(\n self, location_name, operation_id, last_backup_name, custom_headers=None, raw=False, polling=True, **operation_config):\n raw_result = self._complete_restore_initial(\n location_name=location_name,\n operation_id=operation_id,\n last_backup_name=last_backup_name,\n custom_headers=custom_headers,\n raw=True,\n **operation_config\n )\n def get_long_running_output(response):\n if raw:\n client_raw_response = ClientRawResponse(None, response)\n return client_raw_response\n lro_delay = operation_config.get(\n 'long_running_operation_timeout',\n self.config.long_running_operation_timeout)\n if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)\n elif polling is False: polling_method = NoPolling()\n else: polling_method = polling\n return LROPoller(self._client, raw_result, get_long_running_output, polling_method)"
},
{
"code": "def post(self, headers={}, body=\"\"):\n code, message = self.command(\"POST\")\n if code != 340:\n raise NNTPReplyError(code, message)\n hdrs = utils.unparse_headers(headers)\n self.socket.sendall(hdrs)\n if isinstance(body, basestring):\n body = cStringIO.StringIO(body)\n illegal = False\n for line in body:\n if line.startswith(\".\"):\n line = \".\" + line\n if line.endswith(\"\\r\\n\"):\n line = line[:-2]\n elif line.endswith(\"\\n\"):\n line = line[:-1]\n if any(c in line for c in \"\\0\\r\"):\n illegal = True\n break\n self.socket.sendall(line + \"\\r\\n\")\n self.socket.sendall(\".\\r\\n\")\n code, message = self.status()\n if illegal:\n raise NNTPDataError(\"Illegal characters found\")\n if code != 240:\n raise NNTPReplyError(code, message)\n message_id = message.split(None, 1)[0]\n if message_id.startswith(\"<\") and message_id.endswith(\">\"):\n return message_id\n return True"
},
{
"code": "def has_context_loop(state, incorrect_msg, exact_names):\n return _test(\n state,\n incorrect_msg or MSG_INCORRECT_LOOP,\n exact_names,\n tv_name=\"_target_vars\",\n highlight_name=\"target\",\n )"
},
{
"code": "def imcrop(img, bboxes, scale=1.0, pad_fill=None):\n chn = 1 if img.ndim == 2 else img.shape[2]\n if pad_fill is not None:\n if isinstance(pad_fill, (int, float)):\n pad_fill = [pad_fill for _ in range(chn)]\n assert len(pad_fill) == chn\n _bboxes = bboxes[None, ...] if bboxes.ndim == 1 else bboxes\n scaled_bboxes = bbox_scaling(_bboxes, scale).astype(np.int32)\n clipped_bbox = bbox_clip(scaled_bboxes, img.shape)\n patches = []\n for i in range(clipped_bbox.shape[0]):\n x1, y1, x2, y2 = tuple(clipped_bbox[i, :])\n if pad_fill is None:\n patch = img[y1:y2 + 1, x1:x2 + 1, ...]\n else:\n _x1, _y1, _x2, _y2 = tuple(scaled_bboxes[i, :])\n if chn == 2:\n patch_shape = (_y2 - _y1 + 1, _x2 - _x1 + 1)\n else:\n patch_shape = (_y2 - _y1 + 1, _x2 - _x1 + 1, chn)\n patch = np.array(\n pad_fill, dtype=img.dtype) * np.ones(\n patch_shape, dtype=img.dtype)\n x_start = 0 if _x1 >= 0 else -_x1\n y_start = 0 if _y1 >= 0 else -_y1\n w = x2 - x1 + 1\n h = y2 - y1 + 1\n patch[y_start:y_start + h, x_start:x_start +\n w, ...] = img[y1:y1 + h, x1:x1 + w, ...]\n patches.append(patch)\n if bboxes.ndim == 1:\n return patches[0]\n else:\n return patches"
},
{
"code": "def validate(self, obj, value):\n try:\n if issubclass(value, self.klass):\n return value\n except:\n if (value is None) and (self._allow_none):\n return value\n self.error(obj, value)"
},
{
"code": "def plot(\n self, data, bbox=None, plot_type='scatter',\n fig_kwargs=None, bmap_kwargs=None, plot_kwargs=None,\n cbar_kwargs=None):\n from mpl_toolkits.basemap import Basemap\n fig_kwargs = fig_kwargs or {}\n bmap_kwargs = bmap_kwargs or {}\n plot_kwargs = plot_kwargs or {}\n cbar_kwargs = cbar_kwargs or {}\n if not bbox:\n bbox = (\n self.nodes_df.y.min(),\n self.nodes_df.x.min(),\n self.nodes_df.y.max(),\n self.nodes_df.x.max())\n fig, ax = plt.subplots(**fig_kwargs)\n bmap = Basemap(\n bbox[1], bbox[0], bbox[3], bbox[2], ax=ax, **bmap_kwargs)\n bmap.drawcoastlines()\n bmap.drawmapboundary()\n x, y = bmap(self.nodes_df.x.values, self.nodes_df.y.values)\n if plot_type == 'scatter':\n plot = bmap.scatter(\n x, y, c=data.values, **plot_kwargs)\n elif plot_type == 'hexbin':\n plot = bmap.hexbin(\n x, y, C=data.values, **plot_kwargs)\n bmap.colorbar(plot, **cbar_kwargs)\n return bmap, fig, ax"
},
{
"code": "def update_configuration(cfgfile=None):\n configobj.DEFAULT_INTERPOLATION = 'template'\n cfgfile = configuration_file(cfgfile)\n cfg = configobj.ConfigObj(cfgfile, configspec=cfgspec, encoding='utf-8')\n validator = Validator()\n val = cfg.validate(validator)\n if val is not True:\n raise ValueError('Invalid configuration: %s' % val)\n if len(cfg['capture']['files']) != len(cfg['capture']['flavors']):\n raise ValueError('List of files and flavors do not match')\n globals()['__config'] = cfg\n logger_init()\n if cfg['server'].get('url', '').endswith('/'):\n logger.warning('Base URL ends with /. This is most likely a '\n 'configuration error. The URL should contain nothing '\n 'of the service paths.')\n logger.info('Configuration loaded from %s' % cfgfile)\n check()\n return cfg"
},
{
"code": "def times_csv(path, times, annotations=None, delimiter=',', fmt='%0.3f'):\n r\n if annotations is not None and len(annotations) != len(times):\n raise ParameterError('len(annotations) != len(times)')\n with open(path, 'w') as output_file:\n writer = csv.writer(output_file, delimiter=delimiter)\n if annotations is None:\n for t in times:\n writer.writerow([fmt % t])\n else:\n for t, lab in zip(times, annotations):\n writer.writerow([(fmt % t), lab])"
},
{
"code": "def add_subgraph(self, info):\n if not info.initialized:\n return\n graph = self._request_graph(info.ui.control)\n if graph is not None:\n subgraph = Subgraph()\n retval = subgraph.edit_traits(parent = info.ui.control,\n kind = \"livemodal\")\n if retval.result:\n graph.subgraphs.append(subgraph)"
},
{
"code": "def _onDeviceStatus(self, client, userdata, pahoMessage):\n try:\n status = Status(pahoMessage)\n self.logger.debug(\"Received %s action from %s\" % (status.action, status.clientId))\n if self.deviceStatusCallback:\n self.deviceStatusCallback(status)\n except InvalidEventException as e:\n self.logger.critical(str(e))"
},
{
"code": "def get_input(prompt, default=None, exit_msg='bye!'):\n try:\n response = six.moves.input(prompt)\n except (KeyboardInterrupt, EOFError):\n print()\n print(exit_msg)\n exit()\n try:\n return int(response)\n except ValueError:\n if response.strip() == \"\" and default is not None:\n return default\n else:\n return response"
},
{
"code": "def encode(self):\n header = bytearray(1)\n varHeader = encode16Int(self.msgId)\n header[0] = 0xB0 \n header.extend(encodeLength(len(varHeader)))\n header.extend(varHeader)\n self.encoded = header\n return str(header) if PY2 else bytes(header)"
},
{
"code": "def set_piece_at(self, square, piece, from_hand=False, into_hand=False):\n if from_hand:\n self.remove_piece_from_hand(piece.piece_type, self.turn)\n self.remove_piece_at(square, into_hand)\n self.pieces[square] = piece.piece_type\n mask = BB_SQUARES[square]\n piece_type = piece.piece_type\n self.piece_bb[piece_type] |= mask\n if piece_type == KING:\n self.king_squares[piece.color] = square\n self.occupied.ixor(mask, piece.color, square)\n if piece.color == BLACK:\n piece_index = (piece.piece_type - 1) * 2\n else:\n piece_index = (piece.piece_type - 1) * 2 + 1\n self.incremental_zobrist_hash ^= DEFAULT_RANDOM_ARRAY[81 * piece_index + 9 * rank_index(square) + file_index(square)]"
},
{
"code": "def _check_relative_import(\n self, modnode, importnode, importedmodnode, importedasname\n ):\n if not self.linter.is_message_enabled(\"relative-import\"):\n return None\n if importedmodnode.file is None:\n return False\n if modnode is importedmodnode:\n return False\n if modnode.absolute_import_activated() or getattr(importnode, \"level\", None):\n return False\n if importedmodnode.name != importedasname:\n self.add_message(\n \"relative-import\",\n args=(importedasname, importedmodnode.name),\n node=importnode,\n )\n return None\n return None"
},
{
"code": "def sold_out_and_unregistered(context):\n user = user_for_context(context)\n if hasattr(user, \"attendee\") and user.attendee.completed_registration:\n return None\n ticket_category = settings.TICKET_PRODUCT_CATEGORY\n categories = available_categories(context)\n return ticket_category not in [cat.id for cat in categories]"
},
{
"code": "def is_token_from_emulator(auth_header: str) -> bool:\n if not auth_header:\n return False\n parts = auth_header.split(' ')\n if len(parts) != 2:\n return False\n auth_scheme = parts[0]\n bearer_token = parts[1]\n if auth_scheme != 'Bearer':\n return False\n token = jwt.decode(bearer_token, verify=False)\n if not token:\n return False\n issuer = token['iss']\n if not issuer:\n return False\n issuer_list = EmulatorValidation.TO_BOT_FROM_EMULATOR_TOKEN_VALIDATION_PARAMETERS.issuer\n if issuer_list and not issuer in issuer_list:\n return False\n return True"
},
{
"code": "def render_template(template_file, dst_file, **kwargs):\n with open(template_file) as f:\n template_text = f.read()\n dst_text = template_text\n for key, value in kwargs.iteritems():\n dst_text = dst_text .replace(\"{{\" + key + \"}}\", value)\n with open(dst_file, \"wt\") as f:\n f.write(dst_text)"
},
{
"code": "def is_subdomain(self, domain=None):\n if domain:\n to_test = domain\n elif self.element:\n to_test = self.element\n else:\n to_test = PyFunceble.INTERN[\"to_test\"]\n return self.is_domain_valid(to_test, subdomain_check=True)"
},
{
"code": "def make_logging_handlers_and_tools(self, multiproc=False):\n log_stdout = self.log_stdout\n if sys.stdout is self._stdout_to_logger:\n log_stdout = False\n if self.log_config:\n if multiproc:\n proc_log_config = self._mp_config\n else:\n proc_log_config = self._sp_config\n if proc_log_config:\n if isinstance(proc_log_config, dict):\n new_dict = self._handle_dict_config(proc_log_config)\n dictConfig(new_dict)\n else:\n parser = self._handle_config_parsing(proc_log_config)\n memory_file = self._parser_to_string_io(parser)\n fileConfig(memory_file, disable_existing_loggers=False)\n if log_stdout:\n std_name, std_level = self.log_stdout\n stdout = StdoutToLogger(std_name, log_level=std_level)\n stdout.start()\n self._tools.append(stdout)"
},
{
"code": "def _get_index_urls_locations(self, project_name):\n def mkurl_pypi_url(url):\n loc = posixpath.join(url, project_url_name)\n if not loc.endswith('/'):\n loc = loc + '/'\n return loc\n project_url_name = urllib_parse.quote(project_name.lower())\n if self.index_urls:\n main_index_url = Link(\n mkurl_pypi_url(self.index_urls[0]),\n trusted=True,\n )\n page = self._get_page(main_index_url)\n if page is None and PyPI.netloc not in str(main_index_url):\n warnings.warn(\n \"Failed to find %r at %s. It is suggested to upgrade \"\n \"your index to support normalized names as the name in \"\n \"/simple/{name}.\" % (project_name, main_index_url),\n RemovedInPip8Warning,\n )\n project_url_name = self._find_url_name(\n Link(self.index_urls[0], trusted=True),\n project_url_name,\n ) or project_url_name\n if project_url_name is not None:\n return [mkurl_pypi_url(url) for url in self.index_urls]\n return []"
},
{
"code": "def _setup_logging(self, log_level: str):\n level = getattr(logging, log_level)\n names = (\n 'aiohttp.access', 'aiohttp.internal', 'aiohttp.server',\n 'aiohttp.web', self.name)\n for name in names:\n setup_logger(name=name, stream=sys.stderr, level=level)"
},
{
"code": "def parse(self, selector):\n log.debug(self.obj)\n tokens = lex(selector)\n if self.peek(tokens, 'operator') == '*':\n self.match(tokens, 'operator')\n results = list(object_iter(self.obj))\n else:\n results = self.selector_production(tokens)\n results = [node.value for node in results]\n if len(results) == 1:\n return results[0]\n elif not len(results):\n return None\n return results"
},
{
"code": "def bandpass_filter(data, low, high, fs, order=5):\n nyq = 0.5 * fs\n low = low / nyq\n high = high / nyq\n b, a = signal.butter(order, [low, high], btype='band')\n y = signal.lfilter(b, a, data)\n return y"
},
{
"code": "def build_schema(m, c_c):\n schema = ET.Element('xs:schema')\n schema.set('xmlns:xs', 'http://www.w3.org/2001/XMLSchema')\n global_filter = lambda selected: ooaofooa.is_global(selected)\n for s_dt in m.select_many('S_DT', global_filter):\n datatype = build_type(s_dt)\n if datatype is not None:\n schema.append(datatype)\n scope_filter = lambda selected: ooaofooa.is_contained_in(selected, c_c)\n for s_dt in m.select_many('S_DT', scope_filter):\n datatype = build_type(s_dt)\n if datatype is not None:\n schema.append(datatype)\n component = build_component(m, c_c)\n schema.append(component)\n return schema"
},
{
"code": "def execute(option):\n namelist_option = []\n makefile_option = []\n flags = \"\"\n for entry in option:\n key = entry.keys()[0]\n if key == \"Problem Size\":\n namelist_option.append({\"SIZE\": entry[key]})\n elif key == \"F90\":\n makefile_option.append(entry)\n else:\n flags += entry[key] + \" \"\n makefile_option.append({\"F90FLAGS\": flags})\n namelist = create_input(namelist_option, \"namelist\",\n template_location=\"templates\")\n makefile_include = create_input(makefile_option, \"Makefile.include\",\n template_location=\"templates\")\n benchmark_base = \"shallow\"\n location = benchmark_base + \"/original/namelist\"\n my_file = open(location, 'w')\n my_file.write(namelist)\n my_file.flush()\n location = benchmark_base + \"/common/Makefile.include\"\n my_file = open(location, 'w')\n my_file.write(makefile_include)\n my_file.flush()\n base_path = benchmark_base + \"/original\"\n import subprocess\n make_process = subprocess.Popen([\"make\", \"clean\"], cwd=base_path,\n stderr=subprocess.PIPE,\n stdout=subprocess.PIPE)\n if make_process.wait() != 0:\n return False, []\n make_process = subprocess.Popen([\"make\"], cwd=base_path,\n stderr=subprocess.PIPE,\n stdout=subprocess.PIPE)\n if make_process.wait() != 0:\n return False, []\n make_process = subprocess.Popen([\"./shallow_base\"], cwd=base_path,\n stderr=subprocess.PIPE,\n stdout=subprocess.PIPE)\n if make_process.wait() != 0:\n return False, []\n stdout = make_process.stdout.read()\n for line in stdout.split(\"\\n\"):\n if \"Time-stepping\" in line:\n total_time = line.split()[2]\n return True, total_time"
},
{
"code": "def img_from_vgg(x):\n x = x.transpose((1, 2, 0))\n x[:, :, 0] += 103.939\n x[:, :, 1] += 116.779\n x[:, :, 2] += 123.68\n x = x[:,:,::-1]\n return x"
},
{
"code": "def remove_unique_identifiers(identifiers_to_tags, pipeline_links):\n for index, val in enumerate(pipeline_links):\n if val[\"input\"][\"process\"] != \"__init__\":\n val[\"input\"][\"process\"] = identifiers_to_tags[\n val[\"input\"][\"process\"]]\n if val[\"output\"][\"process\"] != \"__init__\":\n val[\"output\"][\"process\"] = identifiers_to_tags[\n val[\"output\"][\"process\"]]\n return pipeline_links"
},
{
"code": "def fetch_items(self, category, **kwargs):\n from_date = kwargs['from_date']\n if self.client.version[0] == 2 and self.client.version[1] == 8:\n fetcher = self._fetch_gerrit28(from_date)\n else:\n fetcher = self._fetch_gerrit(from_date)\n for review in fetcher:\n yield review"
},
{
"code": "def _imported_module(self, node, mod_path, relative):\n module = node.root()\n context_name = module.name\n if relative:\n mod_path = \"%s.%s\" % (\".\".join(context_name.split(\".\")[:-1]), mod_path)\n if self.compute_module(context_name, mod_path):\n if not hasattr(module, \"depends\"):\n module.depends = []\n mod_paths = module.depends\n if mod_path not in mod_paths:\n mod_paths.append(mod_path)"
},
{
"code": "def _get_existing_instance(self, query, value):\n if self.columns:\n result = query.filter_by(\n **{prop.key: value.get(prop.key) for prop in self.related_keys}\n ).one()\n else:\n result = query.get([value.get(prop.key) for prop in self.related_keys])\n if result is None:\n raise NoResultFound\n return result"
},
{
"code": "def deprecated(*args):\n def wrap(func):\n def wrapped_func(*args, **kwargs):\n warnings.warn(msg, category=DeprecationWarning)\n return func(*args, **kwargs)\n return wrapped_func\n if len(args) == 1 and callable(args[0]):\n msg = \"Function '%s' will be deprecated in future versions of \" \\\n \"Neurosynth.\" % args[0].__name__\n return wrap(args[0])\n else:\n msg = args[0]\n return wrap"
},
{
"code": "def _get_required_args(fn):\n argspec = tf_inspect.getfullargspec(fn)\n args = argspec.args\n if tf_inspect.isclass(fn):\n args = args[1:]\n if argspec.defaults:\n args = args[:-len(argspec.defaults)]\n return tuple(args)"
},
{
"code": "def compute_lst(self):\n if self.header[b'telescope_id'] == 6:\n self.coords = gbt_coords\n elif self.header[b'telescope_id'] == 4:\n self.coords = parkes_coords\n else:\n raise RuntimeError(\"Currently only Parkes and GBT supported\")\n if HAS_SLALIB:\n dut1 = 0.0\n mjd = self.header[b'tstart']\n tellong = np.deg2rad(self.coords[1])\n last = s.sla_gmst(mjd) - tellong + s.sla_eqeqx(mjd) + dut1\n if last < 0.0 : last = last + 2.0*np.pi\n return last\n else:\n raise RuntimeError(\"This method requires pySLALIB\")"
},
{
"code": "def register_metric(metric_name: str) -> Callable[..., Any]:\n def decorate(fn):\n fn_name = fn.__module__ + ':' + fn.__name__\n if metric_name in _REGISTRY and _REGISTRY[metric_name] != fn_name:\n log.warning('\"{}\" is already registered as a metric name, the old function will be ignored'\n .format(metric_name))\n _REGISTRY[metric_name] = fn_name\n return fn\n return decorate"
},
{
"code": "def _check_type(var, vtype):\n if vtype is None:\n return var is None\n if isinstance(vtype, _primitive_type):\n return var == vtype\n if vtype is str:\n return isinstance(var, _str_type)\n if vtype is int:\n return isinstance(var, _int_type)\n if vtype is numeric:\n return isinstance(var, _num_type)\n if isinstance(vtype, MagicType):\n return vtype.check(var)\n if isinstance(vtype, type):\n return isinstance(var, vtype)\n if isinstance(vtype, list):\n elem_type = U(*vtype)\n return isinstance(var, list) and all(_check_type(item, elem_type) for item in var)\n if isinstance(vtype, set):\n elem_type = U(*vtype)\n return isinstance(var, set) and all(_check_type(item, elem_type) for item in var)\n if isinstance(vtype, tuple):\n return (isinstance(var, tuple) and len(vtype) == len(var) and\n all(_check_type(var[i], vtype[i]) for i in range(len(vtype))))\n if isinstance(vtype, dict):\n ttkv = U(*viewitems(vtype))\n return isinstance(var, dict) and all(_check_type(kv, ttkv) for kv in viewitems(var))\n if isinstance(vtype, (FunctionType, BuiltinFunctionType)):\n return vtype(var)\n raise RuntimeError(\"Ivalid type %r in _check_type()\" % vtype)"
},
{
"code": "def _basilisp_bytecode(\n mtime: int, source_size: int, code: List[types.CodeType]\n) -> bytes:\n data = bytearray(MAGIC_NUMBER)\n data.extend(_w_long(mtime))\n data.extend(_w_long(source_size))\n data.extend(marshal.dumps(code))\n return data"
},
{
"code": "def select_name_pattern(source, pat):\n return filter(lambda x: pat.match(x.xml_name) is not None, select_elements(source))"
},
{
"code": "def get_overrides_filename(variable):\n filename = os.environ.get(variable)\n if filename is None:\n msg = 'Please set the {} environment variable.'.format(variable)\n raise EnvironmentError(msg)\n return filename"
},
{
"code": "def get_order(self, order_id):\n resp = self.get('/orders/{}'.format(order_id))\n return Order(resp)"
},
{
"code": "def networkdays(from_date, to_date, locale='en-US'):\n holidays = locales[locale]\n return workdays.networkdays(from_date, to_date, holidays)"
},
{
"code": "def start_proxy(self):\n self._download_sql_proxy_if_needed()\n if self.sql_proxy_process:\n raise AirflowException(\"The sql proxy is already running: {}\".format(\n self.sql_proxy_process))\n else:\n command_to_run = [self.sql_proxy_path]\n command_to_run.extend(self.command_line_parameters)\n try:\n self.log.info(\"Creating directory %s\",\n self.cloud_sql_proxy_socket_directory)\n os.makedirs(self.cloud_sql_proxy_socket_directory)\n except OSError:\n pass\n command_to_run.extend(self._get_credential_parameters())\n self.log.info(\"Running the command: `%s`\", \" \".join(command_to_run))\n self.sql_proxy_process = Popen(command_to_run,\n stdin=PIPE, stdout=PIPE, stderr=PIPE)\n self.log.info(\"The pid of cloud_sql_proxy: %s\", self.sql_proxy_process.pid)\n while True:\n line = self.sql_proxy_process.stderr.readline().decode('utf-8')\n return_code = self.sql_proxy_process.poll()\n if line == '' and return_code is not None:\n self.sql_proxy_process = None\n raise AirflowException(\n \"The cloud_sql_proxy finished early with return code {}!\".format(\n return_code))\n if line != '':\n self.log.info(line)\n if \"googleapi: Error\" in line or \"invalid instance name:\" in line:\n self.stop_proxy()\n raise AirflowException(\n \"Error when starting the cloud_sql_proxy {}!\".format(\n line))\n if \"Ready for new connections\" in line:\n return"
},
{
"code": "def init_role(self, role_name, role_vms, role_perms):\n pvms = self.get_session.query(sqla_models.PermissionView).all()\n pvms = [p for p in pvms if p.permission and p.view_menu]\n role = self.find_role(role_name)\n if not role:\n role = self.add_role(role_name)\n if len(role.permissions) == 0:\n self.log.info('Initializing permissions for role:%s in the database.', role_name)\n role_pvms = set()\n for pvm in pvms:\n if pvm.view_menu.name in role_vms and pvm.permission.name in role_perms:\n role_pvms.add(pvm)\n role.permissions = list(role_pvms)\n self.get_session.merge(role)\n self.get_session.commit()\n else:\n self.log.debug('Existing permissions for the role:%s '\n 'within the database will persist.', role_name)"
},
{
"code": "def glm(interactive=True, echo=True, testing=False):\n def demo_body(go):\n go()\n h2o.init()\n go()\n prostate = h2o.load_dataset(\"prostate\")\n go()\n prostate.describe()\n go()\n train, test = prostate.split_frame(ratios=[0.70])\n go()\n train[\"CAPSULE\"] = train[\"CAPSULE\"].asfactor()\n test[\"CAPSULE\"] = test[\"CAPSULE\"].asfactor()\n go()\n from h2o.estimators import H2OGeneralizedLinearEstimator\n prostate_glm = H2OGeneralizedLinearEstimator(family=\"binomial\", alpha=[0.5])\n prostate_glm.train(x=[\"AGE\", \"RACE\", \"PSA\", \"VOL\", \"GLEASON\"],\n y=\"CAPSULE\", training_frame=train)\n go()\n prostate_glm.show()\n go()\n predictions = prostate_glm.predict(test)\n predictions.show()\n go()\n performance = prostate_glm.model_performance(test)\n performance.show()\n _run_demo(demo_body, interactive, echo, testing)"
},
{
"code": "def dsync_handler(self, args):\n self.opt.recursive = True\n self.opt.sync_check = True\n self.opt.force = True\n self.validate('cmd|s3,local|s3,local', args)\n source = args[1]\n target = args[2]\n self.s3handler().dsync_files(source, target)"
},
{
"code": "def mkstemp(self, suffix, prefix, directory=None):\n if not directory:\n directory = self.artifacts_dir\n fd, fname = tempfile.mkstemp(suffix, prefix, directory)\n os.close(fd)\n os.chmod(fname, 0o644)\n return fname"
},
{
"code": "def patch_protocol_for_agent(protocol):\n old_makeConnection = protocol.makeConnection\n old_connectionLost = protocol.connectionLost\n def new_makeConnection(transport):\n patch_transport_fake_push_producer(transport)\n patch_transport_abortConnection(transport, protocol)\n return old_makeConnection(transport)\n def new_connectionLost(reason):\n if protocol._fake_connection_aborted and reason.check(ConnectionDone):\n reason = Failure(ConnectionAborted())\n return old_connectionLost(reason)\n protocol.makeConnection = new_makeConnection\n protocol.connectionLost = new_connectionLost\n protocol._fake_connection_aborted = False"
},
{
"code": "def cinder(*arg):\n check_event_type(Openstack.Cinder, *arg)\n event_type = arg[0]\n def decorator(func):\n if event_type.find(\"*\") != -1:\n event_type_pattern = pre_compile(event_type)\n cinder_customer_process_wildcard[event_type_pattern] = func\n else:\n cinder_customer_process[event_type] = func\n log.info(\"add function {0} to process event_type:{1}\".format(func.__name__, event_type))\n @functools.wraps(func)\n def wrapper(*args, **kwargs):\n func(*args, **kwargs)\n return wrapper\n return decorator"
},
{
"code": "def formalize(self):\n source_class = self.source_link.to_metaclass\n target_class = self.target_link.to_metaclass\n source_class.referential_attributes |= set(self.source_keys)\n target_class.identifying_attributes |= set(self.target_keys)\n def fget(inst, ref_name, alt_prop):\n other_inst = self.target_link.navigate_one(inst)\n if other_inst is None and alt_prop:\n return alt_prop.fget(inst)\n return getattr(other_inst, ref_name, None)\n def fset(inst, value, name, ref_name, alt_prop):\n kind = get_metaclass(inst).kind\n raise MetaException('%s.%s is a referential attribute '\\\n 'and cannot be assigned directly'% (kind, name))\n for ref_key, primary_key in zip(self.source_keys, self.target_keys):\n prop = getattr(source_class.clazz, ref_key, None)\n prop = property(partial(fget, ref_name=primary_key, alt_prop=prop), \n partial(fset, name=ref_key, ref_name=primary_key, alt_prop=prop))\n setattr(source_class.clazz, ref_key, prop)"
},
{
"code": "def write(self, output_stream, kmip_version=enums.KMIPVersion.KMIP_1_0):\n local_stream = utils.BytearrayStream()\n if self._unique_identifier:\n self._unique_identifier.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._cryptographic_parameters:\n self._cryptographic_parameters.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._data:\n self._data.write(local_stream, kmip_version=kmip_version)\n if self._digested_data:\n self._digested_data.write(local_stream, kmip_version=kmip_version)\n if self._signature_data:\n self._signature_data.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._correlation_value:\n self._correlation_value.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._init_indicator:\n self._init_indicator.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._final_indicator:\n self._final_indicator.write(\n local_stream,\n kmip_version=kmip_version\n )\n self.length = local_stream.length()\n super(SignatureVerifyRequestPayload, self).write(\n output_stream,\n kmip_version=kmip_version\n )\n output_stream.write(local_stream.buffer)"
},
{
"code": "def get_imap_capabilities(server):\n capabilities = list(map(str, list(server.capabilities())))\n for i in range(len(capabilities)):\n capabilities[i] = str(capabilities[i]).replace(\"b'\",\n \"\").replace(\"'\",\n \"\")\n logger.debug(\"IMAP server supports: {0}\".format(capabilities))\n return capabilities"
},
{
"code": "def get_prices(self, date: str, currency: str) -> List[PriceModel]:\n from .repositories import PriceRepository\n session = self.session\n repo = PriceRepository(session)\n query = repo.query\n if date:\n query = query.filter(dal.Price.date == date)\n if currency:\n query = query.filter(dal.Price.currency == currency)\n query = query.order_by(dal.Price.namespace, dal.Price.symbol)\n price_entities = query.all()\n mapper = mappers.PriceMapper()\n result = []\n for entity in price_entities:\n model = mapper.map_entity(entity)\n result.append(model)\n return result"
},
{
"code": "def _handle_display_data(self, msg):\n self.log.debug(\"display: %s\", msg.get('content', ''))\n if not self._hidden and self._is_from_this_session(msg):\n source = msg['content']['source']\n data = msg['content']['data']\n metadata = msg['content']['metadata']\n if data.has_key('text/html'):\n html = data['text/html']\n self._append_html(html, True)\n elif data.has_key('text/plain'):\n text = data['text/plain']\n self._append_plain_text(text, True)\n self._append_plain_text(u'\\n', True)"
},
{
"code": "def check_type(self, value):\n if self.__dict__['dtype'] is None:\n return\n elif value is None:\n return\n elif isinstance(value, self.__dict__['dtype']):\n return\n msg = \"Value of type %s, when %s was expected.\" % (\n type(value), self.__dict__['dtype'])\n raise TypeError(msg)"
},
{
"code": "def s3walk(self, basedir, show_dir=None):\n if not show_dir:\n show_dir = self.opt.show_dir\n if basedir[-1] == PATH_SEP:\n basedir = basedir[0:-1]\n s3url = S3URL(basedir)\n result = []\n pool = ThreadPool(ThreadUtil, self.opt)\n pool.s3walk(s3url, s3url.get_fixed_path(), s3url.path, result)\n pool.join()\n if not show_dir and len(result) == 1 and result[0]['is_dir']:\n path = result[0]['name']\n s3url = S3URL(path)\n result = []\n pool = ThreadPool(ThreadUtil, self.opt)\n pool.s3walk(s3url, s3url.get_fixed_path(), s3url.path, result)\n pool.join()\n def compare(x, y):\n result = -cmp(x['is_dir'], y['is_dir'])\n if result != 0:\n return result\n return cmp(x['name'], y['name'])\n return sorted(result, key=cmp_to_key(compare))"
},
{
"code": "def write(self, output_buffer, kmip_version=enums.KMIPVersion.KMIP_1_0):\n local_buffer = utils.BytearrayStream()\n if self._unique_identifier:\n self._unique_identifier.write(\n local_buffer,\n kmip_version=kmip_version\n )\n self.length = local_buffer.length()\n super(GetAttributeListRequestPayload, self).write(\n output_buffer,\n kmip_version=kmip_version\n )\n output_buffer.write(local_buffer.buffer)"
},
{
"code": "def _construct_schema(elements, nsmap):\n schema = {\n 'properties': {},\n 'geometry': None\n }\n schema_key = None\n gml_key = None\n if nsmap:\n for key in nsmap:\n if nsmap[key] == XS_NAMESPACE:\n schema_key = key\n if nsmap[key] in GML_NAMESPACES:\n gml_key = key\n else:\n gml_key = 'gml'\n schema_key = 'xsd'\n mappings = {\n 'PointPropertyType': 'Point',\n 'PolygonPropertyType': 'Polygon',\n 'LineStringPropertyType': 'LineString',\n 'MultiPointPropertyType': 'MultiPoint',\n 'MultiLineStringPropertyType': 'MultiLineString',\n 'MultiPolygonPropertyType': 'MultiPolygon',\n 'MultiGeometryPropertyType': 'MultiGeometry',\n 'GeometryPropertyType': 'GeometryCollection',\n 'SurfacePropertyType': '3D Polygon',\n 'MultiSurfacePropertyType': '3D MultiPolygon'\n }\n for element in elements:\n data_type = element.attrib['type'].replace(gml_key + ':', '')\n name = element.attrib['name']\n if data_type in mappings:\n schema['geometry'] = mappings[data_type]\n schema['geometry_column'] = name\n else:\n schema['properties'][name] = data_type.replace(schema_key+':', '')\n if schema['properties'] or schema['geometry']:\n return schema\n else:\n return None"
},
{
"code": "def _exit_gracefully(self, signum, frame):\n self.log.info(\"Exiting gracefully upon receiving signal %s\", signum)\n self.terminate()\n self.end()\n self.log.debug(\"Finished terminating DAG processors.\")\n sys.exit(os.EX_OK)"
},
{
"code": "def convertArgsToTokens(self, data):\n tdict = []\n tokens = []\n d = open(data, 'r')\n for line in d.readlines():\n tdict.append(line.rstrip())\n tokens += line.split()\n d.close()\n tokens = list(set(tokens))\n return tdict, tokens"
},
{
"code": "def _nested_convert_to_tensor(struct, dtype=None, name=None):\n if dtype is not None or not tf.nest.is_nested(struct):\n return tf.convert_to_tensor(struct, dtype=dtype)\n if _maybe_convertible_to_tensor(struct):\n try:\n return tf.convert_to_tensor(value=struct, name=name)\n except (ValueError, TypeError):\n pass\n shallow_struct = _get_shallow_structure(struct)\n return nest.map_structure_up_to(\n shallow_struct, lambda s: _nested_convert_to_tensor(s, name=name), struct)"
},
{
"code": "def __get_or_create(\n ns_cache: NamespaceMap,\n name: sym.Symbol,\n module: types.ModuleType = None,\n core_ns_name=CORE_NS,\n ) -> lmap.Map:\n ns = ns_cache.entry(name, None)\n if ns is not None:\n return ns_cache\n new_ns = Namespace(name, module=module)\n if name.name != core_ns_name:\n core_ns = ns_cache.entry(sym.symbol(core_ns_name), None)\n assert core_ns is not None, \"Core namespace not loaded yet!\"\n new_ns.refer_all(core_ns)\n return ns_cache.assoc(name, new_ns)"
},
{
"code": "def gauss(x, *p):\n A, mu, sigma = p\n return A * np.exp(-0.5 * (-mu + x)**2 / sigma**2)"
},
{
"code": "def tempfile_set(tempfile, target):\n if target:\n os.rename(tempfile, target)\n else:\n os.unlink(tempfile)\n if target in TEMP_FILES:\n TEMP_FILES.remove(tempfile)"
},
{
"code": "def _get_properties(config):\n property_classes = {BUILTIN_PROPERTY}\n property_names = set()\n if config is not None:\n property_classes.update(config.property_classes)\n property_names.update(\n (prop.rsplit(\".\", 1)[-1] for prop in config.property_classes)\n )\n return property_classes, property_names"
},
{
"code": "def duration(self):\n ecc = self.ecc if not np.isnan(self.ecc) else np.sqrt(self.ecw**2 + self.esw**2)\n esw = self.esw if not np.isnan(self.esw) else ecc * np.sin(self.w)\n aRs = ((G * self.rhos * (1. + self.MpMs) * \n (self.per * DAYSEC)**2.) / (3. * np.pi))**(1./3.)\n inc = np.arccos(self.bcirc/aRs)\n becc = self.bcirc * (1 - ecc**2)/(1 - esw)\n tdur = self.per / 2. / np.pi * np.arcsin(((1. + self.RpRs)**2 -\n becc**2)**0.5 / (np.sin(inc) * aRs))\n tdur *= np.sqrt(1. - ecc**2.)/(1. - esw)\n return tdur"
},
{
"code": "def __fetch_items(self, path, page=1):\n fetch_data = True\n parsed_crates = 0\n total_crates = 0\n while fetch_data:\n logger.debug(\"Fetching page: %i\", page)\n try:\n payload = {'sort': 'alphabetical', 'page': page}\n raw_content = self.fetch(path, payload=payload)\n content = json.loads(raw_content)\n parsed_crates += len(content['crates'])\n if not total_crates:\n total_crates = content['meta']['total']\n except requests.exceptions.HTTPError as e:\n logger.error(\"HTTP exception raised - %s\", e.response.text)\n raise e\n yield raw_content\n page += 1\n if parsed_crates >= total_crates:\n fetch_data = False"
},
{
"code": "def _joint_mean(self):\n with tf.name_scope(\"mean_joint\"):\n with tf.control_dependencies(self.runtime_assertions):\n initial_latent_mean = _broadcast_to_shape(\n self.initial_state_prior.mean()[..., tf.newaxis],\n tf.concat([self.batch_shape_tensor(),\n [self.latent_size, 1]], axis=0))\n initial_observation_mean = _propagate_mean(\n initial_latent_mean,\n self.get_observation_matrix_for_timestep(self.initial_step),\n self.get_observation_noise_for_timestep(self.initial_step))\n mean_step = build_kalman_mean_step(\n self.get_transition_matrix_for_timestep,\n self.get_transition_noise_for_timestep,\n self.get_observation_matrix_for_timestep,\n self.get_observation_noise_for_timestep)\n (latent_means, observation_means) = tf.scan(\n mean_step,\n elems=tf.range(self.initial_step+1, self.final_step),\n initializer=(initial_latent_mean, initial_observation_mean))\n latent_means = tf.concat([initial_latent_mean[tf.newaxis, ...],\n latent_means], axis=0)\n observation_means = tf.concat([initial_observation_mean[tf.newaxis, ...],\n observation_means], axis=0)\n latent_means = tf.squeeze(latent_means, -1)\n latent_means = distribution_util.move_dimension(latent_means, 0, -2)\n observation_means = tf.squeeze(observation_means, -1)\n observation_means = distribution_util.move_dimension(\n observation_means, 0, -2)\n return latent_means, observation_means"
},
{
"code": "def resolve_outputs(self):\n input_shape = None\n for i, shape in enumerate(self._input_shapes.values()):\n if i == 0:\n input_shape = shape\n if len(input_shape) != len(shape) or any(\n a is not None and b is not None and a != b\n for a, b in zip(input_shape[:-1], shape[:-1])):\n raise util.ConfigurationError(\n 'layer \"{}\" incompatible input shapes {}'\n .format(self.name, self._input_shapes))\n size = self.kwargs.get('size')\n shape = self.kwargs.get('shape')\n if shape is not None:\n pass\n elif size is not None:\n shape = tuple(input_shape[:-1]) + (size, )\n else:\n raise util.ConfigurationError(\n 'layer \"{}\" does not specify a size'.format(self.name))\n self._output_shapes['out'] = shape"
},
{
"code": "def read(self, filename):\n kwargs = {}\n if sys.version_info >= (3, 2):\n kwargs['encoding'] = \"utf-8\"\n return configparser.RawConfigParser.read(self, filename, **kwargs)"
},
{
"code": "def normalize(self, dt, is_dst=False):\n if dt.tzinfo is None:\n raise ValueError('Naive time - no tzinfo set')\n return dt.replace(tzinfo=self)"
},
{
"code": "def close(self):\n if self._closed:\n return\n self._socket.close()\n self._closed = True"
},
{
"code": "def add_patches(self, patches, after=None):\n if after is None:\n self.insert_patches(patches)\n else:\n self._check_patch(after)\n patchlines = self._patchlines_before(after)\n patchlines.append(self.patch2line[after])\n for patch in patches:\n patchline = PatchLine(patch)\n patchlines.append(patchline)\n self.patch2line[patchline.get_patch()] = patchline\n patchlines.extend(self._patchlines_after(after))\n self.patchlines = patchlines"
},
{
"code": "def update_key(\n self, vault_base_url, key_name, key_version, key_ops=None, key_attributes=None, tags=None, custom_headers=None, raw=False, **operation_config):\n parameters = models.KeyUpdateParameters(key_ops=key_ops, key_attributes=key_attributes, tags=tags)\n url = self.update_key.metadata['url']\n path_format_arguments = {\n 'vaultBaseUrl': self._serialize.url(\"vault_base_url\", vault_base_url, 'str', skip_quote=True),\n 'key-name': self._serialize.url(\"key_name\", key_name, 'str'),\n 'key-version': self._serialize.url(\"key_version\", key_version, 'str')\n }\n url = self._client.format_url(url, **path_format_arguments)\n query_parameters = {}\n query_parameters['api-version'] = self._serialize.query(\"self.api_version\", self.api_version, 'str')\n header_parameters = {}\n header_parameters['Content-Type'] = 'application/json; charset=utf-8'\n if self.config.generate_client_request_id:\n header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())\n if custom_headers:\n header_parameters.update(custom_headers)\n if self.config.accept_language is not None:\n header_parameters['accept-language'] = self._serialize.header(\"self.config.accept_language\", self.config.accept_language, 'str')\n body_content = self._serialize.body(parameters, 'KeyUpdateParameters')\n request = self._client.patch(url, query_parameters)\n response = self._client.send(\n request, header_parameters, body_content, stream=False, **operation_config)\n if response.status_code not in [200]:\n raise models.KeyVaultErrorException(self._deserialize, response)\n deserialized = None\n if response.status_code == 200:\n deserialized = self._deserialize('KeyBundle', response)\n if raw:\n client_raw_response = ClientRawResponse(deserialized, response)\n return client_raw_response\n return deserialized"
},
{
"code": "def specific_gains(string):\n if not string:\n return {}\n gains = {}\n for gain in string.split(','):\n amp_name, value = gain.split('=')\n gains[amp_name.strip()] = float(value.strip())\n return gains"
},
{
"code": "def _with_loc(f: W) -> W:\n @functools.wraps(f)\n def with_lineno_and_col(ctx):\n meta = lmap.map(\n {READER_LINE_KW: ctx.reader.line, READER_COL_KW: ctx.reader.col}\n )\n v = f(ctx)\n try:\n return v.with_meta(meta)\n except AttributeError:\n return v\n return cast(W, with_lineno_and_col)"
},
{
"code": "def updates(self, **kwargs):\n regs = regularizers.from_kwargs(self, **kwargs)\n _, updates = self.build_graph(regs)\n return updates"
},
{
"code": "def sqrt(wave):\n r\n dep_units = \"{0}**0.5\".format(wave.dep_units)\n return _operation(wave, \"sqrt\", dep_units, np.sqrt)"
},
{
"code": "def parse_args():\n usage = \"Usage: create_concordance <infile> [<outfile>]\"\n description = \"Simple Concordance Generator\"\n argparser = argparse.ArgumentParser(\n usage=usage, description=description)\n argparser.add_argument(\n 'infile', type=argparse.FileType('r'),\n help=\"File read in to create concordance\")\n argparser.add_argument(\n 'outfile', nargs='?', type=argparse.FileType('w'),\n default=sys.stdout, help=\"File to write concordance to. \"\n \"Default is stdout\")\n argparser.add_argument(\n '--word', nargs=\"?\", const=str, help=\"Display a word in concordance\")\n args = argparser.parse_args()\n return args"
},
{
"code": "def _count_table_rows(self, table_name):\n cursor = self._db.cursor()\n select_stmt = \"SELECT COUNT(*) FROM \" + table_name\n try:\n cursor.execute(select_stmt)\n row = cursor.fetchone()\n except sqlite3.DatabaseError as e:\n msg = \"invalid archive file; cause: %s\" % str(e)\n raise ArchiveError(cause=msg)\n finally:\n cursor.close()\n return row[0]"
},
{
"code": "def discount_status(request, form):\n discounts = form.cleaned_data[\"discount\"]\n items = commerce.DiscountItem.objects.filter(\n Q(discount__in=discounts),\n ).select_related(\"cart\", \"product\", \"product__category\")\n items = group_by_cart_status(\n items,\n [\"discount\"],\n [\"discount\", \"discount__description\"],\n )\n headings = [\n \"Discount\", \"Paid\", \"Reserved\", \"Unreserved\", \"Refunded\",\n ]\n data = []\n for item in items:\n data.append([\n item[\"discount__description\"],\n item[\"total_paid\"],\n item[\"total_reserved\"],\n item[\"total_unreserved\"],\n item[\"total_refunded\"],\n ])\n return ListReport(\"Usage by item\", headings, data)"
},
{
"code": "def spin(self):\n if self._notification_socket:\n self._flush_notifications()\n if self._iopub_socket:\n self._flush_iopub(self._iopub_socket)\n if self._mux_socket:\n self._flush_results(self._mux_socket)\n if self._task_socket:\n self._flush_results(self._task_socket)\n if self._control_socket:\n self._flush_control(self._control_socket)\n if self._query_socket:\n self._flush_ignored_hub_replies()"
},
{
"code": "def show(self, title=''):\n self.render(title=title)\n if self.fig:\n plt.show(self.fig)"
},
{
"code": "def f_get_groups(self, copy=True):\n if copy:\n return self._groups.copy()\n else:\n return self._groups"
},
{
"code": "def create_domain(self, domain_name, username=None, alphabet=Domain.DEFAULT_ALPHABET,\n length=Domain.DEFAULT_KEY_LENGTH):\n try:\n return self._create_domain(domain_name, username, alphabet, length)\n except Exception as ex:\n _logger.warn(\"Inserting new domain failed: %s\", ex)\n raise DuplicateDomainException"
},
{
"code": "def get_help(self):\n if self.help:\n return self.help\n elif self.__doc__ and self.__doc__.strip():\n return self.__doc__.strip()\n else:\n return ''"
},
{
"code": "def _unique_constraint_name(table: str, field, keys):\n postfix = '_'.join(keys)\n return '{table}_{field}_unique_{postfix}'.format(\n table=table,\n field=field.column,\n postfix=postfix\n )"
},
{
"code": "def get_result(self, indices_or_msg_ids=None, block=None):\n block = self.block if block is None else block\n if indices_or_msg_ids is None:\n indices_or_msg_ids = -1\n if not isinstance(indices_or_msg_ids, (list,tuple)):\n indices_or_msg_ids = [indices_or_msg_ids]\n theids = []\n for id in indices_or_msg_ids:\n if isinstance(id, int):\n id = self.history[id]\n if not isinstance(id, basestring):\n raise TypeError(\"indices must be str or int, not %r\"%id)\n theids.append(id)\n local_ids = filter(lambda msg_id: msg_id in self.history or msg_id in self.results, theids)\n remote_ids = filter(lambda msg_id: msg_id not in local_ids, theids)\n if remote_ids:\n ar = AsyncHubResult(self, msg_ids=theids)\n else:\n ar = AsyncResult(self, msg_ids=theids)\n if block:\n ar.wait()\n return ar"
},
{
"code": "def load_python_global(module, name):\n if module == '__builtin__' and six.PY3:\n module = 'builtins'\n module = importlib.import_module(module)\n return getattr(module, name)"
},
{
"code": "def _req_rep_retry(self, request):\n retries_left = self.RETRIES\n while retries_left:\n self._logger.log(1, 'Sending REQ `%s`', request)\n self._send_request(request)\n socks = dict(self._poll.poll(self.TIMEOUT))\n if socks.get(self._socket) == zmq.POLLIN:\n response = self._receive_response()\n self._logger.log(1, 'Received REP `%s`', response)\n return response, self.RETRIES - retries_left\n else:\n self._logger.debug('No response from server (%d retries left)' %\n retries_left)\n self._close_socket(confused=True)\n retries_left -= 1\n if retries_left == 0:\n raise RuntimeError('Server seems to be offline!')\n time.sleep(self.SLEEP)\n self._start_socket()"
},
{
"code": "def _check_inputs(self):\n try:\n _ = self._inputs[0]\n except TypeError:\n raise RuntimeError(\n \"inputs should be iterable but found type='{0}', value=\"\n \"'{1}'\".format(type(self._inputs), str(self._inputs)))\n from melody.inputs import Input\n for check_input in self._inputs:\n if not isinstance(check_input, Input):\n raise RuntimeError(\n \"input should be a subclass of the Input class but \"\n \"found type='{0}', value='{1}'\".format(type(check_input),\n str(check_input)))"
},
{
"code": "def individuals(context, institute, causatives, case_id):\n LOG.info(\"Running scout view individuals\")\n adapter = context.obj['adapter']\n individuals = []\n if case_id:\n case = adapter.case(case_id=case_id)\n if case:\n cases = [case]\n else:\n LOG.info(\"Could not find case %s\", case_id)\n return\n else:\n cases = [case_obj for case_obj in\n adapter.cases(\n collaborator=institute,\n has_causatives=causatives)]\n if len(cases) == 0:\n LOG.info(\"Could not find cases that match criteria\")\n return\n individuals = (ind_obj for case_obj in cases for ind_obj in case_obj['individuals'])\n click.echo(\"\n for case in cases:\n for ind_obj in case['individuals']:\n ind_info = [\n case['_id'], ind_obj['individual_id'],\n ind_obj['display_name'], SEX_MAP[int(ind_obj['sex'])],\n PHENOTYPE_MAP[ind_obj['phenotype']], ind_obj['mother'],\n ind_obj['father']\n ]\n click.echo('\\t'.join(ind_info))"
},
{
"code": "def show(self, *args, **kwargs):\n from webbrowser import open as webopen\n return webopen(str(self), *args, **kwargs)"
},
{
"code": "def insert_child ( self, object, index, child ):\n if isinstance( child, Subgraph ):\n object.subgraphs.insert( index, child )\n elif isinstance( child, Cluster ):\n object.clusters.insert( index, child )\n elif isinstance( child, Node ):\n object.nodes.insert( index, child )\n elif isinstance( child, Edge ):\n object.edges.insert( index, child )\n else:\n pass"
},
{
"code": "def get_private_keys(\n self,\n index=0,\n count=1,\n security_level=AddressGenerator.DEFAULT_SECURITY_LEVEL,\n ):\n return commands.GetPrivateKeysCommand(self.adapter)(\n seed=self.seed,\n index=index,\n count=count,\n securityLevel=security_level,\n )"
},
{
"code": "async def limited(until):\n duration = int(round(until - time.time()))\n mins = duration / 60\n fmt = 'We have exhausted a ratelimit quota. Retrying in %.2f seconds (%.3f minutes).'\n log.warn(fmt, duration, mins)"
},
{
"code": "def get_last_activities(self, n):\n filenames = self.get_activity_list().iloc[-n:].filename.tolist()\n last_activities = [self.get_activity(f) for f in filenames]\n return last_activities"
},
{
"code": "def fetch(self, category=CATEGORY_QUESTION, offset=DEFAULT_OFFSET):\n if not offset:\n offset = DEFAULT_OFFSET\n kwargs = {\"offset\": offset}\n items = super().fetch(category, **kwargs)\n return items"
},
{
"code": "def get_public_tokens(self):\n r = self.remote_utils.get_url(self.url() + \"public_tokens/\")\n return r.json()"
},
{
"code": "def validate_token(self, token, expected_data=None):\n try:\n data = self.load_token(token)\n if expected_data:\n for k in expected_data:\n if expected_data[k] != data[\"data\"].get(k):\n return None\n return data\n except BadData:\n return None"
},
{
"code": "async def set_session_state(self, state):\n await self._can_run()\n state = state.encode(self.encoding) if isinstance(state, six.text_type) else state\n return await self._mgmt_request_response(\n REQUEST_RESPONSE_SET_SESSION_STATE_OPERATION,\n {'session-id': self.session_id, 'session-state': bytearray(state)},\n mgmt_handlers.default)"
},
{
"code": "def error(self, relative_to='AME2003'):\n df = self.df - Table(relative_to).df\n return Table(df=df)"
},
{
"code": "def update_event_hub(self, hub_name, hub=None):\n _validate_not_none('hub_name', hub_name)\n request = HTTPRequest()\n request.method = 'PUT'\n request.host = self._get_host()\n request.path = '/' + _str(hub_name) + '?api-version=2014-01'\n request.body = _get_request_body(_convert_event_hub_to_xml(hub))\n request.path, request.query = self._httpclient._update_request_uri_query(request)\n request.headers.append(('If-Match', '*'))\n request.headers = self._update_service_bus_header(request)\n response = self._perform_request(request)\n return _convert_response_to_event_hub(response)"
},
{
"code": "def _get_pipeline_processes(self):\n with open(self.log_file) as fh:\n for line in fh:\n if re.match(\".*Creating operator.*\", line):\n match = re.match(\".*Creating operator > (.*) --\", line)\n process = match.group(1)\n if any([process.startswith(x) for x in self._blacklist]):\n continue\n if process not in self.skip_processes:\n self.processes[match.group(1)] = {\n \"barrier\": \"W\",\n \"submitted\": set(),\n \"finished\": set(),\n \"failed\": set(),\n \"retry\": set(),\n \"cpus\": None,\n \"memory\": None\n }\n self.process_tags[process] = {}\n if re.match(\".*Launching `.*` \\[.*\\] \", line):\n tag_match = re.match(\".*Launching `.*` \\[(.*)\\] \", line)\n self.pipeline_tag = tag_match.group(1) if tag_match else \\\n \"?\"\n name_match = re.match(\".*Launching `(.*)` \\[.*\\] \", line)\n self.pipeline_name = name_match.group(1) if name_match \\\n else \"?\"\n self.content_lines = len(self.processes)"
},
{
"code": "def allow_request(self, request, view):\n if request.method != 'POST':\n return True\n return super(PostRequestThrottleMixin, self).allow_request(request, view)"
},
{
"code": "def mr_reader(job, input_stream, loads=core.loads):\n for line in input_stream:\n yield loads(line),"
},
{
"code": "def until_traits_are_present(self, element_with_traits):\n end_time = time.time() + self._timeout\n count = 1\n missing_traits_descriptions = None\n while True:\n missing_traits_descriptions = []\n try:\n missing_traits_descriptions = element_with_traits.evaluate_traits()\n if len(missing_traits_descriptions) == 0:\n return True\n else:\n logger.debug(\"\n missing_traits_descriptions)))\n except self._ignored_exceptions as ex:\n logger.debug(\"Captured {0}: {1}\".format(str(ex.__class__).replace(\"<type '\", \"\").replace(\"'>\", \"\"),\n str(ex)))\n pass\n time.sleep(self._poll)\n count += 1\n if time.time() > end_time:\n break\n raise TimeoutException(\n msg=\"conditions \" + '<' + '> <'.join(missing_traits_descriptions) + '>' + \" not true after \" + str(\n self._timeout) + \" seconds.\")"
},
{
"code": "def find_max_rad_npnp(self):\n max_rad = 0\n max_npnp = 0\n for res, _ in self.items():\n if res != 'KEY':\n for _, ff_params in self[res].items():\n if max_rad < ff_params[1]:\n max_rad = ff_params[1]\n if max_npnp < ff_params[4]:\n max_npnp = ff_params[4]\n return max_rad, max_npnp"
},
{
"code": "def crscode_to_string(codetype, code, format):\n link = 'http://spatialreference.org/ref/%s/%s/%s/' %(codetype,code,format)\n result = urllib2.urlopen(link).read()\n if not isinstance(result, str):\n result = result.decode()\n return result"
},
{
"code": "def intern(self, sym: sym.Symbol, var: Var, force: bool = False) -> Var:\n m: lmap.Map = self._interns.swap(Namespace._intern, sym, var, force=force)\n return m.entry(sym)"
},
{
"code": "def clone(url, path):\n adapter = None\n if url[:4] == \"git@\" or url[-4:] == \".git\":\n adapter = Git(path)\n if url[:6] == \"svn://\":\n adapter = Svn(path)\n if url[:6] == \"bzr://\":\n adapter = Bzr(path)\n if url[:9] == \"ssh://hg@\":\n adapter = Hg(path)\n if adapter is None:\n raise RepositoryAdapterNotFound(\n \"Can't find adapter for `%s` repository url\" % url)\n return adapter.clone(url)"
},
{
"code": "def _send_file(self, local, remote):\n remote = \"%s:%s\" % (self.location, remote)\n for i in range(10):\n if not os.path.exists(local):\n self.log.debug(\"waiting for %s\" % local)\n time.sleep(1)\n else:\n break\n self.log.info(\"sending %s to %s\", local, remote)\n check_output(self.scp_cmd + [local, remote])"
},
{
"code": "def set_default_tlw(self, tlw, designer, inspector):\n \"track default top level window for toolbox menu default action\"\n self.designer = designer\n self.inspector = inspector"
},
{
"code": "def _chunk_pars(freq_vector, data_matrix, pformat):\n pformat = pformat.upper()\n length = 4\n for freq, data in zip(freq_vector, data_matrix):\n data = data.flatten()\n for index in range(0, data.size, length):\n fpoint = [freq] if not index else [None]\n cdata = data[index : index + length]\n if pformat == \"MA\":\n vector1 = np.abs(cdata)\n vector2 = np.rad2deg(np.angle(cdata))\n elif pformat == \"RI\":\n vector1 = np.real(cdata)\n vector2 = np.imag(cdata)\n else:\n vector1 = 20.0 * np.log10(np.abs(cdata))\n vector2 = np.rad2deg(np.angle(cdata))\n sep_data = np.array([])\n for item1, item2 in zip(vector1, vector2):\n sep_data = np.concatenate((sep_data, np.array([item1, item2])))\n ret = np.concatenate((np.array(fpoint), sep_data))\n yield ret"
},
{
"code": "def _determine_function_name_type(node, config=None):\n property_classes, property_names = _get_properties(config)\n if not node.is_method():\n return \"function\"\n if node.decorators:\n decorators = node.decorators.nodes\n else:\n decorators = []\n for decorator in decorators:\n if isinstance(decorator, astroid.Name) or (\n isinstance(decorator, astroid.Attribute)\n and decorator.attrname in property_names\n ):\n infered = utils.safe_infer(decorator)\n if infered and infered.qname() in property_classes:\n return \"attr\"\n elif isinstance(decorator, astroid.Attribute) and decorator.attrname in (\n \"setter\",\n \"deleter\",\n ):\n return \"attr\"\n return \"method\""
},
{
"code": "def get(self, name, factory, *factory_args, **factory_kwargs):\n update_thread_local = getattr(factory, 'update_thread_local', True)\n if (not update_thread_local) or (name not in self.__dict__):\n obj = factory(*factory_args, **factory_kwargs)\n if update_thread_local:\n setattr(self, name, obj)\n return obj\n return getattr(self, name)"
},
{
"code": "def _build_point_formats_dtypes(point_format_dimensions, dimensions_dict):\n return {\n fmt_id: _point_format_to_dtype(point_fmt, dimensions_dict)\n for fmt_id, point_fmt in point_format_dimensions.items()\n }"
},
{
"code": "def fetch_metric(self, metric, start, end, tags={}, aggregator=\"sum\",\n downsample=None, ms_resolution=True):\n query = \"{aggregator}:{downsample}{metric}{{{tags}}}\".format(\n aggregator=aggregator,\n downsample=downsample + \"-avg:\" if downsample else \"\",\n metric=metric,\n tags=','.join(\"%s=%s\" % (k, v) for k, v in tags.items())\n )\n params = {\n 'ms': ms_resolution,\n 'start': '{0:.3f}'.format(start.timestamp()),\n 'end': '{0:.3f}'.format(end.timestamp()),\n 'm': query\n }\n response = self.__request(\"/query\", params)\n if response.status_code == 200:\n try:\n return response.json()[0]['dps']\n except IndexError:\n return {}\n raise QueryError(response.json())"
},
{
"code": "def read(self):\n self.__fileobj.seek(self.data_offset)\n self.data = self.__fileobj.read(self.data_size)"
},
{
"code": "def gen_timeout_resend(attempts):\n timeout = 2 ** (attempts + 1) + random.uniform(-1, +1)\n logger.debug('next timeout resending will happen on %s',\n future_dt_str(nowutc(), timeout))\n return timeout"
},
{
"code": "def apply(self, method, args):\n try:\n params = args['params']\n if isinstance(params, dict):\n result = method(**params)\n else:\n result = method(*params)\n except Exception as error:\n server_error(args['id'], error)\n else:\n return result"
},
{
"code": "def _add_group_from_storage(self, args, kwargs):\n return self._nn_interface._add_generic(self,\n type_name=GROUP,\n group_type_name=GROUP,\n args=args,\n kwargs=kwargs,\n add_prefix=False,\n check_naming=False)"
},
{
"code": "def hflip(img):\n if not _is_pil_image(img):\n raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n return img.transpose(Image.FLIP_LEFT_RIGHT)"
},
{
"code": "def save_image(self, imagefile, save_path, file_ext, mime_type):\n file_to_save = InMemoryUploadedFile(\n imagefile,\n None,\n 'foo.%s' % file_ext,\n mime_type,\n imagefile.tell(),\n None\n )\n file_to_save.seek(0)\n self.storage.save(save_path, file_to_save)"
},
{
"code": "def draw(self):\n if not self.visible:\n return\n if not isinstance(self.submenu,Container):\n glEnable(GL_SCISSOR_TEST)\n glScissor(*self.pos+self.size)\n SubMenu.draw(self)\n if not isinstance(self.submenu,Container):\n glDisable(GL_SCISSOR_TEST)"
},
{
"code": "def cb_help_message(self, option, optname, value, parser):\n self.linter.msgs_store.help_message(utils._splitstrip(value))\n sys.exit(0)"
},
{
"code": "def open(path, mode=gdalconst.GA_ReadOnly):\n path = getattr(path, 'name', path)\n try:\n return Raster(vsiprefix(path), mode)\n except AttributeError:\n try:\n imgdata = path.read()\n except AttributeError:\n raise TypeError('Not a file-like object providing read()')\n else:\n imgio = MemFileIO(delete=False)\n gdal.FileFromMemBuffer(imgio.name, imgdata)\n return Raster(imgio, mode)\n raise ValueError('Failed to open raster from \"%r\"' % path)"
},
{
"code": "def from_connection_string(cls, conn_str, *, loop=None, **kwargs):\n address, policy, key, _ = parse_conn_str(conn_str)\n parsed_namespace = urlparse(address)\n namespace, _, base = parsed_namespace.hostname.partition('.')\n return cls(\n service_namespace=namespace,\n shared_access_key_name=policy,\n shared_access_key_value=key,\n host_base='.' + base,\n loop=loop,\n **kwargs)"
},
{
"code": "def _read_config(self):\n self._config_loaded = True\n conf = []\n for f in self._candidate_log_files():\n if os.path.isfile(f):\n self._logger.info(\"Reading config file %s\" % f)\n section_rx = re.compile(r\"^\\[(\\w+)\\]$\")\n keyvalue_rx = re.compile(r\"^(\\w+:)?([\\w.]+)\\s*=(.*)$\")\n with io.open(f, \"rt\", encoding=\"utf-8\") as config_file:\n section_name = None\n for lineno, line in enumerate(config_file):\n line = line.strip()\n if line == \"\" or line.startswith(\"\n m1 = section_rx.match(line)\n if m1:\n section_name = m1.group(1)\n continue\n m2 = keyvalue_rx.match(line)\n if m2:\n lng = m2.group(1)\n key = m2.group(2)\n val = m2.group(3).strip()\n if lng and lng.lower() != \"py:\": continue\n if section_name:\n key = section_name + \".\" + key\n if key in H2OConfigReader._allowed_config_keys:\n conf.append((key, val))\n else:\n self._logger.error(\"Key %s is not a valid config key\" % key)\n continue\n self._logger.error(\"Syntax error in config file line %d: %s\" % (lineno, line))\n self._config = dict(conf)\n return"
},
{
"code": "def clean_time_slots(self):\n ts = ((a[0], a[1]) for t in self.tiers.values() for a in t[0].values())\n for a in {a for b in ts for a in b} ^ set(self.timeslots):\n del(self.timeslots[a])"
},
{
"code": "def __last_beat(cumscore):\n maxes = util.localmax(cumscore)\n med_score = np.median(cumscore[np.argwhere(maxes)])\n return np.argwhere((cumscore * maxes * 2 > med_score)).max()"
},
{
"code": "def _basename_in_blacklist_re(base_name, black_list_re):\n for file_pattern in black_list_re:\n if file_pattern.match(base_name):\n return True\n return False"
},
{
"code": "def _parse_header(line):\n parts = _parseparam(';' + line)\n key = parts.next()\n pdict = {}\n for p in parts:\n i = p.find('=')\n if i >= 0:\n name = p[:i].strip().lower()\n value = p[i+1:].strip()\n if len(value) >= 2 and value[0] == value[-1] == '\"':\n value = value[1:-1]\n value = value.replace('\\\\\\\\', '\\\\').replace('\\\\\"', '\"')\n pdict[name] = value\n return key, pdict"
},
{
"code": "def plot_tree(T, res=None, title=None, cmap_id=\"Pastel2\"):\n import matplotlib.pyplot as plt\n def round_time(t, res=0.1):\n v = int(t / float(res)) * res\n return v\n cmap = plt.get_cmap(cmap_id)\n level_bounds = []\n for level in T.levels:\n if level == \"root\":\n continue\n segments = T.get_segments_in_level(level)\n level_bounds.append(segments)\n B = float(len(level_bounds))\n for i, segments in enumerate(level_bounds):\n labels = utils.segment_labels_to_floats(segments)\n for segment, label in zip(segments, labels):\n if res is None:\n start = segment.start\n end = segment.end\n xlabel = \"Time (seconds)\"\n else:\n start = int(round_time(segment.start, res=res) / res)\n end = int(round_time(segment.end, res=res) / res)\n xlabel = \"Time (frames)\"\n plt.axvspan(start, end,\n ymax=(len(level_bounds) - i) / B,\n ymin=(len(level_bounds) - i - 1) / B,\n facecolor=cmap(label))\n L = float(len(T.levels) - 1)\n plt.yticks(np.linspace(0, (L - 1) / L, num=L) + 1 / L / 2.,\n T.levels[1:][::-1])\n plt.xlabel(xlabel)\n if title is not None:\n plt.title(title)\n plt.gca().set_xlim([0, end])"
},
{
"code": "def validate_zone(zone):\n if not has_valid_id(zone):\n raise InvalidZone(\"%s must contain a valid 'id' attribute\" % zone.__name__)\n if not has_valid_name(zone):\n raise InvalidZone(\"%s must contain a valid 'name' attribute\" % zone.__name__)"
},
{
"code": "def _merge(self, old, new, use_equals=False):\n if old is None:\n return new\n if new is None:\n return old\n if (old == new) if use_equals else (old is new):\n return old\n raise ValueError(\"Incompatible values: %s != %s\" % (old, new))"
},
{
"code": "def list(self, resource=None, type=None, actorId=None, _from=None, to=None,\n max=None, **request_parameters):\n check_type(resource, basestring)\n check_type(type, basestring)\n check_type(actorId, basestring)\n check_type(_from, basestring)\n check_type(to, basestring)\n check_type(max, int)\n params = dict_from_items_with_values(\n request_parameters,\n resource=resource,\n type=type,\n actorId=actorId,\n _from=_from,\n to=to,\n max=max,\n )\n if _from:\n params[\"from\"] = params.pop(\"_from\")\n items = self._session.get_items(API_ENDPOINT, params=params)\n for item in items:\n yield self._object_factory(OBJECT_TYPE, item)"
},
{
"code": "def _reformat_historical_formating_error(self):\n if PyFunceble.CONFIGURATION[\"inactive_database\"]:\n historical_formating_error = (\n PyFunceble.CURRENT_DIRECTORY + \"inactive-db.json\"\n )\n if PyFunceble.path.isfile(historical_formating_error):\n data = Dict().from_json(File(historical_formating_error).read())\n data_to_parse = {}\n top_keys = data.keys()\n for top_key in top_keys:\n low_keys = data[top_key].keys()\n data_to_parse[top_key] = {}\n for low_key in low_keys:\n if low_key.isdigit():\n data_to_parse[top_key][\n int(low_key) - (self.one_day_in_seconds * 30)\n ] = data[top_key][low_key]\n else:\n data_to_parse[top_key][\n int(PyFunceble.time()) - (self.one_day_in_seconds * 30)\n ] = data[top_key][low_key]\n if \"inactive_db\" in PyFunceble.INTERN:\n PyFunceble.INTERN[\"inactive_db\"].update(data_to_parse)\n else:\n PyFunceble.INTERN[\"inactive_db\"] = data_to_parse\n File(historical_formating_error).delete()"
},
{
"code": "def _copy_image(self, name):\n image = self._get_image(name)\n QtGui.QApplication.clipboard().setImage(image)"
},
{
"code": "def list(self):\n url = \"api/v0002/mgmt/custom/bundle\"\n r = self._apiClient.get(url)\n if r.status_code == 200:\n return r.json()\n else:\n raise ApiException(r)"
},
{
"code": "def log_attempt(self, key):\n with self.lock:\n if key not in self.attempts:\n self.attempts[key] = 1\n else:\n self.attempts[key] += 1\n if self.attempts[key] >= self.max_attempts:\n log.info('Account %s locked due to too many login attempts' % key)\n self.locks[key] = datetime.datetime.utcnow() + datetime.timedelta(seconds=self.lock_duration)"
},
{
"code": "def get_process_gids(self):\n real, effective, saved = _psutil_bsd.get_process_gids(self.pid)\n return nt_gids(real, effective, saved)"
},
{
"code": "def get_service_certificate(self, service_name, thumbalgorithm, thumbprint):\n _validate_not_none('service_name', service_name)\n _validate_not_none('thumbalgorithm', thumbalgorithm)\n _validate_not_none('thumbprint', thumbprint)\n return self._perform_get(\n '/' + self.subscription_id + '/services/hostedservices/' +\n _str(service_name) + '/certificates/' +\n _str(thumbalgorithm) + '-' + _str(thumbprint) + '',\n Certificate)"
},
{
"code": "def calc_n_ints_in_file(filename):\n h = read_header(filename)\n n_bytes = int(h[b'nbits'] / 8)\n n_chans = h[b'nchans']\n n_ifs = h[b'nifs']\n idx_data = len_header(filename)\n f = open(filename, 'rb')\n f.seek(idx_data)\n filesize = os.path.getsize(filename)\n n_bytes_data = filesize - idx_data\n if h[b'nbits'] == 2:\n n_ints = int(4 * n_bytes_data / (n_chans * n_ifs))\n else:\n n_ints = int(n_bytes_data / (n_bytes * n_chans * n_ifs))\n return n_ints"
},
{
"code": "def collect_things_entry_points():\n things = dict()\n for entry_point in iter_entry_points(group='invenio_migrator.things'):\n things[entry_point.name] = entry_point.load()\n return things"
},
{
"code": "def _check_token_present(self):\n\t\ttry:\n\t\t\tself._get_value(CONFIGKEY_TOKEN)\n\t\t\tself._get_value(CONFIGKEY_REFRESH_TOKEN)\n\t\t\tself._get_value(CONFIGKEY_REFRESHABLE)\n\t\texcept KeyError:\n\t\t\tself._log(\"Request new Token (CTP)\")\n\t\t\tself._get_new_access_information()"
},
{
"code": "def parse(self, *args):\n parsed_args = self.parser.parse_args(args)\n if parsed_args.category is None:\n delattr(parsed_args, 'category')\n if self._from_date:\n parsed_args.from_date = str_to_datetime(parsed_args.from_date)\n if self._to_date and parsed_args.to_date:\n parsed_args.to_date = str_to_datetime(parsed_args.to_date)\n if self._archive and parsed_args.archived_since:\n parsed_args.archived_since = str_to_datetime(parsed_args.archived_since)\n if self._archive and parsed_args.fetch_archive and parsed_args.no_archive:\n raise AttributeError(\"fetch-archive and no-archive arguments are not compatible\")\n if self._archive and parsed_args.fetch_archive and not parsed_args.category:\n raise AttributeError(\"fetch-archive needs a category to work with\")\n for alias, arg in self.aliases.items():\n if (alias not in parsed_args) and (arg in parsed_args):\n value = getattr(parsed_args, arg, None)\n setattr(parsed_args, alias, value)\n return parsed_args"
},
{
"code": "def connection_lost(self, exc):\n logger.debug(\"worker connection lost\")\n self._worker.close()\n self._workers.remove(self._worker)"
},
{
"code": "def register_handler(self, name, handler, esc_strings):\n self._handlers[name] = handler\n for esc_str in esc_strings:\n self._esc_handlers[esc_str] = handler"
},
{
"code": "def get_plugin_option(self, plugin, key):\n if plugin in self.plugins:\n plugin = self.plugins[plugin]\n return plugin.get_option(key)"
},
{
"code": "def release(self):\n if self.table is None:\n raise GiraffeError(\"Cannot release. Target table has not been set.\")\n log.info(\"BulkLoad\", \"Attempting release for table {}\".format(self.table))\n self.mload.release(self.table)"
},
{
"code": "def get_enumerations_from_bit_mask(enumeration, mask):\n return [x for x in enumeration if (x.value & mask) == x.value]"
},
{
"code": "def update_w(self):\n def update_single_w(i):\n FB = base.matrix(np.float64(np.dot(-self.data.T, W_hat[:,i])))\n be = solvers.qp(HB, FB, INQa, INQb, EQa, EQb)\n self.beta[i,:] = np.array(be['x']).reshape((1, self._num_samples))\n HB = base.matrix(np.float64(np.dot(self.data[:,:].T, self.data[:,:])))\n EQb = base.matrix(1.0, (1, 1))\n W_hat = np.dot(self.data, pinv(self.H))\n INQa = base.matrix(-np.eye(self._num_samples))\n INQb = base.matrix(0.0, (self._num_samples, 1))\n EQa = base.matrix(1.0, (1, self._num_samples))\n for i in range(self._num_bases):\n update_single_w(i)\n self.W = np.dot(self.beta, self.data.T).T"
},
{
"code": "def inverse(self):\n return Snapshot(self.num_qubits, self.num_clbits, self.params[0],\n self.params[1])"
},
{
"code": "def prune_all(self) -> int:\n from .repositories import PriceRepository\n repo = PriceRepository()\n items = repo.query.distinct(dal.Price.namespace, dal.Price.symbol).all()\n count = 0\n for item in items:\n symbol = SecuritySymbol(item.namespace, item.symbol)\n deleted = self.prune(symbol)\n if deleted:\n count += 1\n return count"
},
{
"code": "def _merge_single_runs(self, other_trajectory, used_runs):\n count = len(self)\n run_indices = range(len(other_trajectory))\n run_name_dict = OrderedDict()\n to_store_groups_with_annotations = []\n for idx in run_indices:\n if idx in used_runs:\n other_info_dict = other_trajectory.f_get_run_information(idx)\n time_ = other_info_dict['time']\n timestamp = other_info_dict['timestamp']\n completed = other_info_dict['completed']\n short_environment_hexsha = other_info_dict['short_environment_hexsha']\n finish_timestamp = other_info_dict['finish_timestamp']\n runtime = other_info_dict['runtime']\n new_idx = used_runs[idx]\n new_runname = self.f_wildcard('$', new_idx)\n run_name_dict[idx] = new_runname\n info_dict = dict(\n idx=new_idx,\n time=time_,\n timestamp=timestamp,\n completed=completed,\n short_environment_hexsha=short_environment_hexsha,\n finish_timestamp=finish_timestamp,\n runtime=runtime)\n self._add_run_info(**info_dict)"
},
{
"code": "def _get_resource_url(self, url, auto_page, data_key):\n headers = {'Accept': 'application/json',\n 'Connection': 'keep-alive'}\n response = DAO.getURL(url, headers)\n if response.status != 200:\n raise DataFailureException(url, response.status, response.data)\n data = json.loads(response.data)\n self.next_page_url = self._next_page(response)\n if auto_page and self.next_page_url:\n if isinstance(data, list):\n data.extend(self._get_resource_url(self.next_page_url, True,\n data_key))\n elif isinstance(data, dict) and data_key is not None:\n data[data_key].extend(self._get_resource_url(\n self.next_page_url, True, data_key)[data_key])\n return data"
},
{
"code": "def start_workers(self, workers_per_task=1):\n if not self.workers:\n for _ in range(workers_per_task):\n self.workers.append(Worker(self._download, self.queues['download'], self.queues['convert'], self.stopper))\n self.workers.append(Worker(self._convert, self.queues['convert'], self.queues['upload'], self.stopper))\n self.workers.append(Worker(self._upload, self.queues['upload'], self.queues['delete'], self.stopper))\n self.workers.append(Worker(self._delete, self.queues['delete'], self.queues['done'], self.stopper))\n self.signal_handler = SignalHandler(self.workers, self.stopper)\n signal.signal(signal.SIGINT, self.signal_handler)\n for worker in self.workers:\n worker.start()"
},
{
"code": "def bind_parameters(self, value_dict):\n new_circuit = self.copy()\n if value_dict.keys() > self.parameters:\n raise QiskitError('Cannot bind parameters ({}) not present in the circuit.'.format(\n [str(p) for p in value_dict.keys() - self.parameters]))\n for parameter, value in value_dict.items():\n new_circuit._bind_parameter(parameter, value)\n for parameter in value_dict:\n del new_circuit._parameter_table[parameter]\n return new_circuit"
},
{
"code": "def _delete_resource(self, url):\n params = {}\n self._set_as_user(params)\n headers = {'Accept': 'application/json',\n 'Connection': 'keep-alive'}\n url = url + self._params(params)\n response = DAO.deleteURL(url, headers)\n if not (response.status == 200 or response.status == 204):\n raise DataFailureException(url, response.status, response.data)\n return response"
},
{
"code": "def process_module(self, node):\n if self.config.file_header:\n if sys.version_info[0] < 3:\n pattern = re.compile(\n '\\A' + self.config.file_header, re.LOCALE | re.MULTILINE)\n else:\n pattern = re.compile(\n '\\A' + self.config.file_header, re.MULTILINE)\n content = None\n with node.stream() as stream:\n content = stream.read().decode('utf-8')\n matches = pattern.findall(content)\n if len(matches) != 1:\n self.add_message('invalid-file-header', 1,\n args=self.config.file_header)"
},
{
"code": "def tree_climber(self, tree_alias, base_item):\n if base_item is not None:\n base_item.in_current_branch = True\n if hasattr(base_item, 'parent') and base_item.parent is not None:\n self.tree_climber(tree_alias, self.get_item_by_id(tree_alias, base_item.parent.id))"
},
{
"code": "def convert_acquire(self, shift, instruction):\n meas_level = self._run_config.get('meas_level', 2)\n command_dict = {\n 'name': 'acquire',\n 't0': shift+instruction.start_time,\n 'duration': instruction.duration,\n 'qubits': [q.index for q in instruction.acquires],\n 'memory_slot': [m.index for m in instruction.mem_slots]\n }\n if meas_level == 2:\n if instruction.command.discriminator:\n command_dict.update({\n 'discriminators': [\n QobjMeasurementOption(\n name=instruction.command.discriminator.name,\n params=instruction.command.discriminator.params)\n ]\n })\n command_dict.update({\n 'register_slot': [regs.index for regs in instruction.reg_slots]\n })\n if meas_level >= 1:\n if instruction.command.kernel:\n command_dict.update({\n 'kernels': [\n QobjMeasurementOption(\n name=instruction.command.kernel.name,\n params=instruction.command.kernel.params)\n ]\n })\n return self._qobj_model(**command_dict)"
},
{
"code": "def getUserId(self):\n self.userId = self(\"GET\", \"{0}/users/self/profile\".format(self.API_USER),\n auth=self.Auth.SkypeToken).json().get(\"username\")"
},
{
"code": "def fields(self, *fields):\n if len(fields) == 0:\n return [el.split() for el in self]\n res = SList()\n for el in [f.split() for f in self]:\n lineparts = []\n for fd in fields:\n try:\n lineparts.append(el[fd])\n except IndexError:\n pass\n if lineparts:\n res.append(\" \".join(lineparts))\n return res"
},
{
"code": "def run_picard_sort(job, bam, sort_by_name=False):\n work_dir = job.fileStore.getLocalTempDir()\n job.fileStore.readGlobalFile(bam, os.path.join(work_dir, 'input.bam'))\n command = ['SortSam',\n 'O=/data/output.bam',\n 'I=/data/input.bam']\n docker_parameters = ['--rm',\n '--log-driver', 'none',\n '-e', 'JAVA_OPTIONS=-Djava.io.tmpdir=/data/ -Xmx{}'.format(job.memory),\n '-v', '{}:/data'.format(work_dir)]\n if sort_by_name:\n command.append('SO=queryname')\n else:\n command.append('SO=coordinate')\n start_time = time.time()\n dockerCall(job=job, workDir=work_dir,\n parameters=command,\n tool='quay.io/ucsc_cgl/picardtools:1.95--dd5ac549b95eb3e5d166a5e310417ef13651994e',\n dockerParameters=docker_parameters)\n end_time = time.time()\n _log_runtime(job, start_time, end_time, \"Picard SortSam\")\n return job.fileStore.writeGlobalFile(os.path.join(work_dir, 'output.bam'))"
},
{
"code": "def crash_handler_lite(etype, evalue, tb):\n traceback.print_exception(etype, evalue, tb)\n from IPython.core.interactiveshell import InteractiveShell\n if InteractiveShell.initialized():\n config = \"%config \"\n else:\n config = \"c.\"\n print >> sys.stderr, _lite_message_template.format(email=author_email, config=config)"
},
{
"code": "def rule(cls, rulename=None, erase=False):\n if not hasattr(cls, '_rules'):\n raise TypeError(\n \"%s didn't seems to be a BasicParser subsclasse\" % cls.__name__)\n class_hook_list = cls._hooks\n class_rule_list = cls._rules\n def wrapper(f):\n nonlocal rulename\n add_method(cls)(f)\n if rulename is None:\n rulename = f.__name__\n if not erase and (rulename in class_hook_list or rulename in class_rule_list):\n raise TypeError(\"%s is already define has rule or hook\" % rulename)\n if '.' not in rulename:\n rulename = cls.__module__ + '.' + cls.__name__ + '.' + rulename\n set_one(class_rule_list, rulename, f)\n return f\n return wrapper"
},
{
"code": "def set_request_header(self, name, value):\n _name = BSTR(name)\n _value = BSTR(value)\n _WinHttpRequest._SetRequestHeader(self, _name, _value)"
},
{
"code": "def source_expand(self, source):\n result = []\n if not isinstance(source, list):\n source = [source]\n for src in source:\n tmp = self.opt.recursive\n self.opt.recursive = False\n result += [f['name'] for f in self.s3walk(src, True)]\n self.opt.recursive = tmp\n if (len(result) == 0) and (not self.opt.ignore_empty_source):\n fail(\"[Runtime Failure] Source doesn't exist.\")\n return result"
},
{
"code": "def new_frontend_master(self):\n ip = self.ip if self.ip in LOCAL_IPS else LOCALHOST\n kernel_manager = self.kernel_manager_class(\n ip=ip,\n connection_file=self._new_connection_file(),\n config=self.config,\n )\n kwargs = dict()\n kwargs['extra_arguments'] = self.kernel_argv\n kernel_manager.start_kernel(**kwargs)\n kernel_manager.start_channels()\n widget = self.widget_factory(config=self.config,\n local_kernel=True)\n self.init_colors(widget)\n widget.kernel_manager = kernel_manager\n widget._existing = False\n widget._may_close = True\n widget._confirm_exit = self.confirm_exit\n return widget"
},
{
"code": "def valid(self):\n if self.expiration_time:\n return self.expiration_time > int(time.time())\n else:\n return True"
},
{
"code": "def add_new_heart_handler(self, handler):\n self.log.debug(\"heartbeat::new_heart_handler: %s\", handler)\n self._new_handlers.add(handler)"
},
{
"code": "def get_ordered_list_type(meta_data, numId, ilvl):\n numbering_dict = meta_data.numbering_dict\n if numId not in numbering_dict:\n return DEFAULT_LIST_NUMBERING_STYLE\n if ilvl not in numbering_dict[numId]:\n return DEFAULT_LIST_NUMBERING_STYLE\n return meta_data.numbering_dict[numId][ilvl]"
},
{
"code": "def configure_inline_support(shell, backend, user_ns=None):\n try:\n from IPython.zmq.pylab.backend_inline import InlineBackend\n except ImportError:\n return\n user_ns = shell.user_ns if user_ns is None else user_ns\n cfg = InlineBackend.instance(config=shell.config)\n cfg.shell = shell\n if cfg not in shell.configurables:\n shell.configurables.append(cfg)\n if backend == backends['inline']:\n from IPython.zmq.pylab.backend_inline import flush_figures\n from matplotlib import pyplot\n shell.register_post_execute(flush_figures)\n pyplot.rcParams.update(cfg.rc)\n user_ns['figsize'] = pyplot.figsize = figsize\n fmt = cfg.figure_format\n select_figure_format(shell, fmt)\n from IPython.core.display import display\n user_ns['display'] = display\n user_ns['getfigs'] = getfigs"
},
{
"code": "def decode_bytecode(bytecode):\n bytecode_wnd = memoryview(bytecode)\n while bytecode_wnd:\n opcode_id = byte2int(bytecode_wnd[0])\n opcode = OPCODE_MAP[opcode_id]\n if opcode.imm_struct is not None:\n offs, imm, _ = opcode.imm_struct.from_raw(None, bytecode_wnd[1:])\n else:\n imm = None\n offs = 0\n insn_len = 1 + offs\n yield Instruction(opcode, imm, insn_len)\n bytecode_wnd = bytecode_wnd[insn_len:]"
},
{
"code": "def __complete_interns(\n self, value: str, include_private_vars: bool = True\n ) -> Iterable[str]:\n if include_private_vars:\n is_match = Namespace.__completion_matcher(value)\n else:\n _is_match = Namespace.__completion_matcher(value)\n def is_match(entry: Tuple[sym.Symbol, Var]) -> bool:\n return _is_match(entry) and not entry[1].is_private\n return map(\n lambda entry: f\"{entry[0].name}\",\n filter(is_match, [(s, v) for s, v in self.interns]),\n )"
},
{
"code": "def configure(self, options, config):\n Plugin.configure(self, options, config)\n self.config = config\n if self.enabled:\n self.stats = {'errors': 0,\n 'failures': 0,\n 'passes': 0,\n 'skipped': 0\n }\n self.errorlist = []\n self.error_report_file = codecs.open(options.xunit_file, 'w',\n self.encoding, 'replace')"
},
{
"code": "def renew_lock(self):\n if self._queue_name:\n self.service_bus_service.renew_lock_queue_message(\n self._queue_name,\n self.broker_properties['SequenceNumber'],\n self.broker_properties['LockToken'])\n elif self._topic_name and self._subscription_name:\n self.service_bus_service.renew_lock_subscription_message(\n self._topic_name,\n self._subscription_name,\n self.broker_properties['SequenceNumber'],\n self.broker_properties['LockToken'])\n else:\n raise AzureServiceBusPeekLockError(_ERROR_MESSAGE_NOT_PEEK_LOCKED_ON_RENEW_LOCK)"
},
{
"code": "def call(self, inputs):\n net = self.encoder_net(tf.cast(inputs, tf.float32))\n return ed.MultivariateNormalDiag(\n loc=net[..., :self.latent_size],\n scale_diag=tf.nn.softplus(net[..., self.latent_size:]),\n name=\"latent_code_posterior\")"
},
{
"code": "def kvlayer_key_to_stream_id(k):\n abs_url_hash, epoch_ticks = k\n return '{0}-{1}'.format(epoch_ticks,\n base64.b16encode(abs_url_hash).lower())"
},
{
"code": "def update_binary_annotations(self, extra_annotations):\n if not self.logging_context:\n self.binary_annotations.update(extra_annotations)\n else:\n self.logging_context.tags.update(extra_annotations)"
},
{
"code": "def status(self,verbose=0):\n self._update_status()\n self._group_report(self.running,'Running')\n self._group_report(self.completed,'Completed')\n self._group_report(self.dead,'Dead')\n self._comp_report[:] = []\n self._dead_report[:] = []"
},
{
"code": "def visit_table(self, layout):\n table_content = self.get_table_content(layout)\n cols_width = [0] * len(table_content[0])\n for row in table_content:\n for index, col in enumerate(row):\n cols_width[index] = max(cols_width[index], len(col))\n self.default_table(layout, table_content, cols_width)\n self.writeln()"
},
{
"code": "def no_exp(number):\n r\n mant, exp = to_scientific_tuple(number)\n if not exp:\n return str(number)\n floating_mant = \".\" in mant\n mant = mant.replace(\".\", \"\")\n if exp < 0:\n return \"0.\" + \"0\" * (-exp - 1) + mant\n if not floating_mant:\n return mant + \"0\" * exp + (\".0\" if isinstance(number, float) else \"\")\n lfpart = len(mant) - 1\n if lfpart < exp:\n return (mant + \"0\" * (exp - lfpart)).rstrip(\".\")\n return mant"
},
{
"code": "def url_query_params(url):\n return dict(urlparse.parse_qsl(urlparse.urlparse(url).query, True))"
},
{
"code": "def path_dispatch_old_new(mname, returns_model):\n def _wrapper(self, old_path, new_path, *args, **kwargs):\n old_prefix, old_mgr, old_mgr_path = _resolve_path(\n old_path, self.managers\n )\n new_prefix, new_mgr, new_mgr_path = _resolve_path(\n new_path, self.managers,\n )\n if old_mgr is not new_mgr:\n raise HTTPError(\n 400,\n \"Can't move files between backends ({old} -> {new})\".format(\n old=old_path,\n new=new_path,\n )\n )\n assert new_prefix == old_prefix\n result = getattr(new_mgr, mname)(\n old_mgr_path,\n new_mgr_path,\n *args,\n **kwargs\n )\n if returns_model and new_prefix:\n return _apply_prefix(new_prefix, result)\n else:\n return result\n return _wrapper"
},
{
"code": "def get_admins(self, account_id, params={}):\n url = ADMINS_API.format(account_id)\n admins = []\n for data in self._get_paged_resource(url, params=params):\n admins.append(CanvasAdmin(data=data))\n return admins"
},
{
"code": "def set_feature_transform(self, mode='polynomial', degree=1):\n if self.status != 'load_train_data':\n print(\"Please load train data first.\")\n return self.train_X\n self.feature_transform_mode = mode\n self.feature_transform_degree = degree\n self.train_X = self.train_X[:, 1:]\n self.train_X = utility.DatasetLoader.feature_transform(\n self.train_X,\n self.feature_transform_mode,\n self.feature_transform_degree\n )\n return self.train_X"
},
{
"code": "def _wanmen_get_title_by_json_topic_part(json_content, tIndex, pIndex):\n return '_'.join([json_content[0]['name'],\n json_content[0]['Topics'][tIndex]['name'],\n json_content[0]['Topics'][tIndex]['Parts'][pIndex]['name']])"
},
{
"code": "def fallback_to_default_project_id(func):\n @functools.wraps(func)\n def inner_wrapper(self, *args, **kwargs):\n if len(args) > 0:\n raise AirflowException(\n \"You must use keyword arguments in this methods rather than\"\n \" positional\")\n if 'project_id' in kwargs:\n kwargs['project_id'] = self._get_project_id(kwargs['project_id'])\n else:\n kwargs['project_id'] = self._get_project_id(None)\n if not kwargs['project_id']:\n raise AirflowException(\"The project id must be passed either as \"\n \"keyword project_id parameter or as project_id extra \"\n \"in GCP connection definition. Both are not set!\")\n return func(self, *args, **kwargs)\n return inner_wrapper"
},
{
"code": "def get_model_class(settings_entry_name):\n app_name, model_name = get_app_n_model(settings_entry_name)\n try:\n model = apps_get_model(app_name, model_name)\n except (LookupError, ValueError):\n model = None\n if model is None:\n raise ImproperlyConfigured(\n '`SITETREE_%s` refers to model `%s` that has not been installed.' % (settings_entry_name, model_name))\n return model"
},
{
"code": "def draw(self):\n self.screen.border(0)\n if self.title is not None:\n self.screen.addstr(2, 2, self.title, curses.A_STANDOUT)\n if self.subtitle is not None:\n self.screen.addstr(4, 2, self.subtitle, curses.A_BOLD)\n for index, item in enumerate(self.items):\n if self.current_option == index:\n text_style = self.highlight\n else:\n text_style = self.normal\n self.screen.addstr(5 + index, 4, item.show(index), text_style)\n screen_rows, screen_cols = CursesMenu.stdscr.getmaxyx()\n top_row = 0\n if 6 + len(self.items) > screen_rows:\n if screen_rows + self.current_option < 6 + len(self.items):\n top_row = self.current_option\n else:\n top_row = 6 + len(self.items) - screen_rows\n self.screen.refresh(top_row, 0, 0, 0, screen_rows - 1, screen_cols - 1)"
},
{
"code": "def svg_to_image(string, size=None):\n if isinstance(string, unicode):\n string = string.encode('utf-8')\n renderer = QtSvg.QSvgRenderer(QtCore.QByteArray(string))\n if not renderer.isValid():\n raise ValueError('Invalid SVG data.')\n if size is None:\n size = renderer.defaultSize()\n image = QtGui.QImage(size, QtGui.QImage.Format_ARGB32)\n painter = QtGui.QPainter(image)\n renderer.render(painter)\n return image"
},
{
"code": "def token_indent(self, idx):\n line_indent = self.line_indent(idx)\n return line_indent + \" \" * (self.start_col(idx) - len(line_indent))"
},
{
"code": "def close(self):\n self.flush()\n setattr(sys, self.channel, self.ostream)\n self.file.close()\n self._closed = True"
},
{
"code": "def info(self):\n for key, val in self.header.items():\n if key == b'src_raj':\n val = val.to_string(unit=u.hour, sep=':')\n if key == b'src_dej':\n val = val.to_string(unit=u.deg, sep=':')\n if key == b'tsamp':\n val *= u.second\n if key in ('foff', 'fch1'):\n val *= u.MHz\n if key == b'tstart':\n print(\"%16s : %32s\" % (\"tstart (ISOT)\", Time(val, format='mjd').isot))\n key = \"tstart (MJD)\"\n print(\"%16s : %32s\" % (key, val))\n print(\"\\n%16s : %32s\" % (\"Num ints in file\", self.n_ints_in_file))\n print(\"%16s : %32s\" % (\"Data shape\", self.data.shape))\n print(\"%16s : %32s\" % (\"Start freq (MHz)\", self.freqs[0]))\n print(\"%16s : %32s\" % (\"Stop freq (MHz)\", self.freqs[-1]))"
},
{
"code": "def fromRaw(cls, skype=None, raw={}):\n return cls(skype, raw, **cls.rawToFields(raw))"
},
{
"code": "def inherit_from_std_ex(node: astroid.node_classes.NodeNG) -> bool:\n ancestors = node.ancestors() if hasattr(node, \"ancestors\") else []\n for ancestor in itertools.chain([node], ancestors):\n if (\n ancestor.name in (\"Exception\", \"BaseException\")\n and ancestor.root().name == EXCEPTIONS_MODULE\n ):\n return True\n return False"
},
{
"code": "def findStationCodesByCity(city_name, token):\n req = requests.get(\n API_ENDPOINT_SEARCH,\n params={\n 'token': token,\n 'keyword': city_name\n })\n if req.status_code == 200 and req.json()[\"status\"] == \"ok\":\n return [result[\"uid\"] for result in req.json()[\"data\"]]\n else:\n return []"
},
{
"code": "def v2_playbook_on_task_start(self, task, **kwargs):\n self.last_task_name = task.get_name()\n self.printed_last_task = False"
},
{
"code": "def _register_stements(self, statements: List[\"HdlStatement\"],\n target: List[\"HdlStatement\"]):\n for stm in flatten(statements):\n assert stm.parentStm is None, stm\n stm._set_parent_stm(self)\n target.append(stm)"
},
{
"code": "def _query_cassandra(self):\n self.hook = CassandraHook(cassandra_conn_id=self.cassandra_conn_id)\n session = self.hook.get_conn()\n cursor = session.execute(self.cql)\n return cursor"
},
{
"code": "def request_tokens(self):\n url = 'https://api.ecobee.com/token'\n params = {'grant_type': 'ecobeePin', 'code': self.authorization_code,\n 'client_id': self.api_key}\n try:\n request = requests.post(url, params=params)\n except RequestException:\n logger.warn(\"Error connecting to Ecobee. Possible connectivity outage.\"\n \"Could not request token.\")\n return\n if request.status_code == requests.codes.ok:\n self.access_token = request.json()['access_token']\n self.refresh_token = request.json()['refresh_token']\n self.write_tokens_to_file()\n self.pin = None\n else:\n logger.warn('Error while requesting tokens from ecobee.com.'\n ' Status code: ' + str(request.status_code))\n return"
},
{
"code": "def cancel_task(self, task_id):\n self.registry.remove(task_id)\n self._scheduler.cancel_job_task(task_id)\n logger.info(\"Task %s canceled\", task_id)"
},
{
"code": "def _superop_to_choi(data, input_dim, output_dim):\n shape = (output_dim, output_dim, input_dim, input_dim)\n return _reshuffle(data, shape)"
},
{
"code": "def status(institute_id, case_name):\n institute_obj, case_obj = institute_and_case(store, institute_id, case_name)\n user_obj = store.user(current_user.email)\n status = request.form.get('status', case_obj['status'])\n link = url_for('.case', institute_id=institute_id, case_name=case_name)\n if status == 'archive':\n store.archive_case(institute_obj, case_obj, user_obj, status, link)\n else:\n store.update_status(institute_obj, case_obj, user_obj, status, link)\n return redirect(request.referrer)"
},
{
"code": "def update_database(self, instance_id, database_id, ddl_statements,\n project_id=None,\n operation_id=None):\n instance = self._get_client(project_id=project_id).instance(\n instance_id=instance_id)\n if not instance.exists():\n raise AirflowException(\"The instance {} does not exist in project {} !\".\n format(instance_id, project_id))\n database = instance.database(database_id=database_id)\n try:\n operation = database.update_ddl(\n ddl_statements=ddl_statements, operation_id=operation_id)\n if operation:\n result = operation.result()\n self.log.info(result)\n return\n except AlreadyExists as e:\n if e.code == 409 and operation_id in e.message:\n self.log.info(\"Replayed update_ddl message - the operation id %s \"\n \"was already done before.\", operation_id)\n return\n except GoogleAPICallError as e:\n self.log.error('An error occurred: %s. Exiting.', e.message)\n raise e"
},
{
"code": "def name(self):\n name = self._platform_impl.get_process_name()\n if os.name == 'posix':\n try:\n cmdline = self.cmdline\n except AccessDenied:\n pass\n else:\n if cmdline:\n extended_name = os.path.basename(cmdline[0])\n if extended_name.startswith(name):\n name = extended_name\n self._platform_impl._process_name = name\n return name"
},
{
"code": "def create_group(self, group):\n self._valid_group_id(group.id)\n body = {\"data\": group.json_data()}\n url = \"{}/group/{}\".format(self.API, group.name)\n data = self._put_resource(url, headers={}, body=body)\n return self._group_from_json(data.get(\"data\"))"
},
{
"code": "def _minimal_export_traces(self, outdir=None, analytes=None,\n samples=None, subset='All_Analyses'):\n if analytes is None:\n analytes = self.analytes\n elif isinstance(analytes, str):\n analytes = [analytes]\n if samples is not None:\n subset = self.make_subset(samples)\n samples = self._get_samples(subset)\n focus_stage = 'rawdata'\n if not os.path.isdir(outdir):\n os.mkdir(outdir)\n for s in samples:\n d = self.data[s].data[focus_stage]\n out = Bunch()\n for a in analytes:\n out[a] = d[a]\n out = pd.DataFrame(out, index=self.data[s].Time)\n out.index.name = 'Time'\n d = dateutil.parser.parse(self.data[s].meta['date'])\n header = ['\n (time.strftime('%Y:%m:%d %H:%M:%S')),\n \"\n '\n '\n '\n '\n header = '\\n'.join(header) + '\\n'\n csv = out.to_csv()\n with open('%s/%s.csv' % (outdir, s), 'w') as f:\n f.write(header)\n f.write(csv)\n return"
},
{
"code": "def as_recarray(self):\n dtype = [(k,v.dtype) for k,v in self.__dict__.iteritems()]\n R = numpy.recarray(len(self.__dict__[k]),dtype=dtype)\n for key in self.__dict__:\n R[key] = self.__dict__[key]\n return R"
},
{
"code": "def unregister(self, mimetype, processor):\n if mimetype in self and processor in self[mimetype]:\n self[mimetype].remove(processor)"
},
{
"code": "def _write_iop_to_file(self, iop, file_name):\n lg.info('Writing :: ' + file_name)\n f = open(file_name, 'w')\n for i in scipy.nditer(iop):\n f.write(str(i) + '\\n')"
},
{
"code": "async def get_tracks(self, *, limit: Optional[int] = 20, offset: Optional[int] = 0) -> List[Track]:\n data = await self.__client.http.album_tracks(self.id, limit=limit, offset=offset)\n return list(Track(self.__client, item) for item in data['items'])"
},
{
"code": "def get_ammo_generator(self):\n af_readers = {\n 'phantom': missile.AmmoFileReader,\n 'slowlog': missile.SlowLogReader,\n 'line': missile.LineReader,\n 'uri': missile.UriReader,\n 'uripost': missile.UriPostReader,\n 'access': missile.AccessLogReader,\n 'caseline': missile.CaseLineReader,\n }\n if self.uris and self.ammo_file:\n raise StepperConfigurationError(\n 'Both uris and ammo file specified. You must specify only one of them'\n )\n elif self.uris:\n ammo_gen = missile.UriStyleGenerator(\n self.uris, self.headers, http_ver=self.http_ver)\n elif self.ammo_file:\n if self.ammo_type in af_readers:\n if self.ammo_type == 'phantom':\n opener = resource.get_opener(self.ammo_file)\n with opener(self.use_cache) as ammo:\n try:\n if not ammo.next()[0].isdigit():\n self.ammo_type = 'uri'\n self.log.info(\n \"Setting ammo_type 'uri' because ammo is not started with digit and you did not specify ammo format\"\n )\n else:\n self.log.info(\n \"Default ammo type ('phantom') used, use 'phantom.ammo_type' option to override it\"\n )\n except StopIteration:\n self.log.exception(\n \"Couldn't read first line of ammo file\")\n raise AmmoFileError(\n \"Couldn't read first line of ammo file\")\n else:\n raise NotImplementedError(\n 'No such ammo type implemented: \"%s\"' % self.ammo_type)\n ammo_gen = af_readers[self.ammo_type](\n self.ammo_file, headers=self.headers, http_ver=self.http_ver, use_cache=self.use_cache)\n else:\n raise StepperConfigurationError(\n 'Ammo not found. Specify uris or ammo file')\n self.log.info(\"Using %s ammo reader\" % type(ammo_gen).__name__)\n return ammo_gen"
},
{
"code": "def check_rdd_dtype(rdd, expected_dtype):\n if not isinstance(rdd, BlockRDD):\n raise TypeError(\"Expected {0} for parameter rdd, got {1}.\"\n .format(BlockRDD, type(rdd)))\n if isinstance(rdd, DictRDD):\n if not isinstance(expected_dtype, dict):\n raise TypeError('Expected {0} for parameter '\n 'expected_dtype, got {1}.'\n .format(dict, type(expected_dtype)))\n accept = True\n types = dict(list(zip(rdd.columns, rdd.dtype)))\n for key, values in expected_dtype.items():\n if not isinstance(values, (tuple, list)):\n values = [values]\n accept = accept and types[key] in values\n return accept\n if not isinstance(expected_dtype, (tuple, list)):\n expected_dtype = [expected_dtype]\n return rdd.dtype in expected_dtype"
},
{
"code": "def entropy(state):\n rho = np.array(state)\n if rho.ndim == 1:\n return 0\n evals = np.maximum(np.linalg.eigvalsh(state), 0.)\n return shannon_entropy(evals, base=np.e)"
},
{
"code": "def python_matches(self,text):\n if \".\" in text:\n try:\n matches = self.attr_matches(text)\n if text.endswith('.') and self.omit__names:\n if self.omit__names == 1:\n no__name = (lambda txt:\n re.match(r'.*\\.__.*?__',txt) is None)\n else:\n no__name = (lambda txt:\n re.match(r'.*\\._.*?',txt) is None)\n matches = filter(no__name, matches)\n except NameError:\n matches = []\n else:\n matches = self.global_matches(text)\n return matches"
},
{
"code": "def subwave(wave, dep_name=None, indep_min=None, indep_max=None, indep_step=None):\n r\n ret = copy.copy(wave)\n if dep_name is not None:\n ret.dep_name = dep_name\n _bound_waveform(ret, indep_min, indep_max)\n pexdoc.addai(\"indep_step\", bool((indep_step is not None) and (indep_step <= 0)))\n exmsg = \"Argument `indep_step` is greater than independent vector range\"\n cond = bool(\n (indep_step is not None)\n and (indep_step > ret._indep_vector[-1] - ret._indep_vector[0])\n )\n pexdoc.addex(RuntimeError, exmsg, cond)\n if indep_step:\n indep_vector = _barange(indep_min, indep_max, indep_step)\n dep_vector = _interp_dep_vector(ret, indep_vector)\n ret._set_indep_vector(indep_vector, check=False)\n ret._set_dep_vector(dep_vector, check=False)\n return ret"
},
{
"code": "def init_transformers(self):\n self._transformers = []\n for transformer_cls in _default_transformers:\n transformer_cls(\n shell=self.shell, prefilter_manager=self, config=self.config\n )"
},
{
"code": "def _mode(self):\n return (self.mean_direction +\n tf.zeros_like(self.concentration)[..., tf.newaxis])"
},
{
"code": "def _prepare_args_with_initial_vertex(objective_function,\n initial_vertex,\n step_sizes,\n objective_at_initial_vertex,\n batch_evaluate_objective):\n dim = tf.size(input=initial_vertex)\n num_vertices = dim + 1\n unit_vectors_along_axes = tf.reshape(\n tf.eye(dim, dim, dtype=initial_vertex.dtype.base_dtype),\n tf.concat([[dim], tf.shape(input=initial_vertex)], axis=0))\n simplex_face = initial_vertex + step_sizes * unit_vectors_along_axes\n simplex = tf.concat([tf.expand_dims(initial_vertex, axis=0),\n simplex_face], axis=0)\n num_evaluations = 0\n if objective_at_initial_vertex is None:\n objective_at_initial_vertex = objective_function(initial_vertex)\n num_evaluations += 1\n objective_at_simplex_face, num_evals = _evaluate_objective_multiple(\n objective_function, simplex_face, batch_evaluate_objective)\n num_evaluations += num_evals\n objective_at_simplex = tf.concat(\n [\n tf.expand_dims(objective_at_initial_vertex, axis=0),\n objective_at_simplex_face\n ], axis=0)\n return (dim,\n num_vertices,\n simplex,\n objective_at_simplex,\n num_evaluations)"
},
{
"code": "def convertBits(self, sigOrVal, toType):\n if isinstance(sigOrVal, Value):\n return convertBits__val(self, sigOrVal, toType)\n elif isinstance(toType, HBool):\n if self.bit_length() == 1:\n v = 0 if sigOrVal._dtype.negated else 1\n return sigOrVal._eq(self.getValueCls().fromPy(v, self))\n elif isinstance(toType, Bits):\n if self.bit_length() == toType.bit_length():\n return sigOrVal._convSign(toType.signed)\n elif toType == INT:\n return Operator.withRes(AllOps.BitsToInt, [sigOrVal], toType)\n return default_auto_cast_fn(self, sigOrVal, toType)"
},
{
"code": "def from_symbol(cls, symbol):\n if symbol.lower() == symbol:\n return cls(PIECE_SYMBOLS.index(symbol), WHITE)\n else:\n return cls(PIECE_SYMBOLS.index(symbol.lower()), BLACK)"
},
{
"code": "def pauli_group(number_of_qubits, case='weight'):\n if number_of_qubits < 5:\n temp_set = []\n if case == 'weight':\n tmp = pauli_group(number_of_qubits, case='tensor')\n return sorted(tmp, key=lambda x: -np.count_nonzero(\n np.array(x.to_label(), 'c') == b'I'))\n elif case == 'tensor':\n for k in range(4 ** number_of_qubits):\n z = np.zeros(number_of_qubits, dtype=np.bool)\n x = np.zeros(number_of_qubits, dtype=np.bool)\n for j in range(number_of_qubits):\n element = (k // (4 ** j)) % 4\n if element == 1:\n x[j] = True\n elif element == 2:\n z[j] = True\n x[j] = True\n elif element == 3:\n z[j] = True\n temp_set.append(Pauli(z, x))\n return temp_set\n else:\n raise QiskitError(\"Only support 'weight' or 'tensor' cases \"\n \"but you have {}.\".format(case))\n raise QiskitError(\"Only support number of qubits is less than 5\")"
},
{
"code": "def _validate(self, qobj):\n n_qubits = qobj.config.n_qubits\n max_qubits = self.configuration().n_qubits\n if n_qubits > max_qubits:\n raise BasicAerError('Number of qubits {} '.format(n_qubits) +\n 'is greater than maximum ({}) '.format(max_qubits) +\n 'for \"{}\".'.format(self.name()))\n for experiment in qobj.experiments:\n name = experiment.header.name\n if experiment.config.memory_slots == 0:\n logger.warning('No classical registers in circuit \"%s\", '\n 'counts will be empty.', name)\n elif 'measure' not in [op.name for op in experiment.instructions]:\n logger.warning('No measurements in circuit \"%s\", '\n 'classical register will remain all zeros.', name)"
},
{
"code": "def classification(self, classification):\n allowed_values = [\"Public Limited Indian Non-Government Company\", \"Private Limited Indian Non-Government Company\", \"One Person Company\", \"Private Limited Foreign Company Incorporated in India\", \"Public Limited Foreign Company Incorporated in India\", \"Union Government Company\", \"State Government Company\", \"Guarantee & Association Public\", \"Guarantee & Association Private\", \"Not For Profit Company\", \"Unlimited Liabilities Public\", \"Unlimited Liabilities Private\", \"Undefined\"]\n if classification not in allowed_values:\n raise ValueError(\n \"Invalid value for `classification`, must be one of {0}\"\n .format(allowed_values)\n )\n self._classification = classification"
},
{
"code": "def val_where(cond, tval, fval):\n if isinstance(tval, tf.Tensor):\n return tf.where(cond, tval, fval)\n elif isinstance(tval, tuple):\n cls = type(tval)\n return cls(*(val_where(cond, t, f) for t, f in zip(tval, fval)))\n else:\n raise Exception(TypeError)"
},
{
"code": "def get_embedding_levels(text, storage, upper_is_rtl=False, debug=False):\n prev_surrogate = False\n base_level = storage['base_level']\n for _ch in text:\n if _IS_UCS2 and (_SURROGATE_MIN <= ord(_ch) <= _SURROGATE_MAX):\n prev_surrogate = _ch\n continue\n elif prev_surrogate:\n _ch = prev_surrogate + _ch\n prev_surrogate = False\n if upper_is_rtl and _ch.isupper():\n bidi_type = 'R'\n else:\n bidi_type = bidirectional(_ch)\n storage['chars'].append({\n 'ch': _ch,\n 'level': base_level,\n 'type': bidi_type,\n 'orig': bidi_type\n })\n if debug:\n debug_storage(storage, base_info=True)"
},
{
"code": "def load(self):\n self._check_open()\n try:\n data = json.load(self.file, **self.load_args)\n except ValueError:\n data = {}\n if not isinstance(data, dict):\n raise ValueError('Root JSON type must be dictionary')\n self.clear()\n self.update(data)"
},
{
"code": "def calc(pvalues, lamb):\n m = len(pvalues)\n pi0 = (pvalues > lamb).sum() / ((1 - lamb)*m)\n pFDR = np.ones(m)\n print(\"pFDR y Pr fastPow\")\n for i in range(m):\n y = pvalues[i]\n Pr = max(1, m - i) / float(m)\n pFDR[i] = (pi0 * y) / (Pr * (1 - math.pow(1-y, m)))\n print(i, pFDR[i], y, Pr, 1.0 - math.pow(1-y, m))\n num_null = pi0*m\n num_alt = m - num_null\n num_negs = np.array(range(m))\n num_pos = m - num_negs\n pp = num_pos / float(m)\n qvalues = np.ones(m)\n qvalues[0] = pFDR[0]\n for i in range(m-1):\n qvalues[i+1] = min(qvalues[i], pFDR[i+1])\n sens = ((1.0 - qvalues) * num_pos) / num_alt\n sens[sens > 1.0] = 1.0\n df = pd.DataFrame(dict(\n pvalue=pvalues,\n qvalue=qvalues,\n FDR=pFDR,\n percentile_positive=pp,\n sens=sens\n ))\n df[\"svalue\"] = df.sens[::-1].cummax()[::-1]\n return df, num_null, m"
},
{
"code": "def series(collection, method, prints = 15, *args, **kwargs):\n if 'verbose' in kwargs.keys():\n verbose = kwargs['verbose']\n else:\n verbose = True\n results = []\n timer = turntable.utils.Timer(nLoops=len(collection), numPrints=prints, verbose=verbose)\n for subject in collection:\n results.append(method(subject, *args, **kwargs))\n timer.loop()\n timer.fin()\n return results"
},
{
"code": "def getlist(self, section, option):\n value_list = self.get(section, option)\n values = []\n for value_line in value_list.split('\\n'):\n for value in value_line.split(','):\n value = value.strip()\n if value:\n values.append(value)\n return values"
},
{
"code": "def glob(self, pattern):\n cls = self.__class__\n return [cls(s) for s in glob.glob(unicode(self / pattern))]"
},
{
"code": "def export_html(html, filename, image_tag = None, inline = True):\n if image_tag is None:\n image_tag = default_image_tag\n else:\n image_tag = ensure_utf8(image_tag)\n if inline:\n path = None\n else:\n root,ext = os.path.splitext(filename)\n path = root + \"_files\"\n if os.path.isfile(path):\n raise OSError(\"%s exists, but is not a directory.\" % path)\n with open(filename, 'w') as f:\n html = fix_html(html)\n f.write(IMG_RE.sub(lambda x: image_tag(x, path = path, format = \"png\"),\n html))"
},
{
"code": "def export(self, cert, key, type=FILETYPE_PEM, days=100,\n digest=_UNSPECIFIED):\n if not isinstance(cert, X509):\n raise TypeError(\"cert must be an X509 instance\")\n if not isinstance(key, PKey):\n raise TypeError(\"key must be a PKey instance\")\n if not isinstance(type, int):\n raise TypeError(\"type must be an integer\")\n if digest is _UNSPECIFIED:\n raise TypeError(\"digest must be provided\")\n digest_obj = _lib.EVP_get_digestbyname(digest)\n if digest_obj == _ffi.NULL:\n raise ValueError(\"No such digest method\")\n bio = _lib.BIO_new(_lib.BIO_s_mem())\n _openssl_assert(bio != _ffi.NULL)\n sometime = _lib.ASN1_TIME_new()\n _openssl_assert(sometime != _ffi.NULL)\n _lib.X509_gmtime_adj(sometime, 0)\n _lib.X509_CRL_set_lastUpdate(self._crl, sometime)\n _lib.X509_gmtime_adj(sometime, days * 24 * 60 * 60)\n _lib.X509_CRL_set_nextUpdate(self._crl, sometime)\n _lib.X509_CRL_set_issuer_name(\n self._crl, _lib.X509_get_subject_name(cert._x509)\n )\n sign_result = _lib.X509_CRL_sign(self._crl, key._pkey, digest_obj)\n if not sign_result:\n _raise_current_error()\n return dump_crl(type, self)"
},
{
"code": "def parse_text(text):\n assert isinstance(text, _str_type), \"`text` parameter should be a string, got %r\" % type(text)\n gen = iter(text.splitlines(True))\n readline = gen.next if hasattr(gen, \"next\") else gen.__next__\n return Code(_tokenize(readline))"
},
{
"code": "def parsed_forensic_reports_to_csv(reports):\n fields = [\"feedback_type\", \"user_agent\", \"version\", \"original_envelope_id\",\n \"original_mail_from\", \"original_rcpt_to\", \"arrival_date\",\n \"arrival_date_utc\", \"subject\", \"message_id\",\n \"authentication_results\", \"dkim_domain\", \"source_ip_address\",\n \"source_country\", \"source_reverse_dns\", \"source_base_domain\",\n \"delivery_result\", \"auth_failure\", \"reported_domain\",\n \"authentication_mechanisms\", \"sample_headers_only\"]\n if type(reports) == OrderedDict:\n reports = [reports]\n csv_file = StringIO()\n csv_writer = DictWriter(csv_file, fieldnames=fields)\n csv_writer.writeheader()\n for report in reports:\n row = report.copy()\n row[\"source_ip_address\"] = report[\"source\"][\"ip_address\"]\n row[\"source_reverse_dns\"] = report[\"source\"][\"reverse_dns\"]\n row[\"source_base_domain\"] = report[\"source\"][\"base_domain\"]\n row[\"source_country\"] = report[\"source\"][\"country\"]\n del row[\"source\"]\n row[\"subject\"] = report[\"parsed_sample\"][\"subject\"]\n row[\"auth_failure\"] = \",\".join(report[\"auth_failure\"])\n authentication_mechanisms = report[\"authentication_mechanisms\"]\n row[\"authentication_mechanisms\"] = \",\".join(\n authentication_mechanisms)\n del row[\"sample\"]\n del row[\"parsed_sample\"]\n csv_writer.writerow(row)\n return csv_file.getvalue()"
},
{
"code": "def print_processor_inputs(self, processor_name):\n p = self.processors(processor_name=processor_name)\n if len(p) == 1:\n p = p[0]\n else:\n Exception('Invalid processor name')\n for field_schema, _, _ in iterate_schema({}, p['input_schema'], 'input'):\n name = field_schema['name']\n typ = field_schema['type']\n print(\"{} -> {}\".format(name, typ))"
},
{
"code": "def add_price_entity(self, price: dal.Price):\n from decimal import Decimal\n repo = self.get_price_repository()\n existing = (\n repo.query\n .filter(dal.Price.namespace == price.namespace)\n .filter(dal.Price.symbol == price.symbol)\n .filter(dal.Price.date == price.date)\n .filter(dal.Price.time == price.time)\n .first()\n )\n if existing:\n new_value = Decimal(price.value) / Decimal(price.denom)\n self.logger.info(f\"Exists: {price}\")\n if price.currency != existing.currency:\n raise ValueError(\n f\"The currency is different for price {price}!\")\n if existing.value != price.value:\n existing.value = price.value\n self.logger.info(f\"Updating to {new_value}.\")\n if existing.denom != price.denom:\n existing.denom = price.denom\n else:\n self.session.add(price)\n self.logger.info(f\"Added {price}\")"
},
{
"code": "def _load_features_from_images(self, images, names=None):\n if names is not None and len(names) != len(images):\n raise Exception(\n \"Lists of feature names and images must be of same length!\")\n self.feature_names = names if names is not None else images\n self.feature_images = imageutils.load_imgs(images, self.masker)"
},
{
"code": "def remove_chain(self, name):\n if name in self.chains:\n delattr(self.chains, name)\n else:\n raise ValueError(\"Chain with this name not found\")"
},
{
"code": "def _use_rev_b_archive(self, records, offset):\n if type(self._ARCHIVE_REV_B) is bool:\n return self._ARCHIVE_REV_B\n data = ArchiveBStruct.unpack_from(records, offset)\n if data['RecType'] == 0:\n log.info('detected archive rev. B')\n self._ARCHIVE_REV_B = True\n else:\n log.info('detected archive rev. A')\n self._ARCHIVE_REV_B = False\n return self._ARCHIVE_REV_B"
},
{
"code": "def do_help(self, options, args, parser):\n if options.help:\n if self.classic:\n self.help_fn(topic='help')\n else:\n self.help_fn(parser=parser)\n return True\n if \"help\" in options.actions:\n if args:\n for a in args:\n parser = CMDS.get(a)\n if parser:\n self.help_fn(parser=parser)\n else:\n self.help_fn(topic=a)\n else:\n self.help_fn(topic='help')\n return True\n if options.version:\n self.help_fn(topic='version')\n return True\n return False"
},
{
"code": "def register_routes(app):\n from . import controllers\n from flask.blueprints import Blueprint\n for module in _import_submodules_from_package(controllers):\n bp = getattr(module, 'bp')\n if bp and isinstance(bp, Blueprint):\n app.register_blueprint(bp)"
},
{
"code": "def flush(self, timeout=60):\n if timeout <= 0:\n raise ErrBadTimeout\n if self.is_closed:\n raise ErrConnectionClosed\n future = asyncio.Future(loop=self._loop)\n try:\n yield from self._send_ping(future)\n yield from asyncio.wait_for(future, timeout, loop=self._loop)\n except asyncio.TimeoutError:\n future.cancel()\n raise ErrTimeout"
},
{
"code": "def match(self):\n result = []\n to_match = comp(self.regex)\n if self.rematch:\n pre_result = to_match.findall(self.data)\n else:\n pre_result = to_match.search(self.data)\n if self.return_data and pre_result:\n if self.rematch:\n for data in pre_result:\n if isinstance(data, tuple):\n result.extend(list(data))\n else:\n result.append(data)\n if self.group != 0:\n return result[self.group]\n else:\n result = pre_result.group(\n self.group\n ).strip()\n return result\n if not self.return_data and pre_result:\n return True\n return False"
},
{
"code": "def reset(self, new_session=True):\n self.history_manager.reset(new_session)\n if new_session:\n self.execution_count = 1\n if self.displayhook.do_full_cache:\n self.displayhook.flush()\n if self.user_ns is not self.user_global_ns:\n self.user_ns.clear()\n ns = self.user_global_ns\n drop_keys = set(ns.keys())\n drop_keys.discard('__builtin__')\n drop_keys.discard('__builtins__')\n drop_keys.discard('__name__')\n for k in drop_keys:\n del ns[k]\n self.user_ns_hidden.clear()\n self.init_user_ns()\n self.alias_manager.clear_aliases()\n self.alias_manager.init_aliases()\n self.clear_main_mod_cache()\n self.new_main_mod()"
},
{
"code": "def event(uid):\n db = get_session()\n event = db.query(RecordedEvent).filter(RecordedEvent.uid == uid).first() \\\n or db.query(UpcomingEvent).filter(UpcomingEvent.uid == uid).first()\n if event:\n return make_data_response(event.serialize())\n return make_error_response('No event with specified uid', 404)"
},
{
"code": "def parse_database_url(url):\n if url == \"sqlite://:memory:\":\n raise Exception(\n 'Your url is \"sqlite://:memory:\", if you want '\n 'an sqlite memory database, just use \"sqlite://\"'\n )\n url_parts = urlsplit(url)\n engine = get_engine(url_parts.scheme)\n database, schema = parse_path(url_parts.path)\n port = url_parts.port\n host = url_parts.hostname\n user = url_parts.username\n password = url_parts.password\n params = {key: val.pop() for key, val in parse_qs(url_parts.query).items()}\n return DatabaseInfo(\n engine=engine,\n name=database,\n schema=schema,\n user=user,\n password=password,\n host=host,\n port=port,\n params=params,\n )"
},
{
"code": "def _matmul(a, b,\n transpose_a=False, transpose_b=False,\n adjoint_a=False, adjoint_b=False,\n a_is_sparse=False, b_is_sparse=False,\n name=None):\n if a_is_sparse or b_is_sparse:\n raise NotImplementedError('Numpy backend does not support sparse matmul.')\n if transpose_a or adjoint_a:\n a = _matrix_transpose(a, conjugate=adjoint_a)\n if transpose_b or adjoint_b:\n b = _matrix_transpose(b, conjugate=adjoint_b)\n return np.matmul(a, b)"
},
{
"code": "def _broadcast_cat_event_and_params(event, params, base_dtype):\n if dtype_util.is_integer(event.dtype):\n pass\n elif dtype_util.is_floating(event.dtype):\n event = tf.cast(event, dtype=tf.int32)\n else:\n raise TypeError(\"`value` should have integer `dtype` or \"\n \"`self.dtype` ({})\".format(base_dtype))\n shape_known_statically = (\n tensorshape_util.rank(params.shape) is not None and\n tensorshape_util.is_fully_defined(params.shape[:-1]) and\n tensorshape_util.is_fully_defined(event.shape))\n if not shape_known_statically or params.shape[:-1] != event.shape:\n params *= tf.ones_like(event[..., tf.newaxis],\n dtype=params.dtype)\n params_shape = tf.shape(input=params)[:-1]\n event *= tf.ones(params_shape, dtype=event.dtype)\n if tensorshape_util.rank(params.shape) is not None:\n tensorshape_util.set_shape(event, params.shape[:-1])\n return event, params"
},
{
"code": "def add_patch(self, patch):\n patchline = PatchLine(patch)\n patch = patchline.get_patch()\n if patch:\n self.patch2line[patch] = patchline\n self.patchlines.append(patchline)"
},
{
"code": "def parse_rrset_record_values(e_resource_records):\n records = []\n for e_record in e_resource_records:\n for e_value in e_record:\n records.append(e_value.text)\n return records"
},
{
"code": "def verify_profile_name(msg, cfg):\n if msg.profile not in cfg.data:\n raise UnknownProfileError(msg.profile)"
},
{
"code": "def bots(self):\n json = self.skype.conn(\"GET\", \"{0}/agents\".format(SkypeConnection.API_BOT),\n auth=SkypeConnection.Auth.SkypeToken).json().get(\"agentDescriptions\", [])\n return [self.merge(SkypeBotUser.fromRaw(self.skype, raw)) for raw in json]"
},
{
"code": "def _makeApiCall(self, parameters=None):\n r = self._apiClient.get(self._url, parameters)\n if r.status_code == 200:\n return r.json()\n else:\n raise Exception(\"HTTP %s %s\" % (r.status_code, r.text))"
},
{
"code": "def volume_down(self):\n self._volume_level -= self._volume_step / self._max_volume\n self._device.vol_down(num=self._volume_step)"
},
{
"code": "def bytesize(self, byteorder='@'):\n seed_size = struct.calcsize(byteorder+'q')\n length_size = struct.calcsize(byteorder+'i')\n hashvalue_size = struct.calcsize(byteorder+'I')\n return seed_size + length_size + len(self) * hashvalue_size"
},
{
"code": "def get_certificate_from_publish_settings(publish_settings_path, path_to_write_certificate, subscription_id=None):\n import base64\n try:\n from xml.etree import cElementTree as ET\n except ImportError:\n from xml.etree import ElementTree as ET\n try:\n import OpenSSL.crypto as crypto\n except:\n raise Exception(\"pyopenssl is required to use get_certificate_from_publish_settings\")\n _validate_not_none('publish_settings_path', publish_settings_path)\n _validate_not_none('path_to_write_certificate', path_to_write_certificate)\n tree = ET.parse(publish_settings_path)\n subscriptions = tree.getroot().findall(\"./PublishProfile/Subscription\")\n if subscription_id:\n subscription = next((s for s in subscriptions if s.get('Id').lower() == subscription_id.lower()), None)\n else:\n subscription = subscriptions[0]\n if subscription is None:\n raise ValueError(\"The provided subscription_id '{}' was not found in the publish settings file provided at '{}'\".format(subscription_id, publish_settings_path))\n cert_string = _decode_base64_to_bytes(subscription.get('ManagementCertificate'))\n cert = crypto.load_pkcs12(cert_string, b'') \n with open(path_to_write_certificate, 'wb') as f:\n f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, cert.get_certificate()))\n f.write(crypto.dump_privatekey(crypto.FILETYPE_PEM, cert.get_privatekey()))\n return subscription.get('Id')"
},
{
"code": "def wantClass(self, cls):\n declared = getattr(cls, '__test__', None)\n if declared is not None:\n wanted = declared\n else:\n wanted = (not cls.__name__.startswith('_')\n and (issubclass(cls, unittest.TestCase)\n or self.matches(cls.__name__)))\n plug_wants = self.plugins.wantClass(cls) \n if plug_wants is not None:\n log.debug(\"Plugin setting selection of %s to %s\", cls, plug_wants)\n wanted = plug_wants\n log.debug(\"wantClass %s? %s\", cls, wanted)\n return wanted"
},
{
"code": "def t_NOTEQUAL(self, t):\n r\"!\\=\"\n t.endlexpos = t.lexpos + len(t.value)\n return t"
},
{
"code": "def get_dict(self, timeout=-1):\n results = self.get(timeout)\n engine_ids = [ md['engine_id'] for md in self._metadata ]\n bycount = sorted(engine_ids, key=lambda k: engine_ids.count(k))\n maxcount = bycount.count(bycount[-1])\n if maxcount > 1:\n raise ValueError(\"Cannot build dict, %i jobs ran on engine\n maxcount, bycount[-1]))\n return dict(zip(engine_ids,results))"
},
{
"code": "def create_file(self, bucket, key, file_versions):\n objs = []\n for file_ver in file_versions:\n f = FileInstance.create().set_uri(\n file_ver['full_path'],\n file_ver['size'],\n 'md5:{0}'.format(file_ver['checksum']),\n )\n obj = ObjectVersion.create(bucket, key).set_file(f)\n obj.created = arrow.get(\n file_ver['creation_date']).datetime.replace(tzinfo=None)\n objs.append(obj)\n db.session.commit()\n return objs[-1]"
},
{
"code": "def cli_command_restart(self, msg):\n info = ''\n if self.state == State.RUNNING and self.sprocess and self.sprocess.proc:\n self.state = State.RESTARTING\n self.sprocess.set_exit_callback(self.proc_exit_cb_restart)\n self.sprocess.proc.kill()\n info = 'killed'\n return info"
},
{
"code": "def _reconstruct_matrix(data_list):\n matrix_format = data_list[0]\n data = data_list[1]\n is_empty = isinstance(data, str) and data == '__empty__'\n if matrix_format == 'csc':\n if is_empty:\n return spsp.csc_matrix(data_list[4])\n else:\n return spsp.csc_matrix(tuple(data_list[1:4]), shape=data_list[4])\n elif matrix_format == 'csr':\n if is_empty:\n return spsp.csr_matrix(data_list[4])\n else:\n return spsp.csr_matrix(tuple(data_list[1:4]), shape=data_list[4])\n elif matrix_format == 'bsr':\n if is_empty:\n return spsp.bsr_matrix(data_list[4])\n else:\n return spsp.bsr_matrix(tuple(data_list[1:4]), shape=data_list[4])\n elif matrix_format == 'dia':\n if is_empty:\n return spsp.dia_matrix(data_list[3])\n else:\n return spsp.dia_matrix(tuple(data_list[1:3]), shape=data_list[3])\n else:\n raise RuntimeError('You shall not pass!')"
},
{
"code": "def pull(dry_run, flavor, interactive, debug):\n try:\n main_section = _get_section_name(flavor)\n config = _try_load_config(main_section, interactive)\n lockfile_path = os.path.join(get_data_path(config, main_section),\n 'bugwarrior.lockfile')\n lockfile = PIDLockFile(lockfile_path)\n lockfile.acquire(timeout=10)\n try:\n issue_generator = aggregate_issues(config, main_section, debug)\n synchronize(issue_generator, config, main_section, dry_run)\n finally:\n lockfile.release()\n except LockTimeout:\n log.critical(\n 'Your taskrc repository is currently locked. '\n 'Remove the file at %s if you are sure no other '\n 'bugwarrior processes are currently running.' % (\n lockfile_path\n )\n )\n except RuntimeError as e:\n log.exception(\"Aborted (%s)\" % e)"
},
{
"code": "def label_search(self, key=None, value=None):\n if key is not None:\n key = key.lower()\n if value is not None:\n value = value.lower()\n show_details = True\n if key is None and value is None:\n url = '%s/labels/search' % (self.base)\n show_details = False\n elif key is not None and value is not None:\n url = '%s/labels/search/%s/key/%s/value' % (self.base, key, value)\n elif key is None:\n url = '%s/labels/search/%s/value' % (self.base, value)\n else:\n url = '%s/labels/search/%s/key' % (self.base, key)\n result = self._get(url)\n if len(result) == 0:\n bot.info(\"No labels found.\")\n sys.exit(0)\n bot.info(\"Labels\\n\")\n rows = []\n for l in result: \n if show_details is True:\n entry = [\"%s:%s\" %(l['key'],l['value']),\n \"\\n%s\\n\\n\" %\"\\n\".join(l['containers'])]\n else:\n entry = [\"N=%s\" %len(l['containers']),\n \"%s:%s\" %(l['key'],l['value']) ]\n rows.append(entry)\n bot.table(rows)\n return rows"
},
{
"code": "def force_iterable(f):\n def wrapper(*args, **kwargs):\n r = f(*args, **kwargs)\n if hasattr(r, '__iter__'):\n return r\n else:\n return [r]\n return wrapper"
},
{
"code": "def main():\n args = get_args()\n ret_code = args.target(args)\n _logger.debug('Exiting with code %d', ret_code)\n sys.exit(ret_code)"
},
{
"code": "def lock(fileobj):\n try:\n import fcntl\n except ImportError:\n return False\n else:\n try:\n fcntl.lockf(fileobj, fcntl.LOCK_EX)\n except IOError:\n return False\n else:\n return True"
},
{
"code": "def make_bintree(levels):\n G = nx.DiGraph()\n root = '0'\n G.add_node(root)\n add_children(G, root, levels, 2)\n return G"
},
{
"code": "def set_option(self, optname, value, action=None, optdict=None):\n if optname in self._options_methods or optname in self._bw_options_methods:\n if value:\n try:\n meth = self._options_methods[optname]\n except KeyError:\n meth = self._bw_options_methods[optname]\n warnings.warn(\n \"%s is deprecated, replace it by %s\"\n % (optname, optname.split(\"-\")[0]),\n DeprecationWarning,\n )\n value = utils._check_csv(value)\n if isinstance(value, (list, tuple)):\n for _id in value:\n meth(_id, ignore_unknown=True)\n else:\n meth(value)\n return\n elif optname == \"output-format\":\n self._reporter_name = value\n if self._reporters:\n self._load_reporter()\n try:\n checkers.BaseTokenChecker.set_option(self, optname, value, action, optdict)\n except config.UnsupportedAction:\n print(\"option %s can't be read from config file\" % optname, file=sys.stderr)"
},
{
"code": "def _send_offer_assignment_notification_email(config, user_email, subject, email_body, site_code, task):\n try:\n sailthru_client = get_sailthru_client(site_code)\n except SailthruError:\n logger.exception(\n '[Offer Assignment] A client error occurred while attempting to send a offer assignment notification.'\n ' Message: {message}'.format(message=email_body)\n )\n return None\n email_vars = {\n 'subject': subject,\n 'email_body': email_body,\n }\n try:\n response = sailthru_client.send(\n template=config['templates']['assignment_email'],\n email=user_email,\n _vars=email_vars\n )\n except SailthruClientError:\n logger.exception(\n '[Offer Assignment] A client error occurred while attempting to send a offer assignment notification.'\n ' Message: {message}'.format(message=email_body)\n )\n return None\n if not response.is_ok():\n error = response.get_error()\n logger.error(\n '[Offer Assignment] A {token_error_code} - {token_error_message} error occurred'\n ' while attempting to send a offer assignment notification.'\n ' Message: {message}'.format(\n message=email_body,\n token_error_code=error.get_error_code(),\n token_error_message=error.get_message()\n )\n )\n if can_retry_sailthru_request(error):\n logger.info(\n '[Offer Assignment] An attempt will be made to resend the offer assignment notification.'\n ' Message: {message}'.format(message=email_body)\n )\n schedule_retry(task, config)\n else:\n logger.warning(\n '[Offer Assignment] No further attempts will be made to send the offer assignment notification.'\n ' Failed Message: {message}'.format(message=email_body)\n )\n return response"
},
{
"code": "def migrate(uri: str, archive_uri: str, case_id: str, dry: bool, force: bool):\n scout_client = MongoClient(uri)\n scout_database = scout_client[uri.rsplit('/', 1)[-1]]\n scout_adapter = MongoAdapter(database=scout_database)\n scout_case = scout_adapter.case(case_id)\n if not force and scout_case.get('is_migrated'):\n print(\"case already migrated\")\n return\n archive_client = MongoClient(archive_uri)\n archive_database = archive_client[archive_uri.rsplit('/', 1)[-1]]\n archive_case = archive_database.case.find_one({\n 'owner': scout_case['owner'],\n 'display_name': scout_case['display_name']\n })\n archive_data = archive_info(archive_database, archive_case)\n if dry:\n print(ruamel.yaml.safe_dump(archive_data))\n else:\n pass"
},
{
"code": "def load_disease_term(self, disease_obj):\n LOG.debug(\"Loading disease term %s into database\", disease_obj['_id'])\n try:\n self.disease_term_collection.insert_one(disease_obj)\n except DuplicateKeyError as err:\n raise IntegrityError(\"Disease term %s already exists in database\".format(disease_obj['_id']))\n LOG.debug(\"Disease term saved\")"
},
{
"code": "def get_elliptic_curve(name):\n for curve in get_elliptic_curves():\n if curve.name == name:\n return curve\n raise ValueError(\"unknown curve name\", name)"
},
{
"code": "def subscribe(self):\n self.stream.setsockopt(zmq.UNSUBSCRIBE, '')\n if '' in self.topics:\n self.log.debug(\"Subscribing to: everything\")\n self.stream.setsockopt(zmq.SUBSCRIBE, '')\n else:\n for topic in self.topics:\n self.log.debug(\"Subscribing to: %r\"%(topic))\n self.stream.setsockopt(zmq.SUBSCRIBE, topic)"
},
{
"code": "def _sem_open(name, value=None):\n if value is None:\n handle = pthread.sem_open(ctypes.c_char_p(name), 0)\n else:\n handle = pthread.sem_open(ctypes.c_char_p(name), SEM_OFLAG, SEM_PERM,\n ctypes.c_int(value))\n if handle == SEM_FAILURE:\n e = ctypes.get_errno()\n if e == errno.EEXIST:\n raise FileExistsError(\"a semaphore named %s already exists\" % name)\n elif e == errno.ENOENT:\n raise FileNotFoundError('cannot find semaphore named %s' % name)\n elif e == errno.ENOSYS:\n raise NotImplementedError('No semaphore implementation on this '\n 'system')\n else:\n raiseFromErrno()\n return handle"
},
{
"code": "def parallel(collection, method, processes=None, args=None, **kwargs):\n if processes is None:\n processes = min(mp.cpu_count(), 20)\n print \"Running parallel process on \" + str(processes) + \" cores. :-)\"\n pool = mp.Pool(processes=processes)\n PROC = []\n tic = time.time()\n for main_arg in collection:\n if args is None:\n ARGS = (main_arg,)\n else:\n if isinstance(args, tuple) == False:\n args = (args,)\n ARGS = (main_arg,) + args\n PROC.append(pool.apply_async(method, args=ARGS, kwds=kwargs))\n RES = []\n for p in PROC:\n try:\n RES.append(p.get())\n except Exception as e:\n print \"shit happens...\"\n print e\n RES.append(None)\n pool.close()\n pool.join()\n toc = time.time()\n elapsed = toc - tic\n print \"Elapsed time: %s on %s processes :-)\\n\" % (str(elapsed), str(processes))\n return RES"
},
{
"code": "def uncache_zipdir(path):\n from zipimport import _zip_directory_cache as zdc\n _uncache(path, zdc)\n _uncache(path, sys.path_importer_cache)"
},
{
"code": "def task_create(asana_workspace_id, name, notes, assignee, projects,\n completed, **kwargs):\n put(\"task_create\",\n asana_workspace_id=asana_workspace_id,\n name=name,\n notes=notes,\n assignee=assignee,\n projects=projects,\n completed=completed,\n **kwargs)"
},
{
"code": "def str_to_num(str_value):\n str_value = str(str_value)\n try:\n return int(str_value)\n except ValueError:\n return float(str_value)"
},
{
"code": "def connect(url='https://github.com', token=None):\n gh_session = None\n if url == 'https://github.com':\n gh_session = create_session(token)\n else:\n gh_session = create_enterprise_session(url, token)\n if gh_session is None:\n msg = 'Unable to connect to (%s) with provided token.'\n raise RuntimeError(msg, url)\n logger.info('Connected to: %s', url)\n return gh_session"
},
{
"code": "def generate_project(args):\n src = os.path.join(dirname(abspath(__file__)), 'project')\n project_name = args.get('<project>')\n if not project_name:\n logger.warning('Project name cannot be empty.')\n return\n dst = os.path.join(os.getcwd(), project_name)\n if os.path.isdir(dst):\n logger.warning('Project directory already exists.')\n return\n logger.info('Start generating project files.')\n _mkdir_p(dst)\n for src_dir, sub_dirs, filenames in os.walk(src):\n relative_path = src_dir.split(src)[1].lstrip(os.path.sep)\n dst_dir = os.path.join(dst, relative_path)\n if src != src_dir:\n _mkdir_p(dst_dir)\n for filename in filenames:\n if filename in ['development.py', 'production.py']:\n continue\n src_file = os.path.join(src_dir, filename)\n dst_file = os.path.join(dst_dir, filename)\n if filename.endswith(REWRITE_FILE_EXTS):\n _rewrite_and_copy(src_file, dst_file, project_name)\n else:\n shutil.copy(src_file, dst_file)\n logger.info(\"New: %s\" % dst_file)\n if filename in ['development_sample.py', 'production_sample.py']:\n dst_file = os.path.join(dst_dir, \"%s.py\" % filename.split('_')[0])\n _rewrite_and_copy(src_file, dst_file, project_name)\n logger.info(\"New: %s\" % dst_file)\n logger.info('Finish generating project files.')"
},
{
"code": "def with_ignored_exceptions(self, *ignored_exceptions):\n for exception in ignored_exceptions:\n self._ignored_exceptions = self._ignored_exceptions + (exception,)\n return self"
},
{
"code": "def indented_short_title(self, item):\n r = \"\"\n if hasattr(item, 'get_absolute_url'):\n r = '<input type=\"hidden\" class=\"medialibrary_file_path\" value=\"%s\" />' % item.get_absolute_url()\n editable_class = ''\n if not getattr(item, 'feincms_editable', True):\n editable_class = ' tree-item-not-editable'\n r += '<span id=\"page_marker-%d\" class=\"page_marker%s\" style=\"width: %dpx;\"> </span> ' % (\n item.id, editable_class, 14 + item.level * 18)\n if hasattr(item, 'short_title'):\n r += item.short_title()\n else:\n r += unicode(item)\n return mark_safe(r)"
},
{
"code": "def render_columns(columns, write_borders=True, column_colors=None):\n if column_colors is not None and len(column_colors) != len(columns):\n raise ValueError('Wrong number of column colors')\n widths = [max(len(cell) for cell in column) for column in columns]\n max_column_length = max(len(column) for column in columns)\n result = '\\n'.join(render_row(i, columns, widths, column_colors)\n for i in range(max_column_length))\n if write_borders:\n border = '+%s+' % '|'.join('-' * (w + 2) for w in widths)\n return '%s\\n%s\\n%s' % (border, result, border)\n else:\n return result"
},
{
"code": "def create_database(self, server_name, name, service_objective_id,\n edition=None, collation_name=None,\n max_size_bytes=None):\n _validate_not_none('server_name', server_name)\n _validate_not_none('name', name)\n _validate_not_none('service_objective_id', service_objective_id)\n return self._perform_post(\n self._get_databases_path(server_name),\n _SqlManagementXmlSerializer.create_database_to_xml(\n name, service_objective_id, edition, collation_name,\n max_size_bytes\n )\n )"
},
{
"code": "def xcom_push(\n self,\n key,\n value,\n execution_date=None):\n if execution_date and execution_date < self.execution_date:\n raise ValueError(\n 'execution_date can not be in the past (current '\n 'execution_date is {}; received {})'.format(\n self.execution_date, execution_date))\n XCom.set(\n key=key,\n value=value,\n task_id=self.task_id,\n dag_id=self.dag_id,\n execution_date=execution_date or self.execution_date)"
},
{
"code": "def merged(self, timeslots: 'TimeslotCollection') -> 'TimeslotCollection':\n slots = [Timeslot(slot.interval, slot.channel) for slot in self.timeslots]\n slots.extend([Timeslot(slot.interval, slot.channel) for slot in timeslots.timeslots])\n return TimeslotCollection(*slots)"
},
{
"code": "def concat(*seqs) -> ISeq:\n allseqs = lseq.sequence(itertools.chain(*filter(None, map(to_seq, seqs))))\n if allseqs is None:\n return lseq.EMPTY\n return allseqs"
},
{
"code": "def _set_logger(self, name=None):\n if name is None:\n cls = self.__class__\n name = '%s.%s' % (cls.__module__, cls.__name__)\n self._logger = logging.getLogger(name)"
},
{
"code": "def as_event_description(self):\n description = {\n self.name: {\n 'timestamp': self.time,\n },\n }\n if self.data is not None:\n description[self.name]['data'] = self.data\n return description"
},
{
"code": "def add_element(self, element):\n if isinstance(element, BaseExpression):\n element.set_parent(self._working_fragment)\n self._working_fragment.elements.append(element)\n return self\n else:\n return self.add_operator(element)"
},
{
"code": "def hub_history(self):\n self.session.send(self._query_socket, \"history_request\", content={})\n idents, msg = self.session.recv(self._query_socket, 0)\n if self.debug:\n pprint(msg)\n content = msg['content']\n if content['status'] != 'ok':\n raise self._unwrap_exception(content)\n else:\n return content['history']"
},
{
"code": "def mk_privkeys(num):\n \"make privkeys that support coloring, see utils.cstr\"\n privkeys = []\n assert num <= num_colors\n for i in range(num):\n j = 0\n while True:\n k = sha3(str(j))\n a = privtoaddr(k)\n an = big_endian_to_int(a)\n if an % num_colors == i:\n break\n j += 1\n privkeys.append(k)\n return privkeys"
},
{
"code": "def parse_list(value):\n segments = _QUOTED_SEGMENT_RE.findall(value)\n for segment in segments:\n left, match, right = value.partition(segment)\n value = ''.join([left, match.replace(',', '\\000'), right])\n return [_dequote(x.strip()).replace('\\000', ',')\n for x in value.split(',')]"
},
{
"code": "def index(context):\n LOG.info(\"Running scout delete index\")\n adapter = context.obj['adapter']\n for collection in adapter.db.collection_names():\n adapter.db[collection].drop_indexes()\n LOG.info(\"All indexes deleted\")"
},
{
"code": "def is_valid_filesys(path):\n if os.path.isabs(path) and os.path.isdir(path) and \\\n not os.path.isfile(path):\n return True\n else:\n raise LocalPortValidationError(\n 'Port value %s is not a valid filesystem location' % path\n )"
},
{
"code": "def parse_coordinates(variant, category):\n ref = variant.REF\n if variant.ALT:\n alt = variant.ALT[0]\n if category==\"str\" and not variant.ALT:\n alt = '.'\n chrom_match = CHR_PATTERN.match(variant.CHROM)\n chrom = chrom_match.group(2)\n svtype = variant.INFO.get('SVTYPE')\n if svtype:\n svtype = svtype.lower()\n mate_id = variant.INFO.get('MATEID')\n svlen = variant.INFO.get('SVLEN')\n svend = variant.INFO.get('END')\n snvend = int(variant.end)\n position = int(variant.POS)\n ref_len = len(ref)\n alt_len = len(alt)\n sub_category = get_sub_category(alt_len, ref_len, category, svtype)\n end = get_end(position, alt, category, snvend, svend)\n length = get_length(alt_len, ref_len, category, position, end, svtype, svlen)\n end_chrom = chrom\n if sub_category == 'bnd':\n if ':' in alt:\n match = BND_ALT_PATTERN.match(alt)\n if match:\n other_chrom = match.group(1)\n match = CHR_PATTERN.match(other_chrom)\n end_chrom = match.group(2)\n cytoband_start = get_cytoband_coordinates(chrom, position)\n cytoband_end = get_cytoband_coordinates(end_chrom, end)\n coordinates = {\n 'position': position,\n 'end': end,\n 'length': length,\n 'sub_category': sub_category,\n 'mate_id': mate_id,\n 'cytoband_start': cytoband_start,\n 'cytoband_end': cytoband_end,\n 'end_chrom': end_chrom,\n }\n return coordinates"
},
{
"code": "def get_metadata(path_or_module, metadata_version=None):\n if isinstance(path_or_module, ModuleType):\n try:\n return Installed(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass\n try:\n __import__(path_or_module)\n except ImportError:\n pass\n else:\n try:\n return Installed(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass\n if os.path.isfile(path_or_module):\n try:\n return SDist(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass\n try:\n return BDist(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass\n try:\n return Wheel(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass\n if os.path.isdir(path_or_module):\n try:\n return Develop(path_or_module, metadata_version)\n except (ValueError, IOError):\n pass"
},
{
"code": "def unsubscribe(self, event, callback):\n try:\n self._subscribers[event].remove(self._Subscription(event, callback))\n except KeyError:\n return False\n return True"
},
{
"code": "def to_archive(self, writer):\n if 'b' not in writer.mode:\n raise GiraffeError(\"Archive writer must be in binary mode\")\n writer.write(GIRAFFE_MAGIC)\n writer.write(self.columns.serialize())\n i = 0\n for n, chunk in enumerate(self._fetchall(ROW_ENCODING_RAW), 1):\n writer.write(chunk)\n yield TeradataEncoder.count(chunk)"
},
{
"code": "def flatten(iterables, level=inf):\n if level >= 0 and isinstance(iterables, (list, tuple, GeneratorType,\n map, zip)):\n level -= 1\n for i in iterables:\n yield from flatten(i, level=level)\n else:\n yield iterables"
},
{
"code": "def send(self):\n self._generate_email()\n if self.verbose:\n print(\n \"Debugging info\"\n \"\\n--------------\"\n \"\\n{} Message created.\".format(timestamp())\n )\n recipients = []\n for i in (self.to, self.cc, self.bcc):\n if i:\n if isinstance(i, MutableSequence):\n recipients += i\n else:\n recipients.append(i)\n session = self._get_session()\n if self.verbose:\n print(timestamp(), \"Login successful.\")\n session.sendmail(self.from_, recipients, self.message.as_string())\n session.quit()\n if self.verbose:\n print(timestamp(), \"Logged out.\")\n if self.verbose:\n print(\n timestamp(),\n type(self).__name__ + \" info:\",\n self.__str__(indentation=\"\\n * \"),\n )\n print(\"Message sent.\")"
},
{
"code": "def node(self, title, **args):\n self._stream.write('%snode: {title:\"%s\"' % (self._indent, title))\n self._write_attributes(NODE_ATTRS, **args)\n self._stream.write(\"}\\n\")"
},
{
"code": "def _next_rdelim(items, pos):\n for num, item in enumerate(items):\n if item > pos:\n break\n else:\n raise RuntimeError(\"Mismatched delimiters\")\n del items[num]\n return item"
},
{
"code": "def _extract_base(self, element):\n if isinstance(element, list):\n return [self._extract_base(x) for x in element]\n base = self.checker.is_url_valid(url=element, return_base=True)\n if base:\n return base\n if \"/\" in element:\n return element.split(\"/\")[0]\n return element"
},
{
"code": "def recent(self):\n url = \"{0}/users/ME/conversations\".format(self.skype.conn.msgsHost)\n params = {\"startTime\": 0,\n \"view\": \"msnp24Equivalent\",\n \"targetType\": \"Passport|Skype|Lync|Thread\"}\n resp = self.skype.conn.syncStateCall(\"GET\", url, params, auth=SkypeConnection.Auth.RegToken).json()\n chats = {}\n for json in resp.get(\"conversations\", []):\n cls = SkypeSingleChat\n if \"threadProperties\" in json:\n info = self.skype.conn(\"GET\", \"{0}/threads/{1}\".format(self.skype.conn.msgsHost, json.get(\"id\")),\n auth=SkypeConnection.Auth.RegToken,\n params={\"view\": \"msnp24Equivalent\"}).json()\n json.update(info)\n cls = SkypeGroupChat\n chats[json.get(\"id\")] = self.merge(cls.fromRaw(self.skype, json))\n return chats"
},
{
"code": "def _html_checker(job_var, interval, status, header,\n _interval_set=False):\n job_status = job_var.status()\n job_status_name = job_status.name\n job_status_msg = job_status.value\n status.value = header % (job_status_msg)\n while job_status_name not in ['DONE', 'CANCELLED']:\n time.sleep(interval)\n job_status = job_var.status()\n job_status_name = job_status.name\n job_status_msg = job_status.value\n if job_status_name == 'ERROR':\n break\n else:\n if job_status_name == 'QUEUED':\n job_status_msg += ' (%s)' % job_var.queue_position()\n if not _interval_set:\n interval = max(job_var.queue_position(), 2)\n else:\n if not _interval_set:\n interval = 2\n status.value = header % (job_status_msg)\n status.value = header % (job_status_msg)"
},
{
"code": "def display(self):\n if isinstance(self.name, six.string_types) and len(self.name) > 0:\n return '{0} ({1})'.format(self.name, self.public_ip)\n else:\n return self.public_ip"
},
{
"code": "def parse_conservation(variant, info_key):\n raw_score = variant.INFO.get(info_key)\n conservations = []\n if raw_score:\n if isinstance(raw_score, numbers.Number):\n raw_score = (raw_score,)\n for score in raw_score:\n if score >= CONSERVATION[info_key]['conserved_min']:\n conservations.append('Conserved')\n else:\n conservations.append('NotConserved')\n return conservations"
},
{
"code": "def _asa_task(q, masks, stft, sample_width, frame_rate, nsamples_for_each_fft):\n for mask in masks:\n mask = np.where(mask > 0, 1, 0)\n masks = [mask * stft for mask in masks]\n nparrs = []\n dtype_dict = {1: np.int8, 2: np.int16, 4: np.int32}\n dtype = dtype_dict[sample_width]\n for m in masks:\n _times, nparr = signal.istft(m, frame_rate, nperseg=nsamples_for_each_fft)\n nparr = nparr.astype(dtype)\n nparrs.append(nparr)\n for m in nparrs:\n q.put(m)\n q.put(\"DONE\")"
},
{
"code": "def client_authentication_required(self, request, *args, **kwargs):\n def is_confidential(client):\n if hasattr(client, 'is_confidential'):\n return client.is_confidential\n client_type = getattr(client, 'client_type', None)\n if client_type:\n return client_type == 'confidential'\n return True\n grant_types = ('password', 'authorization_code', 'refresh_token')\n client_id, _ = self._get_client_creds_from_request(request)\n if client_id and request.grant_type in grant_types:\n client = self._clientgetter(client_id)\n if client:\n return is_confidential(client)\n return False"
},
{
"code": "def contains(self, k):\n if self._changed():\n self._read()\n return k in self.store.keys()"
},
{
"code": "def assert_is_type(var, *types, **kwargs):\n assert types, \"The list of expected types was not provided\"\n expected_type = types[0] if len(types) == 1 else U(*types)\n if _check_type(var, expected_type): return\n assert set(kwargs).issubset({\"message\", \"skip_frames\"}), \"Unexpected keyword arguments: %r\" % kwargs\n message = kwargs.get(\"message\", None)\n skip_frames = kwargs.get(\"skip_frames\", 1)\n args = _retrieve_assert_arguments()\n vname = args[0]\n etn = _get_type_name(expected_type, dump=\", \".join(args[1:]))\n vtn = _get_type_name(type(var))\n raise H2OTypeError(var_name=vname, var_value=var, var_type_name=vtn, exp_type_name=etn, message=message,\n skip_frames=skip_frames)"
},
{
"code": "def success(self):\n any_success = False\n for step_event in itertools.chain(\n self.input_expectations, self.output_expectations, self.transforms\n ):\n if step_event.event_type == DagsterEventType.STEP_FAILURE:\n return False\n if step_event.event_type == DagsterEventType.STEP_SUCCESS:\n any_success = True\n return any_success"
},
{
"code": "def session_new(self, **kwargs):\n path = self._get_path('session_new')\n response = self._GET(path, kwargs)\n self._set_attrs_to_values(response)\n return response"
},
{
"code": "def filter_new(self, name, filt_str):\n filt = self.filt.grab_filt(filt=filt_str)\n self.filt.add(name, filt, info=filt_str)\n return"
},
{
"code": "def _observe_mode(self, change):\n block = self.block\n if block and self.is_initialized and change['type'] == 'update':\n if change['oldvalue'] == 'replace':\n raise NotImplementedError\n for c in self.children:\n block.children.remove(c)\n c.set_parent(None)\n self.refresh_items()"
},
{
"code": "def read(self, input_buffer, kmip_version=enums.KMIPVersion.KMIP_1_0):\n super(GetAttributeListResponsePayload, self).read(\n input_buffer,\n kmip_version=kmip_version\n )\n local_buffer = utils.BytearrayStream(input_buffer.read(self.length))\n if self.is_tag_next(enums.Tags.UNIQUE_IDENTIFIER, local_buffer):\n self._unique_identifier = primitives.TextString(\n tag=enums.Tags.UNIQUE_IDENTIFIER\n )\n self._unique_identifier.read(\n local_buffer,\n kmip_version=kmip_version\n )\n else:\n raise exceptions.InvalidKmipEncoding(\n \"The GetAttributeList response payload encoding is missing \"\n \"the unique identifier.\"\n )\n names = list()\n if kmip_version < enums.KMIPVersion.KMIP_2_0:\n while self.is_tag_next(enums.Tags.ATTRIBUTE_NAME, local_buffer):\n name = primitives.TextString(tag=enums.Tags.ATTRIBUTE_NAME)\n name.read(local_buffer, kmip_version=kmip_version)\n names.append(name)\n if len(names) == 0:\n raise exceptions.InvalidKmipEncoding(\n \"The GetAttributeList response payload encoding is \"\n \"missing the attribute names.\"\n )\n self._attribute_names = names\n else:\n while self.is_tag_next(\n enums.Tags.ATTRIBUTE_REFERENCE,\n local_buffer\n ):\n if self.is_type_next(enums.Types.STRUCTURE, local_buffer):\n reference = objects.AttributeReference()\n reference.read(local_buffer, kmip_version=kmip_version)\n names.append(\n primitives.TextString(\n value=reference.attribute_name,\n tag=enums.Tags.ATTRIBUTE_NAME\n )\n )\n elif self.is_type_next(enums.Types.ENUMERATION, local_buffer):\n reference = primitives.Enumeration(\n enums.Tags,\n tag=enums.Tags.ATTRIBUTE_REFERENCE\n )\n reference.read(local_buffer, kmip_version=kmip_version)\n name = enums.convert_attribute_tag_to_name(reference.value)\n names.append(\n primitives.TextString(\n value=name,\n tag=enums.Tags.ATTRIBUTE_NAME\n )\n )\n else:\n raise exceptions.InvalidKmipEncoding(\n \"The GetAttributeList response payload encoding \"\n \"contains an invalid AttributeReference type.\"\n )\n self._attribute_names = names\n self.is_oversized(local_buffer)"
},
{
"code": "def registerAdminSite(appName, excludeModels=[]):\n for model in apps.get_app_config(appName).get_models():\n if model not in excludeModels:\n admin.site.register(model)"
},
{
"code": "def _load_rels(self, source):\n\t\tself.relationships.load(source=self, data=source)"
},
{
"code": "def protocol_version_to_kmip_version(value):\n if not isinstance(value, ProtocolVersion):\n return None\n if value.major == 1:\n if value.minor == 0:\n return enums.KMIPVersion.KMIP_1_0\n elif value.minor == 1:\n return enums.KMIPVersion.KMIP_1_1\n elif value.minor == 2:\n return enums.KMIPVersion.KMIP_1_2\n elif value.minor == 3:\n return enums.KMIPVersion.KMIP_1_3\n elif value.minor == 4:\n return enums.KMIPVersion.KMIP_1_4\n else:\n return None\n else:\n return None"
},
{
"code": "def genes_by_alias(self, build='37', genes=None):\n LOG.info(\"Fetching all genes by alias\")\n alias_genes = {}\n if not genes:\n genes = self.hgnc_collection.find({'build':build})\n for gene in genes:\n hgnc_id = gene['hgnc_id']\n hgnc_symbol = gene['hgnc_symbol']\n for alias in gene['aliases']:\n true_id = None\n if alias == hgnc_symbol:\n true_id = hgnc_id\n if alias in alias_genes:\n alias_genes[alias]['ids'].add(hgnc_id)\n if true_id:\n alias_genes[alias]['true'] = hgnc_id\n else:\n alias_genes[alias] = {\n 'true': hgnc_id,\n 'ids': set([hgnc_id])\n }\n return alias_genes"
},
{
"code": "def _expand_to_event_rank(self, x):\n expanded_x = x\n for _ in range(tensorshape_util.rank(self.event_shape)):\n expanded_x = tf.expand_dims(expanded_x, -1)\n return expanded_x"
},
{
"code": "def start(self):\n if self._collectors:\n self._collectors[-1].pause()\n self._collectors.append(self)\n traces0 = []\n if hasattr(sys, \"gettrace\"):\n fn0 = sys.gettrace()\n if fn0:\n tracer0 = getattr(fn0, '__self__', None)\n if tracer0:\n traces0 = getattr(tracer0, 'traces', [])\n fn = self._start_tracer()\n for args in traces0:\n (frame, event, arg), lineno = args\n try:\n fn(frame, event, arg, lineno=lineno)\n except TypeError:\n raise Exception(\n \"fullcoverage must be run with the C trace function.\"\n )\n threading.settrace(self._installation_trace)"
},
{
"code": "def _has_connection(hostname, port):\n try:\n host = socket.gethostbyname(hostname)\n socket.create_connection((host, port), 2)\n return True\n except Exception:\n return False"
},
{
"code": "def rps_at(self, t):\n if 0 <= t <= self.duration:\n return self.minrps + \\\n float(self.maxrps - self.minrps) * t / self.duration\n else:\n return 0"
},
{
"code": "def get_all_child_m2m_relations(model):\n return [\n field for field in model._meta.get_fields()\n if isinstance(field, ParentalManyToManyField)\n ]"
},
{
"code": "def display_json(*objs, **kwargs):\n raw = kwargs.pop('raw',False)\n if raw:\n for obj in objs:\n publish_json(obj)\n else:\n display(*objs, include=['text/plain','application/json'])"
},
{
"code": "def pick_scalar_condition(pred, true_value, false_value, name=None):\n with tf.name_scope(name or \"pick_scalar_condition\"):\n pred = tf.convert_to_tensor(\n value=pred, dtype_hint=tf.bool, name=\"pred\")\n true_value = tf.convert_to_tensor(value=true_value, name=\"true_value\")\n false_value = tf.convert_to_tensor(value=false_value, name=\"false_value\")\n pred_ = tf.get_static_value(pred)\n if pred_ is None:\n return tf.where(pred, true_value, false_value)\n return true_value if pred_ else false_value"
},
{
"code": "def adapter(data, headers, table_format=None, **kwargs):\n keys = ('title', )\n table = table_format_handler[table_format]\n t = table([headers] + list(data), **filter_dict_by_key(kwargs, keys))\n dimensions = terminaltables.width_and_alignment.max_dimensions(\n t.table_data,\n t.padding_left,\n t.padding_right)[:3]\n for r in t.gen_table(*dimensions):\n yield u''.join(r)"
},
{
"code": "def print_hex(data):\n hex_msg = \"\"\n for c in data:\n hex_msg += \"\\\\x\" + format(c, \"02x\")\n _LOGGER.debug(hex_msg)"
},
{
"code": "def fetch(self, category=CATEGORY_BUILD):\n kwargs = {}\n items = super().fetch(category, **kwargs)\n return items"
},
{
"code": "def _status_new(self):\n self._update_status()\n new_comp = self._group_report(self._comp_report, 'Completed')\n new_dead = self._group_report(self._dead_report,\n 'Dead, call jobs.traceback() for details')\n self._comp_report[:] = []\n self._dead_report[:] = []\n return new_comp or new_dead"
},
{
"code": "def encode(self):\n header = bytearray(1)\n varHeader = bytearray()\n payload = bytearray()\n if self.qos:\n header[0] = 0x30 | self.retain | (self.qos << 1) | (self.dup << 3)\n varHeader.extend(encodeString(self.topic))\n varHeader.extend(encode16Int(self.msgId))\n else:\n header[0] = 0x30 | self.retain\n varHeader.extend(encodeString(self.topic))\n if isinstance(self.payload, bytearray):\n payload.extend(self.payload)\n elif isinstance(self.payload, str):\n payload.extend(bytearray(self.payload, encoding='utf-8'))\n else:\n raise PayloadTypeError(type(self.payload))\n totalLen = len(varHeader) + len(payload)\n if totalLen > 268435455:\n raise PayloadValueError(totalLen)\n header.extend(encodeLength(totalLen))\n header.extend(varHeader)\n header.extend(payload)\n self.encoded = header\n return str(header) if PY2 else bytes(header)"
},
{
"code": "def symmetrized_csiszar_function(logu, csiszar_function, name=None):\n with tf.compat.v1.name_scope(name, \"symmetrized_csiszar_function\", [logu]):\n logu = tf.convert_to_tensor(value=logu, name=\"logu\")\n return 0.5 * (csiszar_function(logu)\n + dual_csiszar_function(logu, csiszar_function))"
},
{
"code": "def get_engine(scheme):\n path = scheme.split(\"+\")\n first, rest = path[0], path[1:]\n second = rest[0] if rest else None\n engine = resolve(ENGINE_MAPPING, first)\n if not isinstance(engine, list):\n if second:\n raise KeyError(\"%s has no sub-engines\" % first)\n return engine\n try:\n engine, extra = engine\n except ValueError:\n raise ValueError(\n \"django-bananas.url' engine \"\n \"configuration is invalid: %r\" % ENGINE_MAPPING\n )\n if second is not None:\n engine = resolve(extra, second)\n assert not isinstance(\n engine, (list, dict)\n ), \"Only two levels of engines \" \"are allowed\"\n assert engine, \"The returned engine is not truthy\"\n return engine"
},
{
"code": "def export_to_storage_bucket(self, bucket, namespace=None, entity_filter=None, labels=None):\n admin_conn = self.get_conn()\n output_uri_prefix = 'gs://' + '/'.join(filter(None, [bucket, namespace]))\n if not entity_filter:\n entity_filter = {}\n if not labels:\n labels = {}\n body = {\n 'outputUrlPrefix': output_uri_prefix,\n 'entityFilter': entity_filter,\n 'labels': labels,\n }\n resp = (admin_conn\n .projects()\n .export(projectId=self.project_id, body=body)\n .execute(num_retries=self.num_retries))\n return resp"
},
{
"code": "def build_package_from_pr_number(gh_token, sdk_id, pr_number, output_folder, *, with_comment=False):\n con = Github(gh_token)\n repo = con.get_repo(sdk_id)\n sdk_pr = repo.get_pull(pr_number)\n package_names = {f.filename.split('/')[0] for f in sdk_pr.get_files() if f.filename.startswith(\"azure\")}\n absolute_output_folder = Path(output_folder).resolve()\n with tempfile.TemporaryDirectory() as temp_dir, \\\n manage_git_folder(gh_token, Path(temp_dir) / Path(\"sdk\"), sdk_id, pr_number=pr_number) as sdk_folder:\n for package_name in package_names:\n _LOGGER.debug(\"Build {}\".format(package_name))\n execute_simple_command(\n [\"python\", \"./build_package.py\", \"--dest\", str(absolute_output_folder), package_name],\n cwd=sdk_folder\n )\n _LOGGER.debug(\"Build finished: {}\".format(package_name))\n if with_comment:\n files = [f.name for f in absolute_output_folder.iterdir()]\n comment_message = None\n dashboard = DashboardCommentableObject(sdk_pr, \"(message created by the CI based on PR content)\")\n try:\n installation_message = build_installation_message(sdk_pr)\n download_message = build_download_message(sdk_pr, files)\n comment_message = installation_message + \"\\n\\n\" + download_message\n dashboard.create_comment(comment_message)\n except Exception:\n _LOGGER.critical(\"Unable to do PR comment:\\n%s\", comment_message)"
},
{
"code": "def verbose(self, msg, *args, **kwargs):\n self.log(logging.VERBOSE, msg, *args, **kwargs)"
},
{
"code": "def set_value(self, value):\n self.validate_value(value)\n self.value.set(value)"
},
{
"code": "def remoteDataReceived(self, connection, data):\n proto = self.getLocalProtocol(connection)\n proto.transport.write(data)\n return {}"
},
{
"code": "def create_validator(data_struct_dict, name=None):\n if name is None:\n name = 'FromDictValidator'\n attrs = {}\n for field_name, field_info in six.iteritems(data_struct_dict):\n field_type = field_info['type']\n if field_type == DictField.FIELD_TYPE_NAME and isinstance(field_info.get('validator'), dict):\n field_info['validator'] = create_validator(field_info['validator'])\n attrs[field_name] = create_field(field_info)\n name = force_str(name)\n return type(name, (Validator, ), attrs)"
},
{
"code": "def get_branch_mutation_matrix(self, node, full_sequence=False):\n pp,pc = self.marginal_branch_profile(node)\n expQt = self.gtr.expQt(self._branch_length_to_gtr(node))\n if len(expQt.shape)==3:\n mut_matrix_stack = np.einsum('ai,aj,ija->aij', pc, pp, expQt)\n else:\n mut_matrix_stack = np.einsum('ai,aj,ij->aij', pc, pp, expQt)\n normalizer = mut_matrix_stack.sum(axis=2).sum(axis=1)\n mut_matrix_stack = np.einsum('aij,a->aij', mut_matrix_stack, 1.0/normalizer)\n if full_sequence:\n return mut_matrix_stack[self.full_to_reduced_sequence_map]\n else:\n return mut_matrix_stack"
},
{
"code": "def get_window(window, Nx, fftbins=True):\n if six.callable(window):\n return window(Nx)\n elif (isinstance(window, (six.string_types, tuple)) or\n np.isscalar(window)):\n return scipy.signal.get_window(window, Nx, fftbins=fftbins)\n elif isinstance(window, (np.ndarray, list)):\n if len(window) == Nx:\n return np.asarray(window)\n raise ParameterError('Window size mismatch: '\n '{:d} != {:d}'.format(len(window), Nx))\n else:\n raise ParameterError('Invalid window specification: {}'.format(window))"
},
{
"code": "def convert_to_this_nbformat(nb, orig_version=2, orig_minor=0):\n if orig_version == 1:\n nb = v2.convert_to_this_nbformat(nb)\n orig_version = 2\n if orig_version == 2:\n nb.nbformat = nbformat\n nb.nbformat_minor = nbformat_minor\n nb.orig_nbformat = 2\n return nb\n elif orig_version == 3:\n if orig_minor != nbformat_minor:\n nb.orig_nbformat_minor = orig_minor\n nb.nbformat_minor = nbformat_minor\n return nb\n else:\n raise ValueError('Cannot convert a notebook from v%s to v3' % orig_version)"
},
{
"code": "def sync_folder(self, path, bucket):\n bucket = self.conn.get_bucket(bucket)\n local_files = self._get_local_files(path)\n s3_files = self._get_s3_files(bucket)\n for filename, hash in local_files.iteritems():\n s3_key = s3_files[filename]\n if s3_key is None:\n s3_key = Key(bucket)\n s3_key.key = filename\n s3_key.etag = '\"!\"'\n if s3_key.etag[1:-1] != hash[0]:\n s3_key.set_contents_from_filename(join(path, filename), md5=hash)"
},
{
"code": "def wrap_class(cls, error_threshold=None):\n methods = inspect.getmembers(cls, inspect.ismethod) + inspect.getmembers(cls, inspect.isfunction)\n for method_name, method in methods:\n wrapped_method = flawless.client.client._wrap_function_with_error_decorator(\n method if not im_self(method) else im_func(method),\n save_current_stack_trace=False,\n error_threshold=error_threshold,\n )\n if im_self(method):\n wrapped_method = classmethod(wrapped_method)\n setattr(cls, method_name, wrapped_method)\n return cls"
},
{
"code": "def check_type(self, value, attr, data):\n root_value = super(InstructionParameter, self).check_type(\n value, attr, data)\n if is_collection(value):\n _ = [super(InstructionParameter, self).check_type(item, attr, data)\n for item in value]\n return root_value"
},
{
"code": "def _batch_gather_with_broadcast(params, indices, axis):\n leading_bcast_shape = tf.broadcast_dynamic_shape(\n tf.shape(input=params)[:axis],\n tf.shape(input=indices)[:-1])\n params += tf.zeros(\n tf.concat((leading_bcast_shape, tf.shape(input=params)[axis:]), axis=0),\n dtype=params.dtype)\n indices += tf.zeros(\n tf.concat((leading_bcast_shape, tf.shape(input=indices)[-1:]), axis=0),\n dtype=indices.dtype)\n return tf.compat.v1.batch_gather(params, indices)"
},
{
"code": "def establish(self, call_id, timeout, limit=None,\n retry=None, max_retries=None):\n rejected = 0\n retried = 0\n results = []\n result_queue = self.result_queues[call_id]\n try:\n with Timeout(timeout, False):\n while True:\n result = result_queue.get()\n if result is None:\n rejected += 1\n if retry is not None:\n if retried == max_retries:\n break\n retry()\n retried += 1\n continue\n results.append(result)\n if len(results) == limit:\n break\n finally:\n del result_queue\n self.remove_result_queue(call_id)\n if not results:\n if rejected:\n raise Rejected('%d workers rejected' % rejected\n if rejected != 1 else\n 'A worker rejected')\n else:\n raise WorkerNotFound('failed to find worker')\n return results"
},
{
"code": "def slicify(slc, dim):\n if isinstance(slc, slice):\n start = 0 if slc.start is None else slc.start\n stop = dim if slc.stop is None else slc.stop\n step = 1 if slc.step is None else slc.step\n if start < 0: start += dim\n if stop < 0: stop += dim\n if step > 0:\n if start < 0: start = 0\n if stop > dim: stop = dim\n else:\n if stop < 0: stop = -1\n if start > dim: start = dim-1\n return slice(start, stop, step)\n elif isinstance(slc, int):\n if slc < 0:\n slc += dim\n return slice(slc, slc+1, 1)\n else:\n raise ValueError(\"Type for slice %s not recongized\" % type(slc))"
},
{
"code": "def enable_gtk(self, app=None):\n import gtk\n try:\n gtk.set_interactive(True)\n self._current_gui = GUI_GTK\n except AttributeError:\n from IPython.lib.inputhookgtk import inputhook_gtk\n self.set_inputhook(inputhook_gtk)\n self._current_gui = GUI_GTK"
},
{
"code": "def overlapping(self, variant_obj):\n category = 'snv' if variant_obj['category'] == 'sv' else 'sv'\n query = {\n '$and': [\n {'case_id': variant_obj['case_id']},\n {'category': category},\n {'hgnc_ids' : { '$in' : variant_obj['hgnc_ids']}}\n ]\n }\n sort_key = [('rank_score', pymongo.DESCENDING)]\n variants = self.variant_collection.find(query).sort(sort_key).limit(30)\n return variants"
},
{
"code": "def convert_camel_case(name):\n s1 = re.sub('(.)([A-Z][a-z]+)', r'\\1_\\2', name)\n return re.sub('([a-z0-9])([A-Z])', r'\\1_\\2', s1).lower()"
},
{
"code": "def incpos(self, length: int=1) -> int:\n if length < 0:\n raise ValueError(\"length must be positive\")\n i = 0\n while (i < length):\n if self._cursor.index < self._len:\n if self.peek_char == '\\n':\n self._cursor.step_next_line()\n self._cursor.step_next_char()\n i += 1\n return self._cursor.index"
},
{
"code": "def cache(func):\n CACHE_DIR = appdirs.user_cache_dir('sportsref', getpass.getuser())\n if not os.path.isdir(CACHE_DIR):\n os.makedirs(CACHE_DIR)\n @funcutils.wraps(func)\n def wrapper(url):\n file_hash = hashlib.md5()\n encoded_url = url.encode(errors='replace')\n file_hash.update(encoded_url)\n file_hash = file_hash.hexdigest()\n filename = '{}/{}'.format(CACHE_DIR, file_hash)\n sport_id = None\n for a_base_url, a_sport_id in sportsref.SITE_ABBREV.items():\n if url.startswith(a_base_url):\n sport_id = a_sport_id\n break\n else:\n print('No sport ID found for {}, not able to check cache'.format(url))\n file_exists = os.path.isfile(filename)\n if sport_id and file_exists:\n cur_time = int(time.time())\n mod_time = int(os.path.getmtime(filename))\n days_since_mod = datetime.timedelta(seconds=(cur_time - mod_time)).days\n days_cache_valid = globals()['_days_valid_{}'.format(sport_id)](url)\n cache_is_valid = days_since_mod < days_cache_valid\n else:\n cache_is_valid = False\n allow_caching = sportsref.get_option('cache')\n if file_exists and cache_is_valid and allow_caching:\n with codecs.open(filename, 'r', encoding='utf-8', errors='replace') as f:\n text = f.read()\n else:\n text = func(url)\n with codecs.open(filename, 'w+', encoding='utf-8') as f:\n f.write(text)\n return text\n return wrapper"
},
{
"code": "def onTWriteCallback__init(self, sim):\n yield from self.onTWriteCallback(sim)\n self.intf.t._sigInside.registerWriteCallback(\n self.onTWriteCallback,\n self.getEnable)\n self.intf.o._sigInside.registerWriteCallback(\n self.onTWriteCallback,\n self.getEnable)"
},
{
"code": "def delims(self, delims):\n expr = '[' + ''.join('\\\\'+ c for c in delims) + ']'\n self._delim_re = re.compile(expr)\n self._delims = delims\n self._delim_expr = expr"
},
{
"code": "def ALL_mentions(target_mentions, chain_mentions):\n found_all = True\n for name in target_mentions:\n found_one = False\n for chain_ment in chain_mentions:\n if name in chain_ment:\n found_one = True\n break\n if not found_one:\n found_all = False\n break\n return found_all"
},
{
"code": "def execute(self, obj):\n try:\n if self.config.stdin:\n self.spawn(self.config.command, stdin_content=obj, stdin=True, timeout=1)\n else:\n if \"@@\" not in self.config.command:\n raise PJFMissingArgument(\"Missing @@ filename indicator while using non-stdin fuzzing method\")\n for x in self.config.command:\n if \"@@\" in x:\n self.config.command[self.config.command.index(x)] = x.replace(\"@@\", obj)\n self.spawn(self.config.command, timeout=2)\n self.logger.debug(\"[{0}] - PJFExternalFuzzer successfully completed\".format(time.strftime(\"%H:%M:%S\")))\n return self._out\n except KeyboardInterrupt:\n return \"\"\n except Exception as e:\n raise PJFBaseException(e.message if hasattr(e, \"message\") else str(e))"
},
{
"code": "def can_cut(self):\n cursor = self._control.textCursor()\n return (cursor.hasSelection() and\n self._in_buffer(cursor.anchor()) and\n self._in_buffer(cursor.position()))"
},
{
"code": "def get_importer(path_item):\n try:\n importer = sys.path_importer_cache[path_item]\n except KeyError:\n for hook in sys.path_hooks:\n try:\n importer = hook(path_item)\n except ImportError:\n pass\n else:\n break\n else:\n importer = None\n sys.path_importer_cache.setdefault(path_item,importer)\n if importer is None:\n try:\n importer = ImpWrapper(path_item)\n except ImportError:\n pass\n return importer"
},
{
"code": "def create_resized_image(self, path_to_image, save_path_on_storage,\n width, height):\n image, file_ext, image_format, mime_type = self.retrieve_image(\n path_to_image\n )\n image, save_kwargs = self.preprocess(image, image_format)\n imagefile = self.process_image(\n image=image,\n image_format=image_format,\n save_kwargs=save_kwargs,\n width=width,\n height=height\n )\n self.save_image(imagefile, save_path_on_storage, file_ext, mime_type)"
},
{
"code": "def predict_on_stream(config: Union[str, Path, dict], batch_size: int = 1, file_path: Optional[str] = None) -> None:\n if file_path is None or file_path == '-':\n if sys.stdin.isatty():\n raise RuntimeError('To process data from terminal please use interact mode')\n f = sys.stdin\n else:\n f = open(file_path, encoding='utf8')\n model: Chainer = build_model(config)\n args_count = len(model.in_x)\n while True:\n batch = list((l.strip() for l in islice(f, batch_size * args_count)))\n if not batch:\n break\n args = []\n for i in range(args_count):\n args.append(batch[i::args_count])\n res = model(*args)\n if len(model.out_params) == 1:\n res = [res]\n for res in zip(*res):\n res = json.dumps(res, ensure_ascii=False)\n print(res, flush=True)\n if f is not sys.stdin:\n f.close()"
},
{
"code": "def paths(input_dir):\n 'yield all file paths under input_dir'\n for root, dirs, fnames in os.walk(input_dir):\n for i_fname in fnames:\n i_path = os.path.join(root, i_fname)\n yield i_path"
},
{
"code": "def evaluate_min_coverage(coverage_opt, assembly_coverage, assembly_size):\n if coverage_opt == \"auto\":\n min_coverage = (assembly_coverage / assembly_size) * .3\n logger.info(\"Minimum assembly coverage automatically set to: \"\n \"{}\".format(min_coverage))\n if min_coverage < 10:\n logger.info(\"Minimum assembly coverage cannot be set to lower\"\n \" that 10. Setting to 10\")\n min_coverage = 10\n else:\n min_coverage = int(coverage_opt)\n logger.info(\"Minimum assembly coverage manually set to: {}\".format(\n min_coverage))\n return min_coverage"
},
{
"code": "def dbgr(self, string):\n print('')\n self.proc.cmd_queue.append(string)\n self.proc.process_command()\n return"
},
{
"code": "def register(self, contract):\n \"registers NativeContract classes\"\n assert issubclass(contract, NativeContractBase)\n assert len(contract.address) == 20\n assert contract.address.startswith(self.native_contract_address_prefix)\n if self.native_contracts.get(contract.address) == contract._on_msg:\n log.debug(\"already registered\", contract=contract, address=contract.address)\n return\n assert contract.address not in self.native_contracts, 'address already taken'\n self.native_contracts[contract.address] = contract._on_msg\n log.debug(\"registered native contract\", contract=contract, address=contract.address)"
},
{
"code": "def assert_no_title(self, title, **kwargs):\n query = TitleQuery(title, **kwargs)\n @self.synchronize(wait=query.wait)\n def assert_no_title():\n if query.resolves_for(self):\n raise ExpectationNotMet(query.negative_failure_message)\n return True\n return assert_no_title()"
},
{
"code": "def IsNotNone(*fields, default=None):\n when_clauses = [\n expressions.When(\n ~expressions.Q(**{field: None}),\n then=expressions.F(field)\n )\n for field in reversed(fields)\n ]\n return expressions.Case(\n *when_clauses,\n default=expressions.Value(default),\n output_field=CharField()\n )"
},
{
"code": "def jenkins_request_with_headers(jenkins_server, req):\n try:\n response = jenkins_server.jenkins_request(req)\n response_body = response.content\n response_headers = response.headers\n if response_body is None:\n raise jenkins.EmptyResponseException(\n \"Error communicating with server[%s]: \"\n \"empty response\" % jenkins_server.server)\n return {'body': response_body.decode('utf-8'), 'headers': response_headers}\n except HTTPError as e:\n if e.code in [401, 403, 500]:\n raise JenkinsException(\n 'Error in request. ' +\n 'Possibly authentication failed [%s]: %s' % (\n e.code, e.msg)\n )\n elif e.code == 404:\n raise jenkins.NotFoundException('Requested item could not be found')\n else:\n raise\n except socket.timeout as e:\n raise jenkins.TimeoutException('Error in request: %s' % e)\n except URLError as e:\n if str(e.reason) == \"timed out\":\n raise jenkins.TimeoutException('Error in request: %s' % e.reason)\n raise JenkinsException('Error in request: %s' % e.reason)"
},
{
"code": "def _left_doubling_increments(batch_shape, max_doublings, step_size, seed=None,\n name=None):\n with tf.compat.v1.name_scope(name, 'left_doubling_increments',\n [batch_shape, max_doublings, step_size]):\n step_size = tf.convert_to_tensor(value=step_size)\n dtype = step_size.dtype.base_dtype\n output_shape = tf.concat(([max_doublings + 1], batch_shape), axis=0)\n expand_left = distributions.Bernoulli(0.5, dtype=dtype).sample(\n sample_shape=output_shape, seed=seed)\n width_multipliers = tf.cast(2 ** tf.range(0, max_doublings+1), dtype=dtype)\n widths_shape = tf.concat(([max_doublings + 1],\n tf.ones_like(batch_shape)), axis=0)\n width_multipliers = tf.reshape(width_multipliers, shape=widths_shape)\n widths = width_multipliers * step_size\n left_increments = tf.cumsum(widths * expand_left, exclusive=True, axis=0)\n return left_increments, widths"
},
{
"code": "def _joint_sample_n(self, n, seed=None):\n with tf.name_scope(\"sample_n_joint\"):\n stream = seed_stream.SeedStream(\n seed, salt=\"LinearGaussianStateSpaceModel_sample_n_joint\")\n sample_and_batch_shape = distribution_util.prefer_static_value(\n tf.concat([[n], self.batch_shape_tensor()],\n axis=0))\n with tf.control_dependencies(self.runtime_assertions):\n initial_latent = self.initial_state_prior.sample(\n sample_shape=_augment_sample_shape(\n self.initial_state_prior,\n sample_and_batch_shape,\n self.validate_args),\n seed=stream())\n initial_latent = initial_latent[..., tf.newaxis]\n initial_observation_matrix = (\n self.get_observation_matrix_for_timestep(self.initial_step))\n initial_observation_noise = (\n self.get_observation_noise_for_timestep(self.initial_step))\n initial_observation_pred = initial_observation_matrix.matmul(\n initial_latent)\n initial_observation = (initial_observation_pred +\n initial_observation_noise.sample(\n sample_shape=_augment_sample_shape(\n initial_observation_noise,\n sample_and_batch_shape,\n self.validate_args),\n seed=stream())[..., tf.newaxis])\n sample_step = build_kalman_sample_step(\n self.get_transition_matrix_for_timestep,\n self.get_transition_noise_for_timestep,\n self.get_observation_matrix_for_timestep,\n self.get_observation_noise_for_timestep,\n full_sample_and_batch_shape=sample_and_batch_shape,\n stream=stream,\n validate_args=self.validate_args)\n (latents, observations) = tf.scan(\n sample_step,\n elems=tf.range(self.initial_step+1, self.final_step),\n initializer=(initial_latent, initial_observation))\n latents = tf.concat([initial_latent[tf.newaxis, ...],\n latents], axis=0)\n observations = tf.concat([initial_observation[tf.newaxis, ...],\n observations], axis=0)\n latents = tf.squeeze(latents, -1)\n latents = distribution_util.move_dimension(latents, 0, -2)\n observations = tf.squeeze(observations, -1)\n observations = distribution_util.move_dimension(observations, 0, -2)\n return latents, observations"
},
{
"code": "def simple_attention(memory, att_size, mask, keep_prob=1.0, scope=\"simple_attention\"):\n with tf.variable_scope(scope):\n BS, ML, MH = tf.unstack(tf.shape(memory))\n memory_do = tf.nn.dropout(memory, keep_prob=keep_prob, noise_shape=[BS, 1, MH])\n logits = tf.layers.dense(tf.layers.dense(memory_do, att_size, activation=tf.nn.tanh), 1, use_bias=False)\n logits = softmax_mask(tf.squeeze(logits, [2]), mask)\n att_weights = tf.expand_dims(tf.nn.softmax(logits), axis=2)\n res = tf.reduce_sum(att_weights * memory, axis=1)\n return res"
},
{
"code": "def _dump_text(self):\n results = self._relay_output['result'];\n for l in results:\n dt = time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime(int(l[1]['ts'])))\n print(\"{0} {1} {2} {3}\".format(l[0], dt, l[1]['type'], l[1]['msg']))"
},
{
"code": "def get_ip_address_info(ip_address, cache=None, nameservers=None,\n timeout=2.0, parallel=False):\n ip_address = ip_address.lower()\n if cache:\n info = cache.get(ip_address, None)\n if info:\n return info\n info = OrderedDict()\n info[\"ip_address\"] = ip_address\n reverse_dns = get_reverse_dns(ip_address,\n nameservers=nameservers,\n timeout=timeout)\n country = get_ip_address_country(ip_address, parallel=parallel)\n info[\"country\"] = country\n info[\"reverse_dns\"] = reverse_dns\n info[\"base_domain\"] = None\n if reverse_dns is not None:\n base_domain = get_base_domain(reverse_dns)\n info[\"base_domain\"] = base_domain\n return info"
},
{
"code": "def _explore(self, explore_iterable):\n if self.v_locked:\n raise pex.ParameterLockedException('Parameter `%s` is locked!' % self.v_full_name)\n if self.f_has_range():\n raise TypeError('Your parameter `%s` is already explored, '\n 'cannot _explore it further!' % self._name)\n if self._data is None:\n raise TypeError('Your parameter `%s` has no default value, please specify one '\n 'via `f_set` before exploration. ' % self.v_full_name)\n data_list = self._data_sanity_checks(explore_iterable)\n self._explored_range = data_list\n self._explored = True\n self.f_lock()"
},
{
"code": "async def fetch(self) -> Response:\n if self.request_config.get('DELAY', 0) > 0:\n await asyncio.sleep(self.request_config['DELAY'])\n timeout = self.request_config.get('TIMEOUT', 10)\n try:\n async with async_timeout.timeout(timeout):\n resp = await self._make_request()\n try:\n resp_data = await resp.text(encoding=self.encoding)\n except UnicodeDecodeError:\n resp_data = await resp.read()\n response = Response(\n url=self.url,\n method=self.method,\n encoding=resp.get_encoding(),\n html=resp_data,\n metadata=self.metadata,\n cookies=resp.cookies,\n headers=resp.headers,\n history=resp.history,\n status=resp.status,\n aws_json=resp.json,\n aws_text=resp.text,\n aws_read=resp.read)\n aws_valid_response = self.request_config.get('VALID')\n if aws_valid_response and iscoroutinefunction(aws_valid_response):\n response = await aws_valid_response(response)\n if response.ok:\n return response\n else:\n return await self._retry(error_msg='request url failed!')\n except asyncio.TimeoutError:\n return await self._retry(error_msg='timeout')\n except Exception as e:\n return await self._retry(error_msg=e)\n finally:\n await self._close_request_session()"
},
{
"code": "def _prm_read_dictionary(self, leaf, full_name):\n try:\n temp_table = self._prm_read_table(leaf, full_name)\n temp_dict = temp_table.to_dict('list')\n innder_dict = {}\n for innerkey, vallist in temp_dict.items():\n innder_dict[innerkey] = vallist[0]\n return innder_dict\n except:\n self._logger.error('Failed loading `%s` of `%s`.' % (leaf._v_name, full_name))\n raise"
},
{
"code": "def _validate_value(key, value, expected_type):\n if not isinstance(value, expected_type):\n raise TypeError(\"{} argument must have a type {} not {}\".format(\n key, expected_type, type(value)))"
},
{
"code": "def unified_file(self):\n if (\n \"file_to_test\" in PyFunceble.INTERN\n and PyFunceble.INTERN[\"file_to_test\"]\n and PyFunceble.CONFIGURATION[\"unified\"]\n ):\n output = (\n self.output_parent_dir + PyFunceble.OUTPUTS[\"default_files\"][\"results\"]\n )\n if PyFunceble.CONFIGURATION[\"less\"]:\n if PyFunceble.HTTP_CODE[\"active\"]:\n to_print = [\n self.tested,\n self.domain_status,\n PyFunceble.INTERN[\"http_code\"],\n ]\n else:\n to_print = [self.tested, self.domain_status, self.source]\n Prints(to_print, \"Less\", output, True).data()\n else:\n to_print = [\n self.tested,\n self.domain_status,\n self.expiration_date,\n self.source,\n PyFunceble.INTERN[\"http_code\"],\n PyFunceble.CURRENT_TIME,\n ]\n Prints(to_print, \"Generic_File\", output, True).data()"
},
{
"code": "def print_table(language):\n table = translation_table(language)\n for code, name in sorted(table.items(), key=operator.itemgetter(0)):\n print(u'{language:<8} {name:\\u3000<20}'.format(\n name=name, language=code\n ))\n return None"
},
{
"code": "def yzy_to_zyz(xi, theta1, theta2, eps=1e-9):\n quaternion_yzy = quaternion_from_euler([theta1, xi, theta2], 'yzy')\n euler = quaternion_yzy.to_zyz()\n quaternion_zyz = quaternion_from_euler(euler, 'zyz')\n out_angles = (euler[1], euler[0], euler[2])\n abs_inner = abs(quaternion_zyz.data.dot(quaternion_yzy.data))\n if not np.allclose(abs_inner, 1, eps):\n raise TranspilerError('YZY and ZYZ angles do not give same rotation matrix.')\n out_angles = tuple(0 if np.abs(angle) < _CHOP_THRESHOLD else angle\n for angle in out_angles)\n return out_angles"
},
{
"code": "def select_lasso(self, expression_x, expression_y, xsequence, ysequence, mode=\"replace\", name=\"default\", executor=None):\n def create(current):\n return selections.SelectionLasso(expression_x, expression_y, xsequence, ysequence, current, mode)\n self._selection(create, name, executor=executor)"
},
{
"code": "def resize_to(self, width, height):\n self.driver.resize_window_to(self.handle, width, height)"
},
{
"code": "def merge(self, new_dict):\n actions = new_dict.pop(\"actions\")\n for action in actions:\n self.add_action(action)\n self.__dict__.update(new_dict)"
},
{
"code": "def _run_writers(self, start_count, next_idx, sources, i_str, t_path):\n name_info = dict(\n first=start_count,\n source=sources.pop(),\n )\n all_o_paths = []\n for writer in self.writers:\n logger.debug('running %r on %r: %r', writer, i_str, name_info)\n o_paths = writer(t_path, name_info, i_str)\n logger.debug('loaded (%d, %d) of %r into %r',\n start_count, next_idx - 1, i_str, o_paths)\n all_o_paths += o_paths\n return all_o_paths"
},
{
"code": "def _height_is_big_enough(image, height):\n if height > image.size[1]:\n raise ImageSizeError(image.size[1], height)"
},
{
"code": "def add_enrichr_parser(subparsers):\n argparser_enrichr = subparsers.add_parser(\"enrichr\", help=\"Using Enrichr API to perform GO analysis.\")\n enrichr_opt = argparser_enrichr.add_argument_group(\"Input arguments\")\n enrichr_opt.add_argument(\"-i\", \"--input-list\", action=\"store\", dest=\"gene_list\", type=str, required=True, metavar='IDs',\n help=\"Enrichr uses a list of gene names as input.\")\n enrichr_opt.add_argument(\"-g\", \"--gene-sets\", action=\"store\", dest=\"library\", type=str, required=True, metavar='GMT',\n help=\"Enrichr library name(s) required. Separate each name by comma.\")\n enrichr_opt.add_argument(\"--org\", \"--organism\", action=\"store\", dest=\"organism\", type=str, default='',\n help=\"Enrichr supported organism name. Default: human. See here: https://amp.pharm.mssm.edu/modEnrichr.\")\n enrichr_opt.add_argument(\"--ds\", \"--description\", action=\"store\", dest=\"descrip\", type=str, default='enrichr', metavar='STRING',\n help=\"It is recommended to enter a short description for your list so that multiple lists \\\n can be differentiated from each other if you choose to save or share your list.\")\n enrichr_opt.add_argument(\"--cut\", \"--cut-off\", action=\"store\", dest=\"thresh\", metavar='float', type=float, default=0.05,\n help=\"Adjust-Pval cutoff, used for generating plots. Default: 0.05.\")\n enrichr_opt.add_argument(\"--bg\", \"--background\", action=\"store\", dest=\"bg\", default='hsapiens_gene_ensembl', metavar='BGNUM',\n help=\"BioMart Dataset name or Background total genes number. Default: None\")\n enrichr_opt.add_argument(\"-t\", \"--top-term\", dest=\"term\", action=\"store\", type=int, default=10, metavar='int',\n help=\"Numbers of top terms shown in the plot. Default: 10\")\n enrichr_output = argparser_enrichr.add_argument_group(\"Output figure arguments\")\n add_output_option(enrichr_output)\n return"
},
{
"code": "def strval(node, outermost=True):\n if not isinstance(node, element):\n return node.xml_value if outermost else [node.xml_value]\n accumulator = []\n for child in node.xml_children:\n if isinstance(child, text):\n accumulator.append(child.xml_value)\n elif isinstance(child, element):\n accumulator.extend(strval(child, outermost=False))\n if outermost: accumulator = ''.join(accumulator)\n return accumulator"
},
{
"code": "def write(self, output_stream, kmip_version=enums.KMIPVersion.KMIP_1_0):\n local_stream = utils.BytearrayStream()\n if self._unique_identifier:\n self._unique_identifier.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._usage_limits_count:\n self._usage_limits_count.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._cryptographic_usage_mask:\n self._cryptographic_usage_mask.write(\n local_stream,\n kmip_version=kmip_version\n )\n if self._lease_time:\n self._lease_time.write(\n local_stream,\n kmip_version=kmip_version\n )\n self.length = local_stream.length()\n super(CheckResponsePayload, self).write(\n output_stream,\n kmip_version=kmip_version\n )\n output_stream.write(local_stream.buffer)"
},
{
"code": "def apply_operation_back(self, op, qargs=None, cargs=None, condition=None):\n qargs = qargs or []\n cargs = cargs or []\n all_cbits = self._bits_in_condition(condition)\n all_cbits.extend(cargs)\n self._check_condition(op.name, condition)\n self._check_bits(qargs, self.output_map)\n self._check_bits(all_cbits, self.output_map)\n self._add_op_node(op, qargs, cargs, condition)\n al = [qargs, all_cbits]\n for q in itertools.chain(*al):\n ie = list(self._multi_graph.predecessors(self.output_map[q]))\n if len(ie) != 1:\n raise DAGCircuitError(\"output node has multiple in-edges\")\n self._multi_graph.add_edge(ie[0], self._id_to_node[self._max_node_id],\n name=\"%s[%s]\" % (q[0].name, q[1]), wire=q)\n self._multi_graph.remove_edge(ie[0], self.output_map[q])\n self._multi_graph.add_edge(self._id_to_node[self._max_node_id], self.output_map[q],\n name=\"%s[%s]\" % (q[0].name, q[1]), wire=q)\n return self._id_to_node[self._max_node_id]"
},
{
"code": "def configure(self, options, config):\n log.debug(\"Configuring plugins\")\n self.config = config\n cfg = PluginProxy('configure', self._plugins)\n cfg(options, config)\n enabled = [plug for plug in self._plugins if plug.enabled]\n self.plugins = enabled\n self.sort()\n log.debug(\"Plugins enabled: %s\", enabled)"
},
{
"code": "def s2n(self):\n M_N = 8.0713171\n f = lambda parent, daugther: -parent + daugther + 2 * M_N\n return self.derived('s2n', (0, -2), f)"
},
{
"code": "async def wait_changed(self):\n if not self.is_complete():\n waiter = self._loop.create_future()\n self._waiters.append(waiter)\n await waiter"
},
{
"code": "def add_virtual_columns_proper_motion2vperpendicular(self, distance=\"distance\", pm_long=\"pm_l\", pm_lat=\"pm_b\",\n vl=\"vl\", vb=\"vb\",\n propagate_uncertainties=False,\n radians=False):\n k = 4.74057\n self.add_variable(\"k\", k, overwrite=False)\n self.add_virtual_column(vl, \"k*{pm_long}*{distance}\".format(**locals()))\n self.add_virtual_column(vb, \"k* {pm_lat}*{distance}\".format(**locals()))\n if propagate_uncertainties:\n self.propagate_uncertainties([self[vl], self[vb]])"
},
{
"code": "def _build_trainable_posterior(param, initial_loc_fn):\n loc = tf.compat.v1.get_variable(\n param.name + '_loc',\n initializer=lambda: initial_loc_fn(param),\n dtype=param.prior.dtype,\n use_resource=True)\n scale = tf.nn.softplus(\n tf.compat.v1.get_variable(\n param.name + '_scale',\n initializer=lambda: -4 * tf.ones_like(initial_loc_fn(param)),\n dtype=param.prior.dtype,\n use_resource=True))\n q = tfd.Normal(loc=loc, scale=scale)\n if (param.prior.event_shape.ndims is None\n or param.prior.event_shape.ndims > 0):\n q = tfd.Independent(\n q, reinterpreted_batch_ndims=param.prior.event_shape.ndims)\n return tfd.TransformedDistribution(q, param.bijector)"
},
{
"code": "def poll(self):\n service = yield self.get_service()\n if not service:\n self.log.warn(\"Docker service not found\")\n return 0\n task_filter = {'service': service['Spec']['Name']}\n tasks = yield self.docker(\n 'tasks', task_filter\n )\n running_task = None\n for task in tasks:\n task_state = task['Status']['State']\n self.log.debug(\n \"Task %s of Docker service %s status: %s\",\n task['ID'][:7],\n self.service_id[:7],\n pformat(task_state),\n )\n if task_state == 'running':\n running_task = task\n if running_task is not None:\n return None\n else:\n return 1"
},
{
"code": "def var(self, axis=None, keepdims=False):\n return self._stat(axis, name='variance', keepdims=keepdims)"
},
{
"code": "def get_ids(self, features, threshold=0.0, func=np.sum, get_weights=False):\n if isinstance(features, str):\n features = [features]\n features = self.search_features(features)\n feature_weights = self.data.ix[:, features]\n weights = feature_weights.apply(func, 1)\n above_thresh = weights[weights >= threshold]\n return above_thresh if get_weights else list(above_thresh.index)"
},
{
"code": "def is_error(node: astroid.node_classes.NodeNG) -> bool:\n for child_node in node.get_children():\n if isinstance(child_node, astroid.Raise):\n return True\n return False"
},
{
"code": "def _sentences(self, clean_visible):\n 'generate strings identified as sentences'\n previous_end = 0\n clean_visible = clean_visible.decode('utf8')\n for start, end in self.sentence_tokenizer.span_tokenize(clean_visible):\n if start < previous_end:\n start = previous_end\n if start > end:\n continue\n try:\n label = self.label_index.find_le(end)\n except ValueError:\n label = None\n if label:\n off = label.offsets[OffsetType.CHARS]\n end = max(off.first + off.length, end)\n previous_end = end\n sent_str = clean_visible[start:end]\n yield start, end, sent_str"
},
{
"code": "def set_default_bg():\n term = environ.get('TERM', None)\n if term:\n if (term.startswith('xterm',) or term.startswith('eterm')\n or term == 'dtterm'):\n return False\n return True"
},
{
"code": "def run(self, data_loaders, workflow, max_epochs, **kwargs):\n assert isinstance(data_loaders, list)\n assert mmcv.is_list_of(workflow, tuple)\n assert len(data_loaders) == len(workflow)\n self._max_epochs = max_epochs\n work_dir = self.work_dir if self.work_dir is not None else 'NONE'\n self.logger.info('Start running, host: %s, work_dir: %s',\n get_host_info(), work_dir)\n self.logger.info('workflow: %s, max: %d epochs', workflow, max_epochs)\n self.call_hook('before_run')\n while self.epoch < max_epochs:\n for i, flow in enumerate(workflow):\n mode, epochs = flow\n if isinstance(mode, str):\n if not hasattr(self, mode):\n raise ValueError(\n 'runner has no method named \"{}\" to run an epoch'.\n format(mode))\n epoch_runner = getattr(self, mode)\n elif callable(mode):\n epoch_runner = mode\n else:\n raise TypeError('mode in workflow must be a str or '\n 'callable function, not {}'.format(\n type(mode)))\n for _ in range(epochs):\n if mode == 'train' and self.epoch >= max_epochs:\n return\n epoch_runner(data_loaders[i], **kwargs)\n time.sleep(1)\n self.call_hook('after_run')"
},
{
"code": "def glance_process(body, message):\n event_type = body['event_type']\n process = glance_customer_process.get(event_type)\n if process is not None:\n process(body, message)\n else:\n matched = False\n process_wildcard = None\n for pattern in glance_customer_process_wildcard.keys():\n if pattern.match(event_type):\n process_wildcard = glance_customer_process_wildcard.get(pattern)\n matched = True\n break\n if matched:\n process_wildcard(body, message)\n else:\n default_process(body, message)\n message.ack()"
},
{
"code": "def pre_build(self, traj, brian_list, network_dict):\n self._pre_build = not _explored_parameters_in_group(traj, traj.parameters.connections)\n self._pre_build = (self._pre_build and 'neurons_i' in network_dict and\n 'neurons_e' in network_dict)\n if self._pre_build:\n self._build_connections(traj, brian_list, network_dict)"
},
{
"code": "def _create_idx_from_stream(self, stream):\n stream_iter = iter(stream)\n dimension = self.properties.dimension\n darray = ctypes.c_double * dimension\n mins = darray()\n maxs = darray()\n no_data = ctypes.cast(ctypes.pointer(ctypes.c_ubyte(0)),\n ctypes.POINTER(ctypes.c_ubyte))\n def py_next_item(p_id, p_mins, p_maxs, p_dimension, p_data, p_length):\n try:\n p_id[0], coordinates, obj = next(stream_iter)\n except StopIteration:\n return -1\n except Exception as exc:\n self._exception = exc\n return -1\n if self.interleaved:\n coordinates = Index.deinterleave(coordinates)\n for i in range(dimension):\n mins[i] = coordinates[i*2]\n maxs[i] = coordinates[(i*2)+1]\n p_mins[0] = ctypes.cast(mins, ctypes.POINTER(ctypes.c_double))\n p_maxs[0] = ctypes.cast(maxs, ctypes.POINTER(ctypes.c_double))\n p_dimension[0] = dimension\n if obj is None:\n p_data[0] = no_data\n p_length[0] = 0\n else:\n p_length[0], data, _ = self._serialize(obj)\n p_data[0] = ctypes.cast(data, ctypes.POINTER(ctypes.c_ubyte))\n return 0\n stream = core.NEXTFUNC(py_next_item)\n return IndexStreamHandle(self.properties.handle, stream)"
},
{
"code": "def isAcquired(self, lockID):\n return self.__lockImpl.isAcquired(lockID, self.__selfID, time.time())"
},
{
"code": "def fill_heatmap(self):\n for module_path, lineno, runtime in self.lines_without_stdlib:\n self._execution_count[module_path][lineno] += 1\n self._heatmap[module_path][lineno] += runtime"
},
{
"code": "def parse_unstruct(unstruct):\n my_json = json.loads(unstruct)\n data = my_json['data']\n schema = data['schema']\n if 'data' in data:\n inner_data = data['data']\n else:\n raise SnowplowEventTransformationException([\"Could not extract inner data field from unstructured event\"])\n fixed_schema = fix_schema(\"unstruct_event\", schema)\n return [(fixed_schema, inner_data)]"
},
{
"code": "def volume_percentage_used(self, volume):\r\n volume = self._get_volume(volume)\r\n if volume is not None:\r\n total = int(volume[\"size\"][\"total\"])\r\n used = int(volume[\"size\"][\"used\"])\r\n if used is not None and used > 0 and \\\r\n total is not None and total > 0:\r\n return round((float(used) / float(total)) * 100.0, 1)"
},
{
"code": "def _sample_3d(self, n, seed=None):\n seed = seed_stream.SeedStream(seed, salt='von_mises_fisher_3d')\n u_shape = tf.concat([[n], self._batch_shape_tensor()], axis=0)\n z = tf.random.uniform(u_shape, seed=seed(), dtype=self.dtype)\n safe_conc = tf.where(self.concentration > 0,\n self.concentration,\n tf.ones_like(self.concentration))\n safe_z = tf.where(z > 0, z, tf.ones_like(z))\n safe_u = 1 + tf.reduce_logsumexp(\n input_tensor=[\n tf.math.log(safe_z),\n tf.math.log1p(-safe_z) - 2 * safe_conc\n ],\n axis=0) / safe_conc\n u = tf.where(self.concentration > tf.zeros_like(safe_u), safe_u,\n 2 * z - 1)\n u = tf.where(tf.equal(z, 0), -tf.ones_like(u), u)\n if not self._allow_nan_stats:\n u = tf.debugging.check_numerics(u, 'u in _sample_3d')\n return u[..., tf.newaxis]"
},
{
"code": "def find_on_path(importer, path_item, only=False):\n path_item = _normalize_cached(path_item)\n if os.path.isdir(path_item) and os.access(path_item, os.R_OK):\n if path_item.lower().endswith('.egg'):\n yield Distribution.from_filename(\n path_item, metadata=PathMetadata(\n path_item, os.path.join(path_item,'EGG-INFO')\n )\n )\n else:\n for entry in os.listdir(path_item):\n lower = entry.lower()\n if lower.endswith('.egg-info') or lower.endswith('.dist-info'):\n fullpath = os.path.join(path_item, entry)\n if os.path.isdir(fullpath):\n metadata = PathMetadata(path_item, fullpath)\n else:\n metadata = FileMetadata(fullpath)\n yield Distribution.from_location(\n path_item, entry, metadata, precedence=DEVELOP_DIST\n )\n elif not only and lower.endswith('.egg'):\n dists = find_distributions(os.path.join(path_item, entry))\n for dist in dists:\n yield dist\n elif not only and lower.endswith('.egg-link'):\n with open(os.path.join(path_item, entry)) as entry_file:\n entry_lines = entry_file.readlines()\n for line in entry_lines:\n if not line.strip():\n continue\n path = os.path.join(path_item, line.rstrip())\n dists = find_distributions(path)\n for item in dists:\n yield item\n break"
},
{
"code": "def lists(self, pattern: str = None) -> List[WikiList]:\n return [\n lst for arg in self.arguments for lst in arg.lists(pattern) if lst]"
},
{
"code": "def make_simple_step_size_update_policy(num_adaptation_steps,\n target_rate=0.75,\n decrement_multiplier=0.01,\n increment_multiplier=0.01,\n step_counter=None):\n if step_counter is None and num_adaptation_steps is not None:\n step_counter = tf.compat.v1.get_variable(\n name='step_size_adaptation_step_counter',\n initializer=np.array(-1, dtype=np.int32),\n dtype=tf.int32,\n trainable=False,\n use_resource=True)\n def step_size_simple_update_fn(step_size_var, kernel_results):\n if kernel_results is None:\n if mcmc_util.is_list_like(step_size_var):\n return [tf.identity(ss) for ss in step_size_var]\n return tf.identity(step_size_var)\n log_n = tf.math.log(\n tf.cast(\n tf.size(input=kernel_results.log_accept_ratio),\n kernel_results.log_accept_ratio.dtype))\n log_mean_accept_ratio = tf.reduce_logsumexp(\n input_tensor=tf.minimum(kernel_results.log_accept_ratio, 0.)) - log_n\n adjustment = tf.where(\n log_mean_accept_ratio < tf.cast(\n tf.math.log(target_rate), log_mean_accept_ratio.dtype),\n -decrement_multiplier / (1. + decrement_multiplier),\n increment_multiplier)\n def build_assign_op():\n if mcmc_util.is_list_like(step_size_var):\n return [\n ss.assign_add(ss * tf.cast(adjustment, ss.dtype))\n for ss in step_size_var\n ]\n return step_size_var.assign_add(\n step_size_var * tf.cast(adjustment, step_size_var.dtype))\n if num_adaptation_steps is None:\n return build_assign_op()\n else:\n with tf.control_dependencies([step_counter.assign_add(1)]):\n return tf.cond(\n pred=step_counter < num_adaptation_steps,\n true_fn=build_assign_op,\n false_fn=lambda: step_size_var)\n return step_size_simple_update_fn"
},
{
"code": "def _update_status(self):\n srun, scomp, sdead = self._s_running, self._s_completed, self._s_dead\n running, completed, dead = self._running, self._completed, self._dead\n for num, job in enumerate(running):\n stat = job.stat_code\n if stat == srun:\n continue\n elif stat == scomp:\n completed.append(job)\n self._comp_report.append(job)\n running[num] = False\n elif stat == sdead:\n dead.append(job)\n self._dead_report.append(job)\n running[num] = False\n running[:] = filter(None, running)"
},
{
"code": "def headers_present(self, headers):\n headers = {name: re.compile('(.*)') for name in headers}\n self.add_matcher(matcher('HeadersMatcher', headers))"
},
{
"code": "def download_csv(data, filename):\n assert_is_type(data, H2OFrame)\n assert_is_type(filename, str)\n url = h2oconn.make_url(\"DownloadDataset\", 3) + \"?frame_id={}&hex_string=false\".format(data.frame_id)\n with open(filename, \"wb\") as f:\n f.write(urlopen()(url).read())"
},
{
"code": "def _bind_parameter(self, parameter, value):\n for (instr, param_index) in self._parameter_table[parameter]:\n instr.params[param_index] = value"
},
{
"code": "def exclude_downhole(filt, threshold=2):\n cfilt = filt.copy()\n inds = bool_2_indices(~filt)\n rem = (np.diff(inds) >= threshold)[:, 0]\n if any(rem):\n if inds[rem].shape[0] > 1:\n limit = inds[rem][1, 0]\n cfilt[limit:] = False\n return cfilt"
},
{
"code": "def init_module(self, run_object):\n self.profile = self.profile_module\n self._run_object, _, self._run_args = run_object.partition(' ')\n self._object_name = '%s (module)' % self._run_object\n self._globs = {\n '__file__': self._run_object,\n '__name__': '__main__',\n '__package__': None,\n }\n program_path = os.path.dirname(self._run_object)\n if sys.path[0] != program_path:\n sys.path.insert(0, program_path)\n self._replace_sysargs()"
},
{
"code": "def _main(self, fileobj, data, offset):\n fileobj.seek(offset)\n fileobj.write(data)"
},
{
"code": "def encode(self, txt):\n return list(self._fwd_index.get(c, 0) for c in txt)"
},
{
"code": "def decrement(self):\n with self._lock:\n if self._count == 0:\n raise RuntimeError(\n 'Counter is at zero. It cannot dip below zero')\n self._count -= 1\n if self._is_finalized and self._count == 0:\n self._callback()"
},
{
"code": "def _initialize_slots(self, seed, hashvalues):\n self.seed = seed\n self.hashvalues = self._parse_hashvalues(hashvalues)"
},
{
"code": "def get(self, *args, **kwargs):\n if 'pk' in kwargs:\n kwargs['parent'] = kwargs['pk']\n kwargs['head'] = True\n del kwargs['pk']\n if 'request' in kwargs:\n\t \trequest = kwargs['request']\n\t \tversion = request.GET.get('version', None)\n\t \tpreview_id = request.GET.get('preview_id', None)\n\t \tif (version is not None) and (preview_id is not None):\n\t \t\tkwargs['revision_id'] = version\n\t \t\tkwargs['preview_id'] = preview_id\n\t \t\tdel kwargs['is_published']\n\t \tdel kwargs['request']\n return super(PublishableManager, self).get(*args, **kwargs)"
},
{
"code": "def withIndent(self, indent=1):\n ctx = copy(self)\n ctx.indent += indent\n return ctx"
},
{
"code": "def fix_header(filename, keyword, new_value):\n hd = read_header(filename)\n hi = read_header(filename, return_idxs=True)\n idx = hi[keyword]\n dtype = header_keyword_types[keyword]\n dtype_to_type = {b'<l' : np.int32,\n b'str' : bytes,\n b'<d' : np.float64,\n b'angle' : to_sigproc_angle}\n value_dtype = dtype_to_type[dtype]\n if isinstance(value_dtype, bytes):\n if len(hd[keyword]) == len(new_value):\n val_str = np.int32(len(new_value)).tostring() + new_value\n else:\n raise RuntimeError(\"String size mismatch. Cannot update without rewriting entire file.\")\n else:\n val_str = value_dtype(new_value).tostring()\n with open(filename, 'rb+') as fh:\n fh.seek(idx)\n fh.write(val_str)"
},
{
"code": "def _match_one(self, rec, tests):\n for key,test in tests.iteritems():\n if not test(rec.get(key, None)):\n return False\n return True"
},
{
"code": "def as_action_description(self):\n description = {\n self.name: {\n 'href': self.href_prefix + self.href,\n 'timeRequested': self.time_requested,\n 'status': self.status,\n },\n }\n if self.input is not None:\n description[self.name]['input'] = self.input\n if self.time_completed is not None:\n description[self.name]['timeCompleted'] = self.time_completed\n return description"
},
{
"code": "def parse(url):\n config = {}\n if not isinstance(url, six.string_types):\n url = ''\n url = urlparse.urlparse(url)\n path = url.path[1:]\n path = path.split('?', 2)[0]\n config.update({\n 'NAME': path,\n 'USER': url.username,\n 'PASSWORD': url.password,\n 'HOST': url.hostname,\n 'PORT': url.port,\n })\n if url.scheme in SCHEMES:\n config['ENGINE'] = SCHEMES[url.scheme]\n return config"
},
{
"code": "def get_table_content(self, table):\n result = [[]]\n cols = table.cols\n for cell in self.compute_content(table):\n if cols == 0:\n result.append([])\n cols = table.cols\n cols -= 1\n result[-1].append(cell)\n while len(result[-1]) < cols:\n result[-1].append(\"\")\n return result"
},
{
"code": "def connect(self):\n SCOPES = 'https://www.googleapis.com/auth/drive'\n store = file.Storage('drive_credentials.json')\n creds = store.get()\n if not creds or creds.invalid:\n try:\n flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)\n except InvalidClientSecretsError:\n log.error('ERROR: Could not find client_secret.json in current directory, please obtain it from the API console.')\n return\n creds = tools.run_flow(flow, store)\n self.connection = build('drive', 'v3', http=creds.authorize(Http()))\n response = self.connection.files().list(q=\"name='Music' and mimeType='application/vnd.google-apps.folder' and trashed=false\").execute()\n try:\n folder_id = response.get('files', [])[0]['id']\n except IndexError:\n log.warning('Music folder is missing. Creating it.')\n folder_metadata = {'name': 'Music', 'mimeType': 'application/vnd.google-apps.folder'}\n folder = self.connection.files().create(body=folder_metadata, fields='id').execute()"
},
{
"code": "def get_type(self, type_name):\n type_name = self._canonicalize_type(type_name)\n if str(type_name) == 'int':\n type_name = 'integer'\n elif str(type_name) == 'str':\n type_name = 'string'\n elif str(type_name) == 'dict':\n type_name = 'basic_dict'\n if self.is_known_type(type_name):\n return self.known_types[type_name]\n base_type, is_complex, subtypes = self.split_type(type_name)\n if is_complex and base_type in self.type_factories:\n self.instantiate_type(type_name, base_type, subtypes)\n return self.known_types[type_name]\n i = 0\n for i, (source, name) in enumerate(self._lazy_type_sources):\n if isinstance(source, str):\n import pkg_resources\n for entry in pkg_resources.iter_entry_points(source):\n try:\n mod = entry.load()\n type_system.load_type_module(mod)\n except:\n fail_info = (\"Entry point group: %s, name: %s\" % (source, entry.name), sys.exc_info)\n logging.exception(\"Error loading external type source from entry point, group: %s, name: %s\", source, entry.name)\n self.failed_sources.append(fail_info)\n else:\n try:\n source(self)\n except:\n fail_info = (\"source: %s\" % name, sys.exc_info)\n logging.exception(\"Error loading external type source, source: %s\", source)\n self.failed_sources.append(fail_info)\n if self.is_known_type(type_name) or (is_complex and base_type in self.type_factories):\n break\n self._lazy_type_sources = self._lazy_type_sources[i:]\n if not (self.is_known_type(type_name) or (is_complex and base_type in self.type_factories)):\n raise ArgumentError(\"get_type called on unknown type\", type=type_name, failed_external_sources=[x[0] for x in self.failed_sources])\n return self.get_type(type_name)"
},
{
"code": "def create(self):\n if self.dirname and not os.path.exists(self.dirname):\n os.makedirs(self.dirname)"
},
{
"code": "def add_server(self, hostname, port, use_ssl, tls_ctx=None):\n if not use_ssl and tls_ctx:\n raise ValueError(\"Cannot specify a TLS context and not use SSL!\")\n server = ldap3.Server(\n hostname,\n port=port,\n use_ssl=use_ssl,\n tls=tls_ctx\n )\n self._server_pool.add(server)\n return server"
},
{
"code": "def get_ref_annotation_data_after_time(self, id_tier, time):\n befores = self.get_ref_annotation_data_between_times(\n id_tier, time, self.get_full_time_interval())\n if befores:\n return [min(befores, key=lambda x: x[0])]\n else:\n return []"
},
{
"code": "def import_data(\n self, resource_group_name, name, files, format=None, custom_headers=None, raw=False, polling=True, **operation_config):\n raw_result = self._import_data_initial(\n resource_group_name=resource_group_name,\n name=name,\n files=files,\n format=format,\n custom_headers=custom_headers,\n raw=True,\n **operation_config\n )\n def get_long_running_output(response):\n if raw:\n client_raw_response = ClientRawResponse(None, response)\n return client_raw_response\n lro_delay = operation_config.get(\n 'long_running_operation_timeout',\n self.config.long_running_operation_timeout)\n if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)\n elif polling is False: polling_method = NoPolling()\n else: polling_method = polling\n return LROPoller(self._client, raw_result, get_long_running_output, polling_method)"
},
{
"code": "def flowshow(flow, win_name='', wait_time=0):\n flow = flowread(flow)\n flow_img = flow2rgb(flow)\n imshow(rgb2bgr(flow_img), win_name, wait_time)"
},
{
"code": "def duplicate(self, new_parent=None):\r\n \"Create a new object exactly similar to self\"\r\n kwargs = {}\r\n for spec_name, spec in self._meta.specs.items():\r\n value = getattr(self, spec_name)\r\n if isinstance(value, Color):\r\n print \"COLOR\", value, value.default\r\n if value.default:\r\n value = None\r\n if value is not None:\r\n kwargs[spec_name] = value\r\n del kwargs['parent'] \r\n new_id = wx.NewId()\r\n kwargs['id'] = new_id\r\n kwargs['name'] = \"%s_%s\" % (kwargs['name'], new_id)\r\n new_obj = self.__class__(new_parent or self.get_parent(), **kwargs)\r\n for child in self:\r\n child.duplicate(new_obj)\r\n return new_obj"
},
{
"code": "def option_attrname(self, opt, optdict=None):\n if optdict is None:\n optdict = self.get_option_def(opt)\n return optdict.get(\"dest\", opt.replace(\"-\", \"_\"))"
},
{
"code": "def set_issuer(self, issuer):\n self._set_name(_lib.X509_set_issuer_name, issuer)\n self._issuer_invalidator.clear()"
},
{
"code": "def search(self, query, verbose=0):\n if verbose > 0:\n print(\"searching \" + query)\n query = query.lower()\n qgram = ng(query, self.slb)\n qocument = set()\n for q in qgram:\n if q in self.ngrams.keys():\n for i in self.ngrams[q]:\n qocument.add(i)\n self.qocument = qocument\n results = {}\n for i in qocument:\n for j in self.D[i].keys():\n if not j in results.keys():\n results[j] = 0\n results[j] = results[j] + self.D[i][j]\n sorted_results = sorted(results.items(), key=operator.itemgetter(1), reverse=True)\n return [self.elements[f[0]] for f in sorted_results]"
},
{
"code": "def layers(self):\n graph_layers = self.multigraph_layers()\n try:\n next(graph_layers)\n except StopIteration:\n return\n def add_nodes_from(layer, nodes):\n layer._multi_graph.add_nodes_from(nodes)\n for graph_layer in graph_layers:\n op_nodes = [node for node in graph_layer if node.type == \"op\"]\n if not op_nodes:\n return\n new_layer = DAGCircuit()\n new_layer.name = self.name\n for creg in self.cregs.values():\n new_layer.add_creg(creg)\n for qreg in self.qregs.values():\n new_layer.add_qreg(qreg)\n add_nodes_from(new_layer, self.input_map.values())\n add_nodes_from(new_layer, self.output_map.values())\n add_nodes_from(new_layer, op_nodes)\n support_list = [\n op_node.qargs\n for op_node in op_nodes\n if op_node.name not in {\"barrier\", \"snapshot\", \"save\", \"load\", \"noise\"}\n ]\n wires = {self.input_map[wire]: self.output_map[wire]\n for wire in self.wires}\n for op_node in op_nodes:\n args = self._bits_in_condition(op_node.condition) \\\n + op_node.cargs + op_node.qargs\n arg_ids = (self.input_map[(arg[0], arg[1])] for arg in args)\n for arg_id in arg_ids:\n wires[arg_id], wires[op_node] = op_node, wires[arg_id]\n new_layer._multi_graph.add_edges_from(wires.items())\n yield {\"graph\": new_layer, \"partition\": support_list}"
},
{
"code": "def current_docker_container_id():\n try:\n with open('/proc/1/cgroup', 'r') as readable:\n raw = readable.read()\n ids = set(re.compile('[0-9a-f]{12,}').findall(raw))\n assert len(ids) == 1\n return ids.pop()\n except:\n logging.exception('Failed to obtain current container ID')\n raise NotInsideContainerError()"
},
{
"code": "def get_student_messaging_for_sis_course_id_and_sis_user_id(\n self, sis_user_id, sis_course_id):\n url = (\"/api/v1/courses/%s/analytics/\"\n \"users/sis_user_id:%s/communication.json\") % (\n self._sis_id(sis_course_id, sis_field=\"course\"), sis_user_id)\n return self._get_resource(url)"
},
{
"code": "def create_instance(self, instance_id, configuration_name, node_count,\n display_name, project_id=None):\n self._apply_to_instance(project_id, instance_id, configuration_name,\n node_count, display_name, lambda x: x.create())"
},
{
"code": "def remove_action(self, action_name, action_id):\n action = self.get_action(action_name, action_id)\n if action is None:\n return False\n action.cancel()\n self.actions[action_name].remove(action)\n return True"
},
{
"code": "def update_x(self, x, indices=None):\n x = _make_np_bool(x)\n if indices is None:\n if len(self._x) != len(x):\n raise QiskitError(\"During updating whole x, you can not change \"\n \"the number of qubits.\")\n self._x = x\n else:\n if not isinstance(indices, list) and not isinstance(indices, np.ndarray):\n indices = [indices]\n for p, idx in enumerate(indices):\n self._x[idx] = x[p]\n return self"
},
{
"code": "def _subgraph_parse(\n self, node, pathnode, extra_blocks\n ):\n loose_ends = []\n self.tail = node\n self.dispatch_list(node.body)\n loose_ends.append(self.tail)\n for extra in extra_blocks:\n self.tail = node\n self.dispatch_list(extra.body)\n loose_ends.append(self.tail)\n if node.orelse:\n self.tail = node\n self.dispatch_list(node.orelse)\n loose_ends.append(self.tail)\n else:\n loose_ends.append(node)\n if node:\n bottom = \"%s\" % self._bottom_counter\n self._bottom_counter += 1\n for le in loose_ends:\n self.graph.connect(le, bottom)\n self.tail = bottom"
},
{
"code": "def set_constant(self, name, value):\n assert isinstance(name, str) or isinstance(name, sympy.Symbol), \\\n \"constant name needs to be of type str, unicode or a sympy.Symbol\"\n assert type(value) is int, \"constant value needs to be of type int\"\n if isinstance(name, sympy.Symbol):\n self.constants[name] = value\n else:\n self.constants[symbol_pos_int(name)] = value"
},
{
"code": "def parse(cls, parser, token):\n bits, as_var = parse_as_var(parser, token)\n tag_name, args, kwargs = parse_token_kwargs(parser, bits, ('template',) + cls.allowed_kwargs, compile_args=cls.compile_args, compile_kwargs=cls.compile_kwargs)\n cls.validate_args(tag_name, *args)\n return cls(tag_name, as_var, *args, **kwargs)"
},
{
"code": "def resolves_for(self, session):\n if self.url:\n self.actual_path = session.current_url\n else:\n result = urlparse(session.current_url)\n if self.only_path:\n self.actual_path = result.path\n else:\n request_uri = result.path\n if result.query:\n request_uri += \"?{0}\".format(result.query)\n self.actual_path = request_uri\n if isregex(self.expected_path):\n return self.expected_path.search(self.actual_path)\n else:\n return normalize_url(self.actual_path) == normalize_url(self.expected_path)"
},
{
"code": "def retrieve_image(self, path_to_image):\n image = self.storage.open(path_to_image, 'rb')\n file_ext = path_to_image.rsplit('.')[-1]\n image_format, mime_type = get_image_metadata_from_file_ext(file_ext)\n return (\n Image.open(image),\n file_ext,\n image_format,\n mime_type\n )"
},
{
"code": "def create_build_package(package_files):\n for package_file in package_files:\n if not os.path.exists(package_file):\n bot.exit('Cannot find %s.' % package_file)\n bot.log('Generating build package for %s files...' % len(package_files))\n build_dir = get_tmpdir(prefix=\"sregistry-build\")\n build_tar = '%s/build.tar.gz' % build_dir\n tar = tarfile.open(build_tar, \"w:gz\")\n for package_file in package_files:\n tar.add(package_file)\n tar.close()\n sha256 = get_file_hash(build_tar)\n hash_tar = \"%s/%s.tar.gz\" %(build_dir, sha256)\n shutil.move(build_tar, hash_tar)\n return hash_tar"
},
{
"code": "def step_next_char(self):\n self._index += 1\n self._col_offset += 1\n if self._index > self._maxindex:\n self._maxindex = self._index\n self._maxcol = self._col_offset\n self._maxline = self._lineno"
},
{
"code": "def _get_cached_arg_spec(fn):\n arg_spec = _ARG_SPEC_CACHE.get(fn)\n if arg_spec is None:\n arg_spec_fn = inspect.getfullargspec if six.PY3 else inspect.getargspec\n try:\n arg_spec = arg_spec_fn(fn)\n except TypeError:\n arg_spec = arg_spec_fn(fn.__call__)\n _ARG_SPEC_CACHE[fn] = arg_spec\n return arg_spec"
},
{
"code": "def export_xhtml(html, filename, image_tag=None):\n if image_tag is None:\n image_tag = default_image_tag\n else:\n image_tag = ensure_utf8(image_tag)\n with open(filename, 'w') as f:\n offset = html.find(\"<html>\")\n assert offset > -1, 'Invalid HTML string: no <html> tag.'\n html = ('<html xmlns=\"http://www.w3.org/1999/xhtml\">\\n'+\n html[offset+6:])\n html = fix_html(html)\n f.write(IMG_RE.sub(lambda x: image_tag(x, path = None, format = \"svg\"),\n html))"
},
{
"code": "def get_properties(self):\n return {prop.get_name(): prop.get_value()\n for prop in self.properties.values()}"
},
{
"code": "def get_card(self, card_id, **query_params):\n card_json = self.fetch_json(\n uri_path=self.base_uri + '/cards/' + card_id\n )\n return self.create_card(card_json)"
},
{
"code": "def with_context(exc, context):\n if not hasattr(exc, 'context'):\n exc.context = {}\n exc.context.update(context)\n return exc"
},
{
"code": "def delete(self, url, **kwargs):\n check_type(url, basestring, may_be_none=False)\n erc = kwargs.pop('erc', EXPECTED_RESPONSE_CODE['DELETE'])\n self.request('DELETE', url, erc, **kwargs)"
},
{
"code": "def effective_sample_size(states,\n filter_threshold=0.,\n filter_beyond_lag=None,\n name=None):\n states_was_list = _is_list_like(states)\n if not states_was_list:\n states = [states]\n filter_beyond_lag = _broadcast_maybelist_arg(states, filter_beyond_lag,\n 'filter_beyond_lag')\n filter_threshold = _broadcast_maybelist_arg(states, filter_threshold,\n 'filter_threshold')\n with tf.compat.v1.name_scope(name, 'effective_sample_size'):\n ess_list = [\n _effective_sample_size_single_state(s, ml, mlt)\n for (s, ml, mlt) in zip(states, filter_beyond_lag, filter_threshold)\n ]\n if states_was_list:\n return ess_list\n return ess_list[0]"
},
{
"code": "def add_requirements(self, metadata_path):\n additional = list(self.setupcfg_requirements())\n if not additional: return\n pkg_info = read_pkg_info(metadata_path)\n if 'Provides-Extra' in pkg_info or 'Requires-Dist' in pkg_info:\n warnings.warn('setup.cfg requirements overwrite values from setup.py')\n del pkg_info['Provides-Extra']\n del pkg_info['Requires-Dist']\n for k, v in additional:\n pkg_info[k] = v\n write_pkg_info(metadata_path, pkg_info)"
},
{
"code": "def get_module(self, name, node):\n for mod in self.modules():\n mod_name = mod.node.name\n if mod_name == name:\n return mod\n package = node.root().name\n if mod_name == \"%s.%s\" % (package, name):\n return mod\n if mod_name == \"%s.%s\" % (package.rsplit(\".\", 1)[0], name):\n return mod\n raise KeyError(name)"
},
{
"code": "def copy(self, copy_source, bucket, key, extra_args=None,\n subscribers=None, source_client=None):\n if extra_args is None:\n extra_args = {}\n if subscribers is None:\n subscribers = []\n if source_client is None:\n source_client = self._client\n self._validate_all_known_args(extra_args, self.ALLOWED_COPY_ARGS)\n call_args = CallArgs(\n copy_source=copy_source, bucket=bucket, key=key,\n extra_args=extra_args, subscribers=subscribers,\n source_client=source_client\n )\n return self._submit_transfer(call_args, CopySubmissionTask)"
},
{
"code": "def write(self, output_stream, kmip_version=enums.KMIPVersion.KMIP_1_0):\n local_stream = utils.BytearrayStream()\n if len(self._credentials) == 0:\n raise ValueError(\"Authentication struct missing credentials.\")\n for credential in self._credentials:\n credential.write(local_stream, kmip_version=kmip_version)\n self.length = local_stream.length()\n super(Authentication, self).write(\n output_stream,\n kmip_version=kmip_version\n )\n output_stream.write(local_stream.buffer)"
},
{
"code": "def dims(x):\n if isinstance(x, tf.TensorShape):\n return x.dims\n r = tf.TensorShape(x).dims\n return None if r is None else list(map(tf.compat.dimension_value, r))"
},
{
"code": "def ancestral_reconstruction(params):\n if assure_tree(params, tmp_dir='ancestral_tmp'):\n return 1\n outdir = get_outdir(params, '_ancestral')\n basename = get_basename(params, outdir)\n gtr = create_gtr(params)\n aln, ref, fixed_pi = read_if_vcf(params)\n is_vcf = True if ref is not None else False\n treeanc = TreeAnc(params.tree, aln=aln, ref=ref, gtr=gtr, verbose=1,\n fill_overhangs=not params.keep_overhangs)\n ndiff =treeanc.infer_ancestral_sequences('ml', infer_gtr=params.gtr=='infer',\n marginal=params.marginal, fixed_pi=fixed_pi)\n if ndiff==ttconf.ERROR:\n return 1\n if params.gtr==\"infer\":\n print('\\nInferred GTR model:')\n print(treeanc.gtr)\n export_sequences_and_tree(treeanc, basename, is_vcf, params.zero_based,\n report_ambiguous=params.report_ambiguous)\n return 0"
},
{
"code": "def chain_nac_proxy(chain, sender, contract_address, value=0):\n \"create an object which acts as a proxy for the contract on the chain\"\n klass = registry[contract_address].im_self\n assert issubclass(klass, NativeABIContract)\n def mk_method(method):\n def m(s, *args):\n data = abi_encode_args(method, args)\n block = chain.head_candidate\n output = test_call(block, sender, contract_address, data)\n if output is not None:\n return abi_decode_return_vals(method, output)\n return m\n class cproxy(object):\n pass\n for m in klass._abi_methods():\n setattr(cproxy, m.__func__.func_name, mk_method(m))\n return cproxy()"
},
{
"code": "def _generate(self, source, name, filename, defer_init=False):\n return generate(source, self, name, filename, defer_init=defer_init)"
},
{
"code": "def send_json(self, ids=None):\n items = ids or self._registration_id\n values = {\"registration_ids\": items}\n if self._data is not None:\n values[\"data\"] = self._data\n for key, val in self._kwargs.items():\n if val:\n values[key] = val\n data = json.dumps(values, separators=(\",\", \":\"), sort_keys=True).encode(\n self.encoding)\n result = json.loads(self._send(data, \"application/json\"))\n if (\"failure\" in result) and (result[\"failure\"]):\n unregistered = []\n throw_error = False\n for index, error in enumerate(result.get(\"results\", [])):\n error = error.get(\"error\", \"\")\n if error in (\"NotRegistered\", \"InvalidRegistration\"):\n unregistered.append(items[index])\n elif error != \"\":\n throw_error = True\n self.deactivate_unregistered_devices(unregistered)\n if throw_error:\n raise GCMPushError(result)\n return result"
},
{
"code": "def compounds(context, case_id):\n adapter = context.obj['adapter']\n LOG.info(\"Running scout update compounds\")\n case_obj = adapter.case(case_id)\n if not case_obj:\n LOG.warning(\"Case %s could not be found\", case_id)\n context.abort()\n try:\n adapter.update_case_compounds(case_obj)\n except Exception as err:\n LOG.warning(err)\n context.abort()"
},
{
"code": "def try_passwordless_ssh(server, keyfile, paramiko=None):\n if paramiko is None:\n paramiko = sys.platform == 'win32'\n if not paramiko:\n f = _try_passwordless_openssh\n else:\n f = _try_passwordless_paramiko\n return f(server, keyfile)"
},
{
"code": "def analyze_entities(self, document, encoding_type=None, retry=None, timeout=None, metadata=None):\n client = self.get_conn()\n return client.analyze_entities(\n document=document, encoding_type=encoding_type, retry=retry, timeout=timeout, metadata=metadata\n )"
},
{
"code": "def __load_symbol_maps(self):\n repo = SymbolMapRepository(self.__get_session())\n all_maps = repo.get_all()\n self.symbol_maps = {}\n for item in all_maps:\n self.symbol_maps[item.in_symbol] = item.out_symbol"
},
{
"code": "def connection(self):\n ctx = _app_ctx_stack.top\n if ctx is not None:\n if not hasattr(ctx, 'mysql_db'):\n ctx.mysql_db = self.connect\n return ctx.mysql_db"
},
{
"code": "def multiqc(store, institute_id, case_name):\n institute_obj, case_obj = institute_and_case(store, institute_id, case_name)\n return dict(\n institute=institute_obj,\n case=case_obj,\n )"
},
{
"code": "def write_change(change):\n action, rrset = change\n change_vals = get_change_values(change)\n e_change = etree.Element(\"Change\")\n e_action = etree.SubElement(e_change, \"Action\")\n e_action.text = action\n e_rrset = etree.SubElement(e_change, \"ResourceRecordSet\")\n e_name = etree.SubElement(e_rrset, \"Name\")\n e_name.text = change_vals['name']\n e_type = etree.SubElement(e_rrset, \"Type\")\n e_type.text = rrset.rrset_type\n if change_vals.get('set_identifier'):\n e_set_id = etree.SubElement(e_rrset, \"SetIdentifier\")\n e_set_id.text = change_vals['set_identifier']\n if change_vals.get('weight'):\n e_weight = etree.SubElement(e_rrset, \"Weight\")\n e_weight.text = change_vals['weight']\n if change_vals.get('alias_hosted_zone_id') or change_vals.get('alias_dns_name'):\n e_alias_target = etree.SubElement(e_rrset, \"AliasTarget\")\n e_hosted_zone_id = etree.SubElement(e_alias_target, \"HostedZoneId\")\n e_hosted_zone_id.text = change_vals['alias_hosted_zone_id']\n e_dns_name = etree.SubElement(e_alias_target, \"DNSName\")\n e_dns_name.text = change_vals['alias_dns_name']\n if change_vals.get('region'):\n e_weight = etree.SubElement(e_rrset, \"Region\")\n e_weight.text = change_vals['region']\n e_ttl = etree.SubElement(e_rrset, \"TTL\")\n e_ttl.text = str(change_vals['ttl'])\n if rrset.is_alias_record_set():\n return e_change\n e_resource_records = etree.SubElement(e_rrset, \"ResourceRecords\")\n for value in change_vals['records']:\n e_resource_record = etree.SubElement(e_resource_records, \"ResourceRecord\")\n e_value = etree.SubElement(e_resource_record, \"Value\")\n e_value.text = value\n return e_change"
},
{
"code": "def _init_transformer(cls, data):\n if isinstance(data, QuantumChannel):\n return data\n if hasattr(data, 'to_quantumchannel'):\n return data.to_channel()\n if hasattr(data, 'to_channel'):\n return data.to_channel()\n return Operator(data)"
},
{
"code": "def _cmd(self, cmd, *args, **kw):\n ok = kw.setdefault('ok', False)\n self._wakeup()\n if args:\n cmd = \"%s %s\" % (cmd, ' '.join(str(a) for a in args))\n for i in xrange(3):\n log.info(\"send: \" + cmd)\n self.port.write(cmd + '\\n')\n if ok:\n ack = self.port.read(len(self.OK))\n log_raw('read', ack)\n if ack == self.OK:\n return\n else:\n ack = self.port.read(len(self.ACK))\n log_raw('read', ack)\n if ack == self.ACK:\n return\n raise NoDeviceException('Can not access weather station')"
},
{
"code": "def _index_put(self, idx_name, *ids_and_fcs):\n keys = self._index_keys_for(idx_name, *ids_and_fcs)\n with_vals = map(lambda k: (k, '0'), keys)\n self.kvl.put(self.INDEX_TABLE, *with_vals)"
},
{
"code": "def valid(schema=None):\n def dec(fun):\n @wraps(fun)\n def d_func(self, ctx, data, *a, **kw):\n try:\n validate(data['params'], schema)\n except ValidationError as err:\n raise InvalidParams(err)\n except SchemaError as err:\n raise InternalError(err)\n return fun(self, ctx, data['params'], *a, **kw)\n return d_func\n return dec"
},
{
"code": "def map_thread_names():\n name2id = {}\n for thread_id in list(threading._active.keys()):\n thread = threading._active[thread_id]\n name = thread.getName()\n if name not in list(name2id.keys()):\n name2id[name] = thread_id\n pass\n pass\n return name2id"
},
{
"code": "def _choi_to_kraus(data, input_dim, output_dim, atol=ATOL_DEFAULT):\n if is_hermitian_matrix(data, atol=atol):\n w, v = la.eigh(data)\n if len(w[w < -atol]) == 0:\n kraus = []\n for val, vec in zip(w, v.T):\n if abs(val) > atol:\n k = np.sqrt(val) * vec.reshape(\n (output_dim, input_dim), order='F')\n kraus.append(k)\n if not kraus:\n kraus.append(np.zeros((output_dim, input_dim), dtype=complex))\n return (kraus, None)\n mat_u, svals, mat_vh = la.svd(data)\n kraus_l = []\n kraus_r = []\n for val, vec_l, vec_r in zip(svals, mat_u.T, mat_vh.conj()):\n kraus_l.append(\n np.sqrt(val) * vec_l.reshape((output_dim, input_dim), order='F'))\n kraus_r.append(\n np.sqrt(val) * vec_r.reshape((output_dim, input_dim), order='F'))\n return (kraus_l, kraus_r)"
},
{
"code": "def login(self, *login_args, **login_kwargs):\n def decorator(f):\n @wraps(f)\n def decorated(*args, **kwargs):\n self.response = make_response()\n adapter = WerkzeugAdapter(request, self.response)\n login_kwargs.setdefault('session', session)\n login_kwargs.setdefault('session_saver', self.session_saver)\n self.result = super(FlaskAuthomatic, self).login(\n adapter,\n *login_args,\n **login_kwargs)\n return f(*args, **kwargs)\n return decorated\n return decorator"
},
{
"code": "def main(args=None):\n options, paths = _parse_options(args)\n format = getattr(options, 'output', 'simple')\n formatter = _FORMATTERS[format](options)\n for path in paths:\n meta = get_metadata(path, options.metadata_version)\n if meta is None:\n continue\n if options.download_url_prefix:\n if meta.download_url is None:\n filename = os.path.basename(path)\n meta.download_url = '%s/%s' % (options.download_url_prefix,\n filename)\n formatter(meta)\n formatter.finish()"
},
{
"code": "def _get_format_from_document(self, token, document):\n code, html = self._formatter._format_lines([(token, u'dummy')]).next()\n self._document.setHtml(html)\n return QtGui.QTextCursor(self._document).charFormat()"
},
{
"code": "def authenticate_credentials(self, key):\n user, token = super(TokenAuthentication, self).authenticate_credentials(key)\n if token.expires < timezone.now():\n msg = _('Token has expired.')\n raise exceptions.AuthenticationFailed(msg)\n token.update_expiry()\n return (user, token)"
},
{
"code": "def parse_issues(raw_page):\n raw_issues = json.loads(raw_page)\n issues = raw_issues['issues']\n for issue in issues:\n yield issue"
},
{
"code": "def nice_pair(pair):\n start, end = pair\n if start == end:\n return \"%d\" % start\n else:\n return \"%d-%d\" % (start, end)"
},
{
"code": "def comments(self):\n record_numbers = range(2, self.fward)\n if not record_numbers:\n return ''\n data = b''.join(self.read_record(n)[0:1000] for n in record_numbers)\n try:\n return data[:data.find(b'\\4')].decode('ascii').replace('\\0', '\\n')\n except IndexError:\n raise ValueError('DAF file comment area is missing its EOT byte')\n except UnicodeDecodeError:\n raise ValueError('DAF file comment area is not ASCII text')"
},
{
"code": "def quadrature_scheme_lognormal_quantiles(\n loc, scale, quadrature_size,\n validate_args=False, name=None):\n with tf.name_scope(name or \"quadrature_scheme_lognormal_quantiles\"):\n dist = transformed_distribution.TransformedDistribution(\n distribution=normal.Normal(loc=loc, scale=scale),\n bijector=exp_bijector.Exp(),\n validate_args=validate_args)\n batch_ndims = tensorshape_util.rank(dist.batch_shape)\n if batch_ndims is None:\n batch_ndims = tf.shape(input=dist.batch_shape_tensor())[0]\n def _compute_quantiles():\n zero = tf.zeros([], dtype=dist.dtype)\n edges = tf.linspace(zero, 1., quadrature_size + 3)[1:-1]\n edges = tf.reshape(\n edges,\n shape=tf.concat(\n [[-1], tf.ones([batch_ndims], dtype=tf.int32)], axis=0))\n quantiles = dist.quantile(edges)\n perm = tf.concat([tf.range(1, 1 + batch_ndims), [0]], axis=0)\n quantiles = tf.transpose(a=quantiles, perm=perm)\n return quantiles\n quantiles = _compute_quantiles()\n grid = (quantiles[..., :-1] + quantiles[..., 1:]) / 2.\n new_shape = tensorshape_util.concatenate(dist.batch_shape,\n [quadrature_size])\n tensorshape_util.set_shape(grid, new_shape)\n probs = tf.fill(\n dims=[quadrature_size], value=1. / tf.cast(quadrature_size, dist.dtype))\n return grid, probs"
},
{
"code": "def do_debug(self, args):\n if not args:\n self.help_fn(\"What information would you like: data, sys?\")\n return ERR\n for info in args:\n if info == 'sys':\n print(\"-- sys ----------------------------------------\")\n for line in info_formatter(self.coverage.sysinfo()):\n print(\" %s\" % line)\n elif info == 'data':\n print(\"-- data ---------------------------------------\")\n self.coverage.load()\n print(\"path: %s\" % self.coverage.data.filename)\n print(\"has_arcs: %r\" % self.coverage.data.has_arcs())\n summary = self.coverage.data.summary(fullpath=True)\n if summary:\n filenames = sorted(summary.keys())\n print(\"\\n%d files:\" % len(filenames))\n for f in filenames:\n print(\"%s: %d lines\" % (f, summary[f]))\n else:\n print(\"No data collected\")\n else:\n self.help_fn(\"Don't know what you mean by %r\" % info)\n return ERR\n return OK"
},
{
"code": "def read_channel(self):\n channel, message = self.protocol.channel_layer.receive_many([u'slack.send'], block=False)\n delay = 0.1\n if channel:\n self.protocols[0].sendSlack(message)\n reactor.callLater(delay, self.read_channel)"
},
{
"code": "def check_range(self, j):\n if isinstance(j, int):\n if j < 0 or j >= self.size:\n raise QiskitIndexError(\"register index out of range\")\n elif isinstance(j, slice):\n if j.start < 0 or j.stop >= self.size or (j.step is not None and\n j.step <= 0):\n raise QiskitIndexError(\"register index slice out of range\")"
},
{
"code": "def split_vert_on_nonmanifold_face(script, vert_displacement_ratio=0.0):\n filter_xml = ''.join([\n ' <filter name=\"Split Vertexes Incident on Non Manifold Faces\">\\n',\n ' <Param name=\"VertDispRatio\" ',\n 'value=\"{}\" '.format(vert_displacement_ratio),\n 'description=\"Vertex Displacement Ratio\" ',\n 'type=\"RichFloat\" ',\n '/>\\n',\n ' </filter>\\n'])\n util.write_filter(script, filter_xml)\n return None"
},
{
"code": "def strsplit(self, pattern):\n fr = H2OFrame._expr(expr=ExprNode(\"strsplit\", self, pattern))\n fr._ex._cache.nrows = self.nrow\n return fr"
},
{
"code": "def setup_cmd_parser(cls):\n parser = BackendCommandArgumentParser(cls.BACKEND.CATEGORIES,\n from_date=True,\n token_auth=True,\n archive=True)\n action = parser.parser._option_string_actions['--api-token']\n action.required = True\n group = parser.parser.add_argument_group('Slack arguments')\n group.add_argument('--max-items', dest='max_items',\n type=int, default=MAX_ITEMS,\n help=\"Maximum number of items requested on the same query\")\n parser.parser.add_argument('channel',\n help=\"Slack channel identifier\")\n return parser"
},
{
"code": "def _step_decorator_args(self, decorator):\n args = decorator.children[3:-2]\n step = None\n if len(args) == 1:\n try:\n step = ast.literal_eval(args[0].get_code())\n except (ValueError, SyntaxError):\n pass\n if isinstance(step, six.string_types+(list,)):\n return step\n logging.error(\"Decorator step accepts either a string or a list of strings - %s:%d\",\n self.file_path, decorator.start_pos[0])\n else:\n logging.error(\"Decorator step accepts only one argument - %s:%d\",\n self.file_path, decorator.start_pos[0])"
},
{
"code": "def _create_prefix(self, dirname):\n if dirname in ('.', '/'):\n dirname = ''\n prefix = os.path.join(self._bucket_root, dirname)\n prefix = prefix.rstrip('/')\n return prefix"
},
{
"code": "def build_fake_input_fns(batch_size):\n num_words = 1000\n vocabulary = [str(i) for i in range(num_words)]\n random_sample = np.random.randint(\n 10, size=(batch_size, num_words)).astype(np.float32)\n def train_input_fn():\n dataset = tf.data.Dataset.from_tensor_slices(random_sample)\n dataset = dataset.batch(batch_size).repeat()\n return tf.compat.v1.data.make_one_shot_iterator(dataset).get_next()\n def eval_input_fn():\n dataset = tf.data.Dataset.from_tensor_slices(random_sample)\n dataset = dataset.batch(batch_size)\n return tf.compat.v1.data.make_one_shot_iterator(dataset).get_next()\n return train_input_fn, eval_input_fn, vocabulary"
},
{
"code": "def voronoi(script, hole_num=50, target_layer=None, sample_layer=None, thickness=0.5, backward=True):\n if target_layer is None:\n target_layer = script.current_layer()\n if sample_layer is None:\n sampling.poisson_disk(script, sample_num=hole_num)\n sample_layer = script.last_layer()\n vert_color.voronoi(script, target_layer=target_layer, source_layer=sample_layer, backward=backward)\n select.vert_quality(script, min_quality=0.0, max_quality=thickness)\n if backward:\n select.invert(script)\n delete.selected(script)\n smooth.laplacian(script, iterations=3)\n return None"
},
{
"code": "def get_ip(self):\n if len(self.client_nodes) > 0:\n node = self.client_nodes[0]\n else:\n node = self.nodes[0]\n return node.get_ip()"
},
{
"code": "def project_dict(self, project_name, token_name, public):\n project_dict = {}\n project_dict['project_name'] = project_name\n if token_name is not None:\n if token_name == '':\n project_dict['token_name'] = project_name\n else:\n project_dict['token_name'] = token_name\n else:\n project_dict['token_name'] = project_name\n if public is not None:\n project_dict['public'] = public\n return project_dict"
},
{
"code": "def extract_tar(archive, output_folder, handle_whiteout=False):\n from .terminal import run_command\n if handle_whiteout is True:\n return _extract_tar(archive, output_folder)\n args = '-xf'\n if archive.endswith(\".tar.gz\"):\n args = '-xzf'\n command = [\"tar\", args, archive, \"-C\", output_folder, \"--exclude=dev/*\"]\n if not bot.is_quiet():\n print(\"Extracting %s\" % archive)\n return run_command(command)"
},
{
"code": "def walk_upgrade_domain(self, service_name, deployment_name,\n upgrade_domain):\n _validate_not_none('service_name', service_name)\n _validate_not_none('deployment_name', deployment_name)\n _validate_not_none('upgrade_domain', upgrade_domain)\n return self._perform_post(\n self._get_deployment_path_using_name(\n service_name, deployment_name) + '/?comp=walkupgradedomain',\n _XmlSerializer.walk_upgrade_domain_to_xml(\n upgrade_domain),\n as_async=True)"
},
{
"code": "def get_clinvar_id(self, submission_id):\n submission_obj = self.clinvar_submission_collection.find_one({'_id': ObjectId(submission_id)})\n clinvar_subm_id = submission_obj.get('clinvar_subm_id')\n return clinvar_subm_id"
},
{
"code": "def generate_sentence(self, chain):\n def weighted_choice(choices):\n total_weight = sum(weight for val, weight in choices)\n rand = random.uniform(0, total_weight)\n upto = 0\n for val, weight in choices:\n if upto + weight >= rand:\n return val\n upto += weight\n sentence = list(random.choice(chain.startwords))\n while not sentence[-1][-1] in ['.', '?', '!']:\n sentence.append(\n weighted_choice(\n chain.content[tuple(sentence[-2:])].items()\n )\n )\n return ' '.join(sentence)"
},
{
"code": "def _bisect(value_and_gradients_function, initial_args, f_lim):\n def _loop_cond(curr):\n return ~tf.reduce_all(input_tensor=curr.stopped)\n def _loop_body(curr):\n mid = value_and_gradients_function((curr.left.x + curr.right.x) / 2)\n failed = (curr.failed | ~is_finite(mid) |\n tf.equal(mid.x, curr.left.x) | tf.equal(mid.x, curr.right.x))\n to_update = ~(curr.stopped | failed)\n update_left = (mid.df < 0) & (mid.f <= f_lim)\n left = val_where(to_update & update_left, mid, curr.left)\n right = val_where(to_update & ~update_left, mid, curr.right)\n stopped = curr.stopped | failed | (right.df >= 0)\n return [_IntermediateResult(\n iteration=curr.iteration,\n stopped=stopped,\n failed=failed,\n num_evals=curr.num_evals + 1,\n left=left,\n right=right)]\n return tf.while_loop(\n cond=_loop_cond, body=_loop_body, loop_vars=[initial_args])[0]"
},
{
"code": "def from_pandas(df, name=\"pandas\", copy_index=True, index_name=\"index\"):\n import six\n vaex_df = vaex.dataframe.DataFrameArrays(name)\n def add(name, column):\n values = column.values\n try:\n vaex_df.add_column(name, values)\n except Exception as e:\n print(\"could not convert column %s, error: %r, will try to convert it to string\" % (name, e))\n try:\n values = values.astype(\"S\")\n vaex_df.add_column(name, values)\n except Exception as e:\n print(\"Giving up column %s, error: %r\" % (name, e))\n for name in df.columns:\n add(name, df[name])\n if copy_index:\n add(index_name, df.index)\n return vaex_df"
},
{
"code": "def network_to_pandas_hdf5(network, filename, rm_nodes=None):\n if rm_nodes is not None:\n nodes, edges = remove_nodes(network, rm_nodes)\n else:\n nodes, edges = network.nodes_df, network.edges_df\n with pd.HDFStore(filename, mode='w') as store:\n store['nodes'] = nodes\n store['edges'] = edges\n store['two_way'] = pd.Series([network._twoway])\n store['impedance_names'] = pd.Series(network.impedance_names)"
},
{
"code": "def build_all_iop(self):\n lg.info('Building all b and c from IOPs')\n self.build_a()\n self.build_bb()\n self.build_b()\n self.build_c()"
},
{
"code": "def _put_information(self):\r\n self.session._add_object()\r\n self.session._out('<<')\r\n self.session._out('/Producer ' + self._text_to_string(\r\n 'PDFLite, https://github.com/katerina7479'))\r\n if self.title:\r\n self.session._out('/Title ' + self._text_to_string(self.title))\r\n if self.subject:\r\n self.session._out('/Subject ' + self._text_to_string(self.subject))\r\n if self.author:\r\n self.session._out('/Author ' + self._text_to_string(self.author))\r\n if self.keywords:\r\n self.session._out('/Keywords ' +\r\n self._text_to_string(self.keywords))\r\n if self.creator:\r\n self.session._out('/Creator ' + self._text_to_string(self.creator))\r\n self.session._out('/CreationDate ' + self._text_to_string(\r\n 'D:' + datetime.now().strftime('%Y%m%d%H%M%S')))\r\n self.session._out('>>')\r\n self.session._out('endobj')"
},
{
"code": "def get_rendition_key_set(key):\n try:\n rendition_key_set = IMAGE_SETS[key]\n except KeyError:\n raise ImproperlyConfigured(\n \"No Rendition Key Set exists at \"\n \"settings.VERSATILEIMAGEFIELD_RENDITION_KEY_SETS['{}']\".format(key)\n )\n else:\n return validate_versatileimagefield_sizekey_list(rendition_key_set)"
},
{
"code": "def _method_magic_marker(magic_kind):\n validate_type(magic_kind)\n def magic_deco(arg):\n call = lambda f, *a, **k: f(*a, **k)\n if callable(arg):\n func = arg\n name = func.func_name\n retval = decorator(call, func)\n record_magic(magics, magic_kind, name, name)\n elif isinstance(arg, basestring):\n name = arg\n def mark(func, *a, **kw):\n record_magic(magics, magic_kind, name, func.func_name)\n return decorator(call, func)\n retval = mark\n else:\n raise TypeError(\"Decorator can only be called with \"\n \"string or function\")\n return retval\n magic_deco.__doc__ = _docstring_template.format('method', magic_kind)\n return magic_deco"
},
{
"code": "def get_management_certificate(self, thumbprint):\n _validate_not_none('thumbprint', thumbprint)\n return self._perform_get(\n '/' + self.subscription_id + '/certificates/' + _str(thumbprint),\n SubscriptionCertificate)"
},
{
"code": "def key_wrapping_data(self):\n key_wrapping_data = {}\n encryption_key_info = {\n 'unique_identifier': self._kdw_eki_unique_identifier,\n 'cryptographic_parameters': {\n 'block_cipher_mode': self._kdw_eki_cp_block_cipher_mode,\n 'padding_method': self._kdw_eki_cp_padding_method,\n 'hashing_algorithm': self._kdw_eki_cp_hashing_algorithm,\n 'key_role_type': self._kdw_eki_cp_key_role_type,\n 'digital_signature_algorithm':\n self._kdw_eki_cp_digital_signature_algorithm,\n 'cryptographic_algorithm':\n self._kdw_eki_cp_cryptographic_algorithm,\n 'random_iv': self._kdw_eki_cp_random_iv,\n 'iv_length': self._kdw_eki_cp_iv_length,\n 'tag_length': self._kdw_eki_cp_tag_length,\n 'fixed_field_length': self._kdw_eki_cp_fixed_field_length,\n 'invocation_field_length':\n self._kdw_eki_cp_invocation_field_length,\n 'counter_length': self._kdw_eki_cp_counter_length,\n 'initial_counter_value':\n self._kdw_eki_cp_initial_counter_value\n }\n }\n if not any(encryption_key_info['cryptographic_parameters'].values()):\n encryption_key_info['cryptographic_parameters'] = {}\n if not any(encryption_key_info.values()):\n encryption_key_info = {}\n mac_sign_key_info = {\n 'unique_identifier': self._kdw_mski_unique_identifier,\n 'cryptographic_parameters': {\n 'block_cipher_mode': self._kdw_mski_cp_block_cipher_mode,\n 'padding_method': self._kdw_mski_cp_padding_method,\n 'hashing_algorithm': self._kdw_mski_cp_hashing_algorithm,\n 'key_role_type': self._kdw_mski_cp_key_role_type,\n 'digital_signature_algorithm':\n self._kdw_mski_cp_digital_signature_algorithm,\n 'cryptographic_algorithm':\n self._kdw_mski_cp_cryptographic_algorithm,\n 'random_iv': self._kdw_mski_cp_random_iv,\n 'iv_length': self._kdw_mski_cp_iv_length,\n 'tag_length': self._kdw_mski_cp_tag_length,\n 'fixed_field_length': self._kdw_mski_cp_fixed_field_length,\n 'invocation_field_length':\n self._kdw_mski_cp_invocation_field_length,\n 'counter_length': self._kdw_mski_cp_counter_length,\n 'initial_counter_value':\n self._kdw_mski_cp_initial_counter_value\n }\n }\n if not any(mac_sign_key_info['cryptographic_parameters'].values()):\n mac_sign_key_info['cryptographic_parameters'] = {}\n if not any(mac_sign_key_info.values()):\n mac_sign_key_info = {}\n key_wrapping_data['wrapping_method'] = self._kdw_wrapping_method\n key_wrapping_data['encryption_key_information'] = encryption_key_info\n key_wrapping_data['mac_signature_key_information'] = mac_sign_key_info\n key_wrapping_data['mac_signature'] = self._kdw_mac_signature\n key_wrapping_data['iv_counter_nonce'] = self._kdw_iv_counter_nonce\n key_wrapping_data['encoding_option'] = self._kdw_encoding_option\n if not any(key_wrapping_data.values()):\n key_wrapping_data = {}\n return key_wrapping_data"
},
{
"code": "def encode(self):\n header = bytearray(1)\n varHeader = bytearray()\n payload = bytearray()\n header[0] = 0x10\n varHeader.extend(encodeString(self.version['tag'])) \n varHeader.append(self.version['level'])\n flags = (self.cleanStart << 1)\n if self.willTopic is not None and self.willMessage is not None:\n flags |= 0x04 | (self.willRetain << 5) | (self.willQoS << 3)\n if self.username is not None:\n flags |= 0x80\n if self.password is not None:\n flags |= 0x40\n varHeader.append(flags)\n varHeader.extend(encode16Int(self.keepalive))\n payload.extend(encodeString(self.clientId))\n if self.willTopic is not None and self.willMessage is not None:\n payload.extend(encodeString(self.willTopic))\n payload.extend(encodeString(self.willMessage))\n if self.username is not None:\n payload.extend(encodeString(self.username))\n if self.password is not None:\n payload.extend(encode16Int(len(self.password)))\n payload.extend(bytearray(self.password, encoding='ascii', errors='ignore'))\n header.extend(encodeLength(len(varHeader) + len(payload)))\n header.extend(varHeader)\n header.extend(payload)\n self.encoded = header\n return str(header) if PY2 else bytes(header)"
},
{
"code": "def stop_step(self, step_name):\n if self.finished is not None:\n raise AlreadyFinished()\n steps = copy.deepcopy(self.steps)\n step_data = self._get_step(step_name, steps=steps)\n if step_data is None:\n raise StepNotStarted()\n elif 'stop' in step_data:\n raise StepAlreadyFinished()\n step_data['stop'] = datetime.utcnow()\n step_data['duration'] = util.timedelta_total_seconds(step_data['stop'] - step_data['start'])\n self._save(steps=steps)"
},
{
"code": "def _notebook_model_from_db(self, record, content):\n path = to_api_path(record['parent_name'] + record['name'])\n model = base_model(path)\n model['type'] = 'notebook'\n model['last_modified'] = model['created'] = record['created_at']\n if content:\n content = reads_base64(record['content'])\n self.mark_trusted_cells(content, path)\n model['content'] = content\n model['format'] = 'json'\n self.validate_notebook_model(model)\n return model"
},
{
"code": "def signal_kernel(self, signum):\n if self.has_kernel:\n self.kernel.send_signal(signum)\n else:\n raise RuntimeError(\"Cannot signal kernel. No kernel is running!\")"
},
{
"code": "def _header_constructor(\n cls, data_to_print, header_separator=\"-\", column_separator=\" \"\n ):\n header_data = []\n header_size = \"\"\n before_size = \"%-\"\n after_size = \"s\"\n if header_separator:\n header_separator_data = []\n length_data_to_print = len(data_to_print) - 1\n i = 0\n for data in data_to_print:\n size = data_to_print[data]\n header_data.append(data)\n header_size += before_size + str(size) + after_size\n if i < length_data_to_print:\n header_size += column_separator\n if header_separator:\n header_separator_data.append(header_separator * size)\n i += 1\n if header_separator:\n return [\n header_size % tuple(header_data),\n header_size % tuple(header_separator_data),\n ]\n return [header_size % tuple(header_data)]"
},
{
"code": "def equals_order_sensitive(self, other):\n if not isinstance(other, Mapping) or len(self) != len(other):\n return False\n return all(i == j for (i, j) in izip(iteritems(self), iteritems(other)))"
},
{
"code": "def admin_footer(parser, token):\n tag_name = token.split_contents()\n if len(tag_name) > 1:\n raise base.TemplateSyntaxError(\n '{} tag does not accept any argument(s): {}'.format(\n token.contents.split()[0],\n ', '.join(token.contents.split()[1:])\n ))\n return AdminFooterNode()"
},
{
"code": "def next(self):\n val = self._current\n self._current = self.readfunc()\n return val"
},
{
"code": "def create(self):\n if not os.path.exists(self.path):\n open(self.path, 'a').close()\n else:\n raise Exception(\"File exists: {}\".format(self.path))"
},
{
"code": "def write_json_report(sample_id, data1, data2):\n parser_map = {\n \"base_sequence_quality\": \">>Per base sequence quality\",\n \"sequence_quality\": \">>Per sequence quality scores\",\n \"base_gc_content\": \">>Per sequence GC content\",\n \"base_n_content\": \">>Per base N content\",\n \"sequence_length_dist\": \">>Sequence Length Distribution\",\n \"per_base_sequence_content\": \">>Per base sequence content\"\n }\n json_dic = {\n \"plotData\": [{\n \"sample\": sample_id,\n \"data\": {\n \"base_sequence_quality\": {\"status\": None, \"data\": []},\n \"sequence_quality\": {\"status\": None, \"data\": []},\n \"base_gc_content\": {\"status\": None, \"data\": []},\n \"base_n_content\": {\"status\": None, \"data\": []},\n \"sequence_length_dist\": {\"status\": None, \"data\": []},\n \"per_base_sequence_content\": {\"status\": None, \"data\": []}\n }\n }]\n }\n for cat, start_str in parser_map.items():\n if cat == \"per_base_sequence_content\":\n fs = 1\n fe = 5\n else:\n fs = 1\n fe = 2\n report1, status1 = _get_quality_stats(data1, start_str,\n field_start=fs, field_end=fe)\n report2, status2 = _get_quality_stats(data2, start_str,\n field_start=fs, field_end=fe)\n status = None\n for i in [\"fail\", \"warn\", \"pass\"]:\n if i in [status1, status2]:\n status = i\n json_dic[\"plotData\"][0][\"data\"][cat][\"data\"] = [report1, report2]\n json_dic[\"plotData\"][0][\"data\"][cat][\"status\"] = status\n return json_dic"
},
{
"code": "def case_insensitive(self, fields_dict):\n if hasattr(self.model, 'CASE_INSENSITIVE_FIELDS'):\n for field in self.model.CASE_INSENSITIVE_FIELDS:\n if field in fields_dict:\n fields_dict[field + '__iexact'] = fields_dict[field]\n del fields_dict[field]"
},
{
"code": "def trim_data_back_to(monthToKeep):\n global g_failed_tests_info_dict\n current_time = time.time()\n oldest_time_allowed = current_time - monthToKeep*30*24*3600\n clean_up_failed_test_dict(oldest_time_allowed)\n clean_up_summary_text(oldest_time_allowed)"
},
{
"code": "def fill(self, doc_contents):\n for key, content in doc_contents.items():\n doc_contents[key] = replace_chars_for_svg_code(content)\n return super(SVGDocument, self).fill(doc_contents=doc_contents)"
},
{
"code": "def In(sigOrVal, iterable):\n res = None\n for i in iterable:\n i = toHVal(i)\n if res is None:\n res = sigOrVal._eq(i)\n else:\n res = res | sigOrVal._eq(i)\n assert res is not None, \"Parameter iterable is empty\"\n return res"
},
{
"code": "def set_client_certificate(self, certificate):\n _certificate = BSTR(certificate)\n _WinHttpRequest._SetClientCertificate(self, _certificate)"
},
{
"code": "def validate_chunks(self, chunks):\n starts = set([ch.byte for ch in chunks])\n for ch in chunks:\n assert all([(ex in starts or ex < 0) for ex in ch.exits])"
},
{
"code": "def get_external_tools_in_account(self, account_id, params={}):\n url = ACCOUNTS_API.format(account_id) + \"/external_tools\"\n external_tools = []\n for data in self._get_paged_resource(url, params=params):\n external_tools.append(data)\n return external_tools"
},
{
"code": "def execute(self, context):\n self.hook = DiscordWebhookHook(\n self.http_conn_id,\n self.webhook_endpoint,\n self.message,\n self.username,\n self.avatar_url,\n self.tts,\n self.proxy\n )\n self.hook.execute()"
},
{
"code": "def make_dict_observable(matrix_observable):\n dict_observable = {}\n observable = np.array(matrix_observable)\n observable_size = len(observable)\n observable_bits = int(np.ceil(np.log2(observable_size)))\n binary_formater = '0{}b'.format(observable_bits)\n if observable.ndim == 2:\n observable = observable.diagonal()\n for state_no in range(observable_size):\n state_str = format(state_no, binary_formater)\n dict_observable[state_str] = observable[state_no]\n return dict_observable"
},
{
"code": "def _check_wiremap_validity(self, wire_map, keymap, valmap):\n for k, v in wire_map.items():\n kname = \"%s[%d]\" % (k[0].name, k[1])\n vname = \"%s[%d]\" % (v[0].name, v[1])\n if k not in keymap:\n raise DAGCircuitError(\"invalid wire mapping key %s\" % kname)\n if v not in valmap:\n raise DAGCircuitError(\"invalid wire mapping value %s\" % vname)\n if type(k) is not type(v):\n raise DAGCircuitError(\"inconsistent wire_map at (%s,%s)\" %\n (kname, vname))"
},
{
"code": "def pformat_dict_summary_html(dict):\n if not dict:\n return ' {}'\n html = []\n for key, value in sorted(six.iteritems(dict)):\n if not isinstance(value, DICT_EXPANDED_TYPES):\n value = '...'\n html.append(_format_dict_item(key, value))\n return mark_safe(u'<br/>'.join(html))"
},
{
"code": "def selected(self):\n if self._selected:\n return self._selected if self.asc else \\\n \"-{0}\".format(self._selected)\n return None"
},
{
"code": "def _helpful_failure(method):\n @wraps(method)\n def wrapper(self, val):\n try:\n return method(self, val)\n except:\n exc_cls, inst, tb = sys.exc_info()\n if hasattr(inst, '_RERAISE'):\n _, expr, _, inner_val = Q.__debug_info__\n Q.__debug_info__ = QDebug(self, expr, val, inner_val)\n raise\n if issubclass(exc_cls, KeyError):\n exc_cls = QKeyError\n prettyval = repr(val)\n if len(prettyval) > 150:\n prettyval = \"<%s instance>\" % (type(val).__name__)\n msg = \"{0}\\n\\n\\tEncountered when evaluating {1}{2}\".format(\n inst, prettyval, self)\n new_exc = exc_cls(msg)\n new_exc._RERAISE = True\n Q.__debug_info__ = QDebug(self, self, val, val)\n six.reraise(exc_cls, new_exc, tb)\n return wrapper"
},
{
"code": "def _add_to_tree(self, start_node, split_names, type_name, group_type_name,\n instance, constructor, args, kwargs):\n try:\n act_node = start_node\n last_idx = len(split_names) - 1\n add_link = type_name == LINK\n link_added = False\n for idx, name in enumerate(split_names):\n if name not in act_node._children:\n if idx == last_idx:\n if add_link:\n new_node = self._create_link(act_node, name, instance)\n link_added = True\n elif group_type_name != type_name:\n new_node = self._create_any_param_or_result(act_node,\n name,\n type_name,\n instance,\n constructor,\n args, kwargs)\n self._flat_leaf_storage_dict[new_node.v_full_name] = new_node\n else:\n new_node = self._create_any_group(act_node, name,\n group_type_name,\n instance,\n constructor,\n args, kwargs)\n else:\n new_node = self._create_any_group(act_node, name,\n group_type_name)\n if name in self._root_instance._run_information:\n self._root_instance._run_parent_groups[act_node.v_full_name] = act_node\n if self._root_instance._is_run:\n if link_added:\n self._root_instance._new_links[(act_node.v_full_name, name)] = \\\n (act_node, new_node)\n else:\n self._root_instance._new_nodes[(act_node.v_full_name, name)] = \\\n (act_node, new_node)\n else:\n if name in act_node._links:\n raise AttributeError('You cannot hop over links when adding '\n 'data to the tree. '\n 'There is a link called `%s` under `%s`.' %\n (name, act_node.v_full_name))\n if idx == last_idx:\n if self._root_instance._no_clobber:\n self._logger.warning('You already have a group/instance/link `%s` '\n 'under `%s`. '\n 'However, you set `v_no_clobber=True`, '\n 'so I will ignore your addition of '\n 'data.' % (name, act_node.v_full_name))\n else:\n raise AttributeError('You already have a group/instance/link `%s` '\n 'under `%s`' % (name, act_node.v_full_name))\n act_node = act_node._children[name]\n return act_node\n except:\n self._logger.error('Failed adding `%s` under `%s`.' %\n (name, start_node.v_full_name))\n raise"
},
{
"code": "def tostring(self):\n root = self.as_element()\n indent(root)\n txt = ET.tostring(root, encoding=\"utf-8\")\n txt = re.sub(r'_[A-Z]_','',txt)\n txt = '<?xml version=\"1.0\" encoding=\"utf-8\"?>\\n' + txt\n return txt"
},
{
"code": "def __head(self,h):\n return '%s%s%s' % (self.color_table.active_colors.header,h,\n self.color_table.active_colors.normal)"
},
{
"code": "def publish(\n self, resource_group_name, automation_account_name, runbook_name, custom_headers=None, raw=False, polling=True, **operation_config):\n raw_result = self._publish_initial(\n resource_group_name=resource_group_name,\n automation_account_name=automation_account_name,\n runbook_name=runbook_name,\n custom_headers=custom_headers,\n raw=True,\n **operation_config\n )\n def get_long_running_output(response):\n if raw:\n client_raw_response = ClientRawResponse(None, response)\n client_raw_response.add_headers({\n 'location': 'str',\n })\n return client_raw_response\n lro_delay = operation_config.get(\n 'long_running_operation_timeout',\n self.config.long_running_operation_timeout)\n if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)\n elif polling is False: polling_method = NoPolling()\n else: polling_method = polling\n return LROPoller(self._client, raw_result, get_long_running_output, polling_method)"
},
{
"code": "def get_rules(self) -> parsing.Node:\n res = None\n try:\n res = self.eval_rule('bnf_dsl')\n if not res:\n self.diagnostic.notify(\n error.Severity.ERROR,\n \"Parse error in '%s' in EBNF bnf\" % self._lastRule,\n error.LocationInfo.from_maxstream(self._stream)\n )\n raise self.diagnostic\n except error.Diagnostic as d:\n d.notify(\n error.Severity.ERROR,\n \"Parse error in '%s' in EBNF bnf\" % self._lastRule\n )\n raise d\n return res"
},
{
"code": "def save(self, filename=None, deleteid3=False):\n if filename is None:\n filename = self.filename\n f = open(filename, 'rb+')\n try:\n self.metadata_blocks.append(Padding(b'\\x00' * 1020))\n MetadataBlock.group_padding(self.metadata_blocks)\n header = self.__check_header(f)\n available = self.__find_audio_offset(f) - header\n data = MetadataBlock.writeblocks(self.metadata_blocks)\n if deleteid3 and header > 4:\n available += header - 4\n header = 4\n if len(data) > available:\n padding = self.metadata_blocks[-1]\n newlength = padding.length - (len(data) - available)\n if newlength > 0:\n padding.length = newlength\n data = MetadataBlock.writeblocks(self.metadata_blocks)\n assert len(data) == available\n elif len(data) < available:\n self.metadata_blocks[-1].length += (available - len(data))\n data = MetadataBlock.writeblocks(self.metadata_blocks)\n assert len(data) == available\n if len(data) != available:\n diff = (len(data) - available)\n insert_bytes(f, diff, header)\n f.seek(header - 4)\n f.write(b\"fLaC\" + data)\n if deleteid3:\n try:\n f.seek(-128, 2)\n except IOError:\n pass\n else:\n if f.read(3) == b\"TAG\":\n f.seek(-128, 2)\n f.truncate()\n finally:\n f.close()"
},
{
"code": "def text(self, etype, value, tb, tb_offset=None, context=5):\n tb_list = self.structured_traceback(etype, value, tb,\n tb_offset, context)\n return self.stb2text(tb_list)"
},
{
"code": "def child_object(self):\n from . import types\n child_klass = types.get(self.task_type.split('.')[1])\n return child_klass.retrieve(self.task_id, client=self._client)"
},
{
"code": "def controller_factory(cls, passes, options, **partial_controller):\n if None in partial_controller.values():\n raise TranspilerError('The controller needs a condition.')\n if partial_controller:\n for registered_controller in cls.registered_controllers.keys():\n if registered_controller in partial_controller:\n return cls.registered_controllers[registered_controller](passes, options,\n **partial_controller)\n raise TranspilerError(\"The controllers for %s are not registered\" % partial_controller)\n else:\n return FlowControllerLinear(passes, options)"
},
{
"code": "def sprint(text, *colors):\n return \"\\33[{}m{content}\\33[{}m\".format(\";\".join([str(color) for color in colors]), RESET, content=text) if IS_ANSI_TERMINAL and colors else text"
},
{
"code": "def __build_question(html_question, question, comments):\n question_object = {}\n question_container = AskbotParser.parse_question_container(html_question[0])\n question_object.update(question_container)\n if comments[int(question['id'])]:\n question_object['comments'] = comments[int(question['id'])]\n answers = []\n for page in html_question:\n answers.extend(AskbotParser.parse_answers(page))\n if len(answers) != 0:\n question_object['answers'] = answers\n for answer in question_object['answers']:\n if comments[int(answer['id'])]:\n answer['comments'] = comments[int(answer['id'])]\n return question_object"
},
{
"code": "def gpio_interrupts_enable(self):\n try:\n bring_gpio_interrupt_into_userspace()\n set_gpio_interrupt_edge()\n except Timeout as e:\n raise InterruptEnableException(\n \"There was an error bringing gpio%d into userspace. %s\" %\n (GPIO_INTERRUPT_PIN, e.message)\n )"
},
{
"code": "def request(self, method, url, **kwargs):\n opts = {\n 'allow_redirects': True,\n 'auth': self._auth,\n 'data': {},\n 'files': None,\n 'headers': dict(self._headers),\n 'params': {},\n 'timeout': 80,\n 'verify': True\n }\n raw = kwargs.pop('raw', False)\n debug = kwargs.pop('debug', False)\n opts.update(kwargs)\n method = method.upper()\n if opts['files']:\n opts['headers'].pop('Content-Type', None)\n else:\n opts['data'] = json.dumps(opts['data'])\n if not url.startswith(self._host):\n url = urljoin(self._host, url)\n logger.debug('API %s Request: %s' % (method, url))\n if debug:\n self._log_raw_request(method, url, **opts)\n try:\n response = self._session.request(method, url, **opts)\n except Exception as e:\n _handle_request_error(e)\n if 429 == response.status_code:\n delay = int(response.headers['retry-after']) + 1\n logger.warn('Too many requests. Retrying in {0}s.'.format(delay))\n time.sleep(delay)\n return self.request(method, url, **kwargs)\n if not (200 <= response.status_code < 400):\n _handle_api_error(response)\n if raw or response.status_code in [204, 301, 302]:\n return response\n return response.json()"
},
{
"code": "def make_default_options_response(self):\n adapter = _request_ctx_stack.top.url_adapter\n if hasattr(adapter, 'allowed_methods'):\n methods = adapter.allowed_methods()\n else:\n methods = []\n try:\n adapter.match(method='--')\n except MethodNotAllowed as e:\n methods = e.valid_methods\n except HTTPException as e:\n pass\n rv = self.response_class()\n rv.allow.update(methods)\n return rv"
},
{
"code": "def load(self, path):\n self.network = graph.Network.load(path)\n return self.network"
},
{
"code": "def _uri2path(self, uri):\n if uri == self.package_name:\n return os.path.join(self.root_path, '__init__.py')\n path = uri.replace('.', os.path.sep)\n path = path.replace(self.package_name + os.path.sep, '')\n path = os.path.join(self.root_path, path)\n if os.path.exists(path + '.py'):\n path += '.py'\n elif os.path.exists(os.path.join(path, '__init__.py')):\n path = os.path.join(path, '__init__.py')\n else:\n return None\n return path"
},
{
"code": "def describe_object(self, obj):\n conn = self.get_conn()\n return conn.__getattr__(obj).describe()"
},
{
"code": "def get_ilvl(li, w_namespace):\n ilvls = li.xpath('.//w:ilvl', namespaces=li.nsmap)\n if len(ilvls) == 0:\n return -1\n return int(ilvls[0].get('%sval' % w_namespace))"
},
{
"code": "def validateAttrib(self, method, cls = None):\n any = False\n for group in self.attribs:\n match = True\n for key, value in group:\n attr = get_method_attr(method, cls, key)\n if callable(value):\n if not value(key, method, cls):\n match = False\n break\n elif value is True:\n if not bool(attr):\n match = False\n break\n elif value is False:\n if bool(attr):\n match = False\n break\n elif type(attr) in (list, tuple):\n if not str(value).lower() in [str(x).lower()\n for x in attr]:\n match = False\n break\n else:\n if (value != attr\n and str(value).lower() != str(attr).lower()):\n match = False\n break\n any = any or match\n if any:\n return None\n return False"
},
{
"code": "def matchmaker_matches(institute_id, case_name):\n user_obj = store.user(current_user.email)\n if 'mme_submitter' not in user_obj['roles']:\n flash('unauthorized request', 'warning')\n return redirect(request.referrer)\n mme_base_url = current_app.config.get('MME_URL')\n mme_token = current_app.config.get('MME_TOKEN')\n if not mme_base_url or not mme_token:\n flash('An error occurred reading matchmaker connection parameters. Please check config file!', 'danger')\n return redirect(request.referrer)\n institute_obj, case_obj = institute_and_case(store, institute_id, case_name)\n data = controllers.mme_matches(case_obj, institute_obj, mme_base_url, mme_token)\n if data and data.get('server_errors'):\n flash('MatchMaker server returned error:{}'.format(data['server_errors']), 'danger')\n return redirect(request.referrer)\n elif not data:\n data = {\n 'institute' : institute_obj,\n 'case' : case_obj\n }\n return data"
},
{
"code": "def get_container(self, name, collection_id, tag=\"latest\", version=None):\n from sregistry.database.models import Container\n if version is None:\n container = Container.query.filter_by(collection_id = collection_id,\n name = name,\n tag = tag).first()\n else:\n container = Container.query.filter_by(collection_id = collection_id,\n name = name,\n tag = tag,\n version = version).first()\n return container"
},
{
"code": "def _plant_trie(strings: _List[str]) -> dict:\n trie = {}\n for string in strings:\n d = trie\n for char in string:\n d[char] = char in d and d[char] or {}\n d = d[char]\n d[''] = None\n return trie"
},
{
"code": "def _is_known_unsigned_by_dtype(dt):\n return {\n tf.bool: True,\n tf.uint8: True,\n tf.uint16: True,\n }.get(dt.base_dtype, False)"
},
{
"code": "def create_record_and_pid(data):\n from invenio_records.api import Record\n from invenio_pidstore.models import PersistentIdentifier, PIDStatus, \\\n RecordIdentifier\n deposit = Record.create(data=data)\n created = arrow.get(data['_p']['created']).datetime\n deposit.model.created = created.replace(tzinfo=None)\n depid = deposit['_p']['id']\n pid = PersistentIdentifier.create(\n pid_type='depid',\n pid_value=str(depid),\n object_type='rec',\n object_uuid=str(deposit.id),\n status=PIDStatus.REGISTERED\n )\n if RecordIdentifier.query.get(int(depid)) is None:\n RecordIdentifier.insert(int(depid))\n deposit.commit()\n return deposit, pid"
},
{
"code": "def is_embargoed(record):\n return record.get('access_right') == 'embargoed' and \\\n record.get('embargo_date') and \\\n record.get('embargo_date') > datetime.utcnow().date()"
},
{
"code": "def add_comment(self, comment_text):\n return self.fetch_json(\n uri_path=self.base_uri + '/actions/comments',\n http_method='POST',\n query_params={'text': comment_text}\n )"
},
{
"code": "def pkt_text(pkt):\n if pkt.src.upper() in BANNED_DEVICES:\n body = ''\n elif pkt.src.upper()[:8] in AMAZON_DEVICES:\n body = '{} (Amazon Device)'.format(pkt.src)\n else:\n body = pkt.src\n return body"
},
{
"code": "def _update_barrier_status(self):\n with open(self.log_file) as fh:\n for line in fh:\n if \"Session aborted\" in line:\n return\n if \"<<< barrier arrive\" in line:\n process_m = re.match(\".*process: (.*)\\)\", line)\n if process_m:\n process = process_m.group(1)\n if process in self.processes:\n self.processes[process][\"barrier\"] = \"C\""
},
{
"code": "def copy_notebook(self, notebook_id):\n last_mod, nb = self.get_notebook_object(notebook_id)\n name = nb.metadata.name + '-Copy'\n path, name = self.increment_filename(name)\n nb.metadata.name = name\n notebook_id = self.new_notebook_id(name)\n self.save_notebook_object(notebook_id, nb)\n return notebook_id"
},
{
"code": "def entity_name_decorator(top_cls):\n class_name = inflection.underscore(top_cls.__name__).lower()\n def entity_name(cls):\n return class_name\n top_cls.entity_name = classmethod(entity_name)\n return top_cls"
},
{
"code": "def init_modules(self):\n if not self.config:\n raise ValueError(\"please read your config file.\")\n log.debug(\"begin to import customer's service modules.\")\n modules = ServiceModules(self.config)\n modules.import_modules()\n log.debug(\"end to import customer's service modules.\")"
},
{
"code": "def _normalized(self, data):\n int_keys = ('frames', 'width', 'height', 'size')\n for key in int_keys:\n if key not in data:\n continue\n try:\n data[key] = int(data[key])\n except ValueError:\n pass\n return data"
},
{
"code": "def get_product_by_name(self, name):\n return next(i for i in self.items if i.name.lower() == name.lower())"
},
{
"code": "def add_point(self, point, value, check=True):\n if self.tier_type != 'TextTier':\n raise Exception('Tiertype must be TextTier.')\n if check and any(i for i in self.intervals if i[0] == point):\n raise Exception('No overlap is allowed')\n self.intervals.append((point, value))"
},
{
"code": "def create_adapter(cmph, ffi, obj):\n if is_file_location(obj):\n fd = open(obj)\n adapter = cmph.cmph_io_nlfile_adapter(fd)\n def dtor():\n cmph.cmph_io_nlfile_adapter_destroy(adapter)\n fd.close()\n return _AdapterCxt(adapter, dtor)\n elif is_file(obj):\n adapter = cmph.cmph_io_nlfile_adapter(obj)\n dtor = lambda: cmph.cmph_io_nlfile_adapter_destroy(adapter)\n return _AdapterCxt(adapter, dtor)\n elif isinstance(obj, Sequence):\n if len(obj) == 0:\n raise ValueError(\"An empty sequence is already a perfect hash!\")\n return _create_pyobj_adapter(cmph, ffi, obj)\n else:\n raise ValueError(\"data cannot have a cmph wrapper generated\")"
},
{
"code": "def _hash_file(self, algo):\n hash_data = getattr(hashlib, algo)()\n with open(self.path, \"rb\") as file:\n content = file.read()\n hash_data.update(content)\n return hash_data.hexdigest()"
},
{
"code": "def to_string(self, indent):\n ind = indent * ' '\n print(ind, 'qreg')\n self.children[0].to_string(indent + 3)"
},
{
"code": "def _installation_trace(self, frame_unused, event_unused, arg_unused):\n sys.settrace(None)\n fn = self._start_tracer()\n if fn:\n fn = fn(frame_unused, event_unused, arg_unused)\n return fn"
},
{
"code": "def parse_sv_frequencies(variant):\n frequency_keys = [\n 'clingen_cgh_benignAF',\n 'clingen_cgh_benign',\n 'clingen_cgh_pathogenicAF',\n 'clingen_cgh_pathogenic',\n 'clingen_ngi',\n 'clingen_ngiAF',\n 'swegen',\n 'swegenAF',\n 'decipherAF',\n 'decipher'\n ]\n sv_frequencies = {}\n for key in frequency_keys:\n value = variant.INFO.get(key, 0)\n if 'AF' in key:\n value = float(value)\n else:\n value = int(value)\n if value > 0:\n sv_frequencies[key] = value\n return sv_frequencies"
},
{
"code": "def calc_fwhm(distribution, is_neg_log=True):\n if isinstance(distribution, interp1d):\n if is_neg_log:\n ymin = distribution.y.min()\n log_prob = distribution.y-ymin\n else:\n log_prob = -np.log(distribution.y)\n log_prob -= log_prob.min()\n xvals = distribution.x\n elif isinstance(distribution, Distribution):\n xvals = distribution._func.x\n log_prob = distribution._func.y\n else:\n raise TypeError(\"Error in computing the FWHM for the distribution. \"\n \" The input should be either Distribution or interpolation object\");\n L = xvals.shape[0]\n tmp = np.where(log_prob < 0.693147)[0]\n x_l, x_u = tmp[0], tmp[-1]\n if L < 2:\n print (\"Not enough points to compute FWHM: returning zero\")\n return min(TINY_NUMBER, distribution.xmax - distribution.xmin)\n else:\n return max(TINY_NUMBER, xvals[min(x_u+1,L-1)] - xvals[max(0,x_l-1)])"
},
{
"code": "def submit_order(self, symbol, qty, side, type, time_in_force,\n limit_price=None, stop_price=None, client_order_id=None):\n params = {\n 'symbol': symbol,\n 'qty': qty,\n 'side': side,\n 'type': type,\n 'time_in_force': time_in_force,\n }\n if limit_price is not None:\n params['limit_price'] = limit_price\n if stop_price is not None:\n params['stop_price'] = stop_price\n if client_order_id is not None:\n params['client_order_id'] = client_order_id\n resp = self.post('/orders', params)\n return Order(resp)"
},
{
"code": "def get_queryset(self):\n queryset = self.get_publishable_queryset()\n queryset = queryset \\\n .select_related('featured_image', 'featured_video', 'topic', 'section', 'subsection') \\\n .prefetch_related(\n 'tags',\n 'featured_image__image__authors',\n 'authors'\n )\n queryset = queryset.order_by('-updated_at')\n q = self.request.query_params.get('q', None)\n section = self.request.query_params.get('section', None)\n tags = self.request.query_params.getlist('tags', None)\n author = self.request.query_params.get('author', None)\n if q is not None:\n queryset = queryset.filter(headline__icontains=q)\n if section is not None:\n queryset = queryset.filter(section_id=section)\n if tags is not None:\n for tag in tags:\n queryset = queryset.filter(tags__id=tag)\n if author is not None:\n queryset = queryset.filter(authors__person_id=author)\n return queryset"
},
{
"code": "def get_instance_group_manager(self, zone, resource_id, project_id=None):\n response = self.get_conn().instanceGroupManagers().get(\n project=project_id,\n zone=zone,\n instanceGroupManager=resource_id\n ).execute(num_retries=self.num_retries)\n return response"
},
{
"code": "def get_contacts(address_books, query, method=\"all\", reverse=False,\n group=False, sort=\"first_name\"):\n contacts = []\n for address_book in address_books:\n contacts.extend(address_book.search(query, method=method))\n if group:\n if sort == \"first_name\":\n return sorted(contacts, reverse=reverse, key=lambda x: (\n unidecode(x.address_book.name).lower(),\n unidecode(x.get_first_name_last_name()).lower()))\n elif sort == \"last_name\":\n return sorted(contacts, reverse=reverse, key=lambda x: (\n unidecode(x.address_book.name).lower(),\n unidecode(x.get_last_name_first_name()).lower()))\n else:\n raise ValueError('sort must be \"first_name\" or \"last_name\" not '\n '{}.'.format(sort))\n else:\n if sort == \"first_name\":\n return sorted(contacts, reverse=reverse, key=lambda x:\n unidecode(x.get_first_name_last_name()).lower())\n elif sort == \"last_name\":\n return sorted(contacts, reverse=reverse, key=lambda x:\n unidecode(x.get_last_name_first_name()).lower())\n else:\n raise ValueError('sort must be \"first_name\" or \"last_name\" not '\n '{}.'.format(sort))"
},
{
"code": "def remove_property(self, property_):\n if property_.name in self.properties:\n del self.properties[property_.name]"
},
{
"code": "def delete(self, filename=None):\n if filename is None:\n filename = self.filename\n delete(filename)\n self.clear()"
},
{
"code": "def DeleteAllItems(self):\r\n \"Remove all the item from the list and unset the related data\"\r\n self._py_data_map.clear()\r\n self._wx_data_map.clear()\r\n wx.ListCtrl.DeleteAllItems(self)"
},
{
"code": "def phone_subcommand(search_terms, vcard_list, parsable):\n all_phone_numbers_list = []\n matching_phone_number_list = []\n for vcard in vcard_list:\n for type, number_list in sorted(vcard.get_phone_numbers().items(),\n key=lambda k: k[0].lower()):\n for number in sorted(number_list):\n if config.display_by_name() == \"first_name\":\n name = vcard.get_first_name_last_name()\n else:\n name = vcard.get_last_name_first_name()\n line_formatted = \"\\t\".join([name, type, number])\n line_parsable = \"\\t\".join([number, name, type])\n if parsable:\n phone_number_line = line_parsable\n else:\n phone_number_line = line_formatted\n if re.search(search_terms,\n \"%s\\n%s\" % (line_formatted, line_parsable),\n re.IGNORECASE | re.DOTALL):\n matching_phone_number_list.append(phone_number_line)\n elif len(re.sub(\"\\D\", \"\", search_terms)) >= 3:\n if re.search(re.sub(\"\\D\", \"\", search_terms),\n re.sub(\"\\D\", \"\", number), re.IGNORECASE):\n matching_phone_number_list.append(phone_number_line)\n all_phone_numbers_list.append(phone_number_line)\n if matching_phone_number_list:\n if parsable:\n print('\\n'.join(matching_phone_number_list))\n else:\n list_phone_numbers(matching_phone_number_list)\n elif all_phone_numbers_list:\n if parsable:\n print('\\n'.join(all_phone_numbers_list))\n else:\n list_phone_numbers(all_phone_numbers_list)\n else:\n if not parsable:\n print(\"Found no phone numbers\")\n sys.exit(1)"
},
{
"code": "def add_and_rename_file(self, filename: str, new_filename: str) -> None:\n dest = os.path.join(\n self.name + ':' + SANDBOX_WORKING_DIR_NAME,\n new_filename)\n subprocess.check_call(['docker', 'cp', filename, dest])\n self._chown_files([new_filename])"
},
{
"code": "def parse_frequencies(variant, transcripts):\n frequencies = {}\n thousand_genomes_keys = ['1000GAF']\n thousand_genomes_max_keys = ['1000G_MAX_AF']\n exac_keys = ['EXACAF']\n exac_max_keys = ['ExAC_MAX_AF', 'EXAC_MAX_AF']\n gnomad_keys = ['GNOMADAF', 'GNOMAD_AF']\n gnomad_max_keys = ['GNOMADAF_POPMAX', 'GNOMADAF_MAX']\n for test_key in thousand_genomes_keys:\n thousand_g = parse_frequency(variant, test_key)\n if thousand_g:\n frequencies['thousand_g'] = thousand_g\n break\n for test_key in thousand_genomes_max_keys:\n thousand_g_max = parse_frequency(variant, test_key)\n if thousand_g_max:\n frequencies['thousand_g_max'] = thousand_g_max\n break\n for test_key in exac_keys:\n exac = parse_frequency(variant, test_key)\n if exac:\n frequencies['exac'] = exac\n break\n for test_key in exac_max_keys:\n exac_max = parse_frequency(variant, test_key)\n if exac_max:\n frequencies['exac_max'] = exac_max\n break\n for test_key in gnomad_keys:\n gnomad = parse_frequency(variant, test_key)\n if gnomad:\n frequencies['gnomad'] = gnomad\n break\n for test_key in gnomad_max_keys:\n gnomad_max = parse_frequency(variant, test_key)\n if gnomad_max:\n frequencies['gnomad_max'] = gnomad_max\n break\n if not frequencies:\n for transcript in transcripts:\n exac = transcript.get('exac_maf')\n exac_max = transcript.get('exac_max')\n thousand_g = transcript.get('thousand_g_maf')\n thousandg_max = transcript.get('thousandg_max')\n gnomad = transcript.get('gnomad_maf')\n gnomad_max = transcript.get('gnomad_max')\n if exac:\n frequencies['exac'] = exac\n if exac_max:\n frequencies['exac_max'] = exac_max\n if thousand_g:\n frequencies['thousand_g'] = thousand_g\n if thousandg_max:\n frequencies['thousand_g_max'] = thousandg_max\n if gnomad:\n frequencies['gnomad'] = gnomad\n if gnomad_max:\n frequencies['gnomad_max'] = gnomad_max\n thousand_g_left = parse_frequency(variant, 'left_1000GAF')\n if thousand_g_left:\n frequencies['thousand_g_left'] = thousand_g_left\n thousand_g_right = parse_frequency(variant, 'right_1000GAF')\n if thousand_g_right:\n frequencies['thousand_g_right'] = thousand_g_right\n return frequencies"
},
{
"code": "def random(cls, num_qubits, seed=None):\n if seed is not None:\n np.random.seed(seed)\n z = np.random.randint(2, size=num_qubits).astype(np.bool)\n x = np.random.randint(2, size=num_qubits).astype(np.bool)\n return cls(z, x)"
},
{
"code": "def lost_dimensions(point_fmt_in, point_fmt_out):\n unpacked_dims_in = PointFormat(point_fmt_in).dtype\n unpacked_dims_out = PointFormat(point_fmt_out).dtype\n out_dims = unpacked_dims_out.fields\n completely_lost = []\n for dim_name in unpacked_dims_in.names:\n if dim_name not in out_dims:\n completely_lost.append(dim_name)\n return completely_lost"
},
{
"code": "def rename(script, label='blank', layer_num=None):\n filter_xml = ''.join([\n ' <filter name=\"Rename Current Mesh\">\\n',\n ' <Param name=\"newName\" ',\n 'value=\"{}\" '.format(label),\n 'description=\"New Label\" ',\n 'type=\"RichString\" ',\n '/>\\n',\n ' </filter>\\n'])\n if isinstance(script, mlx.FilterScript):\n if (layer_num is None) or (layer_num == script.current_layer()):\n util.write_filter(script, filter_xml)\n script.layer_stack[script.current_layer()] = label\n else:\n cur_layer = script.current_layer()\n change(script, layer_num)\n util.write_filter(script, filter_xml)\n change(script, cur_layer)\n script.layer_stack[layer_num] = label\n else:\n util.write_filter(script, filter_xml)\n return None"
},
{
"code": "def verify_signature(amazon_cert: crypto.X509, signature: str, request_body: bytes) -> bool:\n signature = base64.b64decode(signature)\n try:\n crypto.verify(amazon_cert, signature, request_body, 'sha1')\n result = True\n except crypto.Error:\n result = False\n return result"
},
{
"code": "def parallel_execute(self, cell, block=None, groupby='type', save_name=None):\n block = self.view.block if block is None else block\n base = \"Parallel\" if block else \"Async parallel\"\n targets = self.view.targets\n if isinstance(targets, list) and len(targets) > 10:\n str_targets = str(targets[:4])[:-1] + ', ..., ' + str(targets[-4:])[1:]\n else:\n str_targets = str(targets)\n if self.verbose:\n print base + \" execution on engine(s): %s\" % str_targets\n result = self.view.execute(cell, silent=False, block=False)\n self.last_result = result\n if save_name:\n self.shell.user_ns[save_name] = result\n if block:\n result.get()\n result.display_outputs(groupby)\n else:\n return result"
},
{
"code": "def class_is_abstract(node: astroid.ClassDef) -> bool:\n for method in node.methods():\n if method.parent.frame() is node:\n if method.is_abstract(pass_is_abstract=False):\n return True\n return False"
},
{
"code": "def _merge_statements(statements: List[\"HdlStatement\"])\\\n -> Tuple[List[\"HdlStatement\"], int]:\n order = {}\n for i, stm in enumerate(statements):\n order[stm] = i\n new_statements = []\n rank_decrease = 0\n for rank, stms in groupedby(statements, lambda s: s.rank):\n if rank == 0:\n new_statements.extend(stms)\n else:\n if len(stms) == 1:\n new_statements.extend(stms)\n continue\n for iA, stmA in enumerate(stms):\n if stmA is None:\n continue\n for iB, stmB in enumerate(islice(stms, iA + 1, None)):\n if stmB is None:\n continue\n if stmA._is_mergable(stmB):\n rank_decrease += stmB.rank\n stmA._merge_with_other_stm(stmB)\n stms[iA + 1 + iB] = None\n new_statements.append(stmA)\n else:\n new_statements.append(stmA)\n new_statements.append(stmB)\n new_statements.sort(key=lambda stm: order[stm])\n return new_statements, rank_decrease"
},
{
"code": "def convert(self, value):\n if not isinstance(value, ConvertingDict) and isinstance(value, dict):\n value = ConvertingDict(value)\n value.configurator = self\n elif not isinstance(value, ConvertingList) and isinstance(value, list):\n value = ConvertingList(value)\n value.configurator = self\n elif not isinstance(value, ConvertingTuple) and\\\n isinstance(value, tuple):\n value = ConvertingTuple(value)\n value.configurator = self\n elif isinstance(value, six.string_types):\n m = self.CONVERT_PATTERN.match(value)\n if m:\n d = m.groupdict()\n prefix = d['prefix']\n converter = self.value_converters.get(prefix, None)\n if converter:\n suffix = d['suffix']\n converter = getattr(self, converter)\n value = converter(suffix)\n return value"
},
{
"code": "def bind_parameter(binding_key, value):\n if config_is_locked():\n raise RuntimeError('Attempted to modify locked Gin config.')\n pbk = ParsedBindingKey(binding_key)\n fn_dict = _CONFIG.setdefault(pbk.config_key, {})\n fn_dict[pbk.arg_name] = value"
},
{
"code": "def verify_signature(self,\n signing_key,\n message,\n signature,\n padding_method,\n signing_algorithm=None,\n hashing_algorithm=None,\n digital_signature_algorithm=None):\n backend = default_backend()\n hash_algorithm = None\n dsa_hash_algorithm = None\n dsa_signing_algorithm = None\n if hashing_algorithm:\n hash_algorithm = self._encryption_hash_algorithms.get(\n hashing_algorithm\n )\n if digital_signature_algorithm:\n algorithm_pair = self._digital_signature_algorithms.get(\n digital_signature_algorithm\n )\n if algorithm_pair:\n dsa_hash_algorithm = algorithm_pair[0]\n dsa_signing_algorithm = algorithm_pair[1]\n if dsa_hash_algorithm and dsa_signing_algorithm:\n if hash_algorithm and (hash_algorithm != dsa_hash_algorithm):\n raise exceptions.InvalidField(\n \"The hashing algorithm does not match the digital \"\n \"signature algorithm.\"\n )\n if (signing_algorithm and\n (signing_algorithm != dsa_signing_algorithm)):\n raise exceptions.InvalidField(\n \"The signing algorithm does not match the digital \"\n \"signature algorithm.\"\n )\n signing_algorithm = dsa_signing_algorithm\n hash_algorithm = dsa_hash_algorithm\n if signing_algorithm == enums.CryptographicAlgorithm.RSA:\n if padding_method == enums.PaddingMethod.PSS:\n if hash_algorithm:\n padding = asymmetric_padding.PSS(\n mgf=asymmetric_padding.MGF1(hash_algorithm()),\n salt_length=asymmetric_padding.PSS.MAX_LENGTH\n )\n else:\n raise exceptions.InvalidField(\n \"A hashing algorithm must be specified for PSS \"\n \"padding.\"\n )\n elif padding_method == enums.PaddingMethod.PKCS1v15:\n padding = asymmetric_padding.PKCS1v15()\n else:\n raise exceptions.InvalidField(\n \"The padding method '{0}' is not supported for signature \"\n \"verification.\".format(padding_method)\n )\n try:\n public_key = backend.load_der_public_key(signing_key)\n except Exception:\n try:\n public_key = backend.load_pem_public_key(signing_key)\n except Exception:\n raise exceptions.CryptographicFailure(\n \"The signing key bytes could not be loaded.\"\n )\n try:\n public_key.verify(\n signature,\n message,\n padding,\n hash_algorithm()\n )\n return True\n except errors.InvalidSignature:\n return False\n except Exception:\n raise exceptions.CryptographicFailure(\n \"The signature verification process failed.\"\n )\n else:\n raise exceptions.InvalidField(\n \"The signing algorithm '{0}' is not supported for \"\n \"signature verification.\".format(signing_algorithm)\n )"
},
{
"code": "def predict(self, x, distributed=True):\n if is_distributed:\n if isinstance(x, np.ndarray):\n features = to_sample_rdd(x, np.zeros([x.shape[0]]))\n elif isinstance(x, RDD):\n features = x\n else:\n raise TypeError(\"Unsupported prediction data type: %s\" % type(x))\n return self.predict_distributed(features)\n else:\n if isinstance(x, np.ndarray):\n return self.predict_local(x)\n else:\n raise TypeError(\"Unsupported prediction data type: %s\" % type(x))"
},
{
"code": "def generate(self, outputfile=None, dotfile=None, mapfile=None):\n import subprocess\n name = self.graphname\n if not dotfile:\n if outputfile and outputfile.endswith(\".dot\"):\n dotfile = outputfile\n else:\n dotfile = \"%s.dot\" % name\n if outputfile is not None:\n storedir, _, target = target_info_from_filename(outputfile)\n if target != \"dot\":\n pdot, dot_sourcepath = tempfile.mkstemp(\".dot\", name)\n os.close(pdot)\n else:\n dot_sourcepath = osp.join(storedir, dotfile)\n else:\n target = \"png\"\n pdot, dot_sourcepath = tempfile.mkstemp(\".dot\", name)\n ppng, outputfile = tempfile.mkstemp(\".png\", name)\n os.close(pdot)\n os.close(ppng)\n pdot = codecs.open(dot_sourcepath, \"w\", encoding=\"utf8\")\n pdot.write(self.source)\n pdot.close()\n if target != \"dot\":\n use_shell = sys.platform == \"win32\"\n if mapfile:\n subprocess.call(\n [\n self.renderer,\n \"-Tcmapx\",\n \"-o\",\n mapfile,\n \"-T\",\n target,\n dot_sourcepath,\n \"-o\",\n outputfile,\n ],\n shell=use_shell,\n )\n else:\n subprocess.call(\n [self.renderer, \"-T\", target, dot_sourcepath, \"-o\", outputfile],\n shell=use_shell,\n )\n os.unlink(dot_sourcepath)\n return outputfile"
},
{
"code": "def connect(com, peers, tree, pub_url, root_id):\n com.connect(peers, tree, pub_url, root_id)"
},
{
"code": "def delete_instance(self, instance_id, project_id=None):\n instance = self.get_instance(instance_id=instance_id, project_id=project_id)\n if instance:\n instance.delete()\n else:\n self.log.info(\"The instance '%s' does not exist in project '%s'. Exiting\", instance_id,\n project_id)"
},
{
"code": "def encode(self, input, errors='strict'):\n if isinstance(input, memoryview):\n input = input.tobytes()\n if not isinstance(input, (binary_type, bytearray)):\n raise with_context(\n exc=TypeError(\n \"Can't encode {type}; byte string expected.\".format(\n type=type(input).__name__,\n )),\n context={\n 'input': input,\n },\n )\n if not isinstance(input, bytearray):\n input = bytearray(input)\n trytes = bytearray()\n for c in input:\n second, first = divmod(c, len(self.alphabet))\n trytes.append(self.alphabet[first])\n trytes.append(self.alphabet[second])\n return binary_type(trytes), len(input)"
},
{
"code": "def get_hash(\n cls,\n version: str,\n frequency: int,\n timestamp: int,\n seed_value: str,\n prev_output: str,\n status_code: str,\n ) -> SHA512Hash:\n return SHA512.new(\n version.encode() +\n struct.pack(\n '>1I1Q64s64s1I',\n frequency,\n timestamp,\n binascii.a2b_hex(seed_value),\n binascii.a2b_hex(prev_output),\n int(status_code),\n )\n )"
},
{
"code": "def init(\n dist='dist',\n minver=None,\n maxver=None,\n use_markdown_readme=True,\n use_stdeb=False,\n use_distribute=False,\n ):\n if not minver == maxver == None:\n import sys\n if not minver <= sys.version < (maxver or 'Any'):\n sys.stderr.write(\n '%s: requires python version in <%s, %s), not %s\\n' % (\n sys.argv[0], minver or 'any', maxver or 'any', sys.version.split()[0]))\n sys.exit(1)\n if use_distribute:\n from distribute_setup import use_setuptools\n use_setuptools(to_dir=dist)\n from setuptools import setup\n else:\n try:\n from setuptools import setup\n except ImportError:\n from distutils.core import setup\n if use_markdown_readme:\n try:\n import setuptools.command.sdist\n setuptools.command.sdist.READMES = tuple(list(getattr(setuptools.command.sdist, 'READMES', ()))\n + ['README.md'])\n except ImportError:\n pass\n if use_stdeb:\n import platform\n if 'debian' in platform.dist():\n try:\n import stdeb\n except ImportError:\n pass\n return setup"
},
{
"code": "def get_defined_srms(srm_file):\n srms = read_table(srm_file)\n return np.asanyarray(srms.index.unique())"
},
{
"code": "def read(self, input_buffer, kmip_version=enums.KMIPVersion.KMIP_2_0):\n if kmip_version < enums.KMIPVersion.KMIP_2_0:\n raise exceptions.VersionNotSupported(\n \"KMIP {} does not support the DefaultsInformation \"\n \"object.\".format(\n kmip_version.value\n )\n )\n super(DefaultsInformation, self).read(\n input_buffer,\n kmip_version=kmip_version\n )\n local_buffer = utils.BytearrayStream(input_buffer.read(self.length))\n object_defaults = []\n while self.is_tag_next(enums.Tags.OBJECT_DEFAULTS, local_buffer):\n object_default = ObjectDefaults()\n object_default.read(local_buffer, kmip_version=kmip_version)\n object_defaults.append(object_default)\n if len(object_defaults) == 0:\n raise exceptions.InvalidKmipEncoding(\n \"The DefaultsInformation encoding is missing the object \"\n \"defaults structure.\"\n )\n else:\n self._object_defaults = object_defaults\n self.is_oversized(local_buffer)"
},
{
"code": "def unused_variable_line_numbers(messages):\n for message in messages:\n if isinstance(message, pyflakes.messages.UnusedVariable):\n yield message.lineno"
},
{
"code": "def set_data(data):\n \"Write content to the clipboard, data can be either a string or a bitmap\" \n try:\n if wx.TheClipboard.Open():\n if isinstance(data, (str, unicode)):\n do = wx.TextDataObject()\n do.SetText(data)\n wx.TheClipboard.SetData(do)\n elif isinstance(data, wx.Bitmap):\n do = wx.BitmapDataObject()\n do.SetBitmap(data)\n wx.TheClipboard.SetData(do)\n wx.TheClipboard.Close()\n except:\n pass"
},
{
"code": "def partial(f, *args):\n @functools.wraps(f)\n def partial_f(*inner_args):\n return f(*itertools.chain(args, inner_args))\n return partial_f"
},
{
"code": "def match(self, request):\n errors = []\n def match(matcher):\n try:\n return matcher.match(request)\n except Exception as err:\n err = '{}: {}'.format(type(matcher).__name__, err)\n errors.append(err)\n return False\n return all([match(matcher) for matcher in self]), errors"
},
{
"code": "def batch_shape_tensor(self):\n batch_shape = tf.constant([], dtype=tf.int32)\n for param in self.parameters:\n batch_shape = tf.broadcast_dynamic_shape(\n batch_shape, param.prior.batch_shape_tensor())\n return batch_shape"
},
{
"code": "def generate(self, *arg, **kw):\n for p, meth in self.plugins:\n result = None\n try:\n result = meth(*arg, **kw)\n if result is not None:\n for r in result:\n yield r\n except (KeyboardInterrupt, SystemExit):\n raise\n except:\n exc = sys.exc_info()\n yield Failure(*exc)\n continue"
},
{
"code": "def fracpols(str, **kwargs):\n I,Q,U,V,L=get_stokes(str, **kwargs)\n return L/I,V/I"
},
{
"code": "def checkUser(self, user):\n return not self.conn(\"POST\", \"{0}/GetCredentialType.srf\".format(SkypeConnection.API_MSACC),\n json={\"username\": user}).json().get(\"IfExistsResult\")"
},
{
"code": "def user_institutes(store, login_user):\n if login_user.is_admin:\n institutes = store.institutes()\n else:\n institutes = [store.institute(inst_id) for inst_id in login_user.institutes]\n return institutes"
},
{
"code": "def start(self, job):\n if self.hostname is None:\n self.hostname = subprocess.check_output([\"hostname\", \"-f\",])[:-1]\n _log.info(\"Started Spark master container.\")\n self.sparkContainerID = dockerCheckOutput(job=job,\n defer=STOP,\n workDir=os.getcwd(),\n tool=\"quay.io/ucsc_cgl/apache-spark-master:1.5.2\",\n dockerParameters=[\"--net=host\",\n \"-d\",\n \"-v\", \"/mnt/ephemeral/:/ephemeral/:rw\",\n \"-e\", \"SPARK_MASTER_IP=\" + self.hostname,\n \"-e\", \"SPARK_LOCAL_DIRS=/ephemeral/spark/local\",\n \"-e\", \"SPARK_WORKER_DIR=/ephemeral/spark/work\"],\n parameters=[self.hostname])[:-1]\n _log.info(\"Started HDFS Datanode.\")\n self.hdfsContainerID = dockerCheckOutput(job=job,\n defer=STOP,\n workDir=os.getcwd(),\n tool=\"quay.io/ucsc_cgl/apache-hadoop-master:2.6.2\",\n dockerParameters=[\"--net=host\",\n \"-d\"],\n parameters=[self.hostname])[:-1]\n return self.hostname"
},
{
"code": "def sequence_LH(self, pos=None, full_sequence=False):\n if not hasattr(self.tree, \"total_sequence_LH\"):\n self.logger(\"TreeAnc.sequence_LH: you need to run marginal ancestral inference first!\", 1)\n self.infer_ancestral_sequences(marginal=True)\n if pos is not None:\n if full_sequence:\n compressed_pos = self.full_to_reduced_sequence_map[pos]\n else:\n compressed_pos = pos\n return self.tree.sequence_LH[compressed_pos]\n else:\n return self.tree.total_sequence_LH"
},
{
"code": "def adjust_saturation(img, saturation_factor):\n if not _is_pil_image(img):\n raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n enhancer = ImageEnhance.Color(img)\n img = enhancer.enhance(saturation_factor)\n return img"
},
{
"code": "def issue_funds(ctx, amount='uint256', rtgs_hash='bytes32', returns=STATUS):\n \"In the IOU fungible the supply is set by Issuer, who issue funds.\"\n ctx.accounts[ctx.msg_sender] += amount\n ctx.issued_amounts[ctx.msg_sender] += amount\n ctx.Issuance(ctx.msg_sender, rtgs_hash, amount)\n return OK"
},
{
"code": "def build_seasonal_transition_noise(\n drift_scale, num_seasons, is_last_day_of_season):\n drift_scale_diag = tf.stack(\n [tf.zeros_like(drift_scale)] * (num_seasons - 1) + [drift_scale],\n axis=-1)\n def seasonal_transition_noise(t):\n noise_scale_diag = dist_util.pick_scalar_condition(\n is_last_day_of_season(t),\n drift_scale_diag,\n tf.zeros_like(drift_scale_diag))\n return tfd.MultivariateNormalDiag(\n loc=tf.zeros(num_seasons, dtype=drift_scale.dtype),\n scale_diag=noise_scale_diag)\n return seasonal_transition_noise"
},
{
"code": "def resolve_url(self, url, follow_redirect=True):\n url = update_scheme(\"http://\", url)\n available_plugins = []\n for name, plugin in self.plugins.items():\n if plugin.can_handle_url(url):\n available_plugins.append(plugin)\n available_plugins.sort(key=lambda x: x.priority(url), reverse=True)\n if available_plugins:\n return available_plugins[0](url)\n if follow_redirect:\n try:\n res = self.http.head(url, allow_redirects=True, acceptable_status=[501])\n if res.status_code == 501:\n res = self.http.get(url, stream=True)\n if res.url != url:\n return self.resolve_url(res.url, follow_redirect=follow_redirect)\n except PluginError:\n pass\n raise NoPluginError"
},
{
"code": "def embed_font_to_svg(filepath, outfile, font_files):\n tree = _embed_font_to_svg(filepath, font_files)\n tree.write(outfile, encoding='utf-8', pretty_print=True)"
},
{
"code": "def verify_type_product(self, satellite):\n if satellite == 'L5':\n id_satellite = '3119'\n stations = ['GLC', 'ASA', 'KIR', 'MOR', 'KHC', 'PAC', 'KIS', 'CHM', 'LGS', 'MGR', 'COA', 'MPS']\n elif satellite == 'L7':\n id_satellite = '3373'\n stations = ['EDC', 'SGS', 'AGS', 'ASN', 'SG1']\n elif satellite == 'L8':\n id_satellite = '4923'\n stations = ['LGN']\n else:\n raise ProductInvalidError('Type product invalid. the permitted types are: L5, L7, L8. ')\n typ_product = dict(id_satelite=id_satellite, stations=stations)\n return typ_product"
},
{
"code": "def brent(seqs, f=None, start=None, key=lambda x: x):\n power = period = 1\n tortise, hare = seqs\n yield hare.next()\n tortise_value = tortise.next()\n hare_value = hare.next()\n while key(tortise_value) != key(hare_value):\n yield hare_value\n if power == period:\n power *= 2\n period = 0\n if f:\n tortise = f_generator(f, hare_value)\n tortise_value = tortise.next()\n else:\n while tortise_value != hare_value:\n tortise_value = tortise.next()\n hare_value = hare.next()\n period += 1\n if f is None:\n raise CycleDetected()\n first = 0\n tortise_value = hare_value = start\n for _ in xrange(period):\n hare_value = f(hare_value)\n while key(tortise_value) != key(hare_value):\n tortise_value = f(tortise_value)\n hare_value = f(hare_value)\n first += 1\n raise CycleDetected(period=period, first=first)"
},
{
"code": "def add_s(self, s, obj, priority= 0 ):\n chain = self.strs.get(s, CommandChainDispatcher())\n chain.add(obj,priority)\n self.strs[s] = chain"
}
] |