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gwastro/pycbc
pycbc/sensitivity.py
compute_search_volume_in_bins
def compute_search_volume_in_bins(found, total, ndbins, sim_to_bins_function): """ Calculate search sensitive volume by integrating efficiency in distance bins No cosmological corrections are applied: flat space is assumed. The first dimension of ndbins must be bins over injected distance. sim_to_bins_function must maps an object to a tuple indexing the ndbins. """ eff, err = compute_search_efficiency_in_bins( found, total, ndbins, sim_to_bins_function) dx = ndbins[0].upper() - ndbins[0].lower() r = ndbins[0].centres() # volume and errors have one fewer dimension than the input NDBins vol = bin_utils.BinnedArray(bin_utils.NDBins(ndbins[1:])) errors = bin_utils.BinnedArray(bin_utils.NDBins(ndbins[1:])) # integrate efficiency to obtain volume vol.array = numpy.trapz(eff.array.T * 4. * numpy.pi * r**2, r, dx) # propagate errors in eff to errors in V errors.array = numpy.sqrt( ((4 * numpy.pi * r**2 * err.array.T * dx)**2).sum(axis=-1) ) return vol, errors
python
def compute_search_volume_in_bins(found, total, ndbins, sim_to_bins_function): """ Calculate search sensitive volume by integrating efficiency in distance bins No cosmological corrections are applied: flat space is assumed. The first dimension of ndbins must be bins over injected distance. sim_to_bins_function must maps an object to a tuple indexing the ndbins. """ eff, err = compute_search_efficiency_in_bins( found, total, ndbins, sim_to_bins_function) dx = ndbins[0].upper() - ndbins[0].lower() r = ndbins[0].centres() # volume and errors have one fewer dimension than the input NDBins vol = bin_utils.BinnedArray(bin_utils.NDBins(ndbins[1:])) errors = bin_utils.BinnedArray(bin_utils.NDBins(ndbins[1:])) # integrate efficiency to obtain volume vol.array = numpy.trapz(eff.array.T * 4. * numpy.pi * r**2, r, dx) # propagate errors in eff to errors in V errors.array = numpy.sqrt( ((4 * numpy.pi * r**2 * err.array.T * dx)**2).sum(axis=-1) ) return vol, errors
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rectpack/maxrects.py
MaxRects._split
def _split(self, rect): """ Split all max_rects intersecting the rectangle rect into up to 4 new max_rects. Arguments: rect (Rectangle): Rectangle Returns: split (Rectangle list): List of rectangles resulting from the split """ max_rects = collections.deque() for r in self._max_rects: if r.intersects(rect): max_rects.extend(self._generate_splits(r, rect)) else: max_rects.append(r) # Add newly generated max_rects self._max_rects = list(max_rects)
python
def _split(self, rect): """ Split all max_rects intersecting the rectangle rect into up to 4 new max_rects. Arguments: rect (Rectangle): Rectangle Returns: split (Rectangle list): List of rectangles resulting from the split """ max_rects = collections.deque() for r in self._max_rects: if r.intersects(rect): max_rects.extend(self._generate_splits(r, rect)) else: max_rects.append(r) # Add newly generated max_rects self._max_rects = list(max_rects)
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charmhelpers/contrib/openstack/amulet/utils.py
OpenStackAmuletUtils.authenticate_keystone
def authenticate_keystone(self, keystone_ip, username, password, api_version=False, admin_port=False, user_domain_name=None, domain_name=None, project_domain_name=None, project_name=None): """Authenticate with Keystone""" self.log.debug('Authenticating with keystone...') if not api_version: api_version = 2 sess, auth = self.get_keystone_session( keystone_ip=keystone_ip, username=username, password=password, api_version=api_version, admin_port=admin_port, user_domain_name=user_domain_name, domain_name=domain_name, project_domain_name=project_domain_name, project_name=project_name ) if api_version == 2: client = keystone_client.Client(session=sess) else: client = keystone_client_v3.Client(session=sess) # This populates the client.service_catalog client.auth_ref = auth.get_access(sess) return client
python
def authenticate_keystone(self, keystone_ip, username, password, api_version=False, admin_port=False, user_domain_name=None, domain_name=None, project_domain_name=None, project_name=None): """Authenticate with Keystone""" self.log.debug('Authenticating with keystone...') if not api_version: api_version = 2 sess, auth = self.get_keystone_session( keystone_ip=keystone_ip, username=username, password=password, api_version=api_version, admin_port=admin_port, user_domain_name=user_domain_name, domain_name=domain_name, project_domain_name=project_domain_name, project_name=project_name ) if api_version == 2: client = keystone_client.Client(session=sess) else: client = keystone_client_v3.Client(session=sess) # This populates the client.service_catalog client.auth_ref = auth.get_access(sess) return client
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robinandeer/puzzle
puzzle/plugins/vcf/mixins/variant_extras/annotations.py
AnnotationExtras._add_genetic_models
def _add_genetic_models(self, variant_obj, info_dict): """Add the genetic models found Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary """ genetic_models_entry = info_dict.get('GeneticModels') if genetic_models_entry: genetic_models = [] for family_annotation in genetic_models_entry.split(','): for genetic_model in family_annotation.split(':')[-1].split('|'): genetic_models.append(genetic_model) logger.debug("Updating genetic models to: {0}".format( ', '.join(genetic_models))) variant_obj.genetic_models = genetic_models
python
def _add_genetic_models(self, variant_obj, info_dict): """Add the genetic models found Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary """ genetic_models_entry = info_dict.get('GeneticModels') if genetic_models_entry: genetic_models = [] for family_annotation in genetic_models_entry.split(','): for genetic_model in family_annotation.split(':')[-1].split('|'): genetic_models.append(genetic_model) logger.debug("Updating genetic models to: {0}".format( ', '.join(genetic_models))) variant_obj.genetic_models = genetic_models
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ClimateImpactLab/DataFS
datafs/core/data_archive.py
DataArchive.isfile
def isfile(self, version=None, *args, **kwargs): ''' Check whether the path exists and is a file ''' version = _process_version(self, version) path = self.get_version_path(version) self.authority.fs.isfile(path, *args, **kwargs)
python
def isfile(self, version=None, *args, **kwargs): ''' Check whether the path exists and is a file ''' version = _process_version(self, version) path = self.get_version_path(version) self.authority.fs.isfile(path, *args, **kwargs)
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ocslegna/auto_py_torrent
auto_py_torrent/auto_py_torrent.py
AutoPy.get_magnet
def get_magnet(self, url): """Get magnet from torrent page. Url already got domain.""" content_most_rated = requests.get(url) rated_soup = BeautifulSoup(content_most_rated.content, 'lxml') if self.page == 'torrent_project': self.magnet = rated_soup.find( 'a', href=True, text=re.compile('Download'))['href'] elif self.page == 'the_pirate_bay': self.magnet = rated_soup.find( 'a', href=True, text=re.compile('Get this torrent'))['href'] elif self.page == '1337x': div1337 = rated_soup.find( 'div', {'class': 'torrent-category-detail'}) self.magnet = div1337.find('a', href=re.compile('magnet'))['href'] elif self.page == 'isohunt': self.magnet = rated_soup.find( 'a', href=re.compile('magnet'))['href'] else: print('Wrong page to get magnet!') sys.exit(1)
python
def get_magnet(self, url): """Get magnet from torrent page. Url already got domain.""" content_most_rated = requests.get(url) rated_soup = BeautifulSoup(content_most_rated.content, 'lxml') if self.page == 'torrent_project': self.magnet = rated_soup.find( 'a', href=True, text=re.compile('Download'))['href'] elif self.page == 'the_pirate_bay': self.magnet = rated_soup.find( 'a', href=True, text=re.compile('Get this torrent'))['href'] elif self.page == '1337x': div1337 = rated_soup.find( 'div', {'class': 'torrent-category-detail'}) self.magnet = div1337.find('a', href=re.compile('magnet'))['href'] elif self.page == 'isohunt': self.magnet = rated_soup.find( 'a', href=re.compile('magnet'))['href'] else: print('Wrong page to get magnet!') sys.exit(1)
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deepmind/sonnet
sonnet/python/modules/basic_rnn.py
BidirectionalRNN._build
def _build(self, input_sequence, state): """Connects the BidirectionalRNN module into the graph. Args: input_sequence: tensor (time, batch, [feature_1, ..]). It must be time_major. state: tuple of states for the forward and backward cores. Returns: A dict with forward/backard states and output sequences: "outputs":{ "forward": ..., "backward": ...}, "state": { "forward": ..., "backward": ...} Raises: ValueError: in case time dimension is not statically known. """ input_shape = input_sequence.get_shape() if input_shape[0] is None: raise ValueError("Time dimension of input (dim 0) must be statically" "known.") seq_length = int(input_shape[0]) forward_state, backward_state = state # Lists for the forward backward output and state. output_sequence_f = [] output_sequence_b = [] # Forward pass over the sequence. with tf.name_scope("forward_rnn"): core_state = forward_state for i in six.moves.range(seq_length): core_output, core_state = self._forward_core( input_sequence[i, :,], core_state) output_sequence_f.append((core_output, core_state)) output_sequence_f = nest.map_structure( lambda *vals: tf.stack(vals), *output_sequence_f) # Backward pass over the sequence. with tf.name_scope("backward_rnn"): core_state = backward_state for i in six.moves.range(seq_length - 1, -1, -1): core_output, core_state = self._backward_core( input_sequence[i, :,], core_state) output_sequence_b.append((core_output, core_state)) output_sequence_b = nest.map_structure( lambda *vals: tf.stack(vals), *output_sequence_b) # Compose the full output and state sequeneces. return { "outputs": { "forward": output_sequence_f[0], "backward": output_sequence_b[0] }, "state": { "forward": output_sequence_f[1], "backward": output_sequence_b[1] } }
python
def _build(self, input_sequence, state): """Connects the BidirectionalRNN module into the graph. Args: input_sequence: tensor (time, batch, [feature_1, ..]). It must be time_major. state: tuple of states for the forward and backward cores. Returns: A dict with forward/backard states and output sequences: "outputs":{ "forward": ..., "backward": ...}, "state": { "forward": ..., "backward": ...} Raises: ValueError: in case time dimension is not statically known. """ input_shape = input_sequence.get_shape() if input_shape[0] is None: raise ValueError("Time dimension of input (dim 0) must be statically" "known.") seq_length = int(input_shape[0]) forward_state, backward_state = state # Lists for the forward backward output and state. output_sequence_f = [] output_sequence_b = [] # Forward pass over the sequence. with tf.name_scope("forward_rnn"): core_state = forward_state for i in six.moves.range(seq_length): core_output, core_state = self._forward_core( input_sequence[i, :,], core_state) output_sequence_f.append((core_output, core_state)) output_sequence_f = nest.map_structure( lambda *vals: tf.stack(vals), *output_sequence_f) # Backward pass over the sequence. with tf.name_scope("backward_rnn"): core_state = backward_state for i in six.moves.range(seq_length - 1, -1, -1): core_output, core_state = self._backward_core( input_sequence[i, :,], core_state) output_sequence_b.append((core_output, core_state)) output_sequence_b = nest.map_structure( lambda *vals: tf.stack(vals), *output_sequence_b) # Compose the full output and state sequeneces. return { "outputs": { "forward": output_sequence_f[0], "backward": output_sequence_b[0] }, "state": { "forward": output_sequence_f[1], "backward": output_sequence_b[1] } }
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RRZE-HPC/pycachesim
cachesim/cache.py
MainMemory.store_from
def store_from(self, last_level_store): """Set level where to store to.""" assert isinstance(last_level_store, Cache), \ "last_level needs to be a Cache object." assert last_level_store.store_to is None, \ "last_level_store must be a last level cache (.store_to is None)." self.last_level_store = last_level_store
python
def store_from(self, last_level_store): """Set level where to store to.""" assert isinstance(last_level_store, Cache), \ "last_level needs to be a Cache object." assert last_level_store.store_to is None, \ "last_level_store must be a last level cache (.store_to is None)." self.last_level_store = last_level_store
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bel/edge/computed.py
compute_edges
def compute_edges(ast: BELAst, spec: BELSpec) -> Edges: """Compute edges""" edges = [] if ast.bel_object.__class__.__name__ == "BELAst": edges.append(ast.bel_object) process_ast(edges, ast, spec) return edges
python
def compute_edges(ast: BELAst, spec: BELSpec) -> Edges: """Compute edges""" edges = [] if ast.bel_object.__class__.__name__ == "BELAst": edges.append(ast.bel_object) process_ast(edges, ast, spec) return edges
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django_services/api/api.py
getattr_in_cls_list
def getattr_in_cls_list(cls_list, attr, default): """ Search for an attribute (attr) in class list (cls_list). Returns attribute value if exists or None if not. """ for cls in cls_list: if hasattr(cls, attr): return getattr(cls, attr) return default
python
def getattr_in_cls_list(cls_list, attr, default): """ Search for an attribute (attr) in class list (cls_list). Returns attribute value if exists or None if not. """ for cls in cls_list: if hasattr(cls, attr): return getattr(cls, attr) return default
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hughsie/python-appstream
appstream/store.py
Store.get_components
def get_components(self): """ Returns all the applications from the store """ components = [] for app_id in self.components: components.append(self.components[app_id]) return components
python
def get_components(self): """ Returns all the applications from the store """ components = [] for app_id in self.components: components.append(self.components[app_id]) return components
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azure-devops/azure/devops/v5_1/git/git_client_base.py
GitClientBase.update_repository
def update_repository(self, new_repository_info, repository_id, project=None): """UpdateRepository. [Preview API] Updates the Git repository with either a new repo name or a new default branch. :param :class:`<GitRepository> <azure.devops.v5_1.git.models.GitRepository>` new_repository_info: Specify a new repo name or a new default branch of the repository :param str repository_id: The name or ID of the repository. :param str project: Project ID or project name :rtype: :class:`<GitRepository> <azure.devops.v5_1.git.models.GitRepository>` """ route_values = {} if project is not None: route_values['project'] = self._serialize.url('project', project, 'str') if repository_id is not None: route_values['repositoryId'] = self._serialize.url('repository_id', repository_id, 'str') content = self._serialize.body(new_repository_info, 'GitRepository') response = self._send(http_method='PATCH', location_id='225f7195-f9c7-4d14-ab28-a83f7ff77e1f', version='5.1-preview.1', route_values=route_values, content=content) return self._deserialize('GitRepository', response)
python
def update_repository(self, new_repository_info, repository_id, project=None): """UpdateRepository. [Preview API] Updates the Git repository with either a new repo name or a new default branch. :param :class:`<GitRepository> <azure.devops.v5_1.git.models.GitRepository>` new_repository_info: Specify a new repo name or a new default branch of the repository :param str repository_id: The name or ID of the repository. :param str project: Project ID or project name :rtype: :class:`<GitRepository> <azure.devops.v5_1.git.models.GitRepository>` """ route_values = {} if project is not None: route_values['project'] = self._serialize.url('project', project, 'str') if repository_id is not None: route_values['repositoryId'] = self._serialize.url('repository_id', repository_id, 'str') content = self._serialize.body(new_repository_info, 'GitRepository') response = self._send(http_method='PATCH', location_id='225f7195-f9c7-4d14-ab28-a83f7ff77e1f', version='5.1-preview.1', route_values=route_values, content=content) return self._deserialize('GitRepository', response)
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csparpa/pyowm
pyowm/weatherapi25/owm25.py
OWM25.weather_at_places
def weather_at_places(self, pattern, searchtype, limit=None): """ Queries the OWM Weather API for the currently observed weather in all the locations whose name is matching the specified text search parameters. A twofold search can be issued: *'accurate'* (exact matching) and *'like'* (matches names that are similar to the supplied pattern). :param pattern: the string pattern (not a regex) to be searched for the toponym :type pattern: str :param searchtype: the search mode to be used, must be *'accurate'* for an exact matching or *'like'* for a likelihood matching :type: searchtype: str :param limit: the maximum number of *Observation* items in the returned list (default is ``None``, which stands for any number of items) :param limit: int or ``None`` :returns: a list of *Observation* objects or ``None`` if no weather data is available :raises: *ParseResponseException* when OWM Weather API responses' data cannot be parsed, *APICallException* when OWM Weather API can not be reached, *ValueError* when bad value is supplied for the search type or the maximum number of items retrieved """ assert isinstance(pattern, str), "'pattern' must be a str" assert isinstance(searchtype, str), "'searchtype' must be a str" if searchtype != "accurate" and searchtype != "like": raise ValueError("'searchtype' value must be 'accurate' or 'like'") if limit is not None: assert isinstance(limit, int), "'limit' must be an int or None" if limit < 1: raise ValueError("'limit' must be None or greater than zero") params = {'q': pattern, 'type': searchtype, 'lang': self._language} if limit is not None: # fix for OWM 2.5 API bug! params['cnt'] = limit - 1 uri = http_client.HttpClient.to_url(FIND_OBSERVATIONS_URL, self._API_key, self._subscription_type, self._use_ssl) _, json_data = self._wapi.cacheable_get_json(uri, params=params) return self._parsers['observation_list'].parse_JSON(json_data)
python
def weather_at_places(self, pattern, searchtype, limit=None): """ Queries the OWM Weather API for the currently observed weather in all the locations whose name is matching the specified text search parameters. A twofold search can be issued: *'accurate'* (exact matching) and *'like'* (matches names that are similar to the supplied pattern). :param pattern: the string pattern (not a regex) to be searched for the toponym :type pattern: str :param searchtype: the search mode to be used, must be *'accurate'* for an exact matching or *'like'* for a likelihood matching :type: searchtype: str :param limit: the maximum number of *Observation* items in the returned list (default is ``None``, which stands for any number of items) :param limit: int or ``None`` :returns: a list of *Observation* objects or ``None`` if no weather data is available :raises: *ParseResponseException* when OWM Weather API responses' data cannot be parsed, *APICallException* when OWM Weather API can not be reached, *ValueError* when bad value is supplied for the search type or the maximum number of items retrieved """ assert isinstance(pattern, str), "'pattern' must be a str" assert isinstance(searchtype, str), "'searchtype' must be a str" if searchtype != "accurate" and searchtype != "like": raise ValueError("'searchtype' value must be 'accurate' or 'like'") if limit is not None: assert isinstance(limit, int), "'limit' must be an int or None" if limit < 1: raise ValueError("'limit' must be None or greater than zero") params = {'q': pattern, 'type': searchtype, 'lang': self._language} if limit is not None: # fix for OWM 2.5 API bug! params['cnt'] = limit - 1 uri = http_client.HttpClient.to_url(FIND_OBSERVATIONS_URL, self._API_key, self._subscription_type, self._use_ssl) _, json_data = self._wapi.cacheable_get_json(uri, params=params) return self._parsers['observation_list'].parse_JSON(json_data)
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Alignak-monitoring/alignak
alignak/daemons/schedulerdaemon.py
Alignak.clean_previous_run
def clean_previous_run(self): """Clean variables from previous configuration :return: None """ # Execute the base class treatment... super(Alignak, self).clean_previous_run() # Clean all lists self.pollers.clear() self.reactionners.clear() self.brokers.clear()
python
def clean_previous_run(self): """Clean variables from previous configuration :return: None """ # Execute the base class treatment... super(Alignak, self).clean_previous_run() # Clean all lists self.pollers.clear() self.reactionners.clear() self.brokers.clear()
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Opentrons/opentrons
api/src/opentrons/hardware_control/__init__.py
API.set_lights
def set_lights(self, button: bool = None, rails: bool = None): """ Control the robot lights. :param button: If specified, turn the button light on (`True`) or off (`False`). If not specified, do not change the button light. :param rails: If specified, turn the rail lights on (`True`) or off (`False`). If not specified, do not change the rail lights. """ self._backend.set_lights(button, rails)
python
def set_lights(self, button: bool = None, rails: bool = None): """ Control the robot lights. :param button: If specified, turn the button light on (`True`) or off (`False`). If not specified, do not change the button light. :param rails: If specified, turn the rail lights on (`True`) or off (`False`). If not specified, do not change the rail lights. """ self._backend.set_lights(button, rails)
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softlayer/softlayer-python
SoftLayer/managers/network.py
NetworkManager.get_subnet
def get_subnet(self, subnet_id, **kwargs): """Returns information about a single subnet. :param string id: Either the ID for the subnet or its network identifier :returns: A dictionary of information about the subnet """ if 'mask' not in kwargs: kwargs['mask'] = DEFAULT_SUBNET_MASK return self.subnet.getObject(id=subnet_id, **kwargs)
python
def get_subnet(self, subnet_id, **kwargs): """Returns information about a single subnet. :param string id: Either the ID for the subnet or its network identifier :returns: A dictionary of information about the subnet """ if 'mask' not in kwargs: kwargs['mask'] = DEFAULT_SUBNET_MASK return self.subnet.getObject(id=subnet_id, **kwargs)
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MolSSI-BSE/basis_set_exchange
basis_set_exchange/sort.py
sort_single_reference
def sort_single_reference(ref_entry): """Sorts a dictionary containing data for a single reference into a standard order """ # yapf: disable _keyorder = [ # Schema stuff # This function gets called on the schema 'entry', too 'schema_type', 'schema_version', # Type of the entry 'type', # Actual publication info 'authors', 'title', 'booktitle', 'series', 'editors', 'journal', 'institution', 'volume', 'number', 'page', 'year', 'note', 'publisher', 'address', 'isbn', 'doi' ] # yapf: enable sorted_entry = sorted(ref_entry.items(), key=lambda x: _keyorder.index(x[0])) if _use_odict: return OrderedDict(sorted_entry) else: return dict(sorted_entry)
python
def sort_single_reference(ref_entry): """Sorts a dictionary containing data for a single reference into a standard order """ # yapf: disable _keyorder = [ # Schema stuff # This function gets called on the schema 'entry', too 'schema_type', 'schema_version', # Type of the entry 'type', # Actual publication info 'authors', 'title', 'booktitle', 'series', 'editors', 'journal', 'institution', 'volume', 'number', 'page', 'year', 'note', 'publisher', 'address', 'isbn', 'doi' ] # yapf: enable sorted_entry = sorted(ref_entry.items(), key=lambda x: _keyorder.index(x[0])) if _use_odict: return OrderedDict(sorted_entry) else: return dict(sorted_entry)
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lago-project/lago
lago/prefix.py
Prefix.cleanup
def cleanup(self): """ Stops any running entities in the prefix and uninitializes it, usually you want to do this if you are going to remove the prefix afterwards Returns: None """ with LogTask('Stop prefix'): self.stop() with LogTask("Tag prefix as uninitialized"): os.unlink(self.paths.prefix_lagofile())
python
def cleanup(self): """ Stops any running entities in the prefix and uninitializes it, usually you want to do this if you are going to remove the prefix afterwards Returns: None """ with LogTask('Stop prefix'): self.stop() with LogTask("Tag prefix as uninitialized"): os.unlink(self.paths.prefix_lagofile())
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necrolyte2/bootstrap_vi
bootstrap_vi.py
bootstrap_vi
def bootstrap_vi(version=None, venvargs=None): ''' Bootstrap virtualenv into current directory :param str version: Virtualenv version like 13.1.0 or None for latest version :param list venvargs: argv list for virtualenv.py or None for default ''' if not version: version = get_latest_virtualenv_version() tarball = download_virtualenv(version) p = subprocess.Popen('tar xzvf {0}'.format(tarball), shell=True) p.wait() p = 'virtualenv-{0}'.format(version) create_virtualenv(p, venvargs)
python
def bootstrap_vi(version=None, venvargs=None): ''' Bootstrap virtualenv into current directory :param str version: Virtualenv version like 13.1.0 or None for latest version :param list venvargs: argv list for virtualenv.py or None for default ''' if not version: version = get_latest_virtualenv_version() tarball = download_virtualenv(version) p = subprocess.Popen('tar xzvf {0}'.format(tarball), shell=True) p.wait() p = 'virtualenv-{0}'.format(version) create_virtualenv(p, venvargs)
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drizzlepac/processInput.py
addIVMInputs
def addIVMInputs(imageObjectList,ivmlist): """ Add IVM filenames provided by user to outputNames dictionary for each input imageObject. """ if ivmlist is None: return for img,ivmname in zip(imageObjectList,ivmlist): img.updateIVMName(ivmname)
python
def addIVMInputs(imageObjectList,ivmlist): """ Add IVM filenames provided by user to outputNames dictionary for each input imageObject. """ if ivmlist is None: return for img,ivmname in zip(imageObjectList,ivmlist): img.updateIVMName(ivmname)
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livvkit/components/verification.py
_print_summary
def _print_summary(case, summary): """ Show some statistics from the run """ for dof, data in summary.items(): b4b = data["Bit for Bit"] conf = data["Configurations"] stdout = data["Std. Out Files"] print(" " + case + " " + str(dof)) print(" --------------------") print(" Bit for bit matches : " + str(b4b[0]) + " of " + str(b4b[1])) print(" Configuration matches : " + str(conf[0]) + " of " + str(conf[1])) print(" Std. Out files parsed : " + str(stdout)) print("")
python
def _print_summary(case, summary): """ Show some statistics from the run """ for dof, data in summary.items(): b4b = data["Bit for Bit"] conf = data["Configurations"] stdout = data["Std. Out Files"] print(" " + case + " " + str(dof)) print(" --------------------") print(" Bit for bit matches : " + str(b4b[0]) + " of " + str(b4b[1])) print(" Configuration matches : " + str(conf[0]) + " of " + str(conf[1])) print(" Std. Out files parsed : " + str(stdout)) print("")
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GNS3/gns3-server
gns3server/compute/dynamips/nios/nio.py
NIO.bind_filter
def bind_filter(self, direction, filter_name): """ Adds a packet filter to this NIO. Filter "freq_drop" drops packets. Filter "capture" captures packets. :param direction: "in", "out" or "both" :param filter_name: name of the filter to apply """ if direction not in self._dynamips_direction: raise DynamipsError("Unknown direction {} to bind filter {}:".format(direction, filter_name)) dynamips_direction = self._dynamips_direction[direction] yield from self._hypervisor.send("nio bind_filter {name} {direction} {filter}".format(name=self._name, direction=dynamips_direction, filter=filter_name)) if direction == "in": self._input_filter = filter_name elif direction == "out": self._output_filter = filter_name elif direction == "both": self._input_filter = filter_name self._output_filter = filter_name
python
def bind_filter(self, direction, filter_name): """ Adds a packet filter to this NIO. Filter "freq_drop" drops packets. Filter "capture" captures packets. :param direction: "in", "out" or "both" :param filter_name: name of the filter to apply """ if direction not in self._dynamips_direction: raise DynamipsError("Unknown direction {} to bind filter {}:".format(direction, filter_name)) dynamips_direction = self._dynamips_direction[direction] yield from self._hypervisor.send("nio bind_filter {name} {direction} {filter}".format(name=self._name, direction=dynamips_direction, filter=filter_name)) if direction == "in": self._input_filter = filter_name elif direction == "out": self._output_filter = filter_name elif direction == "both": self._input_filter = filter_name self._output_filter = filter_name
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adamchainz/django-mysql
django_mysql/models/handler.py
Handler._extract_where
def _extract_where(cls, queryset): """ Was this a queryset with filters/excludes/expressions set? If so, extract the WHERE clause from the ORM output so we can use it in the handler queries. """ if not cls._is_simple_query(queryset.query): raise ValueError("This QuerySet's WHERE clause is too complex to " "be used in a HANDLER") sql, params = queryset.query.sql_with_params() where_pos = sql.find('WHERE ') if where_pos != -1: # Cut the query to extract just its WHERE clause where_clause = sql[where_pos:] # Replace absolute table.column references with relative ones # since that is all HANDLER can work with # This is a bit flakey - if you inserted extra SQL with extra() or # an expression or something it might break. where_clause, _ = cls.absolute_col_re.subn(r"\1", where_clause) return (where_clause, params) else: return ("", ())
python
def _extract_where(cls, queryset): """ Was this a queryset with filters/excludes/expressions set? If so, extract the WHERE clause from the ORM output so we can use it in the handler queries. """ if not cls._is_simple_query(queryset.query): raise ValueError("This QuerySet's WHERE clause is too complex to " "be used in a HANDLER") sql, params = queryset.query.sql_with_params() where_pos = sql.find('WHERE ') if where_pos != -1: # Cut the query to extract just its WHERE clause where_clause = sql[where_pos:] # Replace absolute table.column references with relative ones # since that is all HANDLER can work with # This is a bit flakey - if you inserted extra SQL with extra() or # an expression or something it might break. where_clause, _ = cls.absolute_col_re.subn(r"\1", where_clause) return (where_clause, params) else: return ("", ())
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opereto/pyopereto
pyopereto/client.py
OperetoClient.search_agents
def search_agents(self, start=0, limit=100, filter={}, **kwargs): ''' search_agents(self, start=0, limit=100, filter={}, **kwargs) Search agents :Parameters: * *start* (`int`) -- start index to retrieve from. Default is 0 * *limit* (`int`) -- maximum number of entities to retrieve. Default is 100 * *filter* (`object`) -- free text search pattern (checks in agent data and properties) :return: List of search results or empty list :Example: .. code-block:: python filter = {'generic': 'my Agent'} search_result = opereto_client.search_agents(filter=filter) ''' request_data = {'start': start, 'limit': limit, 'filter': filter} request_data.update(kwargs) return self._call_rest_api('post', '/search/agents', data=request_data, error='Failed to search agents')
python
def search_agents(self, start=0, limit=100, filter={}, **kwargs): ''' search_agents(self, start=0, limit=100, filter={}, **kwargs) Search agents :Parameters: * *start* (`int`) -- start index to retrieve from. Default is 0 * *limit* (`int`) -- maximum number of entities to retrieve. Default is 100 * *filter* (`object`) -- free text search pattern (checks in agent data and properties) :return: List of search results or empty list :Example: .. code-block:: python filter = {'generic': 'my Agent'} search_result = opereto_client.search_agents(filter=filter) ''' request_data = {'start': start, 'limit': limit, 'filter': filter} request_data.update(kwargs) return self._call_rest_api('post', '/search/agents', data=request_data, error='Failed to search agents')
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search_agents(self, start=0, limit=100, filter={}, **kwargs) Search agents :Parameters: * *start* (`int`) -- start index to retrieve from. Default is 0 * *limit* (`int`) -- maximum number of entities to retrieve. Default is 100 * *filter* (`object`) -- free text search pattern (checks in agent data and properties) :return: List of search results or empty list :Example: .. code-block:: python filter = {'generic': 'my Agent'} search_result = opereto_client.search_agents(filter=filter)
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chibisov/drf-extensions
docs/backdoc.py
_slugify
def _slugify(text, delim=u'-'): """Generates an ASCII-only slug.""" result = [] for word in _punct_re.split(text.lower()): word = word.encode('utf-8') if word: result.append(word) slugified = delim.join([i.decode('utf-8') for i in result]) return re.sub('[^a-zA-Z0-9\\s\\-]{1}', replace_char, slugified).lower()
python
def _slugify(text, delim=u'-'): """Generates an ASCII-only slug.""" result = [] for word in _punct_re.split(text.lower()): word = word.encode('utf-8') if word: result.append(word) slugified = delim.join([i.decode('utf-8') for i in result]) return re.sub('[^a-zA-Z0-9\\s\\-]{1}', replace_char, slugified).lower()
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gmr/tinman
tinman/application.py
Application._prepare_version
def _prepare_version(self): """Setup the application version""" if config.VERSION not in self._config: self._config[config.VERSION] = __version__
python
def _prepare_version(self): """Setup the application version""" if config.VERSION not in self._config: self._config[config.VERSION] = __version__
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pkgw/pwkit
pwkit/lmmin.py
_calc_covariance
def _calc_covariance(r, pmut, tol=1e-14): """Calculate the covariance matrix of the fitted parameters Parameters: r - n-by-n matrix, the full upper triangle of R pmut - n-vector, defines the permutation of R tol - scalar, relative column scale for determining rank deficiency. Default 1e-14. Returns: cov - n-by-n matrix, the covariance matrix C Given an n-by-n matrix A, the corresponding covariance matrix is C = inverse(A^T A) This routine is given information relating to the pivoted transposed QR factorization of A, which is defined by matrices such that A P = R Q where P is a permutation matrix, Q has orthogonal rows, and R is a lower triangular matrix with diagonal elements of nonincreasing magnitude. In particular we take the full lower triangle of R ('r') and a vector describing P ('pmut'). The covariance matrix is then C = P inverse(R^T R) P^T If A is nearly rank-deficient, it may be desirable to compute the covariance matrix corresponding to the linearly-independent columns of A. We use a tolerance, 'tol', to define the numerical rank of A. If j is the largest integer such that |R[j,j]| > tol*|R[0,0]|, then we compute the covariance matrix for the first j columns of R. For k > j, the corresponding covariance entries (pmut[k]) are set to zero. """ # This routine could save an allocation by operating on r in-place, # which might be worthwhile for large n, and is what the original # Fortran does. n = r.shape[1] assert r.shape[0] >= n r = r.copy() # Form the inverse of R in the full lower triangle of R. jrank = -1 abstol = tol * abs(r[0,0]) for i in range(n): if abs(r[i,i]) <= abstol: break r[i,i] **= -1 for j in range(i): temp = r[i,i] * r[i,j] r[i,j] = 0. r[i,:j+1] -= temp * r[j,:j+1] jrank = i # Form the full lower triangle of the inverse(R^T R) in the full # lower triangle of R. for i in range(jrank + 1): for j in range(i): r[j,:j+1] += r[i,j] * r[i,:j+1] r[i,:i+1] *= r[i,i] # Form the full upper triangle of the covariance matrix in the # strict upper triangle of R and in wa. wa = np.empty(n) wa.fill(r[0,0]) for i in range(n): pi = pmut[i] sing = i > jrank for j in range(i + 1): if sing: r[i,j] = 0. pj = pmut[j] if pj > pi: r[pi,pj] = r[i,j] elif pj < pi: r[pj,pi] = r[i,j] wa[pi] = r[i,i] # Symmetrize. for i in range(n): r[i,:i+1] = r[:i+1,i] r[i,i] = wa[i] return r
python
def _calc_covariance(r, pmut, tol=1e-14): """Calculate the covariance matrix of the fitted parameters Parameters: r - n-by-n matrix, the full upper triangle of R pmut - n-vector, defines the permutation of R tol - scalar, relative column scale for determining rank deficiency. Default 1e-14. Returns: cov - n-by-n matrix, the covariance matrix C Given an n-by-n matrix A, the corresponding covariance matrix is C = inverse(A^T A) This routine is given information relating to the pivoted transposed QR factorization of A, which is defined by matrices such that A P = R Q where P is a permutation matrix, Q has orthogonal rows, and R is a lower triangular matrix with diagonal elements of nonincreasing magnitude. In particular we take the full lower triangle of R ('r') and a vector describing P ('pmut'). The covariance matrix is then C = P inverse(R^T R) P^T If A is nearly rank-deficient, it may be desirable to compute the covariance matrix corresponding to the linearly-independent columns of A. We use a tolerance, 'tol', to define the numerical rank of A. If j is the largest integer such that |R[j,j]| > tol*|R[0,0]|, then we compute the covariance matrix for the first j columns of R. For k > j, the corresponding covariance entries (pmut[k]) are set to zero. """ # This routine could save an allocation by operating on r in-place, # which might be worthwhile for large n, and is what the original # Fortran does. n = r.shape[1] assert r.shape[0] >= n r = r.copy() # Form the inverse of R in the full lower triangle of R. jrank = -1 abstol = tol * abs(r[0,0]) for i in range(n): if abs(r[i,i]) <= abstol: break r[i,i] **= -1 for j in range(i): temp = r[i,i] * r[i,j] r[i,j] = 0. r[i,:j+1] -= temp * r[j,:j+1] jrank = i # Form the full lower triangle of the inverse(R^T R) in the full # lower triangle of R. for i in range(jrank + 1): for j in range(i): r[j,:j+1] += r[i,j] * r[i,:j+1] r[i,:i+1] *= r[i,i] # Form the full upper triangle of the covariance matrix in the # strict upper triangle of R and in wa. wa = np.empty(n) wa.fill(r[0,0]) for i in range(n): pi = pmut[i] sing = i > jrank for j in range(i + 1): if sing: r[i,j] = 0. pj = pmut[j] if pj > pi: r[pi,pj] = r[i,j] elif pj < pi: r[pj,pi] = r[i,j] wa[pi] = r[i,i] # Symmetrize. for i in range(n): r[i,:i+1] = r[:i+1,i] r[i,i] = wa[i] return r
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spyder-ide/spyder-notebook
spyder_notebook/notebookplugin.py
NotebookPlugin.add_to_recent
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python
def add_to_recent(self, notebook): """ Add an entry to recent notebooks. We only maintain the list of the 20 most recent notebooks. """ if notebook not in self.recent_notebooks: self.recent_notebooks.insert(0, notebook) self.recent_notebooks = self.recent_notebooks[:20]
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tensorflow/tensorboard
tensorboard/plugins/interactive_inference/utils/inference_utils.py
get_label_vocab
def get_label_vocab(vocab_path): """Returns a list of label strings loaded from the provided path.""" if vocab_path: try: with tf.io.gfile.GFile(vocab_path, 'r') as f: return [line.rstrip('\n') for line in f] except tf.errors.NotFoundError as err: tf.logging.error('error reading vocab file: %s', err) return []
python
def get_label_vocab(vocab_path): """Returns a list of label strings loaded from the provided path.""" if vocab_path: try: with tf.io.gfile.GFile(vocab_path, 'r') as f: return [line.rstrip('\n') for line in f] except tf.errors.NotFoundError as err: tf.logging.error('error reading vocab file: %s', err) return []
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theiviaxx/Frog
frog/models.py
Video.generateThumbnail
def generateThumbnail(self): """Generates a square thumbnail""" source = ROOT / self.source.name thumbnail = source.parent / '_{}.jpg'.format(source.namebase) # -- Save thumbnail and put into queue poster = source.parent / '__{}.jpg'.format(source.namebase) cmd = [FROG_FFMPEG, '-i', str(source), '-ss', '1', '-vframes', '1', str(thumbnail), '-y'] proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) proc.communicate() image = pilImage.open(thumbnail) image.save(poster) self.poster = poster.replace(ROOT, '') box, width, height = cropBox(self.width, self.height) # Resize image.thumbnail((width, height), pilImage.ANTIALIAS) # Crop from center box = cropBox(*image.size)[0] image = image.crop(box) # save self.thumbnail = thumbnail.replace(ROOT, '') image.save(thumbnail)
python
def generateThumbnail(self): """Generates a square thumbnail""" source = ROOT / self.source.name thumbnail = source.parent / '_{}.jpg'.format(source.namebase) # -- Save thumbnail and put into queue poster = source.parent / '__{}.jpg'.format(source.namebase) cmd = [FROG_FFMPEG, '-i', str(source), '-ss', '1', '-vframes', '1', str(thumbnail), '-y'] proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) proc.communicate() image = pilImage.open(thumbnail) image.save(poster) self.poster = poster.replace(ROOT, '') box, width, height = cropBox(self.width, self.height) # Resize image.thumbnail((width, height), pilImage.ANTIALIAS) # Crop from center box = cropBox(*image.size)[0] image = image.crop(box) # save self.thumbnail = thumbnail.replace(ROOT, '') image.save(thumbnail)
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saltstack/salt
salt/daemons/masterapi.py
AutoKey.check_autosign
def check_autosign(self, keyid, autosign_grains=None): ''' Checks if the specified keyid should automatically be signed. ''' if self.opts['auto_accept']: return True if self.check_signing_file(keyid, self.opts.get('autosign_file', None)): return True if self.check_autosign_dir(keyid): return True if self.check_autosign_grains(autosign_grains): return True return False
python
def check_autosign(self, keyid, autosign_grains=None): ''' Checks if the specified keyid should automatically be signed. ''' if self.opts['auto_accept']: return True if self.check_signing_file(keyid, self.opts.get('autosign_file', None)): return True if self.check_autosign_dir(keyid): return True if self.check_autosign_grains(autosign_grains): return True return False
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wandb/client
wandb/vendor/prompt_toolkit/contrib/telnet/server.py
TelnetServer._process_callbacks
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python
def _process_callbacks(self): """ Process callbacks from `call_from_executor` in eventloop. """ # Flush all the pipe content. os.read(self._schedule_pipe[0], 1024) # Process calls from executor. calls_from_executor, self._calls_from_executor = self._calls_from_executor, [] for c in calls_from_executor: c()
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epfl-lts2/pygsp
pygsp/filters/filter.py
Filter.synthesize
def synthesize(self, s, method='chebyshev', order=30): r"""Convenience wrapper around :meth:`filter`. Will be an alias to `adjoint().filter()` in the future. """ if s.shape[-1] != self.Nf: raise ValueError('Last dimension (#features) should be the number ' 'of filters Nf = {}, got {}.'.format(self.Nf, s.shape)) return self.filter(s, method, order)
python
def synthesize(self, s, method='chebyshev', order=30): r"""Convenience wrapper around :meth:`filter`. Will be an alias to `adjoint().filter()` in the future. """ if s.shape[-1] != self.Nf: raise ValueError('Last dimension (#features) should be the number ' 'of filters Nf = {}, got {}.'.format(self.Nf, s.shape)) return self.filter(s, method, order)
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nvbn/thefuck
thefuck/types.py
Rule.from_path
def from_path(cls, path): """Creates rule instance from path. :type path: pathlib.Path :rtype: Rule """ name = path.name[:-3] with logs.debug_time(u'Importing rule: {};'.format(name)): rule_module = load_source(name, str(path)) priority = getattr(rule_module, 'priority', DEFAULT_PRIORITY) return cls(name, rule_module.match, rule_module.get_new_command, getattr(rule_module, 'enabled_by_default', True), getattr(rule_module, 'side_effect', None), settings.priority.get(name, priority), getattr(rule_module, 'requires_output', True))
python
def from_path(cls, path): """Creates rule instance from path. :type path: pathlib.Path :rtype: Rule """ name = path.name[:-3] with logs.debug_time(u'Importing rule: {};'.format(name)): rule_module = load_source(name, str(path)) priority = getattr(rule_module, 'priority', DEFAULT_PRIORITY) return cls(name, rule_module.match, rule_module.get_new_command, getattr(rule_module, 'enabled_by_default', True), getattr(rule_module, 'side_effect', None), settings.priority.get(name, priority), getattr(rule_module, 'requires_output', True))
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JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v10/matrixpilot.py
MAVLink.mission_write_partial_list_encode
def mission_write_partial_list_encode(self, target_system, target_component, start_index, end_index): ''' This message is sent to the MAV to write a partial list. If start index == end index, only one item will be transmitted / updated. If the start index is NOT 0 and above the current list size, this request should be REJECTED! target_system : System ID (uint8_t) target_component : Component ID (uint8_t) start_index : Start index, 0 by default and smaller / equal to the largest index of the current onboard list. (int16_t) end_index : End index, equal or greater than start index. (int16_t) ''' return MAVLink_mission_write_partial_list_message(target_system, target_component, start_index, end_index)
python
def mission_write_partial_list_encode(self, target_system, target_component, start_index, end_index): ''' This message is sent to the MAV to write a partial list. If start index == end index, only one item will be transmitted / updated. If the start index is NOT 0 and above the current list size, this request should be REJECTED! target_system : System ID (uint8_t) target_component : Component ID (uint8_t) start_index : Start index, 0 by default and smaller / equal to the largest index of the current onboard list. (int16_t) end_index : End index, equal or greater than start index. (int16_t) ''' return MAVLink_mission_write_partial_list_message(target_system, target_component, start_index, end_index)
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ltalirz/aiida-phtools
aiida_phtools/calculations/distance_matrix.py
DistanceMatrixCalculation._validate_inputs
def _validate_inputs(self, inputdict): """ Validate input links. """ # Check code try: code = inputdict.pop(self.get_linkname('code')) except KeyError: raise InputValidationError("No code specified for this " "calculation") # Check input files try: surface_sample = inputdict.pop(self.get_linkname('surface_sample')) if not isinstance(surface_sample, SinglefileData): raise InputValidationError( "surface_sample not of type SinglefileData") except KeyError: raise InputValidationError( "No input structure specified for calculation") try: cell = inputdict.pop(self.get_linkname('cell')) if not isinstance(cell, SinglefileData): raise InputValidationError("cell not of type SinglefileData") except KeyError: raise InputValidationError( "No input structure specified for calculation") # Check that nothing is left unparsed if inputdict: raise ValidationError("Unrecognized inputs: {}".format(inputdict)) return code, surface_sample, cell
python
def _validate_inputs(self, inputdict): """ Validate input links. """ # Check code try: code = inputdict.pop(self.get_linkname('code')) except KeyError: raise InputValidationError("No code specified for this " "calculation") # Check input files try: surface_sample = inputdict.pop(self.get_linkname('surface_sample')) if not isinstance(surface_sample, SinglefileData): raise InputValidationError( "surface_sample not of type SinglefileData") except KeyError: raise InputValidationError( "No input structure specified for calculation") try: cell = inputdict.pop(self.get_linkname('cell')) if not isinstance(cell, SinglefileData): raise InputValidationError("cell not of type SinglefileData") except KeyError: raise InputValidationError( "No input structure specified for calculation") # Check that nothing is left unparsed if inputdict: raise ValidationError("Unrecognized inputs: {}".format(inputdict)) return code, surface_sample, cell
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examples/shared/variational_autoencoder.py
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def transform(self, X): """Transform data by mapping it into the latent space.""" # Note: This maps to mean of distribution, we could alternatively # sample from Gaussian distribution return self.sess.run(self.z_mean, feed_dict={self.x: X})
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def transform(self, X): """Transform data by mapping it into the latent space.""" # Note: This maps to mean of distribution, we could alternatively # sample from Gaussian distribution return self.sess.run(self.z_mean, feed_dict={self.x: X})
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T-002/pycast
bin/examples/LivingRoomEnergy/server.py
holtWinters
def holtWinters(request): """ Performs Holt Winters Smoothing on the given post data. Expects the following values set in the post of the request: smoothingFactor - float trendSmoothingFactor - float seasonSmoothingFactor - float seasonLength - integer valuesToForecast - integer data - two dimensional array of [timestamp, value] """ #Parse arguments smoothingFactor = float(request.POST.get('smoothingFactor', 0.2)) trendSmoothingFactor = float(request.POST.get('trendSmoothingFactor', 0.3)) seasonSmoothingFactor = float(request.POST.get('seasonSmoothingFactor', 0.4)) seasonLength = int(request.POST.get('seasonLength', 6)) valuesToForecast = int(request.POST.get('valuesToForecast', 0)) data = json.loads(request.POST.get('data', [])) #perform smoothing hwm = HoltWintersMethod(smoothingFactor = smoothingFactor, trendSmoothingFactor = trendSmoothingFactor, seasonSmoothingFactor = seasonSmoothingFactor, seasonLength = seasonLength, valuesToForecast = valuesToForecast) original = TimeSeries.from_twodim_list(data) original.set_timeformat("%d.%m") smoothed = hwm.execute(original) smoothed.set_timeformat("%d.%m") error = SMAPE() error.initialize(original, smoothed) #process the result result = { 'original': original, 'smoothed': smoothed, 'error': round(error.get_error(), 3) } return itty.Response(json.dumps(result, cls=PycastEncoder), content_type='application/json')
python
def holtWinters(request): """ Performs Holt Winters Smoothing on the given post data. Expects the following values set in the post of the request: smoothingFactor - float trendSmoothingFactor - float seasonSmoothingFactor - float seasonLength - integer valuesToForecast - integer data - two dimensional array of [timestamp, value] """ #Parse arguments smoothingFactor = float(request.POST.get('smoothingFactor', 0.2)) trendSmoothingFactor = float(request.POST.get('trendSmoothingFactor', 0.3)) seasonSmoothingFactor = float(request.POST.get('seasonSmoothingFactor', 0.4)) seasonLength = int(request.POST.get('seasonLength', 6)) valuesToForecast = int(request.POST.get('valuesToForecast', 0)) data = json.loads(request.POST.get('data', [])) #perform smoothing hwm = HoltWintersMethod(smoothingFactor = smoothingFactor, trendSmoothingFactor = trendSmoothingFactor, seasonSmoothingFactor = seasonSmoothingFactor, seasonLength = seasonLength, valuesToForecast = valuesToForecast) original = TimeSeries.from_twodim_list(data) original.set_timeformat("%d.%m") smoothed = hwm.execute(original) smoothed.set_timeformat("%d.%m") error = SMAPE() error.initialize(original, smoothed) #process the result result = { 'original': original, 'smoothed': smoothed, 'error': round(error.get_error(), 3) } return itty.Response(json.dumps(result, cls=PycastEncoder), content_type='application/json')
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onnx/onnxmltools
onnxmltools/convert/sparkml/_parse.py
_parse_sparkml
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python
def _parse_sparkml(spark, scope, model, global_inputs, output_dict): ''' This is a delegate function. It doesn't nothing but invoke the correct parsing function according to the input model's type. :param scope: Scope object :param model: A spark-ml object (e.g., OneHotEncoder and LogisticRegression) :param inputs: A list of variables :return: The output variables produced by the input model ''' if isinstance(model, PipelineModel): return _parse_sparkml_pipeline(spark, scope, model, global_inputs, output_dict) else: return _parse_sparkml_simple_model(spark, scope, model, global_inputs, output_dict)
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flowersteam/explauto
explauto/sensorimotor_model/inverse/cma.py
CMADataLogger.plot_all
def plot_all(self, fig=None, iabscissa=1, iteridx=None, foffset=1e-19, x_opt=None, fontsize=9): """ plot data from a `CMADataLogger` (using the files written by the logger). Arguments --------- `fig` figure number, by default 425 `iabscissa` ``0==plot`` versus iteration count, ``1==plot`` versus function evaluation number `iteridx` iteration indices to plot Return `CMADataLogger` itself. Examples -------- :: import cma logger = cma.CMADataLogger() # with default name # try to plot the "default logging" data (e.g. # from previous fmin calls, which is essentially what # also cma.plot() does) logger.plot_all() cma.savefig('fig425.png') # save current figure logger.closefig() Dependencies: matlabplotlib/pyplot. """ try: # pyplot: prodedural interface for matplotlib from matplotlib.pyplot import figure, subplot, gcf except ImportError: ImportError('could not find matplotlib.pyplot module, function plot() is not available') return if fig is None: fig = 426 if iabscissa not in (0, 1): iabscissa = 1 self.load() dat = self # index out some data if iteridx is not None: self.select_data(iteridx) if len(dat.f) == 0: print('nothing to plot') return # not in use anymore, see formatter above # xticklocs = np.arange(5) * np.round(minxend/4., -int(np.log10(minxend/4.))) # dfit(dfit<1e-98) = NaN; # TODO: if abscissa==0 plot in chunks, ie loop over subsets where dat.f[:,0]==countiter is monotonous figure(fig) self._enter_plotting(fontsize) self.fighandle = gcf() # fighandle.number if 1 < 3: subplot(2, 3, 1) self.plot_divers(iabscissa, foffset) pyplot.xlabel('') # standard deviations subplot(2, 3, 4) self.plot_stds(iabscissa) # Scaling subplot(2, 3, 2) self.plot_axes_scaling(iabscissa) pyplot.xlabel('') # spectrum of correlation matrix subplot(2, 3, 5) self.plot_correlations(iabscissa) # x-vectors subplot(2, 3, 3) self.plot_xrecent(iabscissa, x_opt) pyplot.xlabel('') subplot(2, 3, 6) self.plot_mean(iabscissa, x_opt) self._finalize_plotting() return self
python
def plot_all(self, fig=None, iabscissa=1, iteridx=None, foffset=1e-19, x_opt=None, fontsize=9): """ plot data from a `CMADataLogger` (using the files written by the logger). Arguments --------- `fig` figure number, by default 425 `iabscissa` ``0==plot`` versus iteration count, ``1==plot`` versus function evaluation number `iteridx` iteration indices to plot Return `CMADataLogger` itself. Examples -------- :: import cma logger = cma.CMADataLogger() # with default name # try to plot the "default logging" data (e.g. # from previous fmin calls, which is essentially what # also cma.plot() does) logger.plot_all() cma.savefig('fig425.png') # save current figure logger.closefig() Dependencies: matlabplotlib/pyplot. """ try: # pyplot: prodedural interface for matplotlib from matplotlib.pyplot import figure, subplot, gcf except ImportError: ImportError('could not find matplotlib.pyplot module, function plot() is not available') return if fig is None: fig = 426 if iabscissa not in (0, 1): iabscissa = 1 self.load() dat = self # index out some data if iteridx is not None: self.select_data(iteridx) if len(dat.f) == 0: print('nothing to plot') return # not in use anymore, see formatter above # xticklocs = np.arange(5) * np.round(minxend/4., -int(np.log10(minxend/4.))) # dfit(dfit<1e-98) = NaN; # TODO: if abscissa==0 plot in chunks, ie loop over subsets where dat.f[:,0]==countiter is monotonous figure(fig) self._enter_plotting(fontsize) self.fighandle = gcf() # fighandle.number if 1 < 3: subplot(2, 3, 1) self.plot_divers(iabscissa, foffset) pyplot.xlabel('') # standard deviations subplot(2, 3, 4) self.plot_stds(iabscissa) # Scaling subplot(2, 3, 2) self.plot_axes_scaling(iabscissa) pyplot.xlabel('') # spectrum of correlation matrix subplot(2, 3, 5) self.plot_correlations(iabscissa) # x-vectors subplot(2, 3, 3) self.plot_xrecent(iabscissa, x_opt) pyplot.xlabel('') subplot(2, 3, 6) self.plot_mean(iabscissa, x_opt) self._finalize_plotting() return self
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fhcrc/taxtastic
taxtastic/ncbi.py
read_names
def read_names(rows, source_id=1): """Return an iterator of rows ready to insert into table "names". Adds columns "is_primary" (identifying the primary name for each tax_id with a vaule of 1) and "is_classified" (always None). * rows - iterator of lists (eg, output from read_archive or read_dmp) * unclassified_regex - a compiled re matching "unclassified" names From the NCBI docs: Taxonomy names file (names.dmp): tax_id -- the id of node associated with this name name_txt -- name itself unique name -- the unique variant of this name if name not unique name class -- (synonym, common name, ...) """ ncbi_keys = ['tax_id', 'tax_name', 'unique_name', 'name_class'] extra_keys = ['source_id', 'is_primary', 'is_classified'] # is_classified applies to species only; we will set this value # later is_classified = None tax_id = ncbi_keys.index('tax_id') tax_name = ncbi_keys.index('tax_name') unique_name = ncbi_keys.index('unique_name') name_class = ncbi_keys.index('name_class') yield ncbi_keys + extra_keys for tid, grp in itertools.groupby(rows, itemgetter(tax_id)): # confirm that each tax_id has exactly one scientific name num_primary = 0 for r in grp: is_primary = r[name_class] == 'scientific name' # fix primary key uniqueness violation if r[unique_name]: r[tax_name] = r[unique_name] num_primary += is_primary yield (r + [source_id, is_primary, is_classified]) assert num_primary == 1
python
def read_names(rows, source_id=1): """Return an iterator of rows ready to insert into table "names". Adds columns "is_primary" (identifying the primary name for each tax_id with a vaule of 1) and "is_classified" (always None). * rows - iterator of lists (eg, output from read_archive or read_dmp) * unclassified_regex - a compiled re matching "unclassified" names From the NCBI docs: Taxonomy names file (names.dmp): tax_id -- the id of node associated with this name name_txt -- name itself unique name -- the unique variant of this name if name not unique name class -- (synonym, common name, ...) """ ncbi_keys = ['tax_id', 'tax_name', 'unique_name', 'name_class'] extra_keys = ['source_id', 'is_primary', 'is_classified'] # is_classified applies to species only; we will set this value # later is_classified = None tax_id = ncbi_keys.index('tax_id') tax_name = ncbi_keys.index('tax_name') unique_name = ncbi_keys.index('unique_name') name_class = ncbi_keys.index('name_class') yield ncbi_keys + extra_keys for tid, grp in itertools.groupby(rows, itemgetter(tax_id)): # confirm that each tax_id has exactly one scientific name num_primary = 0 for r in grp: is_primary = r[name_class] == 'scientific name' # fix primary key uniqueness violation if r[unique_name]: r[tax_name] = r[unique_name] num_primary += is_primary yield (r + [source_id, is_primary, is_classified]) assert num_primary == 1
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estnltk/text.py
Text.starts
def starts(self, layer): """Retrieve start positions of elements if given layer.""" starts = [] for data in self[layer]: starts.append(data[START]) return starts
python
def starts(self, layer): """Retrieve start positions of elements if given layer.""" starts = [] for data in self[layer]: starts.append(data[START]) return starts
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pgmpy/sampling/Sampling.py
GibbsSampling._get_kernel_from_bayesian_model
def _get_kernel_from_bayesian_model(self, model): """ Computes the Gibbs transition models from a Bayesian Network. 'Probabilistic Graphical Model Principles and Techniques', Koller and Friedman, Section 12.3.3 pp 512-513. Parameters: ----------- model: BayesianModel The model from which probabilities will be computed. """ self.variables = np.array(model.nodes()) self.cardinalities = {var: model.get_cpds(var).variable_card for var in self.variables} for var in self.variables: other_vars = [v for v in self.variables if var != v] other_cards = [self.cardinalities[v] for v in other_vars] cpds = [cpd for cpd in model.cpds if var in cpd.scope()] prod_cpd = factor_product(*cpds) kernel = {} scope = set(prod_cpd.scope()) for tup in itertools.product(*[range(card) for card in other_cards]): states = [State(v, s) for v, s in zip(other_vars, tup) if v in scope] prod_cpd_reduced = prod_cpd.reduce(states, inplace=False) kernel[tup] = prod_cpd_reduced.values / sum(prod_cpd_reduced.values) self.transition_models[var] = kernel
python
def _get_kernel_from_bayesian_model(self, model): """ Computes the Gibbs transition models from a Bayesian Network. 'Probabilistic Graphical Model Principles and Techniques', Koller and Friedman, Section 12.3.3 pp 512-513. Parameters: ----------- model: BayesianModel The model from which probabilities will be computed. """ self.variables = np.array(model.nodes()) self.cardinalities = {var: model.get_cpds(var).variable_card for var in self.variables} for var in self.variables: other_vars = [v for v in self.variables if var != v] other_cards = [self.cardinalities[v] for v in other_vars] cpds = [cpd for cpd in model.cpds if var in cpd.scope()] prod_cpd = factor_product(*cpds) kernel = {} scope = set(prod_cpd.scope()) for tup in itertools.product(*[range(card) for card in other_cards]): states = [State(v, s) for v, s in zip(other_vars, tup) if v in scope] prod_cpd_reduced = prod_cpd.reduce(states, inplace=False) kernel[tup] = prod_cpd_reduced.values / sum(prod_cpd_reduced.values) self.transition_models[var] = kernel
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pyciss/opusapi.py
OPUS.create_request_with_query
def create_request_with_query(self, kind, query, size="thumb", fmt="json"): """api/data.[fmt], api/images/[size].[fmt] api/files.[fmt] kind = ['data', 'images', 'files'] """ if kind == "data" or kind == "files": url = "{}/{}.{}".format(base_url, kind, fmt) elif kind == "images": url = "{}/images/{}.{}".format(base_url, size, fmt) self.url = url self.r = requests.get(url, params=unquote(urlencode(query)))
python
def create_request_with_query(self, kind, query, size="thumb", fmt="json"): """api/data.[fmt], api/images/[size].[fmt] api/files.[fmt] kind = ['data', 'images', 'files'] """ if kind == "data" or kind == "files": url = "{}/{}.{}".format(base_url, kind, fmt) elif kind == "images": url = "{}/images/{}.{}".format(base_url, size, fmt) self.url = url self.r = requests.get(url, params=unquote(urlencode(query)))
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clean_dict
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python
def clean_dict(d, test=lambda v: v): """ Return only keys that meet the test :param d: Dictionary :param test: the test to run on the value (example override is: "lambda v: v is not None") :return: Cleaned dictionary """ return {k: v for k, v in d.items() if test(v)}
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bcbio/rnaseq/express.py
_get_column
def _get_column(in_file, out_file, column, data=None): """Subset one column from a file """ with file_transaction(data, out_file) as tx_out_file: with open(in_file) as in_handle: with open(tx_out_file, 'w') as out_handle: for line in in_handle: cols = line.strip().split("\t") if line.find("eff_count") > 0: continue number = cols[column] if column == 7: number = int(round(float(number), 0)) out_handle.write("%s\t%s\n" % (cols[1], number)) return out_file
python
def _get_column(in_file, out_file, column, data=None): """Subset one column from a file """ with file_transaction(data, out_file) as tx_out_file: with open(in_file) as in_handle: with open(tx_out_file, 'w') as out_handle: for line in in_handle: cols = line.strip().split("\t") if line.find("eff_count") > 0: continue number = cols[column] if column == 7: number = int(round(float(number), 0)) out_handle.write("%s\t%s\n" % (cols[1], number)) return out_file
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argyle/system.py
create_user
def create_user(name, groups=None, key_file=None): """Create a user. Adds a key file to authorized_keys if given.""" groups = groups or [] if not user_exists(name): for group in groups: if not group_exists(group): sudo(u"addgroup %s" % group) groups = groups and u'-G %s' % u','.join(groups) or '' sudo(u"useradd -m %s -s /bin/bash %s" % (groups, name)) sudo(u"passwd -d %s" % name) if key_file: sudo(u"mkdir -p /home/%s/.ssh" % name) put(key_file, u"/home/%s/.ssh/authorized_keys" % name, use_sudo=True) sudo(u"chown -R %(name)s:%(name)s /home/%(name)s/.ssh" % {'name': name})
python
def create_user(name, groups=None, key_file=None): """Create a user. Adds a key file to authorized_keys if given.""" groups = groups or [] if not user_exists(name): for group in groups: if not group_exists(group): sudo(u"addgroup %s" % group) groups = groups and u'-G %s' % u','.join(groups) or '' sudo(u"useradd -m %s -s /bin/bash %s" % (groups, name)) sudo(u"passwd -d %s" % name) if key_file: sudo(u"mkdir -p /home/%s/.ssh" % name) put(key_file, u"/home/%s/.ssh/authorized_keys" % name, use_sudo=True) sudo(u"chown -R %(name)s:%(name)s /home/%(name)s/.ssh" % {'name': name})
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pydeconz/__init__.py
DeconzSession.async_event_handler
def async_event_handler(self, event: dict) -> None: """Receive event from websocket and identifies where the event belong. { "t": "event", "e": "changed", "r": "sensors", "id": "12", "state": { "buttonevent": 2002 } } """ if event['e'] == 'added': if event['r'] == 'lights' and event['id'] not in self.lights: device_type = 'light' device = self.lights[event['id']] = DeconzLight( event['id'], event['light'], self.async_put_state) elif event['r'] == 'sensors' and event['id'] not in self.sensors: if supported_sensor(event['sensor']): device_type = 'sensor' device = self.sensors[event['id']] = create_sensor( event['id'], event['sensor'], self.async_put_state) else: _LOGGER.warning('Unsupported sensor %s', event) return else: _LOGGER.debug('Unsupported event %s', event) return if self.async_add_device_callback: self.async_add_device_callback(device_type, device) elif event['e'] == 'changed': if event['r'] == 'groups' and event['id'] in self.groups: self.groups[event['id']].async_update(event) elif event['r'] == 'lights' and event['id'] in self.lights: self.lights[event['id']].async_update(event) self.update_group_color([event['id']]) elif event['r'] == 'sensors' and event['id'] in self.sensors: self.sensors[event['id']].async_update(event) else: _LOGGER.debug('Unsupported event %s', event) elif event['e'] == 'deleted': _LOGGER.debug('Removed event %s', event) else: _LOGGER.debug('Unsupported event %s', event)
python
def async_event_handler(self, event: dict) -> None: """Receive event from websocket and identifies where the event belong. { "t": "event", "e": "changed", "r": "sensors", "id": "12", "state": { "buttonevent": 2002 } } """ if event['e'] == 'added': if event['r'] == 'lights' and event['id'] not in self.lights: device_type = 'light' device = self.lights[event['id']] = DeconzLight( event['id'], event['light'], self.async_put_state) elif event['r'] == 'sensors' and event['id'] not in self.sensors: if supported_sensor(event['sensor']): device_type = 'sensor' device = self.sensors[event['id']] = create_sensor( event['id'], event['sensor'], self.async_put_state) else: _LOGGER.warning('Unsupported sensor %s', event) return else: _LOGGER.debug('Unsupported event %s', event) return if self.async_add_device_callback: self.async_add_device_callback(device_type, device) elif event['e'] == 'changed': if event['r'] == 'groups' and event['id'] in self.groups: self.groups[event['id']].async_update(event) elif event['r'] == 'lights' and event['id'] in self.lights: self.lights[event['id']].async_update(event) self.update_group_color([event['id']]) elif event['r'] == 'sensors' and event['id'] in self.sensors: self.sensors[event['id']].async_update(event) else: _LOGGER.debug('Unsupported event %s', event) elif event['e'] == 'deleted': _LOGGER.debug('Removed event %s', event) else: _LOGGER.debug('Unsupported event %s', event)
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Token.pos
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python
def pos(self): """ Lazy-loads the part of speech tag for this word :getter: Returns the plain string value of the POS tag for the word :type: str """ if self._pos is None: poses = self._element.xpath('POS/text()') if len(poses) > 0: self._pos = poses[0] return self._pos
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bin/benchmark_nc.py
extract_native_client_tarball
def extract_native_client_tarball(dir): r''' Download a native_client.tar.xz file from TaskCluster and extract it to dir. ''' assert_valid_dir(dir) target_tarball = os.path.join(dir, 'native_client.tar.xz') if os.path.isfile(target_tarball) and os.stat(target_tarball).st_size == 0: return subprocess.check_call(['pixz', '-d', 'native_client.tar.xz'], cwd=dir) subprocess.check_call(['tar', 'xf', 'native_client.tar'], cwd=dir) os.unlink(os.path.join(dir, 'native_client.tar')) open(target_tarball, 'w').close()
python
def extract_native_client_tarball(dir): r''' Download a native_client.tar.xz file from TaskCluster and extract it to dir. ''' assert_valid_dir(dir) target_tarball = os.path.join(dir, 'native_client.tar.xz') if os.path.isfile(target_tarball) and os.stat(target_tarball).st_size == 0: return subprocess.check_call(['pixz', '-d', 'native_client.tar.xz'], cwd=dir) subprocess.check_call(['tar', 'xf', 'native_client.tar'], cwd=dir) os.unlink(os.path.join(dir, 'native_client.tar')) open(target_tarball, 'w').close()
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hazelcast/protocol/codec/atomic_reference_set_and_get_codec.py
calculate_size
def calculate_size(name, new_value): """ Calculates the request payload size""" data_size = 0 data_size += calculate_size_str(name) data_size += BOOLEAN_SIZE_IN_BYTES if new_value is not None: data_size += calculate_size_data(new_value) return data_size
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def calculate_size(name, new_value): """ Calculates the request payload size""" data_size = 0 data_size += calculate_size_str(name) data_size += BOOLEAN_SIZE_IN_BYTES if new_value is not None: data_size += calculate_size_data(new_value) return data_size
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azure-devops/azure/devops/v5_0/service_hooks/service_hooks_client.py
ServiceHooksClient.get_notification
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python
def get_notification(self, subscription_id, notification_id): """GetNotification. Get a specific notification for a subscription. :param str subscription_id: ID for a subscription. :param int notification_id: :rtype: :class:`<Notification> <azure.devops.v5_0.service_hooks.models.Notification>` """ route_values = {} if subscription_id is not None: route_values['subscriptionId'] = self._serialize.url('subscription_id', subscription_id, 'str') if notification_id is not None: route_values['notificationId'] = self._serialize.url('notification_id', notification_id, 'int') response = self._send(http_method='GET', location_id='0c62d343-21b0-4732-997b-017fde84dc28', version='5.0', route_values=route_values) return self._deserialize('Notification', response)
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list
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python
def list(): """ List available format. """ choice_len = max(map(len, _input_choices.keys())) tmpl = " {:<%d}: {}\n" % choice_len text = ''.join(map( lambda k_v: tmpl.format(k_v[0], k_v[1][0]), six.iteritems(_input_choices))) click.echo(text)
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pumpp/sampler.py
SequentialSampler.indices
def indices(self, data): '''Generate patch start indices Parameters ---------- data : dict of np.ndarray As produced by pumpp.transform Yields ------ start : int >= 0 The start index of a sample patch ''' duration = self.data_duration(data) for start in range(0, duration - self.duration, self.stride): yield start
python
def indices(self, data): '''Generate patch start indices Parameters ---------- data : dict of np.ndarray As produced by pumpp.transform Yields ------ start : int >= 0 The start index of a sample patch ''' duration = self.data_duration(data) for start in range(0, duration - self.duration, self.stride): yield start
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saltstack/salt
salt/modules/pdbedit.py
modify
def modify( login, password=None, password_hashed=False, domain=None, profile=None, script=None, drive=None, homedir=None, fullname=None, account_desc=None, account_control=None, machine_sid=None, user_sid=None, reset_login_hours=False, reset_bad_password_count=False, ): ''' Modify user account login : string login name password : string password password_hashed : boolean set if password is a nt hash instead of plain text domain : string users domain profile : string profile path script : string logon script drive : string home drive homedir : string home directory fullname : string full name account_desc : string account description machine_sid : string specify the machines new primary group SID or rid user_sid : string specify the users new primary group SID or rid account_control : string specify user account control properties .. note:: Only the following can be set: - N: No password required - D: Account disabled - H: Home directory required - L: Automatic Locking - X: Password does not expire reset_login_hours : boolean reset the users allowed logon hours reset_bad_password_count : boolean reset the stored bad login counter .. note:: if user is absent and password is provided, the user will be created CLI Example: .. code-block:: bash salt '*' pdbedit.modify inara fullname='Inara Serra' salt '*' pdbedit.modify simon password=r1v3r salt '*' pdbedit.modify jane drive='V:' homedir='\\\\serenity\\jane\\profile' salt '*' pdbedit.modify mal account_control=NX ''' ret = 'unchanged' # flag mapping flags = { 'domain': '--domain=', 'full name': '--fullname=', 'account desc': '--account-desc=', 'home directory': '--homedir=', 'homedir drive': '--drive=', 'profile path': '--profile=', 'logon script': '--script=', 'account flags': '--account-control=', 'user sid': '-U ', 'machine sid': '-M ', } # field mapping provided = { 'domain': domain, 'full name': fullname, 'account desc': account_desc, 'home directory': homedir, 'homedir drive': drive, 'profile path': profile, 'logon script': script, 'account flags': account_control, 'user sid': user_sid, 'machine sid': machine_sid, } # update password if password: ret = create(login, password, password_hashed)[login] if ret not in ['updated', 'created', 'unchanged']: return {login: ret} elif login not in list_users(False): return {login: 'absent'} # check for changes current = get_user(login, hashes=True) changes = {} for key, val in provided.items(): if key in ['user sid', 'machine sid']: if val is not None and key in current and not current[key].endswith(six.text_type(val)): changes[key] = six.text_type(val) elif key in ['account flags']: if val is not None: if val.startswith('['): val = val[1:-1] new = [] for f in val.upper(): if f not in ['N', 'D', 'H', 'L', 'X']: logmsg = 'pdbedit.modify - unknown {} flag for account_control, ignored'.format(f) log.warning(logmsg) else: new.append(f) changes[key] = "[{flags}]".format(flags="".join(new)) else: if val is not None and key in current and current[key] != val: changes[key] = val # apply changes if changes or reset_login_hours or reset_bad_password_count: cmds = [] for change in changes: cmds.append('{flag}{value}'.format( flag=flags[change], value=_quote_args(changes[change]), )) if reset_login_hours: cmds.append('--logon-hours-reset') if reset_bad_password_count: cmds.append('--bad-password-count-reset') res = __salt__['cmd.run_all']( 'pdbedit --modify --user {login} {changes}'.format( login=_quote_args(login), changes=" ".join(cmds), ), ) if res['retcode'] > 0: return {login: res['stderr'] if 'stderr' in res else res['stdout']} if ret != 'created': ret = 'updated' return {login: ret}
python
def modify( login, password=None, password_hashed=False, domain=None, profile=None, script=None, drive=None, homedir=None, fullname=None, account_desc=None, account_control=None, machine_sid=None, user_sid=None, reset_login_hours=False, reset_bad_password_count=False, ): ''' Modify user account login : string login name password : string password password_hashed : boolean set if password is a nt hash instead of plain text domain : string users domain profile : string profile path script : string logon script drive : string home drive homedir : string home directory fullname : string full name account_desc : string account description machine_sid : string specify the machines new primary group SID or rid user_sid : string specify the users new primary group SID or rid account_control : string specify user account control properties .. note:: Only the following can be set: - N: No password required - D: Account disabled - H: Home directory required - L: Automatic Locking - X: Password does not expire reset_login_hours : boolean reset the users allowed logon hours reset_bad_password_count : boolean reset the stored bad login counter .. note:: if user is absent and password is provided, the user will be created CLI Example: .. code-block:: bash salt '*' pdbedit.modify inara fullname='Inara Serra' salt '*' pdbedit.modify simon password=r1v3r salt '*' pdbedit.modify jane drive='V:' homedir='\\\\serenity\\jane\\profile' salt '*' pdbedit.modify mal account_control=NX ''' ret = 'unchanged' # flag mapping flags = { 'domain': '--domain=', 'full name': '--fullname=', 'account desc': '--account-desc=', 'home directory': '--homedir=', 'homedir drive': '--drive=', 'profile path': '--profile=', 'logon script': '--script=', 'account flags': '--account-control=', 'user sid': '-U ', 'machine sid': '-M ', } # field mapping provided = { 'domain': domain, 'full name': fullname, 'account desc': account_desc, 'home directory': homedir, 'homedir drive': drive, 'profile path': profile, 'logon script': script, 'account flags': account_control, 'user sid': user_sid, 'machine sid': machine_sid, } # update password if password: ret = create(login, password, password_hashed)[login] if ret not in ['updated', 'created', 'unchanged']: return {login: ret} elif login not in list_users(False): return {login: 'absent'} # check for changes current = get_user(login, hashes=True) changes = {} for key, val in provided.items(): if key in ['user sid', 'machine sid']: if val is not None and key in current and not current[key].endswith(six.text_type(val)): changes[key] = six.text_type(val) elif key in ['account flags']: if val is not None: if val.startswith('['): val = val[1:-1] new = [] for f in val.upper(): if f not in ['N', 'D', 'H', 'L', 'X']: logmsg = 'pdbedit.modify - unknown {} flag for account_control, ignored'.format(f) log.warning(logmsg) else: new.append(f) changes[key] = "[{flags}]".format(flags="".join(new)) else: if val is not None and key in current and current[key] != val: changes[key] = val # apply changes if changes or reset_login_hours or reset_bad_password_count: cmds = [] for change in changes: cmds.append('{flag}{value}'.format( flag=flags[change], value=_quote_args(changes[change]), )) if reset_login_hours: cmds.append('--logon-hours-reset') if reset_bad_password_count: cmds.append('--bad-password-count-reset') res = __salt__['cmd.run_all']( 'pdbedit --modify --user {login} {changes}'.format( login=_quote_args(login), changes=" ".join(cmds), ), ) if res['retcode'] > 0: return {login: res['stderr'] if 'stderr' in res else res['stdout']} if ret != 'created': ret = 'updated' return {login: ret}
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queries_start_with
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python
def queries_start_with(queries, prefixes): """Check if any queries start with any item from *prefixes*.""" for query in sqlparse.split(queries): if query and query_starts_with(query, prefixes) is True: return True return False
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geopy/geopy
geopy/geocoders/geolake.py
Geolake.geocode
def geocode( self, query, country_codes=None, exactly_one=True, timeout=DEFAULT_SENTINEL, ): """ Return a location point by address. :param str query: The address or query you wish to geocode. For a structured query, provide a dictionary whose keys are one of: `country`, `state`, `city`, `zipcode`, `street`, `address`, `houseNumber` or `subNumber`. :param country_codes: Provides the geocoder with a list of country codes that the query may reside in. This value will limit the geocoder to the supplied countries. The country code is a 2 character code as defined by the ISO-3166-1 alpha-2 standard (e.g. ``FR``). Multiple countries can be specified with a Python list. .. versionchanged:: 1.19.0 Previously only a Python list of countries could be specified. Now a single country as a string can be specified as well. :type country_codes: str or list :param bool exactly_one: Return one result or a list of one result. :param int timeout: Time, in seconds, to wait for the geocoding service to respond before raising a :class:`geopy.exc.GeocoderTimedOut` exception. Set this only if you wish to override, on this call only, the value set during the geocoder's initialization. :rtype: ``None``, :class:`geopy.location.Location` or a list of them, if ``exactly_one=False``. """ if isinstance(query, dict): params = { key: val for key, val in query.items() if key in self.structured_query_params } params['api_key'] = self.api_key else: params = { 'api_key': self.api_key, 'q': self.format_string % query, } if not country_codes: country_codes = [] if isinstance(country_codes, string_compare): country_codes = [country_codes] if country_codes: params['countryCodes'] = ",".join(country_codes) url = "?".join((self.api, urlencode(params))) logger.debug("%s.geocode: %s", self.__class__.__name__, url) return self._parse_json( self._call_geocoder(url, timeout=timeout), exactly_one )
python
def geocode( self, query, country_codes=None, exactly_one=True, timeout=DEFAULT_SENTINEL, ): """ Return a location point by address. :param str query: The address or query you wish to geocode. For a structured query, provide a dictionary whose keys are one of: `country`, `state`, `city`, `zipcode`, `street`, `address`, `houseNumber` or `subNumber`. :param country_codes: Provides the geocoder with a list of country codes that the query may reside in. This value will limit the geocoder to the supplied countries. The country code is a 2 character code as defined by the ISO-3166-1 alpha-2 standard (e.g. ``FR``). Multiple countries can be specified with a Python list. .. versionchanged:: 1.19.0 Previously only a Python list of countries could be specified. Now a single country as a string can be specified as well. :type country_codes: str or list :param bool exactly_one: Return one result or a list of one result. :param int timeout: Time, in seconds, to wait for the geocoding service to respond before raising a :class:`geopy.exc.GeocoderTimedOut` exception. Set this only if you wish to override, on this call only, the value set during the geocoder's initialization. :rtype: ``None``, :class:`geopy.location.Location` or a list of them, if ``exactly_one=False``. """ if isinstance(query, dict): params = { key: val for key, val in query.items() if key in self.structured_query_params } params['api_key'] = self.api_key else: params = { 'api_key': self.api_key, 'q': self.format_string % query, } if not country_codes: country_codes = [] if isinstance(country_codes, string_compare): country_codes = [country_codes] if country_codes: params['countryCodes'] = ",".join(country_codes) url = "?".join((self.api, urlencode(params))) logger.debug("%s.geocode: %s", self.__class__.__name__, url) return self._parse_json( self._call_geocoder(url, timeout=timeout), exactly_one )
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DLR-RM/RAFCON
source/rafcon/gui/controllers/utils/tree_view_controller.py
TreeViewController.select_entry
def select_entry(self, core_element_id, by_cursor=True): """Selects the row entry belonging to the given core_element_id by cursor or tree selection""" path = self.get_path_for_core_element(core_element_id) if path: if by_cursor: self.tree_view.set_cursor(path) else: self.tree_view.get_selection().select_path(path) else: self._logger.warning("Path not valid: {0} (by_cursor {1})".format(str(core_element_id), str(by_cursor)))
python
def select_entry(self, core_element_id, by_cursor=True): """Selects the row entry belonging to the given core_element_id by cursor or tree selection""" path = self.get_path_for_core_element(core_element_id) if path: if by_cursor: self.tree_view.set_cursor(path) else: self.tree_view.get_selection().select_path(path) else: self._logger.warning("Path not valid: {0} (by_cursor {1})".format(str(core_element_id), str(by_cursor)))
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metator/scripts/fasta_utils.py
rename_proteins
def rename_proteins(prot_in, prot_out=None, chunk_size=DEFAULT_CHUNK_SIZE): """Rename prodigal output files Rename output files from prodigal according to the following naming scheme: >contigX_chunkY__geneZ Chunk numbering starts at 0 and gene identification is taken from prodigal. Parameters ---------- prot_in : file, str or pathlib.Path The input protein file in FASTA format to be renamed. prot_out : file, str or pathlib.Path The output protein file to be renamed into. chunk_size : int, optional The size of the chunks (in bp) used in the pipeline. Default is 1000. """ if prot_out is None: prot_out = "{}_renamed.fa".format(prot_in.split(".")[0]) with open(prot_out, "w") as prot_out_handle: for record in SeqIO.parse(prot_in, "fasta"): header = record.description name, pos_start, _, _, _ = header.split("#") chunk_start = int(pos_start) // chunk_size name_split = name.split("_") contig_name = "_".join(name_split[:-1]) gene_id = name_split[-1] new_record_id = "{}_{}__gene{}".format( contig_name, chunk_start, gene_id ) prot_out_handle.write(">{}\n".format(new_record_id)) prot_out_handle.write("{}\n".format(str(record.seq)))
python
def rename_proteins(prot_in, prot_out=None, chunk_size=DEFAULT_CHUNK_SIZE): """Rename prodigal output files Rename output files from prodigal according to the following naming scheme: >contigX_chunkY__geneZ Chunk numbering starts at 0 and gene identification is taken from prodigal. Parameters ---------- prot_in : file, str or pathlib.Path The input protein file in FASTA format to be renamed. prot_out : file, str or pathlib.Path The output protein file to be renamed into. chunk_size : int, optional The size of the chunks (in bp) used in the pipeline. Default is 1000. """ if prot_out is None: prot_out = "{}_renamed.fa".format(prot_in.split(".")[0]) with open(prot_out, "w") as prot_out_handle: for record in SeqIO.parse(prot_in, "fasta"): header = record.description name, pos_start, _, _, _ = header.split("#") chunk_start = int(pos_start) // chunk_size name_split = name.split("_") contig_name = "_".join(name_split[:-1]) gene_id = name_split[-1] new_record_id = "{}_{}__gene{}".format( contig_name, chunk_start, gene_id ) prot_out_handle.write(">{}\n".format(new_record_id)) prot_out_handle.write("{}\n".format(str(record.seq)))
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astropy/photutils
photutils/psf/photometry.py
IterativelySubtractedPSFPhotometry._do_photometry
def _do_photometry(self, param_tab, n_start=1): """ Helper function which performs the iterations of the photometry process. Parameters ---------- param_names : list Names of the columns which represent the initial guesses. For example, ['x_0', 'y_0', 'flux_0'], for intial guesses on the center positions and the flux. n_start : int Integer representing the start index of the iteration. It is 1 if init_guesses are None, and 2 otherwise. Returns ------- output_table : `~astropy.table.Table` or None Table with the photometry results, i.e., centroids and fluxes estimations and the initial estimates used to start the fitting process. """ output_table = Table() self._define_fit_param_names() for (init_parname, fit_parname) in zip(self._pars_to_set.keys(), self._pars_to_output.keys()): output_table.add_column(Column(name=init_parname)) output_table.add_column(Column(name=fit_parname)) sources = self.finder(self._residual_image) n = n_start while(sources is not None and (self.niters is None or n <= self.niters)): apertures = CircularAperture((sources['xcentroid'], sources['ycentroid']), r=self.aperture_radius) sources['aperture_flux'] = aperture_photometry( self._residual_image, apertures)['aperture_sum'] init_guess_tab = Table(names=['id', 'x_0', 'y_0', 'flux_0'], data=[sources['id'], sources['xcentroid'], sources['ycentroid'], sources['aperture_flux']]) for param_tab_name, param_name in self._pars_to_set.items(): if param_tab_name not in (['x_0', 'y_0', 'flux_0']): init_guess_tab.add_column( Column(name=param_tab_name, data=(getattr(self.psf_model, param_name) * np.ones(len(sources))))) star_groups = self.group_maker(init_guess_tab) table, self._residual_image = super().nstar( self._residual_image, star_groups) star_groups = star_groups.group_by('group_id') table = hstack([star_groups, table]) table['iter_detected'] = n*np.ones(table['x_fit'].shape, dtype=np.int32) output_table = vstack([output_table, table]) # do not warn if no sources are found beyond the first iteration with warnings.catch_warnings(): warnings.simplefilter('ignore', NoDetectionsWarning) sources = self.finder(self._residual_image) n += 1 return output_table
python
def _do_photometry(self, param_tab, n_start=1): """ Helper function which performs the iterations of the photometry process. Parameters ---------- param_names : list Names of the columns which represent the initial guesses. For example, ['x_0', 'y_0', 'flux_0'], for intial guesses on the center positions and the flux. n_start : int Integer representing the start index of the iteration. It is 1 if init_guesses are None, and 2 otherwise. Returns ------- output_table : `~astropy.table.Table` or None Table with the photometry results, i.e., centroids and fluxes estimations and the initial estimates used to start the fitting process. """ output_table = Table() self._define_fit_param_names() for (init_parname, fit_parname) in zip(self._pars_to_set.keys(), self._pars_to_output.keys()): output_table.add_column(Column(name=init_parname)) output_table.add_column(Column(name=fit_parname)) sources = self.finder(self._residual_image) n = n_start while(sources is not None and (self.niters is None or n <= self.niters)): apertures = CircularAperture((sources['xcentroid'], sources['ycentroid']), r=self.aperture_radius) sources['aperture_flux'] = aperture_photometry( self._residual_image, apertures)['aperture_sum'] init_guess_tab = Table(names=['id', 'x_0', 'y_0', 'flux_0'], data=[sources['id'], sources['xcentroid'], sources['ycentroid'], sources['aperture_flux']]) for param_tab_name, param_name in self._pars_to_set.items(): if param_tab_name not in (['x_0', 'y_0', 'flux_0']): init_guess_tab.add_column( Column(name=param_tab_name, data=(getattr(self.psf_model, param_name) * np.ones(len(sources))))) star_groups = self.group_maker(init_guess_tab) table, self._residual_image = super().nstar( self._residual_image, star_groups) star_groups = star_groups.group_by('group_id') table = hstack([star_groups, table]) table['iter_detected'] = n*np.ones(table['x_fit'].shape, dtype=np.int32) output_table = vstack([output_table, table]) # do not warn if no sources are found beyond the first iteration with warnings.catch_warnings(): warnings.simplefilter('ignore', NoDetectionsWarning) sources = self.finder(self._residual_image) n += 1 return output_table
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secdev/scapy
scapy/layers/l2.py
is_promisc
def is_promisc(ip, fake_bcast="ff:ff:00:00:00:00", **kargs): """Try to guess if target is in Promisc mode. The target is provided by its ip.""" # noqa: E501 responses = srp1(Ether(dst=fake_bcast) / ARP(op="who-has", pdst=ip), type=ETH_P_ARP, iface_hint=ip, timeout=1, verbose=0, **kargs) # noqa: E501 return responses is not None
python
def is_promisc(ip, fake_bcast="ff:ff:00:00:00:00", **kargs): """Try to guess if target is in Promisc mode. The target is provided by its ip.""" # noqa: E501 responses = srp1(Ether(dst=fake_bcast) / ARP(op="who-has", pdst=ip), type=ETH_P_ARP, iface_hint=ip, timeout=1, verbose=0, **kargs) # noqa: E501 return responses is not None
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2,761
Chilipp/psyplot
psyplot/data.py
CFDecoder._check_triangular_bounds
def _check_triangular_bounds(self, var, coords=None, axis='x', nans=None): """ Checks whether the bounds in the variable attribute are triangular Parameters ---------- %(CFDecoder.get_cell_node_coord.parameters)s Returns ------- bool or None True, if unstructered, None if it could not be determined xarray.Coordinate or None the bounds corrdinate (if existent)""" # !!! WILL BE REMOVED IN THE NEAR FUTURE! !!! bounds = self.get_cell_node_coord(var, coords, axis=axis, nans=nans) if bounds is not None: return bounds.shape[-1] == 3, bounds else: return None, None
python
def _check_triangular_bounds(self, var, coords=None, axis='x', nans=None): """ Checks whether the bounds in the variable attribute are triangular Parameters ---------- %(CFDecoder.get_cell_node_coord.parameters)s Returns ------- bool or None True, if unstructered, None if it could not be determined xarray.Coordinate or None the bounds corrdinate (if existent)""" # !!! WILL BE REMOVED IN THE NEAR FUTURE! !!! bounds = self.get_cell_node_coord(var, coords, axis=axis, nans=nans) if bounds is not None: return bounds.shape[-1] == 3, bounds else: return None, None
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src/anyconfig/backend/xml.py
_process_elem_attrs
def _process_elem_attrs(elem, dic, subdic, container=dict, attrs="@attrs", **options): """ :param elem: ET Element object or None :param dic: <container> (dict[-like]) object converted from elem :param subdic: Sub <container> object converted from elem :param options: Keyword options, see the description of :func:`elem_to_container` for more details. :return: None but updating dic and subdic as side effects """ adic = _parse_attrs(elem, container=container, **options) if not elem.text and not len(elem) and options.get("merge_attrs"): dic[elem.tag] = adic else: subdic[attrs] = adic
python
def _process_elem_attrs(elem, dic, subdic, container=dict, attrs="@attrs", **options): """ :param elem: ET Element object or None :param dic: <container> (dict[-like]) object converted from elem :param subdic: Sub <container> object converted from elem :param options: Keyword options, see the description of :func:`elem_to_container` for more details. :return: None but updating dic and subdic as side effects """ adic = _parse_attrs(elem, container=container, **options) if not elem.text and not len(elem) and options.get("merge_attrs"): dic[elem.tag] = adic else: subdic[attrs] = adic
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invenio_files_rest/serializer.py
PartSchema.wrap
def wrap(self, data, many): """Wrap response in envelope.""" if not many: return data else: data = {'parts': data} multipart = self.context.get('multipart') if multipart: data.update(MultipartObjectSchema(context={ 'bucket': multipart.bucket}).dump(multipart).data) return data
python
def wrap(self, data, many): """Wrap response in envelope.""" if not many: return data else: data = {'parts': data} multipart = self.context.get('multipart') if multipart: data.update(MultipartObjectSchema(context={ 'bucket': multipart.bucket}).dump(multipart).data) return data
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dpkp/kafka-python
kafka/client_async.py
KafkaClient._maybe_connect
def _maybe_connect(self, node_id): """Idempotent non-blocking connection attempt to the given node id.""" with self._lock: conn = self._conns.get(node_id) if conn is None: broker = self.cluster.broker_metadata(node_id) assert broker, 'Broker id %s not in current metadata' % (node_id,) log.debug("Initiating connection to node %s at %s:%s", node_id, broker.host, broker.port) host, port, afi = get_ip_port_afi(broker.host) cb = WeakMethod(self._conn_state_change) conn = BrokerConnection(host, broker.port, afi, state_change_callback=cb, node_id=node_id, **self.config) self._conns[node_id] = conn # Check if existing connection should be recreated because host/port changed elif self._should_recycle_connection(conn): self._conns.pop(node_id) return False elif conn.connected(): return True conn.connect() return conn.connected()
python
def _maybe_connect(self, node_id): """Idempotent non-blocking connection attempt to the given node id.""" with self._lock: conn = self._conns.get(node_id) if conn is None: broker = self.cluster.broker_metadata(node_id) assert broker, 'Broker id %s not in current metadata' % (node_id,) log.debug("Initiating connection to node %s at %s:%s", node_id, broker.host, broker.port) host, port, afi = get_ip_port_afi(broker.host) cb = WeakMethod(self._conn_state_change) conn = BrokerConnection(host, broker.port, afi, state_change_callback=cb, node_id=node_id, **self.config) self._conns[node_id] = conn # Check if existing connection should be recreated because host/port changed elif self._should_recycle_connection(conn): self._conns.pop(node_id) return False elif conn.connected(): return True conn.connect() return conn.connected()
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nuagenetworks/bambou
bambou/nurest_object.py
NUMetaRESTObject.rest_name
def rest_name(cls): """ Represents a singular REST name """ if cls.__name__ == "NURESTRootObject" or cls.__name__ == "NURESTObject": return "Not Implemented" if cls.__rest_name__ is None: raise NotImplementedError('%s has no defined name. Implement rest_name property first.' % cls) return cls.__rest_name__
python
def rest_name(cls): """ Represents a singular REST name """ if cls.__name__ == "NURESTRootObject" or cls.__name__ == "NURESTObject": return "Not Implemented" if cls.__rest_name__ is None: raise NotImplementedError('%s has no defined name. Implement rest_name property first.' % cls) return cls.__rest_name__
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saltstack/salt
salt/version.py
msi_conformant_version
def msi_conformant_version(): ''' An msi installer uninstalls/replaces a lower "internal version" of itself. "internal version" is ivMAJOR.ivMINOR.ivBUILD with max values 255.255.65535. Using the build nr allows continuous integration of the installer. "Display version" is indipendent and free format: Year.Month.Bugfix as in Salt 2016.11.3. Calculation of the internal version fields: ivMAJOR = 'short year' (2 digits). ivMINOR = 20*(month-1) + Bugfix Combine Month and Bugfix to free ivBUILD for the build number This limits Bugfix < 20. The msi automatically replaces only 19 bugfixes of a month, one must uninstall manually. ivBUILD = git commit count (noc) noc for tags is 0, representing the final word, translates to the highest build number (65535). Examples: git checkout Display version Internal version Remark develop 2016.11.0-742 16.200.742 The develop branch has bugfix 0 2016.11 2016.11.2-78 16.202.78 2016.11 2016.11.9-88 16.209.88 2018.8 2018.3.2-1306 18.42.1306 v2016.11.0 2016.11.0 16.200.65535 Tags have noc 0 v2016.11.2 2016.11.2 16.202.65535 ''' short_year = int(six.text_type(__saltstack_version__.major)[2:]) month = __saltstack_version__.minor bugfix = __saltstack_version__.bugfix if bugfix > 19: bugfix = 19 noc = __saltstack_version__.noc if noc == 0: noc = 65535 return '{}.{}.{}'.format(short_year, 20*(month-1)+bugfix, noc)
python
def msi_conformant_version(): ''' An msi installer uninstalls/replaces a lower "internal version" of itself. "internal version" is ivMAJOR.ivMINOR.ivBUILD with max values 255.255.65535. Using the build nr allows continuous integration of the installer. "Display version" is indipendent and free format: Year.Month.Bugfix as in Salt 2016.11.3. Calculation of the internal version fields: ivMAJOR = 'short year' (2 digits). ivMINOR = 20*(month-1) + Bugfix Combine Month and Bugfix to free ivBUILD for the build number This limits Bugfix < 20. The msi automatically replaces only 19 bugfixes of a month, one must uninstall manually. ivBUILD = git commit count (noc) noc for tags is 0, representing the final word, translates to the highest build number (65535). Examples: git checkout Display version Internal version Remark develop 2016.11.0-742 16.200.742 The develop branch has bugfix 0 2016.11 2016.11.2-78 16.202.78 2016.11 2016.11.9-88 16.209.88 2018.8 2018.3.2-1306 18.42.1306 v2016.11.0 2016.11.0 16.200.65535 Tags have noc 0 v2016.11.2 2016.11.2 16.202.65535 ''' short_year = int(six.text_type(__saltstack_version__.major)[2:]) month = __saltstack_version__.minor bugfix = __saltstack_version__.bugfix if bugfix > 19: bugfix = 19 noc = __saltstack_version__.noc if noc == 0: noc = 65535 return '{}.{}.{}'.format(short_year, 20*(month-1)+bugfix, noc)
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wonambi-python/wonambi
wonambi/ioeeg/abf.py
_read_header
def _read_header(fid): """Based on neo/rawio/axonrawio.py, but I only kept of data with no-gaps and in one segment. """ fid.seek(0, SEEK_SET) fFileSignature = fid.read(4) assert fFileSignature == b'ABF2', 'only format ABF2 is currently supported' header = {} for key, offset, fmt in headerDescriptionV2: fid.seek(0 + offset, SEEK_SET) val = unpack(fmt, fid.read(calcsize(fmt))) if len(val) == 1: header[key] = val[0] else: header[key] = val # sections sections = {} for s, sectionName in enumerate(sectionNames): fid.seek(76 + s * 16) uBlockIndex, uBytes, llNumEntries = unpack('IIl', fid.read(calcsize('IIl'))) sections[sectionName] = {} sections[sectionName]['uBlockIndex'] = uBlockIndex sections[sectionName]['uBytes'] = uBytes sections[sectionName]['llNumEntries'] = llNumEntries header['sections'] = sections # strings sections # hack for reading channels names and units fid.seek(sections['StringsSection']['uBlockIndex'] * BLOCKSIZE) big_string = fid.read(sections['StringsSection']['uBytes']) goodstart = -1 for key in [b'AXENGN', b'clampex', b'Clampex', b'CLAMPEX', b'axoscope', b'Clampfit']: goodstart = big_string.find(key) if goodstart != -1: break assert goodstart != -1, 'This file does not contain clampex, axoscope or clampfit in the header' big_string = big_string[goodstart:] strings = big_string.split(b'\x00') # ADC sections header['listADCInfo'] = [] for i in range(sections['ADCSection']['llNumEntries']): # read ADCInfo fid.seek(sections['ADCSection']['uBlockIndex'] * BLOCKSIZE + sections['ADCSection']['uBytes'] * i) ADCInfo = _read_info_as_dict(fid, ADCInfoDescription) ADCInfo['ADCChNames'] = strings[ADCInfo['lADCChannelNameIndex'] - 1] ADCInfo['ADCChUnits'] = strings[ADCInfo['lADCUnitsIndex'] - 1] header['listADCInfo'].append(ADCInfo) # protocol sections fid.seek(sections['ProtocolSection']['uBlockIndex'] * BLOCKSIZE) header['protocol'] = _read_info_as_dict(fid, protocolInfoDescription) header['sProtocolPath'] = strings[header['uProtocolPathIndex'] - 1] # DAC sections header['listDACInfo'] = [] for i in range(sections['DACSection']['llNumEntries']): # read DACInfo fid.seek(sections['DACSection']['uBlockIndex'] * BLOCKSIZE + sections['DACSection']['uBytes'] * i) DACInfo = _read_info_as_dict(fid, DACInfoDescription) DACInfo['DACChNames'] = strings[DACInfo['lDACChannelNameIndex'] - 1] DACInfo['DACChUnits'] = strings[ DACInfo['lDACChannelUnitsIndex'] - 1] header['listDACInfo'].append(DACInfo) """ Not present in test file. No tests, no code. # tags listTag = [] for i in range(sections['TagSection']['llNumEntries']): fid.seek(sections['TagSection']['uBlockIndex'] * BLOCKSIZE + sections['TagSection']['uBytes'] * i) tag = _read_info_as_dict(fid, TagInfoDescription) listTag.append(tag) header['listTag'] = listTag # EpochPerDAC sections # header['dictEpochInfoPerDAC'] is dict of dicts: # - the first index is the DAC number # - the second index is the epoch number # It has to be done like that because data may not exist # and may not be in sorted order header['dictEpochInfoPerDAC'] = {} for i in range(sections['EpochPerDACSection']['llNumEntries']): # read DACInfo fid.seek(sections['EpochPerDACSection']['uBlockIndex'] * BLOCKSIZE + sections['EpochPerDACSection']['uBytes'] * i) EpochInfoPerDAC = _read_info_as_dict(fid, EpochInfoPerDACDescription) DACNum = EpochInfoPerDAC['nDACNum'] EpochNum = EpochInfoPerDAC['nEpochNum'] # Checking if the key exists, if not, the value is empty # so we have to create empty dict to populate if DACNum not in header['dictEpochInfoPerDAC']: header['dictEpochInfoPerDAC'][DACNum] = {} header['dictEpochInfoPerDAC'][DACNum][EpochNum] =\ EpochInfoPerDAC """ return header
python
def _read_header(fid): """Based on neo/rawio/axonrawio.py, but I only kept of data with no-gaps and in one segment. """ fid.seek(0, SEEK_SET) fFileSignature = fid.read(4) assert fFileSignature == b'ABF2', 'only format ABF2 is currently supported' header = {} for key, offset, fmt in headerDescriptionV2: fid.seek(0 + offset, SEEK_SET) val = unpack(fmt, fid.read(calcsize(fmt))) if len(val) == 1: header[key] = val[0] else: header[key] = val # sections sections = {} for s, sectionName in enumerate(sectionNames): fid.seek(76 + s * 16) uBlockIndex, uBytes, llNumEntries = unpack('IIl', fid.read(calcsize('IIl'))) sections[sectionName] = {} sections[sectionName]['uBlockIndex'] = uBlockIndex sections[sectionName]['uBytes'] = uBytes sections[sectionName]['llNumEntries'] = llNumEntries header['sections'] = sections # strings sections # hack for reading channels names and units fid.seek(sections['StringsSection']['uBlockIndex'] * BLOCKSIZE) big_string = fid.read(sections['StringsSection']['uBytes']) goodstart = -1 for key in [b'AXENGN', b'clampex', b'Clampex', b'CLAMPEX', b'axoscope', b'Clampfit']: goodstart = big_string.find(key) if goodstart != -1: break assert goodstart != -1, 'This file does not contain clampex, axoscope or clampfit in the header' big_string = big_string[goodstart:] strings = big_string.split(b'\x00') # ADC sections header['listADCInfo'] = [] for i in range(sections['ADCSection']['llNumEntries']): # read ADCInfo fid.seek(sections['ADCSection']['uBlockIndex'] * BLOCKSIZE + sections['ADCSection']['uBytes'] * i) ADCInfo = _read_info_as_dict(fid, ADCInfoDescription) ADCInfo['ADCChNames'] = strings[ADCInfo['lADCChannelNameIndex'] - 1] ADCInfo['ADCChUnits'] = strings[ADCInfo['lADCUnitsIndex'] - 1] header['listADCInfo'].append(ADCInfo) # protocol sections fid.seek(sections['ProtocolSection']['uBlockIndex'] * BLOCKSIZE) header['protocol'] = _read_info_as_dict(fid, protocolInfoDescription) header['sProtocolPath'] = strings[header['uProtocolPathIndex'] - 1] # DAC sections header['listDACInfo'] = [] for i in range(sections['DACSection']['llNumEntries']): # read DACInfo fid.seek(sections['DACSection']['uBlockIndex'] * BLOCKSIZE + sections['DACSection']['uBytes'] * i) DACInfo = _read_info_as_dict(fid, DACInfoDescription) DACInfo['DACChNames'] = strings[DACInfo['lDACChannelNameIndex'] - 1] DACInfo['DACChUnits'] = strings[ DACInfo['lDACChannelUnitsIndex'] - 1] header['listDACInfo'].append(DACInfo) """ Not present in test file. No tests, no code. # tags listTag = [] for i in range(sections['TagSection']['llNumEntries']): fid.seek(sections['TagSection']['uBlockIndex'] * BLOCKSIZE + sections['TagSection']['uBytes'] * i) tag = _read_info_as_dict(fid, TagInfoDescription) listTag.append(tag) header['listTag'] = listTag # EpochPerDAC sections # header['dictEpochInfoPerDAC'] is dict of dicts: # - the first index is the DAC number # - the second index is the epoch number # It has to be done like that because data may not exist # and may not be in sorted order header['dictEpochInfoPerDAC'] = {} for i in range(sections['EpochPerDACSection']['llNumEntries']): # read DACInfo fid.seek(sections['EpochPerDACSection']['uBlockIndex'] * BLOCKSIZE + sections['EpochPerDACSection']['uBytes'] * i) EpochInfoPerDAC = _read_info_as_dict(fid, EpochInfoPerDACDescription) DACNum = EpochInfoPerDAC['nDACNum'] EpochNum = EpochInfoPerDAC['nEpochNum'] # Checking if the key exists, if not, the value is empty # so we have to create empty dict to populate if DACNum not in header['dictEpochInfoPerDAC']: header['dictEpochInfoPerDAC'][DACNum] = {} header['dictEpochInfoPerDAC'][DACNum][EpochNum] =\ EpochInfoPerDAC """ return header
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Based on neo/rawio/axonrawio.py, but I only kept of data with no-gaps and in one segment.
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mthornhill/django-postal
src/postal/resource.py
Emitter.get
def get(cls, format): """ Gets an emitter, returns the class and a content-type. """ if cls.EMITTERS.has_key(format): return cls.EMITTERS.get(format) raise ValueError("No emitters found for type %s" % format)
python
def get(cls, format): """ Gets an emitter, returns the class and a content-type. """ if cls.EMITTERS.has_key(format): return cls.EMITTERS.get(format) raise ValueError("No emitters found for type %s" % format)
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roycehaynes/scrapy-rabbitmq
scrapy_rabbitmq/queue.py
SpiderQueue.pop
def pop(self): """Pop a request""" method_frame, header, body = self.server.basic_get(queue=self.key) if body: return self._decode_request(body)
python
def pop(self): """Pop a request""" method_frame, header, body = self.server.basic_get(queue=self.key) if body: return self._decode_request(body)
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LudovicRousseau/pyscard
smartcard/ExclusiveTransmitCardConnection.py
ExclusiveTransmitCardConnection.transmit
def transmit(self, bytes, protocol=None): '''Gain exclusive access to card during APDU transmission for if this decorator decorates a PCSCCardConnection.''' data, sw1, sw2 = CardConnectionDecorator.transmit( self, bytes, protocol) return data, sw1, sw2
python
def transmit(self, bytes, protocol=None): '''Gain exclusive access to card during APDU transmission for if this decorator decorates a PCSCCardConnection.''' data, sw1, sw2 = CardConnectionDecorator.transmit( self, bytes, protocol) return data, sw1, sw2
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dnanexus/dx-toolkit
src/python/dxpy/api.py
system_find_global_workflows
def system_find_global_workflows(input_params={}, always_retry=True, **kwargs): """ Invokes the /system/findGlobalWorkflows API method. """ return DXHTTPRequest('/system/findGlobalWorkflows', input_params, always_retry=always_retry, **kwargs)
python
def system_find_global_workflows(input_params={}, always_retry=True, **kwargs): """ Invokes the /system/findGlobalWorkflows API method. """ return DXHTTPRequest('/system/findGlobalWorkflows', input_params, always_retry=always_retry, **kwargs)
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JukeboxPipeline/jukeboxmaya
src/jukeboxmaya/reftrack/asset.py
AssetReftypeInterface.delete
def delete(self, refobj): """Delete the content of the given refobj :param refobj: the refobj that represents the content that should be deleted :type refobj: refobj :returns: None :rtype: None :raises: None """ refobjinter = self.get_refobjinter() reference = refobjinter.get_reference(refobj) if reference: fullns = cmds.referenceQuery(reference, namespace=True) cmds.file(removeReference=True, referenceNode=reference) else: parentns = common.get_namespace(refobj) ns = cmds.getAttr("%s.namespace" % refobj) fullns = ":".join((parentns.rstrip(":"), ns.lstrip(":"))) cmds.namespace(removeNamespace=fullns, deleteNamespaceContent=True)
python
def delete(self, refobj): """Delete the content of the given refobj :param refobj: the refobj that represents the content that should be deleted :type refobj: refobj :returns: None :rtype: None :raises: None """ refobjinter = self.get_refobjinter() reference = refobjinter.get_reference(refobj) if reference: fullns = cmds.referenceQuery(reference, namespace=True) cmds.file(removeReference=True, referenceNode=reference) else: parentns = common.get_namespace(refobj) ns = cmds.getAttr("%s.namespace" % refobj) fullns = ":".join((parentns.rstrip(":"), ns.lstrip(":"))) cmds.namespace(removeNamespace=fullns, deleteNamespaceContent=True)
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pywbem/pywbem
pywbem/_recorder.py
LogOperationRecorder.stage_wbem_connection
def stage_wbem_connection(self, wbem_connection): """ Log connection information. This includes the connection id (conn_id) that is output with the log entry. This entry is logged if either http or api loggers are enable. It honors both the logger and detail level of either api logger if defined or http logger if defined. If the api logger does not exist, the output shows this as an http loggger output since we do not want to create an api logger for this specific output """ self._conn_id = wbem_connection.conn_id if self.enabled: if self.api_detail_level is not None: logger = self.apilogger detail_level = self.api_detail_level max_len = self.api_maxlen elif self.http_detail_level is not None: logger = self.httplogger detail_level = self.http_detail_level max_len = self.http_maxlen else: return if logger.isEnabledFor(logging.DEBUG): conn_data = str(wbem_connection) if detail_level == 'summary' \ else repr(wbem_connection) if max_len and (len(conn_data) > max_len): conn_data = conn_data[:max_len] + '...' logger.debug('Connection:%s %s', self._conn_id, conn_data)
python
def stage_wbem_connection(self, wbem_connection): """ Log connection information. This includes the connection id (conn_id) that is output with the log entry. This entry is logged if either http or api loggers are enable. It honors both the logger and detail level of either api logger if defined or http logger if defined. If the api logger does not exist, the output shows this as an http loggger output since we do not want to create an api logger for this specific output """ self._conn_id = wbem_connection.conn_id if self.enabled: if self.api_detail_level is not None: logger = self.apilogger detail_level = self.api_detail_level max_len = self.api_maxlen elif self.http_detail_level is not None: logger = self.httplogger detail_level = self.http_detail_level max_len = self.http_maxlen else: return if logger.isEnabledFor(logging.DEBUG): conn_data = str(wbem_connection) if detail_level == 'summary' \ else repr(wbem_connection) if max_len and (len(conn_data) > max_len): conn_data = conn_data[:max_len] + '...' logger.debug('Connection:%s %s', self._conn_id, conn_data)
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ihmeuw/vivarium
src/vivarium/framework/randomness.py
RandomnessManager.get_randomness_stream
def get_randomness_stream(self, decision_point: str, for_initialization: bool=False) -> RandomnessStream: """Provides a new source of random numbers for the given decision point. Parameters ---------- decision_point : A unique identifier for a stream of random numbers. Typically represents a decision that needs to be made each time step like 'moves_left' or 'gets_disease'. for_initialization : A flag indicating whether this stream is used to generate key initialization information that will be used to identify simulants in the Common Random Number framework. These streams cannot be copied and should only be used to generate the state table columns specified in ``builder.configuration.randomness.key_columns``. Raises ------ RandomnessError : If another location in the simulation has already created a randomness stream with the same identifier. """ if decision_point in self._decision_points: raise RandomnessError(f"Two separate places are attempting to create " f"the same randomness stream for {decision_point}") stream = RandomnessStream(key=decision_point, clock=self._clock, seed=self._seed, index_map=self._key_mapping, manager=self, for_initialization=for_initialization) self._decision_points[decision_point] = stream return stream
python
def get_randomness_stream(self, decision_point: str, for_initialization: bool=False) -> RandomnessStream: """Provides a new source of random numbers for the given decision point. Parameters ---------- decision_point : A unique identifier for a stream of random numbers. Typically represents a decision that needs to be made each time step like 'moves_left' or 'gets_disease'. for_initialization : A flag indicating whether this stream is used to generate key initialization information that will be used to identify simulants in the Common Random Number framework. These streams cannot be copied and should only be used to generate the state table columns specified in ``builder.configuration.randomness.key_columns``. Raises ------ RandomnessError : If another location in the simulation has already created a randomness stream with the same identifier. """ if decision_point in self._decision_points: raise RandomnessError(f"Two separate places are attempting to create " f"the same randomness stream for {decision_point}") stream = RandomnessStream(key=decision_point, clock=self._clock, seed=self._seed, index_map=self._key_mapping, manager=self, for_initialization=for_initialization) self._decision_points[decision_point] = stream return stream
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ugali/utils/projector.py
dms2dec
def dms2dec(dms): """ Convert latitude from degrees,minutes,seconds in string or 3-array format to decimal degrees. """ DEGREE = 360. HOUR = 24. MINUTE = 60. SECOND = 3600. # Be careful here, degree needs to be a float so that negative zero # can have its signbit set: # http://docs.scipy.org/doc/numpy-1.7.0/reference/c-api.coremath.html#NPY_NZERO if isstring(dms): degree,minute,second = np.array(re.split('[dms]',hms))[:3].astype(float) else: degree,minute,second = dms.T sign = np.copysign(1.0,degree) decimal = np.abs(degree) + minute * 1./MINUTE + second * 1./SECOND decimal *= sign return decimal
python
def dms2dec(dms): """ Convert latitude from degrees,minutes,seconds in string or 3-array format to decimal degrees. """ DEGREE = 360. HOUR = 24. MINUTE = 60. SECOND = 3600. # Be careful here, degree needs to be a float so that negative zero # can have its signbit set: # http://docs.scipy.org/doc/numpy-1.7.0/reference/c-api.coremath.html#NPY_NZERO if isstring(dms): degree,minute,second = np.array(re.split('[dms]',hms))[:3].astype(float) else: degree,minute,second = dms.T sign = np.copysign(1.0,degree) decimal = np.abs(degree) + minute * 1./MINUTE + second * 1./SECOND decimal *= sign return decimal
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wave/serializers.py
ModelSerializer.get_default_field_names
def get_default_field_names(self, declared_fields, model_info): """ Return the default list of field names that will be used if the `Meta.fields` option is not specified. """ return ( [model_info.pk.name] + list(declared_fields.keys()) + list(model_info.fields.keys()) + list(model_info.forward_relations.keys()) )
python
def get_default_field_names(self, declared_fields, model_info): """ Return the default list of field names that will be used if the `Meta.fields` option is not specified. """ return ( [model_info.pk.name] + list(declared_fields.keys()) + list(model_info.fields.keys()) + list(model_info.forward_relations.keys()) )
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lib/stsci/tools/fitsdiff.py
list_parse
def list_parse(name_list): """Parse a comma-separated list of values, or a filename (starting with @) containing a list value on each line. """ if name_list and name_list[0] == '@': value = name_list[1:] if not os.path.exists(value): log.warning('The file %s does not exist' % value) return try: return [v.strip() for v in open(value, 'r').readlines()] except IOError as e: log.warning('reading %s failed: %s; ignoring this file' % (value, e)) else: return [v.strip() for v in name_list.split(',')]
python
def list_parse(name_list): """Parse a comma-separated list of values, or a filename (starting with @) containing a list value on each line. """ if name_list and name_list[0] == '@': value = name_list[1:] if not os.path.exists(value): log.warning('The file %s does not exist' % value) return try: return [v.strip() for v in open(value, 'r').readlines()] except IOError as e: log.warning('reading %s failed: %s; ignoring this file' % (value, e)) else: return [v.strip() for v in name_list.split(',')]
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convert_path
def convert_path(pathname): """Return 'pathname' as a name that will work on the native filesystem. The path is split on '/' and put back together again using the current directory separator. Needed because filenames in the setup script are always supplied in Unix style, and have to be converted to the local convention before we can actually use them in the filesystem. Raises ValueError on non-Unix-ish systems if 'pathname' either starts or ends with a slash. """ if os.sep == '/': return pathname if not pathname: return pathname if pathname[0] == '/': raise ValueError("path '%s' cannot be absolute" % pathname) if pathname[-1] == '/': raise ValueError("path '%s' cannot end with '/'" % pathname) paths = pathname.split('/') while os.curdir in paths: paths.remove(os.curdir) if not paths: return os.curdir return os.path.join(*paths)
python
def convert_path(pathname): """Return 'pathname' as a name that will work on the native filesystem. The path is split on '/' and put back together again using the current directory separator. Needed because filenames in the setup script are always supplied in Unix style, and have to be converted to the local convention before we can actually use them in the filesystem. Raises ValueError on non-Unix-ish systems if 'pathname' either starts or ends with a slash. """ if os.sep == '/': return pathname if not pathname: return pathname if pathname[0] == '/': raise ValueError("path '%s' cannot be absolute" % pathname) if pathname[-1] == '/': raise ValueError("path '%s' cannot end with '/'" % pathname) paths = pathname.split('/') while os.curdir in paths: paths.remove(os.curdir) if not paths: return os.curdir return os.path.join(*paths)
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DLR-RM/RAFCON
source/rafcon/core/states/container_state.py
ContainerState._check_data_flow_ports
def _check_data_flow_ports(self, data_flow): """Checks the validity of the ports of a data flow Checks whether the ports of a data flow are existing and whether it is allowed to connect these ports. :param rafcon.core.data_flow.DataFlow data_flow: The data flow to be checked :return bool validity, str message: validity is True, when the data flow is valid, False else. message gives more information especially if the data flow is not valid """ from_state_id = data_flow.from_state to_state_id = data_flow.to_state from_data_port_id = data_flow.from_key to_data_port_id = data_flow.to_key # Check whether to and from port are existing from_data_port = self.get_data_port(from_state_id, from_data_port_id) if not from_data_port: return False, "Data flow origin not existing -> {0}".format(data_flow) to_data_port = self.get_data_port(to_state_id, to_data_port_id) if not to_data_port: return False, "Data flow target not existing -> {0}".format(data_flow) # Data_ports without parents are not allowed to be connected twice if not from_data_port.parent: return False, "Source data port does not have a parent -> {0}".format(data_flow) if not to_data_port.parent: return False, "Target data port does not have a parent -> {0}".format(data_flow) # Check if data ports are identical if from_data_port is to_data_port: return False, "Source and target data ports of data flow must not be identical -> {}".format(data_flow) # Check, whether the origin of the data flow is valid if from_state_id == self.state_id: # data_flow originates in container state if from_data_port_id not in self.input_data_ports and from_data_port_id not in self.scoped_variables: return False, "Data flow origin port must be an input port or scoped variable, when the data flow " \ "starts in the parent state -> {0}".format(data_flow) else: # data flow originates in child state if from_data_port_id not in from_data_port.parent.output_data_ports: return False, "Data flow origin port must be an output port, when the data flow " \ "starts in the child state -> {0}".format(data_flow) # Check, whether the target of a data flow is valid if to_state_id == self.state_id: # data_flow ends in container state if to_data_port_id not in self.output_data_ports and to_data_port_id not in self.scoped_variables: return False, "Data flow target port must be an output port or scoped variable, when the data flow " \ "goes to the parent state -> {0}".format(data_flow) else: # data_flow ends in child state if to_data_port_id not in to_data_port.parent.input_data_ports: return False, "Data flow target port must be an input port, when the data flow goes to a child state" \ " -> {0}".format(data_flow) # Check if data flow connects two scoped variables if isinstance(from_data_port, ScopedVariable) and isinstance(to_data_port, ScopedVariable): return False, "Data flows must not connect two scoped variables -> {}".format(data_flow) # Check, whether the target port is already connected for existing_data_flow in self.data_flows.values(): to_data_port_existing = self.get_data_port(existing_data_flow.to_state, existing_data_flow.to_key) from_data_port_existing = self.get_data_port(existing_data_flow.from_state, existing_data_flow.from_key) if to_data_port is to_data_port_existing and data_flow is not existing_data_flow: if from_data_port is from_data_port_existing: return False, "Exactly the same data flow is already existing -> {0}".format(data_flow) return True, "valid"
python
def _check_data_flow_ports(self, data_flow): """Checks the validity of the ports of a data flow Checks whether the ports of a data flow are existing and whether it is allowed to connect these ports. :param rafcon.core.data_flow.DataFlow data_flow: The data flow to be checked :return bool validity, str message: validity is True, when the data flow is valid, False else. message gives more information especially if the data flow is not valid """ from_state_id = data_flow.from_state to_state_id = data_flow.to_state from_data_port_id = data_flow.from_key to_data_port_id = data_flow.to_key # Check whether to and from port are existing from_data_port = self.get_data_port(from_state_id, from_data_port_id) if not from_data_port: return False, "Data flow origin not existing -> {0}".format(data_flow) to_data_port = self.get_data_port(to_state_id, to_data_port_id) if not to_data_port: return False, "Data flow target not existing -> {0}".format(data_flow) # Data_ports without parents are not allowed to be connected twice if not from_data_port.parent: return False, "Source data port does not have a parent -> {0}".format(data_flow) if not to_data_port.parent: return False, "Target data port does not have a parent -> {0}".format(data_flow) # Check if data ports are identical if from_data_port is to_data_port: return False, "Source and target data ports of data flow must not be identical -> {}".format(data_flow) # Check, whether the origin of the data flow is valid if from_state_id == self.state_id: # data_flow originates in container state if from_data_port_id not in self.input_data_ports and from_data_port_id not in self.scoped_variables: return False, "Data flow origin port must be an input port or scoped variable, when the data flow " \ "starts in the parent state -> {0}".format(data_flow) else: # data flow originates in child state if from_data_port_id not in from_data_port.parent.output_data_ports: return False, "Data flow origin port must be an output port, when the data flow " \ "starts in the child state -> {0}".format(data_flow) # Check, whether the target of a data flow is valid if to_state_id == self.state_id: # data_flow ends in container state if to_data_port_id not in self.output_data_ports and to_data_port_id not in self.scoped_variables: return False, "Data flow target port must be an output port or scoped variable, when the data flow " \ "goes to the parent state -> {0}".format(data_flow) else: # data_flow ends in child state if to_data_port_id not in to_data_port.parent.input_data_ports: return False, "Data flow target port must be an input port, when the data flow goes to a child state" \ " -> {0}".format(data_flow) # Check if data flow connects two scoped variables if isinstance(from_data_port, ScopedVariable) and isinstance(to_data_port, ScopedVariable): return False, "Data flows must not connect two scoped variables -> {}".format(data_flow) # Check, whether the target port is already connected for existing_data_flow in self.data_flows.values(): to_data_port_existing = self.get_data_port(existing_data_flow.to_state, existing_data_flow.to_key) from_data_port_existing = self.get_data_port(existing_data_flow.from_state, existing_data_flow.from_key) if to_data_port is to_data_port_existing and data_flow is not existing_data_flow: if from_data_port is from_data_port_existing: return False, "Exactly the same data flow is already existing -> {0}".format(data_flow) return True, "valid"
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tensorflow/tensor2tensor
tensor2tensor/models/image_transformer.py
imagetransformer_base_8l_8h_big_cond_dr03_dan
def imagetransformer_base_8l_8h_big_cond_dr03_dan(): """big 1d model for conditional image generation.2.99 on cifar10.""" hparams = imagetransformer_sep_channels_8l() hparams.block_width = 256 hparams.block_length = 256 hparams.hidden_size = 512 hparams.num_heads = 8 hparams.filter_size = 2048 hparams.batch_size = 4 hparams.max_length = 3075 hparams.layer_preprocess_sequence = "none" hparams.layer_postprocess_sequence = "dan" hparams.num_decoder_layers = 8 hparams.layer_prepostprocess_dropout = 0.3 return hparams
python
def imagetransformer_base_8l_8h_big_cond_dr03_dan(): """big 1d model for conditional image generation.2.99 on cifar10.""" hparams = imagetransformer_sep_channels_8l() hparams.block_width = 256 hparams.block_length = 256 hparams.hidden_size = 512 hparams.num_heads = 8 hparams.filter_size = 2048 hparams.batch_size = 4 hparams.max_length = 3075 hparams.layer_preprocess_sequence = "none" hparams.layer_postprocess_sequence = "dan" hparams.num_decoder_layers = 8 hparams.layer_prepostprocess_dropout = 0.3 return hparams
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deepmind/sonnet
sonnet/python/custom_getters/override_args.py
override_args
def override_args(**kwargs): """Creates a custom getter that applies specified named arguments. Args: **kwargs: Overriding arguments for the custom getter to use in preference the named arguments it's called with. Returns: Custom getter. """ override_kwargs = kwargs def custom_getter(getter, *args, **kwargs): """Custom getter with certain named arguments overridden. Args: getter: Underlying variable getter to invoke. *args: Arguments, compatible with those of tf.get_variable. **kwargs: Keyword arguments, compatible with those of tf.get_variable. Returns: The result of invoking `getter(*args, **kwargs)` except that certain kwargs entries may have been overridden. """ kwargs.update(override_kwargs) return getter(*args, **kwargs) return custom_getter
python
def override_args(**kwargs): """Creates a custom getter that applies specified named arguments. Args: **kwargs: Overriding arguments for the custom getter to use in preference the named arguments it's called with. Returns: Custom getter. """ override_kwargs = kwargs def custom_getter(getter, *args, **kwargs): """Custom getter with certain named arguments overridden. Args: getter: Underlying variable getter to invoke. *args: Arguments, compatible with those of tf.get_variable. **kwargs: Keyword arguments, compatible with those of tf.get_variable. Returns: The result of invoking `getter(*args, **kwargs)` except that certain kwargs entries may have been overridden. """ kwargs.update(override_kwargs) return getter(*args, **kwargs) return custom_getter
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Diaoul/subliminal
subliminal/refiners/omdb.py
refine
def refine(video, **kwargs): """Refine a video by searching `OMDb API <http://omdbapi.com/>`_. Several :class:`~subliminal.video.Episode` attributes can be found: * :attr:`~subliminal.video.Episode.series` * :attr:`~subliminal.video.Episode.year` * :attr:`~subliminal.video.Episode.series_imdb_id` Similarly, for a :class:`~subliminal.video.Movie`: * :attr:`~subliminal.video.Movie.title` * :attr:`~subliminal.video.Movie.year` * :attr:`~subliminal.video.Video.imdb_id` """ if isinstance(video, Episode): # exit if the information is complete if video.series_imdb_id: logger.debug('No need to search') return # search the series results = search(video.series, 'series', video.year) if not results: logger.warning('No results for series') return logger.debug('Found %d results', len(results)) # filter the results results = [r for r in results if sanitize(r['Title']) == sanitize(video.series)] if not results: logger.warning('No matching series found') return # process the results found = False for result in sorted(results, key=operator.itemgetter('Year')): if video.original_series and video.year is None: logger.debug('Found result for original series without year') found = True break if video.year == int(result['Year'].split(u'\u2013')[0]): logger.debug('Found result with matching year') found = True break if not found: logger.warning('No matching series found') return # add series information logger.debug('Found series %r', result) video.series = result['Title'] video.year = int(result['Year'].split(u'\u2013')[0]) video.series_imdb_id = result['imdbID'] elif isinstance(video, Movie): # exit if the information is complete if video.imdb_id: return # search the movie results = search(video.title, 'movie', video.year) if not results: logger.warning('No results') return logger.debug('Found %d results', len(results)) # filter the results results = [r for r in results if sanitize(r['Title']) == sanitize(video.title)] if not results: logger.warning('No matching movie found') return # process the results found = False for result in results: if video.year is None: logger.debug('Found result for movie without year') found = True break if video.year == int(result['Year']): logger.debug('Found result with matching year') found = True break if not found: logger.warning('No matching movie found') return # add movie information logger.debug('Found movie %r', result) video.title = result['Title'] video.year = int(result['Year'].split(u'\u2013')[0]) video.imdb_id = result['imdbID']
python
def refine(video, **kwargs): """Refine a video by searching `OMDb API <http://omdbapi.com/>`_. Several :class:`~subliminal.video.Episode` attributes can be found: * :attr:`~subliminal.video.Episode.series` * :attr:`~subliminal.video.Episode.year` * :attr:`~subliminal.video.Episode.series_imdb_id` Similarly, for a :class:`~subliminal.video.Movie`: * :attr:`~subliminal.video.Movie.title` * :attr:`~subliminal.video.Movie.year` * :attr:`~subliminal.video.Video.imdb_id` """ if isinstance(video, Episode): # exit if the information is complete if video.series_imdb_id: logger.debug('No need to search') return # search the series results = search(video.series, 'series', video.year) if not results: logger.warning('No results for series') return logger.debug('Found %d results', len(results)) # filter the results results = [r for r in results if sanitize(r['Title']) == sanitize(video.series)] if not results: logger.warning('No matching series found') return # process the results found = False for result in sorted(results, key=operator.itemgetter('Year')): if video.original_series and video.year is None: logger.debug('Found result for original series without year') found = True break if video.year == int(result['Year'].split(u'\u2013')[0]): logger.debug('Found result with matching year') found = True break if not found: logger.warning('No matching series found') return # add series information logger.debug('Found series %r', result) video.series = result['Title'] video.year = int(result['Year'].split(u'\u2013')[0]) video.series_imdb_id = result['imdbID'] elif isinstance(video, Movie): # exit if the information is complete if video.imdb_id: return # search the movie results = search(video.title, 'movie', video.year) if not results: logger.warning('No results') return logger.debug('Found %d results', len(results)) # filter the results results = [r for r in results if sanitize(r['Title']) == sanitize(video.title)] if not results: logger.warning('No matching movie found') return # process the results found = False for result in results: if video.year is None: logger.debug('Found result for movie without year') found = True break if video.year == int(result['Year']): logger.debug('Found result with matching year') found = True break if not found: logger.warning('No matching movie found') return # add movie information logger.debug('Found movie %r', result) video.title = result['Title'] video.year = int(result['Year'].split(u'\u2013')[0]) video.imdb_id = result['imdbID']
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GNS3/gns3-server
gns3server/compute/builtin/nodes/cloud.py
Cloud._add_linux_ethernet
def _add_linux_ethernet(self, port_info, bridge_name): """ Use raw sockets on Linux. If interface is a bridge we connect a tap to it """ interface = port_info["interface"] if gns3server.utils.interfaces.is_interface_bridge(interface): network_interfaces = [interface["name"] for interface in self._interfaces()] i = 0 while True: tap = "gns3tap{}-{}".format(i, port_info["port_number"]) if tap not in network_interfaces: break i += 1 yield from self._ubridge_send('bridge add_nio_tap "{name}" "{interface}"'.format(name=bridge_name, interface=tap)) yield from self._ubridge_send('brctl addif "{interface}" "{tap}"'.format(tap=tap, interface=interface)) else: yield from self._ubridge_send('bridge add_nio_linux_raw {name} "{interface}"'.format(name=bridge_name, interface=interface))
python
def _add_linux_ethernet(self, port_info, bridge_name): """ Use raw sockets on Linux. If interface is a bridge we connect a tap to it """ interface = port_info["interface"] if gns3server.utils.interfaces.is_interface_bridge(interface): network_interfaces = [interface["name"] for interface in self._interfaces()] i = 0 while True: tap = "gns3tap{}-{}".format(i, port_info["port_number"]) if tap not in network_interfaces: break i += 1 yield from self._ubridge_send('bridge add_nio_tap "{name}" "{interface}"'.format(name=bridge_name, interface=tap)) yield from self._ubridge_send('brctl addif "{interface}" "{tap}"'.format(tap=tap, interface=interface)) else: yield from self._ubridge_send('bridge add_nio_linux_raw {name} "{interface}"'.format(name=bridge_name, interface=interface))
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pydata/xarray
xarray/core/variable.py
Variable._getitem_with_mask
def _getitem_with_mask(self, key, fill_value=dtypes.NA): """Index this Variable with -1 remapped to fill_value.""" # TODO(shoyer): expose this method in public API somewhere (isel?) and # use it for reindex. # TODO(shoyer): add a sanity check that all other integers are # non-negative # TODO(shoyer): add an optimization, remapping -1 to an adjacent value # that is actually indexed rather than mapping it to the last value # along each axis. if fill_value is dtypes.NA: fill_value = dtypes.get_fill_value(self.dtype) dims, indexer, new_order = self._broadcast_indexes(key) if self.size: if isinstance(self._data, dask_array_type): # dask's indexing is faster this way; also vindex does not # support negative indices yet: # https://github.com/dask/dask/pull/2967 actual_indexer = indexing.posify_mask_indexer(indexer) else: actual_indexer = indexer data = as_indexable(self._data)[actual_indexer] chunks_hint = getattr(data, 'chunks', None) mask = indexing.create_mask(indexer, self.shape, chunks_hint) data = duck_array_ops.where(mask, fill_value, data) else: # array cannot be indexed along dimensions of size 0, so just # build the mask directly instead. mask = indexing.create_mask(indexer, self.shape) data = np.broadcast_to(fill_value, getattr(mask, 'shape', ())) if new_order: data = np.moveaxis(data, range(len(new_order)), new_order) return self._finalize_indexing_result(dims, data)
python
def _getitem_with_mask(self, key, fill_value=dtypes.NA): """Index this Variable with -1 remapped to fill_value.""" # TODO(shoyer): expose this method in public API somewhere (isel?) and # use it for reindex. # TODO(shoyer): add a sanity check that all other integers are # non-negative # TODO(shoyer): add an optimization, remapping -1 to an adjacent value # that is actually indexed rather than mapping it to the last value # along each axis. if fill_value is dtypes.NA: fill_value = dtypes.get_fill_value(self.dtype) dims, indexer, new_order = self._broadcast_indexes(key) if self.size: if isinstance(self._data, dask_array_type): # dask's indexing is faster this way; also vindex does not # support negative indices yet: # https://github.com/dask/dask/pull/2967 actual_indexer = indexing.posify_mask_indexer(indexer) else: actual_indexer = indexer data = as_indexable(self._data)[actual_indexer] chunks_hint = getattr(data, 'chunks', None) mask = indexing.create_mask(indexer, self.shape, chunks_hint) data = duck_array_ops.where(mask, fill_value, data) else: # array cannot be indexed along dimensions of size 0, so just # build the mask directly instead. mask = indexing.create_mask(indexer, self.shape) data = np.broadcast_to(fill_value, getattr(mask, 'shape', ())) if new_order: data = np.moveaxis(data, range(len(new_order)), new_order) return self._finalize_indexing_result(dims, data)
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umbra/managers/notifications_manager.py
NotificationsManager.register_notification
def register_notification(self, notification): """ Registers given notification. :param notification: Notification to register. :type notification: Notification :return: Method success. :rtype: bool """ LOGGER.debug("> Registering notification: '{0}'.".format(notification)) self.__notifications.append(notification) self.notification_registered.emit(notification) return True
python
def register_notification(self, notification): """ Registers given notification. :param notification: Notification to register. :type notification: Notification :return: Method success. :rtype: bool """ LOGGER.debug("> Registering notification: '{0}'.".format(notification)) self.__notifications.append(notification) self.notification_registered.emit(notification) return True
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google/grr
grr/core/grr_response_core/lib/utils.py
StreamingZipGenerator.WriteFileHeader
def WriteFileHeader(self, arcname=None, compress_type=None, st=None): """Writes a file header.""" if not self._stream: raise ArchiveAlreadyClosedError( "Attempting to write to a ZIP archive that was already closed.") self.cur_zinfo = self._GenerateZipInfo( arcname=arcname, compress_type=compress_type, st=st) self.cur_file_size = 0 self.cur_compress_size = 0 if self.cur_zinfo.compress_type == zipfile.ZIP_DEFLATED: self.cur_cmpr = zlib.compressobj(zlib.Z_DEFAULT_COMPRESSION, zlib.DEFLATED, -15) else: self.cur_cmpr = None self.cur_crc = 0 if not self._stream: raise ArchiveAlreadyClosedError( "Attempting to write to a ZIP archive that was already closed.") self.cur_zinfo.header_offset = self._stream.tell() # Call _writeCheck(self.cur_zinfo) to do sanity checking on zinfo structure # that we've constructed. self._zip_fd._writecheck(self.cur_zinfo) # pylint: disable=protected-access # Mark ZipFile as dirty. We have to keep self._zip_fd's internal state # coherent so that it behaves correctly when close() is called. self._zip_fd._didModify = True # pylint: disable=protected-access # Write FileHeader now. It's incomplete, but CRC and uncompressed/compressed # sized will be written later in data descriptor. self._stream.write(self.cur_zinfo.FileHeader()) return self._stream.GetValueAndReset()
python
def WriteFileHeader(self, arcname=None, compress_type=None, st=None): """Writes a file header.""" if not self._stream: raise ArchiveAlreadyClosedError( "Attempting to write to a ZIP archive that was already closed.") self.cur_zinfo = self._GenerateZipInfo( arcname=arcname, compress_type=compress_type, st=st) self.cur_file_size = 0 self.cur_compress_size = 0 if self.cur_zinfo.compress_type == zipfile.ZIP_DEFLATED: self.cur_cmpr = zlib.compressobj(zlib.Z_DEFAULT_COMPRESSION, zlib.DEFLATED, -15) else: self.cur_cmpr = None self.cur_crc = 0 if not self._stream: raise ArchiveAlreadyClosedError( "Attempting to write to a ZIP archive that was already closed.") self.cur_zinfo.header_offset = self._stream.tell() # Call _writeCheck(self.cur_zinfo) to do sanity checking on zinfo structure # that we've constructed. self._zip_fd._writecheck(self.cur_zinfo) # pylint: disable=protected-access # Mark ZipFile as dirty. We have to keep self._zip_fd's internal state # coherent so that it behaves correctly when close() is called. self._zip_fd._didModify = True # pylint: disable=protected-access # Write FileHeader now. It's incomplete, but CRC and uncompressed/compressed # sized will be written later in data descriptor. self._stream.write(self.cur_zinfo.FileHeader()) return self._stream.GetValueAndReset()
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ngram.py
NGram.searchitem
def searchitem(self, item, threshold=None): """Search the index for items whose key exceeds the threshold similarity to the key of the given item. :return: list of pairs of (item, similarity) by decreasing similarity. >>> from ngram import NGram >>> n = NGram([(0, "SPAM"), (1, "SPAN"), (2, "EG"), ... (3, "SPANN")], key=lambda x:x[1]) >>> sorted(n.searchitem((2, "SPA"), 0.35)) [((0, 'SPAM'), 0.375), ((1, 'SPAN'), 0.375)] """ return self.search(self.key(item), threshold)
python
def searchitem(self, item, threshold=None): """Search the index for items whose key exceeds the threshold similarity to the key of the given item. :return: list of pairs of (item, similarity) by decreasing similarity. >>> from ngram import NGram >>> n = NGram([(0, "SPAM"), (1, "SPAN"), (2, "EG"), ... (3, "SPANN")], key=lambda x:x[1]) >>> sorted(n.searchitem((2, "SPA"), 0.35)) [((0, 'SPAM'), 0.375), ((1, 'SPAN'), 0.375)] """ return self.search(self.key(item), threshold)
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dfvfs/lib/tsk_partition.py
GetTSKVsPartByPathSpec
def GetTSKVsPartByPathSpec(tsk_volume, path_spec): """Retrieves the TSK volume system part object from the TSK volume object. Args: tsk_volume (pytsk3.Volume_Info): TSK volume information. path_spec (PathSpec): path specification. Returns: tuple: contains: pytsk3.TSK_VS_PART_INFO: TSK volume system part information or None on error. int: partition index or None if not available. """ location = getattr(path_spec, 'location', None) part_index = getattr(path_spec, 'part_index', None) start_offset = getattr(path_spec, 'start_offset', None) partition_index = None if part_index is None: if location is not None: if location.startswith('/p'): try: partition_index = int(location[2:], 10) - 1 except ValueError: pass if partition_index is None or partition_index < 0: location = None if location is None and start_offset is None: return None, None bytes_per_sector = TSKVolumeGetBytesPerSector(tsk_volume) current_part_index = 0 current_partition_index = 0 tsk_vs_part = None # pytsk3 does not handle the Volume_Info iterator correctly therefore # the explicit cast to list is needed to prevent the iterator terminating # too soon or looping forever. tsk_vs_part_list = list(tsk_volume) number_of_tsk_vs_parts = len(tsk_vs_part_list) if number_of_tsk_vs_parts > 0: if (part_index is not None and (part_index < 0 or part_index >= number_of_tsk_vs_parts)): return None, None for tsk_vs_part in tsk_vs_part_list: if TSKVsPartIsAllocated(tsk_vs_part): if partition_index is not None: if partition_index == current_partition_index: break current_partition_index += 1 if part_index is not None and part_index == current_part_index: break if start_offset is not None: start_sector = TSKVsPartGetStartSector(tsk_vs_part) if start_sector is not None: start_sector *= bytes_per_sector if start_sector == start_offset: break current_part_index += 1 # Note that here we cannot solely rely on testing if tsk_vs_part is set # since the for loop will exit with tsk_vs_part set. if tsk_vs_part is None or current_part_index >= number_of_tsk_vs_parts: return None, None if not TSKVsPartIsAllocated(tsk_vs_part): current_partition_index = None return tsk_vs_part, current_partition_index
python
def GetTSKVsPartByPathSpec(tsk_volume, path_spec): """Retrieves the TSK volume system part object from the TSK volume object. Args: tsk_volume (pytsk3.Volume_Info): TSK volume information. path_spec (PathSpec): path specification. Returns: tuple: contains: pytsk3.TSK_VS_PART_INFO: TSK volume system part information or None on error. int: partition index or None if not available. """ location = getattr(path_spec, 'location', None) part_index = getattr(path_spec, 'part_index', None) start_offset = getattr(path_spec, 'start_offset', None) partition_index = None if part_index is None: if location is not None: if location.startswith('/p'): try: partition_index = int(location[2:], 10) - 1 except ValueError: pass if partition_index is None or partition_index < 0: location = None if location is None and start_offset is None: return None, None bytes_per_sector = TSKVolumeGetBytesPerSector(tsk_volume) current_part_index = 0 current_partition_index = 0 tsk_vs_part = None # pytsk3 does not handle the Volume_Info iterator correctly therefore # the explicit cast to list is needed to prevent the iterator terminating # too soon or looping forever. tsk_vs_part_list = list(tsk_volume) number_of_tsk_vs_parts = len(tsk_vs_part_list) if number_of_tsk_vs_parts > 0: if (part_index is not None and (part_index < 0 or part_index >= number_of_tsk_vs_parts)): return None, None for tsk_vs_part in tsk_vs_part_list: if TSKVsPartIsAllocated(tsk_vs_part): if partition_index is not None: if partition_index == current_partition_index: break current_partition_index += 1 if part_index is not None and part_index == current_part_index: break if start_offset is not None: start_sector = TSKVsPartGetStartSector(tsk_vs_part) if start_sector is not None: start_sector *= bytes_per_sector if start_sector == start_offset: break current_part_index += 1 # Note that here we cannot solely rely on testing if tsk_vs_part is set # since the for loop will exit with tsk_vs_part set. if tsk_vs_part is None or current_part_index >= number_of_tsk_vs_parts: return None, None if not TSKVsPartIsAllocated(tsk_vs_part): current_partition_index = None return tsk_vs_part, current_partition_index
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radujica/baloo
baloo/weld/weld_ops.py
weld_unique
def weld_unique(array, weld_type): """Return the unique elements of the array. Parameters ---------- array : numpy.ndarray or WeldObject Input array. weld_type : WeldType Type of each element in the input array. Returns ------- WeldObject Representation of this computation. """ obj_id, weld_obj = create_weld_object(array) weld_template = """map( tovec( result( for( map( {array}, |e| {{e, 0si}} ), dictmerger[{type}, i16, +], |b: dictmerger[{type}, i16, +], i: i64, e: {{{type}, i16}}| merge(b, e) ) ) ), |e| e.$0 )""" weld_obj.weld_code = weld_template.format(array=obj_id, type=weld_type) return weld_obj
python
def weld_unique(array, weld_type): """Return the unique elements of the array. Parameters ---------- array : numpy.ndarray or WeldObject Input array. weld_type : WeldType Type of each element in the input array. Returns ------- WeldObject Representation of this computation. """ obj_id, weld_obj = create_weld_object(array) weld_template = """map( tovec( result( for( map( {array}, |e| {{e, 0si}} ), dictmerger[{type}, i16, +], |b: dictmerger[{type}, i16, +], i: i64, e: {{{type}, i16}}| merge(b, e) ) ) ), |e| e.$0 )""" weld_obj.weld_code = weld_template.format(array=obj_id, type=weld_type) return weld_obj
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shtalinberg/django-el-pagination
el_pagination/decorators.py
page_templates
def page_templates(mapping): """Like the *page_template* decorator but manage multiple paginations. You can map multiple templates to *querystring_keys* using the *mapping* dict, e.g.:: @page_templates({ 'page_contents1.html': None, 'page_contents2.html': 'go_to_page', }) def myview(request): ... When the value of the dict is None then the default *querystring_key* (defined in settings) is used. You can use this decorator instead of chaining multiple *page_template* calls. """ def decorator(view): @wraps(view) def decorated(request, *args, **kwargs): # Trust the developer: he wrote ``context.update(extra_context)`` # in his view. extra_context = kwargs.setdefault('extra_context', {}) querystring_key = request.GET.get(QS_KEY, request.POST.get(QS_KEY, PAGE_LABEL)) template = _get_template(querystring_key, mapping) extra_context['page_template'] = template # Switch the template when the request is Ajax. if request.is_ajax() and template: kwargs[TEMPLATE_VARNAME] = template return view(request, *args, **kwargs) return decorated return decorator
python
def page_templates(mapping): """Like the *page_template* decorator but manage multiple paginations. You can map multiple templates to *querystring_keys* using the *mapping* dict, e.g.:: @page_templates({ 'page_contents1.html': None, 'page_contents2.html': 'go_to_page', }) def myview(request): ... When the value of the dict is None then the default *querystring_key* (defined in settings) is used. You can use this decorator instead of chaining multiple *page_template* calls. """ def decorator(view): @wraps(view) def decorated(request, *args, **kwargs): # Trust the developer: he wrote ``context.update(extra_context)`` # in his view. extra_context = kwargs.setdefault('extra_context', {}) querystring_key = request.GET.get(QS_KEY, request.POST.get(QS_KEY, PAGE_LABEL)) template = _get_template(querystring_key, mapping) extra_context['page_template'] = template # Switch the template when the request is Ajax. if request.is_ajax() and template: kwargs[TEMPLATE_VARNAME] = template return view(request, *args, **kwargs) return decorated return decorator
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DataMedSci/mcpartools
setup.py
get_version
def get_version(): """ Get project version (using versioneer) :return: string containing version """ setup_versioneer() clean_cache() import versioneer version = versioneer.get_version() parsed_version = parse_version(version) if '*@' in str(parsed_version): import time version += str(int(time.time())) return version
python
def get_version(): """ Get project version (using versioneer) :return: string containing version """ setup_versioneer() clean_cache() import versioneer version = versioneer.get_version() parsed_version = parse_version(version) if '*@' in str(parsed_version): import time version += str(int(time.time())) return version
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cmbruns/pyopenvr
src/openvr/__init__.py
IVRApplications.getDefaultApplicationForMimeType
def getDefaultApplicationForMimeType(self, pchMimeType, pchAppKeyBuffer, unAppKeyBufferLen): """return the app key that will open this mime type""" fn = self.function_table.getDefaultApplicationForMimeType result = fn(pchMimeType, pchAppKeyBuffer, unAppKeyBufferLen) return result
python
def getDefaultApplicationForMimeType(self, pchMimeType, pchAppKeyBuffer, unAppKeyBufferLen): """return the app key that will open this mime type""" fn = self.function_table.getDefaultApplicationForMimeType result = fn(pchMimeType, pchAppKeyBuffer, unAppKeyBufferLen) return result
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piotr-rusin/spam-lists
spam_lists/structures.py
Hostname.is_subdomain
def is_subdomain(self, other): """Test if the object is a subdomain of the other. :param other: the object to which we compare this instance :returns: True if this instance is a subdomain of the other """ compared = other.value if hasattr(other, 'value') else other try: return self.value.is_subdomain(compared) except AttributeError: return False
python
def is_subdomain(self, other): """Test if the object is a subdomain of the other. :param other: the object to which we compare this instance :returns: True if this instance is a subdomain of the other """ compared = other.value if hasattr(other, 'value') else other try: return self.value.is_subdomain(compared) except AttributeError: return False
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holoviews/util/transform.py
dim.norm
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python
def norm(self, limits=None): """Unity-based normalization to scale data into 0-1 range. (values - min) / (max - min) Args: limits: tuple of (min, max) defining the normalization range """ kwargs = {} if limits is not None: kwargs = {'min': limits[0], 'max': limits[1]} return dim(self, norm, **kwargs)
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trimesh/base.py
Trimesh.convert_units
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python
def convert_units(self, desired, guess=False): """ Convert the units of the mesh into a specified unit. Parameters ---------- desired : string Units to convert to (eg 'inches') guess : boolean If self.units are not defined should we guess the current units of the document and then convert? """ units._convert_units(self, desired, guess) return self
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ndb/query.py
QueryIterator.next
def next(self): """Iterator protocol: get next item or raise StopIteration.""" if self._fut is None: self._fut = self._iter.getq() try: try: # The future result is set by this class's _extended_callback # method. # pylint: disable=unpacking-non-sequence (ent, self._cursor_before, self._cursor_after, self._more_results) = self._fut.get_result() return ent except EOFError: self._exhausted = True raise StopIteration finally: self._fut = None
python
def next(self): """Iterator protocol: get next item or raise StopIteration.""" if self._fut is None: self._fut = self._iter.getq() try: try: # The future result is set by this class's _extended_callback # method. # pylint: disable=unpacking-non-sequence (ent, self._cursor_before, self._cursor_after, self._more_results) = self._fut.get_result() return ent except EOFError: self._exhausted = True raise StopIteration finally: self._fut = None
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SheffieldML/GPy
GPy/kern/src/ODE_UYC.py
ODE_UYC.Kdiag
def Kdiag(self, X): """Compute the diagonal of the covariance matrix associated to X.""" Kdiag = np.zeros(X.shape[0]) ly=1/self.lengthscale_Y lu=np.sqrt(3)/self.lengthscale_U Vu = self.variance_U Vy=self.variance_Y k1 = (2*lu+ly)/(lu+ly)**2 k2 = (ly-2*lu + 2*lu-ly ) / (ly-lu)**2 k3 = 1/(lu+ly) + (lu)/(lu+ly)**2 slices = index_to_slices(X[:,-1]) for i, ss1 in enumerate(slices): for s1 in ss1: if i==0: Kdiag[s1]+= self.variance_U + self.ubias elif i==1: Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: raise ValueError("invalid input/output index") #Kdiag[slices[0][0]]+= self.variance_U #matern32 diag #Kdiag[slices[1][0]]+= self.variance_U*self.variance_Y*(k1+k2+k3) # diag return Kdiag
python
def Kdiag(self, X): """Compute the diagonal of the covariance matrix associated to X.""" Kdiag = np.zeros(X.shape[0]) ly=1/self.lengthscale_Y lu=np.sqrt(3)/self.lengthscale_U Vu = self.variance_U Vy=self.variance_Y k1 = (2*lu+ly)/(lu+ly)**2 k2 = (ly-2*lu + 2*lu-ly ) / (ly-lu)**2 k3 = 1/(lu+ly) + (lu)/(lu+ly)**2 slices = index_to_slices(X[:,-1]) for i, ss1 in enumerate(slices): for s1 in ss1: if i==0: Kdiag[s1]+= self.variance_U + self.ubias elif i==1: Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: raise ValueError("invalid input/output index") #Kdiag[slices[0][0]]+= self.variance_U #matern32 diag #Kdiag[slices[1][0]]+= self.variance_U*self.variance_Y*(k1+k2+k3) # diag return Kdiag
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bihealth/vcfpy
vcfpy/reader.py
Reader.close
def close(self): """Close underlying stream""" if self.tabix_file and not self.tabix_file.closed: self.tabix_file.close() if self.stream: self.stream.close()
python
def close(self): """Close underlying stream""" if self.tabix_file and not self.tabix_file.closed: self.tabix_file.close() if self.stream: self.stream.close()
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inveniosoftware/invenio-accounts
invenio_accounts/alembic/e12419831262_add_new_columns_on_sessionactivity.py
upgrade
def upgrade(): """Upgrade database.""" with op.batch_alter_table('accounts_user_session_activity') as batch_op: batch_op.add_column(sa.Column('browser', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('browser_version', sa.String(30), nullable=True)) batch_op.add_column( sa.Column('country', sa.String(3), nullable=True)) batch_op.add_column( sa.Column('device', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('ip', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('os', sa.String(80), nullable=True))
python
def upgrade(): """Upgrade database.""" with op.batch_alter_table('accounts_user_session_activity') as batch_op: batch_op.add_column(sa.Column('browser', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('browser_version', sa.String(30), nullable=True)) batch_op.add_column( sa.Column('country', sa.String(3), nullable=True)) batch_op.add_column( sa.Column('device', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('ip', sa.String(80), nullable=True)) batch_op.add_column( sa.Column('os', sa.String(80), nullable=True))
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