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def _plot1d(plotfunc): """ Decorator for common 2d plotting logic Also adds the 2d plot method to class _PlotMethods """ commondoc = """ Parameters ---------- darray : DataArray Must be 2 dimensional, unless creating faceted plots x : string, optional Coordinate for ...
def _plot1d(plotfunc): """ Decorator for common 1d plotting logic. Also adds the 2d plot method to class _PlotMethods """ commondoc = """ Parameters ---------- darray : DataArray Must be 2 dimensional, unless creating faceted plots x : string, optional Coordinate for...
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def _qmu_like(mu, data, pdf, init_pars, par_bounds): """ Clipped version of _tmu where _qmu = 0 if muhat > 0 else _tmu If the lower bound of the POI is 0 this automatically implments qmu_tilde. Otherwise this is qmu (no tilde). """ tensorlib, optimizer = get_backend() tmu_stat, (mubhathat, ...
def _qmu_like(mu, data, pdf, init_pars, par_bounds): """ Clipped version of _tmu where _qmu = 0 if muhat > 0 else _tmu If the lower bound of the POI is 0 this automatically implments qmu_tilde. Otherwise this is qmu (no tilde). """ tensorlib, optimizer = get_backend() tmu_stat, (mubhathat, ...
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def test_pandas_dtypes(conn_cnx): with conn_cnx( session_parameters={ PARAMETER_PYTHON_CONNECTOR_QUERY_RESULT_FORMAT: "arrow_force" } ) as cnx: with cnx.cursor() as cur: cur.execute( "select 1::integer, 2.3::double, 'foo'::string, current_timestamp...
def test_pandas_dtypes(conn_cnx): with conn_cnx( session_parameters={ PARAMETER_PYTHON_CONNECTOR_QUERY_RESULT_FORMAT: "arrow_force" } ) as cnx: with cnx.cursor() as cur: cur.execute( "select 1::integer, 2.3::double, 'foo'::string, current_timestamp...
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def emd(a, b, M, numItermax=100000, log=False, center_dual=True): r"""Solves the Earth Movers distance problem and returns the OT matrix .. math:: \gamma = arg\min_\gamma <\gamma,M>_F s.t. \gamma 1 = a \gamma^T 1= b \gamma\geq 0 where : - M is the metric cost matr...
def emd(a, b, M, numItermax=100000, log=False, center_dual=True): r"""Solves the Earth Movers distance problem and returns the OT matrix .. math:: \gamma = arg\min_\gamma <\gamma,M>_F s.t. \gamma 1 = a \gamma^T 1= b \gamma\geq 0 where : - M is the metric cost matr...
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def mock_snakemake(rulename, **wildcards): """ This function is expected to be executed from the 'scripts'-directory of ' the snakemake project. It returns a snakemake.script.Snakemake object, based on the Snakefile. If a rule has wildcards, you have to specify them in **wildcards. Parameters ...
def mock_snakemake(rulename, **wildcards): """ This function is expected to be executed from the 'scripts'-directory of ' the snakemake project. It returns a snakemake.script.Snakemake object, based on the Snakefile. If a rule has wildcards, you have to specify them in **wildcards. Parameters ...
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def _subprocess_transform(): communicate = (bytes("string", "ascii"), bytes("string", "ascii")) communicate_signature = "def communicate(self, input=None, timeout=None)" args = """\ self, args, bufsize=-1, executable=None, stdin=None, stdout=None, stderr=None, preexec_fn=None, close_fds=True...
def _subprocess_transform(): communicate = (bytes("string", "ascii"), bytes("string", "ascii")) communicate_signature = "def communicate(self, input=None, timeout=None)" args = """\ self, args, bufsize=-1, executable=None, stdin=None, stdout=None, stderr=None, preexec_fn=None, close_fds=True...
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def check_if_updates_and_builds_set(ctx, param, value): """ Print an error to stderr if the user has set both the --updates and --builds flags. Args: ctx (click.core.Context): The Click context, used to find out if the other flags are set. param (click.core.Option): The option being handled...
def check_if_updates_and_builds_set(ctx, param, value): """ Print an error to stderr if the user has set both the --updates and --builds flags. Args: ctx (click.core.Context): The Click context, used to find out if the other flags are set. param (click.core.Option): The option being handled...
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def add_subparser( subparsers: argparse._SubParsersAction, parents: List[argparse.ArgumentParser] ): scaffold_parser = subparsers.add_parser( "init", parents=parents, help="Creates a new project, with example training data, actions, and config files.", formatter_class=argparse.Ar...
def add_subparser( subparsers: argparse._SubParsersAction, parents: List[argparse.ArgumentParser] ): scaffold_parser = subparsers.add_parser( "init", parents=parents, help="Creates a new project, with example training data, actions, and config files.", formatter_class=argparse.Ar...
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def fetch_incidents(last_run, first_run_time_range): target_orgs = [] if BROKER: orgs = list_org() for org in orgs: target_orgs.append(org['org_name']) else: target_orgs.append(None) next_run = {} incidents = [] for target_org in target_orgs: if targe...
def fetch_incidents(last_run, first_run_time_range): target_orgs = [] if BROKER: orgs = list_org() for org in orgs: target_orgs.append(org['org_name']) else: target_orgs.append(None) next_run = {} incidents = [] for target_org in target_orgs: if targe...
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def observable(me_tables, init_term=0, mapping="jordan_wigner", wires=None): r"""Builds the many-body observable whose expectation value can be measured in PennyLane. This function can be used to build second-quantized operators in the basis of single-particle states (e.g., HF states) and to transform...
def observable(me_tables, init_term=0, mapping="jordan_wigner", wires=None): r"""Builds the many-body observable whose expectation value can be measured in PennyLane. This function can be used to build second-quantized operators in the basis of single-particle states (e.g., HF states) and to transform...
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def _is_applicable( module_details: ModuleDetails, cfg: dict, schema: Optional[dict] = None ) -> bool: if not module_details.module.meta.get("skippable", False): return True normalized_name = f"cc_{module_details.name}".replace("-", "_") config_keys = get_config_keys(normalized_name, schema=sche...
def _is_applicable( module_details: ModuleDetails, cfg: dict, schema: Optional[dict] = None ) -> bool: if not module_details.module.meta.get("skip_on_inapplicable_schema", False): return True normalized_name = f"cc_{module_details.name}".replace("-", "_") config_keys = get_config_keys(normalized...
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def get_variation_from_env(envvar_value): """Return a tuple with variation data from the specific environment variable key. Raise an exception if the passed in envvar doesn't look something like: '0 100' """ try: # We want to create a tuple of integers from a string containing #...
def get_variation_from_env(envvar_value): """Return a tuple with variation data from the specific environment variable key. Raise an exception if the passed in envvar doesn't look something like: '0 100' """ try: # We want to create a tuple of integers from a string containing #...
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def journal_entry(cmdr, is_beta, system, station, entry, state): # Always update, even if we're not the *current* system or station provider. this.system_address = entry.get('SystemAddress') or this.system_address this.system = entry.get('StarSystem') or this.system # We need pop == 0 to set the value ...
def journal_entry(cmdr, is_beta, system, station, entry, state): # Always update, even if we're not the *current* system or station provider. this.system_address = entry.get('SystemAddress') or this.system_address this.system = entry.get('StarSystem') or this.system # We need pop == 0 to set the value ...
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def test_multilabel_binarizer_unknown_class(): mlb = MultiLabelBinarizer() y = [[1, 2]] Y = np.array([[1, 0], [0, 1]]) warning_message = 'will be ignored' with pytest.warns(UserWarning, match=warning_message): matrix = mlb.fit(y).transform([[4, 1], [2, 0]]) Y = np.array([[1, 0, 0], [0, ...
def test_multilabel_binarizer_unknown_class(): mlb = MultiLabelBinarizer() y = [[1, 2]] Y = np.array([[1, 0], [0, 1]]) warning_message = 'unknown class.* will be ignored' with pytest.warns(UserWarning, match=warning_message): matrix = mlb.fit(y).transform([[4, 1], [2, 0]]) Y = np.array(...
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def _has_different_parameter_names_only(original, overridden): """Check if the original and the overridden parameters have different names but the same type.If they do, raise arguments-renamed. In any other case return False. Args: original (astroid.FunctionDef): original function's definition...
def _has_different_parameter_names_only(original: astroid.FunctionDef, overridden: astroid.FunctionDef) -> bool: """Check if the original and the overridden parameters have different names but the same type.If they do, raise arguments-renamed. In any other case return False. Args: original (as...
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def get_terminal_width() -> int: """Get number of columns of the terminal.""" return shutil.get_terminal_size().columns - 1
def get_terminal_width() -> int: """Return the width of the terminal window. The width of the terminal connected to sys.__stdout__ is obtained via os.get_terminal_size. If the terminal size cannot be determined, the environment variable COLUMNS is used if defined. Otherwise, fallback value is retur...
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def _modify_relative_data(relative_data, replace_spaces=False): modified_relative_data = OrderedDict() for key, value in relative_data.items(): for i, string in enumerate(value): string = RELATIVE_PATTERN.sub(r'(\\d+)', string) if replace_spaces: string = re.sub(r...
def _modify_relative_data(relative_data, replace_spaces=False): modified_relative_data = OrderedDict() for key, value in relative_data.items(): for i, string in enumerate(value): string = RELATIVE_PATTERN.sub(r'(\\d+)', string) if replace_spaces: string = re.sub(r...
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def sortable_lcc_to_short_lcc(lcc): """ As close to the inverse of make_sortable_lcc as possible :param basestring lcc: :rtype: basestring """ m = LCC_PARTS_RE.match(lcc) parts = m.groupdict() parts['letters'] = parts['letters'].strip('-') parts['number'] = parts['number'].strip('0')...
def sortable_lcc_to_short_lcc(lcc): """ As close to the inverse of make_sortable_lcc as possible :param basestring lcc: :rtype: basestring """ m = LCC_PARTS_RE.match(lcc) parts = m.groupdict() parts['letters'] = parts['letters'].strip('-') parts['number'] = parts['number'].strip('0')...
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def _get_config_or_cache_dir(xdg_base): configdir = os.environ.get('MPLCONFIGDIR') if configdir: configdir = Path(configdir).resolve() elif sys.platform.startswith(('linux', 'freebsd')) and xdg_base: configdir = Path(xdg_base, "matplotlib") else: configdir = Path.home() / ".matpl...
def _get_config_or_cache_dir(xdg_base): configdir = os.environ.get('MPLCONFIGDIR') if configdir: configdir = Path(configdir).resolve() elif sys.platform.startswith(('linux', 'freebsd')) and xdg_base: configdir = Path(xdg_base, "matplotlib") else: configdir = Path.home() / ".matpl...
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def iterator_suffix(iterator, stop: int): for i, item in enumerate(iterator): if i < stop: # [no-else-continue] continue else: yield item
def even_number_under(n: int): for i in range(n): if i%2 == 1: # [no-else-continue] continue else: yield i
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def check(check_data): """ Invoke clang with an action which called by processes. Different analyzer object belongs to for each build action. skiplist handler is None if no skip file was configured. """ actions_map, action, context, analyzer_config, \ output_dir, skip_handler, quiet_out...
def check(check_data): """ Invoke clang with an action which called by processes. Different analyzer object belongs to for each build action. skiplist handler is None if no skip file was configured. """ actions_map, action, context, analyzer_config, \ output_dir, skip_handler, quiet_out...
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def export_regions(objs): """ Convenience function to convert a sequence of Ginga canvas objects to a ds9 file containing regions and return a list of matching . Parameters ---------- objs : seq of subclasses of `~ginga.canvas.CanvasObject.CanvasObjectBase` Sequence of Ginga canvas ...
def export_regions(objs): """ Convenience function to convert a sequence of Ginga canvas objects to a ds9 file containing regions and return a list of matching regions. Parameters ---------- objs : seq of subclasses of `~ginga.canvas.CanvasObject.CanvasObjectBase` Sequence of Ginga ...
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def log_current_packages(packages: Tuple[str], install: bool = True): ''' Log which packages are installed or removed. :param packages: List of packages that are affected. :param install: Identifier to distinguish installation from removal. ''' action = 'Installing' if install else 'Removing' ...
def log_current_packages(packages: Tuple[str], install: bool = True): ''' Log which packages are installed or removed. :param packages: List of packages that are affected. :param install: Identifier to distinguish installation from removal. ''' logging.info(f'{action} {" ".join(packages)}') ...
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def process_alias(io, data, name, print_name=False): return process_rr(io, data, 'ALIAS', 'target-resource-id', name, print_name)
def process_alias(io, data, name, print_name=False): return process_rr(io, data, 'ALIAS', 'target-resource-id', name, print_name)
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def is_definitely_not_enum_member(name: str, typ: Optional[Type]) -> bool: """ Return `True` if we are certain that an object inside an enum class statement will not be converted to become a member of the enum. The following things are not converted: 1. Assignments with private names like in `__pro...
def is_definitely_not_enum_member(name: str, typ: Type | None) -> bool: """ Return `True` if we are certain that an object inside an enum class statement will not be converted to become a member of the enum. The following things are not converted: 1. Assignments with private names like in `__prop =...
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def tiltProjection(taux: torch.Tensor, tauy: torch.Tensor, inv: bool = False) -> torch.Tensor: r"""Estimate the tilt projection matrix or the inverse tilt projection matrix Args: taux (torch.Tensor): Rotation angle in radians around the :math:`x`-axis with shape :math:`(*, 1)`. tauy (torch.Tens...
def tiltProjection(taux: torch.Tensor, tauy: torch.Tensor, inv: bool = False) -> torch.Tensor: r"""Estimate the tilt projection matrix or the inverse tilt projection matrix Args: taux (torch.Tensor): Rotation angle in radians around the :math:`x`-axis with shape :math:`(*, 1)`. tauy (torch.Tens...
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def check_if_incident_was_modified_in_xdr(incident_id): demisto_incident = demisto.get_incidents()[0] last_mirrored_in_time = demisto_incident.get('CustomFields', {}).get('lastmirroredintime') last_mirrored_in_time_timestamp = arg_to_timestamp(last_mirrored_in_time, 'last_mirrored_in_time') last_modifi...
def check_if_incident_was_modified_in_xdr(incident_id): demisto_incident = demisto.get_incidents()[0] last_mirrored_in_time = demisto_incident.get('CustomFields', {}).get('lastmirroredintime') last_mirrored_in_time_timestamp = arg_to_timestamp(last_mirrored_in_time, 'last_mirrored_in_time') last_modifi...
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def patched_api_call(original_func, instance, args, kwargs): pin = Pin.get_from(instance) if not pin or not pin.enabled(): return original_func(*args, **kwargs) endpoint_name = deep_getattr(instance, '_endpoint._endpoint_prefix') with pin.tracer.trace('{}.command'.format(endpoint_name), ...
def patched_api_call(original_func, instance, args, kwargs): pin = Pin.get_from(instance) if not pin or not pin.enabled(): return original_func(*args, **kwargs) endpoint_name = deep_getattr(instance, '_endpoint._endpoint_prefix') with pin.tracer.trace('{}.command'.format(endpoint_name), ...
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def get_model_class(name): for cls in get_all_subclasses(Model): if cls.__name__.lower() == name: return cls raise ValueError("There is not model class with this name: {}".format(name))
def get_model_class(name): for cls in get_all_subclasses(Model): if cls.__name__.lower() == name: return cls raise ValueError("There is no model class with this name: {}".format(name))
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def dice_loss(inputs: Tensor, targets: Tensor, num_masks: float) -> Tensor: r""" Compute the DICE loss, similar to generalized IOU for masks as follow .. math:: \mathcal{L}_{\text{dice}(x, y) = 1 - \frac{2 * x \cap y }{x \cup y + 1}} In practice, since `targets` is a binary mask, (only 0s and ...
def dice_loss(inputs: Tensor, targets: Tensor, num_masks: float) -> Tensor: r""" Compute the DICE loss, similar to generalized IOU for masks as follow .. math:: \mathcal{L}_{\text{dice}(x, y) = 1 - \frac{2 * x \cap y }{x \cup y + 1}} In practice, since `targets` is a binary mask, (only 0s and ...
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def move_git_repo(source_path, new_path): """ Moves git folder and .gitignore to the new backup directory. """ if os.path.exists(os.path.join(new_path, '.git')) or os.path.exists(os.path.join(new_path, '.gitignore')): print_red_bold("Git repository already exists new path ({})".format(new_path)) print_red_bold(...
def move_git_repo(source_path, new_path): """ Moves git folder and .gitignore to the new backup directory. """ if os.path.exists(os.path.join(new_path, '.git')) or os.path.exists(os.path.join(new_path, '.gitignore')): print_red_bold("A git repo already exists here: {}".format(new_path)) print_red_bold("Please c...
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def _run_pip(args, additional_paths=None): # Add our bundled software to the sys.path so we can import it if additional_paths is not None: sys.path = additional_paths + sys.path # Invoke pip as if it's the main module, and catch the exit. backup_argv = sys.argv[:] sys.argv[1:] = args tr...
def _run_pip(args, additional_paths=None): # Add our bundled software to the sys.path so we can import it if additional_paths is not None: sys.path = additional_paths + sys.path # Invoke pip as if it's the main module, and catch the exit. backup_argv = sys.argv[:] sys.argv[1:] = args tr...
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def decompose_clifford_tableau_to_operations( qubits: List['cirq.Qid'], clifford_tableau: qis.CliffordTableau ) -> List[ops.Operation]: """Decompose an n-qubit Clifford Tableau into a list of one/two qubit operations. Args: qubits: The list of qubits being operated on. clifford_tableau: The...
def decompose_clifford_tableau_to_operations( qubits: List['cirq.Qid'], clifford_tableau: qis.CliffordTableau ) -> List[ops.Operation]: """Decompose an n-qubit Clifford Tableau into a list of one/two qubit operations. Args: qubits: The list of qubits being operated on. clifford_tableau: The...
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def urisfy_regex_or_tree( unit: Any, is_ascii: bool, is_wide: bool, is_nocase: bool, ) -> Optional[UrsaExpression]: or_strings = flatten_regex_or_tree(unit) if or_strings and all(s is not None for s in or_strings): or_ursa_strings: List[UrsaExpression] = [] for s in or_strings: u...
def urisfy_regex_or_tree( unit: Any, is_ascii: bool, is_wide: bool, is_nocase: bool, ) -> Optional[UrsaExpression]: or_strings = flatten_regex_or_tree(unit) if or_strings and all(or_strings): or_ursa_strings: List[UrsaExpression] = [] for s in or_strings: ursified_s = ursify_rege...
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def main() -> None: params = {k: v for k, v in demisto.params().items() if v is not None} params['indicator_type'] = FeedIndicatorType.File params['feed_name_to_config'] = { 'File': { 'url': params.get("url") + "/api/v1/", 'extractor': "data", 'indicator': 'sha256...
def main() -> None: params = {k: v for k, v in demisto.params().items() if v is not None} params['indicator_type'] = FeedIndicatorType.File params['feed_name_to_config'] = { 'File': { 'url': params.get("url") + "/api/v1/", 'extractor': "data", 'indicator': 'sha256...
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def test_output_version(): class InputSpec(nib.TraitedSpec): foo = nib.traits.Int(desc='a random int') class OutputSpec(nib.TraitedSpec): foo = nib.traits.Int(desc='a random int', min_ver='0.9') class DerivedInterface1(nib.BaseInterface): input_spec = InputSpec output_spec ...
def test_output_version(): class InputSpec(nib.TraitedSpec): foo = nib.traits.Int(desc='a random int') class OutputSpec(nib.TraitedSpec): foo = nib.traits.Int(desc='a random int', min_ver='0.9') class DerivedInterface1(nib.BaseInterface): input_spec = InputSpec output_spec ...
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def remove_default_ca_certs(distro_name): """ Removes all default trusted CA certificates from the system. To actually apply the change you must also call L{update_ca_certs}. """ distro_cfg = _distro_ca_certs_configs(distro_name) util.delete_dir_contents(distro_cfg['ca_cert_path']) util.dele...
def remove_default_ca_certs(distro_name): """ Removes all default trusted CA certificates from the system. To actually apply the change you must also call L{update_ca_certs}. """ distro_cfg = _distro_ca_certs_configs(distro_name) util.delete_dir_contents(distro_cfg['ca_cert_path']) util.dele...
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def user_dictize( user, context, include_password_hash=False, include_plugin_extras=False): if context.get('with_capacity'): user, capacity = user result_dict = d.table_dictize(user, context, capacity=capacity) else: result_dict = d.table_dictize(user, context) pass...
def user_dictize( user, context, include_password_hash=False, include_plugin_extras=False): if context.get('with_capacity'): user, capacity = user result_dict = d.table_dictize(user, context, capacity=capacity) else: result_dict = d.table_dictize(user, context) pass...
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def _compute_dt_correlations(catalog, master, min_link, event_id_mapper, stream_dict, min_cc, extract_len, pre_pick, shift_len, interpolate, max_workers=1): """ Compute cross-correlation delay times. """ max_workers = max_workers or 1 Logger.info( ...
def _compute_dt_correlations(catalog, master, min_link, event_id_mapper, stream_dict, min_cc, extract_len, pre_pick, shift_len, interpolate, max_workers=1): """ Compute cross-correlation delay times. """ max_workers = max_workers or 1 Logger.info( ...
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def install_pip(): print('') print('Install pip') print('') try: from urllib.request import urlopen except ImportError: from urllib2 import urlopen tmp = tempfile.mkdtemp(prefix='buildout-dev-') try: get_pip = os.path.join(tmp, 'get-pip.py') with open(get_pip...
def install_pip(): print('') print('Install pip') print('') try: from urllib.request import urlopen except ImportError: from urllib2 import urlopen tmp = tempfile.mkdtemp(prefix='buildout-dev-') try: get_pip = os.path.join(tmp, 'get-pip.py') with open(get_pip...
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def filter_ids( pools: 'List[Pool]', ids: 'Iterable[str]', *, warn: 'bool' = True, out: 'IDTokens' = IDTokens.Task, pattern_match: 'bool' = True, # ) -> _RET: ): """Filter IDs against a pool of tasks. Args: pool: The pool to match against. ids: ...
def filter_ids( pools: 'List[Pool]', ids: 'Iterable[str]', *, warn: 'bool' = True, out: 'IDTokens' = IDTokens.Task, pattern_match: 'bool' = True, # ) -> _RET: ): """Filter IDs against a pool of tasks. Args: pool: The pool to match against. ids: ...
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def _parse_char_metrics(fh): """ Parse the given filehandle for character metrics information and return the information as dicts. It is assumed that the file cursor is on the line behind 'StartCharMetrics'. Returns ------- ascii_d : dict A mapping "ASCII num of the character"...
def _parse_char_metrics(fh): """ Parse the given filehandle for character metrics information and return the information as dicts. It is assumed that the file cursor is on the line behind 'StartCharMetrics'. Returns ------- ascii_d : dict A mapping "ASCII num of the character"...
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def _parse_pulse_args(backend, qubit_lo_freq, meas_lo_freq, qubit_lo_range, meas_lo_range, schedule_los, meas_level, meas_return, meas_map, memory_slot_size, rep_time, rep_delay, parametric_pulses, ...
def _parse_pulse_args(backend, qubit_lo_freq, meas_lo_freq, qubit_lo_range, meas_lo_range, schedule_los, meas_level, meas_return, meas_map, memory_slot_size, rep_time, rep_delay, parametric_pulses, ...
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def _toqclass_helper(im): data = None colortable = None # handle filename, if given instead of image name if hasattr(im, "toUtf8"): # FIXME - is this really the best way to do this? im = str(im.toUtf8(), "utf-8") if isPath(im): im = Image.open(im) if im.mode == "1": ...
def _toqclass_helper(im): data = None colortable = None # handle filename, if given instead of image name if hasattr(im, "toUtf8"): # FIXME - is this really the best way to do this? im = str(im.toUtf8(), "utf-8") if isPath(im): im = Image.open(im) if im.mode == "1": ...
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def get_time_as_str(t, timezone=None): if timezone is None: timezone = config.get("TIMEZONE") s = (t - datetime.utcnow()).total_seconds() (m, s) = divmod(s, 60) (h, m) = divmod(m, 60) d = timedelta(hours=h, minutes=m, seconds=s) if timezone is not None: disappear_time = datetime....
def get_time_as_str(t, timezone=None): if timezone is None: timezone = config.get("TIMEZONE") s = (t - datetime.utcnow()).total_seconds() (m, s) = divmod(s, 60) (h, m) = divmod(m, 60) d = timedelta(hours=h, minutes=m, seconds=s) if timezone is not None: disappear_time = datetime....
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def main(argv=None): parser = get_parser() arguments = parser.parse_args(argv) verbose = arguments.v set_loglevel(verbose=verbose) # Default params param = Param() # Get parser info fname_data = arguments.i fname_mask = arguments.m fname_mask_noise = arguments.m_noise m...
def main(argv=None): parser = get_parser() arguments = parser.parse_args(argv) verbose = arguments.v set_loglevel(verbose=verbose) # Default params param = Param() # Get parser info fname_data = arguments.i fname_mask = arguments.m fname_mask_noise = arguments.m_noise m...
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def config_proxy_skip(proxies, uri, skip_proxy=False): """ Returns an amended copy of the proxies dictionary - used by `requests`, it will disable the proxy if the uri provided is to be reached directly. :param proxies dict with existing proxies: 'https', 'http', 'no' as pontential keys :param uri u...
def config_proxy_skip(proxies, uri, skip_proxy=False): """ Returns an amended copy of the proxies dictionary - used by `requests`, it will disable the proxy if the uri provided is to be reached directly. :param proxies dict with existing proxies: 'https', 'http', 'no' as pontential keys :param uri U...
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def _vectfit_xs(energy, ce_xs, mts, rtol=1e-3, atol=1e-5, orders=None, n_vf_iter=30, log=False, path_out=None, **kwargs): r"""Convert point-wise cross section to multipole data via Vector Fitting. Parameters ---------- energy : np.ndarray Energy array ce_xs : np.ndarray ...
def _vectfit_xs(energy, ce_xs, mts, rtol=1e-3, atol=1e-5, orders=None, n_vf_iter=30, log=False, path_out=None, **kwargs): r"""Convert point-wise cross section to multipole data via Vector Fitting. Parameters ---------- energy : np.ndarray Energy array ce_xs : np.ndarray ...
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def get_pid_filename(options, pid_dir): """Get the pid filename in ``pid_dir`` from the given ``options``. :param options: command line options :param str pid_dir: path to the pid directory :return: absolute filename of the pid file By default, it's ``sopel.pid``, but if a configuration filename i...
def get_pid_filename(options, pid_dir): """Get the pid file name in ``pid_dir`` from the given ``options``. :param options: command line options :param str pid_dir: path to the pid directory :return: absolute filename of the pid file By default, it's ``sopel.pid``, but if a configuration filename ...
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def ks_2samp(data1, data2, alternative='two-sided', mode='auto'): """ Compute the Kolmogorov-Smirnov statistic on 2 samples. This is a two-sided test for the null hypothesis that 2 independent samples are drawn from the same continuous distribution. The alternative hypothesis can be either 'two-si...
def ks_2samp(data1, data2, alternative='two-sided', mode='auto'): """ Compute the Kolmogorov-Smirnov statistic on 2 samples. This is a two-sided test for the null hypothesis that 2 independent samples are drawn from the same continuous distribution. The alternative hypothesis can be either 'two-si...
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def getgccversion(chost=None): """ rtype: C{str} return: the current in-use gcc version """ gcc_ver_command = ["gcc", "-dumpversion"] gcc_ver_prefix = "gcc-" # accept clang as system compiler too clang_ver_command = ["clang", "--version"] clang_ver_prefix = "clang-" ubinpath ...
def getgccversion(chost=None): """ rtype: C{str} return: the current in-use gcc version """ gcc_ver_command = ["gcc", "-dumpversion"] gcc_ver_prefix = "gcc-" # accept clang as system compiler too clang_ver_command = ["clang", "--version"] clang_ver_prefix = "clang-" ubinpath ...
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def _plot1d(plotfunc): """ Decorator for common 2d plotting logic Also adds the 2d plot method to class _PlotMethods """ commondoc = """ Parameters ---------- darray : DataArray Must be 2 dimensional, unless creating faceted plots x : string, optional Coordinate for ...
def _plot1d(plotfunc): """ Decorator for common 2d plotting logic Also adds the 2d plot method to class _PlotMethods """ commondoc = """ Parameters ---------- darray : DataArray Must be 2 dimensional, unless creating faceted plots x : string, optional Coordinate for ...
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def dot(*arrays, dims=None, **kwargs): """Generalized dot product for xarray objects. Like np.einsum, but provides a simpler interface based on array dimensions. Parameters ---------- arrays: DataArray (or Variable) objects Arrays to compute. dims: xarray.ALL_DIMS, str or tuple of strin...
def dot(*arrays, dims=None, **kwargs): """Generalized dot product for xarray objects. Like np.einsum, but provides a simpler interface based on array dimensions. Parameters ---------- arrays: DataArray (or Variable) objects Arrays to compute. dims: '...', str or tuple of strings, option...
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def _van_es_entropy(X, m): """Compute the van Es estimator as described in [6]""" # No equation number, but referred to as HVE_mn. # Typo: there should be a log within the summation. n = X.shape[-1] term1 = 1/(n-m) * np.sum(np.log((n+1)/m * (X[..., m:] - X[..., :-m])), a...
def _van_es_entropy(X, m): """Compute the van Es estimator as described in [6].""" # No equation number, but referred to as HVE_mn. # Typo: there should be a log within the summation. n = X.shape[-1] term1 = 1/(n-m) * np.sum(np.log((n+1)/m * (X[..., m:] - X[..., :-m])), ...
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def library_payload(roon_server, zone_id, media_content_id): """Create response payload for the library.""" opts = { "hierarchy": "browse", "zone_or_output_id": zone_id, "count": ITEM_LIMIT, } # Roon starts browsing for a zone where it left off - so start from the top unless ot...
def library_payload(roon_server, zone_id, media_content_id): """Create response payload for the library.""" opts = { "hierarchy": "browse", "zone_or_output_id": zone_id, "count": ITEM_LIMIT, } # Roon starts browsing for a zone where it left off - so start from the top unless ot...
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def initialize_instance(values, **kwargs): # TODO: remove when deprecation is finalized https://github.com/DataDog/integrations-core/pull/9340 if 'username' not in values and 'user' in values: values['username'] = values['user'] _validate_authenticator_option(values) if 'private_key_password' ...
def initialize_instance(values, **kwargs): # TODO: remove when deprecation is finalized https://github.com/DataDog/integrations-core/pull/9340 if 'username' not in values and 'user' in values: values['username'] = values['user'] _validate_authenticator_option(values) if 'private_key_password' ...
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def _first_ip_nexthop_from_route(routes: Iterable) -> None | str: """Find the first RTA_PREFSRC in the routes.""" _LOGGER.debug("Routes: %s", routes) for route in routes: for key, value in route["attrs"]: if key == "RTA_PREFSRC": return cast(str, value) return None
def _first_ip_nexthop_from_route(routes: Iterable) -> str | None: """Find the first RTA_PREFSRC in the routes.""" _LOGGER.debug("Routes: %s", routes) for route in routes: for key, value in route["attrs"]: if key == "RTA_PREFSRC": return cast(str, value) return None
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def state_vector_to_probabilities(state_vector: 'cirq.STATE_VECTOR_LIKE') -> np.ndarray: normalized_vector = format(state_vector) return np.abs(normalized_vector) ** 2
def state_vector_to_probabilities(state_vector: 'cirq.STATE_VECTOR_LIKE') -> np.ndarray: normalized_vector = format(state_vector) return np.abs(valid_state_vector) ** 2
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def var( values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True, axis: int | None = None, ddof: int = 1, ): if not values.size or mask.all(): return libmissing.NA return _reductions( np.var, values=values, mask=mask, skipna=skipna, axis=axis, **{"ddof": ...
def var( values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True, axis: int | None = None, ddof: int = 1, ): if not values.size or mask.all(): return libmissing.NA return _reductions( np.var, values=values, mask=mask, skipna=skipna, axis=axis, ddof=ddof ...
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def get_language_name(code): lang = web.ctx.site.get('/languages/' + code) return lang.name if lang else "'%s' unknown" % code
def read_author_facet(author_facet: str) -> tuple[str, str]: key, name = author_facet.split(' ', 1) return key, name """ >>> read_author_facet("OL26783A Leo Tolstoy") ('OL26783A', 'Leo Tolstoy') """ key, name = author_facet.strip().split(' ', 1) lang = web.ctx.site.get('/languages/' + ...
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def main(): # noqa: C901, CCR001 """Run the main code of the program.""" try: # arg parsing parser = argparse.ArgumentParser( prog=appcmdname, description='Prints the current system and station (if docked) to stdout and optionally writes player ' ...
def main(): # noqa: C901, CCR001 """Run the main code of the program.""" try: # arg parsing parser = argparse.ArgumentParser( prog=appcmdname, description='Prints the current system and station (if docked) to stdout and optionally writes player ' ...
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def compute_evaluation_metrics(metrics, labels, predictions, model_type, label_dict=None, grid_objective=None, probability=False, ...
def compute_evaluation_metrics(metrics, labels, predictions, model_type, label_dict=None, grid_objective=None, probability=False, ...
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def import_ivar_by_name(name: str, prefixes: List[str] = [None], last_errors = None) -> Tuple[str, Any, Any, str]: """Import an instance variable that has the given *name*, under one of the *prefixes*. The first name that succeeds is used. """ try: name, attr = name.rsplit(".", 1) real_...
def import_ivar_by_name(name: str, prefixes: List[str] = [None], last_errors = None) -> Tuple[str, Any, Any, str]: """Import an instance variable that has the given *name*, under one of the *prefixes*. The first name that succeeds is used. """ try: name, attr = name.rsplit(".", 1) real_...
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def resnet152(weights: Optional[ResNet152Weights] = None, progress: bool = True, **kwargs: Any) -> ResNet: if "pretrained" in kwargs: warnings.warn("The argument pretrained is deprecated, please use weights instead.") weights = ResNet152Weights.ImageNet1K_RefV1 if kwargs.pop("pretrained") else None ...
def resnet152(weights: Optional[ResNet152Weights] = None, progress: bool = True, **kwargs: Any) -> ResNet: if "pretrained" in kwargs: warnings.warn("The argument pretrained is deprecated, please use weights instead.") weights = ResNet152Weights.ImageNet1K_RefV1 if kwargs.pop("pretrained") else None ...
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def gti_dirint(poa_global, aoi, solar_zenith, solar_azimuth, times, surface_tilt, surface_azimuth, pressure=101325., use_delta_kt_prime=True, temp_dew=None, albedo=.25, model='perez', model_perez='allsitescomposite1990', calculate_gt_90=True, max_iterations=30...
def gti_dirint(poa_global, aoi, solar_zenith, solar_azimuth, times, surface_tilt, surface_azimuth, pressure=101325., use_delta_kt_prime=True, temp_dew=None, albedo=.25, model='perez', model_perez='allsitescomposite1990', calculate_gt_90=True, max_iterations=30...
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def clean_multiline_string(multiline_string, sep='\n'): """ Dedent, split, remove first and last empty lines, rejoin. """ multiline_string = textwrap.dedent(multiline_string) string_list = multiline_string.split(sep) if not string_list[0]: string_list = string_list[1:] if not string_...
def clean_multiline_string(multiline_string, sep='\n'): """ Dedent, split, remove first and last empty lines, rejoin. """ multiline_string = textwrap.dedent(multiline_string) string_list = multiline_string.split(sep) if not string_list[0]: string_list = string_list[1:] if not string_...
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def create_new_key_pair(secret: bytes = None) -> KeyPair: """ Returns a new Secp256k1 keypair derived from the provided ``secret``, a sequence of bytes corresponding to some integer between 0 and the group order. A valid secret is created if ``None`` is passed. """ private_key = Secp256k1Privat...
def create_new_key_pair(secret: bytes = None) -> KeyPair: """ Returns a new Secp256k1 keypair derived from the provided ``secret``, a sequence of bytes corresponding to some integer between 0 and the group order. A valid secret is created if ``None`` is passed. """ private_key = Secp256k1Privat...
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def laplacian_pe(g, k, padding=False, return_eigval=False): r"""Laplacian Positional Encoding, as introduced in `Benchmarking Graph Neural Networks <https://arxiv.org/abs/2003.00982>`__ This function computes the laplacian positional encodings as the k smallest non-trivial eigenvectors. Parame...
def laplacian_pe(g, k, padding=False, return_eigval=False): r"""Laplacian Positional Encoding, as introduced in `Benchmarking Graph Neural Networks <https://arxiv.org/abs/2003.00982>`__ This function computes the laplacian positional encodings as the k smallest non-trivial eigenvectors. Parame...
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def maybe_base64(value: Optional[str]) -> Optional[str]: if not value: return None elif set(value).issubset(_base64_alphabet): return value return base64.b64encode(value.encode()).decode()
def decode_base64(value: Optional[str]) -> Optional[str]: """ Lazy decoding of base64-encoded data. If the character set indicates a base64-encoded content, decoding is attempted and the result returned. Otherwise, or if the decoding fails, the original string is returned. """ if not value: ...
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def _array_repeat_op(translator, expr): op = expr.op() arr, times = op.args arr_ = _parenthesize(translator, arr) times_ = _parenthesize(translator, times) repeat_fmt = ''' (select arrayFlatten(groupArray(arr)) from ( select {} as arr from system.numbers ...
def _array_repeat_op(translator, expr): op = expr.op() arr, times = op.args arr_ = _parenthesize(translator, arr) times_ = _parenthesize(translator, times) repeat_fmt = ''' (select arrayFlatten(groupArray(arr)) from ( select {arr_} as arr from system.numbers...
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def execute(): if frappe.db.exists("DocType", "Desk Page"): if frappe.db.exists('DocType Workspace'): # this patch was not added initially, so this page might still exist frappe.delete_doc('DocType', 'Desk Page') else: rename_doc('DocType', 'Desk Page', 'Workspace') rename_doc('DocType', 'Desk Chart', '...
def execute(): if frappe.db.exists("DocType", "Desk Page"): if frappe.db.exists('DocType', 'Workspace'): # this patch was not added initially, so this page might still exist frappe.delete_doc('DocType', 'Desk Page') else: rename_doc('DocType', 'Desk Page', 'Workspace') rename_doc('DocType', 'Desk Chart'...
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def combine_evoked(all_evoked, weights): """Merge evoked data by weighted addition or subtraction. Each `~mne.Evoked` in ``all_evoked`` should have the same channels and the same time instants. Subtraction can be performed by passing ``weights=[1, -1]``. .. Warning:: Other than cases like ...
def combine_evoked(all_evoked, weights): """Merge evoked data by weighted addition or subtraction. Each `~mne.Evoked` in ``all_evoked`` should have the same channels and the same time instants. Subtraction can be performed by passing ``weights=[1, -1]``. .. Warning:: Other than cases like ...
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def render_logs_progress(): valid_checks = sorted(get_valid_checks()) total_checks = len(valid_checks) checks_with_logs = 0 lines = ['## Logs specs', '', None, '', '??? check "Completed"'] for check in valid_checks: config_file = get_config_file(check) status = ' ' tile_onl...
def render_logs_progress(): valid_checks = sorted(get_valid_checks()) total_checks = len(valid_checks) checks_with_logs = 0 lines = ['## Logs specs', '', None, '', '??? check "Completed"'] for check in valid_checks: config_file = get_config_file(check) status = ' ' tile_onl...
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def require_valid_meta_tag_content(meta_tag_content): """Generic meta tag content validation. Args: meta_tag_content: str. The meta tag content to validate. Raises: Exception. Meta tag content is not a string. Exception. Meta tag content is long. """ ...
def require_valid_meta_tag_content(meta_tag_content): """Generic meta tag content validation. Args: meta_tag_content: str. The meta tag content to validate. Raises: Exception. Meta tag content is not a string. Exception. Meta tag content is longer than expected....
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def _check_spark_version_in_range(ver, min_ver, max_ver): if Version(ver) > Version(min_ver): ver = _reset_minor_version(ver) return _check_version_in_range(ver, min_ver, max_ver)
def _check_spark_version_in_range(ver, min_ver, max_ver): parsed_ver = Version(ver) if parsed_ver > Version(min_ver): ver = f"{parsed_ver.major}.{parsed_ver.minor}" return _check_version_in_range(ver, min_ver, max_ver)
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def buildCOLR( colorGlyphs: _ColorGlyphsDict, version: int = 0, glyphMap: Optional[Mapping[str, int]] = None, varStore: Optional[ot.VarStore] = None, ) -> C_O_L_R_.table_C_O_L_R_: """Build COLR table from color layers mapping. Args: colorGlyphs: If version == 0, a map of base glyph name...
def buildCOLR( colorGlyphs: _ColorGlyphsDict, version: int = 0, glyphMap: Optional[Mapping[str, int]] = None, varStore: Optional[ot.VarStore] = None, ) -> C_O_L_R_.table_C_O_L_R_: """Build COLR table from color layers mapping. Args: colorGlyphs: If version == 0, a map of base glyph name...
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def _get_edf_plot(studies: List[Study]) -> "go.Figure": if len(studies) == 0: raise ValueError("No studies were given.") layout = go.Layout( title="EDF Plot", xaxis={"title": "Objective Value"}, yaxis={"title": "Cumulative Probability"}, ) all_trials = list( ite...
def _get_edf_plot(studies: List[Study]) -> "go.Figure": if len(studies) == 0: raise ValueError("No studies were given.") layout = go.Layout( title="EDF Plot", xaxis={"title": "Objective Value"}, yaxis={"title": "Cumulative Probability"}, ) all_trials = list( ite...
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def get_domain_details(client: Client, **args) -> CommandResults: domain = args.get("domain") uri = f"/domain/{domain}" response = client._http_request("GET", uri) md = "" current_dns = response["current_dns"] del response["current_dns"] md = tableToMarkdown(f"Details for {domain}", respons...
def get_domain_details(client: Client, **args) -> CommandResults: domain = args.get("domain") uri = f"/domain/{domain}" response = client._http_request("GET", uri) md = "" current_dns = response["current_dns"] del response["current_dns"] md = tableToMarkdown(f"Details for {domain}", respons...
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def process_search_results(results): """ Transform result representation from the output of the widget to the test framework comparison representation. """ matches = {} for result in results.values(): file, line, col, _ = result filename = osp.basename(file) if filename n...
def process_search_results(results): """ Transform result representation from the output of the widget to the test framework comparison representation. """ matches = {} for result in results.values(): file, line, col, __ = result filename = osp.basename(file) if filename ...
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def get_plain_text(secret: Union[SecretStr, SecretBytes, None, str]) -> Optional[str]: if secret: return secret.get_secret_value() else: return secret
def get_plain_text(secret: Union[SecretStr, SecretBytes, None, str]) -> Optional[str]: try: return secret.get_secret_value() except AttributeError: return secret
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def fetch_openml( name: Optional[str] = None, *, version: Union[str, int] = "active", data_id: Optional[int] = None, data_home: Optional[str] = None, target_column: Optional[Union[str, List]] = "default-target", cache: bool = True, return_X_y: bool = False, as_frame: Union[str, bool]...
def fetch_openml( name: Optional[str] = None, *, version: Union[str, int] = "active", data_id: Optional[int] = None, data_home: Optional[str] = None, target_column: Optional[Union[str, List]] = "default-target", cache: bool = True, return_X_y: bool = False, as_frame: Union[str, bool]...
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def test_rebase_path_traits(): """Check rebase_path_traits.""" spec = _test_spec() a = rebase_path_traits( spec.trait('a'), '/some/path/f1.txt', '/some/path') assert '%s' % a == 'f1.txt' b = rebase_path_traits( spec.trait('b'), ('/some/path/f1.txt', '/some/path/f2.txt'), '/some/pat...
def test_rebase_path_traits(): """Check rebase_path_traits.""" spec = _test_spec() a = rebase_path_traits( spec.trait('a'), '/some/path/f1.txt', '/some/path') assert a == Path('f1.txt') b = rebase_path_traits( spec.trait('b'), ('/some/path/f1.txt', '/some/path/f2.txt'), '/some/path...
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def get_request_args(params): limit = request.args.get('n', None) offset = request.args.get('s', None) out_format = request.args.get('v', None) query = request.args.get('q', None) if limit is None: limit = try_parse_integer(params.get('list_size'), CTX_LIMIT_ERR_MSG) else: limi...
def get_request_args(params): limit = request.args.get('n', None) offset = request.args.get('s', None) out_format = request.args.get('v', params.get('format')) query = request.args.get('q', None) if limit is None: limit = try_parse_integer(params.get('list_size'), CTX_LIMIT_ERR_MSG) el...
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def kahypar_cut( num_fragments: int, adjacent_nodes: List[int], edge_splits: List[int], imbalance: int = None, edge_weights: List[Union[int, float]] = None, node_weights: List[Union[int, float]] = None, block_weights: List[Union[int, float]] = None, edges: Iterable[Any] = None, seed:...
def kahypar_cut( num_fragments: int, adjacent_nodes: List[int], edge_splits: List[int], imbalance: int = None, edge_weights: List[Union[int, float]] = None, node_weights: List[Union[int, float]] = None, fragment_weights: List[Union[int, float]] = None, edges: Iterable[Any] = None, se...
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def mantis_get_issue_by_id_command(client, args): """ Returns Hello {somename} Args: client (Client): Mantis client. args (dict): all command arguments. Returns: Mantis """ _id = args.get('id') resp = client.get_issue(_id).get('issues')[0] issues = create_output...
def mantis_get_issue_by_id_command(client, args): """ Returns Hello {somename} Args: client (Client): Mantis client. args (dict): all command arguments. Returns: Mantis """ _id = args.get('id') resp = client.get_issue(_id).get('issues')[0] issues = create_output...
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def results_return(command, thingtoreturn): for item in thingtoreturn: description = '' ip_reputation = { 'indicator': item['Address'], } try: if item['Malicious']['Vendor']: score = Common.DBotScore.BAD description = ip_reputat...
def results_return(command, thingtoreturn): for item in thingtoreturn: description = '' ip_reputation = { 'indicator': item['Address'], } try: if item['Malicious']['Vendor']: score = Common.DBotScore.BAD description = ip_reputat...
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def parse_arguments(): parser = argparse.ArgumentParser( prog="spotdl", description=help_notice, formatter_class=argparse.RawDescriptionHelpFormatter, ) parser.add_argument( "query", type=str, nargs="+", help="URL/String for a song/album/playlist/artist" ) parser.add_...
def parse_arguments(): parser = argparse.ArgumentParser( prog="spotdl", description=help_notice, formatter_class=argparse.RawDescriptionHelpFormatter, ) parser.add_argument( "query", type=str, nargs="+", help="URL/String for a song/album/playlist/artist" ) parser.add_...
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def decompose_clifford_tableau_to_operations( qubits: List['cirq.Qid'], clifford_tableau: qis.CliffordTableau ) -> List[ops.Operation]: """Decompose an n-qubit Clifford Tableau into a list of one/two qubit operations. Args: qubits: The list of qubits being operated on. clifford_tableau: The...
def decompose_clifford_tableau_to_operations( qubits: List['cirq.Qid'], clifford_tableau: qis.CliffordTableau ) -> List[ops.Operation]: """Decompose an n-qubit Clifford Tableau into a list of one/two qubit operations. Args: qubits: The list of qubits being operated on. clifford_tableau: The...
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def panda_state_function(q: Queue): pm = messaging.PubMaster(['pandaState']) while 1: if not q.empty(): if q.get() == "quit": break dat = messaging.new_message('pandaState') dat.valid = True dat.pandaState = { 'ignitionLine': True, 'pandaType': "blackPanda", 'control...
def panda_state_function(q: Queue): pm = messaging.PubMaster(['pandaState']) while not exit_event.is_set(): dat = messaging.new_message('pandaState') dat.valid = True dat.pandaState = { 'ignitionLine': True, 'pandaType': "blackPanda", 'controlsAllowed': True, 'safetyModel': 'hon...
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def _munge_featureset_name(featureset): """ Joins features in ``featureset`` by '+' if ``featureset`` is not a string. Otherwise, returns ``featureset``. Parameters ---------- featureset : SKLL.FeatureSet A SKLL ``FeatureSet`` object. Returns ------- res : str ``fea...
def _munge_featureset_name(featureset): """ Joins features in ``featureset`` by '+' if ``featureset`` is not a string. Otherwise, returns ``featureset``. Parameters ---------- featureset : skll.data.FeatureSet A SKLL ``FeatureSet`` object. Returns ------- res : str ...
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def rec_iter( filenames: List[str], sensor: Optional[str], ignore_rules: Dict[str, Dict[str, List[Tuple[int, int]]]], ) -> Generator[Record, None, None]: ignorenets = ignore_rules.get("IGNORENETS", {}) neverignore = ignore_rules.get("NEVERIGNORE", {}) for fname in filenames: with P0fFile...
def rec_iter( filenames: List[str], sensor: Optional[str], ignore_rules: Dict[str, Dict[str, List[Tuple[int, int]]]], ) -> Generator[Record, None, None]: ignorenets = ignore_rules.get("IGNORENETS", {}) neverignore = ignore_rules.get("NEVERIGNORE", {}) for fname in filenames: with P0fFile...
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def get_parameters(): parser = argparse.ArgumentParser(description='This script is curating dataset data_axondeepseg_tem to BIDS') # Define input path parser.add_argument("-d", "--data", help="Path to folder containing the dataset to be curated", required=True...
def get_parameters(): parser = argparse.ArgumentParser(description='This script is curating the demo dataset to BIDS') # Define input path parser.add_argument("-d", "--data", help="Path to folder containing the dataset to be curated", required=True) # Defi...
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def implements(obj: "Interface", interface: Tuple[type, type]) -> bool: """Return whether the give object (maybe an instance or class) implements the interface. """ kimplements = getattr(obj, "__implements__", ()) if not isinstance(kimplements, (list, tuple)): kimplements = (kimplements,) ...
def implements(obj: "Interface", interface: Tuple[type, type]) -> bool: """Return whether the give object (maybe an instance or class) implements the interface. """ kimplements = getattr(obj, "__implements__", ()) if not isinstance(kimplements, (list, tuple)): kimplements = (kimplements,) ...
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def qnode_spectrum(qnode, encoding_args=None, argnum=None, decimals=8, validation_kwargs=None): r"""Compute the frequency spectrum of the Fourier representation of quantum circuits, including classical preprocessing. The circuit must only use gates as input-encoding gates that can be decomposed into si...
def qnode_spectrum(qnode, encoding_args=None, argnum=None, decimals=8, validation_kwargs=None): r"""Compute the frequency spectrum of the Fourier representation of quantum circuits, including classical preprocessing. The circuit must only use gates as input-encoding gates that can be decomposed into si...
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def voronoi_partition_pts(points, outline, no_multipolygons=False): """ Compute the polygons of a voronoi partition of `points` within the polygon `outline`. Taken from https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py Attributes ---------- points : Nx2 - ndarray[dtype=float...
def voronoi_partition_pts(points, outline, no_multipolygons=False): """ Compute the polygons of a voronoi partition of `points` within the polygon `outline`. Taken from https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py Attributes ---------- points : Nx2 - ndarray[dtype=float...
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def email_command(client, args, email_suspicious_score_threshold, email_malicious_score_threshold, reliability): emails = argToList(args.get("email"), ",") results = [] for email in emails: result = client.get_email_reputation(email) result['address'] = email human_readable = tableT...
def email_command(client, args, email_suspicious_score_threshold, email_malicious_score_threshold, reliability): emails = argToList(args.get("email"), ",") results = [] for email in emails: result = client.get_email_reputation(email) result['address'] = email human_readable = tableT...
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def nuclear_attraction(la, lb, ra, rb, alpha, beta, r): r"""Compute nuclear attraction integral between primitive Gaussian functions. The nuclear attraction integral between two Gaussian functions denoted by :math:`a` and :math:`b` can be computed as [`Helgaker (1995) p820 <https://www.worldscientific....
def nuclear_attraction(la, lb, ra, rb, alpha, beta, r): r"""Compute nuclear attraction integral between primitive Gaussian functions. The nuclear attraction integral between two Gaussian functions denoted by :math:`a` and :math:`b` can be computed as [`Helgaker (1995) p820 <https://www.worldscientific....
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def language_code_to_iso_3166(language): """Turn a language name (en-us) into an ISO 3166 format (en-US).""" language, _, country = language.lower().partition('-') if country: return language + '-' + country.upper() return language
def language_code_to_iso_3166(language): """Turn a language name (en-us) into an ISO 3166 format (en-US).""" language, _, country = language.lower().partition('-') if country: return f'{language}-{country.upper()}' return language
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def pytest_collect_file( fspath: Path, path: py.path.local, parent: Collector, ) -> Optional[Union["DoctestModule", "DoctestTextfile"]]: config = parent.config if fspath.suffix == ".py": if config.option.doctestmodules and not _is_setup_py(fspath): mod: DoctestModule = DoctestModule.from...
def pytest_collect_file( fspath: Path, parent: Collector ) -> Optional[Union["DoctestModule", "DoctestTextfile"]]: config = parent.config if fspath.suffix == ".py": if config.option.doctestmodules and not _is_setup_py(fspath): mod: DoctestModule = DoctestModule.from_parent(parent, fspath...
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def test_fsspec_url(): fsspec = pytest.importorskip("fsspec") import fsspec.implementations.memory class MyMemoryFileSystem(fsspec.implementations.memory.MemoryFileSystem): # Simple fsspec filesystem that adds a required keyword. # Attempting to use this filesystem without the keyword will ...
def test_fsspec_url(): fsspec = pytest.importorskip("fsspec") import fsspec.implementations.memory class MyMemoryFileSystem(fsspec.implementations.memory.MemoryFileSystem): # Simple fsspec filesystem that adds a required keyword. # Attempting to use this filesystem without the keyword will ...