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def get_client(client_id): """Load the client. Needed for grant_type client_credentials. Add support for OAuth client_credentials access type, with user inactivation support. :param client_id: The client ID. :returns: The client instance or ``None``. """ client = Client.query.get(client_id) if client and client.user.active: return client
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def authenticate(self, request): """ Attempt to authenticate the request. :param request: django.http.Request instance :return bool: True if success else raises HTTP_401 """ authenticators = self._meta.authenticators if request.method == 'OPTIONS' and ADREST_ALLOW_OPTIONS: self.auth = AnonimousAuthenticator(self) return True error_message = "Authorization required." for authenticator in authenticators: auth = authenticator(self) try: if not auth.authenticate(request): raise AssertionError(error_message) self.auth = auth auth.configure(request) return True except AssertionError, e: error_message = str(e) raise HttpError(error_message, status=status.HTTP_401_UNAUTHORIZED)
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def integer(token): """ Convert numeric strings into integers. @type token: str @param token: String to parse. @rtype: int @return: Parsed integer value. """ token = token.strip() neg = False if token.startswith(compat.b('-')): token = token[1:] neg = True if token.startswith(compat.b('0x')): result = int(token, 16) # hexadecimal elif token.startswith(compat.b('0b')): result = int(token[2:], 2) # binary elif token.startswith(compat.b('0o')): result = int(token, 8) # octal else: try: result = int(token) # decimal except ValueError: result = int(token, 16) # hexadecimal (no "0x" prefix) if neg: result = -result return result
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def readfp(self, fp, filename=None): """Like read() but the argument must be a file-like object. The `fp' argument must have a `readline' method. Optional second argument is the `filename', which if not given, is taken from fp.name. If fp has no `name' attribute, `<???>' is used. """ if filename is None: try: filename = fp.name except AttributeError: filename = '<???>' self._read(fp, filename)
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def write_inp(self): """ Returns the material definition as a string in Abaqus INP format. """ template = self.get_template() plastic_table = self.get_plastic_table() return template.substitute({ "class": self.__class__.__name__, "label": self.label, "young_modulus": self.young_modulus, "poisson_ratio": self.poisson_ratio, "plastic_table": (self.get_plastic_table()[["stress", "plastic_strain"]] .to_csv(header = False, index = False, sep = ",").strip())}).strip()
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def match_metric(regex): ''' Display the current values of all metrics whose names match the given regular expression. .. versionadded:: 2016.11.0 .. code-block:: bash salt '*' trafficserver.match_metric regex ''' if _TRAFFICCTL: cmd = _traffic_ctl('metric', 'match', regex) else: cmd = _traffic_ctl('-m', regex) return _subprocess(cmd)
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def check_messages(*messages: str) -> Callable: """decorator to store messages that are handled by a checker method""" def store_messages(func): func.checks_msgs = messages return func return store_messages
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def _parse_size(self, size, has_time=False): """Parse size inputs""" if has_time: size = size or 4 else: size = size or 10 if isinstance(size, str): size = {'column': size} if isinstance(size, dict): if 'column' not in size: raise ValueError("`size` must include a 'column' key/value") if has_time: raise ValueError("When time is specified, size can " "only be a fixed size") old_size = size # Default size range, bins, and bin_method size = { 'range': [5, 25], 'bins': 5, 'bin_method': BinMethod.quantiles, } # Assign default range and update if min/max given old_size['range'] = old_size.get('range', size['range']) if 'min' in old_size: old_size['range'][0] = old_size['min'] old_size.pop('min') if 'max' in old_size: old_size['range'][1] = old_size['max'] old_size.pop('max') # Update all the keys in size if they exist in old_size size.update(old_size) self.style_cols[size['column']] = None return size
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def dif(a, b): """ copy from http://stackoverflow.com/a/8545526 """ return [i for i in range(len(a)) if a[i] != b[i]]
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def cql_encode_datetime(self, val): """ Converts a :class:`datetime.datetime` object to a (string) integer timestamp with millisecond precision. """ timestamp = calendar.timegm(val.utctimetuple()) return str(long(timestamp * 1e3 + getattr(val, 'microsecond', 0) / 1e3))
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def set_visa_attribute(self, name, state): """Sets the state of an attribute. :param name: Attribute for which the state is to be modified. (Attributes.*) :param state: The state of the attribute to be set for the specified object. :return: return value of the library call. :rtype: :class:`pyvisa.constants.StatusCode` """ return self.visalib.set_attribute(self.session, name, state)
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def unprotected_ids(doc, options): u"""Returns a list of unprotected IDs within the document doc.""" identifiedElements = findElementsWithId(doc.documentElement) if not (options.protect_ids_noninkscape or options.protect_ids_list or options.protect_ids_prefix): return identifiedElements if options.protect_ids_list: protect_ids_list = options.protect_ids_list.split(",") if options.protect_ids_prefix: protect_ids_prefixes = options.protect_ids_prefix.split(",") for id in list(identifiedElements): protected = False if options.protect_ids_noninkscape and not id[-1].isdigit(): protected = True if options.protect_ids_list and id in protect_ids_list: protected = True if options.protect_ids_prefix: for prefix in protect_ids_prefixes: if id.startswith(prefix): protected = True if protected: del identifiedElements[id] return identifiedElements
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def api_key(self, api_key): """ Sets the api_key of this GlobalSignCredentials. Unique ID for API client (provided by GlobalSign). :param api_key: The api_key of this GlobalSignCredentials. :type: str """ if api_key is None: raise ValueError("Invalid value for `api_key`, must not be `None`") if api_key is not None and len(api_key) > 1000: raise ValueError("Invalid value for `api_key`, length must be less than or equal to `1000`") self._api_key = api_key
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def licenses( ctx, summary=False, from_classifier=False, with_system=False, with_authors=False, with_urls=False, ): """ List dependency licenses. """ licenses_command = "pip-licenses --order=license" report.info(ctx, "package.licenses", "listing licenses of package dependencies") if summary: report.debug(ctx, "package.licenses", "summarizing licenses") licenses_command += " --summary" if from_classifier: report.debug(ctx, "package.licenses", "reporting from classifiers") licenses_command += " --from-classifier" if with_system: report.debug(ctx, "package.licenses", "including system packages") licenses_command += " --with-system" if with_authors: report.debug(ctx, "package.licenses", "including package authors") licenses_command += " --with-authors" if with_urls: report.debug(ctx, "package.licenses", "including package urls") licenses_command += " --with-urls" ctx.run(licenses_command)
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async def wasAdded(self, node): ''' Fire the onAdd() callbacks for node creation. ''' for func in self.onadds: try: retn = func(node) if s_coro.iscoro(retn): await retn except asyncio.CancelledError: raise except Exception: logger.exception('error on onadd for %s' % (self.name,)) await node.snap.core.triggers.runNodeAdd(node)
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def list_function_versions(FunctionName, region=None, key=None, keyid=None, profile=None): ''' List the versions available for the given function. Returns list of function versions CLI Example: .. code-block:: yaml versions: - {...} - {...} ''' try: conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) vers = [] for ret in __utils__['boto3.paged_call'](conn.list_versions_by_function, FunctionName=FunctionName): vers.extend(ret['Versions']) if not bool(vers): log.warning('No versions found') return {'Versions': vers} except ClientError as e: return {'error': __utils__['boto3.get_error'](e)}
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def make_dict_unstructure_fn(cl, converter, **kwargs): # type: (Type[T], Converter) -> Callable[[T], Dict[str, Any]] """Generate a specialized dict unstructuring function for a class.""" cl_name = cl.__name__ fn_name = "unstructure_" + cl_name globs = {"__c_u": converter.unstructure} lines = [] post_lines = [] attrs = cl.__attrs_attrs__ lines.append("def {}(i):".format(fn_name)) lines.append(" res = {") for a in attrs: attr_name = a.name override = kwargs.pop(attr_name, _neutral) d = a.default if a.type is None: # No type annotation, doing runtime dispatch. if d is not attr.NOTHING and override.omit_if_default: def_name = "__cattr_def_{}".format(attr_name) if isinstance(d, attr.Factory): globs[def_name] = d.factory if d.takes_self: post_lines.append( " if i.{name} != {def_name}(i):".format( name=attr_name, def_name=def_name ) ) else: post_lines.append( " if i.{name} != {def_name}():".format( name=attr_name, def_name=def_name ) ) post_lines.append( " res['{name}'] = i.{name}".format( name=attr_name ) ) else: globs[def_name] = d post_lines.append( " if i.{name} != {def_name}:".format( name=attr_name, def_name=def_name ) ) post_lines.append( " res['{name}'] = __c_u(i.{name})".format( name=attr_name ) ) else: # No default or no override. lines.append( " '{name}': __c_u(i.{name}),".format(name=attr_name) ) else: # Do the dispatch here and now. type = a.type conv_function = converter._unstructure_func.dispatch(type) if d is not attr.NOTHING and override.omit_if_default: def_name = "__cattr_def_{}".format(attr_name) if isinstance(d, attr.Factory): # The default is computed every time. globs[def_name] = d.factory if d.takes_self: post_lines.append( " if i.{name} != {def_name}(i):".format( name=attr_name, def_name=def_name ) ) else: post_lines.append( " if i.{name} != {def_name}():".format( name=attr_name, def_name=def_name ) ) if conv_function == converter._unstructure_identity: # Special case this, avoid a function call. post_lines.append( " res['{name}'] = i.{name}".format( name=attr_name ) ) else: unstruct_fn_name = "__cattr_unstruct_{}".format( attr_name ) globs[unstruct_fn_name] = conv_function post_lines.append( " res['{name}'] = {fn}(i.{name}),".format( name=attr_name, fn=unstruct_fn_name ) ) else: # Default is not a factory, but a constant. globs[def_name] = d post_lines.append( " if i.{name} != {def_name}:".format( name=attr_name, def_name=def_name ) ) if conv_function == converter._unstructure_identity: post_lines.append( " res['{name}'] = i.{name}".format( name=attr_name ) ) else: unstruct_fn_name = "__cattr_unstruct_{}".format( attr_name ) globs[unstruct_fn_name] = conv_function post_lines.append( " res['{name}'] = {fn}(i.{name})".format( name=attr_name, fn=unstruct_fn_name ) ) else: # No omitting of defaults. if conv_function == converter._unstructure_identity: # Special case this, avoid a function call. lines.append( " '{name}': i.{name},".format(name=attr_name) ) else: unstruct_fn_name = "__cattr_unstruct_{}".format(attr_name) globs[unstruct_fn_name] = conv_function lines.append( " '{name}': {fn}(i.{name}),".format( name=attr_name, fn=unstruct_fn_name ) ) lines.append(" }") total_lines = lines + post_lines + [" return res"] eval(compile("\n".join(total_lines), "", "exec"), globs) fn = globs[fn_name] return fn
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def _do_cb(self, cb, error_cb, *args, **kw): """ Called internally by callback(). Does cb and error_cb selection. """ try: res = self.work(*args, **kw) except Exception as e: if error_cb is None: show_err() elif error_cb: error_cb(e) else: # Success, let's call away! cb(res)
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def assign_operation_ids(spec, operids): """ used to assign caller provided operationId values into a spec """ empty_dict = {} for path_name, path_data in six.iteritems(spec['paths']): for method, method_data in six.iteritems(path_data): oper_id = operids.get(path_name, empty_dict).get(method) if oper_id: method_data['operationId'] = oper_id
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def _get_int_removals_helper(self, spec_amts_oxi, oxid_el, oxid_els, numa): """ This is a helper method for get_removals_int_oxid! Args: spec_amts_oxi - a dict of species to their amounts in the structure oxid_el - the element to oxidize oxid_els - the full list of elements that might be oxidized numa - a running set of numbers of A cation at integer oxidation steps Returns: a set of numbers A; steps for for oxidizing oxid_el first, then the other oxid_els in this list """ # If Mn is the oxid_el, we have a mixture of Mn2+, Mn3+, determine the minimum oxidation state for Mn #this is the state we want to oxidize! oxid_old = min([spec.oxi_state for spec in spec_amts_oxi if spec.symbol == oxid_el.symbol]) oxid_new = math.floor(oxid_old + 1) #if this is not a valid solution, break out of here and don't add anything to the list if oxid_new > oxid_el.max_oxidation_state: return numa #update the spec_amts_oxi map to reflect that the oxidation took place spec_old = Specie(oxid_el.symbol, oxid_old) spec_new = Specie(oxid_el.symbol, oxid_new) specamt = spec_amts_oxi[spec_old] spec_amts_oxi = {sp: amt for sp, amt in spec_amts_oxi.items() if sp != spec_old} spec_amts_oxi[spec_new] = specamt spec_amts_oxi = Composition(spec_amts_oxi) #determine the amount of cation A in the structure needed for charge balance and add it to the list oxi_noA = sum([spec.oxi_state * spec_amts_oxi[spec] for spec in spec_amts_oxi if spec.symbol not in self.cation.symbol]) a = max(0, -oxi_noA / self.cation_charge) numa = numa.union({a}) #recursively try the other oxidation states if a == 0: return numa else: for oxid_el in oxid_els: numa = numa.union( self._get_int_removals_helper(spec_amts_oxi.copy(), oxid_el, oxid_els, numa)) return numa
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def get_measurement_metadata(self, fields, ids=None, noneval=nan, output_format='DataFrame'): """ Get the metadata fields of specified measurements (all if None given). Parameters ---------- fields : str | iterable of str Names of metadata fields to be returned. ids : hashable| iterable of hashables | None Keys of measurements for which metadata will be returned. If None is given return metadata of all measurements. noneval : obj Value returned if applyto is 'data' but no data is available. output_format : 'DataFrame' | 'dict' 'DataFrame' : return DataFrame, 'dict' : return dictionary. Returns ------- Measurement metadata in specified output_format. """ fields = to_list(fields) func = lambda x: x.get_meta_fields(fields) meta_d = self.apply(func, ids=ids, applyto='measurement', noneval=noneval, output_format='dict') if output_format is 'dict': return meta_d elif output_format is 'DataFrame': from pandas import DataFrame as DF meta_df = DF(meta_d, index=fields) return meta_df else: msg = ("The output_format must be either 'dict' or 'DataFrame'. " + "Encountered unsupported value %s." % repr(output_format)) raise Exception(msg)
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def serialize(expr): """Serialize input expr into a parsable value. :rtype: str""" result = None if isinstance(expr, string_types): result = expr elif expr is not None: result = '=py:{0}'.format(expr) return result
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def open_allowed(self) -> bool: """Door can be opened unattended.""" return next( attr['Value'] for attr in self._device_json.get('Attributes', []) if attr.get('AttributeDisplayName') == 'isunattendedopenallowed')\ == "1"
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def start(self): """ Launch the process and start processing the DAG. """ self._process = DagFileProcessor._launch_process( self._result_queue, self.file_path, self._pickle_dags, self._dag_id_white_list, "DagFileProcessor{}".format(self._instance_id), self._zombies) self._start_time = timezone.utcnow()
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33.666667
10.833333
def get_inclusion_states(self, transactions, tips): # type: (Iterable[TransactionHash], Iterable[TransactionHash]) -> dict """ Get the inclusion states of a set of transactions. This is for determining if a transaction was accepted and confirmed by the network or not. You can search for multiple tips (and thus, milestones) to get past inclusion states of transactions. :param transactions: List of transactions you want to get the inclusion state for. :param tips: List of tips (including milestones) you want to search for the inclusion state. References: - https://iota.readme.io/docs/getinclusionstates """ return core.GetInclusionStatesCommand(self.adapter)( transactions=transactions, tips=tips, )
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35.875
22.958333
def _logfile_sigterm_handler(*_): # type: (...) -> None """Handle exit signals and write out a log file. Raises: SystemExit: Contains the signal as the return code. """ logging.error('Received SIGTERM.') write_logfile() print('Received signal. Please see the log file for more information.', file=sys.stderr) sys.exit(signal)
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30.416667
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def p_call_expr(self, p): """call_expr : member_expr arguments | call_expr arguments | call_expr LBRACKET expr RBRACKET | call_expr PERIOD identifier """ if len(p) == 3: p[0] = ast.FunctionCall(p[1], p[2]) elif len(p) == 4: p[0] = ast.DotAccessor(p[1], p[3]) else: p[0] = ast.BracketAccessor(p[1], p[3])
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35.916667
10.333333
def create_signature(secret, value, digestmod='sha256', encoding='utf-8'): """ Create HMAC Signature from secret for value. """ if isinstance(secret, str): secret = secret.encode(encoding) if isinstance(value, str): value = value.encode(encoding) if isinstance(digestmod, str): digestmod = getattr(hashlib, digestmod, hashlib.sha1) hm = hmac.new(secret, digestmod=digestmod) hm.update(value) return hm.hexdigest()
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32.5
17.357143
def snapshot(self, mode): ''' Take a snapshot of the system. ''' self._init_env() self._save_cfg_packages(self._get_changed_cfg_pkgs(self._get_cfg_pkgs())) self._save_payload(*self._scan_payload())
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29.875
22.625
def make_from_catalogue(cls, catalogue, spacing, dilate): ''' Defines the grid on the basis of the catalogue ''' new = cls() cat_bbox = get_catalogue_bounding_polygon(catalogue) if dilate > 0: cat_bbox = cat_bbox.dilate(dilate) # Define Grid spacing new.update({'xmin': np.min(cat_bbox.lons), 'xmax': np.max(cat_bbox.lons), 'xspc': spacing, 'ymin': np.min(cat_bbox.lats), 'ymax': np.max(cat_bbox.lats), 'yspc': spacing, 'zmin': 0., 'zmax': np.max(catalogue.data['depth']), 'zspc': np.max(catalogue.data['depth'])}) if new['zmin'] == new['zmax'] == new['zspc'] == 0: new['zmax'] = new['zspc'] = 1 return new
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def digital_write(self, pin, value): """ Set the specified pin to the specified value. :param pin: pin number :param value: pin value :return: No return value """ # The command value is not a fixed value, but needs to be calculated using the # pin's port number # # port = pin // 8 calculated_command = self._command_handler.DIGITAL_MESSAGE + port mask = 1 << (pin % 8) # Calculate the value for the pin's position in the port mask if value == 1: self.digital_output_port_pins[port] |= mask else: self.digital_output_port_pins[port] &= ~mask # Assemble the command command = (calculated_command, self.digital_output_port_pins[port] & 0x7f, (self.digital_output_port_pins[port] >> 7) & 0x7f) self._command_handler.send_command(command)
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def p_notminus_assignment(self, t): '''notminus_assignment : IDENT EQ NOTMINUS''' self.accu.add(Term('obs_vlabel', [self.name,"gen(\""+t[1]+"\")","notMinus"]))
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def get_df(self, data_file): """ 读取历史财务数据文件,并返回pandas结果 , 类似gpcw20171231.zip格式,具体字段含义参考 https://github.com/rainx/pytdx/issues/133 :param data_file: 数据文件地址, 数据文件类型可以为 .zip 文件,也可以为解压后的 .dat :return: pandas DataFrame格式的历史财务数据 """ crawler = QAHistoryFinancialCrawler() with open(data_file, 'rb') as df: data = crawler.parse(download_file=df) return crawler.to_df(data)
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def skos_related(rdf): """Make sure that skos:related is stated in both directions (S23).""" for s, o in rdf.subject_objects(SKOS.related): rdf.add((o, SKOS.related, s))
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def set_xy_labels(units, kpc_per_arcsec, xlabelsize, ylabelsize, xyticksize): """Set the x and y labels of the figure, and set the fontsize of those labels. The x and y labels are always the distance scales, thus the labels are either arc-seconds or kpc and depend on the \ units the figure is plotted in. Parameters ----------- units : str The units of the y / x axis of the plots, in arc-seconds ('arcsec') or kiloparsecs ('kpc'). kpc_per_arcsec : float The conversion factor between arc-seconds and kiloparsecs, required to plot the units in kpc. xlabelsize : int The fontsize of the x axes label. ylabelsize : int The fontsize of the y axes label. xyticksize : int The font size of the x and y ticks on the figure axes. """ if units in 'arcsec' or kpc_per_arcsec is None: plt.xlabel('x (arcsec)', fontsize=xlabelsize) plt.ylabel('y (arcsec)', fontsize=ylabelsize) elif units in 'kpc': plt.xlabel('x (kpc)', fontsize=xlabelsize) plt.ylabel('y (kpc)', fontsize=ylabelsize) else: raise exc.PlottingException('The units supplied to the plotted are not a valid string (must be pixels | ' 'arcsec | kpc)') plt.tick_params(labelsize=xyticksize)
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def _add_or_remove_flag(self, flag, add): """ Add the given `flag` if `add` is True, remove it otherwise. """ meth = self.add_flag if add else self.remove_flag meth(flag)
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def prepare_destruction(self): """Prepares the model for destruction Unregister itself as observer from the state machine and the root state """ if self.state_machine is None: logger.verbose("Multiple calls of prepare destruction for {0}".format(self)) self.destruction_signal.emit() if self.history is not None: self.history.prepare_destruction() if self.auto_backup is not None: self.auto_backup.prepare_destruction() try: self.unregister_observer(self) self.root_state.unregister_observer(self) except KeyError: # Might happen if the observer was already unregistered pass with self.state_machine.modification_lock(): self.root_state.prepare_destruction() self.root_state = None self.state_machine = None super(StateMachineModel, self).prepare_destruction()
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def errata_applicability(self, synchronous=True, **kwargs): """Force regenerate errata applicability :param synchronous: What should happen if the server returns an HTTP 202 (accepted) status code? Wait for the task to complete if ``True``. Immediately return the server's response otherwise. :param kwargs: Arguments to pass to requests. :returns: The server's response, with all content decoded. :raises: ``requests.exceptions.HTTPError`` If the server responds with an HTTP 4XX or 5XX message. """ kwargs = kwargs.copy() # shadow the passed-in kwargs kwargs.update(self._server_config.get_client_kwargs()) response = client.put(self.path('errata/applicability'), **kwargs) return _handle_response(response, self._server_config, synchronous)
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def get_xml_attr(source, name, path=None): """Get the XML attribute with name from source. If path is not Mone, it will instead get the XML attribute with name from the child indicated by path. """ if path is None: return source.attrib[name] else: return get_xml_attr(get_xml_child(source, path), name)
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def case(*, to, **kwargs): """Converts an identifier from one case type to another. An identifier is an ASCII string consisting of letters, digits and underscores, not starting with a digit. The supported case types are camelCase, PascalCase, snake_case, and CONSTANT_CASE, identified as camel, pascal, snake, and constant. The input identifier is given as a keyword argument with one of these names, and the output type is given as a string in the `to` keyword argument. If a given string does not conform to the specified case type (such as underscores in camel or pascal case strings, or double__underscores in general), the result may not be as desired, although things like snaKe_casE or CONStaNT_CASe will generally work.""" if len(kwargs) != 1: raise ValueError("expect exactly one source string argument") [(typ, string)] = kwargs.items() types = {'pascal', 'camel', 'snake', 'constant'} if typ not in types: raise ValueError(f"source string keyword must be one of {types}") if to not in types: raise ValueError(f"\"to\" argument must be one of {types}") def pascal_iter(string): yield from (m.group(0) for m in re.finditer(r'[A-Z][a-z0-9]*|[a-z0-9]+', string)) def snake_iter(string): yield from (m.group(2) for m in re.finditer(r'(^|_)([A-Za-z0-9]+)', string)) inputs = { 'pascal': pascal_iter, 'camel': pascal_iter, 'snake': snake_iter, 'constant': snake_iter, } def out_fun(sep, case=None, case_fst=None): if case is None: case = lambda x: x if case_fst is None: case_fst = case return lambda tokens: sep.join(case_fst(token) if i == 0 else case(token) for i, token in enumerate(tokens)) outputs = { 'pascal': out_fun('', str.capitalize), 'camel': out_fun('', str.capitalize, str.lower), 'snake': out_fun('_', str.lower), 'constant': out_fun('_', str.upper), } tokens = inputs[typ](string) return outputs[to](tokens)
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def delete_serv_obj(self, tenant_id): """Creates and stores the service object associated with a tenant. """ self.del_obj(tenant_id, self.service_attr[tenant_id]) del self.service_attr[tenant_id]
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def token_getter(remote, token=''): """Retrieve OAuth access token. Used by flask-oauthlib to get the access token when making requests. :param remote: The remote application. :param token: Type of token to get. Data passed from ``oauth.request()`` to identify which token to retrieve. (Default: ``''``) :returns: The token. """ session_key = token_session_key(remote.name) if session_key not in session and current_user.is_authenticated: # Fetch key from token store if user is authenticated, and the key # isn't already cached in the session. remote_token = RemoteToken.get( current_user.get_id(), remote.consumer_key, token_type=token, ) if remote_token is None: return None # Store token and secret in session session[session_key] = remote_token.token() return session.get(session_key, None)
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def parse(filename=""): "Open, read and eval the resource from the source file" # use the provided resource file: s = open(filename).read() ##s.decode("latin1").encode("utf8") import datetime, decimal rsrc = eval(s) return rsrc
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def last(self): """ Returns the last batch for the batched sequence. :rtype: :class:`Batch` instance. """ start = max(self.number - 1, 0) * self.size return Batch(start, self.size, self.total_size)
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def _set_tieBreaking(self, v, load=False): """ Setter method for tieBreaking, mapped from YANG variable /brocade_mpls_rpc/show_mpls_te_path/input/tieBreaking (tie-breaking) If this variable is read-only (config: false) in the source YANG file, then _set_tieBreaking is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_tieBreaking() directly. YANG Description: Tie breaking mode for CSPF when multiple paths to destination exists """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'most-fill': {'value': 2}, u'random': {'value': 0}, u'least-fill': {'value': 1}},), is_leaf=True, yang_name="tieBreaking", rest_name="tieBreaking", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-mpls', defining_module='brocade-mpls', yang_type='tie-breaking', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """tieBreaking must be of a type compatible with tie-breaking""", 'defined-type': "brocade-mpls:tie-breaking", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'most-fill': {'value': 2}, u'random': {'value': 0}, u'least-fill': {'value': 1}},), is_leaf=True, yang_name="tieBreaking", rest_name="tieBreaking", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, namespace='urn:brocade.com:mgmt:brocade-mpls', defining_module='brocade-mpls', yang_type='tie-breaking', is_config=True)""", }) self.__tieBreaking = t if hasattr(self, '_set'): self._set()
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def rprint(sep='\n', end='\n', file=sys.stdout, flush=False): """A coroutine sink which prints received items stdout Args: sep: Optional separator to be printed between received items. end: Optional terminator to be printed after the last item. file: Optional stream to which to print. flush: Optional flag to force flushing after each item. """ try: first_item = (yield) file.write(str(first_item)) if flush: file.flush() while True: item = (yield) file.write(sep) file.write(str(item)) if flush: file.flush() except GeneratorExit: file.write(end) if flush: file.flush()
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30.708333
17.666667
def QA_SU_save_stock_transaction( client=DATABASE, ui_log=None, ui_progress=None ): """save stock_transaction Keyword Arguments: client {[type]} -- [description] (default: {DATABASE}) """ stock_list = QA_fetch_get_stock_list().code.unique().tolist() coll = client.stock_transaction coll.create_index('code') err = [] def __saving_work(code): QA_util_log_info( '##JOB11 Now Saving STOCK_TRANSACTION ==== {}'.format(str(code)), ui_log=ui_log ) try: coll.insert_many( QA_util_to_json_from_pandas( # 🛠todo str(stock_list[code]) 参数不对? QA_fetch_get_stock_transaction( str(code), '1990-01-01', str(now_time())[0:10] ) ) ) except: err.append(str(code)) for i_ in range(len(stock_list)): # __saving_work('000001') QA_util_log_info( 'The {} of Total {}'.format(i_, len(stock_list)), ui_log=ui_log ) strLogProgress = 'DOWNLOAD PROGRESS {} '.format( str(float(i_ / len(stock_list) * 100))[0:4] + '%' ) intLogProgress = int(float(i_ / len(stock_list) * 10000.0)) QA_util_log_info( strLogProgress, ui_log=ui_log, ui_progress=ui_progress, ui_progress_int_value=intLogProgress ) __saving_work(stock_list[i_]) if len(err) < 1: QA_util_log_info('SUCCESS', ui_log=ui_log) else: QA_util_log_info(' ERROR CODE \n ', ui_log=ui_log) QA_util_log_info(err, ui_log=ui_log)
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29.1
18.3
def _parse_shape_list(shape_list, crs): """ Checks if the given list of shapes is in correct format and parses geometry objects :param shape_list: The parameter `shape_list` from class initialization :type shape_list: list(shapely.geometry.multipolygon.MultiPolygon or shapely.geometry.polygon.Polygon) :raises: ValueError """ if not isinstance(shape_list, list): raise ValueError('Splitter must be initialized with a list of shapes') return [AreaSplitter._parse_shape(shape, crs) for shape in shape_list]
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51.363636
26.090909
def get_numeric_value(string_value): """ parses string_value and returns only number-like part """ num_chars = ['.', '+', '-'] number = '' for c in string_value: if c.isdigit() or c in num_chars: number += c return number
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28.555556
10.333333
def get_organisation_information(self, query_params=None): ''' Get information fot this organisation. Returns a dictionary of values. ''' return self.fetch_json( uri_path=self.base_uri, query_params=query_params or {} )
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34.5
20.25
def render(self, ctx=None): ''' Render the current value into a :class:`bitstring.Bits` object :rtype: :class:`bitstring.Bits` :return: the rendered field ''' self._initialize() if ctx is None: ctx = RenderContext() # # if we are called from within render, return a dummy object... # if self in ctx: self._current_rendered = self._in_render_value() else: ctx.push(self) if self.dependency_type == Calculated.VALUE_BASED: self._rendered_field = self._field.render(ctx) self._render() ctx.pop() return self._current_rendered
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31.545455
19.818182
def validate(self): """Validation of configuration to check for required values""" if not self.server.enabled: if self.security.signature_certificate_file is self.security.defaults['signature_certificate_file']: print("ISSUE: If you are not configuring a server, you need to set 'signature_certificate_file'") if self.security.signature_private_key_file is self.security.defaults['signature_private_key_file']: print("ISSUE: If you are not configuring a server, you need to set 'signature_private_key_file'") else: if self.client.enabled: print("ISSUE: Client and server enabled at the same time?") if self.server.protocol is self.server.defaults['protocol']: if self.server.server_certificate_file is self.server.defaults['server_certificate_file'] or \ self.server.server_private_key_file is self.server.defaults['server_private_key_file']: print("ISSUE: 'server_certificate_file' and/or 'server_private_key_file' are not configured and will be auto-generated.") if self.server.certification_authority_certificate_file is self.server.defaults['certification_authority_certificate_file'] or \ self.server.certification_authority_private_key_file is self.server.defaults['certification_authority_private_key_file']: print("ISSUE: 'certification_authority_certificate_file' and/or 'certification_authority_private_key_file' are not configured and will be auto-generated - this is NOT recommended.") if self.server.authentication_script is self.server.defaults['authentication_script']: print("ISSUE: No 'authentication_script' has been provided and all authentication requests will be rejected!") if self.client.enabled: if self.client.server_endpoint is self.client.defaults['server_endpoint']: print("ISSUE: You are running in client mode, but you are using a default server address.") if not self.client.disable_peer_verification is self.client.defaults['disable_peer_verification'] or \ not self.client.disable_host_verification is self.client.defaults['disable_host_verification']: print("ISSUE: Disabling peer/host verification is NOT recommended - AT ALL.") if self.client.username is self.client.defaults['username'] or \ self.client.password is self.client.defaults['password']: print("ISSUE: No username and/or password has been configured for a client.") if self.fscp.contact is self.fscp.defaults['contact']: if not self.server.enabled and not self.client.enabled: print("ISSUE: You have not defined any contact points while you are neither running as server nor client.") ## hostname_resolution_protocol=ipv4/ipv6 ## ipv4_address_prefix_length=9.0.0.1/24 ## ipv6_address_prefix_length=2aa1::1/8 if self.security.authority_certificate_file is self.security.defaults['authority_certificate_file']: print("ISSUE: You need to set 'authority_certificate_file'") if self.tap_adapter.ipv4_address_prefix_length is self.tap_adapter.defaults['ipv4_address_prefix_length']: print("ISSUE: You are using the default network address - make sure you set a different ip for every machine 'ipv4_address_prefix_length'")
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62.303571
49.875
def as_labeller(x, default=label_value, multi_line=True): """ Coerse to labeller function Parameters ---------- x : function | dict Object to coerce default : function | str Default labeller. If it is a string, it should be the name of one the labelling functions provided by plotnine. multi_line : bool Whether to place each variable on a separate line Returns ------- out : function Labelling function """ if x is None: x = default # One of the labelling functions as string with suppress(KeyError, TypeError): x = LABELLERS[x] # x is a labeller with suppress(AttributeError): if x.__name__ == '_labeller': return x def _labeller(label_info): label_info = pd.Series(label_info).astype(str) if callable(x) and x.__name__ in LABELLERS: # labellers in this module return x(label_info) elif hasattr(x, '__contains__'): # dictionary lookup for var in label_info.index: if label_info[var] in x: label_info[var] = x[label_info[var]] return label_info elif callable(x): # generic function for var in label_info.index: label_info[var] = x(label_info[var]) return label_info else: msg = "Could not use '{0}' for labelling." raise PlotnineError(msg.format(x)) return _labeller
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27.574074
15.907407
def str_to_python_object(input_str): """ a conversion that will import a module and class name """ if not input_str: return None if six.PY3 and isinstance(input_str, six.binary_type): input_str = to_str(input_str) if not isinstance(input_str, six.string_types): # gosh, we didn't get a string, we can't convert anything but strings # we're going to assume that what we got is actually what was wanted # as the output return input_str input_str = str_quote_stripper(input_str) if '.' not in input_str and input_str in known_mapping_str_to_type: return known_mapping_str_to_type[input_str] parts = [x.strip() for x in input_str.split('.') if x.strip()] try: try: # first try as a complete module package = __import__(input_str) except ImportError: # it must be a class from a module if len(parts) == 1: # since it has only one part, it must be a class from __main__ parts = ('__main__', input_str) package = __import__('.'.join(parts[:-1]), globals(), locals(), []) obj = package for name in parts[1:]: obj = getattr(obj, name) return obj except AttributeError as x: raise CannotConvertError("%s cannot be found" % input_str) except ImportError as x: raise CannotConvertError(str(x))
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41.411765
15.764706
def has_none_of_selectors(self, selector, *locators, **kwargs): """ Checks if none of the provided selectors are present on the given page or descendants of the current node. If options are provided, the assertion will check that each locator is present with those options as well (other than ``wait``). :: page.has_none_of_selectors("custom", "Tom", "Joe", visible="all") page.has_none_of_selectors("css", "#my_div", "a.not_clicked") It accepts all options that :meth:`find_all` accepts, such as ``text`` and ``visible``. The ``wait`` option applies to all of the selectors as a group, so none of the locators must be present with ``wait`` (defaults to :data:`capybara.default_max_wait_time`) seconds. If the given selector is not a valid selector, the first argument is assumed to be a locator and the default selector will be used. Args: selector (str, optional): The name of the selector to use. Defaults to :data:`capybara.default_selector`. *locators (str): Variable length list of locators. **kwargs: Arbitrary keyword arguments for :class:`SelectorQuery`. """ return self.assert_none_of_selectors(selector, *locators, **kwargs)
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51.56
35.24
def triplify(self, data, parent=None): """ Recursively generate statements from the data supplied. """ if data is None: return if self.is_object: for res in self._triplify_object(data, parent): yield res elif self.is_array: for item in data: for res in self.items.triplify(item, parent): yield res else: # TODO: figure out if I ever want to check for reverse here. type_name = typecast.name(data) obj = typecast.stringify(type_name, data) if obj is not None: obj = obj.strip() yield (parent, self.predicate, obj, type_name)
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37.368421
15.421053
def get_basket_items(request): """ Get all items in the basket """ bid = basket_id(request) return BasketItem.objects.filter(basket_id=bid), bid
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27.333333
7.333333
def _run_job(self): """ Build a bsub argument that will run lsf_runner.py on the directory we've specified. """ args = [] if isinstance(self.output(), list): log_output = os.path.split(self.output()[0].path) else: log_output = os.path.split(self.output().path) args += ["bsub", "-q", self.queue_flag] args += ["-n", str(self.n_cpu_flag)] args += ["-M", str(self.memory_flag)] args += ["-R", "rusage[%s]" % self.resource_flag] args += ["-W", str(self.runtime_flag)] if self.job_name_flag: args += ["-J", str(self.job_name_flag)] args += ["-o", os.path.join(log_output[0], "job.out")] args += ["-e", os.path.join(log_output[0], "job.err")] if self.extra_bsub_args: args += self.extra_bsub_args.split() # Find where the runner file is runner_path = os.path.abspath(lsf_runner.__file__) args += [runner_path] args += [self.tmp_dir] # That should do it. Let the world know what we're doing. LOGGER.info("### LSF SUBMISSION ARGS: %s", " ".join([str(a) for a in args])) # Submit the job run_job_proc = subprocess.Popen( [str(a) for a in args], stdin=subprocess.PIPE, stdout=subprocess.PIPE, cwd=self.tmp_dir) output = run_job_proc.communicate()[0] # ASSUMPTION # The result will be of the format # Job <123> is submitted ot queue <myqueue> # So get the number in those first brackets. # I cannot think of a better workaround that leaves logic on the Task side of things. LOGGER.info("### JOB SUBMISSION OUTPUT: %s", str(output)) self.job_id = int(output.split("<")[1].split(">")[0]) LOGGER.info( "Job %ssubmitted as job %s", self.job_name_flag + ' ', str(self.job_id) ) self._track_job() # If we want to save the job temporaries, then do so # We'll move them to be next to the job output if self.save_job_info: LOGGER.info("Saving up temporary bits") # dest_dir = self.output().path shutil.move(self.tmp_dir, "/".join(log_output[0:-1])) # Now delete the temporaries, if they're there. self._finish()
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def set_resource_value(self, device_id, resource_path, resource_value, fix_path=True, timeout=None): """Set resource value for given resource path, on device. Will block and wait for response to come through. Usage: .. code-block:: python try: v = api.set_resource_value(device, path, value) print("Success, new value:", v) except AsyncError, e: print("Error", e) :param str device_id: The name/id of the device (Required) :param str resource_path: The resource path to update (Required) :param str resource_value: The new value to set for given path :param fix_path: Unused :param timeout: Timeout in seconds :raises: AsyncError :returns: The value of the new resource :rtype: str """ self.ensure_notifications_thread() return self.set_resource_value_async( device_id, resource_path, resource_value ).wait(timeout)
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37.925926
17.925926
def kill_tasks(self, app_id, scale=False, wipe=False, host=None, batch_size=0, batch_delay=0): """Kill all tasks belonging to app. :param str app_id: application ID :param bool scale: if true, scale down the app by the number of tasks killed :param str host: if provided, only terminate tasks on this Mesos slave :param int batch_size: if non-zero, terminate tasks in groups of this size :param int batch_delay: time (in seconds) to wait in between batched kills. If zero, automatically determine :returns: list of killed tasks :rtype: list[:class:`marathon.models.task.MarathonTask`] """ def batch(iterable, size): sourceiter = iter(iterable) while True: batchiter = itertools.islice(sourceiter, size) yield itertools.chain([next(batchiter)], batchiter) if batch_size == 0: # Terminate all at once params = {'scale': scale, 'wipe': wipe} if host: params['host'] = host response = self._do_request( 'DELETE', '/v2/apps/{app_id}/tasks'.format(app_id=app_id), params) # Marathon is inconsistent about what type of object it returns on the multi # task deletion endpoint, depending on the version of Marathon. See: # https://github.com/mesosphere/marathon/blob/06a6f763a75fb6d652b4f1660685ae234bd15387/src/main/scala/mesosphere/marathon/api/v2/AppTasksResource.scala#L88-L95 if "tasks" in response.json(): return self._parse_response(response, MarathonTask, is_list=True, resource_name='tasks') else: return response.json() else: # Terminate in batches tasks = self.list_tasks( app_id, host=host) if host else self.list_tasks(app_id) for tbatch in batch(tasks, batch_size): killed_tasks = [self.kill_task(app_id, t.id, scale=scale, wipe=wipe) for t in tbatch] # Pause until the tasks have been killed to avoid race # conditions killed_task_ids = set(t.id for t in killed_tasks) running_task_ids = killed_task_ids while killed_task_ids.intersection(running_task_ids): time.sleep(1) running_task_ids = set( t.id for t in self.get_app(app_id).tasks) if batch_delay == 0: # Pause until the replacement tasks are healthy desired_instances = self.get_app(app_id).instances running_instances = 0 while running_instances < desired_instances: time.sleep(1) running_instances = sum( t.started_at is None for t in self.get_app(app_id).tasks) else: time.sleep(batch_delay) return tasks
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48.741935
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def wider_bn(layer, start_dim, total_dim, n_add, weighted=True): '''wider batch norm layer. ''' n_dim = get_n_dim(layer) if not weighted: return get_batch_norm_class(n_dim)(layer.num_features + n_add) weights = layer.get_weights() new_weights = [ add_noise(np.ones(n_add, dtype=np.float32), np.array([0, 1])), add_noise(np.zeros(n_add, dtype=np.float32), np.array([0, 1])), add_noise(np.zeros(n_add, dtype=np.float32), np.array([0, 1])), add_noise(np.ones(n_add, dtype=np.float32), np.array([0, 1])), ] student_w = tuple() for weight, new_weight in zip(weights, new_weights): temp_w = weight.copy() temp_w = np.concatenate( (temp_w[:start_dim], new_weight, temp_w[start_dim:total_dim]) ) student_w += (temp_w,) new_layer = get_batch_norm_class(n_dim)(layer.num_features + n_add) new_layer.set_weights(student_w) return new_layer
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36.076923
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def dead(self): """Whether the callback no longer exists. If the callback is maintained via a weak reference, and that weak reference has been collected, this will be true instead of false. """ if not self._weak: return False cb = self._callback() if cb is None: return True return False
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28.615385
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def get_status(self): """Get the details from the bulb.""" try: request = requests.get( '{}/{}/'.format(self.resource, URI), timeout=self.timeout) raw_data = request.json() # Doesn't always work !!!!! #self._mac = next(iter(self.raw_data)) self.data = raw_data[self._mac] return self.data except (requests.exceptions.ConnectionError, ValueError): raise exceptions.MyStromConnectionError()
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41.75
12.75
def zero_dataset(train=False, dev=False, test=False, train_rows=256, dev_rows=64, test_rows=64): """ Load the Zero dataset. The Zero dataset is a simple task of predicting zero from zero. This dataset is useful for integration testing. The extreme simplicity of the dataset allows for models to learn the task quickly allowing for quick end-to-end testing. Args: train (bool, optional): If to load the training split of the dataset. dev (bool, optional): If to load the development split of the dataset. test (bool, optional): If to load the test split of the dataset. train_rows (int, optional): Number of training rows to generate. dev_rows (int, optional): Number of development rows to generate. test_rows (int, optional): Number of test rows to generate. Returns: :class:`tuple` of :class:`torchnlp.datasets.Dataset` or :class:`torchnlp.datasets.Dataset`: Returns between one and all dataset splits (train, dev and test) depending on if their respective boolean argument is ``True``. Example: >>> from torchnlp.datasets import zero_dataset >>> train = zero_dataset(train=True) >>> train[0:2] [{'source': '0', 'target': '0'}, {'source': '0', 'target': '0'}] """ ret = [] for is_requested, n_rows in [(train, train_rows), (dev, dev_rows), (test, test_rows)]: if not is_requested: continue rows = [{'source': str(0), 'target': str(0)} for i in range(n_rows)] ret.append(Dataset(rows)) if len(ret) == 1: return ret[0] else: return tuple(ret)
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42.578947
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def initialize_bars(self, sender=None, **kwargs): """Calls the initializers of all bound navigation bars.""" for bar in self.bars.values(): for initializer in bar.initializers: initializer(self)
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46.8
5.2
def getFileDialogFilter(self): """ Returns a filter that can be used in open file dialogs, for example: 'All files (*);;Txt (*.txt;*.text);;netCDF(*.nc;*.nc4)' """ filters = [] for regRti in self.items: filters.append(regRti.getFileDialogFilter()) return ';;'.join(filters)
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41.25
12.5
def client_getname(self, encoding=_NOTSET): """Get the current connection name.""" return self.execute(b'CLIENT', b'GETNAME', encoding=encoding)
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52.666667
10.666667
def slow_highlight(img1, img2, opts): """Try to find similar areas between two images. Produces two masks for img1 and img2. The algorithm works by comparing every possible alignment of the images, smoothing it a bit to reduce spurious matches in areas that are perceptibly different (e.g. text), and then taking the point-wise minimum of all those difference maps. This way if you insert a few pixel rows/columns into an image, similar areas should match even if different areas need to be aligned with different shifts. As you can imagine, this brute-force approach can be pretty slow, if there are many possible alignments. The closer the images are in size, the faster this will work. If would work better if it could compare alignments that go beyond the outer boundaries of the images, in case some pixels got shifted closer to an edge. """ w1, h1 = img1.size w2, h2 = img2.size W, H = max(w1, w2), max(h1, h2) pimg1 = Image.new('RGB', (W, H), opts.bgcolor) pimg2 = Image.new('RGB', (W, H), opts.bgcolor) pimg1.paste(img1, (0, 0)) pimg2.paste(img2, (0, 0)) diff = Image.new('L', (W, H), 255) # It is not a good idea to keep one diff image; it should track the # relative positions of the two images. I think that's what explains # the fuzz I see near the edges of the different areas. xr = abs(w1 - w2) + 1 yr = abs(h1 - h2) + 1 try: p = Progress(xr * yr, timeout=opts.timeout) for x in range(xr): for y in range(yr): p.next() this = ImageChops.difference(pimg1, pimg2).convert('L') this = this.filter(ImageFilter.MaxFilter(7)) diff = ImageChops.darker(diff, this) if h1 > h2: pimg2 = ImageChops.offset(pimg2, 0, 1) else: pimg1 = ImageChops.offset(pimg1, 0, 1) if h1 > h2: pimg2 = ImageChops.offset(pimg2, 0, -yr) else: pimg1 = ImageChops.offset(pimg1, 0, -yr) if w1 > w2: pimg2 = ImageChops.offset(pimg2, 1, 0) else: pimg1 = ImageChops.offset(pimg1, 1, 0) except KeyboardInterrupt: return None, None diff = diff.filter(ImageFilter.MaxFilter(5)) diff1 = diff.crop((0, 0, w1, h1)) diff2 = diff.crop((0, 0, w2, h2)) mask1 = tweak_diff(diff1, opts.opacity) mask2 = tweak_diff(diff2, opts.opacity) return mask1, mask2
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def get_url_for_service(service, region, endpoint_type): if 'type' not in service: return None identity_version = get_version_from_service(service) service_endpoints = service.get('endpoints', []) available_endpoints = [endpoint for endpoint in service_endpoints if region == _get_endpoint_region(endpoint)] """if we are dealing with the identity service and there is no endpoint in the current region, it is okay to use the first endpoint for any identity service endpoints and we can assume that it is global """ if service['type'] == 'identity' and not available_endpoints: available_endpoints = [endpoint for endpoint in service_endpoints] for endpoint in available_endpoints: try: if identity_version < 3: return endpoint.get(endpoint_type) else: interface = \ ENDPOINT_TYPE_TO_INTERFACE.get(endpoint_type, '') if endpoint.get('interface') == interface: return endpoint.get('url') except (IndexError, KeyError): # it could be that the current endpoint just doesn't match the # type, continue trying the next one pass return None
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def write_to_stream(self, stream_id, data, sandbox=None): """ Write to the stream :param stream_id: The stream identifier :param data: The stream instances :param sandbox: The sandbox for this stream :type stream_id: StreamId :return: None :raises: NotImplementedError """ if sandbox is not None: raise NotImplementedError if stream_id not in self.streams: raise StreamNotFoundError("Stream with id '{}' does not exist".format(stream_id)) writer = self.get_stream_writer(self.streams[stream_id]) if isinstance(data, StreamInstance): data = [data] for instance in data: if not isinstance(instance, StreamInstance): raise ValueError("Expected StreamInstance, got {}".format(str(type(instance)))) writer(instance)
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def command_dependents(options): """Command launched by CLI.""" dependents = dependencies(options.package, options.recursive, options.info) if dependents: print(*dependents, sep='\n')
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def _columns_for_table(table_name): """ Return all of the columns registered for a given table. Parameters ---------- table_name : str Returns ------- columns : dict of column wrappers Keys will be column names. """ return {cname: col for (tname, cname), col in _COLUMNS.items() if tname == table_name}
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def is_subdomain(self, other): """Is self a subdomain of other? The notion of subdomain includes equality. @rtype: bool """ (nr, o, nl) = self.fullcompare(other) if nr == NAMERELN_SUBDOMAIN or nr == NAMERELN_EQUAL: return True return False
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def adsSyncSetTimeoutEx(port, nMs): # type: (int, int) -> None """Set Timeout. :param int port: local AMS port as returned by adsPortOpenEx() :param int nMs: timeout in ms """ adsSyncSetTimeoutFct = _adsDLL.AdsSyncSetTimeoutEx cms = ctypes.c_long(nMs) err_code = adsSyncSetTimeoutFct(port, cms) if err_code: raise ADSError(err_code)
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def save_as(self, new_filename): """ Save our file with the name provided. Args: new_filename: New name for the workbook file. String. Returns: Nothing. """ xfile._save_file( self._filename, self._workbookTree, new_filename)
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def pack_into_dict(fmt, names, buf, offset, data, **kwargs): """Same as :func:`~bitstruct.pack_into()`, but data is read from a dictionary. See :func:`~bitstruct.pack_dict()` for details on `names`. """ return CompiledFormatDict(fmt, names).pack_into(buf, offset, data, **kwargs)
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def post(method, hmc, uri, uri_parms, body, logon_required, wait_for_completion): """Operation: Set CPC Power Capping (any CPC mode).""" assert wait_for_completion is True # async not supported yet cpc_oid = uri_parms[0] try: cpc = hmc.cpcs.lookup_by_oid(cpc_oid) except KeyError: raise InvalidResourceError(method, uri) check_required_fields(method, uri, body, ['power-capping-state']) power_capping_state = body['power-capping-state'] power_cap_current = body.get('power-cap-current', None) if power_capping_state not in ['disabled', 'enabled', 'custom']: raise BadRequestError(method, uri, reason=7, message="Invalid power-capping-state value: " "%r" % power_capping_state) if power_capping_state == 'enabled' and power_cap_current is None: raise BadRequestError(method, uri, reason=7, message="Power-cap-current must be provided " "when enabling power capping") cpc.properties['cpc-power-capping-state'] = power_capping_state cpc.properties['cpc-power-cap-current'] = power_cap_current cpc.properties['zcpc-power-capping-state'] = power_capping_state cpc.properties['zcpc-power-cap-current'] = power_cap_current
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async def _download_lsst_bibtex(bibtex_names): """Asynchronously download a set of lsst-texmf BibTeX bibliographies from GitHub. Parameters ---------- bibtex_names : sequence of `str` Names of lsst-texmf BibTeX files to download. For example: .. code-block:: python ['lsst', 'lsst-dm', 'refs', 'books', 'refs_ads'] Returns ------- bibtexs : `list` of `str` List of BibTeX file content, in the same order as ``bibtex_names``. """ blob_url_template = ( 'https://raw.githubusercontent.com/lsst/lsst-texmf/master/texmf/' 'bibtex/bib/{name}.bib' ) urls = [blob_url_template.format(name=name) for name in bibtex_names] tasks = [] async with ClientSession() as session: for url in urls: task = asyncio.ensure_future(_download_text(url, session)) tasks.append(task) return await asyncio.gather(*tasks)
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def get_elemental_abunds(self,cycle,index=None): """ returns the elemental abundances for one cycle, either for the whole star or a specific zone depending upon the value of 'index'. Parameters ---------- cycle : string or integer Model to get the abundances for. index : integer or list, optional zone number for which to get elemental abundances. If None the entire abundance profile is returned. If a 1x2 list, the abundances are returned between indices of index[0] and index[1]. The default is None. """ isoabunds=self.se.get(cycle,'iso_massf') A=array(self.se.A) Z=array(self.se.Z) names=self.se.isos Zuq=list(set(Z)) # list of unique Zs Zuq.sort() if index==None: index=[0,len(isoabunds)] if type(index)==list: elemabunds=[] for zone in range(index[0],index[1]): percent=int((zone-index[0])*100./(index[1]-index[0])) sys.stdout.flush() sys.stdout.write("\rgetting elemental abundances " + "...%d%%" % percent) elemabunds.append([sum(isoabunds[zone][where(Z==iZ)]) for iZ in Zuq]) else: elemabunds=[sum(isoabunds[index][where(Z==iZ)]) for iZ in Zuq] return elemabunds
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def update_function(self, param_vals): """Updates the opt_obj, returns new error.""" self.opt_obj.update_function(param_vals) return self.opt_obj.get_error()
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def drop_indexes(self): """Drops all indexes on this collection. Can be used on non-existant collections or collections with no indexes. Raises OperationFailure on an error. .. note:: The :attr:`~pymongo.collection.Collection.write_concern` of this collection is automatically applied to this operation when using MongoDB >= 3.4. .. versionchanged:: 3.4 Apply this collection's write concern automatically to this operation when connected to MongoDB >= 3.4. """ self.__database.client._purge_index(self.__database.name, self.__name) self.drop_index("*")
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def _get_connection(self): ''' _get_connection - Maybe get a new connection, or reuse if passed in. Will share a connection with a model internal ''' if self._connection is None: self._connection = self._get_new_connection() return self._connection
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def _is_iterable(item): """ Checks if an item is iterable (list, tuple, generator), but not string """ return isinstance(item, collections.Iterable) and not isinstance(item, six.string_types)
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65.666667
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def _vn_decode(self, msg): """VN: Version information.""" elkm1_version = "{}.{}.{}".format(int(msg[4:6], 16), int(msg[6:8], 16), int(msg[8:10], 16)) xep_version = "{}.{}.{}".format(int(msg[10:12], 16), int(msg[12:14], 16), int(msg[14:16], 16)) return {'elkm1_version': elkm1_version, 'xep_version': xep_version}
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24.285714
def populate(self, priority, address, rtr, data): """ data bytes (high + low) 1 + 2 = current temp 3 + 4 = min temp 5 + 6 = max temp :return: None """ assert isinstance(data, bytes) self.needs_no_rtr(rtr) self.needs_data(data, 6) self.set_attributes(priority, address, rtr) self.cur = (((data[0] << 8)| data[1]) / 32 ) * 0.0625 self.min = (((data[2] << 8) | data[3]) / 32 ) * 0.0625 self.max = (((data[4] << 8) | data[5]) / 32 ) * 0.0625
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36.866667
10.6
def forwards(self, orm): "Write your forwards methods here." orm['avocado.DataField'].objects.get_or_create( app_name='variants', model_name='variantphenotype', field_name='hgmd_id', defaults={ 'name': 'HGMD', 'published': True })
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32.9
11.1
def cli(env, billing_id, datacenter): """Adds a load balancer given the id returned from create-options.""" mgr = SoftLayer.LoadBalancerManager(env.client) if not formatting.confirm("This action will incur charges on your " "account. Continue?"): raise exceptions.CLIAbort('Aborted.') mgr.add_local_lb(billing_id, datacenter=datacenter) env.fout("Load balancer is being created!")
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47.888889
13.777778
def dM(self, t, param, Mt, tips=None, gaps=None): """See docs for method in `Model` abstract base class.""" assert isinstance(t, float) and t > 0, "Invalid t: {0}".format(t) assert (param == 't') or (param in self.freeparams), ( "Invalid param: {0}".format(param)) if Mt is None: Mt = self.M(t, tips=tips, gaps=gaps) if (param == 'mu') or (param == 't'): if param == 'mu': alpha = t else: alpha = self.mu if tips is None: dM_param = broadcastMatrixMultiply(self.Prxy, Mt, alpha=alpha) else: dM_param = broadcastMatrixVectorMultiply(self.Prxy, Mt, alpha=alpha) if gaps is not None: dM_param[gaps] = scipy.zeros(N_CODON, dtype='float') return dM_param paramval = getattr(self, param) if isinstance(paramval, float): paramisvec = False else: assert isinstance(paramval, numpy.ndarray) and paramval.ndim == 1 paramisvec = True paramlength = paramval.shape[0] if ('expD', t) not in self._cached: self._cached[('expD', t)] = scipy.exp(self.D * self.mu * t) expD = self._cached[('expD', t)] if ('V', t) not in self._cached: if 'Dxx_Dyy' not in self._cached: Dyy = scipy.tile(self.D, (1, N_CODON)).reshape( self.nsites, N_CODON, N_CODON) Dxx = scipy.array([Dyy[r].transpose() for r in range(self.nsites)]) self._cached['Dxx_Dyy'] = Dxx - Dyy Dxx_Dyy = self._cached['Dxx_Dyy'] if 'Dxx_Dyy_lt_ALMOST_ZERO' not in self._cached: self._cached['Dxx_Dyy_lt_ALMOST_ZERO'] = scipy.fabs( Dxx_Dyy) < ALMOST_ZERO Dxx_Dyy_lt_ALMOST_ZERO = self._cached['Dxx_Dyy_lt_ALMOST_ZERO'] with scipy.errstate(divide='raise', under='ignore', over='raise', invalid='ignore'): expDyy = scipy.tile(expD,(1, N_CODON)).reshape( self.nsites, N_CODON, N_CODON) expDxx = scipy.array([expDyy[r].transpose() for r in range(self.nsites)]) V = (expDxx - expDyy) / Dxx_Dyy with scipy.errstate(under='ignore'): # OK if some values 0 scipy.copyto(V, self.mu * t * expDxx, where= Dxx_Dyy_lt_ALMOST_ZERO) self._cached[('V', t)] = V V = self._cached[('V', t)] with scipy.errstate(under='ignore'): # don't worry if some values 0 if tips is None: if not paramisvec: dM_param = broadcastMatrixMultiply(self.A, broadcastMatrixMultiply(self.B[param] * V, self.Ainv)) else: dM_param = scipy.ndarray((paramlength, self.nsites, N_CODON, N_CODON), dtype='float') for j in range(paramlength): dM_param[j] = broadcastMatrixMultiply(self.A, broadcastMatrixMultiply(self.B[param][j] * V, self.Ainv)) else: if not paramisvec: dM_param = broadcastMatrixVectorMultiply(self.A, broadcastGetCols(broadcastMatrixMultiply( self.B[param] * V, self.Ainv), tips)) else: dM_param = scipy.ndarray((paramlength, self.nsites, N_CODON), dtype='float') for j in range(paramlength): dM_param[j] = broadcastMatrixVectorMultiply(self.A, broadcastGetCols(broadcastMatrixMultiply( self.B[param][j] * V, self.Ainv), tips)) if gaps is not None: if not paramisvec: dM_param[gaps] = scipy.zeros(N_CODON, dtype='float') else: dM_param[:, gaps] = scipy.zeros(N_CODON, dtype='float') return dM_param
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46.755556
18.677778
def intersect_one_round(candidates, intersections): """Perform one step of the intersection process. .. note:: This is a helper for :func:`_all_intersections` and that function has a Fortran equivalent. Checks if the bounding boxes of each pair in ``candidates`` intersect. If the bounding boxes do not intersect, the pair is discarded. Otherwise, the pair is "accepted". Then we attempt to linearize each curve in an "accepted" pair and track the overall linearization error for every curve encountered. Args: candidates (Union[list, itertools.chain]): An iterable of pairs of curves (or linearized curves). intersections (list): A list of already encountered intersections. If any intersections can be readily determined during this round of subdivision, then they will be added to this list. Returns: list: Returns a list of the next round of ``candidates``. """ next_candidates = [] # NOTE: In the below we replace ``isinstance(a, B)`` with # ``a.__class__ is B``, which is a 3-3.5x speedup. for first, second in candidates: both_linearized = False if first.__class__ is Linearization: if second.__class__ is Linearization: both_linearized = True bbox_int = bbox_intersect( first.curve.nodes, second.curve.nodes ) else: bbox_int = bbox_line_intersect( second.nodes, first.start_node, first.end_node ) else: if second.__class__ is Linearization: bbox_int = bbox_line_intersect( first.nodes, second.start_node, second.end_node ) else: bbox_int = bbox_intersect(first.nodes, second.nodes) if bbox_int == BoxIntersectionType.DISJOINT: continue elif bbox_int == BoxIntersectionType.TANGENT and not both_linearized: # NOTE: Ignore tangent bounding boxes in the linearized case # because ``tangent_bbox_intersection()`` assumes that both # curves are not linear. tangent_bbox_intersection(first, second, intersections) continue if both_linearized: # If both ``first`` and ``second`` are linearizations, then # we can intersect them immediately. from_linearized(first, second, intersections) continue # If we haven't ``continue``-d, add the accepted pair. # NOTE: This may be a wasted computation, e.g. if ``first`` # or ``second`` occur in multiple accepted pairs (the caller # only passes one pair at a time). However, in practice # the number of such pairs will be small so this cost # will be low. lin1 = six.moves.map(Linearization.from_shape, first.subdivide()) lin2 = six.moves.map(Linearization.from_shape, second.subdivide()) next_candidates.extend(itertools.product(lin1, lin2)) return next_candidates
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42.027027
21.905405
def _chk_type(recdef, rec): """Checks if type of `rec` matches `recdef` :param recdef: instance of RecordDef :param rec: instance of Record :raises: `TypeError` """ if len(recdef) != len(rec): raise TypeError("Number of columns (%d) is different from RecordDef (%d)" % (len(rec), len(recdef))) for i in xrange(len(recdef)): try: def_type = recdef[i].type col_type = Type.equivalent_relshell_type(rec[i]) if col_type != def_type: raise TypeError("Column %d has mismatched type: Got '%s' [%s] ; Expected [%s]" % (i, rec[i], col_type, def_type)) except AttributeError as e: # recdef[i].type is not defined, then any relshell type is allowed try: Type.equivalent_relshell_type(rec[i]) except NotImplementedError as e: raise TypeError("%s" % (e))
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46.136364
17.136364
def postinit( self, bases, body, decorators, newstyle=None, metaclass=None, keywords=None ): """Do some setup after initialisation. :param bases: What the class inherits from. :type bases: list(NodeNG) :param body: The contents of the class body. :type body: list(NodeNG) :param decorators: The decorators that are applied to this class. :type decorators: Decorators or None :param newstyle: Whether this is a new style class or not. :type newstyle: bool or None :param metaclass: The metaclass of this class. :type metaclass: NodeNG or None :param keywords: The keywords given to the class definition. :type keywords: list(Keyword) or None """ self.keywords = keywords self.bases = bases self.body = body self.decorators = decorators if newstyle is not None: self._newstyle = newstyle if metaclass is not None: self._metaclass = metaclass
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32.612903
18
def data(self, column, role): """Return the data for the specified column and role For DisplayRole the element in the list will be converted to a sting and returned. :param column: the data column :type column: int :param role: the data role :type role: QtCore.Qt.ItemDataRole :returns: data depending on the role, or None if the column is out of range :rtype: depending on the role or None :raises: None """ if role == QtCore.Qt.DisplayRole: if column >= 0 and column < len(self._list): return str(self._list[column])
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38.8125
16
def to_type(self, dtype: type, *cols, **kwargs): """ Convert colums values to a given type in the main dataframe :param dtype: a type to convert to: ex: ``str`` :type dtype: type :param \*cols: names of the colums :type \*cols: str, at least one :param \*\*kwargs: keyword arguments for ``df.astype`` :type \*\*kwargs: optional :example: ``ds.to_type(str, "mycol")`` """ try: allcols = self.df.columns.values for col in cols: if col not in allcols: self.err("Column " + col + " not found") return self.df[col] = self.df[col].astype(dtype, **kwargs) except Exception as e: self.err(e, "Can not convert to type")
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34.913043
13.608696
def create(self): """ Executes ``ansible-playbook`` against the create playbook and returns None. :return: None """ pb = self._get_ansible_playbook(self.playbooks.create) pb.execute()
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25.777778
20.888889
def optional(e, default=Ignore): """ Create a PEG function to optionally match an expression. """ def match_optional(s, grm=None, pos=0): try: return e(s, grm, pos) except PegreError: return PegreResult(s, default, (pos, pos)) return match_optional
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29.9
10.9
def plot_variability_thresholds(varthreshpkl, xmin_lcmad_stdev=5.0, xmin_stetj_stdev=2.0, xmin_iqr_stdev=2.0, xmin_inveta_stdev=2.0, lcformat='hat-sql', lcformatdir=None, magcols=None): '''This makes plots for the variability threshold distributions. Parameters ---------- varthreshpkl : str The pickle produced by the function above. xmin_lcmad_stdev,xmin_stetj_stdev,xmin_iqr_stdev,xmin_inveta_stdev : float or np.array Values of the threshold values to override the ones in the `vartresholdpkl`. If provided, will plot the thresholds accordingly instead of using the ones in the input pickle directly. lcformat : str This is the `formatkey` associated with your light curve format, which you previously passed in to the `lcproc.register_lcformat` function. This will be used to look up how to find and read the light curves specified in `basedir` or `use_list_of_filenames`. lcformatdir : str or None If this is provided, gives the path to a directory when you've stored your lcformat description JSONs, other than the usual directories lcproc knows to search for them in. Use this along with `lcformat` to specify an LC format JSON file that's not currently registered with lcproc. magcols : list of str or None The magcol keys to use from the lcdict. Returns ------- str The file name of the threshold plot generated. ''' try: formatinfo = get_lcformat(lcformat, use_lcformat_dir=lcformatdir) if formatinfo: (dfileglob, readerfunc, dtimecols, dmagcols, derrcols, magsarefluxes, normfunc) = formatinfo else: LOGERROR("can't figure out the light curve format") return None except Exception as e: LOGEXCEPTION("can't figure out the light curve format") return None if magcols is None: magcols = dmagcols with open(varthreshpkl,'rb') as infd: allobjects = pickle.load(infd) magbins = allobjects['magbins'] for magcol in magcols: min_lcmad_stdev = ( xmin_lcmad_stdev or allobjects[magcol]['min_lcmad_stdev'] ) min_stetj_stdev = ( xmin_stetj_stdev or allobjects[magcol]['min_stetj_stdev'] ) min_iqr_stdev = ( xmin_iqr_stdev or allobjects[magcol]['min_iqr_stdev'] ) min_inveta_stdev = ( xmin_inveta_stdev or allobjects[magcol]['min_inveta_stdev'] ) fig = plt.figure(figsize=(20,16)) # the mag vs lcmad plt.subplot(221) plt.plot(allobjects[magcol]['sdssr'], allobjects[magcol]['lcmad']*1.483, marker='.',ms=1.0, linestyle='none', rasterized=True) plt.plot(allobjects[magcol]['binned_sdssr_median'], np.array(allobjects[magcol]['binned_lcmad_median'])*1.483, linewidth=3.0) plt.plot( allobjects[magcol]['binned_sdssr_median'], np.array(allobjects[magcol]['binned_lcmad_median'])*1.483 + min_lcmad_stdev*np.array( allobjects[magcol]['binned_lcmad_stdev'] ), linewidth=3.0, linestyle='dashed' ) plt.xlim((magbins.min()-0.25, magbins.max())) plt.xlabel('SDSS r') plt.ylabel(r'lightcurve RMS (MAD $\times$ 1.483)') plt.title('%s - SDSS r vs. light curve RMS' % magcol) plt.yscale('log') plt.tight_layout() # the mag vs stetsonj plt.subplot(222) plt.plot(allobjects[magcol]['sdssr'], allobjects[magcol]['stetsonj'], marker='.',ms=1.0, linestyle='none', rasterized=True) plt.plot(allobjects[magcol]['binned_sdssr_median'], allobjects[magcol]['binned_stetsonj_median'], linewidth=3.0) plt.plot( allobjects[magcol]['binned_sdssr_median'], np.array(allobjects[magcol]['binned_stetsonj_median']) + min_stetj_stdev*np.array( allobjects[magcol]['binned_stetsonj_stdev'] ), linewidth=3.0, linestyle='dashed' ) plt.xlim((magbins.min()-0.25, magbins.max())) plt.xlabel('SDSS r') plt.ylabel('Stetson J index') plt.title('%s - SDSS r vs. Stetson J index' % magcol) plt.yscale('log') plt.tight_layout() # the mag vs IQR plt.subplot(223) plt.plot(allobjects[magcol]['sdssr'], allobjects[magcol]['iqr'], marker='.',ms=1.0, linestyle='none', rasterized=True) plt.plot(allobjects[magcol]['binned_sdssr_median'], allobjects[magcol]['binned_iqr_median'], linewidth=3.0) plt.plot( allobjects[magcol]['binned_sdssr_median'], np.array(allobjects[magcol]['binned_iqr_median']) + min_iqr_stdev*np.array( allobjects[magcol]['binned_iqr_stdev'] ), linewidth=3.0, linestyle='dashed' ) plt.xlabel('SDSS r') plt.ylabel('IQR') plt.title('%s - SDSS r vs. IQR' % magcol) plt.xlim((magbins.min()-0.25, magbins.max())) plt.yscale('log') plt.tight_layout() # the mag vs IQR plt.subplot(224) plt.plot(allobjects[magcol]['sdssr'], allobjects[magcol]['inveta'], marker='.',ms=1.0, linestyle='none', rasterized=True) plt.plot(allobjects[magcol]['binned_sdssr_median'], allobjects[magcol]['binned_inveta_median'], linewidth=3.0) plt.plot( allobjects[magcol]['binned_sdssr_median'], np.array(allobjects[magcol]['binned_inveta_median']) + min_inveta_stdev*np.array( allobjects[magcol]['binned_inveta_stdev'] ), linewidth=3.0, linestyle='dashed' ) plt.xlabel('SDSS r') plt.ylabel(r'$1/\eta$') plt.title(r'%s - SDSS r vs. $1/\eta$' % magcol) plt.xlim((magbins.min()-0.25, magbins.max())) plt.yscale('log') plt.tight_layout() plt.savefig('varfeatures-%s-%s-distributions.png' % (varthreshpkl, magcol), bbox_inches='tight') plt.close('all')
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SDSS r vs. light curve RMS'", "%", "magcol", ")", "plt", ".", "yscale", "(", "'log'", ")", "plt", ".", "tight_layout", "(", ")", "# the mag vs stetsonj", "plt", ".", "subplot", "(", "222", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'sdssr'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'stetsonj'", "]", ",", "marker", "=", "'.'", ",", "ms", "=", "1.0", ",", "linestyle", "=", "'none'", ",", "rasterized", "=", "True", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'binned_stetsonj_median'", "]", ",", "linewidth", "=", "3.0", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_stetsonj_median'", "]", ")", "+", "min_stetj_stdev", "*", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_stetsonj_stdev'", "]", ")", ",", "linewidth", "=", "3.0", ",", "linestyle", "=", "'dashed'", ")", "plt", ".", "xlim", "(", "(", "magbins", ".", "min", "(", ")", "-", "0.25", ",", "magbins", ".", "max", "(", ")", ")", ")", "plt", ".", "xlabel", "(", "'SDSS r'", ")", "plt", ".", "ylabel", "(", "'Stetson J index'", ")", "plt", ".", "title", "(", "'%s - SDSS r vs. Stetson J index'", "%", "magcol", ")", "plt", ".", "yscale", "(", "'log'", ")", "plt", ".", "tight_layout", "(", ")", "# the mag vs IQR", "plt", ".", "subplot", "(", "223", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'sdssr'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'iqr'", "]", ",", "marker", "=", "'.'", ",", "ms", "=", "1.0", ",", "linestyle", "=", "'none'", ",", "rasterized", "=", "True", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'binned_iqr_median'", "]", ",", "linewidth", "=", "3.0", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_iqr_median'", "]", ")", "+", "min_iqr_stdev", "*", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_iqr_stdev'", "]", ")", ",", "linewidth", "=", "3.0", ",", "linestyle", "=", "'dashed'", ")", "plt", ".", "xlabel", "(", "'SDSS r'", ")", "plt", ".", "ylabel", "(", "'IQR'", ")", "plt", ".", "title", "(", "'%s - SDSS r vs. IQR'", "%", "magcol", ")", "plt", ".", "xlim", "(", "(", "magbins", ".", "min", "(", ")", "-", "0.25", ",", "magbins", ".", "max", "(", ")", ")", ")", "plt", ".", "yscale", "(", "'log'", ")", "plt", ".", "tight_layout", "(", ")", "# the mag vs IQR", "plt", ".", "subplot", "(", "224", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'sdssr'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'inveta'", "]", ",", "marker", "=", "'.'", ",", "ms", "=", "1.0", ",", "linestyle", "=", "'none'", ",", "rasterized", "=", "True", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "allobjects", "[", "magcol", "]", "[", "'binned_inveta_median'", "]", ",", "linewidth", "=", "3.0", ")", "plt", ".", "plot", "(", "allobjects", "[", "magcol", "]", "[", "'binned_sdssr_median'", "]", ",", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_inveta_median'", "]", ")", "+", "min_inveta_stdev", "*", "np", ".", "array", "(", "allobjects", "[", "magcol", "]", "[", "'binned_inveta_stdev'", "]", ")", ",", "linewidth", "=", "3.0", ",", "linestyle", "=", "'dashed'", ")", "plt", ".", "xlabel", "(", "'SDSS r'", ")", "plt", ".", "ylabel", "(", "r'$1/\\eta$'", ")", "plt", ".", "title", "(", "r'%s - SDSS r vs. $1/\\eta$'", "%", "magcol", ")", "plt", ".", "xlim", "(", "(", "magbins", ".", "min", "(", ")", "-", "0.25", ",", "magbins", ".", "max", "(", ")", ")", ")", "plt", ".", "yscale", "(", "'log'", ")", "plt", ".", "tight_layout", "(", ")", "plt", ".", "savefig", "(", "'varfeatures-%s-%s-distributions.png'", "%", "(", "varthreshpkl", ",", "magcol", ")", ",", "bbox_inches", "=", "'tight'", ")", "plt", ".", "close", "(", "'all'", ")" ]
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def mute(self, mute): """Mute receiver via HTTP get command.""" try: if mute: if self.send_get_command(self._urls.command_mute_on): self._mute = STATE_ON return True else: return False else: if self.send_get_command(self._urls.command_mute_off): self._mute = STATE_OFF return True else: return False except requests.exceptions.RequestException: _LOGGER.error("Connection error: mute command not sent.") return False
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36.333333
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def get_variables_substitution_dictionaries(self, lhs_graph, rhs_graph): """ Looks for sub-isomorphisms of rhs into lhs :param lhs_graph: The graph to look sub-isomorphisms into (the bigger graph) :param rhs_graph: The smaller graph :return: The list of matching names """ if not rhs_graph: return {}, {}, {} self.matching_code_container.add_graph_to_namespace(lhs_graph) self.matching_code_container.add_graph_to_namespace(rhs_graph) return self.__collect_variables_that_match_graph(lhs_graph, rhs_graph)
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45.076923
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def authenticate(self, code: str) -> 'Preston': """Authenticates using the code from the EVE SSO. A new Preston object is returned; this object is not modified. The intended usage is: auth = preston.authenticate('some_code_here') Args: code: SSO code Returns: new Preston, authenticated """ headers = self._get_authorization_headers() data = { 'grant_type': 'authorization_code', 'code': code } r = self.session.post(self.TOKEN_URL, headers=headers, data=data) if not r.status_code == 200: raise Exception(f'Could not authenticate, got repsonse code {r.status_code}') new_kwargs = dict(self._kwargs) response_data = r.json() new_kwargs['access_token'] = response_data['access_token'] new_kwargs['access_expiration'] = time.time() + float(response_data['expires_in']) new_kwargs['refresh_token'] = response_data['refresh_token'] return Preston(**new_kwargs)
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def density_grid(*args, **kwargs): """ Estimates point density of the given linear orientation measurements (Interpreted as poles, lines, rakes, or "raw" longitudes and latitudes based on the `measurement` keyword argument.). Returns a regular (in lat-long space) grid of density estimates over a hemispherical surface. Parameters ---------- *args : 2 or 3 sequences of measurements By default, this will be expected to be ``strike`` & ``dip``, both array-like sequences representing poles to planes. (Rake measurements require three parameters, thus the variable number of arguments.) The ``measurement`` kwarg controls how these arguments are interpreted. measurement : string, optional Controls how the input arguments are interpreted. Defaults to ``"poles"``. May be one of the following: ``"poles"`` : strikes, dips Arguments are assumed to be sequences of strikes and dips of planes. Poles to these planes are used for contouring. ``"lines"`` : plunges, bearings Arguments are assumed to be sequences of plunges and bearings of linear features. ``"rakes"`` : strikes, dips, rakes Arguments are assumed to be sequences of strikes, dips, and rakes along the plane. ``"radians"`` : lon, lat Arguments are assumed to be "raw" longitudes and latitudes in the stereonet's underlying coordinate system. method : string, optional The method of density estimation to use. Defaults to ``"exponential_kamb"``. May be one of the following: ``"exponential_kamb"`` : Kamb with exponential smoothing A modified Kamb method using exponential smoothing [1]_. Units are in numbers of standard deviations by which the density estimate differs from uniform. ``"linear_kamb"`` : Kamb with linear smoothing A modified Kamb method using linear smoothing [1]_. Units are in numbers of standard deviations by which the density estimate differs from uniform. ``"kamb"`` : Kamb with no smoothing Kamb's method [2]_ with no smoothing. Units are in numbers of standard deviations by which the density estimate differs from uniform. ``"schmidt"`` : 1% counts The traditional "Schmidt" (a.k.a. 1%) method. Counts points within a counting circle comprising 1% of the total area of the hemisphere. Does not take into account sample size. Units are in points per 1% area. sigma : int or float, optional The number of standard deviations defining the expected number of standard deviations by which a random sample from a uniform distribution of points would be expected to vary from being evenly distributed across the hemisphere. This controls the size of the counting circle, and therefore the degree of smoothing. Higher sigmas will lead to more smoothing of the resulting density distribution. This parameter only applies to Kamb-based methods. Defaults to 3. gridsize : int or 2-item tuple of ints, optional The size of the grid that the density is estimated on. If a single int is given, it is interpreted as an NxN grid. If a tuple of ints is given it is interpreted as (nrows, ncols). Defaults to 100. weights : array-like, optional The relative weight to be applied to each input measurement. The array will be normalized to sum to 1, so absolute value of the weights do not affect the result. Defaults to None. Returns ------- xi, yi, zi : 2D arrays The longitude, latitude and density values of the regularly gridded density estimates. Longitude and latitude are in radians. See Also --------- mplstereonet.StereonetAxes.density_contourf mplstereonet.StereonetAxes.density_contour References ---------- .. [1] Vollmer, 1995. C Program for Automatic Contouring of Spherical Orientation Data Using a Modified Kamb Method. Computers & Geosciences, Vol. 21, No. 1, pp. 31--49. .. [2] Kamb, 1959. Ice Petrofabric Observations from Blue Glacier, Washington, in Relation to Theory and Experiment. Journal of Geophysical Research, Vol. 64, No. 11, pp. 1891--1909. """ def do_nothing(x, y): return x, y measurement = kwargs.get('measurement', 'poles') gridsize = kwargs.get('gridsize', 100) weights = kwargs.get('weights', None) try: gridsize = int(gridsize) gridsize = (gridsize, gridsize) except TypeError: pass func = {'poles':stereonet_math.pole, 'lines':stereonet_math.line, 'rakes':stereonet_math.rake, 'radians':do_nothing}[measurement] lon, lat = func(*args) method = kwargs.get('method', 'exponential_kamb') sigma = kwargs.get('sigma', 3) func = {'linear_kamb':_linear_inverse_kamb, 'square_kamb':_square_inverse_kamb, 'schmidt':_schmidt_count, 'kamb':_kamb_count, 'exponential_kamb':_exponential_kamb, }[method] lon, lat, z = _count_points(lon, lat, func, sigma, gridsize, weights) return lon, lat, z
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43.786885
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