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def idxstats(in_bam, data): index(in_bam, data["config"], check_timestamp=False) AlignInfo = collections.namedtuple("AlignInfo", ["contig", "length", "aligned", "unaligned"]) samtools = config_utils.get_program("samtools", data["config"]) idxstats_out = subprocess.check_output([samtools, "idxstats"...
Return BAM index stats for the given file, using samtools idxstats.
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def handle_jmespath_query(self, args): continue_flag = False query_symbol = SELECT_SYMBOL[] symbol_len = len(query_symbol) try: if len(args) == 1: if args[0] == query_symbol: result = self.last.result ...
handles the jmespath query for injection or printing
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def _parse_engine(self): if self._parser.has_option(, ): engine = str(self._parser.get(, )) else: engine = ENGINE_DROPBOX assert isinstance(engine, str) if engine not in [ENGINE_DROPBOX, ENGINE_GDRIVE, ...
Parse the storage engine in the config. Returns: str
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def do_a(self, line): index, value_string = self.index_and_value_from_line(line) if index and value_string: try: self.application.apply_update(opendnp3.Analog(float(value_string)), index) except ValueError: print()
Send the Master an AnalogInput (group 32) value. Command syntax is: a index value
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def p_var_decl(p): for vardata in p[2]: SYMBOL_TABLE.declare_variable(vardata[0], vardata[1], p[3]) p[0] = None
var_decl : DIM idlist typedef
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def _check_args(logZ, f, x, samples, weights): if logZ is None: logZ = [0] f = [f] samples = [samples] weights = [weights] logZ = numpy.array(logZ, dtype=) if len(logZ.shape) is not 1: raise ValueError("logZ should be a 1D array") x = numpy.a...
Sanity-check the arguments for :func:`fgivenx.drivers.compute_samples`. Parameters ---------- f, x, samples, weights: see arguments for :func:`fgivenx.drivers.compute_samples`
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def flag_to_list(flagval, flagtype): if flagtype == : return [int(_) for _ in flagval.split() if _] elif flagtype == : return [float(_) for _ in flagval.split() if _] elif flagtype == : return [_ for _ in flagval.split() if _] else: raise Exception("incorrect type...
Convert a string of comma-separated tf flags to a list of values.
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def save(self): self._check_custom_fields() if not self._changes: return None for tag in self._remap_to_id: self._remap_tag_to_tag_id(tag, self._changes) for tag, type in self._field_type.items(): try: raw_data = se...
Save all changes on this item (if any) back to Redmine.
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def get_relation_cnt(self): ctr = cx.Counter() for ntgpad in self.associations: if ntgpad.Extension is not None: ctr += ntgpad.Extension.get_relations_cnt() return ctr
Return a Counter containing all relations contained in the Annotation Extensions.
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def _build_loss(self, lstm_outputs): batch_size = self.options[] unroll_steps = self.options[] n_tokens_vocab = self.options[] def _get_next_token_placeholders(suffix): name = + suffix id_placeholder = tf.placeholder(DTYPE_INT, ...
Create: self.total_loss: total loss op for training self.softmax_W, softmax_b: the softmax variables self.next_token_id / _reverse: placeholders for gold input
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def get_extra_context(site, ctx): ctx[] = site ctx[] = feeds = site.active_feeds.order_by() def get_mod_chk(k): mod, chk = ( (max(vals) if vals else None) for vals in ( filter(None, it.imap(op.attrgetter(k), feeds)) for k in [, ] ) ) chk = chk or datetime(1970, 1, 1, 0, 0, 0, 0, timezone.utc) c...
Returns extra data useful to the templates.
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def copyFileToHdfs(localFilePath, hdfsFilePath, hdfsClient, override=True): if not os.path.exists(localFilePath): raise Exception() if os.path.isdir(localFilePath): raise Exception() if hdfsClient.exists(hdfsFilePath): if override: hdfsClient.delete(hdfsFilePath) ...
Copy a local file to HDFS directory
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def simple_response(self, status, msg=): status = str(status) proto_status = % (self.server.protocol, status) content_length = % len(msg) content_type = buf = [ proto_status.encode(), content_length.encode(), content_type.encode(), ...
Write a simple response back to the client.
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def redirectURL(self, realm, return_to=None, immediate=False): message = self.getMessage(realm, return_to, immediate) return message.toURL(self.endpoint.server_url)
Returns a URL with an encoded OpenID request. The resulting URL is the OpenID provider's endpoint URL with parameters appended as query arguments. You should redirect the user agent to this URL. OpenID 2.0 endpoints also accept POST requests, see C{L{shouldSendRedirect}} and C...
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def is_response(cls, response): if response.body: if cls.is_file(response.body): return True
Return whether the document is likely to be a Sitemap.
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def check_update_J(self): self._J_update_counter += 1 update = self._J_update_counter >= self.update_J_frequency return update & (not self._fresh_JTJ)
Checks if the full J should be updated. Right now, just updates after update_J_frequency loops
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def parse_json_date(value): if not value: return None return datetime.datetime.strptime(value, JSON_DATETIME_FORMAT).replace(tzinfo=pytz.UTC)
Parses an ISO8601 formatted datetime from a string value
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def _initializer_for(self, raw_name: str, cooked_name: str, prefix: Optional[str]) -> List[str]: mt_val = self._ebnf.mt_value(self._typ) rval = [] if is_valid_python(raw_name): if prefix: rval.append(f"self.{raw_name} = {prefix}.{raw_name}")...
Create an initializer entry for the entry :param raw_name: name unadjusted for python compatibility. :param cooked_name: name that may or may not be python compatible :param prefix: owner of the element - used when objects passed as arguments :return: Initialization statements
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def columns(self): if self.df.empty: return None columns = [] sample_size = min(INFER_COL_TYPES_SAMPLE_SIZE, len(self.df.index)) sample = self.df if sample_size: sample = self.df.sample(sample_size) for col in self.df.dtypes.keys(): ...
Provides metadata about columns for data visualization. :return: dict, with the fields name, type, is_date, is_dim and agg.
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def get_num_chunks(length, chunksize): r n_chunks = int(math.ceil(length / chunksize)) return n_chunks
r""" Returns the number of chunks that a list will be split into given a chunksize. Args: length (int): chunksize (int): Returns: int: n_chunks CommandLine: python -m utool.util_progress --exec-get_num_chunks:0 Example0: >>> # ENABLE_DOCTEST >>...
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def create( cls, api_key=None, idempotency_key=None, stripe_account=None, **params ): url = cls.class_url() headers = populate_headers(idempotency_key) return make_request( cls, , url, stripe_account=stripe_account, headers=headers, params=params)
Return a deferred.
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def register_func_list(self, func_and_handler): for func, handler in func_and_handler: self._function_dispatch.register(func, handler) self.dispatch.cache_clear()
register a function to determine if the handle should be used for the type
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def candidate(self, cand_func, args=None, kwargs=None, name=, context=None): self._candidates.append({ : cand_func, : args or [], : kwargs or {}, : name, : context or {}, })
Adds a candidate function to an experiment. Can be used multiple times for multiple candidates. :param callable cand_func: your control function :param iterable args: positional arguments to pass to your function :param dict kwargs: keyword arguments to pass to your function :pa...
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def safe_unicode(obj, *args): try: return unicode(obj, *args) except UnicodeDecodeError: ascii_text = str(obj).encode() try: return unicode(ascii_text) except NameError: return obj
return the unicode representation of obj
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def libvlc_media_new_path(p_instance, path): f = _Cfunctions.get(, None) or \ _Cfunction(, ((1,), (1,),), class_result(Media), ctypes.c_void_p, Instance, ctypes.c_char_p) return f(p_instance, path)
Create a media for a certain file path. See L{libvlc_media_release}. @param p_instance: the instance. @param path: local filesystem path. @return: the newly created media or NULL on error.
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def http_time(time): return formatdate(timeval=mktime(time.timetuple()), localtime=False, usegmt=True)
Formats a datetime as an RFC 1123 compliant string.
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def get_cameras(self): response = api.request_homescreen(self) try: all_cameras = {} for camera in response[]: camera_network = str(camera[]) camera_name = camera[] camera_id = camera[] camera_info = {: came...
Retrieve a camera list for each onboarded network.
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def sensoryCompute(self, activeMinicolumns, learn): inputParams = { "activeColumns": activeMinicolumns, "basalInput": self.getLocationRepresentation(), "basalGrowthCandidates": self.getLearnableLocationRepresentation(), "learn": learn } self.L4.compute(**inputParams) locati...
@param activeMinicolumns (numpy array) List of indices of minicolumns to activate. @param learn (bool) If True, the two layers should learn this association. @return (tuple of dicts) Data for logging/tracing.
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def start_background_task(self, target, *args, **kwargs): return self.server.start_background_task(target, *args, **kwargs)
Start a background task using the appropriate async model. This is a utility function that applications can use to start a background task using the method that is compatible with the selected async mode. :param target: the target function to execute. :param args: arguments to ...
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def _build_url(self, endpoint): try: path = self.endpoints[endpoint] except KeyError: msg = raise ValueError(msg.format(endpoint)) absolute_url = urljoin(self.target, path) return absolute_url
Builds the absolute URL using the target and desired endpoint.
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def create_ebnf_parser(files): flag = False for belspec_fn in files: if config["bel"]["lang"]["specification_github_repo"]: tmpl_fn = get_ebnf_template() ebnf_fn = belspec_fn.replace(".yaml", ".ebnf") if not os.path.exists(ebnf_fn) or os.path.getmtime...
Create EBNF files and EBNF-based parsers
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def reply_count(self, url, mode=5, after=0): sql = [, , , , , ] return dict(self.db.execute(sql, [url, mode, mode, after]).fetchall())
Return comment count for main thread and all reply threads for one url.
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def check_venv(self): if self.zappa: venv = self.zappa.get_current_venv() else: venv = Zappa.get_current_venv() if not venv: raise ClickException( click.style("Zappa", bold=True) + " requires an " + click.style("active vir...
Ensure we're inside a virtualenv.
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def findExtNum(self, extname=None, extver=1): extnum = None extname = extname.upper() if not self._isSimpleFits: for ext in self._image: if (hasattr(ext,) and in ext._extension and (ext.extname == extname) and (ext.extver == extver)): ...
Find the extension number of the give extname and extver.
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def get(self, block=True, timeout=None): return self._queue.get(block, timeout)
Get item from underlying queue.
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def add(self, user, password): if self.__contains__(user): raise UserExists self.new_users[user] = self._encrypt_password(password) + "\n"
Adds a user with password
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def load_aead(self, public_id): connection = self.engine.connect() trans = connection.begin() try: s = sqlalchemy.select([self.aead_table]).where( (self.aead_table.c.public_id == public_id) & self.aead_table.c.keyhandle.in_([kh[1] for kh in s...
Loads AEAD from the specified database.
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def evaluate(ref_time, ref_freqs, est_time, est_freqs, **kwargs): scores = collections.OrderedDict() (scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[], scores[])...
Evaluate two multipitch (multi-f0) transcriptions, where the first is treated as the reference (ground truth) and the second as the estimate to be evaluated (prediction). Examples -------- >>> ref_time, ref_freq = mir_eval.io.load_ragged_time_series('ref.txt') >>> est_time, est_freq = mir_eval....
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def Enable(self, value): "enable or disable all top menus" for i in range(self.GetMenuCount()): self.EnableTop(i, value)
enable or disable all top menus
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def map_reduce(self, map_function, data, function_kwargs=None, chunk_size=None, data_length=None): if data_length is None: data_length = len(data) if not chunk_size: chunk_size = self.calculate_best_chunk_size(data_length) chunk_generator = self.partition(data,...
This method contains the core functionality of the DistributorBaseClass class. It maps the map_function to each element of the data and reduces the results to return a flattened list. How the jobs are calculated, is determined by the classes :func:`tsfresh.utilities.distribution.Distr...
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def dense(x, output_dim, reduced_dims=None, expert_dims=None, use_bias=True, activation=None, master_dtype=tf.float32, slice_dtype=tf.float32, variable_dtype=None, name=None): if variable_dtype is None: variable_dtype = mtf.VariableDType(master_dtype, slice_dty...
Dense layer doing (kernel*x + bias) computation. Args: x: a mtf.Tensor of shape [..., reduced_dims]. output_dim: a mtf.Dimension reduced_dims: an optional list of mtf.Dimensions of x to be reduced. If omitted, we reduce the last dimension. expert_dims: an optional list of mtf.Dimension which re...
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def reset_course_favorites(self): path = {} data = {} params = {} self.logger.debug("DELETE /api/v1/users/self/favorites/courses with query params: {params} and form data: {data}".format(params=params, data=data, **path)) return self.generic_request("DELETE", "/a...
Reset course favorites. Reset the current user's course favorites to the default automatically generated list of enrolled courses
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def changes(self): report = {} for k, k_changes in self._changes.items(): if len(k_changes) == 1: report[k] = k_changes[0] else: first = k_changes[0] last = k_changes[-1] if first.old_value != last.new_value...
Returns a mapping of items to their effective change objects which include the old values and the new. The mapping includes only items whose value or raw string value has changed in the context.
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def get_single_score(self, point, centroids=None, sd=None): normalised_point = array(point) / array(sd) observation_score = { : point, : normalised_point.tolist(), } distances = [ euclidean(normalised_point, centroid) for centroi...
Get a single score is a wrapper around the result of classifying a Point against a group of centroids. \ Attributes: observation_score (dict): Original received point and normalised point. :Example: >>> { "original": [0.40369016, 0.65217912], "normalised": [1.65915104,...
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def _graph_wrap(func, graph): @wraps(func) def _wrapped(*args, **kwargs): with graph.as_default(): return func(*args, **kwargs) return _wrapped
Constructs function encapsulated in the graph.
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def path_components(path): components = [] while True: (new_path, tail) = os.path.split(path) components.append(tail) if new_path == path: break path = new_path components.append(new_path) components.reverse() ...
Return the individual components of a given file path string (for the local operating system). Taken from https://stackoverflow.com/q/21498939/438386
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def make_forecasting_frame(x, kind, max_timeshift, rolling_direction): n = len(x) if isinstance(x, pd.Series): t = x.index else: t = range(n) df = pd.DataFrame({"id": ["id"] * n, "time": t, "value": x, "kind": ki...
Takes a singular time series x and constructs a DataFrame df and target vector y that can be used for a time series forecasting task. The returned df will contain, for every time stamp in x, the last max_timeshift data points as a new time series, such can be used to fit a time series forecasting model. ...
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def refactor_use_function(self, offset): try: refactor = UseFunction(self.project, self.resource, offset) except RefactoringError as e: raise Fault( .format(e), code=400 ) return self._get_changes(refactor)
Use the function at point wherever possible.
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def addGenotypePhenotypeSearchOptions(parser): parser.add_argument( "--phenotype_association_set_id", "-s", default=None, help="Only return associations from this phenotype_association_set.") parser.add_argument( "--feature_ids", "-f", default=None, help="Only return associa...
Adds options to a g2p searches command line parser.
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def execute_command_in_dir(command, directory, verbose=DEFAULTS[], prefix="Output: ", env=None): if os.name == : directory = os.path.normpath(directory) print_comment("Executing: (%s) in directory: %s" % (command, directory), verbose)...
Execute a command in specific working directory
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def as_nddata(self, nddata_class=None): "Return a version of ourself as an astropy.nddata.NDData object" if nddata_class is None: from astropy.nddata import NDData nddata_class = NDData ahdr = self.get_header() header = OrderedDict(ahdr.items()) ...
Return a version of ourself as an astropy.nddata.NDData object
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def options(self, context, module_options): self.contype = self.port = 5900 self.password = None if not in module_options: context.log.error() exit(1) if in module_options: self.contype = module_options[] if in modu...
CONTYPE Specifies the VNC connection type, choices are: reverse, bind (default: reverse). PORT VNC Port (default: 5900) PASSWORD Specifies the connection password.
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def CheckCStyleCast(filename, clean_lines, linenum, cast_type, pattern, error): line = clean_lines.elided[linenum] match = Search(pattern, line) if not match: return False context = line[0:match.start(1) - 1] if Match(r, context): return False if linenum > 0: for i in xrange(linenu...
Checks for a C-style cast by looking for the pattern. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. cast_type: The string for the C++ cast to recommend. This is either reinterpret_cast, static_...
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def add_request_handler_chain(self, request_handler_chain): if request_handler_chain is None or not isinstance( request_handler_chain, GenericRequestHandlerChain): raise DispatchException( "Request Handler Chain is not a GenericRequestHandlerChain " ...
Checks the type before adding it to the request_handler_chains instance variable. :param request_handler_chain: Request Handler Chain instance. :type request_handler_chain: RequestHandlerChain :raises: :py:class:`ask_sdk_runtime.exceptions.DispatchException` if a null input...
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def delete_servers(*servers, **options): *** test = options.pop(, False) commit = options.pop(, True) return __salt__[](, servers=servers, test=test, commit=commit, ...
Removes NTP servers configured on the device. :param servers: list of IP Addresses/Domain Names to be removed as NTP servers :param test (bool): discard loaded config. By default ``test`` is False (will not dicard the changes) :param commit (bool): commit loaded config. By default ``commit`...
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def makedirs(self, path, mode=0x777): "Super-mkdir: create a leaf directory and all intermediate ones." self.directory_create(path, mode, [library.DirectoryCreateFlag.parents])
Super-mkdir: create a leaf directory and all intermediate ones.
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def is_provider_configured(opts, provider, required_keys=(), log_message=True, aliases=()): if in provider: alias, driver = provider.split() if alias not in opts[]: return False if driver not in opts[][alias]: return False for key in required_keys: ...
Check and return the first matching and fully configured cloud provider configuration.
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def addFeature(self, f, conflict="error", missing="other"): OPTIONS = ["error", "ignore", "me", "other"] assert missing in OPTIONS, "Invalid value in `missing`." assert conflict in OPTIONS, "Invalid value in `missing`." if f.prop not in self.props and missing == "error": ...
Add a feature. Args: - f(Feature): feature to add. - conflict(str): if a property hasn't compatible values/constrains, do: - ``"error"``: raise exception. - ``"ignore"``: go on. - ``"me"``: keep the old value. - ``"other"``: set the passed value. ...
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def _compute_include_paths(self, target): paths = OrderedSet() paths.add(os.path.join(get_buildroot(), target.target_base)) def collect_paths(dep): if not dep.has_sources(): return paths.add(os.path.join(get_buildroot(), dep.target_base)) collect_paths(target) target.walk(...
Computes the set of paths that thrifty uses to lookup imports. The IDL files under these paths are not compiled, but they are required to compile downstream IDL files. :param target: the JavaThriftyLibrary target to compile. :return: an ordered set of directories to pass along to thrifty.
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def edit_team_push_restrictions(self, *teams): assert all(isinstance(element, (str, unicode)) or isinstance(element, (str, unicode)) for element in teams), teams headers, data = self._requester.requestJsonAndCheck( "POST", self.protection_url + "/restrictions/teams", ...
:calls: `POST /repos/:owner/:repo/branches/:branch/protection/restrictions <https://developer.github.com/v3/repos/branches>`_ :teams: list of strings
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def grant_user_access(self, user, db_names, strict=True): user = utils.get_name(user) uri = "/%s/%s/databases" % (self.uri_base, user) db_names = self._get_db_names(db_names, strict=strict) dbs = [{"name": db_name} for db_name in db_names] body = {"databases": dbs} ...
Gives access to the databases listed in `db_names` to the user. You may pass in either a single db or a list of dbs. If any of the databases do not exist, a NoSuchDatabase exception will be raised, unless you specify `strict=False` in the call.
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def beta_diversity(self, metric="braycurtis", rank="auto"): if metric not in ("jaccard", "braycurtis", "cityblock"): raise OneCodexException( "For beta diversity, metric must be one of: jaccard, braycurtis, cityblock" ) if self._guess_normalized...
Calculate the diversity between two communities. Parameters ---------- metric : {'jaccard', 'braycurtis', 'cityblock'} The distance metric to calculate. rank : {'auto', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'}, optional Analysis will b...
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def read_json(self): with reading_ancillary_files(self): metadata = super(ImpactLayerMetadata, self).read_json() if in metadata: for provenance_step in metadata[]: try: title = provenance_step[] ...
read metadata from json and set all the found properties. :return: the read metadata :rtype: dict
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def angleDiff(angle1, angle2, take_smaller=True): a = np.arctan2(np.sin(angle1 - angle2), np.cos(angle1 - angle2)) if isinstance(a, np.ndarray) and take_smaller: a = np.abs(a) ab = np.abs(np.pi - a) with np.errstate(invalid=): i = a > ab a[i] = ab[i] ...
smallest difference between 2 angles code from http://stackoverflow.com/questions/1878907/the-smallest-difference-between-2-angles
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def get_default_jvm_opts(tmp_dir=None, parallel_gc=False): opts = ["-XX:+UseSerialGC"] if not parallel_gc else [] if tmp_dir: opts.append("-Djava.io.tmpdir=%s" % tmp_dir) return opts
Retrieve default JVM tuning options Avoids issues with multiple spun up Java processes running into out of memory errors. Parallel GC can use a lot of cores on big machines and primarily helps reduce task latency and responsiveness which are not needed for batch jobs. https://github.com/bcbio/bcbio-nex...
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def get_structure_by_id(self, cod_id, **kwargs): r = requests.get("http://www.crystallography.net/cod/%s.cif" % cod_id) return Structure.from_str(r.text, fmt="cif", **kwargs)
Queries the COD for a structure by id. Args: cod_id (int): COD id. kwargs: All kwargs supported by :func:`pymatgen.core.structure.Structure.from_str`. Returns: A Structure.
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def dec(self,*args,**kwargs): _check_roSet(self,kwargs,) radec= self._radec(*args,**kwargs) return radec[:,1]
NAME: dec PURPOSE: return the declination INPUT: t - (optional) time at which to get dec obs=[X,Y,Z] - (optional) position of observer (in kpc) (default=Object-wide default) OR Orbit object that corresponds to...
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def record_process(self, process, prg=): self._log(self.logFileProcess, force_to_string(process), prg)
log a process or program - log a physical program (.py, .bat, .exe)
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def put_container(self, path): path = make_path(path) container = self for segment in path: try: container = container._values[segment] if not isinstance(container, ValueTree): raise ValueError() except KeyError...
Creates a container at the specified path, creating any necessary intermediate containers. :param path: str or Path instance :raises ValueError: A component of path is a field name.
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def MAKE_WPARAM(wParam): wParam = ctypes.cast(wParam, LPVOID).value if wParam is None: wParam = 0 return wParam
Convert arguments to the WPARAM type. Used automatically by SendMessage, PostMessage, etc. You shouldn't need to call this function.
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def _build_dependent_model_list(self, obj_schema): dep_models_list = [] if obj_schema: obj_schema[] = obj_schema.get(, ) if obj_schema[] == : dep_models_list.extend(self._build_dependent_model_list(obj_schema.get(, {}))) else: ref = obj_schem...
Helper function to build the list of models the given object schema is referencing.
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def set_learning_rate(self, lr): if not isinstance(self._optimizer, opt.Optimizer): raise UserWarning("Optimizer has to be defined before its learning " "rate is mutated.") else: self._optimizer.set_learning_rate(lr)
Sets a new learning rate of the optimizer. Parameters ---------- lr : float The new learning rate of the optimizer.
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def unquote(s): res = s.split() if len(res) == 1: return s s = res[0] for item in res[1:]: try: s += _hextochr[item[:2]] + item[2:] except KeyError: s += + item except UnicodeDecodeError: s += chr(int(item[:2], 16)) + item[2:...
unquote('abc%20def') -> 'abc def'.
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def print_multi_line(content, force_single_line, sort_key): global last_output_lines global overflow_flag global is_atty if not is_atty: if isinstance(content, list): for line in content: print(line) elif isinstance(content, dict): for k, v ...
'sort_key' 参数只在 dict 模式时有效 'sort_key' parameter only available in 'dict' mode
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def uploadFiles(self): for each_file in self.filesToSync: self.uploadFile(each_file["name"], each_file["ispickle"], each_file["at_home"])
Uploads all the files in 'filesToSync'
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def _compute_closed_central_moments(self, central_from_raw_exprs, n_counter, k_counter): n_species = len([None for pm in k_counter if pm.order == 1]) covariance_matrix = sp.Matrix(n_species, n_species, lambda x,y: self._get_covariance_symbol(n_counter,x,y)) positive_n_counter = [n for n...
Computes parametric expressions (e.g. in terms of mean, variance, covariances) for all central moments up to max_order + 1 order. :param central_from_raw_exprs: :param n_counter: a list of :class:`~means.core.descriptors.Moment`\s representing central moments :type n_counter: list[:clas...
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def compute_lower_upper_errors(sample, num_sigma=1): if num_sigma > 3: raise ValueError("Number of sigma-constraints restircted to three. %s not valid" % num_sigma) num = len(sample) num_threshold1 = int(round((num-1)*0.833)) num_threshold2 = int(round((num-1)*0.977249868)) num_threshol...
computes the upper and lower sigma from the median value. This functions gives good error estimates for skewed pdf's :param sample: 1-D sample :return: median, lower_sigma, upper_sigma
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def last(args, dbtype=None): p = OptionParser(last.__doc__) p.add_option("--dbtype", default="nucl", choices=("nucl", "prot"), help="Molecule type of subject database") p.add_option("--path", help="Specify LAST path") p.add_option("--mask", default=False, action="s...
%prog database.fasta query.fasta Run LAST by calling LASTDB and LASTAL. LAST program available: <http://last.cbrc.jp> Works with LAST-719.
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def record(self): if not self._initialized: raise pycdlibexception.PyCdlibInternalError() return struct.pack(self.FMT, self.extent_length, self.log_block_num, self.part_ref_num, self.impl_use)
A method to generate the string representing this UDF Long AD. Parameters: None. Returns: A string representing this UDF Long AD.
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def _getID(self): id = [] for key in self._sqlPrimary: value = self.__dict__[key] if isinstance(value, Forgetter): value.save() try: (value,) = value._getID() except: ...
Get the ID values as a tuple annotated by sqlPrimary
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def getSystemVariable(self, remote, name): if self._server is not None: return self._server.getSystemVariable(remote, name)
Get single system variable from CCU / Homegear
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def point_image_value(image, xy, scale=1): return getinfo(ee.Image(image).reduceRegion( reducer=ee.Reducer.first(), geometry=ee.Geometry.Point(xy), scale=scale))
Extract the output value from a calculation at a point
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def rename_categories(self, new_categories, inplace=False): inplace = validate_bool_kwarg(inplace, ) cat = self if inplace else self.copy() if isinstance(new_categories, ABCSeries): msg = ("Treating Series as a list-like and using " "the values. In a fut...
Rename categories. Parameters ---------- new_categories : list-like, dict-like or callable * list-like: all items must be unique and the number of items in the new categories must match the existing number of categories. * dict-like: specifies a mapping from...
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def create_expanded_design_for_mixing(design, draw_list, mixing_pos, rows_to_mixers): if len(mixing_pos) != len(draw_list): msg = "mixing_pos == {}".format(mixing_pos) msg_2 = "len(...
Parameters ---------- design : 2D ndarray. All elements should be ints, floats, or longs. Each row corresponds to an available alternative for a given individual. There should be one column per index coefficient being estimated. draw_list : list of 2D ndarrays. All numpy arra...
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def tag(self, sbo): sbo_name = "-".join(sbo.split("-")[:-1]) find = GetFromInstalled(sbo_name).name() if find_package(sbo, self.meta.pkg_path): paint = self.meta.color["GREEN"] self.count_ins += 1 if "--rebuild" in self.flag: ...
Tag with color green if package already installed, color yellow for packages to upgrade and color red if not installed.
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def register_variable(self, v, key, eternal=True): if type(key) is not tuple: raise TypeError("Variable tracking key must be a tuple") if eternal: self.eternal_tracked_variables[key] = v else: self.temporal_tracked_variables = dict(self.temporal_track...
Register a value with the variable tracking system :param v: The BVS to register :param key: A tuple to register the variable under :parma eternal: Whether this is an eternal variable, default True. If False, an incrementing counter will be appended to the key.
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def publish_extensions(self, handler): if isinstance(self.media_content, list): [PyRSS2Gen._opt_element(handler, "media:content", mc_element) for mc_element in self.media_content] else: PyRSS2Gen._opt_element(handler, "media:content", ...
Publish the Media RSS Feed elements as XML.
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def _count(self, X, Y): self.feature_count_ += safe_sparse_dot(Y.T, X) self.class_count_ += Y.sum(axis=0)
Count and smooth feature occurrences.
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def get_commit_req(self): if not self.commit_req: self.commit_req = datastore.CommitRequest() self.commit_req.transaction = self.tx return self.commit_req
Lazy commit request getter.
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def _format_return_timestamps(self, return_timestamps=None): if return_timestamps is None: return_timestamps_array = np.arange( self.components.initial_time(), self.components.final_time() + self.components.saveper(), ...
Format the passed in return timestamps value as a numpy array. If no value is passed, build up array of timestamps based upon model start and end times, and the 'saveper' value.
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def json_2_team(json_obj): LOGGER.debug("Team.json_2_team") return Team(teamid=json_obj[], name=json_obj[], description=json_obj[], color_code=json_obj[], app_ids=json_obj[], osi_ids=json_obj[])
transform JSON obj coming from Ariane to ariane_clip3 object :param json_obj: the JSON obj coming from Ariane :return: ariane_clip3 Team object
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def canonic(self, file_name): if file_name == "<" + file_name[1:-1] + ">": return file_name c_file_name = self.file_name_cache.get(file_name) if not c_file_name: c_file_name = os.path.abspath(file_name) c_file_name = os.path.normcase(c_file_name) ...
returns canonical version of a file name. A canonical file name is an absolute, lowercase normalized path to a given file.
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def filter_dict_by_key(d, keys): return {k: v for k, v in d.items() if k in keys}
Filter the dict *d* to remove keys not in *keys*.
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def list(self, device_path, timeout_ms=None): return self.filesync_service.list( device_path, timeouts.PolledTimeout.from_millis(timeout_ms))
Yield filesync_service.DeviceFileStat objects for directory contents.
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def scale(self, new_volume: float) -> "Lattice": versors = self.matrix / self.abc geo_factor = abs(dot(np.cross(versors[0], versors[1]), versors[2])) ratios = np.array(self.abc) / self.c new_c = (new_volume / (geo_factor * np.prod(ratios))) ** (1 / 3.0) return Lattic...
Return a new Lattice with volume new_volume by performing a scaling of the lattice vectors so that length proportions and angles are preserved. Args: new_volume: New volume to scale to. Returns: New lattice with desired volume.
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def _validate_apns_certificate(self, certfile): try: with open(certfile, "r") as f: content = f.read() check_apns_certificate(content) except Exception as e: raise ImproperlyConfigured( "The APNS certificate file at %r is not readable: %s" % (certfile, e) )
Validate the APNS certificate at startup.
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async def inject_request_id(app, handler): async def trace_request(request): request[] = \ request.headers.get() or str(uuid.uuid4()) return await handler(request) return trace_request
aiohttp middleware: ensures each request has a unique request ID. See: ``inject_request_id``.
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def clear_cached_authc_info(self, identifier): msg = "Clearing cached authc_info for [{0}]".format(identifier) logger.debug(msg) self.cache_handler.delete( + self.name, identifier)
When cached credentials are no longer needed, they can be manually cleared with this method. However, account credentials may be cached with a short expiration time (TTL), making the manual clearing of cached credentials an alternative use case. :param identifier: the identifier of a s...
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def is_propagating(self, images, augmenter, parents, default): if self.propagator is None: return default else: return self.propagator(images, augmenter, parents, default)
Returns whether an augmenter may call its children to augment an image. This is independent of the augmenter itself possible changing the image, without calling its children. (Most (all?) augmenters with children currently dont perform any changes themselves.) Returns ------- ...
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def size_changed(self, settings, key, user_data): RectCalculator.set_final_window_rect(self.settings, self.guake.window)
If the gconf var window_height or window_width are changed, this method will be called and will call the resize function in guake.