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def get_connection(self, host, port): log.debug(" self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) self.sock.settimeout(self.sock_connect_timeout / 1000) self.sock.connect((host, port)) self.sock.settimeout(self.sock_request_timeout / 1000) self.write(self.RPC_HEADER) self.write(struct.pack(, self.version)) self.write(struct.pack(, self.RPC_SERVICE_CLASS)) if self.use_sasl: self.write(struct.pack(, self.AUTH_PROTOCOL_SASL)) else: self.write(struct.pack(, self.AUTH_PROTOCOL_NONE)) if self.use_sasl: sasl = SaslRpcClient(self, hdfs_namenode_principal=self.hdfs_namenode_principal) sasl_connected = sasl.connect() if not sasl_connected: raise TransientException("SASL is configured, but cannot get connected") rpc_header = self.create_rpc_request_header() context = self.create_connection_context() header_length = len(rpc_header) + encoder._VarintSize(len(rpc_header)) +len(context) + encoder._VarintSize(len(context)) if log.getEffectiveLevel() == logging.DEBUG: log.debug("Header length: %s (%s)" % (header_length, format_bytes(struct.pack(, header_length)))) self.write(struct.pack(, header_length)) self.write_delimited(rpc_header) self.write_delimited(context)
Open a socket connection to a given host and port and writes the Hadoop header The Hadoop RPC protocol looks like this when creating a connection: +---------------------------------------------------------------------+ | Header, 4 bytes ("hrpc") | +---------------------------------------------------------------------+ | Version, 1 byte (default verion 9) | +---------------------------------------------------------------------+ | RPC service class, 1 byte (0x00) | +---------------------------------------------------------------------+ | Auth protocol, 1 byte (Auth method None = 0) | +---------------------------------------------------------------------+ | Length of the RpcRequestHeaderProto + length of the | | of the IpcConnectionContextProto (4 bytes/32 bit int) | +---------------------------------------------------------------------+ | Serialized delimited RpcRequestHeaderProto | +---------------------------------------------------------------------+ | Serialized delimited IpcConnectionContextProto | +---------------------------------------------------------------------+
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def get_name_DID_info(self, name): db = get_db_state(self.working_dir) did_info = db.get_name_DID_info(name) if did_info is None: return {: , : 404} return did_info
Get a name's DID info Returns None if not found
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def ColorWithLightness(self, lightness): h, s, l = self.__hsl return Color((h, s, lightness), , self.__a, self.__wref)
Create a new instance based on this one with a new lightness value. Parameters: :lightness: The lightness of the new color [0...1]. Returns: A grapefruit.Color instance. >>> Color.NewFromHsl(30, 1, 0.5).ColorWithLightness(0.25) (0.5, 0.25, 0.0, 1.0) >>> Color.NewFromHsl(30, 1, 0.5).ColorWithLightness(0.25).hsl (30, 1, 0.25)
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def _cast_float(temp_dt): if type(temp_dt) == str: fmt = base_dt = temp_dt[0:19] tz_offset = eval(temp_dt[19:22]) temp_dt = datetime.datetime.strptime(base_dt, fmt) - \ datetime.timedelta(hours=tz_offset) return (temp_dt - datetime.datetime(1970, 1, 1)).total_seconds()
returns utc timestamp
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def unique_str(self): unique_str = "_".join(["%.3f" % f for f in self.geotransform] + ["%d" % d for d in self.x_size, self.y_size] ) if self.date is not None: unique_str += + str(self.date) if self.time is not None: unique_str += + str(self.time) return unique_str.replace(, )
A string that (ideally) uniquely represents this GC object. This helps with naming files for caching. 'Unique' is defined as 'If GC1 != GC2, then GC1.unique_str() != GC2.unique_str()'; conversely, 'If GC1 == GC2, then GC1.unique_str() == GC2.unique_str()'. The string should be filename-safe (no \/:*?"<>|). ..note::Because of length/readability restrictions, this fxn ignores wkt. Example output: "-180.000_0.250_0.000_90.000_0.000_-0.251_512_612_2013-05-21_12_32_52.945000"
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def idf(self, term, transform=None): r docs_with_term = 0 docs = self.docs_of_words() for doc in docs: doc_set = set(doc) if transform: transformed_doc = [] for word in doc_set: transformed_doc.append(transform(word)) doc_set = set(transformed_doc) if term in doc_set: docs_with_term += 1 if docs_with_term == 0: return float() return log10(len(docs) / docs_with_term)
r"""Calculate the Inverse Document Frequency of a term in the corpus. Parameters ---------- term : str The term to calculate the IDF of transform : function A function to apply to each document term before checking for the presence of term Returns ------- float The IDF Examples -------- >>> tqbf = 'The quick brown fox jumped over the lazy dog.\n\n' >>> tqbf += 'And then it slept.\n\n And the dog ran off.' >>> corp = Corpus(tqbf) >>> print(corp.docs()) [[['The', 'quick', 'brown', 'fox', 'jumped', 'over', 'the', 'lazy', 'dog.']], [['And', 'then', 'it', 'slept.']], [['And', 'the', 'dog', 'ran', 'off.']]] >>> round(corp.idf('dog'), 10) 0.4771212547 >>> round(corp.idf('the'), 10) 0.1760912591
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def ev_to_s(offset_us, source_to_detector_m, array): time_s = np.sqrt(81.787 / (array * 1000.)) * source_to_detector_m / 3956. time_record_s = time_s - offset_us * 1e-6 return time_record_s
convert energy (eV) to time (us) Parameters: =========== array: array (in eV) offset_us: float. Delay of detector in us source_to_detector_m: float. Distance source to detector in m Returns: ======== time: array in s
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def step1(self, username, password): self._check_initialized() context = AtvSRPContext( str(username), str(password), prime=constants.PRIME_2048, generator=constants.PRIME_2048_GEN) self.session = SRPClientSession( context, binascii.hexlify(self._auth_private).decode())
First authentication step.
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def mass_tot(self, rho0, Rs): m_tot = 2*np.pi*rho0*Rs**3 return m_tot
total mass within the profile :param rho0: :param a: :param s: :return:
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def list_commands(self, ctx): rv = [] files = [_ for _ in next(os.walk(self.folder))[2] if not _.startswith("_") and _.endswith(".py")] for filename in files: rv.append(filename[:-3]) rv.sort() return rv
List commands from folder.
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def query_string(cls, query, default_field=None, default_operator=None, analyzer=None, allow_leading_wildcard=None, lowercase_expanded_terms=None, enable_position_increments=None, fuzzy_prefix_length=None, fuzzy_min_sim=None, phrase_slop=None, boost=None, analyze_wildcard=None, auto_generate_phrase_queries=None, minimum_should_match=None): this AND that OR thuscontent instance = cls(query_string={: query}) if default_field is not None: instance[][] = default_field if default_operator is not None: instance[][] = default_operator if analyzer is not None: instance[][] = analyzer if allow_leading_wildcard is not None: instance[][] = allow_leading_wildcard if lowercase_expanded_terms is not None: instance[][] = lowercase_expanded_terms if enable_position_increments is not None: instance[][] = enable_position_increments if fuzzy_prefix_length is not None: instance[][] = fuzzy_prefix_length if fuzzy_min_sim is not None: instance[][] = fuzzy_min_sim if phrase_slop is not None: instance[][] = phrase_slop if boost is not None: instance[][] = boost if analyze_wildcard is not None: instance[][] = analyze_wildcard if auto_generate_phrase_queries is not None: instance[][] = auto_generate_phrase_queries if minimum_should_match is not None: instance[][] = minimum_should_match return instance
http://www.elasticsearch.org/guide/reference/query-dsl/query-string-query.html A query that uses a query parser in order to parse its content. > query = ElasticQuery().query_string('this AND that OR thus', default_field='content')
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def get(self, fragment_info): if not self.is_cached(fragment_info): raise KeyError(u"Attempt to get text not cached") return self.cache[fragment_info]
Get the value associated with the given key. :param fragment_info: the text key :type fragment_info: tuple of str ``(language, text)`` :raises: KeyError if the key is not present in the cache
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def __package_app(tasks_pkg, dist_dir, custom_main=None, extra_data=None): logging.info() tasks_dir_splits = os.path.split(os.path.realpath(tasks_pkg)) shutil.make_archive(os.path.join(dist_dir, ), , tasks_dir_splits[0], tasks_dir_splits[1]) if custom_main is None: from . import _main main_path = _main.__file__ if main_path[-3:] == : main_path = main_path[:-1] shutil.copy(os.path.realpath(main_path), os.path.join(dist_dir, )) else: shutil.copy(os.path.realpath(custom_main), os.path.join(dist_dir, )) shutil.make_archive(os.path.join(dist_dir, ), , os.path.join(os.path.dirname(os.path.realpath(__file__)), , ), ) if extra_data: for dat in extra_data: real_path = os.path.realpath(dat) target = os.path.join(dist_dir, os.path.split(real_path)[1]) if os.path.isfile(real_path): shutil.copy(real_path, target) elif os.path.isdir(real_path): shutil.copytree(real_path, target) else: raise IOError( % (dat, real_path))
Packages the `tasks_pkg` (as zip) to `dist_dir`. Also copies the 'main' python file to `dist_dir`, to be submitted to spark. Same for `extra_data`. Parameters ---------- tasks_pkg (str): Path to the python package containing tasks dist_dir (str): Path to the directory where the packaged code should be stored custom_main (str): Path to a custom 'main' python file. extra_data (List[str]): List containing paths to files/directories that should also be packaged and submitted to spark
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def parse_spec(spec, relative_to=None, subproject_roots=None): def normalize_absolute_refs(ref): return strip_prefix(ref, ) subproject = longest_dir_prefix(relative_to, subproject_roots) if subproject_roots else None def prefix_subproject(spec_path): if not subproject: return spec_path elif spec_path: return os.path.join(subproject, spec_path) else: return os.path.normpath(subproject) spec_parts = spec.rsplit(, 1) if len(spec_parts) == 1: default_target_spec = spec_parts[0] spec_path = prefix_subproject(normalize_absolute_refs(default_target_spec)) target_name = os.path.basename(spec_path) else: spec_path, target_name = spec_parts if not spec_path and relative_to: spec_path = fast_relpath(relative_to, subproject) if subproject else relative_to spec_path = prefix_subproject(normalize_absolute_refs(spec_path)) return spec_path, target_name
Parses a target address spec and returns the path from the root of the repo to this Target and Target name. :API: public :param string spec: Target address spec. :param string relative_to: path to use for sibling specs, ie: ':another_in_same_build_family', interprets the missing spec_path part as `relative_to`. :param list subproject_roots: Paths that correspond with embedded build roots under the current build root. For Example:: some_target(name='mytarget', dependencies=['path/to/buildfile:targetname'] ) Where ``path/to/buildfile:targetname`` is the dependent target address spec In case the target name is empty it returns the last component of the path as target name, ie:: spec_path, target_name = parse_spec('path/to/buildfile/foo') Will return spec_path as 'path/to/buildfile/foo' and target_name as 'foo'. Optionally, specs can be prefixed with '//' to denote an absolute spec path. This is normally not significant except when a spec referring to a root level target is needed from deeper in the tree. For example, in ``path/to/buildfile/BUILD``:: some_target(name='mytarget', dependencies=[':targetname'] ) The ``targetname`` spec refers to a target defined in ``path/to/buildfile/BUILD*``. If instead you want to reference ``targetname`` in a root level BUILD file, use the absolute form. For example:: some_target(name='mytarget', dependencies=['//:targetname'] )
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def validate_hier_intervals(intervals_hier): label_top = util.generate_labels(intervals_hier[0]) boundaries = set(util.intervals_to_boundaries(intervals_hier[0])) for level, intervals in enumerate(intervals_hier[1:], 1): label_current = util.generate_labels(intervals) validate_structure(intervals_hier[0], label_top, intervals, label_current) new_bounds = set(util.intervals_to_boundaries(intervals)) if boundaries - new_bounds: warnings.warn( .format(level)) boundaries |= new_bounds
Validate a hierarchical segment annotation. Parameters ---------- intervals_hier : ordered list of segmentations Raises ------ ValueError If any segmentation does not span the full duration of the top-level segmentation. If any segmentation does not start at 0.
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def _parse_caption(self, node, state): if node.tag not in ["caption", "figcaption"]: return state parent = state["parent"][node] stable_id = ( f"{state[].name}" f"::" f"{}" f":" f"{state[][]}" ) name = node.attrib["name"] if "name" in node.attrib else None if isinstance(parent, Table): state["context"][node] = Caption( document=state["document"], table=parent, figure=None, stable_id=stable_id, name=name, position=state["caption"]["idx"], ) elif isinstance(parent, Figure): state["context"][node] = Caption( document=state["document"], table=None, figure=parent, stable_id=stable_id, name=name, position=state["caption"]["idx"], ) else: raise NotImplementedError("Caption must be a child of Table or Figure.") state["caption"]["idx"] += 1 return state
Parse a Caption of the node. :param node: The lxml node to parse :param state: The global state necessary to place the node in context of the document as a whole.
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def guest_inspect_stats(self, userid_list): if not isinstance(userid_list, list): userid_list = [userid_list] action = "get the statistics of guest " % str(userid_list) with zvmutils.log_and_reraise_sdkbase_error(action): return self._monitor.inspect_stats(userid_list)
Get the statistics including cpu and mem of the guests :param userid_list: a single userid string or a list of guest userids :returns: dictionary describing the cpu statistics of the vm in the form {'UID1': { 'guest_cpus': xx, 'used_cpu_time_us': xx, 'elapsed_cpu_time_us': xx, 'min_cpu_count': xx, 'max_cpu_limit': xx, 'samples_cpu_in_use': xx, 'samples_cpu_delay': xx, 'used_mem_kb': xx, 'max_mem_kb': xx, 'min_mem_kb': xx, 'shared_mem_kb': xx }, 'UID2': { 'guest_cpus': xx, 'used_cpu_time_us': xx, 'elapsed_cpu_time_us': xx, 'min_cpu_count': xx, 'max_cpu_limit': xx, 'samples_cpu_in_use': xx, 'samples_cpu_delay': xx, 'used_mem_kb': xx, 'max_mem_kb': xx, 'min_mem_kb': xx, 'shared_mem_kb': xx } } for the guests that are shutdown or not exist, no data returned in the dictionary
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def read (self, size = -1): if size == 0: return self._empty_buffer if size < 0: self.expect (self.delimiter) return self.before if self._buffer_type is bytes: pat = (u % size).encode() else: pat = u % size cre = re.compile(pat, re.DOTALL) index = self.expect ([cre, self.delimiter]) if index == 0: return self.after return self.before
This reads at most "size" bytes from the file (less if the read hits EOF before obtaining size bytes). If the size argument is negative or omitted, read all data until EOF is reached. The bytes are returned as a string object. An empty string is returned when EOF is encountered immediately.
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async def event_wait(event: asyncio.Event, timeout=None): if timeout is None: await event.wait() return True try: await asyncio.wait_for(event.wait(), timeout) except asyncio.TimeoutError: return False return True
Wait on an an asyncio event with an optional timeout Returns: true if the event got set, None if timed out
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def parse_peddy_csv(self, f, pattern): parsed_data = dict() headers = None s_name_idx = None for l in f[].splitlines(): s = l.split(",") if headers is None: headers = s try: s_name_idx = [headers.index("sample_id")] except ValueError: try: s_name_idx = [headers.index("sample_a"), headers.index("sample_b")] except ValueError: log.warn("Could not find sample name in Peddy output: {}".format(f[])) return None else: s_name = .join([s[idx] for idx in s_name_idx]) parsed_data[s_name] = dict() for i, v in enumerate(s): if i not in s_name_idx: if headers[i] == "error" and pattern == "sex_check": v = "True" if v == "False" else "False" try: parsed_data[s_name][headers[i] + "_" + pattern] = float(v) except ValueError: parsed_data[s_name][headers[i] + "_" + pattern] = v if len(parsed_data) == 0: return None return parsed_data
Parse csv output from peddy
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def __generate(self): base = [] texted = [] for pat in ALL_PATTERNS: data = pat.copy() data[] = data[] data[] = True data[] = data[] base.append(data) data = pat.copy() data[] = data[] data[] += data[] = True data[] = data[] + Optional(Literal(",")).suppress() + BASE_TIME_PATTERNS[] data[] = data[] = { : data[][] + 5, : data[][] + 8} base.append(data) data = pat.copy() data[] = data[] data[] = True data[] += data[] = data[] + Optional(oneOf([, ])).suppress() + BASE_TIME_PATTERNS[] data[] = data[] = { : data[][] + 9, : data[][] + 9} base.append(data) for pat in base: data = pat.copy() data[] += data[] = lineStart + data[] + Optional(oneOf([, , , ])).suppress() + restOfLine.suppress() data[] = { : data[][] + 1, : data[][] + 90} texted.append(data) base.extend(texted) self.patterns = base
Generates dates patterns
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def fmtval(value, colorstr=None, precision=None, spacing=True, trunc=True, end=): colwidth = opts.colwidth if precision is None: precision = opts.precision fmt = % precision result = locale.format(fmt, value, True) if spacing: result = % colwidth % result if trunc: if len(result) > colwidth: result = truncstr(result, colwidth) if opts.incolor and colorstr: return colorstr % result + end else: return result + end
Formats and returns a given number according to specifications.
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def _combine_ranges_on_length(self, data_len, first, second): first = get_true_slice(first, data_len) second = get_true_slice(second, data_len) final_start, final_step, final_stop = (None, None, None) if first.start == None and second.start == None: final_start = None else: final_start = (first.start if first.start else 0)+(second.start if second.start else 0) if second.stop == None: final_stop = first.stop elif first.stop == None: final_stop = (first.start if first.start else 0) + second.stop else: final_stop = min(first.stop, (first.start if first.start else 0) + second.stop) if first.step == None and second.step == None: final_step = None else: final_step = (first.step if first.step else 1)*(second.step if second.step else 1) if final_start > final_stop: final_start = final_stop return slice(final_start, final_stop, final_step)
Combines a first range with a second range, where the second range is considered within the scope of the first.
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def handle(self, message): opcode = message[] if opcode == 10: self.on_hello(message) elif opcode == 11: self.on_heartbeat(message) elif opcode == 0: self.on_message(message) else: logger.debug("Not a message we handle: OPCODE {}".format(opcode)) return
Dispatches messages to appropriate handler based on opcode Args: message (dict): Full message from Discord websocket connection
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def usable_id(cls, id): try: qry_id = int(id) except Exception: qry_id = None if not qry_id: msg = % id cls.error(msg) return qry_id
Retrieve id from input which can be num or id.
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def fit_tomography_data(tomo_data, method=, options=None): if isinstance(method, str) and method.lower() in [, ]: trace = __get_option(, options) beta = __get_option(, options) rho = __leastsq_fit(tomo_data, trace=trace, beta=beta) if method == : epsilon = __get_option(, options) rho = __wizard(rho, epsilon=epsilon) return rho else: raise Exception( % method)
Reconstruct a density matrix or process-matrix from tomography data. If the input data is state_tomography_data the returned operator will be a density matrix. If the input data is process_tomography_data the returned operator will be a Choi-matrix in the column-vectorization convention. Args: tomo_data (dict): process tomography measurement data. method (str): the fitting method to use. Available methods: - 'wizard' (default) - 'leastsq' options (dict or None): additional options for fitting method. Returns: numpy.array: The fitted operator. Available methods: - 'wizard' (Default): The returned operator will be constrained to be positive-semidefinite. Options: - 'trace': the trace of the returned operator. The default value is 1. - 'beta': hedging parameter for computing frequencies from zero-count data. The default value is 0.50922. - 'epsilon: threshold for truncating small eigenvalues to zero. The default value is 0 - 'leastsq': Fitting without positive-semidefinite constraint. Options: - 'trace': Same as for 'wizard' method. - 'beta': Same as for 'wizard' method. Raises: Exception: if the `method` parameter is not valid.
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def respond_via_request(self, task): warn(f"Detected slow response into webhook. " f"(Greater than {RESPONSE_TIMEOUT} seconds)\n" f"Recommended to use decorator from Dispatcher for handler with long timeouts.", TimeoutWarning) dispatcher = self.get_dispatcher() loop = dispatcher.loop try: results = task.result() except Exception as e: loop.create_task( dispatcher.errors_handlers.notify(dispatcher, types.Update.get_current(), e)) else: response = self.get_response(results) if response is not None: asyncio.ensure_future(response.execute_response(dispatcher.bot), loop=loop)
Handle response after 55 second. :param task: :return:
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def to_python(self,value): if value==self.emptyValue or value in EMPTY_VALUES: return self.emptyValue try: value=self.coerce(value) except(ValueError,TypeError,ValidationError): raise ValidationError(self.error_messages[]%{:value}) return value
Validates that the value is in self.choices and can be coerced to the right type.
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def default_exchange_proposed_fn(prob_exchange): def default_exchange_proposed_fn_(num_replica, seed=None): seed_stream = distributions.SeedStream(seed, ) zero_start = tf.random.uniform([], seed=seed_stream()) > 0.5 if num_replica % 2 == 0: def _exchange(): flat_exchange = tf.range(num_replica) if num_replica > 2: start = tf.cast(~zero_start, dtype=tf.int32) end = num_replica - start flat_exchange = flat_exchange[start:end] return tf.reshape(flat_exchange, [tf.size(input=flat_exchange) // 2, 2]) else: def _exchange(): start = tf.cast(zero_start, dtype=tf.int32) end = num_replica - tf.cast(~zero_start, dtype=tf.int32) flat_exchange = tf.range(num_replica)[start:end] return tf.reshape(flat_exchange, [tf.size(input=flat_exchange) // 2, 2]) def _null_exchange(): return tf.reshape(tf.cast([], dtype=tf.int32), shape=[0, 2]) return tf.cond( pred=tf.random.uniform([], seed=seed_stream()) < prob_exchange, true_fn=_exchange, false_fn=_null_exchange) return default_exchange_proposed_fn_
Default exchange proposal function, for replica exchange MC. With probability `prob_exchange` propose combinations of replica for exchange. When exchanging, create combinations of adjacent replicas in [Replica Exchange Monte Carlo]( https://en.wikipedia.org/wiki/Parallel_tempering) ``` exchange_fn = default_exchange_proposed_fn(prob_exchange=0.5) exchange_proposed = exchange_fn(num_replica=3) exchange_proposed.eval() ==> [[0, 1]] # 1 exchange, 0 <--> 1 exchange_proposed.eval() ==> [] # 0 exchanges ``` Args: prob_exchange: Scalar `Tensor` giving probability that any exchanges will be generated. Returns: default_exchange_proposed_fn_: Python callable which take a number of replicas (a Python integer), and return combinations of replicas for exchange as an [n, 2] integer `Tensor`, `0 <= n <= num_replica // 2`, with *unique* values in the set `{0, ..., num_replica}`.
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def get_relationship_admin_session_for_family(self, family_id): if not self.supports_relationship_admin(): raise errors.Unimplemented() return sessions.RelationshipAdminSession(family_id, runtime=self._runtime)
Gets the ``OsidSession`` associated with the relationship administration service for the given family. arg: family_id (osid.id.Id): the ``Id`` of the ``Family`` return: (osid.relationship.RelationshipAdminSession) - a ``RelationshipAdminSession`` raise: NotFound - no family found by the given ``Id`` raise: NullArgument - ``family_id`` is ``null`` raise: OperationFailed - unable to complete request raise: Unimplemented - ``supports_relationship_admin()`` or ``supports_visible_federation()`` is ``false`` *compliance: optional -- This method must be implemented if ``supports_relationship_admin()`` and ``supports_visible_federation()`` are ``true``*
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def topk(timestep: int, batch_size: int, beam_size: int, inactive: mx.nd.NDArray, scores: mx.nd.NDArray, hypotheses: List[ConstrainedHypothesis], best_ids: mx.nd.NDArray, best_word_ids: mx.nd.NDArray, seq_scores: mx.nd.NDArray) -> Tuple[np.array, np.array, np.array, List[ConstrainedHypothesis], mx.nd.NDArray]: for sentno in range(batch_size): rows = slice(sentno * beam_size, sentno * beam_size + beam_size) if hypotheses[rows.start] is not None and hypotheses[rows.start].size() > 0: best_ids[rows], best_word_ids[rows], seq_scores[rows], \ hypotheses[rows], inactive[rows] = _sequential_topk(timestep, beam_size, inactive[rows], scores[rows], hypotheses[rows], best_ids[rows] - rows.start, best_word_ids[rows], seq_scores[rows]) best_ids[rows] += rows.start else: inactive[rows] = 0 return best_ids, best_word_ids, seq_scores, hypotheses, inactive
Builds a new topk list such that the beam contains hypotheses having completed different numbers of constraints. These items are built from three different types: (1) the best items across the whole scores matrix, (2) the set of words that must follow existing constraints, and (3) k-best items from each row. :param timestep: The current decoder timestep. :param batch_size: The number of segments in the batch. :param beam_size: The length of the beam for each segment. :param inactive: Array listing inactive rows (shape: (beam_size,)). :param scores: The scores array (shape: (batch_size if t==1 else beam_size, target_vocab_size)). :param hypotheses: The list of hypothesis objects. :param best_ids: The current list of best hypotheses (shape: (beam_size,)). :param best_word_ids: The parallel list of best word IDs (shape: (beam_size,)). :param seq_scores: (shape: (beam_size, 1)). :return: A tuple containing the best hypothesis rows, the best hypothesis words, the scores, the updated constrained hypotheses, and the updated set of inactive hypotheses.
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def expool(name): name = stypes.stringToCharP(name) found = ctypes.c_int() libspice.expool_c(name, ctypes.byref(found)) return bool(found.value)
Confirm the existence of a kernel variable in the kernel pool. http://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/expool_c.html :param name: Name of the variable whose value is to be returned. :type name: str :return: True when the variable is in the pool. :rtype: bool
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def parse_date(self, value): if value is None: raise Exception("Unable to parse date from %r" % value) elif isinstance(value, string_types): return self.str2date(value) elif isinstance(value, int): return date.fromordinal(value) elif isinstance(value, datetime): return value.date() elif isinstance(value, date): return value else: raise Exception("Unable to parse date from %r" % value)
A lazy method to parse anything to date. If input data type is: - string: parse date from it - integer: use from ordinal - datetime: use date part - date: just return it
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def _update_armed_status(self, message=None, status=None, status_stay=None): arm_status = status stay_status = status_stay if isinstance(message, Message): arm_status = message.armed_away stay_status = message.armed_home if arm_status is None or stay_status is None: return self._armed_status, old_status = arm_status, self._armed_status self._armed_stay, old_stay = stay_status, self._armed_stay if arm_status != old_status or stay_status != old_stay: if old_status is not None or message is None: if self._armed_status or self._armed_stay: self.on_arm(stay=stay_status) else: self.on_disarm() return self._armed_status or self._armed_stay
Uses the provided message to update the armed state. :param message: message to use to update :type message: :py:class:`~alarmdecoder.messages.Message` :param status: armed status, overrides message bits :type status: bool :param status_stay: armed stay status, overrides message bits :type status_stay: bool :returns: bool indicating the new status
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def play(quiet, session_file, shell, speed, prompt, commentecho): run( session_file.readlines(), shell=shell, speed=speed, quiet=quiet, test_mode=TESTING, prompt_template=prompt, commentecho=commentecho, )
Play a session file.
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def get_log(db, job_id): logs = db(, job_id) out = [] for log in logs: time = str(log.timestamp)[:-4] out.append( % (time, job_id, log.level, log.message)) return out
Extract the logs as a big string :param db: a :class:`openquake.server.dbapi.Db` instance :param job_id: a job ID
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def list(self, request, *args, **kwargs): return super(CustomerPermissionViewSet, self).list(request, *args, **kwargs)
Each customer is associated with a group of users that represent customer owners. The link is maintained through **api/customer-permissions/** endpoint. To list all visible links, run a **GET** query against a list. Response will contain a list of customer owners and their brief data. To add a new user to the customer, **POST** a new relationship to **customer-permissions** endpoint: .. code-block:: http POST /api/customer-permissions/ HTTP/1.1 Accept: application/json Authorization: Token 95a688962bf68678fd4c8cec4d138ddd9493c93b Host: example.com { "customer": "http://example.com/api/customers/6c9b01c251c24174a6691a1f894fae31/", "role": "owner", "user": "http://example.com/api/users/82cec6c8e0484e0ab1429412fe4194b7/" }
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def authorization_middleware(get_response): middleware_settings = settings() logger = _create_logger(middleware_settings) min_scope = middleware_settings[] def get_token_subject(sub): return sub def always_ok(*args, **kwargs): return True def authorize_function(scopes, token_signature, x_unique_id=None): log_msg_scopes = def is_authorized(*needed_scopes): granted_scopes = set(scopes) needed_scopes = set(needed_scopes) result = needed_scopes.issubset(granted_scopes) if result: msg = log_msg_scopes.format(needed_scopes, granted_scopes, token_signature) if x_unique_id: msg += .format(x_unique_id) logger.info(msg) return result return is_authorized def authorize_forced_anonymous(_): raise Exception( ) def insufficient_scope(): msg = response = http.HttpResponse(, status=401) response[] = msg return response def expired_token(): msg = response = http.HttpResponse(, status=401) response[] = msg return response def invalid_token(): msg = response = http.HttpResponse(, status=401) response[] = msg return response def invalid_request(): msg = ( "Bearer realm=\"datapunt\", error=\"invalid_request\", " "error_description=\"Invalid Authorization header format; " "should be: \"") response = http.HttpResponse(, status=400) response[] = msg return response def token_data(authorization): try: prefix, token = authorization.split() except ValueError: logger.warning( .format(authorization)) raise _AuthorizationHeaderError(invalid_request()) if prefix.lower() != : logger.warning( .format(authorization)) raise _AuthorizationHeaderError(invalid_request()) try: header = jwt.get_unverified_header(token) except jwt.ExpiredSignatureError: logger.info("Expired token") raise _AuthorizationHeaderError(expired_token()) except (jwt.InvalidTokenError, jwt.DecodeError): logger.exception("API authz problem: JWT decode error while reading header") raise _AuthorizationHeaderError(invalid_token()) if not in header: logger.exception("Did not get a valid key identifier") raise _AuthorizationHeaderError(invalid_token()) keys = middleware_settings[].verifiers if header[] not in keys: logger.exception("Unknown key identifier: {}".format(header[])) raise _AuthorizationHeaderError(invalid_token()) key = keys[header[]] try: decoded = jwt.decode(token, key=key.key, algorithms=(key.alg,)) except jwt.InvalidTokenError: logger.exception( .format(token)) raise _AuthorizationHeaderError(invalid_token()) if not in decoded: logger.warning( .format(token)) raise _AuthorizationHeaderError(invalid_token()) else: scopes = decoded[] if in decoded: sub = decoded[] else: sub = None token_signature = token.split()[2] return scopes, token_signature, sub def middleware(request): request_path = request.path forced_anonymous = any( request_path.startswith(route) for route in middleware_settings[]) if middleware_settings[]: logger.warning() request.is_authorized_for = always_ok request.get_token_subject = return get_response(request) is_options = request.method == if forced_anonymous or is_options: authz_func = authorize_forced_anonymous subject = None else: authorization = request.META.get() token_signature = sub = None if authorization: try: scopes, token_signature, sub = token_data(authorization) except _AuthorizationHeaderError as e: return e.response else: scopes = [] x_unique_id = request.META.get() authz_func = authorize_function(scopes, token_signature, x_unique_id) subject = get_token_subject(sub) if len(min_scope) > 0 and not authz_func(min_scope): return insufficient_scope() request.is_authorized_for = authz_func request.get_token_subject = subject response = get_response(request) return response return middleware
Django middleware to parse incoming access tokens, validate them and set an authorization function on the request. The decision to use a generic middleware rather than an AuthenticationMiddleware is explicitly made, because inctances of the latter come with a number of assumptions (i.e. that user.is_authorized() exists, or that request.user uses the User model). Example usage: :: request.is_authorized_for() :param get_response: callable that creates the response object :return: response :todo: Two things needs to be done when we can completely remove the Django JWT plugin: - Nested function 'middleware' allows both 'JWT' (not IANA-registered) and 'Bearer' as Authorization header prefix; JWT should not be accepted. - The Django JWT middleware does not include the authz claim, so this plugin does not fail if it is not present; this behavior is wrong when we no longer use the Django JWT plugin.
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def _parse(jsonOutput): metadatacontent parsed={} if not jsonOutput: return parsed parsed["status"] = jsonOutput[0] if jsonOutput[1] == None or jsonOutput[1] == "": return parsed realJson = json.loads(jsonOutput[1]) content = "" for js in realJson: if "X-TIKA:content" in js: content += js["X-TIKA:content"] if content == "": content = None parsed["content"] = content parsed["metadata"] = {} for js in realJson: for n in js: if n != "X-TIKA:content": if n in parsed["metadata"]: if not isinstance(parsed["metadata"][n], list): parsed["metadata"][n] = [parsed["metadata"][n]] parsed["metadata"][n].append(js[n]) else: parsed["metadata"][n] = js[n] return parsed
Parses JSON response from Tika REST API server :param jsonOutput: JSON output from Tika Server :return: a dictionary having 'metadata' and 'content' values
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def _set_lsp_reoptimize_timer(self, v, load=False): if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={: []}, int_size=32), restriction_dict={: [u]}), is_leaf=True, yang_name="lsp-reoptimize-timer", rest_name="reoptimize-timer", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u: {u: None, u: u, u: None, u: u}}, namespace=, defining_module=, yang_type=, is_config=True) except (TypeError, ValueError): raise ValueError({ : , : "uint32", : , }) self.__lsp_reoptimize_timer = t if hasattr(self, ): self._set()
Setter method for lsp_reoptimize_timer, mapped from YANG variable /mpls_config/router/mpls/mpls_cmds_holder/lsp/secondary_path/lsp_reoptimize_timer (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_lsp_reoptimize_timer is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_lsp_reoptimize_timer() directly.
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def is_Linear(self): coeff_dict = self.expression.as_coefficients_dict() for key in coeff_dict.keys(): if len(key.free_symbols) < 2 and (key.is_Add or key.is_Mul or key.is_Atom): pass else: return False if key.is_Pow and key.args[1] != 1: return False else: return True
Returns True if expression is linear (a polynomial with degree 1 or 0) (read-only).
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def send(message, request_context=None, binary=False): if binary: return uwsgi.websocket_send_binary(message, request_context) return uwsgi.websocket_send(message, request_context)
Sends a message to websocket. :param str message: data to send :param request_context: :raises IOError: If unable to send a message.
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def interact_GxG(pheno,snps1,snps2=None,K=None,covs=None): if K is None: K=SP.eye(N) N=snps1.shape[0] if snps2 is None: snps2 = snps1 return interact_GxE(snps=snps1,pheno=pheno,env=snps2,covs=covs,K=K)
Epistasis test between two sets of SNPs Args: pheno: [N x 1] SP.array of 1 phenotype for N individuals snps1: [N x S1] SP.array of S1 SNPs for N individuals snps2: [N x S2] SP.array of S2 SNPs for N individuals K: [N x N] SP.array of LMM-covariance/kinship koefficients (optional) If not provided, then linear regression analysis is performed covs: [N x D] SP.array of D covariates for N individuals Returns: pv: [S2 x S1] SP.array of P values for epistasis tests beten all SNPs in snps1 and snps2
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def is_identity(self): if not self.terms: return True return len(self.terms) == 1 and not self.terms[0].ops and self.terms[0].coeff == 1.0
If `self` is I, returns True, otherwise False.
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def send_data(self): if not self.connection._sock: raise err.InterfaceError("(0, )") conn = self.connection try: with open(self.filename, ) as open_file: packet_size = min(conn.max_allowed_packet, 16*1024) while True: chunk = open_file.read(packet_size) if not chunk: break conn.write_packet(chunk) except IOError: raise err.OperationalError(1017, "Can{0}')
Send data packets from the local file to the server
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def doc_files(self): doc_files = [] for doc_file_re in settings.DOC_FILES_RE: doc_files.extend( self.archive.get_files_re(doc_file_re, ignorecase=True)) return [.join(x.split()[1:]) for x in doc_files]
Returns list of doc files that should be used for %doc in specfile. Returns: List of doc files from the archive - only basenames, not full paths.
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def build_dir(): tag_arr = [, , , , ] path_arr = [os.path.join(CRUD_PATH, x) for x in tag_arr] for wpath in path_arr: if os.path.exists(wpath): continue os.makedirs(wpath)
Build the directory used for templates.
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def _convert_scalar_indexer(self, key, kind=None): assert kind in [, , , , None] if is_scalar(key): is_int = is_integer(key) is_flt = is_float(key) if kind in [] and (is_int or is_flt): self._invalid_indexer(, key) elif kind in [, ] and is_flt: self._invalid_indexer(, key) return super()._convert_scalar_indexer(key, kind=kind)
We don't allow integer or float indexing on datetime-like when using loc. Parameters ---------- key : label of the slice bound kind : {'ix', 'loc', 'getitem', 'iloc'} or None
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def _replaces(self): return {concat(a, c, b[1:]) for a, b in self.slices[:-1] for c in ALPHABET}
tge
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def _parse_row(self, i): row = self.data[i] for j in range(len(row)): self.data[i][j] = self._parse_value(self.data[i][j])
Parses row :param i: index of row to parse
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def add_project(self, path): if not foundations.common.path_exists(path): return False path = os.path.normpath(path) if self.__model.get_project_nodes(path): self.__engine.notifications_manager.warnify( "{0} | project is already opened!".format(self.__class__.__name__, path)) return False LOGGER.info("{0} | Adding project!".format(self.__class__.__name__, path)) project_node = self.__model.register_project(path) if not project_node: return False self.__model.set_project_nodes(project_node) return True
Adds a project. :param path: Project path. :type path: unicode :return: Method success. :rtype: bool
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def check_for_lime(self, pattern): check = self.commands.lime_check.value lime_loaded = False result = self.shell.execute(check) stdout = self.shell.decode(result[]) connections = self.net_parser.parse(stdout) for conn in connections: local_addr, remote_addr = conn if local_addr == pattern: lime_loaded = True break return lime_loaded
Check to see if LiME has loaded on the remote system :type pattern: str :param pattern: pattern to check output against :type listen_port: int :param listen_port: port LiME is listening for connections on
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def pick_peaks(nc, L=16): offset = nc.mean() / 20. nc = filters.gaussian_filter1d(nc, sigma=4) th = filters.median_filter(nc, size=L) + offset peaks = [] for i in range(1, nc.shape[0] - 1): if nc[i - 1] < nc[i] and nc[i] > nc[i + 1]: if nc[i] > th[i]: peaks.append(i) return peaks
Obtain peaks from a novelty curve using an adaptive threshold.
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def blank_dc(self, n_coarse_chan): if n_coarse_chan < 1: logger.warning() return None if not n_coarse_chan % int(n_coarse_chan) == 0: logger.warning() return None n_coarse_chan = int(n_coarse_chan) n_chan = self.data.shape[-1] n_chan_per_coarse = int(n_chan / n_coarse_chan) mid_chan = int(n_chan_per_coarse / 2) for ii in range(n_coarse_chan): ss = ii*n_chan_per_coarse self.data[..., ss+mid_chan] = np.median(self.data[..., ss+mid_chan+5:ss+mid_chan+10])
Blank DC bins in coarse channels. Note: currently only works if entire file is read
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def bam_needs_processing(data): return ((data.get("work_bam") or data.get("align_bam")) and (any(tz.get_in(["config", "algorithm", x], data) for x in ["variantcaller", "mark_duplicates", "recalibrate", "realign", "svcaller", "jointcaller", "variant_regions"]) or any(k in data for k in ["cwl_keys", "output_cwl_keys"])))
Check if a work input needs processing for parallelization.
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def timing(name, delta, rate=1, tags=None): return client().timing(name, delta, rate=rate, tags=tags)
Sends new timing information. `delta` is in milliseconds. >>> import statsdecor >>> statsdecor.timing('my.metric', 314159265359)
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def get_subset(self, subset): if len(subset) > 50: raise ze.TooManyItems("You may only retrieve 50 items per call") params = self.url_params retr = [] for itm in subset: retr.extend(self.item(itm)) self.url_params = params self.url_params = None return retr
Retrieve a subset of items Accepts a single argument: a list of item IDs
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def on_recv_rsp(self, rsp_pb): ret_code, msg, _= SubAccPush.unpack_rsp(rsp_pb) if self._notify_obj is not None: self._notify_obj.on_async_sub_acc_push(ret_code, msg) return ret_code, msg
receive response callback function
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def _keplerian_to_keplerian_mean(cls, coord, center): a, e, i, Ω, ω, ν = coord if e < 1: cos_E = (e + cos(ν)) / (1 + e * cos(ν)) sin_E = (sin(ν) * sqrt(1 - e ** 2)) / (1 + e * cos(ν)) E = arctan2(sin_E, cos_E) % (2 * np.pi) M = E - e * sin(E) else: H = arccosh((e + cos(ν)) / (1 + e * cos(ν))) M = e * sinh(H) - H return np.array([a, e, i, Ω, ω, M], dtype=float)
Conversion from Keplerian to Keplerian Mean The difference is the use of Mean anomaly instead of True anomaly
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def stmt_star_handler( self, stmts, prev_node_to_avoid=None ): break_nodes = list() cfg_statements = list() self.prev_nodes_to_avoid.append(prev_node_to_avoid) self.last_control_flow_nodes.append(None) first_node = None node_not_to_step_past = self.nodes[-1] for stmt in stmts: node = self.visit(stmt) if isinstance(node, ControlFlowNode) and not isinstance(node.test, TryNode): self.last_control_flow_nodes.append(node.test) else: self.last_control_flow_nodes.append(None) if isinstance(node, ControlFlowNode): break_nodes.extend(node.break_statements) elif isinstance(node, BreakNode): break_nodes.append(node) if not isinstance(node, IgnoredNode): cfg_statements.append(node) if not first_node: if isinstance(node, ControlFlowNode): first_node = node.test else: first_node = get_first_node( node, node_not_to_step_past ) self.prev_nodes_to_avoid.pop() self.last_control_flow_nodes.pop() connect_nodes(cfg_statements) if cfg_statements: if first_node: first_statement = first_node else: first_statement = get_first_statement(cfg_statements[0]) last_statements = get_last_statements(cfg_statements) return ConnectStatements( first_statement=first_statement, last_statements=last_statements, break_statements=break_nodes ) else: return IgnoredNode()
Handle stmt* expressions in an AST node. Links all statements together in a list of statements, accounting for statements with multiple last nodes.
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def add(self, parent, obj_type, **attributes): return self.ixn.add(parent.obj_ref(), obj_type, *self._get_args_list(**attributes))
IXN API add command @param parent: object parent - object will be created under this parent. @param object_type: object type. @param attributes: additional attributes. @return: IXN object reference.
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def start_consuming(self, to_tuple=False, auto_decode=True): while not self.is_closed: self.process_data_events( to_tuple=to_tuple, auto_decode=auto_decode ) if self.consumer_tags: sleep(IDLE_WAIT) continue break
Start consuming messages. :param bool to_tuple: Should incoming messages be converted to a tuple before delivery. :param bool auto_decode: Auto-decode strings when possible. :raises AMQPChannelError: Raises if the channel encountered an error. :raises AMQPConnectionError: Raises if the connection encountered an error. :return:
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def _height_is_big_enough(image, height): if height > image.size[1]: raise ImageSizeError(image.size[1], height)
Check that the image height is superior to `height`
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def rotate(data, axis=(1., 0, 0), angle=0., center=None, mode="constant", interpolation="linear"): if center is None: center = tuple([s // 2 for s in data.shape]) cx, cy, cz = center m = np.dot(mat4_translate(cx, cy, cz), np.dot(mat4_rotate(angle, *axis), mat4_translate(-cx, -cy, -cz))) m = np.linalg.inv(m) return affine(data, m, mode=mode, interpolation=interpolation)
rotates data around axis by a given angle Parameters ---------- data: ndarray 3d array axis: tuple axis to rotate by angle about axis = (x,y,z) angle: float center: tuple or None origin of rotation (cz,cy,cx) in pixels if None, center is the middle of data mode: string boundary mode, one of the following: 'constant' pads with zeros 'edge' pads with edge values 'wrap' pads with the repeated version of the input interpolation, string interpolation mode, one of the following 'linear' 'nearest' Returns ------- res: ndarray rotated array (same shape as input)
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def get_deviations(self): mean_vec = self.mean() df = self.loc[:,:].copy() for col in df.columns: df.loc[:,col] -= mean_vec[col] return type(self).from_dataframe(pst=self.pst,df=df)
get the deviations of the ensemble value from the mean vector Returns ------- en : pyemu.Ensemble Ensemble of deviations from the mean
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def start_archive(self, session_id, has_audio=True, has_video=True, name=None, output_mode=OutputModes.composed, resolution=None): if not isinstance(output_mode, OutputModes): raise OpenTokException(u().format(output_mode)) if resolution and output_mode == OutputModes.individual: raise OpenTokException(u()) payload = {: name, : session_id, : has_audio, : has_video, : output_mode.value, : resolution, } response = requests.post(self.endpoints.archive_url(), data=json.dumps(payload), headers=self.json_headers(), proxies=self.proxies, timeout=self.timeout) if response.status_code < 300: return Archive(self, response.json()) elif response.status_code == 403: raise AuthError() elif response.status_code == 400: raise RequestError(response.json().get("message")) elif response.status_code == 404: raise NotFoundError("Session not found") elif response.status_code == 409: raise ArchiveError(response.json().get("message")) else: raise RequestError("An unexpected error occurred", response.status_code)
Starts archiving an OpenTok session. Clients must be actively connected to the OpenTok session for you to successfully start recording an archive. You can only record one archive at a time for a given session. You can only record archives of sessions that use the OpenTok Media Router (sessions with the media mode set to routed); you cannot archive sessions with the media mode set to relayed. For more information on archiving, see the `OpenTok archiving <https://tokbox.com/opentok/tutorials/archiving/>`_ programming guide. :param String session_id: The session ID of the OpenTok session to archive. :param String name: This is the name of the archive. You can use this name to identify the archive. It is a property of the Archive object, and it is a property of archive-related events in the OpenTok.js library. :param Boolean has_audio: if set to True, an audio track will be inserted to the archive. has_audio is an optional parameter that is set to True by default. If you set both has_audio and has_video to False, the call to the start_archive() method results in an error. :param Boolean has_video: if set to True, a video track will be inserted to the archive. has_video is an optional parameter that is set to True by default. :param OutputModes output_mode: Whether all streams in the archive are recorded to a single file (OutputModes.composed, the default) or to individual files (OutputModes.individual). :param String resolution (Optional): The resolution of the archive, either "640x480" (the default) or "1280x720". This parameter only applies to composed archives. If you set this parameter and set the output_mode parameter to OutputModes.individual, the call to the start_archive() method results in an error. :rtype: The Archive object, which includes properties defining the archive, including the archive ID.
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def _get_float_remainder(fvalue, signs=9): check_positive(fvalue) if isinstance(fvalue, six.integer_types): return "0" if isinstance(fvalue, Decimal) and fvalue.as_tuple()[2] == 0: return "0" signs = min(signs, len(FRACTIONS)) remainder = str(fvalue).split()[1] iremainder = int(remainder) orig_remainder = remainder factor = len(str(remainder)) - signs if factor > 0: iremainder = int(round(iremainder / (10.0**factor))) format = "%%0%dd" % min(len(remainder), signs) remainder = format % iremainder if len(remainder) > signs: raise ValueError("Signs overflow: I can't round only fractional part \ of %s to fit %s in %d signs" % \ (str(fvalue), orig_remainder, signs)) return remainder
Get remainder of float, i.e. 2.05 -> '05' @param fvalue: input value @type fvalue: C{integer types}, C{float} or C{Decimal} @param signs: maximum number of signs @type signs: C{integer types} @return: remainder @rtype: C{str} @raise ValueError: fvalue is negative @raise ValueError: signs overflow
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def get_encrypted_field(base_class): assert not isinstance(base_class, models.Field) field_name = + base_class.__name__ if base_class not in FIELD_CACHE: FIELD_CACHE[base_class] = type(field_name, (EncryptedMixin, base_class), { : base_class, }) return FIELD_CACHE[base_class]
A get or create method for encrypted fields, we cache the field in the module to avoid recreation. This also allows us to always return the same class reference for a field. :type base_class: models.Field[T] :rtype: models.Field[EncryptedMixin, T]
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def parse_data_line(self, sline): } self._addRawResult(resid, values, False) return 0
Parses the data line and builds the dictionary. :param sline: a split data line to parse :returns: the number of rows to jump and parse the next data line or return the code error -1
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def pid_exists(pid): if pid < 0: return False try: os.kill(pid, 0) except OSError as e: return e.errno == errno.EPERM else: return True
Check whether pid exists in the current process table.
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def setup_mturk_connection(self): if ((self.aws_access_key_id == ) or (self.aws_secret_access_key == )): print "AWS access key not set in ~/.psiturkconfig; please enter a valid access key." assert False if self.is_sandbox: endpoint_url = else: endpoint_url = self.mtc = boto3.client(, region_name=, aws_access_key_id=self.aws_access_key_id, aws_secret_access_key=self.aws_secret_access_key, endpoint_url=endpoint_url) return True
Connect to turk
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def has_axon(neuron, treefun=_read_neurite_type): s neurites Returns: CheckResult with result ' return CheckResult(NeuriteType.axon in (treefun(n) for n in neuron.neurites))
Check if a neuron has an axon Arguments: neuron(Neuron): The neuron object to test treefun: Optional function to calculate the tree type of neuron's neurites Returns: CheckResult with result
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def forget(self, obj): ve modified is not automatically saved on ``session.commit()`` . ' self._init() self.known.pop(obj._pk, None) self.wknown.pop(obj._pk, None)
Forgets about an entity (automatically called when an entity is deleted). Call this to ensure that an entity that you've modified is not automatically saved on ``session.commit()`` .
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def IntegerLike(msg=None): def fn(value): if not any([ isinstance(value, numbers.Integral), (isinstance(value, float) and value.is_integer()), (isinstance(value, basestring) and value.isdigit()) ]): raise Invalid(msg or ( .format(value)) ) else: return value return fn
Checks whether a value is: - int, or - long, or - float without a fractional part, or - str or unicode composed only of digits
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def add_middleware(middleware: EFBMiddleware): global middlewares if isinstance(middleware, EFBMiddleware): middlewares.append(middleware) else: raise TypeError("Middleware instance is expected")
Register a middleware with the coordinator. Args: middleware (EFBMiddleware): Middleware to register
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def attach(self, media: typing.Union[InputMedia, typing.Dict]): if isinstance(media, dict): if not in media: raise ValueError(f"Invalid media!") media_type = media[] if media_type == : media = InputMediaPhoto(**media) elif media_type == : media = InputMediaVideo(**media) else: raise TypeError(f"Invalid media type !") elif not isinstance(media, InputMedia): raise TypeError(f"Media must be an instance of InputMedia or dict, not {type(media).__name__}") elif media.type in [, , ]: raise ValueError(f"This type of media is not supported by media groups!") self.media.append(media)
Attach media :param media:
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def server_powerstatus(host=None, admin_username=None, admin_password=None, module=None): ret = __execute_ret(, host=host, admin_username=admin_username, admin_password=admin_password, module=module) result = {: 0} if ret[] == : result[] = True result[] = if ret[] == : result[] = False result[] = if ret[].startswith(): result[] = False result[] = ret[] return result
return the power status for the passed module CLI Example: .. code-block:: bash salt dell drac.server_powerstatus
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def _append_params(oauth_params, params): merged = list(params) merged.extend(oauth_params) merged.sort(key=lambda i: i[0].startswith()) return merged
Append OAuth params to an existing set of parameters. Both params and oauth_params is must be lists of 2-tuples. Per `section 3.5.2`_ and `3.5.3`_ of the spec. .. _`section 3.5.2`: https://tools.ietf.org/html/rfc5849#section-3.5.2 .. _`3.5.3`: https://tools.ietf.org/html/rfc5849#section-3.5.3
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def get_and_write(self, iso_path, local_path, blocksize=8192): iso_pathiso_path if not self._initialized: raise pycdlibexception.PyCdlibInvalidInput() with open(local_path, ) as fp: self._get_and_write_fp(utils.normpath(iso_path), fp, blocksize)
(deprecated) Fetch a single file from the ISO and write it out to the specified file. Note that this will overwrite the contents of the local file if it already exists. Also note that 'iso_path' must be an absolute path to the file. Finally, the 'iso_path' can be an ISO9660 path, a Rock Ridge path, or a Joliet path. In the case of ambiguity, the Joliet path is tried first, followed by the ISO9660 path, followed by the Rock Ridge path. It is recommended to use the get_file_from_iso API instead to resolve this ambiguity. Parameters: iso_path - The absolute path to the file to get data from. local_path - The local filename to write the contents to. blocksize - The blocksize to use when copying data; the default is 8192. Returns: Nothing.
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def readmegen(): hitchpylibrarytoolkit.readmegen( _storybook(), DIR.project, DIR.key, DIR.gen, "commandlib" )
Build documentation.
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def comparison(self, lhs, rhs): if len(rhs) > 0: return ast.Compare(left=lhs, ops=list(map(lambda x: x[0], rhs)), comparators=list(map(lambda x: x[1], rhs)), loc=lhs.loc.join(rhs[-1][1].loc)) else: return lhs
(2.6, 2.7) comparison: expr (comp_op expr)* (3.0, 3.1) comparison: star_expr (comp_op star_expr)* (3.2-) comparison: expr (comp_op expr)*
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def get_bug_report(): platform_info = BugReporter.get_platform_info() module_info = { : hal_version.__version__, : hal_version.__build__ } return { : platform_info, : module_info }
Generate information for a bug report :return: information for bug report
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def close_document(self, path): to_close = [] for widget in self.widgets(include_clones=True): p = os.path.normpath(os.path.normcase(widget.file.path)) path = os.path.normpath(os.path.normcase(path)) if p == path: to_close.append(widget) for widget in to_close: tw = widget.parent_tab_widget tw.remove_tab(tw.indexOf(widget))
Closes a text document. :param path: Path of the document to close.
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def sense_dep(self, target): self.chipset.rf_configuration(0x02, b"\x0B\x0B\x0A") return super(Device, self).sense_dep(target)
Search for a DEP Target in active or passive communication mode.
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def _prepare_uimodules(self): for key, value in self._config.get(config.UI_MODULES, {}).iteritems(): self._config[config.UI_MODULES][key] = self._import_class(value) self._config[config.UI_MODULES] = dict(self._config[config.UI_MODULES] or {})
Prepare the UI Modules from a list of namespaced paths.
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async def load_message_field(obj, msg, field, field_archiver=None): fname, ftype, params = field[0], field[1], field[2:] field_archiver = field_archiver if field_archiver else load_field await field_archiver(obj[fname], ftype, params, eref(msg, fname))
Loads message field from the object. Field is defined by the message field specification. Returns loaded value, supports field reference. :param reader: :param msg: :param field: :param field_archiver: :return:
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def clear(self): self._delete_child_storage(self.root_node) self._delete_node_storage(self.root_node) self.root_node = BLANK_NODE
clear all tree data
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def sevenths_inv(reference_labels, estimated_labels): validate(reference_labels, estimated_labels) seventh_qualities = [, , , , , ] valid_semitones = np.array([QUALITIES[name] for name in seventh_qualities]) ref_roots, ref_semitones, ref_basses = encode_many(reference_labels, False) est_roots, est_semitones, est_basses = encode_many(estimated_labels, False) eq_roots_basses = (ref_roots == est_roots) * (ref_basses == est_basses) eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_roots_basses * eq_semitones).astype(np.float) is_valid = np.array([np.all(np.equal(ref_semitones, semitones), axis=1) for semitones in valid_semitones]) comparison_scores[np.sum(is_valid, axis=0) == 0] = -1 valid_inversion = np.ones(ref_basses.shape, dtype=bool) bass_idx = ref_basses >= 0 valid_inversion[bass_idx] = ref_semitones[bass_idx, ref_basses[bass_idx]] comparison_scores[valid_inversion == 0] = -1 return comparison_scores
Compare chords along MIREX 'sevenths' rules. Chords with qualities outside [maj, maj7, 7, min, min7, N] are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.sevenths_inv(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut.
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def create_folder(self, folder_name, parent_kind_str, parent_uuid): data = { : folder_name, : { : parent_kind_str, : parent_uuid } } return self._post("/folders", data)
Send POST to /folders to create a new folder with specified name and parent. :param folder_name: str name of the new folder :param parent_kind_str: str type of parent folder has(dds-folder,dds-project) :param parent_uuid: str uuid of the parent object :return: requests.Response containing the successful result
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def _one_q_sic_prep(index, qubit): if index == 0: return Program() theta = 2 * np.arccos(1 / np.sqrt(3)) zx_plane_rotation = Program([ RX(-pi / 2, qubit), RZ(theta - pi, qubit), RX(-pi / 2, qubit), ]) if index == 1: return zx_plane_rotation elif index == 2: return zx_plane_rotation + RZ(-2 * pi / 3, qubit) elif index == 3: return zx_plane_rotation + RZ(2 * pi / 3, qubit) raise ValueError(f)
Prepare the index-th SIC basis state.
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def volume_show(name, profile=None, **kwargs): * conn = _auth(profile, **kwargs) return conn.volume_show(name)
Create a block storage volume name Name of the volume profile Profile to use CLI Example: .. code-block:: bash salt '*' nova.volume_show myblock profile=openstack
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def libvlc_vlm_del_media(p_instance, psz_name): f = _Cfunctions.get(, None) or \ _Cfunction(, ((1,), (1,),), None, ctypes.c_int, Instance, ctypes.c_char_p) return f(p_instance, psz_name)
Delete a media (VOD or broadcast). @param p_instance: the instance. @param psz_name: the media to delete. @return: 0 on success, -1 on error.
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def script(experiment, projects): benchbuild_c = local[local.path(sys.argv[0])] slurm_script = local.cwd / experiment.name + "-" + str( CFG[][]) srun = local["srun"] srun_args = [] if not CFG["slurm"]["multithread"]: srun_args.append("--hint=nomultithread") if not CFG["slurm"]["turbo"]: srun_args.append("--pstate-turbo=off") srun = srun[srun_args] srun = srun[benchbuild_c["run"]] return __save__(slurm_script, srun, experiment, projects)
Prepare a slurm script that executes the experiment for a given project. Args: experiment: The experiment we want to execute projects: All projects we generate an array job for.
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def grab_literal(template, l_del): global _CURRENT_LINE try: literal, template = template.split(l_del, 1) _CURRENT_LINE += literal.count() return (literal, template) except ValueError: return (template, )
Parse a literal from the template
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def append_ISO19115_keywords(keywords): } ISO19115_keywords = {} for key, value in list(ISO19115_mapping.items()): ISO19115_keywords[value] = setting(key, expected_type=str) keywords.update(ISO19115_keywords)
Append ISO19115 from setting to keywords. :param keywords: The keywords destination. :type keywords: dict
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def _parseLine(cls, line): r = cls._PROG.match(line) if not r: raise ValueError("Error: parsing . Correct: \"<number> <number> [<text>]\"" % line) d = r.groupdict() if len(d[]) == 0 or len(d[]) == 0: raise ValueError("Error: parsing . Correct: \"<number> <number> [<text>]\"" % line) return AudioClipSpec(d[], d[], d[].strip())
Parsers a single line of text and returns an AudioClipSpec Line format: <number> <number> [<text>] Returns: list(AudioClipSpec) or None
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def directory_files(path): for entry in os.scandir(path): if not entry.name.startswith() and entry.is_file(): yield entry.name
Yield directory file names.
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def permute_point(p, permutation=None): if not permutation: return p return [p[int(permutation[i])] for i in range(len(p))]
Permutes the point according to the permutation keyword argument. The default permutation is "012" which does not change the order of the coordinate. To rotate counterclockwise, use "120" and to rotate clockwise use "201".
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def poll(self, poll_rate=None, timeout=None): return _poll_task( self.id, self._server_config, poll_rate, timeout )
Return the status of a task or timeout. There are several API calls that trigger asynchronous tasks, such as synchronizing a repository, or publishing or promoting a content view. It is possible to check on the status of a task if you know its UUID. This method polls a task once every ``poll_rate`` seconds and, upon task completion, returns information about that task. :param poll_rate: Delay between the end of one task check-up and the start of the next check-up. Defaults to ``nailgun.entity_mixins.TASK_POLL_RATE``. :param timeout: Maximum number of seconds to wait until timing out. Defaults to ``nailgun.entity_mixins.TASK_TIMEOUT``. :returns: Information about the asynchronous task. :raises: ``nailgun.entity_mixins.TaskTimedOutError`` if the task completes with any result other than "success". :raises: ``nailgun.entity_mixins.TaskFailedError`` if the task finishes with any result other than "success". :raises: ``requests.exceptions.HTTPError`` If the API returns a message with an HTTP 4XX or 5XX status code.
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def _vcap_from_service_definition(service_def): if in service_def: credentials = service_def[] else: credentials = service_def service = {} service[] = credentials service[] = _name_from_service_definition(service_def) vcap = {: [service]} return vcap
Turn a service definition into a vcap services containing a single service.