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def connect_ssh(*args, **kwargs): client = SSHClient() client.connect(*args, **kwargs) return client
Create a new connected :class:`SSHClient` instance. All arguments are passed to :meth:`SSHClient.connect`.
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def _iflat_tasks_wti(self, status=None, op="==", nids=None, with_wti=True): nids = as_set(nids) if status is None: for wi, work in enumerate(self): for ti, task in enumerate(work): if nids and task.node_id not in nids: continue if with_wti: yield task, wi, ti else: yield task else: op = operator_from_str(op) status = Status.as_status(status) for wi, work in enumerate(self): for ti, task in enumerate(work): if nids and task.node_id not in nids: continue if op(task.status, status): if with_wti: yield task, wi, ti else: yield task
Generators that produces a flat sequence of task. if status is not None, only the tasks with the specified status are selected. nids is an optional list of node identifiers used to filter the tasks. Returns: (task, work_index, task_index) if with_wti is True else task
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def check_network_health(self): r health = HealthDict() health[] = [] health[] = [] health[] = [] health[] = [] health[] = [] health[] = [] health[] = [] hits = sp.where(self[] > self.Np - 1)[0] if sp.size(hits) > 0: health[] = sp.unique(hits) return health P12 = self[] hits = sp.where(P12[:, 0] == P12[:, 1])[0] if sp.size(hits) > 0: health[] = hits Ps = self.num_neighbors(self.pores()) if sp.sum(Ps == 0) > 0: health[] = sp.where(Ps == 0)[0] temp = [] am = self.create_adjacency_matrix(fmt=, triu=True) Cs = csg.connected_components(am, directed=False)[1] if sp.unique(Cs).size > 1: for i in sp.unique(Cs): temp.append(sp.where(Cs == i)[0]) b = sp.array([len(item) for item in temp]) c = sp.argsort(b)[::-1] for i in range(0, len(c)): health[].append(temp[c[i]]) if i > 0: health[].extend(temp[c[i]]) am = self.create_adjacency_matrix(fmt=, triu=True).tocoo() hits = sp.where(am.data > 1)[0] if len(hits): mergeTs = [] hits = sp.vstack((am.row[hits], am.col[hits])).T ihits = hits[:, 0] + 1j*hits[:, 1] conns = self[] iconns = conns[:, 0] + 1j*conns[:, 1] for item in ihits: mergeTs.append(sp.where(iconns == item)[0]) health[] = mergeTs adjmat = self.create_adjacency_matrix(fmt=) num_full = adjmat.sum() temp = sprs.triu(adjmat, k=1) num_upper = temp.sum() if num_full > num_upper: biTs = sp.where(self[][:, 0] > self[][:, 1])[0] health[] = biTs.tolist() return health
r""" This method check the network topological health by checking for: (1) Isolated pores (2) Islands or isolated clusters of pores (3) Duplicate throats (4) Bidirectional throats (ie. symmetrical adjacency matrix) (5) Headless throats Returns ------- A dictionary containing the offending pores or throat numbers under each named key. It also returns a list of which pores and throats should be trimmed from the network to restore health. This list is a suggestion only, and is based on keeping the largest cluster and trimming the others. Notes ----- - Does not yet check for duplicate pores - Does not yet suggest which throats to remove - This is just a 'check' and does not 'fix' the problems it finds
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def cli(ctx, timeout, proxy, output, quiet, lyric, again): ctx.obj = NetEase(timeout, proxy, output, quiet, lyric, again)
A command tool to download NetEase-Music's songs.
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def flush_to_index(self): assert self._smref is not None assert not isinstance(self._file_or_files, BytesIO) sm = self._smref() if sm is not None: index = self._index if index is None: index = sm.repo.index index.add([sm.k_modules_file], write=self._auto_write) sm._clear_cache()
Flush changes in our configuration file to the index
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def _getphoto_location(self,pid): logger.debug(%(pid)) lat=None lon=None accuracy=None resp=self.fb.photos_geo_getLocation(photo_id=pid) if resp.attrib[]!=: logger.error("%s - fb: photos_geo_getLocation failed with status: %s",\ resp.attrib[]); return (None,None,None) for location in resp.find(): lat=location.attrib[] lon=location.attrib[] accuracy=location.attrib[] return (lat,lon,accuracy)
Asks fb for photo location information returns tuple with lat,lon,accuracy
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def view_page(name=None): if request.method == : if name is None: if len(request.forms.filename) > 0: name = request.forms.filename if name is not None: filename = "{0}.rst".format(name) file_handle = open(filename, ) file_handle.write(request.forms.content.encode()) file_handle.close() add_file_to_repo(filename) commit(filename) response.set_header(, ) response.set_header(, ) if name is None: index_files = glob.glob("./[Ii][Nn][Dd][Ee][Xx].rst") if len(index_files) == 0: return view_meta_index() else: name = index_files[0][2:-4] files = glob.glob("{0}.rst".format(name)) if len(files) > 0: file_handle = open(files[0], ) html_body = publish_parts(file_handle.read(), writer=AttowikiWriter(), settings=None, settings_overrides=None)[] history = commit_history("{0}.rst".format(name)) return template(, type="view", name=name, extended_name=None, is_repo=check_repo(), history=history, gitref=None, content=html_body) else: return static_file(name, )
Serve a page name. .. note:: this is a bottle view * if the view is called with the POST method, write the new page content to the file, commit the modification and then display the html rendering of the restructured text file * if the view is called with the GET method, directly display the html rendering of the restructured text file Keyword Arguments: :name: (str) -- name of the rest file (without the .rst extension) OPTIONAL if no filename is given, first try to find a "index.rst" file in the directory and serve it. If not found, serve the meta page __index__ Returns: bottle response object
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def send(node_name): my_data = nago.core.get_my_info() if not node_name: node_name = nago.settings.get() node = nago.core.get_node(node_name) json_params = {} json_params[] = node_name json_params[] = "node_info" for k, v in my_data.items(): nago.core.log("sending %s to %s" % (k, node[]), level="notice") json_params[k] = v return node.send_command(, , node_name=node.token, key="node_info", **my_data)
Send our information to a remote nago instance Arguments: node -- node_name or token for the node this data belongs to
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def logger_init(level): levellist = [logging.ERROR, logging.WARNING, logging.INFO, logging.DEBUG] handler = logging.StreamHandler() fmt = ( ) handler.setFormatter(logging.Formatter(fmt)) logger = logging.root logger.addHandler(handler) logger.setLevel(levellist[level])
Initialize the logger for this thread. Sets the log level to ERROR (0), WARNING (1), INFO (2), or DEBUG (3), depending on the argument `level`.
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def serialize(self): result = self.to_project_config(with_packages=True) result.update(self.to_profile_info(serialize_credentials=True)) result[] = deepcopy(self.cli_vars) return result
Serialize the full configuration to a single dictionary. For any instance that has passed validate() (which happens in __init__), it matches the Configuration contract. Note that args are not serialized. :returns dict: The serialized configuration.
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def traverse(self, id_=None): if id_ is None: id_ = self.group nodes = r_client.smembers(_children_key(id_)) while nodes: current_id = nodes.pop() details = r_client.get(current_id) if details is None: r_client.srem(_children_key(id_), current_id) continue details = self._decode(details) if details[] == : children = r_client.smembers(_children_key(details[])) if children is not None: nodes.update(children) yield details
Traverse groups and yield info dicts for jobs
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async def connect( self, hostname: str = None, port: int = None, source_address: DefaultStrType = _default, timeout: DefaultNumType = _default, loop: asyncio.AbstractEventLoop = None, use_tls: bool = None, validate_certs: bool = None, client_cert: DefaultStrType = _default, client_key: DefaultStrType = _default, tls_context: DefaultSSLContextType = _default, cert_bundle: DefaultStrType = _default, ) -> SMTPResponse: await self._connect_lock.acquire() if hostname is not None: self.hostname = hostname if loop is not None: self.loop = loop if use_tls is not None: self.use_tls = use_tls if validate_certs is not None: self.validate_certs = validate_certs if port is not None: self.port = port if self.port is None: self.port = SMTP_TLS_PORT if self.use_tls else SMTP_PORT if timeout is not _default: self.timeout = timeout if source_address is not _default: self._source_address = source_address if client_cert is not _default: self.client_cert = client_cert if client_key is not _default: self.client_key = client_key if tls_context is not _default: self.tls_context = tls_context if cert_bundle is not _default: self.cert_bundle = cert_bundle if self.tls_context is not None and self.client_cert is not None: raise ValueError( "Either a TLS context or a certificate/key must be provided" ) response = await self._create_connection() return response
Initialize a connection to the server. Options provided to :meth:`.connect` take precedence over those used to initialize the class. :keyword hostname: Server name (or IP) to connect to :keyword port: Server port. Defaults to 25 if ``use_tls`` is False, 465 if ``use_tls`` is True. :keyword source_address: The hostname of the client. Defaults to the result of :func:`socket.getfqdn`. Note that this call blocks. :keyword timeout: Default timeout value for the connection, in seconds. Defaults to 60. :keyword loop: event loop to run on. If not set, uses :func:`asyncio.get_event_loop()`. :keyword use_tls: If True, make the initial connection to the server over TLS/SSL. Note that if the server supports STARTTLS only, this should be False. :keyword validate_certs: Determines if server certificates are validated. Defaults to True. :keyword client_cert: Path to client side certificate, for TLS. :keyword client_key: Path to client side key, for TLS. :keyword tls_context: An existing :class:`ssl.SSLContext`, for TLS. Mutually exclusive with ``client_cert``/``client_key``. :keyword cert_bundle: Path to certificate bundle, for TLS verification. :raises ValueError: mutually exclusive options provided
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def update(self, other=None, **kwargs): if other is None: other = () if hasattr(other, ): for key in other: self._update(key, other[key]) else: for key,value in other: self._update(key, value) for key,value in six.iteritems(kwargs): self._update(key, value)
x.update(E, **F) -> None. update x from trie/dict/iterable E or F. If E has a .keys() method, does: for k in E: x[k] = E[k] If E lacks .keys() method, does: for (k, v) in E: x[k] = v In either case, this is followed by: for k in F: x[k] = F[k]
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def formatted(text, *args, **kwargs): if not text or "{" not in text: return text strict = kwargs.pop("strict", True) max_depth = kwargs.pop("max_depth", 3) objects = list(args) + [kwargs] if kwargs else args[0] if len(args) == 1 else args if not objects: return text definitions = {} markers = RE_FORMAT_MARKERS.findall(text) while markers: key = markers.pop() if key in definitions: continue val = _find_value(key, objects) if strict and val is None: return None val = str(val) if val is not None else "{%s}" % key markers.extend(m for m in RE_FORMAT_MARKERS.findall(val) if m not in definitions) definitions[key] = val if not max_depth or not isinstance(max_depth, int) or max_depth <= 0: return text expanded = dict((k, _rformat(k, v, definitions, max_depth)) for k, v in definitions.items()) return text.format(**expanded)
Args: text (str | unicode): Text to format *args: Objects to extract values from (as attributes) **kwargs: Optional values provided as named args Returns: (str): Attributes from this class are expanded if mentioned
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def _isstring(dtype): return dtype.type == numpy.unicode_ or dtype.type == numpy.string_
Given a numpy dtype, determines whether it is a string. Returns True if the dtype is string or unicode.
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def parse(self) -> Statement: self.opt_separator() start = self.offset res = self.statement() if res.keyword not in ["module", "submodule"]: self.offset = start raise UnexpectedInput(self, " or ") if self.name is not None and res.argument != self.name: raise ModuleNameMismatch(res.argument, self.name) if self.rev: revst = res.find1("revision") if revst is None or revst.argument != self.rev: raise ModuleRevisionMismatch(revst.argument, self.rev) try: self.opt_separator() except EndOfInput: return res raise UnexpectedInput(self, "end of input")
Parse a complete YANG module or submodule. Args: mtext: YANG module text. Raises: EndOfInput: If past the end of input. ModuleNameMismatch: If parsed module name doesn't match `self.name`. ModuleRevisionMismatch: If parsed revision date doesn't match `self.rev`. UnexpectedInput: If top-level statement isn't ``(sub)module``.
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def username(anon, obj, field, val): return anon.faker.user_name(field=field)
Generates a random username
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def max_brightness(self): self._max_brightness, value = self.get_cached_attr_int(self._max_brightness, ) return value
Returns the maximum allowable brightness value.
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def snyder_opt(self, structure): nsites = structure.num_sites volume = structure.volume num_density = 1e30 * nsites / volume return 1.66914e-23 * \ (self.long_v(structure) + 2.*self.trans_v(structure))/3. \ / num_density ** (-2./3.) * (1 - nsites ** (-1./3.))
Calculates Snyder's optical sound velocity (in SI units) Args: structure: pymatgen structure object Returns: Snyder's optical sound velocity (in SI units)
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def set_gss_host(self, gss_host, trust_dns=True, gssapi_requested=True): if not gssapi_requested: return if gss_host is None: gss_host = self.hostname if trust_dns and gss_host is not None: gss_host = socket.getfqdn(gss_host) self.gss_host = gss_host
Normalize/canonicalize ``self.gss_host`` depending on various factors. :param str gss_host: The explicitly requested GSS-oriented hostname to connect to (i.e. what the host's name is in the Kerberos database.) Defaults to ``self.hostname`` (which will be the 'real' target hostname and/or host portion of given socket object.) :param bool trust_dns: Indicates whether or not DNS is trusted; if true, DNS will be used to canonicalize the GSS hostname (which again will either be ``gss_host`` or the transport's default hostname.) (Defaults to True due to backwards compatibility.) :param bool gssapi_requested: Whether GSSAPI key exchange or authentication was even requested. If not, this is a no-op and nothing happens (and ``self.gss_host`` is not set.) (Defaults to True due to backwards compatibility.) :returns: ``None``.
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def rnaseq2ga(quantificationFilename, sqlFilename, localName, rnaType, dataset=None, featureType="gene", description="", programs="", featureSetNames="", readGroupSetNames="", biosampleId=""): readGroupSetName = "" if readGroupSetNames: readGroupSetName = readGroupSetNames.strip().split(",")[0] featureSetIds = "" readGroupIds = "" if dataset: featureSetIdList = [] if featureSetNames: for annotationName in featureSetNames.split(","): featureSet = dataset.getFeatureSetByName(annotationName) featureSetIdList.append(featureSet.getId()) featureSetIds = ",".join(featureSetIdList) if readGroupSetName: readGroupSet = dataset.getReadGroupSetByName(readGroupSetName) readGroupIds = ",".join( [x.getId() for x in readGroupSet.getReadGroups()]) if rnaType not in SUPPORTED_RNA_INPUT_FORMATS: raise exceptions.UnsupportedFormatException(rnaType) rnaDB = RnaSqliteStore(sqlFilename) if rnaType == "cufflinks": writer = CufflinksWriter(rnaDB, featureType, dataset=dataset) elif rnaType == "kallisto": writer = KallistoWriter(rnaDB, featureType, dataset=dataset) elif rnaType == "rsem": writer = RsemWriter(rnaDB, featureType, dataset=dataset) writeRnaseqTable(rnaDB, [localName], description, featureSetIds, readGroupId=readGroupIds, programs=programs, biosampleId=biosampleId) writeExpressionTable(writer, [(localName, quantificationFilename)])
Reads RNA Quantification data in one of several formats and stores the data in a sqlite database for use by the GA4GH reference server. Supports the following quantification output types: Cufflinks, kallisto, RSEM.
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def get_links(self, recall, timeout): for _ in range(recall): try: soup = BeautifulSoup(self.source) out_links = [] for tag in soup.findAll(["a", "link"], href=True): tag["href"] = urljoin(self.url, tag["href"]) out_links.append(tag["href"]) return sorted(out_links) except: time.sleep(timeout)
Gets links in page :param recall: max times to attempt to fetch url :param timeout: max times :return: array of out_links
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def disable_signing(self): self.mav.signing.secret_key = None self.mav.signing.sign_outgoing = False self.mav.signing.allow_unsigned_callback = None self.mav.signing.link_id = 0 self.mav.signing.timestamp = 0
disable MAVLink2 signing
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def view_hmap(token, dstore): try: poe = valid.probability(token.split()[1]) except IndexError: poe = 0.1 mean = dict(extract(dstore, ))[] oq = dstore[] hmap = calc.make_hmap_array(mean, oq.imtls, [poe], len(mean)) dt = numpy.dtype([(, U32)] + [(imt, F32) for imt in oq.imtls]) array = numpy.zeros(len(hmap), dt) for i, vals in enumerate(hmap): array[i] = (i, ) + tuple(vals) array.sort(order=list(oq.imtls)[0]) return rst_table(array[:20])
Display the highest 20 points of the mean hazard map. Called as $ oq show hmap:0.1 # 10% PoE
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def _popup(self): res = () for child in self.formulas: if type(child) == type(self): superchilds = child.formulas res += superchilds else: res += (child, ) return tuple(res)
recursively find commutative binary operator among child formulas and pop up them at the same level
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def load_config(path): path = os.path.abspath(path) if os.path.isdir(path): config, wordlists = _load_data(path) elif os.path.isfile(path): config = _load_config(path) wordlists = {} else: raise InitializationError(.format(path)) for name, wordlist in wordlists.items(): if name in config: raise InitializationError("Conflict: list {!r} is defined both in config " "and in *.txt file. If it's a {!r} list, " "you should remove it from config." .format(name, _CONF.TYPE.WORDS)) config[name] = wordlist return config
Loads configuration from a path. Path can be a json file, or a directory containing config.json and zero or more *.txt files with word lists or phrase lists. Returns config dict. Raises InitializationError when something is wrong.
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def to_json(self): return json.dumps({ "statistics": self.get_statistics() , "authors": [json.loads(author.to_json()) for author in self.get_authors()] }, indent=2)
Serialises the content of the KnowledgeBase as JSON. :return: TODO
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def start(self, *args, **kwargs): if self.is_running(): raise RuntimeError() self._running = self.run(*args, **kwargs) try: yielded = next(self._running) except StopIteration: raise TypeError() if yielded is not None: raise TypeError()
Starts the instance. :raises RuntimeError: has been already started. :raises TypeError: :meth:`run` is not canonical.
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def multchoicebox(message=, title=, choices=[]): return psidialogs.multi_choice(message=message, title=title, choices=choices)
Original doc: Present the user with a list of choices. allow him to select multiple items and return them in a list. if the user doesn't choose anything from the list, return the empty list. return None if he cancelled selection.
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def count(self): return functools.reduce(lambda x, y: x * y, (x.count for x in self.bounds))
Total number of array cells
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def get_resource_siblings(raml_resource): path = raml_resource.path return [res for res in raml_resource.root.resources if res.path == path]
Get siblings of :raml_resource:. :param raml_resource: Instance of ramlfications.raml.ResourceNode.
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def nsx_controller_connection_addr_port(self, **kwargs): config = ET.Element("config") nsx_controller = ET.SubElement(config, "nsx-controller", xmlns="urn:brocade.com:mgmt:brocade-tunnels") name_key = ET.SubElement(nsx_controller, "name") name_key.text = kwargs.pop() connection_addr = ET.SubElement(nsx_controller, "connection-addr") port = ET.SubElement(connection_addr, "port") port.text = kwargs.pop() callback = kwargs.pop(, self._callback) return callback(config)
Auto Generated Code
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def mag_to_fnu(self, mag): if len(band) != 2 or band[1] != : raise ValueError( + band) return abmag_to_fnu_cgs(mag)
SDSS *primed* magnitudes to F_ν. The primed magnitudes are the "USNO" standard-star system defined in Smith+ (2002AJ....123.2121S) and Fukugita+ (1996AJ....111.1748F). This system is anchored to the AB magnitude system, and as far as I can tell it is not known to have measurable offsets from that system. (As of DR10, the *unprimed* SDSS system is known to have small offsets from AB, but I do not believe that that necessarily has implications for u'g'r'i'z'.) However, as far as I can tell the filter responses of the USNO telescope are not published -- only those of the main SDSS 2.5m telescope. The whole reason for the existence of both the primed and unprimed ugriz systems is that their responses do not quite match. For my current application, which involves a completely different telescope anyway, the difference shouldn't matter.
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def loads(string, triples=False, cls=PENMANCodec, **kwargs): codec = cls(**kwargs) return list(codec.iterdecode(string, triples=triples))
Deserialize a list of PENMAN-encoded graphs from *string*. Args: string: a string containing graph data triples: if True, read graphs as triples instead of as PENMAN cls: serialization codec class kwargs: keyword arguments passed to the constructor of *cls* Returns: a list of Graph objects
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def search_dashboard_deleted_for_facet(self, facet, **kwargs): kwargs[] = True if kwargs.get(): return self.search_dashboard_deleted_for_facet_with_http_info(facet, **kwargs) else: (data) = self.search_dashboard_deleted_for_facet_with_http_info(facet, **kwargs) return data
Lists the values of a specific facet over the customer's deleted dashboards # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.search_dashboard_deleted_for_facet(facet, async_req=True) >>> result = thread.get() :param async_req bool :param str facet: (required) :param FacetSearchRequestContainer body: :return: ResponseContainerFacetResponse If the method is called asynchronously, returns the request thread.
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def analyze_text( self, text, **kwargs ): SYHSYHBIOs text; Regardless the return type, a layer named NOUN_CHUNKS will be added to the input Text containing noun phrase annotations; cutPhrasesforce_parsingsyntax_layercutMaxThresholdreturn_type Unexpected return type: Unsupported argument given: (!) Unknown type of syntactic parser: OBI'] else l for l in np_labels ] all_np_labels.extend( np_labels ) if annotate_text: self.annotateText( text, NOUN_CHUNKS, all_np_labels ) if return_type == "text": return text elif return_type == "labels": return all_np_labels elif return_type == "tokens": return self.get_phrases(text, all_np_labels) else: return self.get_phrase_texts(text, all_np_labels)
Analyzes given Text for noun phrase chunks. As result of analysis, a layer NOUN_CHUNKS will be attached to the input Text object, containing a noun phrases detected from the Text; Note: for preprocessing the Text, MaltParser is used by default. In order to obtain a decent performance with MaltParser, it is advisable to analyse texts at their full extent with this method. Splitting a text into smaller chunks, such as clauses or sentences, and analysing one-small-chunk-at-time may be rather demanding in terms of performance, because a file-based preprocessing is used for obtaining the dependency relations. Parameters ---------- text: estnltk.text.Text The input text that should be analysed for noun phrases; force_parsing : bool If True, uses the *self.parser* to parse the given *text*, and overrides the syntactic annotations in *text* with the new layer obtained from the parser; (default: False) syntax_layer : str Specifies which layer of syntactic annotations should be used as a basis for NP chunking; If the *syntax_layer* exists within the *text* (and force_parsing==False), uses the syntactic annotations from *text[syntax_layer]*; (default: LAYER_CONLL) cutPhrases: bool If True, all phrases exceeding the cutMaxThreshold will be cut into single word phrases, consisting only of part-of-speech categories 'S', 'Y', 'H'; (default: True) cutMaxThreshold: int Threshold indicating the maximum number of words allowed in a phrase. If cutPhrases is set, all phrases exceeding the threshold will be cut into single word phrases, consisting only of part-of-speech categories 'S', 'Y', 'H'; Automatic analysis of the Balanced Corpus of Estonian suggests that 97% of all NP chunks are likely chunks of length 1-3, thus the default threshold is set to 3; (default value: 3) return_type: string If return_type=="text" (Default), returns the input Text object; If return_type=="labels", returns a list of NP labels (strings), containing a label for each word token in Text, indicating whether the word is at the beginning of a phrase ('B'), inside a phrase ('I') or does not belong to any phrase ('O'). If return_type=="tokens", returns a list of phrases, where each phrase is a list of tokens, and each token is a dictionary representing word; If return_type=="strings", returns a list of text strings, where each string is phrase's text; Regardless the return type, a layer named NOUN_CHUNKS will be added to the input Text containing noun phrase annotations;
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def output_to_table(obj, olist=, oformat=, table_ends=False, prefix=""): para = "" property_list = [] if olist == : property_list = obj.inputs elif olist == : for item in obj.__dict__: if "_" != item[0]: property_list.append(item) for item in property_list: if hasattr(obj, item): value = getattr(obj, item) value_str = format_value(value) if oformat == "latex": delimeter = " & " else: delimeter = "," para += "{0}{1}{2}\\\\\n".format(prefix + format_name(item), delimeter, value_str) if table_ends: para = add_table_ends(para, oformat) return para
Compile the properties to a table. :param olist: list, Names of the parameters to be in the output table :param oformat: str, The type of table to be output :param table_ends: bool, Add ends to the table :param prefix: str, A string to be added to the start of each parameter name :return: para, str, table as a string
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def main(): parser = OptionParser() parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, type=, default=) parser.add_option(, , help=, dest=, action=, default=False) options, _ = parser.parse_args() try: lockfile = os.path.join(options.lockdir, ) with open(lockfile, ) as lock: fcntl.lockf(lock, fcntl.LOCK_EX | fcntl.LOCK_NB) work(options) except IOError: info("=> Another instance is already running") sys.exit(254)
Main entry point
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def get_filepath(self, filename): return os.path.join(self.parent_folder, self.product_id, self.add_file_extension(filename)).replace(, )
Creates file path for the file. :param filename: name of the file :type filename: str :return: filename with path on disk :rtype: str
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async def _connect(self, connection_lost_callbk=None): self.connection_lost_callbk = connection_lost_callbk url = self._config[] LOG.info("Connecting to ElkM1 at %s", url) scheme, dest, param, ssl_context = parse_url(url) conn = partial(Connection, self.loop, self._connected, self._disconnected, self._got_data, self._timeout) try: if scheme == : await serial_asyncio.create_serial_connection( self.loop, conn, dest, baudrate=param) else: await asyncio.wait_for(self.loop.create_connection( conn, host=dest, port=param, ssl=ssl_context), timeout=30) except (ValueError, OSError, asyncio.TimeoutError) as err: LOG.warning("Could not connect to ElkM1 (%s). Retrying in %d seconds", err, self._connection_retry_timer) self.loop.call_later(self._connection_retry_timer, self.connect) self._connection_retry_timer = 2 * self._connection_retry_timer \ if self._connection_retry_timer < 32 else 60
Asyncio connection to Elk.
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def add_install_defaults(args): if attr == "genomes" and len(args.genomes) > 0: continue for x in default_args.get(attr, []): x = str(x) new_val = getattr(args, attr) if x not in getattr(args, attr): new_val.append(x) setattr(args, attr, new_val) args = _datatarget_defaults(args, default_args) if "isolate" in default_args and args.isolate is not True: args.isolate = default_args["isolate"] return args
Add any saved installation defaults to the upgrade.
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def set_line_join(self, line_join): cairo.cairo_set_line_join(self._pointer, line_join) self._check_status()
Set the current :ref:`LINE_JOIN` within the cairo context. As with the other stroke parameters, the current line cap style is examined by :meth:`stroke`, :meth:`stroke_extents`, and :meth:`stroke_to_path`, but does not have any effect during path construction. The default line cap is :obj:`MITER <LINE_JOIN_MITER>`. :param line_join: A :ref:`LINE_JOIN` string.
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def get_blank_row(self, filler="-", splitter="+"): return self.get_pretty_row( ["" for _ in self.widths], filler, splitter, )
Gets blank row :param filler: Fill empty columns with this char :param splitter: Separate columns with this char :return: Pretty formatted blank row (with no meaningful data in it)
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def filter_by_analysis_period(self, analysis_period): self._check_analysis_period(analysis_period) _filtered_data = self.filter_by_moys(analysis_period.moys) _filtered_data.header._analysis_period = analysis_period return _filtered_data
Filter a Data Collection based on an analysis period. Args: analysis period: A Ladybug analysis period Return: A new Data Collection with filtered data
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def hardware_custom_profile_kap_custom_profile_xstp_xstp_hello_interval(self, **kwargs): config = ET.Element("config") hardware = ET.SubElement(config, "hardware", xmlns="urn:brocade.com:mgmt:brocade-hardware") custom_profile = ET.SubElement(hardware, "custom-profile") kap_custom_profile = ET.SubElement(custom_profile, "kap-custom-profile") name_key = ET.SubElement(kap_custom_profile, "name") name_key.text = kwargs.pop() xstp = ET.SubElement(kap_custom_profile, "xstp") xstp_hello_interval = ET.SubElement(xstp, "xstp_hello_interval") xstp_hello_interval.text = kwargs.pop() callback = kwargs.pop(, self._callback) return callback(config)
Auto Generated Code
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def setSignals(self, vehID, signals): self._connection._sendIntCmd( tc.CMD_SET_VEHICLE_VARIABLE, tc.VAR_SIGNALS, vehID, signals)
setSignals(string, integer) -> None Sets an integer encoding the state of the vehicle's signals.
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def pix2vec(nside, ipix, nest=False): lon, lat = healpix_to_lonlat(ipix, nside, order= if nest else ) return ang2vec(*_lonlat_to_healpy(lon, lat))
Drop-in replacement for healpy `~healpy.pixelfunc.pix2vec`.
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def getSegmentOnCell(self, c, i, segIdx): segList = self.cells4.getNonEmptySegList(c,i) seg = self.cells4.getSegment(c, i, segList[segIdx]) numSyn = seg.size() assert numSyn != 0 result = [] result.append([int(segIdx), bool(seg.isSequenceSegment()), seg.getPositiveActivations(), seg.getTotalActivations(), seg.getLastActiveIteration(), seg.getLastPosDutyCycle(), seg.getLastPosDutyCycleIteration()]) for s in xrange(numSyn): sc, si = self.getColCellIdx(seg.getSrcCellIdx(s)) result.append([int(sc), int(si), seg.getPermanence(s)]) return result
Overrides :meth:`nupic.algorithms.backtracking_tm.BacktrackingTM.getSegmentOnCell`.
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def append(self, data: Union[bytes, bytearray, memoryview]) -> None: size = len(data) if size > self._large_buf_threshold: if not isinstance(data, memoryview): data = memoryview(data) self._buffers.append((True, data)) elif size > 0: if self._buffers: is_memview, b = self._buffers[-1] new_buf = is_memview or len(b) >= self._large_buf_threshold else: new_buf = True if new_buf: self._buffers.append((False, bytearray(data))) else: b += data self._size += size
Append the given piece of data (should be a buffer-compatible object).
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def preprocess(self): s convertible. ' self.processed_tables = [] self.flags_by_table = [] self.units_by_table = [] for worksheet, rtable in enumerate(self.raw_tables): ptable, flags, units = self.preprocess_worksheet(rtable, worksheet) self.processed_tables.append(ptable) self.flags_by_table.append(flags) self.units_by_table.append(units) return self.processed_tables
Performs initial cell conversions to standard types. This will strip units, scale numbers, and identify numeric data where it's convertible.
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def p_sigtypes(self, p): p[0] = p[1] + (p[2],) p.set_lineno(0, p.lineno(1))
sigtypes : sigtypes sigtype
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def document_from_string(self, schema, request_string): key = self.get_key_for_schema_and_document_string(schema, request_string) if key not in self.cache_map: self.cache_map[key] = self.fallback_backend.document_from_string( schema, request_string ) self.get_worker().queue(self.queue_backend, key, schema, request_string) return self.cache_map[key]
This method returns a GraphQLQuery (from cache if present)
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def get_bins_by_resource(self, resource_id): mgr = self._get_provider_manager(, local=True) lookup_session = mgr.get_bin_lookup_session(proxy=self._proxy) return lookup_session.get_bins_by_ids( self.get_bin_ids_by_resource(resource_id))
Gets the list of ``Bin`` objects mapped to a ``Resource``. arg: resource_id (osid.id.Id): ``Id`` of a ``Resource`` return: (osid.resource.BinList) - list of bins raise: NotFound - ``resource_id`` is not found raise: NullArgument - ``resource_id`` is ``null`` raise: OperationFailed - unable to complete request raise: PermissionDenied - authorization failure *compliance: mandatory -- This method must be implemented.*
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def calc_acceleration(xdata, dt): acceleration = _np.diff(_np.diff(xdata))/dt**2 return acceleration
Calculates the acceleration from the position Parameters ---------- xdata : ndarray Position data dt : float time between measurements Returns ------- acceleration : ndarray values of acceleration from position 2 to N.
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def _get_layer_converter_fn(layer, add_custom_layers = False): layer_type = type(layer) if layer_type in _KERAS_LAYER_REGISTRY: convert_func = _KERAS_LAYER_REGISTRY[layer_type] if convert_func is _layers2.convert_activation: act_name = _layers2._get_activation_name_from_keras_layer(layer) if act_name == : return None return convert_func elif add_custom_layers: return None else: raise TypeError("Keras layer of type %s is not supported." % type(layer))
Get the right converter function for Keras
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def text(what="sentence", *args, **kwargs): if what == "character": return character(*args, **kwargs) elif what == "characters": return characters(*args, **kwargs) elif what == "word": return word(*args, **kwargs) elif what == "words": return words(*args, **kwargs) elif what == "sentence": return sentence(*args, **kwargs) elif what == "sentences": return sentences(*args, **kwargs) elif what == "paragraph": return paragraph(*args, **kwargs) elif what == "paragraphs": return paragraphs(*args, **kwargs) elif what == "title": return title(*args, **kwargs) else: raise NameError()
An aggregator for all above defined public methods.
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def reference_to_greatcircle(reference_frame, greatcircle_frame): pole = greatcircle_frame.pole.transform_to(coord.ICRS) ra0 = greatcircle_frame.ra0 center = greatcircle_frame.center R_rot = rotation_matrix(greatcircle_frame.rotation, ) if not np.isnan(ra0): xaxis = np.array([np.cos(ra0), np.sin(ra0), 0.]) zaxis = pole.cartesian.xyz.value if np.abs(zaxis[2]) >= 1e-15: xaxis[2] = -(zaxis[0]*xaxis[0] + zaxis[1]*xaxis[1]) / zaxis[2] else: xaxis[2] = 0. xaxis = xaxis / np.sqrt(np.sum(xaxis**2)) yaxis = np.cross(zaxis, xaxis) R = np.stack((xaxis, yaxis, zaxis)) elif center is not None: R1 = rotation_matrix(pole.ra, ) R2 = rotation_matrix(90*u.deg - pole.dec, ) Rtmp = matrix_product(R2, R1) rot = center.cartesian.transform(Rtmp) rot_lon = rot.represent_as(coord.UnitSphericalRepresentation).lon R3 = rotation_matrix(rot_lon, ) R = matrix_product(R3, R2, R1) else: R1 = rotation_matrix(pole.ra, ) R2 = rotation_matrix(pole.dec, ) R = matrix_product(R2, R1) return matrix_product(R_rot, R)
Convert a reference coordinate to a great circle frame.
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def QA_util_code_tolist(code, auto_fill=True): if isinstance(code, str): if auto_fill: return [QA_util_code_tostr(code)] else: return [code] elif isinstance(code, list): if auto_fill: return [QA_util_code_tostr(item) for item in code] else: return [item for item in code]
转换code==> list Arguments: code {[type]} -- [description] Keyword Arguments: auto_fill {bool} -- 是否自动补全(一般是用于股票/指数/etf等6位数,期货不适用) (default: {True}) Returns: [list] -- [description]
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def _compute_dependencies(self): from _markerlib import compile as compile_marker dm = self.__dep_map = {None: []} reqs = [] for req in self._parsed_pkg_info.get_all() or []: distvers, mark = self._preparse_requirement(req) parsed = parse_requirements(distvers).next() parsed.marker_fn = compile_marker(mark) reqs.append(parsed) def reqs_for_extra(extra): for req in reqs: if req.marker_fn(override={:extra}): yield req common = frozenset(reqs_for_extra(None)) dm[None].extend(common) for extra in self._parsed_pkg_info.get_all() or []: extra = safe_extra(extra.strip()) dm[extra] = list(frozenset(reqs_for_extra(extra)) - common) return dm
Recompute this distribution's dependencies.
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def previous(self, cli): if len(self.focus_stack) > 1: try: return self[self.focus_stack[-2]] except KeyError: pass
Return the previously focussed :class:`.Buffer` or `None`.
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def foreach(self, f): from pyspark.rdd import _wrap_function from pyspark.serializers import PickleSerializer, AutoBatchedSerializer from pyspark.taskcontext import TaskContext if callable(f): def func_without_process(_, iterator): for x in iterator: f(x) return iter([]) func = func_without_process else: if not hasattr(f, ): raise Exception("Provided object does not have a method") if not callable(getattr(f, )): raise Exception("Attribute in provided object is not callable") def doesMethodExist(method_name): exists = hasattr(f, method_name) if exists and not callable(getattr(f, method_name)): raise Exception( "Attribute in provided object is not callable" % method_name) return exists open_exists = doesMethodExist() close_exists = doesMethodExist() def func_with_open_process_close(partition_id, iterator): epoch_id = TaskContext.get().getLocalProperty() if epoch_id: epoch_id = int(epoch_id) else: raise Exception("Could not get batch id from TaskContext") should_process = True if open_exists: should_process = f.open(partition_id, epoch_id) error = None try: if should_process: for x in iterator: f.process(x) except Exception as ex: error = ex finally: if close_exists: f.close(error) if error: raise error return iter([]) func = func_with_open_process_close serializer = AutoBatchedSerializer(PickleSerializer()) wrapped_func = _wrap_function(self._spark._sc, func, serializer, serializer) jForeachWriter = \ self._spark._sc._jvm.org.apache.spark.sql.execution.python.PythonForeachWriter( wrapped_func, self._df._jdf.schema()) self._jwrite.foreach(jForeachWriter) return self
Sets the output of the streaming query to be processed using the provided writer ``f``. This is often used to write the output of a streaming query to arbitrary storage systems. The processing logic can be specified in two ways. #. A **function** that takes a row as input. This is a simple way to express your processing logic. Note that this does not allow you to deduplicate generated data when failures cause reprocessing of some input data. That would require you to specify the processing logic in the next way. #. An **object** with a ``process`` method and optional ``open`` and ``close`` methods. The object can have the following methods. * ``open(partition_id, epoch_id)``: *Optional* method that initializes the processing (for example, open a connection, start a transaction, etc). Additionally, you can use the `partition_id` and `epoch_id` to deduplicate regenerated data (discussed later). * ``process(row)``: *Non-optional* method that processes each :class:`Row`. * ``close(error)``: *Optional* method that finalizes and cleans up (for example, close connection, commit transaction, etc.) after all rows have been processed. The object will be used by Spark in the following way. * A single copy of this object is responsible of all the data generated by a single task in a query. In other words, one instance is responsible for processing one partition of the data generated in a distributed manner. * This object must be serializable because each task will get a fresh serialized-deserialized copy of the provided object. Hence, it is strongly recommended that any initialization for writing data (e.g. opening a connection or starting a transaction) is done after the `open(...)` method has been called, which signifies that the task is ready to generate data. * The lifecycle of the methods are as follows. For each partition with ``partition_id``: ... For each batch/epoch of streaming data with ``epoch_id``: ....... Method ``open(partitionId, epochId)`` is called. ....... If ``open(...)`` returns true, for each row in the partition and batch/epoch, method ``process(row)`` is called. ....... Method ``close(errorOrNull)`` is called with error (if any) seen while processing rows. Important points to note: * The `partitionId` and `epochId` can be used to deduplicate generated data when failures cause reprocessing of some input data. This depends on the execution mode of the query. If the streaming query is being executed in the micro-batch mode, then every partition represented by a unique tuple (partition_id, epoch_id) is guaranteed to have the same data. Hence, (partition_id, epoch_id) can be used to deduplicate and/or transactionally commit data and achieve exactly-once guarantees. However, if the streaming query is being executed in the continuous mode, then this guarantee does not hold and therefore should not be used for deduplication. * The ``close()`` method (if exists) will be called if `open()` method exists and returns successfully (irrespective of the return value), except if the Python crashes in the middle. .. note:: Evolving. >>> # Print every row using a function >>> def print_row(row): ... print(row) ... >>> writer = sdf.writeStream.foreach(print_row) >>> # Print every row using a object with process() method >>> class RowPrinter: ... def open(self, partition_id, epoch_id): ... print("Opened %d, %d" % (partition_id, epoch_id)) ... return True ... def process(self, row): ... print(row) ... def close(self, error): ... print("Closed with error: %s" % str(error)) ... >>> writer = sdf.writeStream.foreach(RowPrinter())
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def mu(self): mu = self._models[0].mu assert all([mu == model.mu for model in self._models]) return mu
See docs for `Model` abstract base class.
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def set_url_part(url, **kwargs): d = parse_url_to_dict(url) d.update(kwargs) return unparse_url_dict(d)
Change one or more parts of a URL
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def add_oxidation_state_by_site_fraction(structure, oxidation_states): try: for i, site in enumerate(structure): new_sp = collections.defaultdict(float) for j, (el, occu) in enumerate(get_z_ordered_elmap(site .species)): specie = Specie(el.symbol, oxidation_states[i][j]) new_sp[specie] += occu structure[i] = new_sp return structure except IndexError: raise ValueError("Oxidation state of all sites must be " "specified in the list.")
Add oxidation states to a structure by fractional site. Args: oxidation_states (list): List of list of oxidation states for each site fraction for each site. E.g., [[2, 4], [3], [-2], [-2], [-2]]
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def clear_cached_values(self): self._prof_interp = None self._prof_y = None self._prof_z = None self._marg_interp = None self._marg_z = None self._post = None self._post_interp = None self._interp = None self._ret_type = None
Removes all of the cached values and interpolators
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def filter_data(data, kernel, mode=, fill_value=0.0, check_normalization=False): from scipy import ndimage if kernel is not None: if isinstance(kernel, Kernel2D): kernel_array = kernel.array else: kernel_array = kernel if check_normalization: if not np.allclose(np.sum(kernel_array), 1.0): warnings.warn(, AstropyUserWarning) return ndimage.convolve(data.astype(float), kernel_array, mode=mode, cval=fill_value) else: return data
Convolve a 2D image with a 2D kernel. The kernel may either be a 2D `~numpy.ndarray` or a `~astropy.convolution.Kernel2D` object. Parameters ---------- data : array_like The 2D array of the image. kernel : array-like (2D) or `~astropy.convolution.Kernel2D` The 2D kernel used to filter the input ``data``. Filtering the ``data`` will smooth the noise and maximize detectability of objects with a shape similar to the kernel. mode : {'constant', 'reflect', 'nearest', 'mirror', 'wrap'}, optional The ``mode`` determines how the array borders are handled. For the ``'constant'`` mode, values outside the array borders are set to ``fill_value``. The default is ``'constant'``. fill_value : scalar, optional Value to fill data values beyond the array borders if ``mode`` is ``'constant'``. The default is ``0.0``. check_normalization : bool, optional If `True` then a warning will be issued if the kernel is not normalized to 1.
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def register_surrogateescape(): if six.PY3: return try: codecs.lookup_error(FS_ERRORS) except LookupError: codecs.register_error(FS_ERRORS, surrogateescape_handler)
Registers the surrogateescape error handler on Python 2 (only)
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def get_clients(self, limit=None, offset=None): data = {} if limit: data[] = limit if offset: data[] = offset result = self._request(, , data=json.dumps(data)) return result.json()
Returns a list of clients.
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def hmget(self, name, keys, *args): "Returns a list of values ordered identically to ``keys``" args = list_or_args(keys, args) return self.execute_command(, name, *args)
Returns a list of values ordered identically to ``keys``
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def p_subidentifiers(self, p): n = len(p) if n == 3: p[0] = p[1] + [p[2]] elif n == 2: p[0] = [p[1]]
subidentifiers : subidentifiers subidentifier | subidentifier
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def run(path, code=None, params=None, ignore=None, select=None, **meta): complexity = params.get(, 10) no_assert = params.get(, False) show_closures = params.get(, False) visitor = ComplexityVisitor.from_code(code, no_assert=no_assert) blocks = visitor.blocks if show_closures: blocks = add_inner_blocks(blocks) return [ {: block.lineno, : block.col_offset, : , : , : % (block.name, block.complexity)} for block in visitor.blocks if block.complexity > complexity ]
Check code with Radon. :return list: List of errors.
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def obj_to_json(self, file_path=None, indent=2, sort_keys=False, quote_numbers=True): data = [row.obj_to_ordered_dict(self.columns) for row in self] if not quote_numbers: for row in data: for k, v in row.items(): if isinstance(v, (bool, int, float)): row[k] = str(row[k]) ret = json.dumps(data, indent=indent, sort_keys=sort_keys) if sys.version_info[0] == 2: ret = ret.replace(, ) self._save_file(file_path, ret) return ret
This will return a str of a json list. :param file_path: path to data file, defaults to self's contents if left alone :param indent: int if set to 2 will indent to spaces and include line breaks. :param sort_keys: sorts columns as oppose to column order. :param quote_numbers: bool if True will quote numbers that are strings :return: string representing the grid formation of the relevant data
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def hr_size(num, suffix=) -> str: for unit in : if abs(num) < 1024.0: return "%3.1f%s%s" % (num, unit if unit != else , suffix) num /= 1024.0 return "%.1f%s%s" % (num, , suffix)
Human-readable data size From https://stackoverflow.com/a/1094933 :param num: number of bytes :param suffix: Optional size specifier :return: Formatted string
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def output(self, stream, disabletransferencoding = None): if self._sendHeaders: raise HttpProtocolException() self.outputstream = stream try: content_length = len(stream) except Exception: pass else: self.header(b, str(content_length).encode()) if disabletransferencoding is not None: self.disabledeflate = disabletransferencoding self._startResponse()
Set output stream and send response immediately
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def encrypt(self, plaintext): if not isinstance(plaintext, int): raise ValueError() if not self.in_range.contains(plaintext): raise OutOfRangeError() return self.encrypt_recursive(plaintext, self.in_range, self.out_range)
Encrypt the given plaintext value
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def add_access_policy_filter(request, query, column_name): q = d1_gmn.app.models.Subject.objects.filter( subject__in=request.all_subjects_set ).values() filter_arg = .format(column_name) return query.filter(**{filter_arg: q})
Filter records that do not have ``read`` or better access for one or more of the active subjects. Since ``read`` is the lowest access level that a subject can have, this method only has to filter on the presence of the subject.
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def xml_endtag (self, name): self.level -= 1 assert self.level >= 0 self.write(self.indent*self.level) self.writeln(u"</%s>" % xmlquote(name))
Write XML end tag.
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def get_angle(self, verify = False): LSB = self.bus.read_byte_data(self.address, self.angle_LSB) MSB = self.bus.read_byte_data(self.address, self.angle_MSB) DATA = (MSB << 6) + LSB if not verify: return (360.0 / 2**14) * DATA else: status = self.get_diagnostics() if not (status[]) and not(status[]) and not(status[]): return (360.0 / 2**14) * DATA else: return None
Retuns measured angle in degrees in range 0-360.
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def interconnect_link_topologies(self): if not self.__interconnect_link_topologies: self.__interconnect_link_topologies = InterconnectLinkTopologies(self.__connection) return self.__interconnect_link_topologies
Gets the InterconnectLinkTopologies API client. Returns: InterconnectLinkTopologies:
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def DiscreteUniform(n=10,LB=1,UB=99,B=100): B = 100 s = [0]*n for i in range(n): s[i] = random.randint(LB,UB) return s,B
DiscreteUniform: create random, uniform instance for the bin packing problem.
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def iflatten(seq, isSeq=isSeq): r for elt in seq: if isSeq(elt): for x in iflatten(elt, isSeq): yield x else: yield elt
r"""Like `flatten` but lazy.
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def _mark_started(self): log = self._params.get(, self._discard) now = time.time() self._started = now limit = self._config_running.get() try: limit = float(_fmt_context(self._get(limit, default=), self._context)) if limit > 0: log.debug("Applying task time limit of %s", self._name, deltafmt(limit)) self._limit = now + limit except Exception as e: log.warn("Task time_limit value invalid -- %s", self._name, limit, e, exc_info=log.isEnabledFor(logging.DEBUG))
Set the state information for a task once it has completely started. In particular, the time limit is applied as of this time (ie after and start delay has been taking.
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def get(key, value=None, conf_file=_DEFAULT_CONF): ** current_conf = _parse_conf(conf_file) stanza = current_conf.get(key, False) if value: if stanza: return stanza.get(value, False) _LOG.warning("Block not present or empty.", key) return stanza
Get the value for a specific configuration line. :param str key: The command or stanza block to configure. :param str value: The command value or command of the block specified by the key parameter. :param str conf_file: The logrotate configuration file. :return: The value for a specific configuration line. :rtype: bool|int|str CLI Example: .. code-block:: bash salt '*' logrotate.get rotate salt '*' logrotate.get /var/log/wtmp rotate /etc/logrotate.conf
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def parse_string(self, timestr, subfmts): components = (, , ) defaults = (None, 1, 1, 0) try: idot = timestr.rindex() except: fracday = 0.0 else: timestr, fracday = timestr[:idot], timestr[idot:] fracday = float(fracday) for _, strptime_fmt_or_regex, _ in subfmts: vals = [] if isinstance(strptime_fmt_or_regex, six.string_types): try: tm = time.strptime(timestr, strptime_fmt_or_regex) tm.tm_hour += int(24 * fracday) tm.tm_min += int(60 * (24 * fracday - tm.tm_hour)) tm.tm_sec += 60 * (60 * (24 * fracday - tm.tm_hour) - tm.tm_min) except ValueError as ex: print ex continue else: vals = [getattr(tm, + component) for component in components] else: tm = re.match(strptime_fmt_or_regex, timestr) if tm is None: continue tm = tm.groupdict() vals = [int(tm.get(component, default)) for component, default in six.moves.zip(components, defaults)] hrprt = int(24 * fracday) vals.append(hrprt) mnprt = int(60 * (24 * fracday - hrprt)) vals.append(mnprt) scprt = 60 * (60 * (24 * fracday - hrprt) - mnprt) vals.append(scprt) return vals else: raise ValueError( .format(timestr, self.name))
Read time from a single string, using a set of possible formats.
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def classify_tangent_intersection( intersection, nodes1, tangent1, nodes2, tangent2 ): dot_prod = np.vdot(tangent1[:, 0], tangent2[:, 0]) curvature1 = _curve_helpers.get_curvature(nodes1, tangent1, intersection.s) curvature2 = _curve_helpers.get_curvature(nodes2, tangent2, intersection.t) if dot_prod < 0: sign1, sign2 = _SIGN([curvature1, curvature2]) if sign1 == sign2: if sign1 == 1.0: return CLASSIFICATION_T.OPPOSED else: return CLASSIFICATION_T.TANGENT_BOTH else: delta_c = abs(curvature1) - abs(curvature2) if delta_c == 0.0: raise NotImplementedError(_SAME_CURVATURE) elif sign1 == _SIGN(delta_c): return CLASSIFICATION_T.OPPOSED else: return CLASSIFICATION_T.TANGENT_BOTH else: if curvature1 > curvature2: return CLASSIFICATION_T.TANGENT_FIRST elif curvature1 < curvature2: return CLASSIFICATION_T.TANGENT_SECOND else: raise NotImplementedError(_SAME_CURVATURE)
Helper for func:`classify_intersection` at tangencies. .. note:: This is a helper used only by :func:`classify_intersection`. Args: intersection (.Intersection): An intersection object. nodes1 (numpy.ndarray): Control points for the first curve at the intersection. tangent1 (numpy.ndarray): The tangent vector to the first curve at the intersection (``2 x 1`` array). nodes2 (numpy.ndarray): Control points for the second curve at the intersection. tangent2 (numpy.ndarray): The tangent vector to the second curve at the intersection (``2 x 1`` array). Returns: IntersectionClassification: The "inside" curve type, based on the classification enum. Will either be ``opposed`` or one of the ``tangent`` values. Raises: NotImplementedError: If the curves are tangent at the intersection and have the same curvature.
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def get_flight_rules(vis: Number, ceiling: Cloud) -> int: if not vis: return 2 if vis.repr == or vis.repr.startswith(): vis = 10 elif vis.repr.startswith(): vis = 0 elif len(vis.repr) == 4: vis = vis.value * 0.000621371 else: vis = vis.value cld = ceiling.altitude if ceiling else 99 if (vis <= 5) or (cld <= 30): if (vis < 3) or (cld < 10): if (vis < 1) or (cld < 5): return 3 return 2 return 1 return 0
Returns int based on current flight rules from parsed METAR data 0=VFR, 1=MVFR, 2=IFR, 3=LIFR Note: Common practice is to report IFR if visibility unavailable
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def calc_avr_uvr_v1(self): con = self.parameters.control.fastaccess der = self.parameters.derived.fastaccess flu = self.sequences.fluxes.fastaccess for i in range(2): if flu.h <= (con.hm+der.hv[i]): flu.avr[i] = 0. flu.uvr[i] = 0. else: flu.avr[i] = (flu.h-(con.hm+der.hv[i]))**2*con.bnvr[i]/2. flu.uvr[i] = (flu.h-(con.hm+der.hv[i]))*(1.+con.bnvr[i]**2)**.5
Calculate the flown through area and the wetted perimeter of both outer embankments. Note that each outer embankment lies beyond its foreland and that all water flowing exactly above the a embankment is added to |AVR|. The theoretical surface seperating water above the foreland from water above its embankment is not contributing to |UVR|. Required control parameters: |HM| |BNVR| Required derived parameter: |HV| Required flux sequence: |H| Calculated flux sequence: |AVR| |UVR| Examples: Generally, right trapezoids are assumed. Here, for simplicity, both forelands are assumed to be symmetrical. Their smaller bases (bottoms) hava a length of 2 meters, their non-vertical legs show an inclination of 1 meter per 4 meters, and their height (depths) is 1 meter. Both forelands lie 1 meter above the main channels bottom. Generally, a triangles are assumed, with the vertical side seperating the foreland from its outer embankment. Here, for simplicity, both forelands are assumed to be symmetrical. Their inclinations are 1 meter per 4 meters and their lowest point is 1 meter above the forelands bottom and 2 meters above the main channels bottom: >>> from hydpy.models.lstream import * >>> parameterstep() >>> hm(1.0) >>> bnvr(4.0) >>> derived.hv(1.0) The first example deals with moderate high flow conditions, where water flows over the forelands, but not over their outer embankments (|HM| < |H| < (|HM| + |HV|)): >>> fluxes.h = 1.5 >>> model.calc_avr_uvr_v1() >>> fluxes.avr avr(0.0, 0.0) >>> fluxes.uvr uvr(0.0, 0.0) The second example deals with extreme high flow conditions, where water flows over the both foreland and their outer embankments ((|HM| + |HV|) < |H|): >>> fluxes.h = 2.5 >>> model.calc_avr_uvr_v1() >>> fluxes.avr avr(0.5, 0.5) >>> fluxes.uvr uvr(2.061553, 2.061553)
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def energy_ratio_by_chunks(x, param): res_data = [] res_index = [] full_series_energy = np.sum(x ** 2) for parameter_combination in param: num_segments = parameter_combination["num_segments"] segment_focus = parameter_combination["segment_focus"] assert segment_focus < num_segments assert num_segments > 0 res_data.append(np.sum(np.array_split(x, num_segments)[segment_focus] ** 2.0)/full_series_energy) res_index.append("num_segments_{}__segment_focus_{}".format(num_segments, segment_focus)) return list(zip(res_index, res_data))
Calculates the sum of squares of chunk i out of N chunks expressed as a ratio with the sum of squares over the whole series. Takes as input parameters the number num_segments of segments to divide the series into and segment_focus which is the segment number (starting at zero) to return a feature on. If the length of the time series is not a multiple of the number of segments, the remaining data points are distributed on the bins starting from the first. For example, if your time series consists of 8 entries, the first two bins will contain 3 and the last two values, e.g. `[ 0., 1., 2.], [ 3., 4., 5.]` and `[ 6., 7.]`. Note that the answer for `num_segments = 1` is a trivial "1" but we handle this scenario in case somebody calls it. Sum of the ratios should be 1.0. :param x: the time series to calculate the feature of :type x: numpy.ndarray :param param: contains dictionaries {"num_segments": N, "segment_focus": i} with N, i both ints :return: the feature values :return type: list of tuples (index, data)
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def connect(self, port=None, baud_rate=115200): if isinstance(port, types.StringTypes): ports = [port] else: ports = port if not ports: ports = serial_ports().index.tolist() if not ports: raise IOError("Arduino Mega2560 not found on any port.") for comport_i in ports: if self.connected(): self.disconnect() self.port = None self._i2c_devices = {} try: logger.debug(, comport_i) Base.connect(self, str(comport_i), baud_rate) self.port = comport_i break except BadVGND, exception: logger.warning(exception) break except RuntimeError, exception: continue else: raise RuntimeError( % ports) name = self.name() version = self.hardware_version() firmware = self.software_version() serial_number_string = "" try: serial_number_string = ", S/N %03d" % self.serial_number except: pass logger.info("Connected to %s v%s (Firmware: %s%s)" % (name, version, firmware, serial_number_string)) logger.info("Poll control board for series resistors and " "capacitance values.") self._read_calibration_data() try: self.__aref__ = self._aref() logger.info("Analog reference = %.2f V" % self.__aref__) except: pass expected = 2 ** 10/2 v = {} channels = [0, 1] damaged = [] for channel in channels: try: v[channel] = np.mean(self.analog_reads(channel, 10)) logger.info("A%d VGND = %.2f V (%.2f%% of Aref)", channel, self.__aref__ * v[channel] / (2 ** 10), 100.0 * v[channel] / (2 ** 10)) if np.abs(v[channel] - expected) / expected > .1: damaged.append(channel) except: break self._i2c_scan() if damaged: if len(damaged) == 1: msg = "Analog channel %d appears" % damaged[0] else: msg = "Analog channels %s appear" % damaged raise BadVGND(msg + " to be damaged. You may need to replace the " "op-amp on the control board.") return self.RETURN_OK
Parameters ---------- port : str or list-like, optional Port (or list of ports) to try to connect to as a DMF Control Board. baud_rate : int, optional Returns ------- str Port DMF control board was connected on. Raises ------ RuntimeError If connection could not be established. IOError If no ports were specified and Arduino Mega2560 not found on any port.
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def standard_parsing_functions(Block, Tx): def stream_block(f, block): assert isinstance(block, Block) block.stream(f) def stream_blockheader(f, blockheader): assert isinstance(blockheader, Block) blockheader.stream_header(f) def stream_tx(f, tx): assert isinstance(tx, Tx) tx.stream(f) def parse_int_6(f): b = f.read(6) + b return struct.unpack(b, "<L")[0] def stream_int_6(f, v): f.write(struct.pack(v, "<L")[:6]) more_parsing = [ ("A", (PeerAddress.parse, lambda f, peer_addr: peer_addr.stream(f))), ("v", (InvItem.parse, lambda f, inv_item: inv_item.stream(f))), ("T", (Tx.parse, stream_tx)), ("B", (Block.parse, stream_block)), ("z", (Block.parse_as_header, stream_blockheader)), ("1", (lambda f: struct.unpack("B", f.read(1))[0], lambda f, v: f.write(struct.pack("B", v)))), ("6", (parse_int_6, stream_int_6)), ("O", (lambda f: True if f.read(1) else False, lambda f, v: f.write(b if v is None else struct.pack("B", v)))), ] all_items = list(STREAMER_FUNCTIONS.items()) all_items.extend(more_parsing) return all_items
Return the standard parsing functions for a given Block and Tx class. The return value is expected to be used with the standard_streamer function.
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def save(self, index=None, force=False): editorstack = self.get_current_editorstack() return editorstack.save(index=index, force=force)
Save file
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def pverb(self, *args, **kwargs): if not self.verbose: return self.pstd(*args, **kwargs)
Console verbose message to STDOUT
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def createPREMISEventXML(eventType, agentIdentifier, eventDetail, eventOutcome, outcomeDetail=None, eventIdentifier=None, linkObjectList=[], eventDate=None): eventXML = etree.Element(PREMIS + "event", nsmap=PREMIS_NSMAP) eventIDXML = etree.SubElement(eventXML, PREMIS + "eventIdentifier") eventTypeXML = etree.SubElement(eventXML, PREMIS + "eventType") eventTypeXML.text = eventType eventIDTypeXML = etree.SubElement( eventIDXML, PREMIS + "eventIdentifierType" ) eventIDTypeXML.text = \ "http://purl.org/net/untl/vocabularies/identifier-qualifiers/ eventIDValueXML = etree.SubElement( eventIDXML, PREMIS + "eventIdentifierValue" ) if eventIdentifier: eventIDValueXML.text = eventIdentifier else: eventIDValueXML.text = uuid.uuid4().hex eventDateTimeXML = etree.SubElement(eventXML, PREMIS + "eventDateTime") if eventDate is None: eventDateTimeXML.text = xsDateTime_format(datetime.utcnow()) else: eventDateTimeXML.text = xsDateTime_format(eventDate) eventDetailXML = etree.SubElement(eventXML, PREMIS + "eventDetail") eventDetailXML.text = eventDetail eventOutcomeInfoXML = etree.SubElement( eventXML, PREMIS + "eventOutcomeInformation" ) eventOutcomeXML = etree.SubElement( eventOutcomeInfoXML, PREMIS + "eventOutcome" ) eventOutcomeXML.text = eventOutcome if outcomeDetail: eventOutcomeDetailXML = etree.SubElement( eventOutcomeInfoXML, PREMIS + "eventOutcomeDetail" ) eventOutcomeDetailNoteXML = etree.SubElement( eventOutcomeDetailXML, PREMIS + "eventOutcomeDetailNote" ) eventOutcomeDetailNoteXML.text = outcomeDetail linkAgentIDXML = etree.SubElement( eventXML, PREMIS + "linkingAgentIdentifier") linkAgentIDTypeXML = etree.SubElement( linkAgentIDXML, PREMIS + "linkingAgentIdentifierType" ) linkAgentIDTypeXML.text = \ "http://purl.org/net/untl/vocabularies/identifier-qualifiers/ linkAgentIDValueXML = etree.SubElement( linkAgentIDXML, PREMIS + "linkingAgentIdentifierValue" ) linkAgentIDValueXML.text = agentIdentifier linkAgentIDRoleXML = etree.SubElement( linkAgentIDXML, PREMIS + "linkingAgentRole" ) linkAgentIDRoleXML.text = \ "http://purl.org/net/untl/vocabularies/linkingAgentRoles/ for linkObject in linkObjectList: linkObjectIDXML = etree.SubElement( eventXML, PREMIS + "linkingObjectIdentifier" ) linkObjectIDTypeXML = etree.SubElement( linkObjectIDXML, PREMIS + "linkingObjectIdentifierType" ) linkObjectIDTypeXML.text = linkObject[1] linkObjectIDValueXML = etree.SubElement( linkObjectIDXML, PREMIS + "linkingObjectIdentifierValue" ) linkObjectIDValueXML.text = linkObject[0] if linkObject[2]: linkObjectRoleXML = etree.SubElement( linkObjectIDXML, PREMIS + "linkingObjectRole" ) linkObjectRoleXML.text = linkObject[2] return eventXML
Actually create our PREMIS Event XML
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def get_instance(self, payload): return NotificationInstance(self._version, payload, account_sid=self._solution[], )
Build an instance of NotificationInstance :param dict payload: Payload response from the API :returns: twilio.rest.api.v2010.account.notification.NotificationInstance :rtype: twilio.rest.api.v2010.account.notification.NotificationInstance
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def _update_port_locations(self, initial_coordinates): particles = list(self.particles()) for port in self.all_ports(): if port.anchor: idx = particles.index(port.anchor) shift = particles[idx].pos - initial_coordinates[idx] port.translate(shift)
Adjust port locations after particles have moved Compares the locations of Particles between 'self' and an array of reference coordinates. Shifts Ports in accordance with how far anchors have been moved. This conserves the location of Ports with respect to their anchor Particles, but does not conserve the orientation of Ports with respect to the molecule as a whole. Parameters ---------- initial_coordinates : np.ndarray, shape=(n, 3), dtype=float Reference coordinates to use for comparing how far anchor Particles have shifted.
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def remove_outcome_hook(self, outcome_id): for transition_id in list(self.transitions.keys()): transition = self.transitions[transition_id] if transition.to_outcome == outcome_id and transition.to_state == self.state_id: self.remove_transition(transition_id)
Removes internal transition going to the outcome
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def _metric_when_multiplied_with_sig_vec(self, sig): return dot((self.B * self.D**-1.).T * sig, self.B * self.D)
return D^-1 B^T diag(sig) B D as a measure for C^-1/2 diag(sig) C^1/2 :param sig: a vector "used" as diagonal matrix :return:
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def collect_modules(self): try: res = {} m = sys.modules for k in m: continue if m[k]: try: d = m[k].__dict__ if "version" in d and d["version"]: res[k] = self.jsonable(d["version"]) elif "__version__" in d and d["__version__"]: res[k] = self.jsonable(d["__version__"]) else: res[k] = get_distribution(k).version except DistributionNotFound: pass except Exception: logger.debug("collect_modules: could not process module: %s" % k) except Exception: logger.debug("collect_modules", exc_info=True) else: return res
Collect up the list of modules in use
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def cross_validate(self, ax): cdpp_opt = self.get_cdpp_arr() for b, brkpt in enumerate(self.breakpoints): log.info("Cross-validating chunk %d/%d..." % (b + 1, len(self.breakpoints))) m = self.get_masked_chunk(b) time = self.time[m] flux = self.fraw[m] ferr = self.fraw_err[m] med = np.nanmedian(self.fraw) gp = GP(self.kernel, self.kernel_params, white=False) gp.compute(time, ferr) masks = list(Chunks(np.arange(0, len(time)), len(time) // self.cdivs)) pre_v = [self.cv_precompute(mask, b) for mask in masks] log_lam_opt = np.log10(self.lam[b]) scatter_opt = self.validation_scatter( log_lam_opt, b, masks, pre_v, gp, flux, time, med) log.info("Iter 0/%d: " % (self.piter) + "logL = (%s), s = %.3f" % (", ".join(["%.3f" % l for l in log_lam_opt]), scatter_opt)) for p in range(self.piter): log_lam = np.array( np.log10(self.lam[b])) * \ (1 + self.ppert * np.random.randn(len(self.lam[b]))) scatter = self.validation_scatter( log_lam, b, masks, pre_v, gp, flux, time, med) log.info("Initializing at: " + "logL = (%s), s = %.3f" % (", ".join(["%.3f" % l for l in log_lam]), scatter)) log_lam, scatter, _, _, _, _ = \ fmin_powell(self.validation_scatter, log_lam, args=(b, masks, pre_v, gp, flux, time, med), maxfun=self.pmaxf, disp=False, full_output=True) tmp = np.array(self.lam[b]) self.lam[b] = 10 ** log_lam self.compute() cdpp = self.get_cdpp_arr()[b] self.lam[b] = tmp if cdpp < cdpp_opt[b]: cdpp_opt[b] = cdpp log_lam_opt = log_lam log.info("Iter %d/%d: " % (p + 1, self.piter) + "logL = (%s), s = %.3f" % (", ".join(["%.3f" % l for l in log_lam]), scatter)) log.info("Found minimum: logL = (%s), s = %.3f" % (", ".join(["%.3f" % l for l in log_lam_opt]), scatter_opt)) self.lam[b] = 10 ** log_lam_opt ax[1].set_xticks(np.arange(1, len(self.breakpoints) + 1))
Performs the cross-validation step.
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def get_products(self): products = set() for _, _, _, react, _ in self.get_kinks(): products = products.union(set([k.reduced_formula for k in react.products])) return list(products)
List of formulas of potential products. E.g., ['Li','O2','Mn'].