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def _set_show_mpls_ldp(self, v, load=False): if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=show_mpls_ldp.show_mpls_ldp, is_leaf=True, yang_name="show-mpls-ldp", rest_name="show-mpls-ldp", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions={u: {u: u, u: u}}, namespace=, defining_module=, yang_type=, is_config=True) except (TypeError, ValueError): raise ValueError({ : , : "rpc", : , }) self.__show_mpls_ldp = t if hasattr(self, ): self._set()
Setter method for show_mpls_ldp, mapped from YANG variable /brocade_mpls_rpc/show_mpls_ldp (rpc) If this variable is read-only (config: false) in the source YANG file, then _set_show_mpls_ldp is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_show_mpls_ldp() directly.
def escape_windows_cmd_string(s): for c in : s = s.replace(c, + c) s = s.replace(, ) return s
Returns a string that is usable by the Windows cmd.exe. The escaping is based on details here and emperical testing: http://www.robvanderwoude.com/escapechars.php
def save_var(name, value): connection = _State.connection() _State.reflect_metadata() vars_table = sqlalchemy.Table( _State.vars_table_name, _State.metadata, sqlalchemy.Column(, sqlalchemy.types.Text, primary_key=True), sqlalchemy.Column(, sqlalchemy.types.LargeBinary), sqlalchemy.Column(, sqlalchemy.types.Text), keep_existing=True ) vars_table.create(bind=connection, checkfirst=True) column_type = get_column_type(value) if column_type == sqlalchemy.types.LargeBinary: value_blob = value else: value_blob = unicode(value).encode() values = dict(name=name, value_blob=value_blob, type=column_type.__visit_name__.lower()) vars_table.insert(prefixes=[]).values(**values).execute()
Save a variable to the table specified by _State.vars_table_name. Key is the name of the variable, and value is the value.
def set_pixel(self, x, y, value): if x < 0 or x > 7 or y < 0 or y > 7: return self.set_led(y * 16 + x, 1 if value & GREEN > 0 else 0) self.set_led(y * 16 + x + 8, 1 if value & RED > 0 else 0)
Set pixel at position x, y to the given value. X and Y should be values of 0 to 8. Value should be OFF, GREEN, RED, or YELLOW.
def convert_string_to_number(value): if value is None: return 1 if isinstance(value, int): return value if value.isdigit(): return int(value) num_list = map(lambda s: NUMBERS[s], re.findall(numbers + , value.lower())) return sum(num_list)
Convert strings to numbers
def get_allow_repeat_items_metadata(self): metadata = dict(self._allow_repeat_items_metadata) metadata.update({: self.my_osid_object_form._my_map[]}) return Metadata(**metadata)
get the metadata for allow repeat items
def describe(table_name, region=None, key=None, keyid=None, profile=None): conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) table = Table(table_name, connection=conn) return table.describe()
Describe a DynamoDB table. CLI example:: salt myminion boto_dynamodb.describe table_name region=us-east-1
def is_valid_delta_name(file): filename = basename(file) pattern = re.compile(Delta.FILENAME_PATTERN) if re.match(pattern, filename): return True return False
Return if a file has a valid name A delta file name can be: - pre-all.py - pre-all.sql - delta_x.x.x_ddmmyyyy.pre.py - delta_x.x.x_ddmmyyyy.pre.sql - delta_x.x.x_ddmmyyyy.py - delta_x.x.x_ddmmyyyy.sql - delta_x.x.x_ddmmyyyy.post.py - delta_x.x.x_ddmmyyyy.post.sql - post-all.py - post-all.sql where x.x.x is the version number and _ddmmyyyy is an optional description, usually representing the date of the delta file
def stream_directory(directory, recursive=False, patterns=, chunk_size=default_chunk_size): stream = DirectoryStream(directory, recursive=recursive, patterns=patterns, chunk_size=chunk_size) return stream.body(), stream.headers
Gets a buffered generator for streaming directories. Returns a buffered generator which encodes a directory as :mimetype:`multipart/form-data` with the corresponding headers. Parameters ---------- directory : str The filepath of the directory to stream recursive : bool Stream all content within the directory recursively? patterns : str | list Single *glob* pattern or list of *glob* patterns and compiled regular expressions to match the names of the filepaths to keep chunk_size : int Maximum size of each stream chunk
def filelist(jottapath, JFS): log.debug("filelist %r", jottapath) try: jf = JFS.getObject(jottapath) except JFSNotFoundError: return set() if not isinstance(jf, JFSFolder): return False return set([f.name for f in jf.files() if not f.is_deleted()])
Get a set() of files from a jottapath (a folder)
def render_to_message(self, extra_context=None, *args, **kwargs): message = super(TemplatedHTMLEmailMessageView, self)\ .render_to_message(extra_context, *args, **kwargs) if extra_context is None: extra_context = {} context = self.get_context_data(**extra_context) content = self.render_html_body(context) message.attach_alternative(content, mimetype=) return message
Renders and returns an unsent message with the given context. Any extra keyword arguments passed will be passed through as keyword arguments to the message constructor. :param extra_context: Any additional context to use when rendering templated content. :type extra_context: :class:`dict` :returns: A message instance. :rtype: :attr:`.message_class`
def update_from_file(yaml_dict, filepaths): yaml_dict.update(registry.load(filepaths, list(yaml_dict)))
Override YAML settings with loaded values from filepaths. - File paths in the list gets the priority by their orders of the list.
def csv(self, jql, limit=1000): url = .format( limit=limit, jql=jql) return self.get(url, not_json_response=True, headers={: })
Get issues from jql search result with all related fields :param jql: JQL query :param limit: max results in the output file :return: CSV file
def add_path_resolver(tag, path, kind=None, Loader=Loader, Dumper=Dumper): Loader.add_path_resolver(tag, path, kind) Dumper.add_path_resolver(tag, path, kind)
Add a path based resolver for the given tag. A path is a list of keys that forms a path to a node in the representation tree. Keys can be string values, integers, or None.
def get_display_dataframe(self): X = self.corpus_.get_term_doc_mat() categories = pd.Series(self.corpus_.get_category_ids()) cat_ar = np.array(self.corpus_.get_categories()) cat_idx_sort = np.argsort(cat_ar) if self.seasonality_column_: print() seasonality_ar = np.array(self.corpus_.get_df()[self.seasonality_column_]) terms = self.corpus_.get_terms() category_idx_store = self.corpus_.get_category_index_store() data = {} seasondata = {} for i, cati in enumerate(cat_idx_sort): cat = cat_ar[cati] if cat >= self.start_category_ and i > self.timesteps_to_lag_: neg_cats = self.sorted_categores_[i - self.timesteps_to_lag_:i] neg_mask = categories.isin(category_idx_store.getidxstrictbatch(neg_cats)).values scores = self._regress_terms(X, cat, categories, category_idx_store, neg_mask, terms) data[cat] = scores if self.seasonality_column_: neg_cats = set(categories[(seasonality_ar == seasonality_ar[cati]) & (categories != categories[cati])]) neg_mask = categories.isin(neg_cats).values scores = self._regress_terms(X, cat, categories, category_idx_store, neg_mask, terms) seasondata[cat] = scores coefs = pd.DataFrame(data) pos_coefs = (coefs.apply(lambda x: (x > 0) * x, axis=1) .sum(axis=1) .sort_values(ascending=False)) term_cat_counts = self.corpus_.get_term_freq_df()[coefs.columns] def dense_percentile(x): return pd.Series(x / x.max(), index=x.index) rank_df = pd.DataFrame({: dense_percentile(pos_coefs), : dense_percentile(term_cat_counts.max(axis=1)), : pos_coefs, : term_cat_counts.max(axis=1)}) if self.seasonality_column_: seasoncoefs = (pd.DataFrame(seasondata).sum(axis=1)) rank_df[] = dense_percentile(seasoncoefs.sort_values(ascending=False) + np.abs(seasoncoefs.min())) weights = [2, 1, 1] vals = [, , ] def gethmean(x): if min(x[vals]) == 0: return 0 return sum(weights) * 1. / sum([weights[i] / x[val] for i, val in enumerate(vals)]) rank_df[] = rank_df.apply(gethmean, axis=1) else: beta = 0.5 rank_df[] = (rank_df .apply(lambda x: 0 if min(x) == 0 else (1 + beta ** 2) * (x.coefr * x.freqr) / ((beta ** 2 * x.coefr) + x.freqr), axis=1)) rank_df = rank_df.sort_values(by=, ascending=False) display_df = pd.merge((term_cat_counts .loc[rank_df.iloc[:self.num_terms_].index] .reset_index() .melt(id_vars=[]) .rename(columns={: , : })), (coefs.loc[rank_df.iloc[:self.num_terms_].index] .reset_index() .melt(id_vars=[]) .rename(columns={: , : })), on=[, ]) display_df[display_df[] == 0] = np.nan display_df = display_df.dropna() return display_df[display_df.term.isin(rank_df.index)]
Gets list of terms to display that have some interesting diachronic variation. Returns ------- pd.DataFrame e.g., term variable frequency trending 2 in 200310 1.0 0.000000 19 for 200310 1.0 0.000000 20 to 200311 1.0 0.000000
def copy(self): copy_cpd = LinearGaussianCPD(self.variable, self.beta, self.variance, list(self.evidence)) return copy_cpd
Returns a copy of the distribution. Returns ------- LinearGaussianCPD: copy of the distribution Examples -------- >>> from pgmpy.factors.continuous import LinearGaussianCPD >>> cpd = LinearGaussianCPD('Y', [0.2, -2, 3, 7], 9.6, ['X1', 'X2', 'X3']) >>> copy_cpd = cpd.copy() >>> copy_cpd.variable 'Y' >>> copy_cpd.evidence ['X1', 'X2', 'X3']
def get_loc(self, key, method=None, tolerance=None): if isinstance(key, str): return self._get_string_slice(key) else: return pd.Index.get_loc(self, key, method=method, tolerance=tolerance)
Adapted from pandas.tseries.index.DatetimeIndex.get_loc
def _buildPointList(self): try: self.properties.pss.value = self.properties.network.read( "{} device {} protocolServicesSupported".format( self.properties.address, self.properties.device_id ) ) except NoResponseFromController as error: self._log.error("Controller not found, aborting. ({})".format(error)) return ("Not Found", "", [], []) except SegmentationNotSupported as error: self._log.warning("Segmentation not supported") self.segmentation_supported = False self.new_state(DeviceDisconnected) self.properties.name = self.properties.network.read( "{} device {} objectName".format( self.properties.address, self.properties.device_id ) ) self._log.info( "Device {}:[{}] found... building points list".format( self.properties.device_id, self.properties.name ) ) try: self.properties.objects_list, self.points, self.trendlogs = self._discoverPoints( self.custom_object_list ) if self.properties.pollDelay > 0: self.poll(delay=self.properties.pollDelay) except NoResponseFromController as error: self._log.error("Cannot retrieve object list, disconnecting...") self.segmentation_supported = False self.new_state(DeviceDisconnected) except IndexError as error: self._log.error("Device creation failed... disconnecting") self.new_state(DeviceDisconnected)
Upon connection to build the device point list and properties.
def _get_database(self, database_name): try: return self._client[database_name] except InvalidName as ex: raise DataSourceError("Cannot connect to database %s!" % self._database) from ex
Get PyMongo client pointing to the current database. :return: MongoDB client of the current database. :raise DataSourceError
def __upload_title(self, kibiter_major): if kibiter_major == "6": resource = ".kibana/doc/projectname" data = {"projectname": {"name": self.project_name}} mapping_resource = ".kibana/_mapping/doc" mapping = {"dynamic": "true"} url = urijoin(self.conf[][], resource) mapping_url = urijoin(self.conf[][], mapping_resource) logger.debug("Adding mapping for dashboard title") res = self.grimoire_con.put(mapping_url, data=json.dumps(mapping), headers=ES6_HEADER) try: res.raise_for_status() except requests.exceptions.HTTPError: logger.error("Couldnt create dashboard title.") logger.error(res.json())
Upload to Kibiter the title for the dashboard. The title is shown on top of the dashboard menu, and is Usually the name of the project being dashboarded. This is done only for Kibiter 6.x. :param kibiter_major: major version of kibiter
def split_lines(source, maxline=79): result = [] extend = result.extend append = result.append line = [] multiline = False count = 0 find = str.find for item in source: index = find(item, ) if index: line.append(item) multiline = index > 0 count += len(item) else: if line: if count <= maxline or multiline: extend(line) else: wrap_line(line, maxline, result) count = 0 multiline = False line = [] append(item) return result
Split inputs according to lines. If a line is short enough, just yield it. Otherwise, fix it.
def root_urns_for_deletion(self): roots = set() for urn in self._urns_for_deletion: new_root = True str_urn = utils.SmartUnicode(urn) fake_roots = [] for root in roots: str_root = utils.SmartUnicode(root) if str_urn.startswith(str_root): new_root = False break elif str_root.startswith(str_urn): fake_roots.append(root) if new_root: roots -= set(fake_roots) roots.add(urn) return roots
Roots of the graph of urns marked for deletion.
def wait_for(self, timeout=None): from broqer.op import OnEmitFuture return self | OnEmitFuture(timeout=timeout)
When a timeout should be applied for awaiting use this method. :param timeout: optional timeout in seconds. :returns: a future returning the emitted value
def due(self): invoice_charges = Charge.objects.filter(invoice=self) invoice_transactions = Transaction.successful.filter(invoice=self) return total_amount(invoice_charges) - total_amount(invoice_transactions)
The amount due for this invoice. Takes into account all entities in the invoice. Can be < 0 if the invoice was overpaid.
def connect(self, retry=0, delay=0): if self.connected: self._LOG.debug("Connect called, but we are connected?") return if self._connecting: self._LOG.debug("Connect called, but we are already connecting.") return self._connecting = True if delay: self._LOG.debug("Delayed connect: %d seconds" % delay) self.emit(self.EVENT_RECONNECT, delay) self.sleep(delay) self._LOG.debug("Connect initiated.") for i, server_addr in enumerate(self.cm_servers): if retry and i > retry: return False start = time() if self.connection.connect(server_addr): break diff = time() - start self._LOG.debug("Failed to connect. Retrying...") if diff < 5: self.sleep(5 - diff) self.current_server_addr = server_addr self.connected = True self.emit(self.EVENT_CONNECTED) self._recv_loop = gevent.spawn(self._recv_messages) self._connecting = False return True
Initiate connection to CM. Blocks until connected unless ``retry`` is specified. :param retry: number of retries before returning. Unlimited when set to ``None`` :type retry: :class:`int` :param delay: delay in secnds before connection attempt :type delay: :class:`int` :return: successful connection :rtype: :class:`bool`
def exif_name(self): mapillary_description = json.loads(self.extract_image_description()) lat = None lon = None ca = None date_time = None if "MAPLatitude" in mapillary_description: lat = mapillary_description["MAPLatitude"] if "MAPLongitude" in mapillary_description: lon = mapillary_description["MAPLongitude"] if "MAPCompassHeading" in mapillary_description: if in mapillary_description["MAPCompassHeading"]: ca = mapillary_description["MAPCompassHeading"][] if "MAPCaptureTime" in mapillary_description: date_time = datetime.datetime.strptime( mapillary_description["MAPCaptureTime"], "%Y_%m_%d_%H_%M_%S_%f").strftime("%Y-%m-%d-%H-%M-%S-%f")[:-3] filename = .format( lat, lon, ca, date_time, uuid.uuid4()) return filename
Name of file in the form {lat}_{lon}_{ca}_{datetime}_{filename}_{hash}
def doDelete(self, WHAT={}): if hasattr(WHAT, ): self._addDBParam(, WHAT.RECORDID) self._addDBParam(, WHAT.MODID) elif type(WHAT) == dict and WHAT.has_key(): self._addDBParam(, WHAT[]) else: raise FMError, % type(WHAT) if self._layout == : raise FMError, if self._checkRecordID() == 0: raise FMError, return self._doAction()
This function will perform the command -delete.
def get_column_flat(self, field, components=None, computed_type=): return self.pack_column_flat(self.get_column(field, components, computed_type), components, offset=field==)
TODO: add documentation return a single merged value (hstacked) from all meshes :parameter str field: name of the mesh columnname :parameter components:
def get_anchor_href(markup): soup = BeautifulSoup(markup, ) return [ % link.get() for link in soup.find_all()]
Given HTML markup, return a list of hrefs for each anchor tag.
def grabImage(self, index): rect = self.visualRect(index) pixmap = QtGui.QPixmap() pixmap = pixmap.grabWidget(self, rect) return pixmap
Gets an image of the item at *index* :param index: index of an item in the view :type index: :qtdoc:`QModelIndex` :returns: :qtdoc:`QPixmap`
def _shutdown_proc(p, timeout): freq = 10 for _ in range(1 + timeout * freq): ret = p.poll() if ret is not None: logging.info("Shutdown gracefully.") return ret time.sleep(1 / freq) logging.warning("Killing the process.") p.kill() return p.wait()
Wait for a proc to shut down, then terminate or kill it after `timeout`.
def collect_filtered_models(discard, *input_values): ids = set([]) collected = [] queued = [] def queue_one(obj): if obj.id not in ids and not (callable(discard) and discard(obj)): queued.append(obj) for value in input_values: _visit_value_and_its_immediate_references(value, queue_one) while queued: obj = queued.pop(0) if obj.id not in ids: ids.add(obj.id) collected.append(obj) _visit_immediate_value_references(obj, queue_one) return collected
Collect a duplicate-free list of all other Bokeh models referred to by this model, or by any of its references, etc, unless filtered-out by the provided callable. Iterate over ``input_values`` and descend through their structure collecting all nested ``Models`` on the go. Args: *discard (Callable[[Model], bool]) a callable which accepts a *Model* instance as its single argument and returns a boolean stating whether to discard the instance. The latter means that the instance will not be added to collected models nor will its references be explored. *input_values (Model) Bokeh models to collect other models from Returns: None
async def set_volume(self, vol: int): if self._lavalink._server_version <= 2: self.volume = max(min(vol, 150), 0) else: self.volume = max(min(vol, 1000), 0) await self._lavalink.ws.send(op=, guildId=self.guild_id, volume=self.volume)
Sets the player's volume (150% or 1000% limit imposed by lavalink depending on the version).
def fit_transform(self, X, y=None, **params): return self.fit(X, y).transform(X, y)
Learn vocabulary and return document id matrix. This is equivalent to fit followed by transform. Args: X : iterable an iterable which yields either str, unicode or file objects. Returns: list : document id matrix. list: label id matrix.
def wide(self): if not opcode_table[self.opcode].get(): return False if self.operands[0].value >= 255: return True if self.opcode == 0x84: if self.operands[1].value >= 255: return True return False
``True`` if this instruction needs to be prefixed by the WIDE opcode.
def load_html(self, mode, html): self._html_loaded_flag = False if mode == HTML_FILE_MODE: self.setUrl(QtCore.QUrl.fromLocalFile(html)) elif mode == HTML_STR_MODE: self.setHtml(html) else: raise InvalidParameterError() counter = 0 sleep_period = 0.1 timeout = 20 while not self._html_loaded_flag and counter < timeout: counter += sleep_period time.sleep(sleep_period) QgsApplication.processEvents()
Load HTML to this class with the mode specified. There are two modes that can be used: * HTML_FILE_MODE: Directly from a local HTML file. * HTML_STR_MODE: From a valid HTML string. :param mode: The mode. :type mode: int :param html: The html that will be loaded. If the mode is a file, then it should be a path to the htm lfile. If the mode is a string, then it should be a valid HTML string. :type html: str
def create_char(self, location, bitmap): assert 0 <= location <= 7, assert len(bitmap) == 8, pos = self.cursor_pos self.command(c.LCD_SETCGRAMADDR | location << 3) for row in bitmap: self._send_data(row) self.cursor_pos = pos
Create a new character. The HD44780 supports up to 8 custom characters (location 0-7). :param location: The place in memory where the character is stored. Values need to be integers between 0 and 7. :type location: int :param bitmap: The bitmap containing the character. This should be a tuple of 8 numbers, each representing a 5 pixel row. :type bitmap: tuple of int :raises AssertionError: Raised when an invalid location is passed in or when bitmap has an incorrect size. Example: .. sourcecode:: python >>> smiley = ( ... 0b00000, ... 0b01010, ... 0b01010, ... 0b00000, ... 0b10001, ... 0b10001, ... 0b01110, ... 0b00000, ... ) >>> lcd.create_char(0, smiley)
def _parse_canonical_regex(doc): regex = doc[] if len(doc) != 1: raise TypeError( % (doc,)) if len(regex) != 2: raise TypeError( % (doc,)) return Regex(regex[], regex[])
Decode a JSON regex to bson.regex.Regex.
def _list_po_to_dict(tokens) -> ListAbundance: func = tokens[FUNCTION] dsl = FUNC_TO_LIST_DSL[func] members = [parse_result_to_dsl(token) for token in tokens[MEMBERS]] return dsl(members)
Convert a list parse object to a node. :type tokens: ParseResult
def calc_model(cortex, model_argument, model_hemi=Ellipsis, radius=np.pi/3): if pimms.is_str(model_argument): h = cortex.chirality if model_hemi is Ellipsis else \ None if model_hemi is None else \ model_hemi model = retinotopy_model(model_argument, hemi=h, radius=radius) else: model = model_argument if not isinstance(model, RegisteredRetinotopyModel): raise ValueError() return model
calc_model loads the appropriate model object given the model argument, which may given the name of the model or a model object itself. Required afferent parameters: @ model_argument Must be either a RegisteredRetinotopyModel object or the name of a model that can be loaded. Optional afferent parameters: @ model_hemi May be used to specify the hemisphere of the model; this is usually only used when the fsaverage_sym hemisphere is desired, in which case this should be set to None; if left at the default value (Ellipsis), then it will use the hemisphere of the cortex param. Provided efferent values: @ model Will be the RegisteredRetinotopyModel object to which the mesh should be registered.
def enable_vxlan_feature(self, nexus_host, nve_int_num, src_intf): starttime = time.time() self.send_edit_string(nexus_host, snipp.PATH_VXLAN_STATE, (snipp.BODY_VXLAN_STATE % "enabled")) self.send_edit_string(nexus_host, snipp.PATH_VNSEG_STATE, (snipp.BODY_VNSEG_STATE % "enabled")) self.send_edit_string( nexus_host, (snipp.PATH_NVE_CREATE % nve_int_num), (snipp.BODY_NVE_CREATE % nve_int_num)) self.send_edit_string( nexus_host, (snipp.PATH_NVE_CREATE % nve_int_num), (snipp.BODY_NVE_ADD_LOOPBACK % ("enabled", src_intf))) self.capture_and_print_timeshot( starttime, "enable_vxlan", switch=nexus_host)
Enable VXLAN on the switch.
def source(self): if len(self.sources) == 0: raise ValueError("No source associated with %s" % self.__class__.__name__) elif len(self.sources) > 1: raise ValueError("Multiple sources for %s" % self.__class__.__name__) return list(self.sources)[0]
Returns the single source name for a variant collection if it is unique, otherwise raises an error.
def validate_location_instance_valid_for_arc(sender, instance, action, reverse, pk_set, *args, **kwargs): if action == : if reverse: for apk in pk_set: arc_node = ArcElementNode.objects.get(pk=apk) if arc_node.parent_outline != instance.outline: raise IntegrityError(_()) else: for lpk in pk_set: loc_instance = LocationInstance.objects.get(pk=lpk) if loc_instance.outline != instance.parent_outline: raise IntegrityError(_())
Evaluates attempts to add location instances to arc, ensuring they are from same outline.
def find_one(cls, *args, **kw): if len(args) == 1 and not isinstance(args[0], Filter): args = (getattr(cls, cls.__pk__) == args[0], ) Doc, collection, query, options = cls._prepare_find(*args, **kw) result = Doc.from_mongo(collection.find_one(query, **options)) return result
Get a single document from the collection this class is bound to. Additional arguments are processed according to `_prepare_find` prior to passing to PyMongo, where positional parameters are interpreted as query fragments, parametric keyword arguments combined, and other keyword arguments passed along with minor transformation. Automatically calls `to_mongo` with the retrieved data. https://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.find_one
def onCancelButton(self, event): if self.grid.changes: dlg1 = wx.MessageDialog(self, caption="Message:", message="Are you sure you want to exit this grid?\nYour changes will not be saved.\n ", style=wx.OK|wx.CANCEL) result = dlg1.ShowModal() if result == wx.ID_OK: dlg1.Destroy() self.Destroy() else: self.Destroy() if self.main_frame: self.main_frame.Show() self.main_frame.Raise()
Quit grid with warning if unsaved changes present
def find_node_type(ast, node_type): if type(ast) is node_type: return [ast] elif type(ast) is list: return reduce(operator.add, list(map(lambda a: find_node_type(a, node_type), ast)), []) elif ast is None: return [] else: return reduce(operator.add, [find_node_type(o[1], node_type) for o in ast.children()], [])
Return list of array references in AST.
def zoom2D(xi, yi, zi, xi_zoom=3., yi_zoom=3., order=3, mode="nearest", cval=0.): xi = ndimage.interpolation.zoom(xi, xi_zoom, order=order, mode="nearest") yi = ndimage.interpolation.zoom(yi, yi_zoom, order=order, mode="nearest") zi = ndimage.interpolation.zoom(zi, (xi_zoom, yi_zoom), order=order, mode=mode, cval=cval) return xi, yi, zi
Zoom a 2D array, with axes. Parameters ---------- xi : 1D array x axis points. yi : 1D array y axis points. zi : 2D array array values. Shape of (x, y). xi_zoom : float (optional) Zoom factor along x axis. Default is 3. yi_zoom : float (optional) Zoom factor along y axis. Default is 3. order : int (optional) The order of the spline interpolation, between 0 and 5. Default is 3. mode : {'constant', 'nearest', 'reflect', or 'wrap'} Points outside the boundaries of the input are filled according to the given mode. Default is nearest. cval : scalar (optional) Value used for constant mode. Default is 0.0.
def V_vertical_torispherical_concave(D, f, k, h): r alpha = asin((1-2*k)/(2.*(f-k))) a1 = f*D*(1-cos(alpha)) a2 = k*D*cos(alpha) D1 = 2*f*D*sin(alpha) s = (k*D*sin(alpha))**2 t = 2*a2 def V1(h): u = h-f*D*(1-cos(alpha)) v1 = pi/4*(2*a1**3/3. + a1*D1**2/2.) + pi*u*((D/2.-k*D)**2 +s) v1 += pi*t*u**2/2. - pi*u**3/3. v1 += pi*D*(1-2*k)*((2*u-t)/4.*(s+t*u-u**2)**0.5 + t*s**0.5/4. + k**2*D**2/2.*(acos((t-2*u)/(2*k*D)) -alpha)) return v1 def V2(h): v2 = pi*h**2/4.*(2*a1 + D1**2/(2.*a1) - 4*h/3.) return v2 if 0 <= h < a2: Vf = pi*D**2*h/4 - V1(a1+a2) + V1(a1+a2-h) elif a2 <= h < a1 + a2: Vf = pi*D**2*h/4 - V1(a1+a2) + V2(a1+a2-h) else: Vf = pi*D**2*h/4 - V1(a1+a2) return Vf
r'''Calculates volume of a vertical tank with a concave torispherical bottom, according to [1]_. No provision for the top of the tank is made here. .. math:: V = \frac{\pi D^2 h}{4} - v_1(h=a_1+a_2) + v_1(h=a_1 + a_2 -h),\; 0 \le h < a_2 .. math:: V = \frac{\pi D^2 h}{4} - v_1(h=a_1+a_2) + v_2(h=a_1 + a_2 -h),\; a_2 \le h < a_1 + a_2 .. math:: V = \frac{\pi D^2 h}{4} - v_1(h=a_1+a_2) + 0,\; h \ge a_1 + a_2 .. math:: v_1 = \frac{\pi}{4}\left(\frac{2a_1^3}{3} + \frac{a_1D_1^2}{2}\right) +\pi u\left[\left(\frac{D}{2}-kD\right)^2 +s\right] + \frac{\pi tu^2}{2} - \frac{\pi u^3}{3} + \pi D(1-2k)\left[ \frac{2u-t}{4}\sqrt{s+tu-u^2} + \frac{t\sqrt{s}}{4} + \frac{k^2D^2}{2}\left(\cos^{-1}\frac{t-2u}{2kD}-\alpha\right)\right] .. math:: v_2 = \frac{\pi h^2}{4}\left(2a_1 + \frac{D_1^2}{2a_1} - \frac{4h}{3}\right) .. math:: \alpha = \sin^{-1}\frac{1-2k}{2(f-k)} .. math:: a_1 = fD(1-\cos\alpha) .. math:: a_2 = kD\cos\alpha .. math:: D_1 = 2fD\sin\alpha .. math:: s = (kD\sin\alpha)^2 .. math:: t = 2a_2 .. math:: u = h - fD(1-\cos\alpha) Parameters ---------- D : float Diameter of the main cylindrical section, [m] f : float Dish-radius parameter; fD = dish radius [1/m] k : float knuckle-radius parameter ; kD = knuckle radius [1/m] h : float Height, as measured up to where the fluid ends, [m] Returns ------- V : float Volume [m^3] Examples -------- Matching example from [1]_, with inputs in inches and volume in gallons. >>> V_vertical_torispherical_concave(D=113., f=0.71, k=0.081, h=15)/231 103.88569287163769 References ---------- .. [1] Jones, D. "Compute Fluid Volumes in Vertical Tanks." Chemical Processing. December 18, 2003. http://www.chemicalprocessing.com/articles/2003/193/
def fly(self): dst_dir = Path(self.conf_file).parent.abspath package_dir = Path(dst_dir, self.package.shortname) try: if package_dir.exists(): shutil.rmtree(package_dir.abspath) except Exception as e: print(" can't be removed! Error: %s" % (package_dir, e)) for pkg, parent, sub_packages, sub_modules in self.package.walk(): if not is_ignored(pkg, self.ignored_package): dir_path = Path(*([dst_dir, ] + pkg.fullname.split("."))) init_path = Path(dir_path, "__init__.rst") make_dir(dir_path.abspath) make_file( init_path.abspath, self.generate_package_content(pkg), ) for mod in sub_modules: if not is_ignored(mod, self.ignored_package): module_path = Path(dir_path, mod.shortname + ".rst") make_file( module_path.abspath, self.generate_module_content(mod), )
Generate doc tree.
def render(self, renderer=None, **kwargs): return Markup(get_renderer(current_app, renderer)(**kwargs).visit( self))
Render the navigational item using a renderer. :param renderer: An object implementing the :class:`~.Renderer` interface. :return: A markupsafe string with the rendered result.
def main(): fmt,plot=,0 outfile="" if in sys.argv: print(main.__doc__) sys.exit() elif in sys.argv: ind=sys.argv.index() file=sys.argv[ind+1] f=open(file,) data=f.readlines() if in sys.argv: ind=sys.argv.index() outfile=open(sys.argv[ind+1],) if in sys.argv: plot=1 if in sys.argv: ind=sys.argv.index() fmt=sys.argv[ind+1] DIs,nDIs,rDIs= [],[],[] for line in data: if in line: rec=line.split() else: rec=line.split() DIs.append([float(rec[0]),float(rec[1])]) ppars=pmag.doprinc(DIs) for rec in DIs: angle=pmag.angle([rec[0],rec[1]],[ppars[],ppars[]]) if angle>90.: rDIs.append(rec) else: nDIs.append(rec) if len(rDIs) >=10 or len(nDIs) >=10: D1,I1=[],[] QQ={:1,:2} pmagplotlib.plot_init(QQ[],5,5) pmagplotlib.plot_init(QQ[],5,5) if len(nDIs) < 10: ppars=pmag.doprinc(rDIs) Drbar,Irbar=ppars[]-180.,-ppars[] Nr=len(rDIs) for di in rDIs: d,irot=pmag.dotilt(di[0],di[1],Drbar-180.,90.-Irbar) drot=d-180. if drot<0:drot=drot+360. D1.append(drot) I1.append(irot) Dtit= Itit= else: ppars=pmag.doprinc(nDIs) Dnbar,Inbar=ppars[],ppars[] Nn=len(nDIs) for di in nDIs: d,irot=pmag.dotilt(di[0],di[1],Dnbar-180.,90.-Inbar) drot=d-180. if drot<0:drot=drot+360. D1.append(drot) I1.append(irot) Dtit= Itit= Mu_n,Mu_ncr=pmagplotlib.plot_qq_unf(QQ[],D1,Dtit) Me_n,Me_ncr=pmagplotlib.plot_qq_exp(QQ[],I1,Itit) if outfile!="": if Mu_n<=Mu_ncr and Me_n<=Me_ncr: F= else: F= outstring=%(Dnbar,Inbar,Nn,Mu_n,Mu_ncr,Me_n,Me_ncr,F) outfile.write(outstring) else: print() sys.exit() if len(rDIs)>10 and len(nDIs)>10: D2,I2=[],[] QQ[]=3 QQ[]=4 pmagplotlib.plot_init(QQ[],5,5) pmagplotlib.plot_init(QQ[],5,5) ppars=pmag.doprinc(rDIs) Drbar,Irbar=ppars[]-180.,-ppars[] Nr=len(rDIs) for di in rDIs: d,irot=pmag.dotilt(di[0],di[1],Drbar-180.,90.-Irbar) drot=d-180. if drot<0:drot=drot+360. D2.append(drot) I2.append(irot) Dtit= Itit= Mu_r,Mu_rcr=pmagplotlib.plot_qq_unf(QQ[],D2,Dtit) Me_r,Me_rcr=pmagplotlib.plot_qq_exp(QQ[],I2,Itit) if outfile!="": if Mu_r<=Mu_rcr and Me_r<=Me_rcr: F= else: F= outstring=%(Drbar,Irbar,Nr,Mu_r,Mu_rcr,Me_r,Me_rcr,F) outfile.write(outstring) files={} for key in list(QQ.keys()): files[key]=file++key++fmt if pmagplotlib.isServer: black = purple = titles={} titles[]= EQ = pmagplotlib.add_borders(EQ,titles,black,purple) pmagplotlib.save_plots(QQ,files) elif plot==1: pmagplotlib.save_plots(QQ,files) else: pmagplotlib.draw_figs(QQ) ans=input(" S[a]ve to save plot, [q]uit without saving: ") if ans=="a": pmagplotlib.save_plots(QQ,files)
NAME fishqq.py DESCRIPTION makes qq plot from dec,inc input data INPUT FORMAT takes dec/inc pairs in space delimited file SYNTAX fishqq.py [command line options] OPTIONS -h help message -f FILE, specify file on command line -F FILE, specify output file for statistics -sav save and quit [saves as input file name plus fmt extension] -fmt specify format for output [png, eps, svg, pdf] OUTPUT: Dec Inc N Mu Mu_crit Me Me_crit Y/N where direction is the principal component and Y/N is Fisherian or not separate lines for each mode with N >=10 (N and R)
def show_vcs_output_vcs_nodes_vcs_node_info_switch_fcf_mac(self, **kwargs): config = ET.Element("config") show_vcs = ET.Element("show_vcs") config = show_vcs output = ET.SubElement(show_vcs, "output") vcs_nodes = ET.SubElement(output, "vcs-nodes") vcs_node_info = ET.SubElement(vcs_nodes, "vcs-node-info") switch_fcf_mac = ET.SubElement(vcs_node_info, "switch-fcf-mac") switch_fcf_mac.text = kwargs.pop() callback = kwargs.pop(, self._callback) return callback(config)
Auto Generated Code
def seoify_hyperlink(hyperlink): last_slash = hyperlink.rfind() return re.sub(r, , hyperlink[last_slash + 1:])
Modify a hyperlink to make it SEO-friendly by replacing hyphens with spaces and trimming multiple spaces. :param hyperlink: URL to attempt to grab SEO from
def update(self, scope, at=0): if hasattr(scope, ) and not at: self._mixins.update(scope._mixins) self[at][].update(scope[at][]) self[at][].extend(scope[at][]) self[at][].extend(scope[at][])
Update scope. Add another scope to this one. Args: scope (Scope): Scope object Kwargs: at (int): Level to update
def transaction_status(transaction): if not transaction or not transaction.get(): return blank() return FormattedItem( transaction[].get(), transaction[].get())
Returns a FormattedItem describing the given transaction. :param item: An object capable of having an active transaction
def listify_string(something): if isinstance(something, (str, six.text_type)): return [something] elif something is not None: return list(something) else: return list()
Takes *something* and make it a list. *something* is either a list of strings or a string, in which case the function returns a list containing the string. If *something* is None, an empty list is returned.
def get_gradebook_column_gradebook_assignment_session(self, proxy): if not self.supports_gradebook_column_gradebook_assignment(): raise errors.Unimplemented() return sessions.GradebookColumnGradebookAssignmentSession(proxy=proxy, runtime=self._runtime)
Gets the session for assigning gradebook column to gradebook mappings. arg: proxy (osid.proxy.Proxy): a proxy return: (osid.grading.GradebookColumnGradebookAssignmentSession) - a ``GradebookColumnGradebookAssignmentSession`` raise: NullArgument - ``proxy`` is ``null`` raise: OperationFailed - unable to complete request raise: Unimplemented - ``supports_gradebook_column_gradebook_assignment()`` is ``false`` *compliance: optional -- This method must be implemented if ``supports_gradebook_column_gradebook_assignment()`` is ``true``.*
def profile_config_set(name, config_key, config_value, remote_addr=None, cert=None, key=None, verify_cert=True): * profile = profile_get( name, remote_addr, cert, key, verify_cert, _raw=True ) return _set_property_dict_item( profile, , config_key, config_value )
Set a profile config item. name : The name of the profile to set the config item to. config_key : The items key. config_value : Its items value. remote_addr : An URL to a remote Server, you also have to give cert and key if you provide remote_addr and its a TCP Address! Examples: https://myserver.lan:8443 /var/lib/mysocket.sock cert : PEM Formatted SSL Certificate. Examples: ~/.config/lxc/client.crt key : PEM Formatted SSL Key. Examples: ~/.config/lxc/client.key verify_cert : True Wherever to verify the cert, this is by default True but in the most cases you want to set it off as LXD normaly uses self-signed certificates. CLI Example: .. code-block:: bash $ salt '*' lxd.profile_config_set autostart boot.autostart 0
def community_post_votes(self, post_id, **kwargs): "https://developer.zendesk.com/rest_api/docs/help_center/votes api_path = "/api/v2/community/posts/{post_id}/votes.json" api_path = api_path.format(post_id=post_id) return self.call(api_path, **kwargs)
https://developer.zendesk.com/rest_api/docs/help_center/votes#list-votes
def get_content_charset(self, failobj=None): missing = object() charset = self.get_param(, missing) if charset is missing: return failobj if isinstance(charset, tuple): pcharset = charset[0] or try: except UnicodeError: return failobj return charset.lower()
Return the charset parameter of the Content-Type header. The returned string is always coerced to lower case. If there is no Content-Type header, or if that header has no charset parameter, failobj is returned.
def permission_to_pyramid_acls(permissions): acls = [] for perm in permissions: if perm.type == "user": acls.append((Allow, perm.user.id, perm.perm_name)) elif perm.type == "group": acls.append((Allow, "group:%s" % perm.group.id, perm.perm_name)) return acls
Returns a list of permissions in a format understood by pyramid :param permissions: :return:
def run_rsync_project(): excludes = for exclude in settings.RSYNC_EXCLUDES: excludes += " --exclude ".format(exclude) command = "rsync -avz --stats --delete {0} {1} {2}".format( excludes, settings.FAB_SETTING(), settings.FAB_SETTING()) run(command)
Copies the project from the git repository to it's destination folder. This has the nice side effect of rsync deleting all ``.pyc`` files and removing other files that might have been left behind by sys admins messing around on the server. Usage:: fab <server> run_rsync_project
def refresh_modules(self, module_string=None, exact=True): if not module_string: if time.time() > (self.last_refresh_ts + 0.1): self.last_refresh_ts = time.time() else: return update_i3status = False for name, module in self.output_modules.items(): if ( module_string is None or (exact and name == module_string) or (not exact and name.startswith(module_string)) ): if module["type"] == "py3status": if self.config["debug"]: self.log("refresh py3status module {}".format(name)) module["module"].force_update() else: if self.config["debug"]: self.log("refresh i3status module {}".format(name)) update_i3status = True if update_i3status: self.i3status_thread.refresh_i3status()
Update modules. if module_string is None all modules are refreshed if module_string then modules with the exact name or those starting with the given string depending on exact parameter will be refreshed. If a module is an i3status one then we refresh i3status. To prevent abuse, we rate limit this function to 100ms for full refreshes.
def update_milestone(id, **kwargs): data = update_milestone_raw(id, **kwargs) if data: return utils.format_json(data)
Update a ProductMilestone
def space_list(args): r = fapi.list_workspaces() fapi._check_response_code(r, 200) spaces = [] project = args.project if project: project = re.compile( + project) for space in r.json(): ns = space[][] if project and not project.match(ns): continue ws = space[][] spaces.append(ns + + ws) return sorted(spaces, key=lambda s: s.lower())
List accessible workspaces, in TSV form: <namespace><TAB>workspace
async def processClaims(self, allClaims: Dict[ID, Claims]): res = [] for schemaId, (claim_signature, claim_attributes) in allClaims.items(): res.append(await self.processClaim(schemaId, claim_attributes, claim_signature)) return res
Processes and saves received Claims. :param claims: claims to be processed and saved for each claim definition.
def add_done_callback(self, future, callback): if future is None: raise bridge.BridgeReferenceError( "Tried to add a callback to a nonexistent Future. " "Make sure you pass the `returns` argument to your JavaMethod") return self.loop.add_done_callback(future, callback)
Add a callback on a future object put here so it can be implemented with different event loops. Parameters ----------- future: Future or Deferred Future implementation for the current EventLoop callback: callable Callback to invoke when the future is done
def _IfdEntryFactory(stream_rdr, offset): ifd_entry_classes = { TIFF_FLD.ASCII: _AsciiIfdEntry, TIFF_FLD.SHORT: _ShortIfdEntry, TIFF_FLD.LONG: _LongIfdEntry, TIFF_FLD.RATIONAL: _RationalIfdEntry, } field_type = stream_rdr.read_short(offset, 2) if field_type in ifd_entry_classes: entry_cls = ifd_entry_classes[field_type] else: entry_cls = _IfdEntry return entry_cls.from_stream(stream_rdr, offset)
Return an |_IfdEntry| subclass instance containing the value of the directory entry at *offset* in *stream_rdr*.
def sample(self, data, sample_size=15000, blocked_proportion=0.5, original_length=None): self._checkData(data) self.active_learner = self.ActiveLearner(self.data_model) self.active_learner.sample_combo(data, blocked_proportion, sample_size, original_length)
Draw a sample of record pairs from the dataset (a mix of random pairs & pairs of similar records) and initialize active learning with this sample Arguments: data -- Dictionary of records, where the keys are record_ids and the values are dictionaries with the keys being field names sample_size -- Size of the sample to draw blocked_proportion -- Proportion of the sample that will be blocked original_length -- Length of original data, should be set if `data` is a sample of full data
def find_disulfide_bridges(self, threshold=3.0): if self.structure: parsed = self.structure else: parsed = self.parse_structure() if not parsed: log.error(.format(self.id)) return disulfide_bridges = ssbio.protein.structure.properties.residues.search_ss_bonds(parsed.first_model, threshold=threshold) if not disulfide_bridges: log.debug(.format(self.id)) for chain, bridges in disulfide_bridges.items(): self.chains.get_by_id(chain).seq_record.annotations[] = disulfide_bridges[chain] log.debug(.format(chain, len(bridges))) log.debug(s seq_record letter_annotations'.format(chain))
Run Biopython's search_ss_bonds to find potential disulfide bridges for each chain and store in ChainProp. Will add a list of tuple pairs into the annotations field, looks like this:: [ ((' ', 79, ' '), (' ', 110, ' ')), ((' ', 174, ' '), (' ', 180, ' ')), ((' ', 369, ' '), (' ', 377, ' '))] Where each pair is a pair of cysteine residues close together in space.
def load_file(self, filename): self._say("Loading file: " + filename) fh = codecs.open(filename, , ) lines = fh.readlines() fh.close() self._say("Parsing " + str(len(lines)) + " lines of code from " + filename) self._parse(filename, lines)
Load and parse a RiveScript document. :param str filename: The path to a RiveScript file.
def get_uri(source): import gst src_info = source_info(source) if src_info[]: return get_uri(src_info[]) elif gst.uri_is_valid(source): uri_protocol = gst.uri_get_protocol(source) if gst.uri_protocol_is_supported(gst.URI_SRC, uri_protocol): return source else: raise IOError() else: raise IOError( % source)
Check a media source as a valid file or uri and return the proper uri
def subscribe(self, requested_timeout=None, auto_renew=False): class AutoRenewThread(threading.Thread): def __init__(self, interval, stop_flag, sub, *args, **kwargs): super(AutoRenewThread, self).__init__(*args, **kwargs) self.interval = interval self.sub = sub self.stop_flag = stop_flag self.daemon = True def run(self): sub = self.sub stop_flag = self.stop_flag interval = self.interval while not stop_flag.wait(interval): log.info("Autorenewing subscription %s", sub.sid) sub.renew() self.requested_timeout = requested_timeout if self._has_been_unsubscribed: raise SoCoException( ) service = self.service if not event_listener.is_running: event_listener.start(service.soco) ip_address, port = event_listener.address if config.EVENT_ADVERTISE_IP: ip_address = config.EVENT_ADVERTISE_IP headers = { : .format(ip_address, port), : } if requested_timeout is not None: headers["TIMEOUT"] = "Second-{}".format(requested_timeout) with _subscriptions_lock: response = requests.request( , service.base_url + service.event_subscription_url, headers=headers) response.raise_for_status() self.sid = response.headers[] timeout = response.headers[] if timeout.lower() == : self.timeout = None else: self.timeout = int(timeout.lstrip()) self._timestamp = time.time() self.is_subscribed = True log.info( "Subscribed to %s, sid: %s", service.base_url + service.event_subscription_url, self.sid) _subscriptions[self.sid] = self atexit.register(self.unsubscribe) if not auto_renew: return interval = self.timeout * 85 / 100 auto_renew_thread = AutoRenewThread( interval, self._auto_renew_thread_flag, self) auto_renew_thread.start()
Subscribe to the service. If requested_timeout is provided, a subscription valid for that number of seconds will be requested, but not guaranteed. Check `timeout` on return to find out what period of validity is actually allocated. Note: SoCo will try to unsubscribe any subscriptions which are still subscribed on program termination, but it is good practice for you to clean up by making sure that you call :meth:`unsubscribe` yourself. Args: requested_timeout(int, optional): The timeout to be requested. auto_renew (bool, optional): If `True`, renew the subscription automatically shortly before timeout. Default `False`.
def getDatabaseFileSize(self): if DISABLE_PERSISTENT_CACHING: return "?" size = os.path.getsize(self.__db_filepath) if size > 1000000000: size = "%0.3fGB" % (size / 1000000000) elif size > 1000000: size = "%0.2fMB" % (size / 1000000) elif size > 1000: size = "%uKB" % (size // 1000) else: size = "%uB" % (size) return size
Return the file size of the database as a pretty string.
def extractFromURL(url, cache=False, cacheDir=, verbose=False, encoding=None, filters=None, userAgent=None, timeout=5, blur=5, ignore_robotstxt=False, only_mime_types=None, raw=False): blur = int(blur) try: import chardet except ImportError as e: raise ImportError(("%s\nYou need to install chardet.\n" + \ "e.g. sudo pip install chardet") % e) if only_mime_types and isinstance(only_mime_types, six.text_type): only_mime_types = only_mime_types.split() if cache: if not os.path.isdir(cacheDir): cache_perms = 488 os.makedirs(cacheDir, cache_perms) cache_key = generate_key(url) cached_content = cache_get(cacheDir, cache_key) if cached_content: return cached_content if not ignore_robotstxt: if not check_robotstxt(url, cache, cacheDir, userAgent=userAgent): if verbose: print("Request denied by robots.txt") return if verbose: print( % url) html = fetch( url, timeout=timeout, userAgent=userAgent, only_mime_types=only_mime_types) if not html: return if not encoding: if isinstance(html, unicode): html = html.encode(, ) encoding_opinion = chardet.detect(html) encoding = encoding_opinion[] if verbose: print( % encoding) if verbose: print( % len(html)) if cache: raw_key = generate_key(url, "%s.raw") cache_set(cacheDir, raw_key, html) if filters: filter_names = map(str.strip, filters.split()) for filter_name in filter_names: fltr = get_filter(filter_name) html = fltr(html) html = tidyHTML(html) if verbose: print( % len(html)) if not html: return html = unicode(html, encoding=encoding, errors=) if raw: return html res = extractFromHTML(html, blur=blur) assert isinstance(res, unicode) res = res.encode(encoding, ) if cache: cache_set(cacheDir, cache_key, res) return res
Extracts text from a URL. Parameters: url := string Remote URL or local filename where HTML will be read. cache := bool True=store and retrieve url from cache False=always retrieve url from the web cacheDir := str Directory where cached url contents will be stored. verbose := bool True=print logging messages False=print no output encoding := string The encoding of the page contents. If none given, it will attempt to guess the encoding. See http://docs.python.org/howto/unicode.html for further info on Python Unicode and encoding support. filters := string Comma-delimited list of filters to apply before parsing. only_mime_types := list of strings A list of mime-types to limit parsing to. If the mime-type of the raw-content retrieved does not match one of these, a value of None will be returned.
def successors(self): if not self.children: return for part in self.children: yield part for subpart in part.successors(): yield subpart
Yield Compounds below self in the hierarchy. Yields ------- mb.Compound The next Particle below self in the hierarchy
def _CreateComplexTypeFromData( self, elem_type, type_is_override, data, set_type_attrs): elem_arguments = dict(elem_type.elements) instantiated_arguments = { k: self._PackArgumentsHelper(elem_arguments[k], v, set_type_attrs) for k, v in data if k != } if set_type_attrs: found_type_attr = next((e_name for e_name, _ in elem_type.elements if e_name.endswith()), None) if found_type_attr and type_is_override: instantiated_arguments[found_type_attr] = elem_type.qname.localname return elem_type(**instantiated_arguments)
Initialize a SOAP element with specific data. Args: elem_type: The type of the element to create. type_is_override: A boolean specifying if the type is being overridden. data: The data to hydrate the type with. set_type_attrs: A boolean indicating whether or not attributes that end in .Type should be set. This is only necessary for batch job service. Returns: An fully initialized SOAP element.
def stylize(self, images, style=None, verbose=True, max_size=800, batch_size = 4): if(batch_size < 1): raise _ToolkitError(" must be greater than or equal to 1") from ._sframe_loader import SFrameSTIter as _SFrameSTIter import mxnet as _mx from mxnet import gluon as _gluon from .._mxnet import _mxnet_utils set_of_all_idx = self._style_indices() style, single_style = self._style_input_check(style) if isinstance(max_size, _six.integer_types): input_shape = (max_size, max_size) else: input_shape = max_size[::-1] images, unpack = self._canonize_content_input(images, single_style=single_style) dataset_size = len(images) output_size = dataset_size * len(style) batch_size_each = min(batch_size, output_size) num_mxnet_gpus = _mxnet_utils.get_num_gpus_in_use(max_devices=batch_size_each) if num_mxnet_gpus == 0: batch_size_each = 1 loader_type = else: loader_type = self._model.batch_size = batch_size_each self._model.hybridize() ctx = _mxnet_utils.get_mxnet_context(max_devices=batch_size_each) batch_size = max(num_mxnet_gpus, 1) * batch_size_each last_time = 0 if dataset_size == 0: raise _ToolkitError("SFrame cannot be empty") content_feature = _tkutl._find_only_image_column(images) _raise_error_if_not_training_sframe(images, content_feature) max_h = 0 max_w = 0 oversized_count = 0 for img in images[content_feature]: if img.height > input_shape[0] or img.width > input_shape[1]: oversized_count += 1 max_h = max(img.height, max_h) max_w = max(img.width, max_w) if input_shape[0] > max_h: input_shape = (max_h, input_shape[1]) if input_shape[1] > max_w: input_shape = (input_shape[0], max_w) format(curr_image=count, max_n=output_size, width=len(str(output_size)))) last_time = cur_time return unpack(sb.close())
Stylize an SFrame of Images given a style index or a list of styles. Parameters ---------- images : SFrame | Image A dataset that has the same content image column that was used during training. style : int or list, optional The selected style or list of styles to use on the ``images``. If `None`, all styles will be applied to each image in ``images``. verbose : bool, optional If True, print progress updates. max_size : int or tuple Max input image size that will not get resized during stylization. Images with a side larger than this value, will be scaled down, due to time and memory constraints. If tuple, interpreted as (max width, max height). Without resizing, larger input images take more time to stylize. Resizing can effect the quality of the final stylized image. batch_size : int, optional If you are getting memory errors, try decreasing this value. If you have a powerful computer, increasing this value may improve performance. Returns ------- out : SFrame or SArray or turicreate.Image If ``style`` is a list, an SFrame is always returned. If ``style`` is a single integer, the output type will match the input type (Image, SArray, or SFrame). See Also -------- create Examples -------- >>> image = tc.Image("/path/to/image.jpg") >>> stylized_images = model.stylize(image, style=[0, 1]) Data: +--------+-------+------------------------+ | row_id | style | stylized_image | +--------+-------+------------------------+ | 0 | 0 | Height: 256 Width: 256 | | 0 | 1 | Height: 256 Width: 256 | +--------+-------+------------------------+ [2 rows x 3 columns] >>> images = tc.image_analysis.load_images('/path/to/images') >>> stylized_images = model.stylize(images) Data: +--------+-------+------------------------+ | row_id | style | stylized_image | +--------+-------+------------------------+ | 0 | 0 | Height: 256 Width: 256 | | 0 | 1 | Height: 256 Width: 256 | | 0 | 2 | Height: 256 Width: 256 | | 0 | 3 | Height: 256 Width: 256 | | 1 | 0 | Height: 640 Width: 648 | | 1 | 1 | Height: 640 Width: 648 | | 1 | 2 | Height: 640 Width: 648 | | 1 | 3 | Height: 640 Width: 648 | +--------+-------+------------------------+ [8 rows x 3 columns]
def pick_flat_z(data): zmes = [] for i in data[]: zmes.append(i[:, 0]) return np.asarray(zmes)
Generate a 2D array of the quasiparticle weight by only selecting the first particle data
def get_covalent_bonds(self, tol=0.2): bonds = [] for site1, site2 in itertools.combinations(self._sites, 2): if CovalentBond.is_bonded(site1, site2, tol): bonds.append(CovalentBond(site1, site2)) return bonds
Determines the covalent bonds in a molecule. Args: tol (float): The tol to determine bonds in a structure. See CovalentBond.is_bonded. Returns: List of bonds
def clear_preview(self): try: rm = self.my_osid_object._get_provider_manager() except AttributeError: rm = self.my_osid_object_form._get_provider_manager() try: aas = rm.get_asset_admin_session_for_repository( Id(self.my_osid_object._my_map[][0])) except AttributeError: aas = rm.get_asset_admin_session_for_repository( Id(self.my_osid_object_form._my_map[][0])) if not in self.my_osid_object_form._my_map[]: raise NotFound() aas.delete_asset( Id(self.my_osid_object_form._my_map[][][])) del self.my_osid_object_form._my_map[][]
stub
def _contextualise(self): deja_vues = [] for rank in reversed(self.taxonomy): clades = [e for e in self.hierarchy[rank] if e[1]] uniques = [e for e in clades if len(e[0]) == 1] uniques = [e for e in uniques if e[0][0].ident not in deja_vues] for e in uniques: ident = e[0][0].ident self[ident][] = e[1] deja_vues.append(ident)
Determine contextual idents (cidents)
def close_hover(self, element, use_js=False): try: if use_js: self._js_hover(, element) else: actions = ActionChains(self.driver) actions.move_to_element_with_offset(element, -100, -100) actions.reset_actions() except (StaleElementReferenceException, MoveTargetOutOfBoundsException): return True
Close hover by moving to a set offset "away" from the element being hovered. :param element: element that triggered the hover to open :param use_js: use javascript to close hover :return: None
def get_entity_propnames(entity): ins = entity if isinstance(entity, InstanceState) else inspect(entity) return set( ins.mapper.column_attrs.keys() + ins.mapper.relationships.keys() )
Get entity property names :param entity: Entity :type entity: sqlalchemy.ext.declarative.api.DeclarativeMeta :returns: Set of entity property names :rtype: set
def CreateGroup(self, GroupName): groups = self.CustomGroups self._DoCommand( % tounicode(GroupName)) for g in self.CustomGroups: if g not in groups and g.DisplayName == GroupName: return g raise SkypeError(0, )
Creates a custom contact group. :Parameters: GroupName : unicode Group name. :return: A group object. :rtype: `Group` :see: `DeleteGroup`
def add_sink(self, sink): if sink is not None: self.sinks.add(sink) if hasattr(sink, ): sink.start()
Add a vehicle data sink to the instance. ``sink`` should be a sub-class of ``DataSink`` or at least have a ``receive(message, **kwargs)`` method. The sink will be started if it is startable. (i.e. it has a ``start()`` method).
def managed(name, venv_bin=None, requirements=None, system_site_packages=False, distribute=False, use_wheel=False, clear=False, python=None, extra_search_dir=None, never_download=None, prompt=None, user=None, cwd=None, index_url=None, extra_index_url=None, pre_releases=False, no_deps=False, pip_download=None, pip_download_cache=None, pip_exists_action=None, pip_ignore_installed=False, proxy=None, use_vt=False, env_vars=None, no_use_wheel=False, pip_upgrade=False, pip_pkgs=None, pip_no_cache_dir=False, pip_cache_dir=None, process_dependency_links=False, no_binary=None, **kwargs): /usr/local/bin/ ret = {: name, : True, : , : {}} if not in __salt__: ret[] = False ret[] = return ret if salt.utils.platform.is_windows(): venv_py = os.path.join(name, , ) else: venv_py = os.path.join(name, , ) venv_exists = os.path.exists(venv_py) return ret
Create a virtualenv and optionally manage it with pip name Path to the virtualenv. venv_bin: virtualenv The name (and optionally path) of the virtualenv command. This can also be set globally in the minion config file as ``virtualenv.venv_bin``. requirements: None Path to a pip requirements file. If the path begins with ``salt://`` the file will be transferred from the master file server. use_wheel: False Prefer wheel archives (requires pip >= 1.4). python : None Python executable used to build the virtualenv user: None The user under which to run virtualenv and pip. cwd: None Path to the working directory where `pip install` is executed. no_deps: False Pass `--no-deps` to `pip install`. pip_exists_action: None Default action of pip when a path already exists: (s)witch, (i)gnore, (w)ipe, (b)ackup. proxy: None Proxy address which is passed to `pip install`. env_vars: None Set environment variables that some builds will depend on. For example, a Python C-module may have a Makefile that needs INCLUDE_PATH set to pick up a header file while compiling. no_use_wheel: False Force to not use wheel archives (requires pip>=1.4) no_binary Force to not use binary packages (requires pip >= 7.0.0) Accepts either :all: to disable all binary packages, :none: to empty the set, or a list of one or more packages pip_upgrade: False Pass `--upgrade` to `pip install`. pip_pkgs: None As an alternative to `requirements`, pass a list of pip packages that should be installed. process_dependency_links: False Run pip install with the --process_dependency_links flag. .. versionadded:: 2017.7.0 Also accepts any kwargs that the virtualenv module will. However, some kwargs, such as the ``pip`` option, require ``- distribute: True``. .. code-block:: yaml /var/www/myvirtualenv.com: virtualenv.managed: - system_site_packages: False - requirements: salt://REQUIREMENTS.txt - env_vars: PATH_VAR: '/usr/local/bin/'
def _crps_cdf_single(x, cdf_or_dist, xmin=None, xmax=None, tol=1e-6): cdf = getattr(cdf_or_dist, , cdf_or_dist) assert callable(cdf) if (tol is not None) and (cdf(xmin) >= tol) or (cdf(xmax) <= (1. - tol)): raise ValueError( % ( if cdf(xmin) >= tol else )) def lhs(y): return np.square(cdf(y)) lhs_int, lhs_tol = integrate.quad(lhs, xmin, x) if (tol is not None) and (lhs_tol >= 0.5 * tol): raise ValueError( % (lhs_tol, lhs_int)) def rhs(y): return np.square(1. - cdf(y)) rhs_int, rhs_tol = integrate.quad(rhs, x, xmax) if (tol is not None) and (rhs_tol >= 0.5 * tol): raise ValueError( % (rhs_tol, rhs_int)) return lhs_int + rhs_int
See crps_cdf for docs.
def mean(data, n=3, **kwargs): if len(data[-n:]) < n: forecast = np.nan else: forecast = np.mean(data[-n:]) return forecast
The mean forecast for the next point is the mean value of the previous ``n`` points in the series. Args: data (np.array): Observed data, presumed to be ordered in time. n (int): period over which to calculate the mean Returns: float: a single-valued forecast for the next value in the series.
def create_core(self, thing_name, config_file, region=None, cert_dir=None, account_id=None, policy_name=, profile_name=None): config = GroupConfigFile(config_file=config_file) if config.is_fresh() is False: raise ValueError( "Config file already tracking previously created core or group" ) if region is None: region = self._region if account_id is None: account_id = self._account_id keys_cert, thing = self.create_thing(thing_name, region, cert_dir) cert_arn = keys_cert[] config[] = { : thing[], : cert_arn, : keys_cert[], : thing_name } logging.debug("create_core cfg:{0}".format(config)) logging.info("Thing: associated with cert:".format( thing_name, cert_arn)) core_policy = self.get_core_policy( core_name=thing_name, account_id=account_id, region=region) iot_client = _get_iot_session(region=region, profile_name=profile_name) self._create_attach_thing_policy( cert_arn, core_policy, iot_client=iot_client, policy_name=policy_name ) misc = config[] misc[] = policy_name config[] = misc
Using the `thing_name` value, creates a Thing in AWS IoT, attaches and downloads new keys & certs to the certificate directory, then records the created information in the local config file for inclusion in the Greengrass Group as a Greengrass Core. :param thing_name: the name of the thing to create and use as a Greengrass Core :param config_file: config file used to track the Greengrass Core in the group :param region: the region in which to create the new core. [default: us-west-2] :param cert_dir: the directory in which to store the thing's keys and certs. If `None` then use the current directory. :param account_id: the account_id in which to create the new core. [default: None] :param policy_name: the name of the policy to associate with the device. [default: 'ggc-default-policy'] :param profile_name: the name of the `awscli` profile to use. [default: None]
def showLayer(self, title=, debugText=): img = PIL.Image.fromarray(self.data, ) if debugText!=: draw = PIL.ImageDraw.Draw(img) font = PIL.ImageFont.truetype("DejaVuSansMono.ttf", 24) draw.text((0, 0),debugText,(255,255,255),font=font) img.show(title=title)
Shows the single layer. :param title: A string with the title of the window where to render the image. :param debugText: A string with some text to render over the image. :rtype: Nothing.
def solveConsPrefShock(solution_next,IncomeDstn,PrefShkDstn, LivPrb,DiscFac,CRRA,Rfree,PermGroFac,BoroCnstArt, aXtraGrid,vFuncBool,CubicBool): solver = ConsPrefShockSolver(solution_next,IncomeDstn,PrefShkDstn,LivPrb, DiscFac,CRRA,Rfree,PermGroFac,BoroCnstArt,aXtraGrid, vFuncBool,CubicBool) solver.prepareToSolve() solution = solver.solve() return solution
Solves a single period of a consumption-saving model with preference shocks to marginal utility. Problem is solved using the method of endogenous gridpoints. Parameters ---------- solution_next : ConsumerSolution The solution to the succeeding one period problem. IncomeDstn : [np.array] A list containing three arrays of floats, representing a discrete approximation to the income process between the period being solved and the one immediately following (in solution_next). Order: event probabilities, permanent shocks, transitory shocks. PrefShkDstn : [np.array] Discrete distribution of the multiplicative utility shifter. Order: probabilities, preference shocks. LivPrb : float Survival probability; likelihood of being alive at the beginning of the succeeding period. DiscFac : float Intertemporal discount factor for future utility. CRRA : float Coefficient of relative risk aversion. Rfree : float Risk free interest factor on end-of-period assets. PermGroGac : float Expected permanent income growth factor at the end of this period. BoroCnstArt: float or None Borrowing constraint for the minimum allowable assets to end the period with. If it is less than the natural borrowing constraint, then it is irrelevant; BoroCnstArt=None indicates no artificial bor- rowing constraint. aXtraGrid: np.array Array of "extra" end-of-period asset values-- assets above the absolute minimum acceptable level. vFuncBool: boolean An indicator for whether the value function should be computed and included in the reported solution. CubicBool: boolean An indicator for whether the solver should use cubic or linear inter- polation. Returns ------- solution: ConsumerSolution The solution to the single period consumption-saving problem. Includes a consumption function cFunc (using linear splines), a marginal value function vPfunc, a minimum acceptable level of normalized market re- sources mNrmMin, normalized human wealth hNrm, and bounding MPCs MPCmin and MPCmax. It might also have a value function vFunc. The consumption function is defined over normalized market resources and the preference shock, c = cFunc(m,PrefShk), but the (marginal) value function is defined unconditionally on the shock, just before it is revealed.
def _pyshark_read_frame(self): from pcapkit.toolkit.pyshark import packet2dict, tcp_traceflow packet = next(self._extmp) self._frnum = int(packet.number) self._proto = packet.frame_info.protocols if self._flag_v: print(f) frnum = f if not self._flag_q: info = packet2dict(packet) if self._flag_f: ofile = self._ofile(f) ofile(info, name=frnum) else: self._ofile(info, name=frnum) if self._flag_d: setattr(packet, , packet2dict) self._frame.append(packet) if self._flag_t: flag, data = tcp_traceflow(packet) if flag: self._trace(data) return packet
Read frames.
def to_bedtool(iterator): def gen(): for i in iterator: yield helpers.asinterval(i) return pybedtools.BedTool(gen())
Convert any iterator into a pybedtools.BedTool object. Note that the supplied iterator is not consumed by this function. To save to a temp file or to a known location, use the `.saveas()` method of the returned BedTool object.
def get_next_step(self): layer_purpose = self.parent.step_kw_purpose.selected_purpose() if layer_purpose != layer_purpose_aggregation: subcategory = self.parent.step_kw_subcategory.\ selected_subcategory() else: subcategory = {: None} field_groups = get_field_groups( layer_purpose[], subcategory[]) compulsory_field = get_compulsory_fields( layer_purpose[], subcategory[]) replace_null=True, in_group=False) if default_inasafe_fields: return self.parent.step_kw_default_inasafe_fields return self.parent.step_kw_source
Find the proper step when user clicks the Next button. :returns: The step to be switched to :rtype: WizardStep
def nth(series, n, order_by=None): if order_by is not None: series = order_series_by(series, order_by) try: return series.iloc[n] except: return np.nan
Returns the nth value of a series. Args: series (pandas.Series): column to summarize. n (integer): position of desired value. Returns `NaN` if out of range. Kwargs: order_by: a pandas.Series or list of series (can be symbolic) to order the input series by before summarization.
def list_customer_users(self, customer_id): content = self._fetch("/customer/users/%s" % customer_id) return map(lambda x: FastlyUser(self, x), content)
List all users from a specified customer id.
def create_control(self, pid, callback, callback_parsed=None): logger.info("create_control(pid=\"%s\", control_cb=%s) [lid=%s]", pid, callback, self.__lid) if callback_parsed: callback = self._client._get_parsed_control_callback(callback_parsed, callback) return self.__create_point(R_CONTROL, pid, control_cb=callback)
Create a control for this Thing with a local point id (pid) and a control request feedback Returns a new [Control](Point.m.html#IoticAgent.IOT.Point.Control) object or the existing one if the Control already exists Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException) containing the error if the infrastructure detects a problem Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException) if there is a communications problem between you and the infrastructure `pid` (required) (string) local id of your Control `callback` (required) (function reference) callback function to invoke on receipt of a control request. The callback receives a single dict argument, with keys of: #!python 'data' # (decoded or raw bytes) 'mime' # (None, unless payload was not decoded and has a mime type) 'subId' # (the global id of the associated subscripion) 'entityLid' # (local id of the Thing to which the control belongs) 'lid' # (local id of control) 'confirm' # (whether a confirmation is expected) 'requestId' # (required for sending confirmation) `callback_parsed` (optional) (function reference) callback function to invoke on receipt of control data. This is equivalent to `callback` except the dict includes the `parsed` key which holds the set of values in a [PointDataObject](./Point.m.html#IoticAgent.IOT.Point.PointDataObject) instance. If both `callback_parsed` and `callback` have been specified, the former takes precedence and `callback` is only called if the point data could not be parsed according to its current value description. `NOTE`: `callback_parsed` can only be used if `auto_encode_decode` is enabled for the client instance.
def discard_member(self, member, pipe=None): pipe = self.redis if pipe is None else pipe pipe.zrem(self.key, self._pickle(member))
Remove *member* from the collection, unconditionally.
def HA2(credentials, request, algorithm): if credentials.get("qop") == "auth" or credentials.get() is None: return H(b":".join([request[].encode(), request[].encode()]), algorithm) elif credentials.get("qop") == "auth-int": for k in , , : if k not in request: raise ValueError("%s required" % k) A2 = b":".join([request[].encode(), request[].encode(), H(request[], algorithm).encode()]) return H(A2, algorithm) raise ValueError
Create HA2 md5 hash If the qop directive's value is "auth" or is unspecified, then HA2: HA2 = md5(A2) = MD5(method:digestURI) If the qop directive's value is "auth-int" , then HA2 is HA2 = md5(A2) = MD5(method:digestURI:MD5(entityBody))