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def address_offset(self): """ Byte address offset of this node relative to it's parent If this node is an array, it's index must be known Raises ------ ValueError If this property is referenced on a node whose array index is not fully defined """ if self.inst.is_array: if self.current_idx is None: raise ValueError("Index of array element must be known to derive address") # Calculate the "flattened" index of a general multidimensional array # For example, a component array declared as: # foo[S0][S1][S2] # and referenced as: # foo[I0][I1][I2] # Is flattened like this: # idx = I0*S1*S2 + I1*S2 + I2 idx = 0 for i in range(len(self.current_idx)): sz = 1 for j in range(i+1, len(self.inst.array_dimensions)): sz *= self.inst.array_dimensions[j] idx += sz * self.current_idx[i] offset = self.inst.addr_offset + idx * self.inst.array_stride else: offset = self.inst.addr_offset return offset
Byte address offset of this node relative to it's parent If this node is an array, it's index must be known Raises ------ ValueError If this property is referenced on a node whose array index is not fully defined
def oauth_login(self, provider, id_column, id, attrs, defaults, redirect_url=None): """Execute a login via oauth. If no user exists, oauth_signup() will be called """ user = self.query.filter(**dict([(id_column, id)])).first() if not redirect_url: redirect_url = request.args.get('next') or url_for(self.options["redirect_after_login"]) if self.logged_in(): if user and user != self.current: if self.options["oauth_user_already_exists_message"]: flash(self.options["oauth_user_already_exists_message"].format(provider=provider), "error") return redirect(redirect_url) if provider not in self.current.auth_providers: self.current.auth_providers.append(provider) current_app.features.models.save(self.current, **attrs) elif not user: return self.oauth_signup(provider, attrs, defaults, redirect_url=redirect_url) else: self.login(user, provider=provider, **attrs) return redirect(redirect_url)
Execute a login via oauth. If no user exists, oauth_signup() will be called
def log(cls, event=None, actor=None, data=None): """Generate and insert a new event Args: event (str): Action performed actor (str): Actor (user or subsystem) triggering the event data (dict): Any extra data necessary for describing the event Returns: `None` """ from cloud_inquisitor.log import auditlog auditlog(event=event, actor=actor, data=data)
Generate and insert a new event Args: event (str): Action performed actor (str): Actor (user or subsystem) triggering the event data (dict): Any extra data necessary for describing the event Returns: `None`
def request(self): """ Returns an OAuth2 Session to be used to make requests. Returns None if a token hasn't yet been received.""" headers = {'Accept': 'application/json'} # Use API Key if possible if self.api_key: headers['X-API-KEY'] = self.api_key return requests,headers else: # Try to use OAuth if self.token: return OAuth2Session(self.client_id, token=self.token),headers else: raise APIError("No API key and no OAuth session available")
Returns an OAuth2 Session to be used to make requests. Returns None if a token hasn't yet been received.
def push(package, is_public=False, is_team=False, reupload=False, hash=None): """ Push a Quilt data package to the server """ team, owner, pkg, subpath = parse_package(package, allow_subpath=True) _check_team_id(team) session = _get_session(team) store, pkgroot = PackageStore.find_package(team, owner, pkg, pkghash=hash) if pkgroot is None: raise CommandException("Package {package} not found.".format(package=package)) pkghash = hash_contents(pkgroot) if hash is not None: assert pkghash == hash contents = pkgroot for component in subpath: try: contents = contents.children[component] except (AttributeError, KeyError): raise CommandException("Invalid subpath: %r" % component) def _push_package(dry_run=False, sizes=dict()): data = json.dumps(dict( dry_run=dry_run, is_public=is_public, is_team=is_team, contents=contents, description="", # TODO sizes=sizes ), default=encode_node) compressed_data = gzip_compress(data.encode('utf-8')) if subpath: return session.post( "{url}/api/package_update/{owner}/{pkg}/{subpath}".format( url=get_registry_url(team), owner=owner, pkg=pkg, subpath='/'.join(subpath) ), data=compressed_data, headers={ 'Content-Encoding': 'gzip' } ) else: return session.put( "{url}/api/package/{owner}/{pkg}/{hash}".format( url=get_registry_url(team), owner=owner, pkg=pkg, hash=pkghash ), data=compressed_data, headers={ 'Content-Encoding': 'gzip' } ) print("Fetching upload URLs from the registry...") resp = _push_package(dry_run=True) obj_urls = resp.json()['upload_urls'] assert set(obj_urls) == set(find_object_hashes(contents)) obj_sizes = { obj_hash: os.path.getsize(store.object_path(obj_hash)) for obj_hash in obj_urls } success = upload_fragments(store, obj_urls, obj_sizes, reupload=reupload) if not success: raise CommandException("Failed to upload fragments") print("Uploading package metadata...") resp = _push_package(sizes=obj_sizes) package_url = resp.json()['package_url'] if not subpath: # Update the latest tag. print("Updating the 'latest' tag...") session.put( "{url}/api/tag/{owner}/{pkg}/{tag}".format( url=get_registry_url(team), owner=owner, pkg=pkg, tag=LATEST_TAG ), data=json.dumps(dict( hash=pkghash )) ) print("Push complete. %s is live:\n%s" % (package, package_url))
Push a Quilt data package to the server
def _parse_status(self, output): ''' Unit testing is so much easier when Vagrant is removed from the equation. ''' parsed = self._parse_machine_readable_output(output) statuses = [] # group tuples by target name # assuming tuples are sorted by target name, this should group all # the tuples with info for each target. for target, tuples in itertools.groupby(parsed, lambda tup: tup[1]): # transform tuples into a dict mapping "type" to "data" info = {kind: data for timestamp, _, kind, data in tuples} status = Status(name=target, state=info.get('state'), provider=info.get('provider-name')) statuses.append(status) return statuses
Unit testing is so much easier when Vagrant is removed from the equation.
def find_genome_length(self): """ Determine the total length of all the contigs for each strain """ for sample in self.metadata: # Use the sum() method to add all the contig lengths in the list sample[self.analysistype].genome_length = sum(sample[self.analysistype].contig_lengths)
Determine the total length of all the contigs for each strain
def _set_formatter(self): """ Inspects config and sets the name of the formatter to either "json" or "text" as instance attr. If not present in config, default is "text" """ if hasattr(self._config, "formatter") and self._config.formatter == "json": self._formatter = "json" else: self._formatter = "text"
Inspects config and sets the name of the formatter to either "json" or "text" as instance attr. If not present in config, default is "text"
def set_nest_transactions_with_savepoints(self, nest_transactions_with_savepoints): """Sets if nested transactions should use savepoints. :param nest_transactions_with_savepoints: `True` or `False` """ if self._transaction_nesting_level > 0: raise DBALConnectionError.may_not_alter_nested_transaction_with_savepoints_in_transaction() if not self._platform.is_savepoints_supported(): raise DBALConnectionError.savepoints_not_supported() self._nest_transactions_with_savepoints = bool(nest_transactions_with_savepoints)
Sets if nested transactions should use savepoints. :param nest_transactions_with_savepoints: `True` or `False`
def _run_runner(self): ''' Actually execute specific runner :return: ''' import salt.minion ret = {} low = {'fun': self.opts['fun']} try: # Allocate a jid async_pub = self._gen_async_pub() self.jid = async_pub['jid'] fun_args = salt.utils.args.parse_input( self.opts['arg'], no_parse=self.opts.get('no_parse', [])) verify_fun(self.functions, low['fun']) args, kwargs = salt.minion.load_args_and_kwargs( self.functions[low['fun']], fun_args) low['arg'] = args low['kwarg'] = kwargs if self.opts.get('eauth'): if 'token' in self.opts: try: with salt.utils.files.fopen(os.path.join(self.opts['cachedir'], '.root_key'), 'r') as fp_: low['key'] = salt.utils.stringutils.to_unicode(fp_.readline()) except IOError: low['token'] = self.opts['token'] # If using eauth and a token hasn't already been loaded into # low, prompt the user to enter auth credentials if 'token' not in low and 'key' not in low and self.opts['eauth']: # This is expensive. Don't do it unless we need to. import salt.auth resolver = salt.auth.Resolver(self.opts) res = resolver.cli(self.opts['eauth']) if self.opts['mktoken'] and res: tok = resolver.token_cli( self.opts['eauth'], res ) if tok: low['token'] = tok.get('token', '') if not res: log.error('Authentication failed') return ret low.update(res) low['eauth'] = self.opts['eauth'] else: user = salt.utils.user.get_specific_user() if low['fun'] in ['state.orchestrate', 'state.orch', 'state.sls']: low['kwarg']['orchestration_jid'] = async_pub['jid'] # Run the runner! if self.opts.get('async', False): if self.opts.get('eauth'): async_pub = self.cmd_async(low) else: async_pub = self.asynchronous(self.opts['fun'], low, user=user, pub=async_pub) # by default: info will be not enough to be printed out ! log.warning( 'Running in asynchronous mode. Results of this execution may ' 'be collected by attaching to the master event bus or ' 'by examing the master job cache, if configured. ' 'This execution is running under tag %s', async_pub['tag'] ) return async_pub['jid'] # return the jid # otherwise run it in the main process if self.opts.get('eauth'): ret = self.cmd_sync(low) if isinstance(ret, dict) and set(ret) == {'data', 'outputter'}: outputter = ret['outputter'] ret = ret['data'] else: outputter = None display_output(ret, outputter, self.opts) else: ret = self._proc_function(self.opts['fun'], low, user, async_pub['tag'], async_pub['jid'], daemonize=False) except salt.exceptions.SaltException as exc: evt = salt.utils.event.get_event('master', opts=self.opts) evt.fire_event({'success': False, 'return': '{0}'.format(exc), 'retcode': 254, 'fun': self.opts['fun'], 'fun_args': fun_args, 'jid': self.jid}, tag='salt/run/{0}/ret'.format(self.jid)) # Attempt to grab documentation if 'fun' in low: ret = self.get_docs('{0}*'.format(low['fun'])) else: ret = None # If we didn't get docs returned then # return the `not availble` message. if not ret: ret = '{0}'.format(exc) if not self.opts.get('quiet', False): display_output(ret, 'nested', self.opts) else: # If we don't have any values in ret by now, that's a problem. # Otherwise, we shouldn't be overwriting the retcode. if not ret: ret = { 'retcode': salt.defaults.exitcodes.EX_SOFTWARE, } log.debug('Runner return: %s', ret) return ret
Actually execute specific runner :return:
def convert_all(cls, records): """Convert the list of bibrecs into one MARCXML. >>> from harvestingkit.bibrecord import BibRecordPackage >>> from harvestingkit.inspire_cds_package import Inspire2CDS >>> bibrecs = BibRecordPackage("inspire.xml") >>> bibrecs.parse() >>> xml = Inspire2CDS.convert_all(bibrecs.get_records()) :param records: list of BibRecord dicts :type records: list :returns: MARCXML as string """ out = ["<collection>"] for rec in records: conversion = cls(rec) out.append(conversion.convert()) out.append("</collection>") return "\n".join(out)
Convert the list of bibrecs into one MARCXML. >>> from harvestingkit.bibrecord import BibRecordPackage >>> from harvestingkit.inspire_cds_package import Inspire2CDS >>> bibrecs = BibRecordPackage("inspire.xml") >>> bibrecs.parse() >>> xml = Inspire2CDS.convert_all(bibrecs.get_records()) :param records: list of BibRecord dicts :type records: list :returns: MARCXML as string
def varify_user_lock(repository_path, session_token): """ Verify that a returning user has a valid token and their lock has not expired """ with open(cpjoin(repository_path, 'user_file'), 'r') as fd2: content = fd2.read() if len(content) == 0: return False try: res = json.loads(content) except ValueError: return False return res['session_token'] == session_token and int(time.time()) < int(res['expires']) return False
Verify that a returning user has a valid token and their lock has not expired
def is_pickle_file(abspath): """Parse file extension. - *.pickle: uncompressed, utf-8 encode pickle file - *.gz: compressed, utf-8 encode pickle file """ abspath = abspath.lower() fname, ext = os.path.splitext(abspath) if ext in [".pickle", ".pk", ".p"]: is_pickle = True elif ext == ".gz": is_pickle = False elif ext == ".tmp": return is_pickle_file(fname) else: raise PickleExtError( "'%s' is not a valid pickle file. " "extension has to be '.pickle' for uncompressed, '.gz' " "for compressed." % abspath) return is_pickle
Parse file extension. - *.pickle: uncompressed, utf-8 encode pickle file - *.gz: compressed, utf-8 encode pickle file
def cmd_log(self, reopen=False, rotate=False): """Allows managing of uWSGI log related stuff :param bool reopen: Reopen log file. Could be required after third party rotation. :param bool rotate: Trigger built-in log rotation. """ cmd = b'' if reopen: cmd += b'l' if rotate: cmd += b'L' return self.send_command(cmd)
Allows managing of uWSGI log related stuff :param bool reopen: Reopen log file. Could be required after third party rotation. :param bool rotate: Trigger built-in log rotation.
def _which_display(self, log: str, output: str) -> HTML: """ Determines if the log or lst should be returned as the results for the cell based on parsing the log looking for errors and the presence of lst output. :param log: str log from code submission :param output: None or str lst output if there was any :return: The correct results based on log and lst :rtype: str """ lines = re.split(r'[\n]\s*', log) i = 0 elog = [] for line in lines: i += 1 e = [] if line.startswith('ERROR'): logger.debug("In ERROR Condition") e = lines[(max(i - 15, 0)):(min(i + 16, len(lines)))] elog = elog + e tlog = '\n'.join(elog) logger.debug("elog count: " + str(len(elog))) logger.debug("tlog: " + str(tlog)) color_log = highlight(log, SASLogLexer(), HtmlFormatter(full=True, style=SASLogStyle, lineseparator="<br>")) # store the log for display in the showSASLog nbextension self.cachedlog = color_log # Are there errors in the log? if show the lines on each side of the error if len(elog) == 0 and len(output) > self.lst_len: # no error and LST output debug1 = 1 logger.debug("DEBUG1: " + str(debug1) + " no error and LST output ") return HTML(output) elif len(elog) == 0 and len(output) <= self.lst_len: # no error and no LST debug1 = 2 logger.debug("DEBUG1: " + str(debug1) + " no error and no LST") return HTML(color_log) elif len(elog) > 0 and len(output) <= self.lst_len: # error and no LST debug1 = 3 logger.debug("DEBUG1: " + str(debug1) + " error and no LST") return HTML(color_log) else: # errors and LST debug1 = 4 logger.debug("DEBUG1: " + str(debug1) + " errors and LST") return HTML(color_log + output)
Determines if the log or lst should be returned as the results for the cell based on parsing the log looking for errors and the presence of lst output. :param log: str log from code submission :param output: None or str lst output if there was any :return: The correct results based on log and lst :rtype: str
def hdf5_cache(filepath=None, parent=None, group=None, names=None, typed=False, hashed_key=False, **h5dcreate_kwargs): """HDF5 cache decorator. Parameters ---------- filepath : string, optional Path to HDF5 file. If None a temporary file name will be used. parent : string, optional Path to group within HDF5 file to use as parent. If None the root group will be used. group : string, optional Path to group within HDF5 file, relative to parent, to use as container for cached data. If None the name of the wrapped function will be used. names : sequence of strings, optional Name(s) of dataset(s). If None, default names will be 'f00', 'f01', etc. typed : bool, optional If True, arguments of different types will be cached separately. For example, f(3.0) and f(3) will be treated as distinct calls with distinct results. hashed_key : bool, optional If False (default) the key will not be hashed, which makes for readable cache group names. If True the key will be hashed, however note that on Python >= 3.3 the hash value will not be the same between sessions unless the environment variable PYTHONHASHSEED has been set to the same value. Returns ------- decorator : function Examples -------- Without any arguments, will cache using a temporary HDF5 file:: >>> import allel >>> @allel.util.hdf5_cache() ... def foo(n): ... print('executing foo') ... return np.arange(n) ... >>> foo(3) executing foo array([0, 1, 2]) >>> foo(3) array([0, 1, 2]) >>> foo.cache_filepath # doctest: +SKIP '/tmp/tmp_jwtwgjz' Supports multiple return values, including scalars, e.g.:: >>> @allel.util.hdf5_cache() ... def bar(n): ... print('executing bar') ... a = np.arange(n) ... return a, a**2, n**2 ... >>> bar(3) executing bar (array([0, 1, 2]), array([0, 1, 4]), 9) >>> bar(3) (array([0, 1, 2]), array([0, 1, 4]), 9) Names can also be specified for the datasets, e.g.:: >>> @allel.util.hdf5_cache(names=['z', 'x', 'y']) ... def baz(n): ... print('executing baz') ... a = np.arange(n) ... return a, a**2, n**2 ... >>> baz(3) executing baz (array([0, 1, 2]), array([0, 1, 4]), 9) >>> baz(3) (array([0, 1, 2]), array([0, 1, 4]), 9) """ # initialise HDF5 file path if filepath is None: import tempfile filepath = tempfile.mktemp(prefix='scikit_allel_', suffix='.h5') atexit.register(os.remove, filepath) # initialise defaults for dataset creation h5dcreate_kwargs.setdefault('chunks', True) def decorator(user_function): # setup the name for the cache container group if group is None: container = user_function.__name__ else: container = group def wrapper(*args, **kwargs): # load from cache or not no_cache = kwargs.pop('no_cache', False) # compute a key from the function arguments key = _make_key(args, kwargs, typed) if hashed_key: key = str(hash(key)) else: key = str(key).replace('/', '__slash__') return _hdf5_cache_act(filepath, parent, container, key, names, no_cache, user_function, args, kwargs, h5dcreate_kwargs) wrapper.cache_filepath = filepath return update_wrapper(wrapper, user_function) return decorator
HDF5 cache decorator. Parameters ---------- filepath : string, optional Path to HDF5 file. If None a temporary file name will be used. parent : string, optional Path to group within HDF5 file to use as parent. If None the root group will be used. group : string, optional Path to group within HDF5 file, relative to parent, to use as container for cached data. If None the name of the wrapped function will be used. names : sequence of strings, optional Name(s) of dataset(s). If None, default names will be 'f00', 'f01', etc. typed : bool, optional If True, arguments of different types will be cached separately. For example, f(3.0) and f(3) will be treated as distinct calls with distinct results. hashed_key : bool, optional If False (default) the key will not be hashed, which makes for readable cache group names. If True the key will be hashed, however note that on Python >= 3.3 the hash value will not be the same between sessions unless the environment variable PYTHONHASHSEED has been set to the same value. Returns ------- decorator : function Examples -------- Without any arguments, will cache using a temporary HDF5 file:: >>> import allel >>> @allel.util.hdf5_cache() ... def foo(n): ... print('executing foo') ... return np.arange(n) ... >>> foo(3) executing foo array([0, 1, 2]) >>> foo(3) array([0, 1, 2]) >>> foo.cache_filepath # doctest: +SKIP '/tmp/tmp_jwtwgjz' Supports multiple return values, including scalars, e.g.:: >>> @allel.util.hdf5_cache() ... def bar(n): ... print('executing bar') ... a = np.arange(n) ... return a, a**2, n**2 ... >>> bar(3) executing bar (array([0, 1, 2]), array([0, 1, 4]), 9) >>> bar(3) (array([0, 1, 2]), array([0, 1, 4]), 9) Names can also be specified for the datasets, e.g.:: >>> @allel.util.hdf5_cache(names=['z', 'x', 'y']) ... def baz(n): ... print('executing baz') ... a = np.arange(n) ... return a, a**2, n**2 ... >>> baz(3) executing baz (array([0, 1, 2]), array([0, 1, 4]), 9) >>> baz(3) (array([0, 1, 2]), array([0, 1, 4]), 9)
def _read(self, source): """ Reads and parses the config source :param file/str source: Config source URL (http/https), or string, file name, or file pointer. """ if source.startswith('http://') or source.startswith('https://'): source = url_content(source, cache_duration=self._cache_duration, from_cache_on_error=True) return super(RemoteConfig, self)._read(source)
Reads and parses the config source :param file/str source: Config source URL (http/https), or string, file name, or file pointer.
def _star_comparison(filter_value, tested_value): """ Tests a filter containing a joker """ if not is_string(tested_value): # Unhandled value type... return False parts = filter_value.split("*") i = 0 last_part = len(parts) - 1 idx = 0 for part in parts: # Find the part in the tested value idx = tested_value.find(part, idx) if idx == -1: # Part not found return False len_part = len(part) if i == 0 and len_part != 0 and idx != 0: # First part is not a star, but the tested value is not at # position 0 => Doesn't match return False if ( i == last_part and len_part != 0 and idx != len(tested_value) - len_part ): # Last tested part is not at the end of the sequence return False # Be sure to test the next part idx += len_part i += 1 # Whole test passed return True
Tests a filter containing a joker
def get_spaces(self): """ Return a flat list of the names for spaces in the organization. """ self.spaces = [] for resource in self._get_spaces()['resources']: self.spaces.append(resource['entity']['name']) return self.spaces
Return a flat list of the names for spaces in the organization.
def serialize(self, pid, record, links_factory=None): """Serialize a single record and persistent identifier. :param pid: Persistent identifier instance. :param record: Record instance. :param links_factory: Factory function for record links. """ return simpledc.tostring( self.transform_record(pid, record, links_factory))
Serialize a single record and persistent identifier. :param pid: Persistent identifier instance. :param record: Record instance. :param links_factory: Factory function for record links.
def _swap_on_miss(partition_result): """ Given a partition_dict result, if the partition missed, swap the before and after. """ before, item, after = partition_result return (before, item, after) if item else (after, item, before)
Given a partition_dict result, if the partition missed, swap the before and after.
def _symbol_extract(self, regex, plus = True, brackets=False): """Extracts a symbol or full symbol from the current line, optionally including the character under the cursor. :arg regex: the compiled regular expression to use for extraction. :arg plus: when true, the character under the cursor *is* included. :arg brackets: when true, matching pairs of brackets are first removed before the regex is run. """ charplus = self.pos[1] + (1 if plus else -1) consider = self.current_line[:charplus][::-1] #We want to remove matching pairs of brackets so that derived types #that have arrays still get intellisense. if brackets==True: #The string has already been reversed, just run through it. rightb = [] lastchar = None for i in range(len(consider)): if consider[i] == ")": rightb.append(i) elif consider[i] == "(" and len(rightb) > 0: lastchar = i rightb.pop() if lastchar is not None: consider = '%' + consider[lastchar+1:] rematch = regex.match(consider) if rematch is not None: return rematch.group("symbol")[::-1] else: return ""
Extracts a symbol or full symbol from the current line, optionally including the character under the cursor. :arg regex: the compiled regular expression to use for extraction. :arg plus: when true, the character under the cursor *is* included. :arg brackets: when true, matching pairs of brackets are first removed before the regex is run.
def compute(self): """Run the SuperSmoother.""" self._compute_primary_smooths() self._smooth_the_residuals() self._select_best_smooth_at_each_point() self._enhance_bass() self._smooth_best_span_estimates() self._apply_best_spans_to_primaries() self._smooth_interpolated_smooth() self._store_unsorted_results(self.smooth_result, numpy.zeros(len(self.smooth_result)))
Run the SuperSmoother.
def smooth_magseries_savgol(mags, windowsize, polyorder=2): '''This smooths the magseries with a Savitsky-Golay filter. Parameters ---------- mags : np.array The input mags/flux time-series to smooth. windowsize : int This is a odd integer containing the smoothing window size. polyorder : int This is an integer containing the polynomial degree order to use when generating the Savitsky-Golay filter. Returns ------- np.array The smoothed mag/flux time-series array. ''' smoothed = savgol_filter(mags, windowsize, polyorder) return smoothed
This smooths the magseries with a Savitsky-Golay filter. Parameters ---------- mags : np.array The input mags/flux time-series to smooth. windowsize : int This is a odd integer containing the smoothing window size. polyorder : int This is an integer containing the polynomial degree order to use when generating the Savitsky-Golay filter. Returns ------- np.array The smoothed mag/flux time-series array.
def lxc_path(cls, *join_paths): """Returns the LXC path (default on ubuntu is /var/lib/lxc)""" response = subwrap.run(['lxc-ls', '-d']) output = response.std_out lxc_path = output.splitlines()[0] lxc_path = lxc_path.strip() return os.path.join(lxc_path, *join_paths)
Returns the LXC path (default on ubuntu is /var/lib/lxc)
def get_member_named(self, name): """Returns the first member found that matches the name provided. The name can have an optional discriminator argument, e.g. "Jake#0001" or "Jake" will both do the lookup. However the former will give a more precise result. Note that the discriminator must have all 4 digits for this to work. If a nickname is passed, then it is looked up via the nickname. Note however, that a nickname + discriminator combo will not lookup the nickname but rather the username + discriminator combo due to nickname + discriminator not being unique. If no member is found, ``None`` is returned. Parameters ----------- name: :class:`str` The name of the member to lookup with an optional discriminator. Returns -------- :class:`Member` The member in this guild with the associated name. If not found then ``None`` is returned. """ result = None members = self.members if len(name) > 5 and name[-5] == '#': # The 5 length is checking to see if #0000 is in the string, # as a#0000 has a length of 6, the minimum for a potential # discriminator lookup. potential_discriminator = name[-4:] # do the actual lookup and return if found # if it isn't found then we'll do a full name lookup below. result = utils.get(members, name=name[:-5], discriminator=potential_discriminator) if result is not None: return result def pred(m): return m.nick == name or m.name == name return utils.find(pred, members)
Returns the first member found that matches the name provided. The name can have an optional discriminator argument, e.g. "Jake#0001" or "Jake" will both do the lookup. However the former will give a more precise result. Note that the discriminator must have all 4 digits for this to work. If a nickname is passed, then it is looked up via the nickname. Note however, that a nickname + discriminator combo will not lookup the nickname but rather the username + discriminator combo due to nickname + discriminator not being unique. If no member is found, ``None`` is returned. Parameters ----------- name: :class:`str` The name of the member to lookup with an optional discriminator. Returns -------- :class:`Member` The member in this guild with the associated name. If not found then ``None`` is returned.
def _css_helper(self): """ Add CSS links for the current page and for the plugins """ entries = [entry for entry in self._plugin_manager.call_hook("css") if entry is not None] # Load javascript for the current page entries += self._get_ctx()["css"] entries = ["<link href='" + entry + "' rel='stylesheet'>" for entry in entries] return "\n".join(entries)
Add CSS links for the current page and for the plugins
def get_argparser(): """ Get the command line argument parser. """ parser = argparse.ArgumentParser("twarc") parser.add_argument('command', choices=commands) parser.add_argument('query', nargs='?', default=None) parser.add_argument("--log", dest="log", default="twarc.log", help="log file") parser.add_argument("--consumer_key", default=None, help="Twitter API consumer key") parser.add_argument("--consumer_secret", default=None, help="Twitter API consumer secret") parser.add_argument("--access_token", default=None, help="Twitter API access key") parser.add_argument("--access_token_secret", default=None, help="Twitter API access token secret") parser.add_argument('--config', help="Config file containing Twitter keys and secrets") parser.add_argument('--profile', help="Name of a profile in your configuration file") parser.add_argument('--warnings', action='store_true', help="Include warning messages in output") parser.add_argument("--connection_errors", type=int, default="0", help="Number of connection errors before giving up") parser.add_argument("--http_errors", type=int, default="0", help="Number of http errors before giving up") parser.add_argument("--max_id", dest="max_id", help="maximum tweet id to search for") parser.add_argument("--since_id", dest="since_id", help="smallest id to search for") parser.add_argument("--result_type", dest="result_type", choices=["mixed", "recent", "popular"], default="recent", help="search result type") parser.add_argument("--lang", dest="lang", help="limit to ISO 639-1 language code"), parser.add_argument("--geocode", dest="geocode", help="limit by latitude,longitude,radius") parser.add_argument("--locations", dest="locations", help="limit filter stream to location(s)") parser.add_argument("--follow", dest="follow", help="limit filter to tweets from given user id(s)") parser.add_argument("--recursive", dest="recursive", action="store_true", help="also fetch replies to replies") parser.add_argument("--tweet_mode", action="store", default="extended", dest="tweet_mode", choices=["compat", "extended"], help="set tweet mode") parser.add_argument("--protected", dest="protected", action="store_true", help="include protected tweets") parser.add_argument("--output", action="store", default=None, dest="output", help="write output to file path") parser.add_argument("--format", action="store", default="json", dest="format", choices=["json", "csv", "csv-excel"], help="set output format") parser.add_argument("--split", action="store", type=int, default=0, help="used with --output to split into numbered files") parser.add_argument("--skip_key_validation", action="store_true", help="skip checking keys are valid on startup") return parser
Get the command line argument parser.
def set_window_class(self, window, name, class_): """ Change the window's classname and or class. :param name: The new class name. If ``None``, no change. :param class_: The new class. If ``None``, no change. """ _libxdo.xdo_set_window_class(self._xdo, window, name, class_)
Change the window's classname and or class. :param name: The new class name. If ``None``, no change. :param class_: The new class. If ``None``, no change.
def _prepare_args(log_likelihood_fn, state, log_likelihood=None, description='log_likelihood'): """Processes input args to meet list-like assumptions.""" state_parts = list(state) if mcmc_util.is_list_like(state) else [state] state_parts = [tf.convert_to_tensor(s, name='current_state') for s in state_parts] log_likelihood = _maybe_call_fn( log_likelihood_fn, state_parts, log_likelihood, description) return [state_parts, log_likelihood]
Processes input args to meet list-like assumptions.
def yieldOutput(self): """ Generate the text output for the table. @rtype: generator of str @return: Text output. """ width = self.__width if width: num_cols = len(width) fmt = ['%%%ds' % -w for w in width] if width[-1] > 0: fmt[-1] = '%s' fmt = self.__sep.join(fmt) for row in self.__cols: row.extend( [''] * (num_cols - len(row)) ) yield fmt % tuple(row)
Generate the text output for the table. @rtype: generator of str @return: Text output.
def execute_lines(self, lines): """Execute lines and give focus to shell""" self.shell.execute_lines(to_text_string(lines)) self.shell.setFocus()
Execute lines and give focus to shell
def to_glyphs_guidelines(self, ufo_obj, glyphs_obj): """Set guidelines.""" if not ufo_obj.guidelines: return for guideline in ufo_obj.guidelines: new_guideline = self.glyphs_module.GSGuideLine() name = guideline.name # Locked if name is not None and name.endswith(LOCKED_NAME_SUFFIX): name = name[: -len(LOCKED_NAME_SUFFIX)] new_guideline.locked = True if guideline.color: name = (name or "") + COLOR_NAME_SUFFIX % str(guideline.color) if guideline.identifier: name = (name or "") + IDENTIFIER_NAME_SUFFIX % guideline.identifier new_guideline.name = name new_guideline.position = Point(guideline.x or 0, guideline.y or 0) if guideline.angle is not None: new_guideline.angle = guideline.angle % 360 elif _is_vertical(guideline.x, guideline.y, None): new_guideline.angle = 90 glyphs_obj.guides.append(new_guideline)
Set guidelines.
def notify(self, msgtype, method, params): """Handle an incoming notify request.""" self.dispatch.call(method, params)
Handle an incoming notify request.
def _send_delete_request(self, path, headers): """ Sends the DELETE request to the Route53 endpoint. :param str path: The path to tack on to the endpoint URL for the query. :param dict headers: A dict of headers to send with the request. :rtype: str :returns: The body of the response. """ r = requests.delete(self.endpoint + path, headers=headers) return r.text
Sends the DELETE request to the Route53 endpoint. :param str path: The path to tack on to the endpoint URL for the query. :param dict headers: A dict of headers to send with the request. :rtype: str :returns: The body of the response.
def format_value(value): """ Integers are numeric values that do not include a decimal and are followed by a trailing i when inserted (e.g. 1i, 345i, 2015i, -10i). Note that all values must have a trailing i. If they do not they will be written as floats. Floats are numeric values that are not followed by a trailing i. (e.g. 1, 1.0, -3.14, 6.0e5, 10). Boolean values indicate true or false. Valid boolean strings for line protocol are (t, T, true, True, TRUE, f, F, false, False and FALSE). Strings are text values. All string field values must be surrounded in double-quotes ". If the string contains a double-quote, the double-quote must be escaped with a backslash, e.g. \". """ if isinstance(value, basestring): value = value.replace('"', '\"') value = u'"{0}"'.format(value) elif isinstance(value, bool): value = str(value) elif isinstance(value, int): value = "{0}i".format(value) elif isinstance(value, float): value = str(value) return value
Integers are numeric values that do not include a decimal and are followed by a trailing i when inserted (e.g. 1i, 345i, 2015i, -10i). Note that all values must have a trailing i. If they do not they will be written as floats. Floats are numeric values that are not followed by a trailing i. (e.g. 1, 1.0, -3.14, 6.0e5, 10). Boolean values indicate true or false. Valid boolean strings for line protocol are (t, T, true, True, TRUE, f, F, false, False and FALSE). Strings are text values. All string field values must be surrounded in double-quotes ". If the string contains a double-quote, the double-quote must be escaped with a backslash, e.g. \".
def create_ustar_header(self, info, encoding, errors): """Return the object as a ustar header block. """ info["magic"] = POSIX_MAGIC if len(info["linkname"]) > LENGTH_LINK: raise ValueError("linkname is too long") if len(info["name"]) > LENGTH_NAME: info["prefix"], info["name"] = self._posix_split_name(info["name"]) return self._create_header(info, USTAR_FORMAT, encoding, errors)
Return the object as a ustar header block.
def visit_BoolOp(self, node): """ Merge BoolOp operand type. BoolOp are "and" and "or" and may return any of these results so all operands should have the combinable type. """ # Visit subnodes self.generic_visit(node) # Merge all operands types. [self.combine(node, value) for value in node.values]
Merge BoolOp operand type. BoolOp are "and" and "or" and may return any of these results so all operands should have the combinable type.
def send(self): """ Send the message to each user on the queryset. Create SentDrip for each user that gets a message. Returns count of created SentDrips. """ if not self.from_email: self.from_email = getattr(settings, 'DRIP_FROM_EMAIL', settings.DEFAULT_FROM_EMAIL) MessageClass = message_class_for(self.drip_model.message_class) count = 0 for user in self.get_queryset(): message_instance = MessageClass(self, user) try: result = message_instance.message.send() if result: SentDrip.objects.create( drip=self.drip_model, user=user, from_email=self.from_email, from_email_name=self.from_email_name, subject=message_instance.subject, body=message_instance.body ) count += 1 except Exception as e: logging.error("Failed to send drip %s to user %s: %s" % (self.drip_model.id, user, e)) return count
Send the message to each user on the queryset. Create SentDrip for each user that gets a message. Returns count of created SentDrips.
def gpg_fetch_key( key_url, key_id=None, config_dir=None ): """ Fetch a GPG public key from the given URL. Supports anything urllib2 supports. If the URL has no scheme, then assume it's a PGP key server, and use GPG to go get it. The key is not accepted into any keyrings. Return the key data on success. If key_id is given, verify the key matches. Return None on error, or on failure to carry out any key verification """ dat = None from_blockstack = False # make sure it's valid try: urlparse.urlparse(key_url) except: log.error("Invalid URL") return None if "://" in key_url and not key_url.lower().startswith("iks://"): opener = None key_data = None # handle blockstack:// URLs if key_url.startswith("blockstack://"): blockstack_opener = BlockstackHandler( config_path=os.path.join(config_dir, blockstack_client.CONFIG_FILENAME) ) opener = urllib2.build_opener( blockstack_opener ) from_blockstack = True elif key_url.lower().startswith("http://") or key_url.lower().startswith("https://"): # fetch, but at least try not to look like a bot opener = urllib2.build_opener() opener.addheaders = [('User-agent', 'Mozilla/5.0')] else: # defaults opener = urllib2.build_opener() try: f = opener.open( key_url ) key_data_str = f.read() key_data = None if from_blockstack: # expect: {'key name': 'PEM string'} key_data_dict = json.loads(key_data_str) assert len(key_data_dict) == 1, "Got multiple keys" key_data = str(key_data_dict[key_data_dict.keys()[0]]) else: # expect: PEM string key_data = key_data_str f.close() except Exception, e: log.exception(e) if key_id is not None: log.error("Failed to fetch key '%s' from '%s'" % (key_id, key_url)) else: log.error("Failed to fetch key from '%s'" % key_url) return None # verify, if we have the ID. # if we don't have the key ID, then we must be fetching from blockstack # (since then the data will have already been verified by the protocol, using locally-hosted trusted information) if not from_blockstack and key_id is None: log.error( "No key ID given for key located at %s" % key_url ) return None if key_id is not None: rc = gpg_verify_key( key_id, key_data, config_dir=config_dir ) if not rc: log.error("Failed to verify key %s" % key_id) return None dat = key_data else: # iks protocol, fetch from keyserver key_server = key_url if '://' in key_server: key_server = urlparse.urlparse(key_server).netloc dat = gpg_download_key( key_id, key_server, config_dir=config_dir ) assert dat is not None and len(dat) > 0, "BUG: no key data received for '%s' from '%s'" % (key_id, key_url) return dat
Fetch a GPG public key from the given URL. Supports anything urllib2 supports. If the URL has no scheme, then assume it's a PGP key server, and use GPG to go get it. The key is not accepted into any keyrings. Return the key data on success. If key_id is given, verify the key matches. Return None on error, or on failure to carry out any key verification
def extract_arguments(text): """ Returns the argument after the command. Examples: extract_arguments("/get name"): 'name' extract_arguments("/get"): '' extract_arguments("/get@botName name"): 'name' :param text: String to extract the arguments from a command :return: the arguments if `text` is a command (according to is_command), else None. """ regexp = re.compile("/\w*(@\w*)*\s*([\s\S]*)",re.IGNORECASE) result = regexp.match(text) return result.group(2) if is_command(text) else None
Returns the argument after the command. Examples: extract_arguments("/get name"): 'name' extract_arguments("/get"): '' extract_arguments("/get@botName name"): 'name' :param text: String to extract the arguments from a command :return: the arguments if `text` is a command (according to is_command), else None.
def rotate_scale(im, angle, scale, borderValue=0, interp=cv2.INTER_CUBIC): """Rotates and scales the image Parameters ---------- im: 2d array The image angle: number The angle, in radians, to rotate scale: positive number The scale factor borderValue: number, default 0 The value for the pixels outside the border (default 0) Returns ------- im: 2d array the rotated and scaled image Notes ----- The output image has the same size as the input. Therefore the image may be cropped in the process. """ im = np.asarray(im, dtype=np.float32) rows, cols = im.shape M = cv2.getRotationMatrix2D( (cols / 2, rows / 2), -angle * 180 / np.pi, 1 / scale) im = cv2.warpAffine(im, M, (cols, rows), borderMode=cv2.BORDER_CONSTANT, flags=interp, borderValue=borderValue) # REPLICATE return im
Rotates and scales the image Parameters ---------- im: 2d array The image angle: number The angle, in radians, to rotate scale: positive number The scale factor borderValue: number, default 0 The value for the pixels outside the border (default 0) Returns ------- im: 2d array the rotated and scaled image Notes ----- The output image has the same size as the input. Therefore the image may be cropped in the process.
def get_packages(self, show): """ Return list of Distributions filtered by active status or all @param show: Type of package(s) to show; active, non-active or all @type show: string: "active", "non-active", "all" @returns: list of pkg_resources Distribution objects """ if show == 'nonactive' or show == "all": all_packages = [] for package in self.environment: #There may be multiple versions of same packages for i in range(len(self.environment[package])): if self.environment[package][i]: all_packages.append(self.environment[package][i]) return all_packages else: # Only activated packages return self.working_set
Return list of Distributions filtered by active status or all @param show: Type of package(s) to show; active, non-active or all @type show: string: "active", "non-active", "all" @returns: list of pkg_resources Distribution objects
def phase_estimation(U: np.ndarray, accuracy: int, reg_offset: int = 0) -> Program: """ Generate a circuit for quantum phase estimation. :param U: A unitary matrix. :param accuracy: Number of bits of accuracy desired. :param reg_offset: Where to start writing measurements (default 0). :return: A Quil program to perform phase estimation. """ assert isinstance(accuracy, int) rows, cols = U.shape m = int(log2(rows)) output_qubits = range(0, accuracy) U_qubits = range(accuracy, accuracy + m) p = Program() ro = p.declare('ro', 'BIT', len(output_qubits)) # Hadamard initialization for i in output_qubits: p.inst(H(i)) # Controlled unitaries for i in output_qubits: if i > 0: U = np.dot(U, U) cU = controlled(U) name = "CONTROLLED-U{0}".format(2 ** i) # define the gate p.defgate(name, cU) # apply it p.inst((name, i) + tuple(U_qubits)) # Compute the QFT p = p + inverse_qft(output_qubits) # Perform the measurements for i in output_qubits: p.measure(i, ro[reg_offset + i]) return p
Generate a circuit for quantum phase estimation. :param U: A unitary matrix. :param accuracy: Number of bits of accuracy desired. :param reg_offset: Where to start writing measurements (default 0). :return: A Quil program to perform phase estimation.
def _deshuffle_field(self, *args): """ Return to original ordering """ ip = self._invpermutation fields = [] for arg in args: fields.append( arg[ip] ) if len(fields) == 1: return fields[0] else: return fields
Return to original ordering
def _run_atexit(): '''Hook frameworks must invoke this after the main hook body has successfully completed. Do not invoke it if the hook fails.''' global _atexit for callback, args, kwargs in reversed(_atexit): callback(*args, **kwargs) del _atexit[:]
Hook frameworks must invoke this after the main hook body has successfully completed. Do not invoke it if the hook fails.
def create(self, model_name): """Create a model. Args: model_name: the short name of the model, such as "iris". Returns: If successful, returns informaiton of the model, such as {u'regions': [u'us-central1'], u'name': u'projects/myproject/models/mymodel'} Raises: If the model creation failed. """ body = {'name': model_name} parent = 'projects/' + self._project_id # Model creation is instant. If anything goes wrong, Exception will be thrown. return self._api.projects().models().create(body=body, parent=parent).execute()
Create a model. Args: model_name: the short name of the model, such as "iris". Returns: If successful, returns informaiton of the model, such as {u'regions': [u'us-central1'], u'name': u'projects/myproject/models/mymodel'} Raises: If the model creation failed.
async def has_started(self): """ Whether the handler has completed all start up processes such as establishing the connection, session, link and authentication, and is not ready to process messages. **This function is now deprecated and will be removed in v2.0+.** :rtype: bool """ # pylint: disable=protected-access timeout = False auth_in_progress = False if self._handler._connection.cbs: timeout, auth_in_progress = await self._handler._auth.handle_token_async() if timeout: raise EventHubError("Authorization timeout.") if auth_in_progress: return False if not await self._handler._client_ready_async(): return False return True
Whether the handler has completed all start up processes such as establishing the connection, session, link and authentication, and is not ready to process messages. **This function is now deprecated and will be removed in v2.0+.** :rtype: bool
def is_less_than(self, other): """ Ensures :attr:`subject` is less than *other*. """ try: unittest_case.assertTrue(self._subject < other) except self._catch as err: raise self._error_factory(_format("Expected {} to be less than {}", self._subject, other)) return ChainInspector(self._subject)
Ensures :attr:`subject` is less than *other*.
def _parse_entry(self, dom): """Sigh....""" entry = {} for tag in self._cap_tags: # we need to handle the geocodes a bit differently if tag == 'cap:geocode': try: geotypes = [] # FIXME: this will parse VTEC and add it to the feed as well, that's both a feature and a bug for item in dom.getElementsByTagName('valueName'): geotypes.append(str(item.firstChild.data)) n = 0 for geotype in geotypes: try: entry[geotype] = str(dom.getElementsByTagName('value')[n].firstChild.data).split(' ') except AttributeError: pass n = n + 1 finally: try: entry['samecodes'] = [x for x in entry['FIPS6'] if str(x).isdigit()] # handle bad nws data except Exception: entry['samecodes'] = [] else: try: entry[tag] = dom.getElementsByTagName(tag)[0].firstChild.data except AttributeError: entry[tag] = '' return entry
Sigh....
def list_tasks(collector): """List the available_tasks""" print("Usage: aws_syncr <environment> <task>") print("") print("Available environments to choose from are") print("-----------------------------------------") print("") for environment in os.listdir(collector.configuration_folder): location = os.path.join(collector.configuration_folder, environment) if os.path.isdir(location) and not environment.startswith("."): print("\t{0}".format(environment)) print("") print("Available tasks to choose from are:") print("-----------------------------------") print("") keygetter = lambda item: item[1].label tasks = sorted(available_actions.items(), key=keygetter) sorted_tasks = sorted(list(tasks), key=lambda item: len(item[0])) max_length = max(len(name) for name, _ in sorted_tasks) for key, task in sorted_tasks: desc = dedent(task.__doc__ or "").strip().split('\n')[0] print("\t{0}{1} :-: {2}".format(" " * (max_length-len(key)), key, desc)) print("")
List the available_tasks
def fix_windows_stdout_stderr(): """ Processes can't write to stdout/stderr on frozen windows apps because they do not exist here if process tries it anyway we get a nasty dialog window popping up, so we redirect the streams to a dummy see https://github.com/jopohl/urh/issues/370 """ if hasattr(sys, "frozen") and sys.platform == "win32": try: sys.stdout.write("\n") sys.stdout.flush() except: class DummyStream(object): def __init__(self): pass def write(self, data): pass def read(self, data): pass def flush(self): pass def close(self): pass sys.stdout, sys.stderr, sys.stdin = DummyStream(), DummyStream(), DummyStream() sys.__stdout__, sys.__stderr__, sys.__stdin__ = DummyStream(), DummyStream(), DummyStream()
Processes can't write to stdout/stderr on frozen windows apps because they do not exist here if process tries it anyway we get a nasty dialog window popping up, so we redirect the streams to a dummy see https://github.com/jopohl/urh/issues/370
def file_hash(fname): """ Calculate the SHA256 hash of a given file. Useful for checking if a file has changed or been corrupted. Parameters ---------- fname : str The name of the file. Returns ------- hash : str The hash of the file. Examples -------- >>> fname = "test-file-for-hash.txt" >>> with open(fname, "w") as f: ... __ = f.write("content of the file") >>> print(file_hash(fname)) 0fc74468e6a9a829f103d069aeb2bb4f8646bad58bf146bb0e3379b759ec4a00 >>> import os >>> os.remove(fname) """ # Calculate the hash in chunks to avoid overloading the memory chunksize = 65536 hasher = hashlib.sha256() with open(fname, "rb") as fin: buff = fin.read(chunksize) while buff: hasher.update(buff) buff = fin.read(chunksize) return hasher.hexdigest()
Calculate the SHA256 hash of a given file. Useful for checking if a file has changed or been corrupted. Parameters ---------- fname : str The name of the file. Returns ------- hash : str The hash of the file. Examples -------- >>> fname = "test-file-for-hash.txt" >>> with open(fname, "w") as f: ... __ = f.write("content of the file") >>> print(file_hash(fname)) 0fc74468e6a9a829f103d069aeb2bb4f8646bad58bf146bb0e3379b759ec4a00 >>> import os >>> os.remove(fname)
def new_multidigraph(self, name, data=None, **attr): """Return a new instance of type MultiDiGraph, initialized with the given data if provided. :arg name: a name for the graph :arg data: dictionary or NetworkX graph object providing initial state """ self._init_graph(name, 'MultiDiGraph') mdg = MultiDiGraph(self, name, data, **attr) self._graph_objs[name] = mdg return mdg
Return a new instance of type MultiDiGraph, initialized with the given data if provided. :arg name: a name for the graph :arg data: dictionary or NetworkX graph object providing initial state
def _set_raw_return(self, sep): """Set the output raw return section :param sep: the separator of current style """ raw = '' if self.dst.style['out'] == 'numpydoc': raw += '\n' spaces = ' ' * 4 with_space = lambda s: '\n'.join([self.docs['out']['spaces'] + spaces + l.lstrip() if i > 0 else l for i, l in enumerate(s.splitlines())]) raw += self.dst.numpydoc.get_key_section_header('return', self.docs['out']['spaces']) if self.docs['out']['rtype']: rtype = self.docs['out']['rtype'] else: rtype = 'type' # case of several returns if type(self.docs['out']['return']) is list: for ret_elem in self.docs['out']['return']: # if tuple (name, desc, rtype) else string desc if type(ret_elem) is tuple and len(ret_elem) == 3: rtype = ret_elem[2] if rtype is None: rtype = '' raw += self.docs['out']['spaces'] if ret_elem[0]: raw += ret_elem[0] + ' : ' raw += rtype + '\n' + self.docs['out']['spaces'] + spaces + with_space(ret_elem[1]).strip() + '\n' else: # There can be a problem raw += self.docs['out']['spaces'] + rtype + '\n' raw += self.docs['out']['spaces'] + spaces + with_space(str(ret_elem)).strip() + '\n' # case of a unique return elif self.docs['out']['return'] is not None: raw += self.docs['out']['spaces'] + rtype raw += '\n' + self.docs['out']['spaces'] + spaces + with_space(self.docs['out']['return']).strip() + '\n' elif self.dst.style['out'] == 'google': raw += '\n' spaces = ' ' * 2 with_space = lambda s: '\n'.join([self.docs['out']['spaces'] + spaces +\ l.lstrip() if i > 0 else\ l for i, l in enumerate(s.splitlines())]) raw += self.dst.googledoc.get_key_section_header('return', self.docs['out']['spaces']) if self.docs['out']['rtype']: rtype = self.docs['out']['rtype'] else: rtype = None # case of several returns if type(self.docs['out']['return']) is list: for ret_elem in self.docs['out']['return']: # if tuple (name=None, desc, rtype) else string desc if type(ret_elem) is tuple and len(ret_elem) == 3: rtype = ret_elem[2] if rtype is None: rtype = '' raw += self.docs['out']['spaces'] + spaces raw += rtype + ': ' + with_space(ret_elem[1]).strip() + '\n' else: # There can be a problem if rtype: raw += self.docs['out']['spaces'] + spaces + rtype + ': ' raw += with_space(str(ret_elem)).strip() + '\n' else: raw += self.docs['out']['spaces'] + spaces + with_space(str(ret_elem)).strip() + '\n' # case of a unique return elif self.docs['out']['return'] is not None: if rtype: raw += self.docs['out']['spaces'] + spaces + rtype + ': ' raw += with_space(self.docs['out']['return']).strip() + '\n' else: raw += self.docs['out']['spaces'] + spaces + with_space(self.docs['out']['return']).strip() + '\n' elif self.dst.style['out'] == 'groups': pass else: with_space = lambda s: '\n'.join([self.docs['out']['spaces'] + l if i > 0 else l for i, l in enumerate(s.splitlines())]) if self.docs['out']['return']: if not self.docs['out']['params']: raw += '\n' raw += self.docs['out']['spaces'] + self.dst.get_key('return', 'out') + sep + with_space(self.docs['out']['return'].rstrip()).strip() + '\n' if self.docs['out']['rtype']: if not self.docs['out']['params']: raw += '\n' raw += self.docs['out']['spaces'] + self.dst.get_key('rtype', 'out') + sep + self.docs['out']['rtype'].rstrip() + '\n' return raw
Set the output raw return section :param sep: the separator of current style
def save(self, obj, run_id): """ Save a workflow obj - instance of a workflow to save run_id - unique id to give the run """ id_code = self.generate_save_identifier(obj, run_id) self.store.save(obj, id_code)
Save a workflow obj - instance of a workflow to save run_id - unique id to give the run
def similar_movies(self, **kwargs): """ Get the similar movies for a specific movie id. Args: page: (optional) Minimum value of 1. Expected value is an integer. language: (optional) ISO 639-1 code. append_to_response: (optional) Comma separated, any movie method. Returns: A dict representation of the JSON returned from the API. """ path = self._get_id_path('similar_movies') response = self._GET(path, kwargs) self._set_attrs_to_values(response) return response
Get the similar movies for a specific movie id. Args: page: (optional) Minimum value of 1. Expected value is an integer. language: (optional) ISO 639-1 code. append_to_response: (optional) Comma separated, any movie method. Returns: A dict representation of the JSON returned from the API.
def create_from_root(self, root_source): """Return a populated Object Root from dictionnary datas """ root_dto = ObjectRoot() root_dto.configuration = root_source.configuration root_dto.versions = [Version(x) for x in root_source.versions.values()] for version in sorted(root_source.versions.values()): hydrator = Hydrator(version, root_source.versions, root_source.versions[version.name].types) for method in version.methods.values(): hydrator.hydrate_method(root_dto, root_source, method) for type in version.types.values(): hydrator.hydrate_type(root_dto, root_source, type) self.define_changes_status(root_dto) return root_dto
Return a populated Object Root from dictionnary datas
def create(self, request): """ Read the GeoJSON feature collection from the request body and create new objects in the database. """ if self.readonly: return HTTPMethodNotAllowed(headers={'Allow': 'GET, HEAD'}) collection = loads(request.body, object_hook=GeoJSON.to_instance) if not isinstance(collection, FeatureCollection): return HTTPBadRequest() session = self.Session() objects = [] for feature in collection.features: create = False obj = None if hasattr(feature, 'id') and feature.id is not None: obj = session.query(self.mapped_class).get(feature.id) if self.before_create is not None: self.before_create(request, feature, obj) if obj is None: obj = self.mapped_class(feature) create = True else: obj.__update__(feature) if create: session.add(obj) objects.append(obj) session.flush() collection = FeatureCollection(objects) if len(objects) > 0 else None request.response.status_int = 201 return collection
Read the GeoJSON feature collection from the request body and create new objects in the database.
def is_valid(self): """Return True if all widget contents are valid""" for lineedit in self.lineedits: if lineedit in self.validate_data and lineedit.isEnabled(): validator, invalid_msg = self.validate_data[lineedit] text = to_text_string(lineedit.text()) if not validator(text): QMessageBox.critical(self, self.get_name(), "%s:<br><b>%s</b>" % (invalid_msg, text), QMessageBox.Ok) return False return True
Return True if all widget contents are valid
def guess_codec(file, errors="strict", require_char=False): """Look at file contents and guess its correct encoding. File must be open in binary mode and positioned at offset 0. If BOM record is present then it is assumed to be UTF-8 or UTF-16 encoded file. GEDCOM header is searched for CHAR record and encoding name is extracted from it, if BOM record is present then CHAR record must match BOM-defined encoding. :param file: File object, must be open in binary mode. :param str errors: Controls error handling behavior during string decoding, accepts same values as standard `codecs.decode` method. :param bool require_char: If True then exception is thrown if CHAR record is not found in a header, if False and CHAR is not in the header then codec determined from BOM or "gedcom" is returned. :returns: Tuple (codec_name, bom_size) :raises: :py:class:`CodecError` when codec name in file is unknown or when codec name in file contradicts codec determined from BOM. :raises: :py:class:`UnicodeDecodeError` when codec fails to decode input lines and `errors` is set to "strict" (default). """ # mapping of gedcom character set specifiers to Python encoding names gedcom_char_to_codec = { 'ansel': 'gedcom', } # check BOM first bom_codec = check_bom(file) bom_size = file.tell() codec = bom_codec or 'gedcom' # scan header until CHAR or end of header while True: # this stops at '\n' line = file.readline() if not line: raise IOError("Unexpected EOF while reading GEDCOM header") # do not decode bytes to strings here, reason is that some # stupid apps split CONC record at byte level (in middle of # of multi-byte characters). This implies that we can only # work with encodings that have ASCII as single-byte subset. line = line.lstrip().rstrip(b"\r\n") words = line.split() if len(words) >= 2 and words[0] == b"0" and words[1] != b"HEAD": # past header but have not seen CHAR if require_char: raise CodecError("GEDCOM header does not have CHAR record") else: break elif len(words) >= 3 and words[0] == b"1" and words[1] == b"CHAR": try: encoding = words[2].decode(codec, errors) encoding = gedcom_char_to_codec.get(encoding.lower(), encoding.lower()) new_codec = codecs.lookup(encoding).name except LookupError: raise CodecError("Unknown codec name {0}".format(encoding)) if bom_codec is None: codec = new_codec elif new_codec != bom_codec: raise CodecError("CHAR codec {0} is different from BOM " "codec {1}".format(new_codec, bom_codec)) break return codec, bom_size
Look at file contents and guess its correct encoding. File must be open in binary mode and positioned at offset 0. If BOM record is present then it is assumed to be UTF-8 or UTF-16 encoded file. GEDCOM header is searched for CHAR record and encoding name is extracted from it, if BOM record is present then CHAR record must match BOM-defined encoding. :param file: File object, must be open in binary mode. :param str errors: Controls error handling behavior during string decoding, accepts same values as standard `codecs.decode` method. :param bool require_char: If True then exception is thrown if CHAR record is not found in a header, if False and CHAR is not in the header then codec determined from BOM or "gedcom" is returned. :returns: Tuple (codec_name, bom_size) :raises: :py:class:`CodecError` when codec name in file is unknown or when codec name in file contradicts codec determined from BOM. :raises: :py:class:`UnicodeDecodeError` when codec fails to decode input lines and `errors` is set to "strict" (default).
def _percentile(N, percent, key=lambda x:x): """ Find the percentile of a list of values. @parameter N - is a list of values. Note N MUST BE already sorted. @parameter percent - a float value from 0.0 to 1.0. @parameter key - optional key function to compute value from each element of N. @return - the percentile of the values """ if not N: return None k = (len(N)-1) * percent f = math.floor(k) c = math.ceil(k) if f == c: return key(N[int(k)]) d0 = key(N[int(f)]) * (c-k) d1 = key(N[int(c)]) * (k-f) return d0+d1
Find the percentile of a list of values. @parameter N - is a list of values. Note N MUST BE already sorted. @parameter percent - a float value from 0.0 to 1.0. @parameter key - optional key function to compute value from each element of N. @return - the percentile of the values
def argument(self) -> bool: """Parse statement argument. Return ``True`` if the argument is followed by block of substatements. """ next = self.peek() if next == "'": quoted = True self.sq_argument() elif next == '"': quoted = True self.dq_argument() elif self._arg == "": quoted = False self.unq_argument() else: raise UnexpectedInput(self, "single or double quote") self.opt_separator() next = self.peek() if next == ";": return False if next == "{": return True elif quoted and next == "+": self.offset += 1 self.opt_separator() return self.argument() else: raise UnexpectedInput(self, "';', '{'" + (" or '+'" if quoted else ""))
Parse statement argument. Return ``True`` if the argument is followed by block of substatements.
def load_bernoulli_mnist_dataset(directory, split_name): """Returns Hugo Larochelle's binary static MNIST tf.data.Dataset.""" amat_file = download(directory, FILE_TEMPLATE.format(split=split_name)) dataset = tf.data.TextLineDataset(amat_file) str_to_arr = lambda string: np.array([c == b"1" for c in string.split()]) def _parser(s): booltensor = tf.compat.v1.py_func(str_to_arr, [s], tf.bool) reshaped = tf.reshape(booltensor, [28, 28, 1]) return tf.cast(reshaped, dtype=tf.float32), tf.constant(0, tf.int32) return dataset.map(_parser)
Returns Hugo Larochelle's binary static MNIST tf.data.Dataset.
def lowpass(ts, cutoff_hz, order=3): """forward-backward butterworth low-pass filter""" orig_ndim = ts.ndim if ts.ndim is 1: ts = ts[:, np.newaxis] channels = ts.shape[1] fs = (len(ts) - 1.0) / (ts.tspan[-1] - ts.tspan[0]) nyq = 0.5 * fs cutoff = cutoff_hz/nyq b, a = signal.butter(order, cutoff, btype='low') if not np.all(np.abs(np.roots(a)) < 1.0): raise ValueError('Filter will not be stable with these values.') dtype = ts.dtype output = np.zeros((len(ts), channels), dtype) for i in range(channels): output[:, i] = signal.filtfilt(b, a, ts[:, i]) if orig_ndim is 1: output = output[:, 0] return Timeseries(output, ts.tspan, labels=ts.labels)
forward-backward butterworth low-pass filter
def supercell_composite(mucape, effective_storm_helicity, effective_shear): r"""Calculate the supercell composite parameter. The supercell composite parameter is designed to identify environments favorable for the development of supercells, and is calculated using the formula developed by [Thompson2004]_: .. math:: \text{SCP} = \frac{\text{MUCAPE}}{1000 \text{J/kg}} * \frac{\text{Effective SRH}}{50 \text{m}^2/\text{s}^2} * \frac{\text{Effective Shear}}{20 \text{m/s}} The effective_shear term is set to zero below 10 m/s and capped at 1 when effective_shear exceeds 20 m/s. Parameters ---------- mucape : `pint.Quantity` Most-unstable CAPE effective_storm_helicity : `pint.Quantity` Effective-layer storm-relative helicity effective_shear : `pint.Quantity` Effective bulk shear Returns ------- array-like supercell composite """ effective_shear = np.clip(atleast_1d(effective_shear), None, 20 * units('m/s')) effective_shear[effective_shear < 10 * units('m/s')] = 0 * units('m/s') effective_shear = effective_shear / (20 * units('m/s')) return ((mucape / (1000 * units('J/kg'))) * (effective_storm_helicity / (50 * units('m^2/s^2'))) * effective_shear).to('dimensionless')
r"""Calculate the supercell composite parameter. The supercell composite parameter is designed to identify environments favorable for the development of supercells, and is calculated using the formula developed by [Thompson2004]_: .. math:: \text{SCP} = \frac{\text{MUCAPE}}{1000 \text{J/kg}} * \frac{\text{Effective SRH}}{50 \text{m}^2/\text{s}^2} * \frac{\text{Effective Shear}}{20 \text{m/s}} The effective_shear term is set to zero below 10 m/s and capped at 1 when effective_shear exceeds 20 m/s. Parameters ---------- mucape : `pint.Quantity` Most-unstable CAPE effective_storm_helicity : `pint.Quantity` Effective-layer storm-relative helicity effective_shear : `pint.Quantity` Effective bulk shear Returns ------- array-like supercell composite
def sleep(self, ms=1): """ Pauses the current green thread for *ms* milliseconds:: p = h.pipe() @h.spawn def _(): p.send('1') h.sleep(50) p.send('2') p.recv() # returns '1' p.recv() # returns '2' after 50 ms """ self.scheduled.add(ms, getcurrent()) self.loop.switch()
Pauses the current green thread for *ms* milliseconds:: p = h.pipe() @h.spawn def _(): p.send('1') h.sleep(50) p.send('2') p.recv() # returns '1' p.recv() # returns '2' after 50 ms
def save_log_to_html(self): """Helper to write the log out as an html file.""" html = html_header() html += ( '<img src="file:///%s/img/logos/inasafe-logo-url.png" ' 'title="InaSAFE Logo" alt="InaSAFE Logo" />' % resources_path()) html += ('<h5 class="info"><i class="icon-info-sign icon-white"></i> ' '%s</h5>' % self.tr('Analysis log')) for item in self.dynamic_messages_log: html += "%s\n" % item.to_html() html += html_footer() if self.log_path is not None: html_to_file(html, self.log_path) else: msg = self.tr('log_path is not set') raise InvalidParameterError(msg)
Helper to write the log out as an html file.
def instantiate(self, params): """ Allows you to fetch the map tiles of a created map :param params: The json with the styling info for the named map :type params: dict :return: :raise: CartoException """ try: self.send(self.Meta.collection_endpoint, "POST", json=params) except CartoRateLimitException as e: raise e except Exception as e: raise CartoException(e)
Allows you to fetch the map tiles of a created map :param params: The json with the styling info for the named map :type params: dict :return: :raise: CartoException
def get_movielens(variant="20m"): """ Gets movielens datasets Parameters --------- variant : string Which version of the movielens dataset to download. Should be one of '20m', '10m', '1m' or '100k'. Returns ------- movies : ndarray An array of the movie titles. ratings : csr_matrix A sparse matrix where the row is the movieId, the column is the userId and the value is the rating. """ filename = "movielens_%s.hdf5" % variant path = os.path.join(_download.LOCAL_CACHE_DIR, filename) if not os.path.isfile(path): log.info("Downloading dataset to '%s'", path) _download.download_file(URL_BASE + filename, path) else: log.info("Using cached dataset at '%s'", path) with h5py.File(path, 'r') as f: m = f.get('movie_user_ratings') plays = csr_matrix((m.get('data'), m.get('indices'), m.get('indptr'))) return np.array(f['movie']), plays
Gets movielens datasets Parameters --------- variant : string Which version of the movielens dataset to download. Should be one of '20m', '10m', '1m' or '100k'. Returns ------- movies : ndarray An array of the movie titles. ratings : csr_matrix A sparse matrix where the row is the movieId, the column is the userId and the value is the rating.
def infer_gtr(self, print_raw=False, marginal=False, normalized_rate=True, fixed_pi=None, pc=5.0, **kwargs): """ Calculates a GTR model given the multiple sequence alignment and the tree. It performs ancestral sequence inferrence (joint or marginal), followed by the branch lengths optimization. Then, the numbers of mutations are counted in the optimal tree and related to the time within the mutation happened. From these statistics, the relative state transition probabilities are inferred, and the transition matrix is computed. The result is used to construct the new GTR model of type 'custom'. The model is assigned to the TreeAnc and is used in subsequent analysis. Parameters ----------- print_raw : bool If True, print the inferred GTR model marginal : bool If True, use marginal sequence reconstruction normalized_rate : bool If True, sets the mutation rate prefactor to 1.0. fixed_pi : np.array Provide the equilibrium character concentrations. If None is passed, the concentrations will be inferred from the alignment. pc: float Number of pseudo counts to use in gtr inference Returns ------- gtr : GTR The inferred GTR model """ # decide which type of the Maximum-likelihood reconstruction use # (marginal) or (joint) if marginal: _ml_anc = self._ml_anc_marginal else: _ml_anc = self._ml_anc_joint self.logger("TreeAnc.infer_gtr: inferring the GTR model from the tree...", 1) if (self.tree is None) or (self.aln is None): self.logger("TreeAnc.infer_gtr: ERROR, alignment or tree are missing", 0) return ttconf.ERROR _ml_anc(final=True, **kwargs) # call one of the reconstruction types alpha = list(self.gtr.alphabet) n=len(alpha) # matrix of mutations n_{ij}: i = derived state, j=ancestral state nij = np.zeros((n,n)) Ti = np.zeros(n) self.logger("TreeAnc.infer_gtr: counting mutations...", 2) for node in self.tree.find_clades(): if hasattr(node,'mutations'): for a,pos, d in node.mutations: i,j = alpha.index(d), alpha.index(a) nij[i,j]+=1 Ti[j] += 0.5*self._branch_length_to_gtr(node) Ti[i] -= 0.5*self._branch_length_to_gtr(node) for ni,nuc in enumerate(node.cseq): i = alpha.index(nuc) Ti[i] += self._branch_length_to_gtr(node)*self.multiplicity[ni] self.logger("TreeAnc.infer_gtr: counting mutations...done", 3) if print_raw: print('alphabet:',alpha) print('n_ij:', nij, nij.sum()) print('T_i:', Ti, Ti.sum()) root_state = np.array([np.sum((self.tree.root.cseq==nuc)*self.multiplicity) for nuc in alpha]) self._gtr = GTR.infer(nij, Ti, root_state, fixed_pi=fixed_pi, pc=pc, alphabet=self.gtr.alphabet, logger=self.logger, prof_map = self.gtr.profile_map) if normalized_rate: self.logger("TreeAnc.infer_gtr: setting overall rate to 1.0...", 2) self._gtr.mu=1.0 return self._gtr
Calculates a GTR model given the multiple sequence alignment and the tree. It performs ancestral sequence inferrence (joint or marginal), followed by the branch lengths optimization. Then, the numbers of mutations are counted in the optimal tree and related to the time within the mutation happened. From these statistics, the relative state transition probabilities are inferred, and the transition matrix is computed. The result is used to construct the new GTR model of type 'custom'. The model is assigned to the TreeAnc and is used in subsequent analysis. Parameters ----------- print_raw : bool If True, print the inferred GTR model marginal : bool If True, use marginal sequence reconstruction normalized_rate : bool If True, sets the mutation rate prefactor to 1.0. fixed_pi : np.array Provide the equilibrium character concentrations. If None is passed, the concentrations will be inferred from the alignment. pc: float Number of pseudo counts to use in gtr inference Returns ------- gtr : GTR The inferred GTR model
def smoothed_joint(seg0, seg1, maxjointsize=3, tightness=1.99): """ See Andy's notes on Smoothing Bezier Paths for an explanation of the method. Input: two segments seg0, seg1 such that seg0.end==seg1.start, and jointsize, a positive number Output: seg0_trimmed, elbow, seg1_trimmed, where elbow is a cubic bezier object that smoothly connects seg0_trimmed and seg1_trimmed. """ assert seg0.end == seg1.start assert 0 < maxjointsize assert 0 < tightness < 2 # sgn = lambda x:x/abs(x) q = seg0.end try: v = seg0.unit_tangent(1) except: v = seg0.unit_tangent(1 - 1e-4) try: w = seg1.unit_tangent(0) except: w = seg1.unit_tangent(1e-4) max_a = maxjointsize / 2 a = min(max_a, min(seg1.length(), seg0.length()) / 20) if isinstance(seg0, Line) and isinstance(seg1, Line): ''' Note: Letting c(t) = elbow.point(t), v= the unit tangent of seg0 at 1, w = the unit tangent vector of seg1 at 0, Q = seg0.point(1) = seg1.point(0), and a,b>0 some constants. The elbow will be the unique CubicBezier, c, such that c(0)= Q-av, c(1)=Q+aw, c'(0) = bv, and c'(1) = bw where a and b are derived above/below from tightness and maxjointsize. ''' # det = v.imag*w.real-v.real*w.imag # Note: # If det is negative, the curvature of elbow is negative for all # real t if and only if b/a > 6 # If det is positive, the curvature of elbow is negative for all # real t if and only if b/a < 2 # if det < 0: # b = (6+tightness)*a # elif det > 0: # b = (2-tightness)*a # else: # raise Exception("seg0 and seg1 are parallel lines.") b = (2 - tightness)*a elbow = CubicBezier(q - a*v, q - (a - b/3)*v, q + (a - b/3)*w, q + a*w) seg0_trimmed = Line(seg0.start, elbow.start) seg1_trimmed = Line(elbow.end, seg1.end) return seg0_trimmed, [elbow], seg1_trimmed elif isinstance(seg0, Line): ''' Note: Letting c(t) = elbow.point(t), v= the unit tangent of seg0 at 1, w = the unit tangent vector of seg1 at 0, Q = seg0.point(1) = seg1.point(0), and a,b>0 some constants. The elbow will be the unique CubicBezier, c, such that c(0)= Q-av, c(1)=Q, c'(0) = bv, and c'(1) = bw where a and b are derived above/below from tightness and maxjointsize. ''' # det = v.imag*w.real-v.real*w.imag # Note: If g has the same sign as det, then the curvature of elbow is # negative for all real t if and only if b/a < 4 b = (4 - tightness)*a # g = sgn(det)*b elbow = CubicBezier(q - a*v, q + (b/3 - a)*v, q - b/3*w, q) seg0_trimmed = Line(seg0.start, elbow.start) return seg0_trimmed, [elbow], seg1 elif isinstance(seg1, Line): args = (seg1.reversed(), seg0.reversed(), maxjointsize, tightness) rseg1_trimmed, relbow, rseg0 = smoothed_joint(*args) elbow = relbow[0].reversed() return seg0, [elbow], rseg1_trimmed.reversed() else: # find a point on each seg that is about a/2 away from joint. Make # line between them. t0 = seg0.ilength(seg0.length() - a/2) t1 = seg1.ilength(a/2) seg0_trimmed = seg0.cropped(0, t0) seg1_trimmed = seg1.cropped(t1, 1) seg0_line = Line(seg0_trimmed.end, q) seg1_line = Line(q, seg1_trimmed.start) args = (seg0_trimmed, seg0_line, maxjointsize, tightness) dummy, elbow0, seg0_line_trimmed = smoothed_joint(*args) args = (seg1_line, seg1_trimmed, maxjointsize, tightness) seg1_line_trimmed, elbow1, dummy = smoothed_joint(*args) args = (seg0_line_trimmed, seg1_line_trimmed, maxjointsize, tightness) seg0_line_trimmed, elbowq, seg1_line_trimmed = smoothed_joint(*args) elbow = elbow0 + [seg0_line_trimmed] + elbowq + [seg1_line_trimmed] + elbow1 return seg0_trimmed, elbow, seg1_trimmed
See Andy's notes on Smoothing Bezier Paths for an explanation of the method. Input: two segments seg0, seg1 such that seg0.end==seg1.start, and jointsize, a positive number Output: seg0_trimmed, elbow, seg1_trimmed, where elbow is a cubic bezier object that smoothly connects seg0_trimmed and seg1_trimmed.
def team(self, team_id): """Returns Team object with information about team specified by ``team_id``. :param int team_id: (required), unique id for the team :returns: :class:`Team <Team>` """ json = None if int(team_id) > 0: url = self._build_url('teams', str(team_id)) json = self._json(self._get(url), 200) return Team(json, self._session) if json else None
Returns Team object with information about team specified by ``team_id``. :param int team_id: (required), unique id for the team :returns: :class:`Team <Team>`
def greedy_mapping(self, reference, hypothesis, uem=None): """Greedy label mapping Parameters ---------- reference : Annotation hypothesis : Annotation Reference and hypothesis diarization uem : Timeline Evaluation map Returns ------- mapping : dict Mapping between hypothesis (key) and reference (value) labels """ if uem: reference, hypothesis = self.uemify(reference, hypothesis, uem=uem) return self.mapper_(hypothesis, reference)
Greedy label mapping Parameters ---------- reference : Annotation hypothesis : Annotation Reference and hypothesis diarization uem : Timeline Evaluation map Returns ------- mapping : dict Mapping between hypothesis (key) and reference (value) labels
def slice_by_size(seq, size): """Slice a sequence into chunks, return as a generation of chunks with `size`.""" filling = null for it in zip(*(itertools_chain(seq, [filling] * size),) * size): if filling in it: it = tuple(i for i in it if i is not filling) if it: yield it
Slice a sequence into chunks, return as a generation of chunks with `size`.
def _save_params(self): """ Saves model parameters at current checkpoint and optionally cleans up older parameter files to save disk space. """ self.model.save_params_to_file(self.current_params_fname) utils.cleanup_params_files(self.model.output_dir, self.max_params_files_to_keep, self.state.checkpoint, self.state.best_checkpoint, self.keep_initializations)
Saves model parameters at current checkpoint and optionally cleans up older parameter files to save disk space.
def remove_from_model(self, remove_orphans=False): """Removes the reaction from a model. This removes all associations between a reaction the associated model, metabolites and genes. The change is reverted upon exit when using the model as a context. Parameters ---------- remove_orphans : bool Remove orphaned genes and metabolites from the model as well """ self._model.remove_reactions([self], remove_orphans=remove_orphans)
Removes the reaction from a model. This removes all associations between a reaction the associated model, metabolites and genes. The change is reverted upon exit when using the model as a context. Parameters ---------- remove_orphans : bool Remove orphaned genes and metabolites from the model as well
def get_alarms_list(self, num_items=100, params=None): """ Get alarms as list of dictionaries :param int num_items: Max items to retrieve :param dict params: Additional params dictionary according to: https://www.alienvault.com/documentation/api/usm-anywhere-api.htm#/alarms :returns list: list of alarms """ if params and set(params.keys()) - VALID_ALARM_PARAMS: self.log.error("Invalid alarm query parameters: {set(params.keys()) - VALID_ALARM_PARAMS}") return None return self._retrieve_items(item_type="alarms", num_items=num_items, params=params)
Get alarms as list of dictionaries :param int num_items: Max items to retrieve :param dict params: Additional params dictionary according to: https://www.alienvault.com/documentation/api/usm-anywhere-api.htm#/alarms :returns list: list of alarms
def chatToId(url): """ Extract the conversation ID from a conversation URL. Matches addresses containing ``conversations/<chat>``. Args: url (str): Skype API URL Returns: str: extracted identifier """ match = re.search(r"conversations/([0-9]+:[^/]+)", url) return match.group(1) if match else None
Extract the conversation ID from a conversation URL. Matches addresses containing ``conversations/<chat>``. Args: url (str): Skype API URL Returns: str: extracted identifier
def generic_filename(path): ''' Extract filename of given path os-indepently, taking care of known path separators. :param path: path :return: filename :rtype: str or unicode (depending on given path) ''' for sep in common_path_separators: if sep in path: _, path = path.rsplit(sep, 1) return path
Extract filename of given path os-indepently, taking care of known path separators. :param path: path :return: filename :rtype: str or unicode (depending on given path)
def parse(self, lines): """Parse the input lines from a robots.txt file. We allow that a user-agent: line is not preceded by one or more blank lines. """ # states: # 0: start state # 1: saw user-agent line # 2: saw an allow or disallow line state = 0 entry = Entry() for line in lines: if not line: if state == 1: entry = Entry() state = 0 elif state == 2: self._add_entry(entry) entry = Entry() state = 0 # remove optional comment and strip line i = line.find('#') if i >= 0: line = line[:i] line = line.strip() if not line: continue line = line.split(':', 1) if len(line) == 2: line[0] = line[0].strip().lower() line[1] = urllib.parse.unquote(line[1].strip()) if line[0] == "user-agent": if state == 2: self._add_entry(entry) entry = Entry() entry.useragents.append(line[1]) state = 1 elif line[0] == "disallow": if state != 0: entry.rulelines.append(RuleLine(line[1], False)) state = 2 elif line[0] == "allow": if state != 0: entry.rulelines.append(RuleLine(line[1], True)) state = 2 if state == 2: self._add_entry(entry)
Parse the input lines from a robots.txt file. We allow that a user-agent: line is not preceded by one or more blank lines.
def edit(text, pos, key): """ Process a key input in the context of a line, and return the resulting text and cursor position. `text' and `key' must be of type str or unicode, and `pos' must be an int in the range [0, len(text)]. If `key' is in keys(), the corresponding command is executed on the line. Otherwise, if `key' is a single character, that character is inserted at the cursor position. If neither condition is met, `text' and `pos' are returned unmodified. """ if key in _key_bindings: return _key_bindings[key](text, pos) elif len(key) == 1: return text[:pos] + key + text[pos:], pos + 1 else: return text, pos
Process a key input in the context of a line, and return the resulting text and cursor position. `text' and `key' must be of type str or unicode, and `pos' must be an int in the range [0, len(text)]. If `key' is in keys(), the corresponding command is executed on the line. Otherwise, if `key' is a single character, that character is inserted at the cursor position. If neither condition is met, `text' and `pos' are returned unmodified.
def _save_results(self, zipdata, outdir, module, gmt, rank_metric, permutation_type): """reformat gsea results, and save to txt""" res = OrderedDict() for gs, gseale, ind, RES in zipdata: rdict = OrderedDict() rdict['es'] = gseale[0] rdict['nes'] = gseale[1] rdict['pval'] = gseale[2] rdict['fdr'] = gseale[3] rdict['geneset_size'] = len(gmt[gs]) rdict['matched_size'] = len(ind) #reformat gene list. _genes = rank_metric.index.values[ind] rdict['genes'] = ";".join([ str(g).strip() for g in _genes ]) if self.module != 'ssgsea': # extract leading edge genes if rdict['es'] > 0: # RES -> ndarray, ind -> list idx = RES.argmax() ldg_pos = list(filter(lambda x: x<= idx, ind)) elif rdict['es'] < 0: idx = RES.argmin() ldg_pos = list(filter(lambda x: x >= idx, ind)) else: ldg_pos = ind # es == 0 ? rdict['ledge_genes'] = ';'.join(list(map(str,rank_metric.iloc[ldg_pos].index))) rdict['RES'] = RES rdict['hits_indices'] = ind # save to one odict res[gs] = rdict # save self.results = res # save to dataframe res_df = pd.DataFrame.from_dict(res, orient='index') res_df.index.name = 'Term' res_df.drop(['RES','hits_indices'], axis=1, inplace=True) res_df.sort_values(by=['fdr','pval'], inplace=True) self.res2d = res_df if self._outdir is None: return out = os.path.join(outdir,'gseapy.{b}.{c}.report.csv'.format(b=module, c=permutation_type)) if self.module == 'ssgsea': out = out.replace(".csv",".txt") with open(out, 'a') as f: f.write('# normalize enrichment scores by random permutation procedure (GSEA method)\n') f.write("# might not proper for publication\n") res_df.to_csv(f, sep='\t') else: res_df.to_csv(out) return
reformat gsea results, and save to txt
def delay_1(year): '''Test for delay of start of new year and to avoid''' # Sunday, Wednesday, and Friday as start of the new year. months = trunc(((235 * year) - 234) / 19) parts = 12084 + (13753 * months) day = trunc((months * 29) + parts / 25920) if ((3 * (day + 1)) % 7) < 3: day += 1 return day
Test for delay of start of new year and to avoid
def get_auth(self, username, password, authoritative_source, auth_options=None): """ Returns an authentication object. Examines the auth backend given after the '@' in the username and returns a suitable instance of a subclass of the BaseAuth class. * `username` [string] Username to authenticate as. * `password` [string] Password to authenticate with. * `authoritative_source` [string] Authoritative source of the query. * `auth_options` [dict] A dict which, if authenticated as a trusted user, can override `username` and `authoritative_source`. """ if auth_options is None: auth_options = {} # validate arguments if (authoritative_source is None): raise AuthError("Missing authoritative_source.") # remove invalid cache entries rem = list() for key in self._auth_cache: if self._auth_cache[key]['valid_until'] < datetime.utcnow(): rem.append(key) for key in rem: del(self._auth_cache[key]) user_authbackend = username.rsplit('@', 1) # Find out what auth backend to use. # If no auth backend was specified in username, use default backend = "" if len(user_authbackend) == 1: backend = self._config.get('auth', 'default_backend') self._logger.debug("Using default auth backend %s" % backend) else: backend = user_authbackend[1] # do we have a cached instance? auth_str = ( str(username) + str(password) + str(authoritative_source) + str(auth_options) ) if auth_str in self._auth_cache: self._logger.debug('found cached auth object for user %s' % username) return self._auth_cache[auth_str]['auth_object'] # Create auth object try: auth = self._backends[backend](backend, user_authbackend[0], password, authoritative_source, auth_options) except KeyError: raise AuthError("Invalid auth backend '%s' specified" % str(backend)) # save auth object to cache self._auth_cache[auth_str] = { 'valid_until': datetime.utcnow() + timedelta(seconds=self._config.getint('auth', 'auth_cache_timeout')), 'auth_object': auth } return auth
Returns an authentication object. Examines the auth backend given after the '@' in the username and returns a suitable instance of a subclass of the BaseAuth class. * `username` [string] Username to authenticate as. * `password` [string] Password to authenticate with. * `authoritative_source` [string] Authoritative source of the query. * `auth_options` [dict] A dict which, if authenticated as a trusted user, can override `username` and `authoritative_source`.
def _gen_pool_xml(name, ptype, target=None, permissions=None, source_devices=None, source_dir=None, source_adapter=None, source_hosts=None, source_auth=None, source_name=None, source_format=None): ''' Generate the XML string to define a libvirt storage pool ''' hosts = [host.split(':') for host in source_hosts or []] context = { 'name': name, 'ptype': ptype, 'target': {'path': target, 'permissions': permissions}, 'source': { 'devices': source_devices or [], 'dir': source_dir, 'adapter': source_adapter, 'hosts': [{'name': host[0], 'port': host[1] if len(host) > 1 else None} for host in hosts], 'auth': source_auth, 'name': source_name, 'format': source_format } } fn_ = 'libvirt_pool.jinja' try: template = JINJA.get_template(fn_) except jinja2.exceptions.TemplateNotFound: log.error('Could not load template %s', fn_) return '' return template.render(**context)
Generate the XML string to define a libvirt storage pool
def gss(args): """ %prog gss fastafile plateMapping Generate sequence files and metadata templates suited for gss submission. The FASTA file is assumed to be exported from the JCVI data delivery folder which looks like: >1127963806024 /library_name=SIL1T054-B-01-120KB /clear_start=0 /clear_end=839 /primer_id=1049000104196 /trace_id=1064147620169 /trace_file_id=1127963805941 /clone_insert_id=1061064364776 /direction=reverse /sequencer_run_id=1064147620155 /sequencer_plate_barcode=B906423 /sequencer_plate_well_coordinates=C3 /sequencer_plate_96well_quadrant=1 /sequencer_plate_96well_coordinates=B02 /template_plate_barcode=CC0251602AB /growth_plate_barcode=BB0273005AB AGCTTTAGTTTCAAGGATACCTTCATTGTCATTCCCGGTTATGATGATATCATCAAGATAAACAAGAATG ACAATGATACCTGTTTGGTTCTGAAGTGTAAAGAGGGTATGTTCAGCTTCAGATCTTCTAAACCCTTTGT CTAGTAAGCTGGCACTTAGCTTCCTATACCAAACCCTTTGTGATTGCTTCAGTCCATAAATTGCCTTTTT Plate mapping file maps the JTC `sequencer_plate_barcode` to external IDs. For example: B906423 SIL-001 """ p = OptionParser(gss.__doc__) opts, args = p.parse_args(args) if len(args) != 2: sys.exit(p.print_help()) fastafile, mappingfile = args seen = defaultdict(int) clone = defaultdict(set) plateMapping = DictFile(mappingfile) fw = open("MetaData.txt", "w") print(PublicationTemplate.format(**vars), file=fw) print(LibraryTemplate.format(**vars), file=fw) print(ContactTemplate.format(**vars), file=fw) logging.debug("Meta data written to `{0}`".format(fw.name)) fw = open("GSS.txt", "w") fw_log = open("GSS.log", "w") for rec in SeqIO.parse(fastafile, "fasta"): # First pass just check well number matchings and populate sequences in # the same clone description = rec.description a = parse_description(description) direction = a["direction"][0] sequencer_plate_barcode = a["sequencer_plate_barcode"][0] sequencer_plate_well_coordinates = \ a["sequencer_plate_well_coordinates"][0] sequencer_plate_96well_quadrant = \ a["sequencer_plate_96well_quadrant"][0] sequencer_plate_96well_coordinates = \ a["sequencer_plate_96well_coordinates"][0] # Check the 96-well ID is correctly converted to 384-well ID w96 = sequencer_plate_96well_coordinates w96quad = int(sequencer_plate_96well_quadrant) w384 = sequencer_plate_well_coordinates assert convert_96_to_384(w96, w96quad) == w384 plate = sequencer_plate_barcode assert plate in plateMapping, \ "{0} not found in `{1}` !".format(plate, mappingfile) plate = plateMapping[plate] d = Directions[direction] cloneID = "{0}{1}".format(plate, w384) gssID = "{0}{1}".format(cloneID, d) seen[gssID] += 1 if seen[gssID] > 1: gssID = "{0}{1}".format(gssID, seen[gssID]) seen[gssID] += 1 clone[cloneID].add(gssID) seen = defaultdict(int) for rec in SeqIO.parse(fastafile, "fasta"): # need to populate gssID, mateID, cloneID, seq, plate, row, column description = rec.description a = parse_description(description) direction = a["direction"][0] sequencer_plate_barcode = a["sequencer_plate_barcode"][0] sequencer_plate_well_coordinates = \ a["sequencer_plate_well_coordinates"][0] w384 = sequencer_plate_well_coordinates plate = sequencer_plate_barcode plate = plateMapping[plate] d = Directions[direction] cloneID = "{0}{1}".format(plate, w384) gssID = "{0}{1}".format(cloneID, d) seen[gssID] += 1 if seen[gssID] > 1: logging.error("duplicate key {0} found".format(gssID)) gssID = "{0}{1}".format(gssID, seen[gssID]) othergss = clone[cloneID] - set([gssID]) othergss = ", ".join(sorted(othergss)) vars.update(locals()) print(GSSTemplate.format(**vars), file=fw) # Write conversion logs to log file print("{0}\t{1}".format(gssID, description), file=fw_log) print("=" * 60, file=fw_log) logging.debug("A total of {0} seqs written to `{1}`".\ format(len(seen), fw.name)) fw.close() fw_log.close()
%prog gss fastafile plateMapping Generate sequence files and metadata templates suited for gss submission. The FASTA file is assumed to be exported from the JCVI data delivery folder which looks like: >1127963806024 /library_name=SIL1T054-B-01-120KB /clear_start=0 /clear_end=839 /primer_id=1049000104196 /trace_id=1064147620169 /trace_file_id=1127963805941 /clone_insert_id=1061064364776 /direction=reverse /sequencer_run_id=1064147620155 /sequencer_plate_barcode=B906423 /sequencer_plate_well_coordinates=C3 /sequencer_plate_96well_quadrant=1 /sequencer_plate_96well_coordinates=B02 /template_plate_barcode=CC0251602AB /growth_plate_barcode=BB0273005AB AGCTTTAGTTTCAAGGATACCTTCATTGTCATTCCCGGTTATGATGATATCATCAAGATAAACAAGAATG ACAATGATACCTGTTTGGTTCTGAAGTGTAAAGAGGGTATGTTCAGCTTCAGATCTTCTAAACCCTTTGT CTAGTAAGCTGGCACTTAGCTTCCTATACCAAACCCTTTGTGATTGCTTCAGTCCATAAATTGCCTTTTT Plate mapping file maps the JTC `sequencer_plate_barcode` to external IDs. For example: B906423 SIL-001
def subrouters(self): """ Generator of sub-routers (middleware inheriting from Router) contained within this router. """ yield from filter(lambda mw: isinstance(mw.func, Router), self.mw_list)
Generator of sub-routers (middleware inheriting from Router) contained within this router.
def blackbox_network(): """A micro-network to demonstrate blackboxing. Diagram:: +----------+ +-------------------->+ A (COPY) + <---------------+ | +----------+ | | +----------+ | | +-----------+ B (COPY) + <-------------+ | v v +----------+ | | +-+-----+-+ +-+-----+-+ | | | | | C (AND) | | F (AND) | | | | | +-+-----+-+ +-+-----+-+ | | ^ ^ | | +----------+ | | | +---------> + D (COPY) +---------------+ | | +----------+ | | +----------+ | +-------------------> + E (COPY) +-----------------+ +----------+ Connectivity Matrix: +---+---+---+---+---+---+---+ | . | A | B | C | D | E | F | +---+---+---+---+---+---+---+ | A | 0 | 0 | 1 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ | B | 0 | 0 | 1 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ | C | 0 | 0 | 0 | 1 | 1 | 0 | +---+---+---+---+---+---+---+ | D | 0 | 0 | 0 | 0 | 0 | 1 | +---+---+---+---+---+---+---+ | E | 0 | 0 | 0 | 0 | 0 | 1 | +---+---+---+---+---+---+---+ | F | 1 | 1 | 0 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ In the documentation example, the state is (0, 0, 0, 0, 0, 0). """ num_nodes = 6 num_states = 2 ** num_nodes tpm = np.zeros((num_states, num_nodes)) for index, previous_state in enumerate(all_states(num_nodes)): current_state = [0 for i in range(num_nodes)] if previous_state[5] == 1: current_state[0] = 1 current_state[1] = 1 if previous_state[0] == 1 and previous_state[1]: current_state[2] = 1 if previous_state[2] == 1: current_state[3] = 1 current_state[4] = 1 if previous_state[3] == 1 and previous_state[4] == 1: current_state[5] = 1 tpm[index, :] = current_state cm = np.array([ [0, 0, 1, 0, 0, 0], [0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 1], [1, 1, 0, 0, 0, 0] ]) return Network(tpm, cm, node_labels=LABELS[:tpm.shape[1]])
A micro-network to demonstrate blackboxing. Diagram:: +----------+ +-------------------->+ A (COPY) + <---------------+ | +----------+ | | +----------+ | | +-----------+ B (COPY) + <-------------+ | v v +----------+ | | +-+-----+-+ +-+-----+-+ | | | | | C (AND) | | F (AND) | | | | | +-+-----+-+ +-+-----+-+ | | ^ ^ | | +----------+ | | | +---------> + D (COPY) +---------------+ | | +----------+ | | +----------+ | +-------------------> + E (COPY) +-----------------+ +----------+ Connectivity Matrix: +---+---+---+---+---+---+---+ | . | A | B | C | D | E | F | +---+---+---+---+---+---+---+ | A | 0 | 0 | 1 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ | B | 0 | 0 | 1 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ | C | 0 | 0 | 0 | 1 | 1 | 0 | +---+---+---+---+---+---+---+ | D | 0 | 0 | 0 | 0 | 0 | 1 | +---+---+---+---+---+---+---+ | E | 0 | 0 | 0 | 0 | 0 | 1 | +---+---+---+---+---+---+---+ | F | 1 | 1 | 0 | 0 | 0 | 0 | +---+---+---+---+---+---+---+ In the documentation example, the state is (0, 0, 0, 0, 0, 0).
def BVirial_Pitzer_Curl(T, Tc, Pc, omega, order=0): r'''Calculates the second virial coefficient using the model in [1]_. Designed for simple calculations. .. math:: B_r=B^{(0)}+\omega B^{(1)} B^{(0)}=0.1445-0.33/T_r-0.1385/T_r^2-0.0121/T_r^3 B^{(1)} = 0.073+0.46/T_r-0.5/T_r^2 -0.097/T_r^3 - 0.0073/T_r^8 Parameters ---------- T : float Temperature of fluid [K] Tc : float Critical temperature of fluid [K] Pc : float Critical pressure of the fluid [Pa] omega : float Acentric factor for fluid, [-] order : int, optional Order of the calculation. 0 for the calculation of B itself; for 1/2/3, the first/second/third derivative of B with respect to temperature; and for -1/-2, the first/second indefinite integral of B with respect to temperature. No other integrals or derivatives are implemented, and an exception will be raised if any other order is given. Returns ------- B : float Second virial coefficient in density form or its integral/derivative if specified, [m^3/mol or m^3/mol/K^order] Notes ----- Analytical models for derivatives and integrals are available for orders -2, -1, 1, 2, and 3, all obtained with SymPy. For first temperature derivative of B: .. math:: \frac{d B^{(0)}}{dT} = \frac{33 Tc}{100 T^{2}} + \frac{277 Tc^{2}}{1000 T^{3}} + \frac{363 Tc^{3}}{10000 T^{4}} \frac{d B^{(1)}}{dT} = - \frac{23 Tc}{50 T^{2}} + \frac{Tc^{2}}{T^{3}} + \frac{291 Tc^{3}}{1000 T^{4}} + \frac{73 Tc^{8}}{1250 T^{9}} For the second temperature derivative of B: .. math:: \frac{d^2 B^{(0)}}{dT^2} = - \frac{3 Tc}{5000 T^{3}} \left(1100 + \frac{1385 Tc}{T} + \frac{242 Tc^{2}}{T^{2}}\right) \frac{d^2 B^{(1)}}{dT^2} = \frac{Tc}{T^{3}} \left(\frac{23}{25} - \frac{3 Tc}{T} - \frac{291 Tc^{2}}{250 T^{2}} - \frac{657 Tc^{7}}{1250 T^{7}}\right) For the third temperature derivative of B: .. math:: \frac{d^3 B^{(0)}}{dT^3} = \frac{3 Tc}{500 T^{4}} \left(330 + \frac{554 Tc}{T} + \frac{121 Tc^{2}}{T^{2}}\right) \frac{d^3 B^{(1)}}{dT^3} = \frac{3 Tc}{T^{4}} \left(- \frac{23}{25} + \frac{4 Tc}{T} + \frac{97 Tc^{2}}{50 T^{2}} + \frac{219 Tc^{7}}{125 T^{7}}\right) For the first indefinite integral of B: .. math:: \int{B^{(0)}} dT = \frac{289 T}{2000} - \frac{33 Tc}{100} \log{\left (T \right )} + \frac{1}{20000 T^{2}} \left(2770 T Tc^{2} + 121 Tc^{3}\right) \int{B^{(1)}} dT = \frac{73 T}{1000} + \frac{23 Tc}{50} \log{\left (T \right )} + \frac{1}{70000 T^{7}} \left(35000 T^{6} Tc^{2} + 3395 T^{5} Tc^{3} + 73 Tc^{8}\right) For the second indefinite integral of B: .. math:: \int\int B^{(0)} dT dT = \frac{289 T^{2}}{4000} - \frac{33 T}{100} Tc \log{\left (T \right )} + \frac{33 T}{100} Tc + \frac{277 Tc^{2}}{2000} \log{\left (T \right )} - \frac{121 Tc^{3}}{20000 T} \int\int B^{(1)} dT dT = \frac{73 T^{2}}{2000} + \frac{23 T}{50} Tc \log{\left (T \right )} - \frac{23 T}{50} Tc + \frac{Tc^{2}}{2} \log{\left (T \right )} - \frac{1}{420000 T^{6}} \left(20370 T^{5} Tc^{3} + 73 Tc^{8}\right) Examples -------- Example matching that in BVirial_Abbott, for isobutane. >>> BVirial_Pitzer_Curl(510., 425.2, 38E5, 0.193) -0.0002084535541385102 References ---------- .. [1] Pitzer, Kenneth S., and R. F. Curl. "The Volumetric and Thermodynamic Properties of Fluids. III. Empirical Equation for the Second Virial Coefficient1." Journal of the American Chemical Society 79, no. 10 (May 1, 1957): 2369-70. doi:10.1021/ja01567a007. ''' Tr = T/Tc if order == 0: B0 = 0.1445 - 0.33/Tr - 0.1385/Tr**2 - 0.0121/Tr**3 B1 = 0.073 + 0.46/Tr - 0.5/Tr**2 - 0.097/Tr**3 - 0.0073/Tr**8 elif order == 1: B0 = Tc*(3300*T**2 + 2770*T*Tc + 363*Tc**2)/(10000*T**4) B1 = Tc*(-2300*T**7 + 5000*T**6*Tc + 1455*T**5*Tc**2 + 292*Tc**7)/(5000*T**9) elif order == 2: B0 = -3*Tc*(1100*T**2 + 1385*T*Tc + 242*Tc**2)/(5000*T**5) B1 = Tc*(1150*T**7 - 3750*T**6*Tc - 1455*T**5*Tc**2 - 657*Tc**7)/(1250*T**10) elif order == 3: B0 = 3*Tc*(330*T**2 + 554*T*Tc + 121*Tc**2)/(500*T**6) B1 = 3*Tc*(-230*T**7 + 1000*T**6*Tc + 485*T**5*Tc**2 + 438*Tc**7)/(250*T**11) elif order == -1: B0 = 289*T/2000 - 33*Tc*log(T)/100 + (2770*T*Tc**2 + 121*Tc**3)/(20000*T**2) B1 = 73*T/1000 + 23*Tc*log(T)/50 + (35000*T**6*Tc**2 + 3395*T**5*Tc**3 + 73*Tc**8)/(70000*T**7) elif order == -2: B0 = 289*T**2/4000 - 33*T*Tc*log(T)/100 + 33*T*Tc/100 + 277*Tc**2*log(T)/2000 - 121*Tc**3/(20000*T) B1 = 73*T**2/2000 + 23*T*Tc*log(T)/50 - 23*T*Tc/50 + Tc**2*log(T)/2 - (20370*T**5*Tc**3 + 73*Tc**8)/(420000*T**6) else: raise Exception('Only orders -2, -1, 0, 1, 2 and 3 are supported.') Br = B0 + omega*B1 return Br*R*Tc/Pc
r'''Calculates the second virial coefficient using the model in [1]_. Designed for simple calculations. .. math:: B_r=B^{(0)}+\omega B^{(1)} B^{(0)}=0.1445-0.33/T_r-0.1385/T_r^2-0.0121/T_r^3 B^{(1)} = 0.073+0.46/T_r-0.5/T_r^2 -0.097/T_r^3 - 0.0073/T_r^8 Parameters ---------- T : float Temperature of fluid [K] Tc : float Critical temperature of fluid [K] Pc : float Critical pressure of the fluid [Pa] omega : float Acentric factor for fluid, [-] order : int, optional Order of the calculation. 0 for the calculation of B itself; for 1/2/3, the first/second/third derivative of B with respect to temperature; and for -1/-2, the first/second indefinite integral of B with respect to temperature. No other integrals or derivatives are implemented, and an exception will be raised if any other order is given. Returns ------- B : float Second virial coefficient in density form or its integral/derivative if specified, [m^3/mol or m^3/mol/K^order] Notes ----- Analytical models for derivatives and integrals are available for orders -2, -1, 1, 2, and 3, all obtained with SymPy. For first temperature derivative of B: .. math:: \frac{d B^{(0)}}{dT} = \frac{33 Tc}{100 T^{2}} + \frac{277 Tc^{2}}{1000 T^{3}} + \frac{363 Tc^{3}}{10000 T^{4}} \frac{d B^{(1)}}{dT} = - \frac{23 Tc}{50 T^{2}} + \frac{Tc^{2}}{T^{3}} + \frac{291 Tc^{3}}{1000 T^{4}} + \frac{73 Tc^{8}}{1250 T^{9}} For the second temperature derivative of B: .. math:: \frac{d^2 B^{(0)}}{dT^2} = - \frac{3 Tc}{5000 T^{3}} \left(1100 + \frac{1385 Tc}{T} + \frac{242 Tc^{2}}{T^{2}}\right) \frac{d^2 B^{(1)}}{dT^2} = \frac{Tc}{T^{3}} \left(\frac{23}{25} - \frac{3 Tc}{T} - \frac{291 Tc^{2}}{250 T^{2}} - \frac{657 Tc^{7}}{1250 T^{7}}\right) For the third temperature derivative of B: .. math:: \frac{d^3 B^{(0)}}{dT^3} = \frac{3 Tc}{500 T^{4}} \left(330 + \frac{554 Tc}{T} + \frac{121 Tc^{2}}{T^{2}}\right) \frac{d^3 B^{(1)}}{dT^3} = \frac{3 Tc}{T^{4}} \left(- \frac{23}{25} + \frac{4 Tc}{T} + \frac{97 Tc^{2}}{50 T^{2}} + \frac{219 Tc^{7}}{125 T^{7}}\right) For the first indefinite integral of B: .. math:: \int{B^{(0)}} dT = \frac{289 T}{2000} - \frac{33 Tc}{100} \log{\left (T \right )} + \frac{1}{20000 T^{2}} \left(2770 T Tc^{2} + 121 Tc^{3}\right) \int{B^{(1)}} dT = \frac{73 T}{1000} + \frac{23 Tc}{50} \log{\left (T \right )} + \frac{1}{70000 T^{7}} \left(35000 T^{6} Tc^{2} + 3395 T^{5} Tc^{3} + 73 Tc^{8}\right) For the second indefinite integral of B: .. math:: \int\int B^{(0)} dT dT = \frac{289 T^{2}}{4000} - \frac{33 T}{100} Tc \log{\left (T \right )} + \frac{33 T}{100} Tc + \frac{277 Tc^{2}}{2000} \log{\left (T \right )} - \frac{121 Tc^{3}}{20000 T} \int\int B^{(1)} dT dT = \frac{73 T^{2}}{2000} + \frac{23 T}{50} Tc \log{\left (T \right )} - \frac{23 T}{50} Tc + \frac{Tc^{2}}{2} \log{\left (T \right )} - \frac{1}{420000 T^{6}} \left(20370 T^{5} Tc^{3} + 73 Tc^{8}\right) Examples -------- Example matching that in BVirial_Abbott, for isobutane. >>> BVirial_Pitzer_Curl(510., 425.2, 38E5, 0.193) -0.0002084535541385102 References ---------- .. [1] Pitzer, Kenneth S., and R. F. Curl. "The Volumetric and Thermodynamic Properties of Fluids. III. Empirical Equation for the Second Virial Coefficient1." Journal of the American Chemical Society 79, no. 10 (May 1, 1957): 2369-70. doi:10.1021/ja01567a007.
def send_subscribe(self, dup, topics): """Send subscribe COMMAND to server.""" pkt = MqttPkt() pktlen = 2 + sum([2+len(topic)+1 for (topic, qos) in topics]) pkt.command = NC.CMD_SUBSCRIBE | (dup << 3) | (1 << 1) pkt.remaining_length = pktlen ret = pkt.alloc() if ret != NC.ERR_SUCCESS: return ret #variable header mid = self.mid_generate() pkt.write_uint16(mid) #payload for (topic, qos) in topics: pkt.write_string(topic) pkt.write_byte(qos) return self.packet_queue(pkt)
Send subscribe COMMAND to server.
def stop_all(self): """Halts both the analog output and input tasks""" if self.aotask is not None: self.aotask.stop() self.aitask.stop() self.daq_lock.release() self.aitask = None self.aotask = None
Halts both the analog output and input tasks
def do_results(args): """ Write the results output file """ config,name,label,coord = args filenames = make_filenames(config,label) srcfile = filenames['srcfile'] samples = filenames['samfile'] if not exists(srcfile): logger.warning("Couldn't find %s; skipping..."%srcfile) return if not exists(samples): logger.warning("Couldn't find %s; skipping..."%samples) return logger.info("Writing %s..."%srcfile) from ugali.analysis.results import write_results write_results(srcfile,config,srcfile,samples)
Write the results output file
def duplicate_nodes(self): """ Return a sequence of node keys of identical meshes. Will combine meshes duplicated by copying in space with different keys in self.geometry, as well as meshes repeated by self.nodes. Returns ----------- duplicates: (m) sequence of keys to self.nodes that represent identical geometry """ # if there is no geometry we can have no duplicate nodes if len(self.geometry) == 0: return [] # geometry name : md5 of mesh mesh_hash = {k: int(m.identifier_md5, 16) for k, m in self.geometry.items()} # the name of nodes in the scene graph with geometry node_names = np.array(self.graph.nodes_geometry) # the geometry names for each node in the same order node_geom = np.array([self.graph[i][1] for i in node_names]) # the mesh md5 for each node in the same order node_hash = np.array([mesh_hash[v] for v in node_geom]) # indexes of identical hashes node_groups = grouping.group(node_hash) # sequence of node names, where each sublist has identical geometry duplicates = [np.sort(node_names[g]).tolist() for g in node_groups] return duplicates
Return a sequence of node keys of identical meshes. Will combine meshes duplicated by copying in space with different keys in self.geometry, as well as meshes repeated by self.nodes. Returns ----------- duplicates: (m) sequence of keys to self.nodes that represent identical geometry
def simOnePeriod(self): ''' Simulates one period for this type. Calls the methods getMortality(), getShocks() or readShocks, getStates(), getControls(), and getPostStates(). These should be defined for AgentType subclasses, except getMortality (define its components simDeath and simBirth instead) and readShocks. Parameters ---------- None Returns ------- None ''' self.getMortality() # Replace some agents with "newborns" if self.read_shocks: # If shock histories have been pre-specified, use those self.readShocks() else: # Otherwise, draw shocks as usual according to subclass-specific method self.getShocks() self.getStates() # Determine each agent's state at decision time self.getControls() # Determine each agent's choice or control variables based on states self.getPostStates() # Determine each agent's post-decision / end-of-period states using states and controls # Advance time for all agents self.t_age = self.t_age + 1 # Age all consumers by one period self.t_cycle = self.t_cycle + 1 # Age all consumers within their cycle self.t_cycle[self.t_cycle == self.T_cycle] = 0
Simulates one period for this type. Calls the methods getMortality(), getShocks() or readShocks, getStates(), getControls(), and getPostStates(). These should be defined for AgentType subclasses, except getMortality (define its components simDeath and simBirth instead) and readShocks. Parameters ---------- None Returns ------- None
def copy(self): """Creates a copy of this :class:`Group`.""" ret = super().copy() for cmd in self.commands: ret.add_command(cmd.copy()) return ret
Creates a copy of this :class:`Group`.
def plot_ts(fignum, dates, ts): """ plot the geomagnetic polarity time scale Parameters __________ fignum : matplotlib figure number dates : bounding dates for plot ts : time scale ck95, gts04, or gts12 """ vertical_plot_init(fignum, 10, 3) TS, Chrons = pmag.get_ts(ts) p = 1 X, Y = [], [] for d in TS: if d <= dates[1]: if d >= dates[0]: if len(X) == 0: ind = TS.index(d) X.append(TS[ind - 1]) Y.append(p % 2) X.append(d) Y.append(p % 2) p += 1 X.append(d) Y.append(p % 2) else: X.append(dates[1]) Y.append(p % 2) plt.plot(X, Y, 'k') plot_vs(fignum, dates, 'w', '-') plot_hs(fignum, [1.1, -.1], 'w', '-') plt.xlabel("Age (Ma): " + ts) isign = -1 for c in Chrons: off = -.1 isign = -1 * isign if isign > 0: off = 1.05 if c[1] >= X[0] and c[1] < X[-1]: plt.text(c[1] - .2, off, c[0]) return
plot the geomagnetic polarity time scale Parameters __________ fignum : matplotlib figure number dates : bounding dates for plot ts : time scale ck95, gts04, or gts12
def rgb_view(qimage, byteorder = 'big'): """Returns RGB view of a given 32-bit color QImage_'s memory. Similarly to byte_view(), the result is a 3D numpy.uint8 array, but reduced to the rgb dimensions (without alpha), and reordered (using negative strides in the last dimension) to have the usual [R,G,B] order. The image must have 32 bit pixel size, i.e. be RGB32, ARGB32, or ARGB32_Premultiplied. (Note that in the latter case, the values are of course premultiplied with alpha.) The order of channels in the last axis depends on the `byteorder`, which defaults to 'big', i.e. RGB order. You may set the argument `byteorder` to 'little' to get BGR, or use None which means sys.byteorder here, i.e. return native order for the machine the code is running on. For your convenience, `qimage` may also be a filename, see `Loading and Saving Images`_ in the documentation. :param qimage: image whose memory shall be accessed via NumPy :type qimage: QImage_ with 32-bit pixel type :param byteorder: specify order of channels in last axis :rtype: numpy.ndarray_ with shape (height, width, 3) and dtype uint8""" if byteorder is None: byteorder = _sys.byteorder bytes = byte_view(qimage, byteorder) if bytes.shape[2] != 4: raise ValueError("For rgb_view, the image must have 32 bit pixel size (use RGB32, ARGB32, or ARGB32_Premultiplied)") if byteorder == 'little': return bytes[...,:3] # strip A off BGRA else: return bytes[...,1:]
Returns RGB view of a given 32-bit color QImage_'s memory. Similarly to byte_view(), the result is a 3D numpy.uint8 array, but reduced to the rgb dimensions (without alpha), and reordered (using negative strides in the last dimension) to have the usual [R,G,B] order. The image must have 32 bit pixel size, i.e. be RGB32, ARGB32, or ARGB32_Premultiplied. (Note that in the latter case, the values are of course premultiplied with alpha.) The order of channels in the last axis depends on the `byteorder`, which defaults to 'big', i.e. RGB order. You may set the argument `byteorder` to 'little' to get BGR, or use None which means sys.byteorder here, i.e. return native order for the machine the code is running on. For your convenience, `qimage` may also be a filename, see `Loading and Saving Images`_ in the documentation. :param qimage: image whose memory shall be accessed via NumPy :type qimage: QImage_ with 32-bit pixel type :param byteorder: specify order of channels in last axis :rtype: numpy.ndarray_ with shape (height, width, 3) and dtype uint8
def normalize_fragment(text, encoding='utf-8'): '''Normalize a fragment. Percent-encodes unacceptable characters and ensures percent-encoding is uppercase. ''' path = percent_encode(text, encoding=encoding, encode_set=FRAGMENT_ENCODE_SET) return uppercase_percent_encoding(path)
Normalize a fragment. Percent-encodes unacceptable characters and ensures percent-encoding is uppercase.
def milestone(self, extra_params=None): """ The Milestone that the Ticket is a part of """ if self.get('milestone_id', None): milestones = self.space.milestones(id=self['milestone_id'], extra_params=extra_params) if milestones: return milestones[0]
The Milestone that the Ticket is a part of