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def load(fp: Union[TextIO, str], load_module: types.ModuleType, **kwargs): """ Convert a file name or file-like object containing stringified JSON into a JSGObject :param fp: file-like object to deserialize :param load_module: module that contains declarations for types :param kwargs: arguments see: json.load for details :return: JSGObject representing the json string """ if isinstance(fp, str): with open(fp) as f: return loads(f.read(), load_module, **kwargs) else: return loads(fp.read(), load_module, **kwargs)
Convert a file name or file-like object containing stringified JSON into a JSGObject :param fp: file-like object to deserialize :param load_module: module that contains declarations for types :param kwargs: arguments see: json.load for details :return: JSGObject representing the json string
def reassign_proficiency_to_objective_bank(self, objective_id, from_objective_bank_id, to_objective_bank_id): """Moves an ``Objective`` from one ``ObjectiveBank`` to another. Mappings to other ``ObjectiveBanks`` are unaffected. arg: objective_id (osid.id.Id): the ``Id`` of the ``Objective`` arg: from_objective_bank_id (osid.id.Id): the ``Id`` of the current ``ObjectiveBank`` arg: to_objective_bank_id (osid.id.Id): the ``Id`` of the destination ``ObjectiveBank`` raise: NotFound - ``objective_id, from_objective_bank_id,`` or ``to_objective_bank_id`` not found or ``objective_id`` not mapped to ``from_objective_bank_id`` raise: NullArgument - ``objective_id, from_objective_bank_id,`` or ``to_objective_bank_id`` is ``null`` raise: OperationFailed - unable to complete request raise: PermissionDenied - authorization failure *compliance: mandatory -- This method must be implemented.* """ # Implemented from template for # osid.resource.ResourceBinAssignmentSession.reassign_resource_to_bin self.assign_objective_to_objective_bank(objective_id, to_objective_bank_id) try: self.unassign_objective_from_objective_bank(objective_id, from_objective_bank_id) except: # something went wrong, roll back assignment to to_objective_bank_id self.unassign_objective_from_objective_bank(objective_id, to_objective_bank_id) raise
Moves an ``Objective`` from one ``ObjectiveBank`` to another. Mappings to other ``ObjectiveBanks`` are unaffected. arg: objective_id (osid.id.Id): the ``Id`` of the ``Objective`` arg: from_objective_bank_id (osid.id.Id): the ``Id`` of the current ``ObjectiveBank`` arg: to_objective_bank_id (osid.id.Id): the ``Id`` of the destination ``ObjectiveBank`` raise: NotFound - ``objective_id, from_objective_bank_id,`` or ``to_objective_bank_id`` not found or ``objective_id`` not mapped to ``from_objective_bank_id`` raise: NullArgument - ``objective_id, from_objective_bank_id,`` or ``to_objective_bank_id`` is ``null`` raise: OperationFailed - unable to complete request raise: PermissionDenied - authorization failure *compliance: mandatory -- This method must be implemented.*
def map(cls, x, palette, limits, na_value=None): """ Map values to a discrete palette Parameters ---------- palette : callable ``f(x)`` palette to use x : array_like Continuous values to scale na_value : object Value to use for missing values. Returns ------- out : array_like Values mapped onto a palette """ n = len(limits) pal = palette(n)[match(x, limits)] try: pal[pd.isnull(x)] = na_value except TypeError: pal = [v if not pd.isnull(v) else na_value for v in pal] return pal
Map values to a discrete palette Parameters ---------- palette : callable ``f(x)`` palette to use x : array_like Continuous values to scale na_value : object Value to use for missing values. Returns ------- out : array_like Values mapped onto a palette
def _add_spin_magnitudes(self, structure): """ Replaces Spin.up/Spin.down with spin magnitudes specified by mag_species_spin. :param structure: :return: """ for idx, site in enumerate(structure): if getattr(site.specie, '_properties', None): spin = site.specie._properties.get('spin', None) sign = int(spin) if spin else 0 if spin: new_properties = site.specie._properties.copy() # this very hacky bit of code only works because we know # that on disordered sites in this class, all species are the same # but have different spins, and this is comma-delimited sp = str(site.specie).split(",")[0] new_properties.update({ 'spin': sign * self.mag_species_spin.get(sp, 0) }) new_specie = Specie(site.specie.symbol, getattr(site.specie, 'oxi_state', None), new_properties) structure.replace(idx, new_specie, properties=site.properties) logger.debug('Structure with spin magnitudes:\n{}'.format(str(structure))) return structure
Replaces Spin.up/Spin.down with spin magnitudes specified by mag_species_spin. :param structure: :return:
def _updateConstructorAndMembers(self): """We overwrite constructor and accessors every time because the constructor might have to consume all members even if their decorator is below the "synthesizeConstructor" decorator and it also might need to update the getters and setters because the naming convention has changed. """ syntheticMetaData = self._syntheticMetaData() constructor = self._constructorFactory.makeConstructor(syntheticMetaData.originalConstructor(), syntheticMetaData.syntheticMemberList(), syntheticMetaData.doesConsumeArguments()) self._class.__init__ = constructor for syntheticMember in syntheticMetaData.syntheticMemberList(): syntheticMember.apply(self._class, syntheticMetaData.originalMemberNameList(), syntheticMetaData.namingConvention()) if syntheticMetaData.hasEqualityGeneration(): eq = self._comparisonFactory.makeEqualFunction(syntheticMetaData.originalEqualFunction(), syntheticMetaData.syntheticMemberList()) ne = self._comparisonFactory.makeNotEqualFunction(syntheticMetaData.originalNotEqualFunction(), syntheticMetaData.syntheticMemberList()) hashFunc = self._comparisonFactory.makeHashFunction(syntheticMetaData.originalHashFunction(), syntheticMetaData.syntheticMemberList()) self._class.__eq__ = eq self._class.__ne__ = ne self._class.__hash__ = hashFunc
We overwrite constructor and accessors every time because the constructor might have to consume all members even if their decorator is below the "synthesizeConstructor" decorator and it also might need to update the getters and setters because the naming convention has changed.
def space_new(args): """ Create a new workspace. """ r = fapi.create_workspace(args.project, args.workspace, args.authdomain, dict()) fapi._check_response_code(r, 201) if fcconfig.verbosity: eprint(r.content) return 0
Create a new workspace.
def _set_cfm_detail(self, v, load=False): """ Setter method for cfm_detail, mapped from YANG variable /cfm_state/cfm_detail (container) If this variable is read-only (config: false) in the source YANG file, then _set_cfm_detail is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_cfm_detail() directly. YANG Description: CFM Details """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=cfm_detail.cfm_detail, is_container='container', presence=False, yang_name="cfm-detail", rest_name="cfm-detail", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'dot1ag-cfm-detail', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-dot1ag-operational', defining_module='brocade-dot1ag-operational', yang_type='container', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """cfm_detail must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=cfm_detail.cfm_detail, is_container='container', presence=False, yang_name="cfm-detail", rest_name="cfm-detail", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'dot1ag-cfm-detail', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-dot1ag-operational', defining_module='brocade-dot1ag-operational', yang_type='container', is_config=False)""", }) self.__cfm_detail = t if hasattr(self, '_set'): self._set()
Setter method for cfm_detail, mapped from YANG variable /cfm_state/cfm_detail (container) If this variable is read-only (config: false) in the source YANG file, then _set_cfm_detail is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_cfm_detail() directly. YANG Description: CFM Details
def fire(self, exclude=None, delay=True): """Notify everyone watching the event. We are explicit about sending notifications; we don't just key off creation signals, because the receiver of a ``post_save`` signal has no idea what just changed, so it doesn't know which notifications to send. Also, we could easily send mail accidentally: for instance, during tests. If we want implicit event firing, we can always register a signal handler that calls :meth:`fire()`. :arg exclude: If a saved user is passed in, that user will not be notified, though anonymous notifications having the same email address may still be sent. A sequence of users may also be passed in. :arg delay: If True (default), the event is handled asynchronously with Celery. This requires the pickle task serializer, which is no longer the default starting in Celery 4.0. If False, the event is processed immediately. """ if delay: # Tasks don't receive the `self` arg implicitly. self._fire_task.apply_async( args=(self,), kwargs={'exclude': exclude}, serializer='pickle') else: self._fire_task(self, exclude=exclude)
Notify everyone watching the event. We are explicit about sending notifications; we don't just key off creation signals, because the receiver of a ``post_save`` signal has no idea what just changed, so it doesn't know which notifications to send. Also, we could easily send mail accidentally: for instance, during tests. If we want implicit event firing, we can always register a signal handler that calls :meth:`fire()`. :arg exclude: If a saved user is passed in, that user will not be notified, though anonymous notifications having the same email address may still be sent. A sequence of users may also be passed in. :arg delay: If True (default), the event is handled asynchronously with Celery. This requires the pickle task serializer, which is no longer the default starting in Celery 4.0. If False, the event is processed immediately.
def from_conll(this_class, stream): """Construct a Sentence. stream is an iterable over strings where each string is a line in CoNLL-X format. If there are multiple sentences in this stream, we only return the first one.""" stream = iter(stream) sentence = this_class() for line in stream: line = line.strip() if line: sentence.append(Token.from_conll(line)) elif sentence: return sentence return sentence
Construct a Sentence. stream is an iterable over strings where each string is a line in CoNLL-X format. If there are multiple sentences in this stream, we only return the first one.
def await_transform_exists(cli, transform_path, does_exist=DEFAULT_TRANSFORM_EXISTS, timeout_seconds=DEFAULT_TIMEOUT_SECONDS): """ Waits for a single transform to exist based on does_exist. :param cli: :param transform_path: :param does_exist: Whether or not to await for exist state (True | False) :param timeout_seconds: How long until this returns with failure :return: bool """ message_payload = { "transform_paths": [transform_path], "do_exist": does_exist, "match_mode": "All", "timeout": timeout_seconds } msg = message.Message("await.unity.transform.exists", message_payload) cli.send_message(msg) response = cli.read_message() verify_response(response) return bool(response['payload']['success'])
Waits for a single transform to exist based on does_exist. :param cli: :param transform_path: :param does_exist: Whether or not to await for exist state (True | False) :param timeout_seconds: How long until this returns with failure :return: bool
def find_region_end(self, lines): """Find the end of the region started with start and end markers""" if self.metadata and 'cell_type' in self.metadata: self.cell_type = self.metadata.pop('cell_type') else: self.cell_type = 'code' parser = StringParser(self.language or self.default_language) for i, line in enumerate(lines): # skip cell header if self.metadata is not None and i == 0: continue if parser.is_quoted(): parser.read_line(line) continue parser.read_line(line) # New code region # Simple code pattern in LightScripts must be preceded with a blank line if self.start_code_re.match(line) or ( self.simple_start_code_re and self.simple_start_code_re.match(line) and (self.cell_marker_start or i == 0 or _BLANK_LINE.match(lines[i - 1]))): if self.explicit_end_marker_required: # Metadata here was conditioned on finding an explicit end marker # before the next start marker. So we dismiss it. self.metadata = None self.language = None if i > 0 and _BLANK_LINE.match(lines[i - 1]): if i > 1 and _BLANK_LINE.match(lines[i - 2]): return i - 2, i, False return i - 1, i, False return i, i, False if not self.ignore_end_marker and self.end_code_re: if self.end_code_re.match(line): return i, i + 1, True elif _BLANK_LINE.match(line): if not next_code_is_indented(lines[i:]): if i > 0: return i, i + 1, False if len(lines) > 1 and not _BLANK_LINE.match(lines[1]): return 1, 1, False return 1, 2, False return len(lines), len(lines), False
Find the end of the region started with start and end markers
def days_to_liquidate_positions(positions, market_data, max_bar_consumption=0.2, capital_base=1e6, mean_volume_window=5): """ Compute the number of days that would have been required to fully liquidate each position on each day based on the trailing n day mean daily bar volume and a limit on the proportion of a daily bar that we are allowed to consume. This analysis uses portfolio allocations and a provided capital base rather than the dollar values in the positions DataFrame to remove the effect of compounding on days to liquidate. In other words, this function assumes that the net liquidation portfolio value will always remain constant at capital_base. Parameters ---------- positions: pd.DataFrame Contains daily position values including cash - See full explanation in tears.create_full_tear_sheet market_data : pd.Panel Panel with items axis of 'price' and 'volume' DataFrames. The major and minor axes should match those of the the passed positions DataFrame (same dates and symbols). max_bar_consumption : float Max proportion of a daily bar that can be consumed in the process of liquidating a position. capital_base : integer Capital base multiplied by portfolio allocation to compute position value that needs liquidating. mean_volume_window : float Trailing window to use in mean volume calculation. Returns ------- days_to_liquidate : pd.DataFrame Number of days required to fully liquidate daily positions. Datetime index, symbols as columns. """ DV = market_data['volume'] * market_data['price'] roll_mean_dv = DV.rolling(window=mean_volume_window, center=False).mean().shift() roll_mean_dv = roll_mean_dv.replace(0, np.nan) positions_alloc = pos.get_percent_alloc(positions) positions_alloc = positions_alloc.drop('cash', axis=1) days_to_liquidate = (positions_alloc * capital_base) / \ (max_bar_consumption * roll_mean_dv) return days_to_liquidate.iloc[mean_volume_window:]
Compute the number of days that would have been required to fully liquidate each position on each day based on the trailing n day mean daily bar volume and a limit on the proportion of a daily bar that we are allowed to consume. This analysis uses portfolio allocations and a provided capital base rather than the dollar values in the positions DataFrame to remove the effect of compounding on days to liquidate. In other words, this function assumes that the net liquidation portfolio value will always remain constant at capital_base. Parameters ---------- positions: pd.DataFrame Contains daily position values including cash - See full explanation in tears.create_full_tear_sheet market_data : pd.Panel Panel with items axis of 'price' and 'volume' DataFrames. The major and minor axes should match those of the the passed positions DataFrame (same dates and symbols). max_bar_consumption : float Max proportion of a daily bar that can be consumed in the process of liquidating a position. capital_base : integer Capital base multiplied by portfolio allocation to compute position value that needs liquidating. mean_volume_window : float Trailing window to use in mean volume calculation. Returns ------- days_to_liquidate : pd.DataFrame Number of days required to fully liquidate daily positions. Datetime index, symbols as columns.
def writeCmdMsg(self, msg): """ Internal method to set the command result string. Args: msg (str): Message built during command. """ ekm_log("(writeCmdMsg | " + self.getContext() + ") " + msg) self.m_command_msg = msg
Internal method to set the command result string. Args: msg (str): Message built during command.
def listify(val, return_type=tuple): """ Examples: >>> listify('abc', return_type=list) ['abc'] >>> listify(None) () >>> listify(False) (False,) >>> listify(('a', 'b', 'c'), return_type=list) ['a', 'b', 'c'] """ # TODO: flatlistify((1, 2, 3), 4, (5, 6, 7)) if val is None: return return_type() elif isiterable(val): return return_type(val) else: return return_type((val, ))
Examples: >>> listify('abc', return_type=list) ['abc'] >>> listify(None) () >>> listify(False) (False,) >>> listify(('a', 'b', 'c'), return_type=list) ['a', 'b', 'c']
def original_query_sequence_length(self): """Similar to get_get_query_sequence_length, but it also includes hard clipped bases if there is no cigar, then default to trying the sequence :return: the length of the query before any clipping :rtype: int """ if not self.is_aligned() or not self.entries.cigar: return self.query_sequence_length # take the naive approach # we are here with something aligned so take more intelligent cigar apporach return sum([x[0] for x in self.cigar_array if re.match('[HMIS=X]',x[1])])
Similar to get_get_query_sequence_length, but it also includes hard clipped bases if there is no cigar, then default to trying the sequence :return: the length of the query before any clipping :rtype: int
def quote_by_instruments(cls, client, ids): """ create instrument urls, fetch, return results """ base_url = "https://api.robinhood.com/instruments" id_urls = ["{}/{}/".format(base_url, _id) for _id in ids] return cls.quotes_by_instrument_urls(client, id_urls)
create instrument urls, fetch, return results
def user_absent(name, channel=14, **kwargs): ''' Remove user Delete all user (uid) records having the matching name. name string name of user to delete channel channel to remove user access from defaults to 14 for auto. kwargs - api_host=localhost - api_user=admin - api_pass= - api_port=623 - api_kg=None ''' ret = {'name': name, 'result': False, 'comment': '', 'changes': {}} user_id_list = __salt__['ipmi.get_name_uids'](name, channel, **kwargs) if not user_id_list: ret['result'] = True ret['comment'] = 'user already absent' return ret if __opts__['test']: ret['comment'] = 'would delete user(s)' ret['result'] = None ret['changes'] = {'delete': user_id_list} return ret for uid in user_id_list: __salt__['ipmi.delete_user'](uid, channel, **kwargs) ret['comment'] = 'user(s) removed' ret['changes'] = {'old': user_id_list, 'new': 'None'} return ret
Remove user Delete all user (uid) records having the matching name. name string name of user to delete channel channel to remove user access from defaults to 14 for auto. kwargs - api_host=localhost - api_user=admin - api_pass= - api_port=623 - api_kg=None
def show_lowstate(**kwargs): ''' List out the low data that will be applied to this minion CLI Example: .. code-block:: bash salt '*' state.show_lowstate ''' __opts__['grains'] = __grains__ opts = salt.utils.state.get_sls_opts(__opts__, **kwargs) st_ = salt.client.ssh.state.SSHHighState( opts, __pillar__, __salt__, __context__['fileclient']) st_.push_active() chunks = st_.compile_low_chunks() _cleanup_slsmod_low_data(chunks) return chunks
List out the low data that will be applied to this minion CLI Example: .. code-block:: bash salt '*' state.show_lowstate
def _mirror_penalized(self, f_values, idx): """obsolete and subject to removal (TODO), return modified f-values such that for each mirror one becomes worst. This function is useless when selective mirroring is applied with no more than (lambda-mu)/2 solutions. Mirrors are leading and trailing values in ``f_values``. """ assert len(f_values) >= 2 * len(idx) m = np.max(np.abs(f_values)) for i in len(idx): if f_values[idx[i]] > f_values[-1 - i]: f_values[idx[i]] += m else: f_values[-1 - i] += m return f_values
obsolete and subject to removal (TODO), return modified f-values such that for each mirror one becomes worst. This function is useless when selective mirroring is applied with no more than (lambda-mu)/2 solutions. Mirrors are leading and trailing values in ``f_values``.
def file_like(name): """A name is file-like if it is a path that exists, or it has a directory part, or it ends in .py, or it isn't a legal python identifier. """ return (os.path.exists(name) or os.path.dirname(name) or name.endswith('.py') or not ident_re.match(os.path.splitext(name)[0]))
A name is file-like if it is a path that exists, or it has a directory part, or it ends in .py, or it isn't a legal python identifier.
def confirm(text, default=False, abort=False, prompt_suffix=': ', show_default=True, err=False): """Prompts for confirmation (yes/no question). If the user aborts the input by sending a interrupt signal this function will catch it and raise a :exc:`Abort` exception. .. versionadded:: 4.0 Added the `err` parameter. :param text: the question to ask. :param default: the default for the prompt. :param abort: if this is set to `True` a negative answer aborts the exception by raising :exc:`Abort`. :param prompt_suffix: a suffix that should be added to the prompt. :param show_default: shows or hides the default value in the prompt. :param err: if set to true the file defaults to ``stderr`` instead of ``stdout``, the same as with echo. """ prompt = _build_prompt(text, prompt_suffix, show_default, default and 'Y/n' or 'y/N') while 1: try: # Write the prompt separately so that we get nice # coloring through colorama on Windows echo(prompt, nl=False, err=err) value = visible_prompt_func('').lower().strip() except (KeyboardInterrupt, EOFError): raise Abort() if value in ('y', 'yes'): rv = True elif value in ('n', 'no'): rv = False elif value == '': rv = default else: echo('Error: invalid input', err=err) continue break if abort and not rv: raise Abort() return rv
Prompts for confirmation (yes/no question). If the user aborts the input by sending a interrupt signal this function will catch it and raise a :exc:`Abort` exception. .. versionadded:: 4.0 Added the `err` parameter. :param text: the question to ask. :param default: the default for the prompt. :param abort: if this is set to `True` a negative answer aborts the exception by raising :exc:`Abort`. :param prompt_suffix: a suffix that should be added to the prompt. :param show_default: shows or hides the default value in the prompt. :param err: if set to true the file defaults to ``stderr`` instead of ``stdout``, the same as with echo.
def get_vulnerability( source, sink, triggers, lattice, cfg, interactive, blackbox_mapping ): """Get vulnerability between source and sink if it exists. Uses triggers to find sanitisers. Note: When a secondary node is in_constraint with the sink but not the source, the secondary is a save_N_LHS node made in process_function in expr_visitor. Args: source(TriggerNode): TriggerNode of the source. sink(TriggerNode): TriggerNode of the sink. triggers(Triggers): Triggers of the CFG. lattice(Lattice): the lattice we're analysing. cfg(CFG): .blackbox_assignments used in is_unknown, .nodes used in build_def_use_chain interactive(bool): determines if we ask the user about blackbox functions not in the mapping file. blackbox_mapping(dict): A map of blackbox functions containing whether or not they propagate taint. Returns: A Vulnerability if it exists, else None """ nodes_in_constraint = [ secondary for secondary in reversed(source.secondary_nodes) if lattice.in_constraint( secondary, sink.cfg_node ) ] nodes_in_constraint.append(source.cfg_node) if sink.trigger.all_arguments_propagate_taint: sink_args = get_sink_args(sink.cfg_node) else: sink_args = get_sink_args_which_propagate(sink, sink.cfg_node.ast_node) tainted_node_in_sink_arg = get_tainted_node_in_sink_args( sink_args, nodes_in_constraint, ) if tainted_node_in_sink_arg: vuln_deets = { 'source': source.cfg_node, 'source_trigger_word': source.trigger_word, 'sink': sink.cfg_node, 'sink_trigger_word': sink.trigger_word } sanitiser_nodes = set() potential_sanitiser = None if sink.sanitisers: for sanitiser in sink.sanitisers: for cfg_node in triggers.sanitiser_dict[sanitiser]: if isinstance(cfg_node, AssignmentNode): sanitiser_nodes.add(cfg_node) elif isinstance(cfg_node, IfNode): potential_sanitiser = cfg_node def_use = build_def_use_chain( cfg.nodes, lattice ) for chain in get_vulnerability_chains( source.cfg_node, sink.cfg_node, def_use ): vulnerability_type, interactive = how_vulnerable( chain, blackbox_mapping, sanitiser_nodes, potential_sanitiser, cfg.blackbox_assignments, interactive, vuln_deets ) if vulnerability_type == VulnerabilityType.FALSE: continue vuln_deets['reassignment_nodes'] = chain return vuln_factory(vulnerability_type)(**vuln_deets), interactive return None, interactive
Get vulnerability between source and sink if it exists. Uses triggers to find sanitisers. Note: When a secondary node is in_constraint with the sink but not the source, the secondary is a save_N_LHS node made in process_function in expr_visitor. Args: source(TriggerNode): TriggerNode of the source. sink(TriggerNode): TriggerNode of the sink. triggers(Triggers): Triggers of the CFG. lattice(Lattice): the lattice we're analysing. cfg(CFG): .blackbox_assignments used in is_unknown, .nodes used in build_def_use_chain interactive(bool): determines if we ask the user about blackbox functions not in the mapping file. blackbox_mapping(dict): A map of blackbox functions containing whether or not they propagate taint. Returns: A Vulnerability if it exists, else None
def _init_trace_logging(self, app): """ Sets up trace logging unless ``APPINSIGHTS_DISABLE_TRACE_LOGGING`` is set in the Flask config. Args: app (flask.Flask). the Flask application for which to initialize the extension. """ enabled = not app.config.get(CONF_DISABLE_TRACE_LOGGING, False) if not enabled: return self._trace_log_handler = LoggingHandler( self._key, telemetry_channel=self._channel) app.logger.addHandler(self._trace_log_handler)
Sets up trace logging unless ``APPINSIGHTS_DISABLE_TRACE_LOGGING`` is set in the Flask config. Args: app (flask.Flask). the Flask application for which to initialize the extension.
def present( name, user=None, fingerprint=None, key=None, port=None, enc=None, config=None, hash_known_hosts=True, timeout=5, fingerprint_hash_type=None): ''' Verifies that the specified host is known by the specified user On many systems, specifically those running with openssh 4 or older, the ``enc`` option must be set, only openssh 5 and above can detect the key type. name The name of the remote host (e.g. "github.com") Note that only a single hostname is supported, if foo.example.com and bar.example.com have the same host you will need two separate Salt States to represent them. user The user who owns the ssh authorized keys file to modify fingerprint The fingerprint of the key which must be present in the known_hosts file (optional if key specified) key The public key which must be present in the known_hosts file (optional if fingerprint specified) port optional parameter, port which will be used to when requesting the public key from the remote host, defaults to port 22. enc Defines what type of key is being used, can be ed25519, ecdsa ssh-rsa or ssh-dss config The location of the authorized keys file relative to the user's home directory, defaults to ".ssh/known_hosts". If no user is specified, defaults to "/etc/ssh/ssh_known_hosts". If present, must be an absolute path when a user is not specified. hash_known_hosts : True Hash all hostnames and addresses in the known hosts file. timeout : int Set the timeout for connection attempts. If ``timeout`` seconds have elapsed since a connection was initiated to a host or since the last time anything was read from that host, then the connection is closed and the host in question considered unavailable. Default is 5 seconds. .. versionadded:: 2016.3.0 fingerprint_hash_type The public key fingerprint hash type that the public key fingerprint was originally hashed with. This defaults to ``sha256`` if not specified. .. versionadded:: 2016.11.4 .. versionchanged:: 2017.7.0: default changed from ``md5`` to ``sha256`` ''' ret = {'name': name, 'changes': {}, 'result': None if __opts__['test'] else True, 'comment': ''} if not user: config = config or '/etc/ssh/ssh_known_hosts' else: config = config or '.ssh/known_hosts' if not user and not os.path.isabs(config): comment = 'If not specifying a "user", specify an absolute "config".' ret['result'] = False return dict(ret, comment=comment) if __opts__['test']: if key and fingerprint: comment = 'Specify either "key" or "fingerprint", not both.' ret['result'] = False return dict(ret, comment=comment) elif key and not enc: comment = 'Required argument "enc" if using "key" argument.' ret['result'] = False return dict(ret, comment=comment) try: result = __salt__['ssh.check_known_host'](user, name, key=key, fingerprint=fingerprint, config=config, port=port, fingerprint_hash_type=fingerprint_hash_type) except CommandNotFoundError as err: ret['result'] = False ret['comment'] = 'ssh.check_known_host error: {0}'.format(err) return ret if result == 'exists': comment = 'Host {0} is already in {1}'.format(name, config) ret['result'] = True return dict(ret, comment=comment) elif result == 'add': comment = 'Key for {0} is set to be added to {1}'.format(name, config) return dict(ret, comment=comment) else: # 'update' comment = 'Key for {0} is set to be updated in {1}'.format(name, config) return dict(ret, comment=comment) result = __salt__['ssh.set_known_host']( user=user, hostname=name, fingerprint=fingerprint, key=key, port=port, enc=enc, config=config, hash_known_hosts=hash_known_hosts, timeout=timeout, fingerprint_hash_type=fingerprint_hash_type) if result['status'] == 'exists': return dict(ret, comment='{0} already exists in {1}'.format(name, config)) elif result['status'] == 'error': return dict(ret, result=False, comment=result['error']) else: # 'updated' if key: new_key = result['new'][0]['key'] return dict(ret, changes={'old': result['old'], 'new': result['new']}, comment='{0}\'s key saved to {1} (key: {2})'.format( name, config, new_key)) else: fingerprint = result['new'][0]['fingerprint'] return dict(ret, changes={'old': result['old'], 'new': result['new']}, comment='{0}\'s key saved to {1} (fingerprint: {2})'.format( name, config, fingerprint))
Verifies that the specified host is known by the specified user On many systems, specifically those running with openssh 4 or older, the ``enc`` option must be set, only openssh 5 and above can detect the key type. name The name of the remote host (e.g. "github.com") Note that only a single hostname is supported, if foo.example.com and bar.example.com have the same host you will need two separate Salt States to represent them. user The user who owns the ssh authorized keys file to modify fingerprint The fingerprint of the key which must be present in the known_hosts file (optional if key specified) key The public key which must be present in the known_hosts file (optional if fingerprint specified) port optional parameter, port which will be used to when requesting the public key from the remote host, defaults to port 22. enc Defines what type of key is being used, can be ed25519, ecdsa ssh-rsa or ssh-dss config The location of the authorized keys file relative to the user's home directory, defaults to ".ssh/known_hosts". If no user is specified, defaults to "/etc/ssh/ssh_known_hosts". If present, must be an absolute path when a user is not specified. hash_known_hosts : True Hash all hostnames and addresses in the known hosts file. timeout : int Set the timeout for connection attempts. If ``timeout`` seconds have elapsed since a connection was initiated to a host or since the last time anything was read from that host, then the connection is closed and the host in question considered unavailable. Default is 5 seconds. .. versionadded:: 2016.3.0 fingerprint_hash_type The public key fingerprint hash type that the public key fingerprint was originally hashed with. This defaults to ``sha256`` if not specified. .. versionadded:: 2016.11.4 .. versionchanged:: 2017.7.0: default changed from ``md5`` to ``sha256``
def get_subdomain_DID_info(fqn, db_path=None, zonefiles_dir=None): """ Get a subdomain's DID info. Return None if not found """ opts = get_blockstack_opts() if not is_subdomains_enabled(opts): log.warn("Subdomain support is disabled") return None if db_path is None: db_path = opts['subdomaindb_path'] if zonefiles_dir is None: zonefiles_dir = opts['zonefiles'] db = SubdomainDB(db_path, zonefiles_dir) try: subrec = db.get_subdomain_entry(fqn) except SubdomainNotFound: log.warn("No such subdomain: {}".format(fqn)) return None try: return db.get_subdomain_DID_info(fqn) except SubdomainNotFound: return None
Get a subdomain's DID info. Return None if not found
def predict(self, data): """ Predict a new data set based on an estimated model. Parameters ---------- data : pandas.DataFrame Data to use for prediction. Must contain all the columns referenced by the right-hand side of the `model_expression`. Returns ------- result : pandas.Series Predicted values as a pandas Series. Will have the index of `data` after applying filters. """ self.assert_fitted() with log_start_finish('predicting model {}'.format(self.name), logger): return predict( data, self.predict_filters, self.model_fit, self.ytransform)
Predict a new data set based on an estimated model. Parameters ---------- data : pandas.DataFrame Data to use for prediction. Must contain all the columns referenced by the right-hand side of the `model_expression`. Returns ------- result : pandas.Series Predicted values as a pandas Series. Will have the index of `data` after applying filters.
def _copy_from(self, rhs): """Copy all data from rhs into this instance, handles usage count""" self._manager = rhs._manager self._rlist = type(rhs._rlist)(rhs._rlist) self._region = rhs._region self._ofs = rhs._ofs self._size = rhs._size for region in self._rlist: region.increment_client_count() if self._region is not None: self._region.increment_client_count()
Copy all data from rhs into this instance, handles usage count
def OnCellFontSize(self, event): """Cell font size event handler""" with undo.group(_("Font size")): self.grid.actions.set_attr("pointsize", event.size) self.grid.ForceRefresh() self.grid.update_attribute_toolbar() event.Skip()
Cell font size event handler
def transpose_list(list_of_dicts): """Transpose a list of dicts to a dict of lists :param list_of_dicts: to transpose, as in the output from a parse call :return: Dict of lists """ res = {} for d in list_of_dicts: for k, v in d.items(): if k in res: res[k].append(v) else: res[k] = [v] return res
Transpose a list of dicts to a dict of lists :param list_of_dicts: to transpose, as in the output from a parse call :return: Dict of lists
def run(cmd, *args, **kwargs): """Echo a command before running it. Defaults to repo as cwd""" log.info('> ' + list2cmdline(cmd)) kwargs.setdefault('cwd', here) kwargs.setdefault('shell', sys.platform == 'win32') if not isinstance(cmd, list): cmd = cmd.split() return check_call(cmd, *args, **kwargs)
Echo a command before running it. Defaults to repo as cwd
def _sig(self, name, dtype=BIT, defVal=None): """ Create signal in this unit """ if isinstance(dtype, HStruct): if defVal is not None: raise NotImplementedError() container = dtype.fromPy(None) for f in dtype.fields: if f.name is not None: r = self._sig("%s_%s" % (name, f.name), f.dtype) setattr(container, f.name, r) return container return self._ctx.sig(name, dtype=dtype, defVal=defVal)
Create signal in this unit
def run(data, samples, force, ipyclient): """ Check all samples requested have been clustered (state=6), make output directory, then create the requested outfiles. Excluded samples are already removed from samples. """ ## prepare dirs data.dirs.outfiles = os.path.join(data.dirs.project, data.name+"_outfiles") if not os.path.exists(data.dirs.outfiles): os.mkdir(data.dirs.outfiles) ## make the snps/filters data base, fills the dups and inds filters ## and fills the splits locations data.database = os.path.join(data.dirs.outfiles, data.name+".hdf5") init_arrays(data) ## Apply filters to supercatg and superhdf5 with selected samples ## and fill the filters and edge arrays. filter_all_clusters(data, samples, ipyclient) ## Everything needed is in the now filled h5 database. Filters were applied ## with 'samples' taken into account. Now we create the loci file (default) ## output and build a stats file. data.outfiles.loci = os.path.join(data.dirs.outfiles, data.name+".loci") data.outfiles.alleles = os.path.join(data.dirs.outfiles, data.name+".alleles.loci") make_loci_and_stats(data, samples, ipyclient) ## OPTIONAL OUTPUTS: output_formats = data.paramsdict["output_formats"] ## held separate from *output_formats cuz it's big and parallelized if any([x in output_formats for x in ["v", "V"]]): full = "V" in output_formats try: make_vcf(data, samples, ipyclient, full=full) except IPyradWarningExit as inst: ## Something fsck vcf build. Sometimes this is simply a memory ## issue, so trap the exception and allow it to try building ## the other output formats. print(" Error building vcf. See ipyrad_log.txt for details.") LOGGER.error(inst) ## make other array-based formats, recalcs keeps and arrays make_outfiles(data, samples, output_formats, ipyclient) ## print friendly message shortpath = data.dirs.outfiles.replace(os.path.expanduser("~"), "~") print("{}Outfiles written to: {}\n".format(data._spacer, shortpath))
Check all samples requested have been clustered (state=6), make output directory, then create the requested outfiles. Excluded samples are already removed from samples.
def convert_bam_to_bed(in_bam, out_file): """Convert BAM to bed file using BEDTools. """ with file_transaction(out_file) as tx_out_file: with open(tx_out_file, "w") as out_handle: subprocess.check_call(["bamToBed", "-i", in_bam, "-tag", "NM"], stdout=out_handle) return out_file
Convert BAM to bed file using BEDTools.
def read(self, size=None): """Read a length of bytes. Return empty on EOF. If 'size' is omitted, return whole file. """ if size is not None: return self.__sf.read(size) block_size = self.__class__.__block_size b = bytearray() received_bytes = 0 while 1: partial = self.__sf.read(block_size) # self.__log.debug("Reading (%d) bytes. (%d) bytes returned." % # (block_size, len(partial))) b.extend(partial) received_bytes += len(partial) if len(partial) < block_size: self.__log.debug("End of file.") break self.__log.debug("Read (%d) bytes for total-file." % (received_bytes)) return b
Read a length of bytes. Return empty on EOF. If 'size' is omitted, return whole file.
def probability_density(self, X): """Compute density function for given copula family. Args: X: `np.ndarray` Returns: np.array: probability density """ self.check_fit() U, V = self.split_matrix(X) if self.theta == 0: return np.multiply(U, V) else: num = np.multiply(np.multiply(-self.theta, self._g(1)), 1 + self._g(np.add(U, V))) aux = np.multiply(self._g(U), self._g(V)) + self._g(1) den = np.power(aux, 2) return num / den
Compute density function for given copula family. Args: X: `np.ndarray` Returns: np.array: probability density
def _request_prepare(self, three_pc_key: Tuple[int, int], recipients: List[str] = None, stash_data: Optional[Tuple[str, str, str]] = None) -> bool: """ Request preprepare """ if recipients is None: recipients = self.node.nodestack.connecteds.copy() primaryName = self.primaryName[:self.primaryName.rfind(":")] recipients.discard(primaryName) return self._request_three_phase_msg(three_pc_key, self.requested_prepares, PREPARE, recipients, stash_data)
Request preprepare
def hide_file(path): """ Set the hidden attribute on a file or directory. From http://stackoverflow.com/questions/19622133/ `path` must be text. """ __import__('ctypes.wintypes') SetFileAttributes = ctypes.windll.kernel32.SetFileAttributesW SetFileAttributes.argtypes = ctypes.wintypes.LPWSTR, ctypes.wintypes.DWORD SetFileAttributes.restype = ctypes.wintypes.BOOL FILE_ATTRIBUTE_HIDDEN = 0x02 ret = SetFileAttributes(path, FILE_ATTRIBUTE_HIDDEN) if not ret: raise ctypes.WinError()
Set the hidden attribute on a file or directory. From http://stackoverflow.com/questions/19622133/ `path` must be text.
def ServiceWorker_startWorker(self, scopeURL): """ Function path: ServiceWorker.startWorker Domain: ServiceWorker Method name: startWorker Parameters: Required arguments: 'scopeURL' (type: string) -> No description No return value. """ assert isinstance(scopeURL, (str,) ), "Argument 'scopeURL' must be of type '['str']'. Received type: '%s'" % type( scopeURL) subdom_funcs = self.synchronous_command('ServiceWorker.startWorker', scopeURL=scopeURL) return subdom_funcs
Function path: ServiceWorker.startWorker Domain: ServiceWorker Method name: startWorker Parameters: Required arguments: 'scopeURL' (type: string) -> No description No return value.
def leagues(self, year=2019): """Return all leagues in dict {id0: league0, id1: league1}. :params year: Year. """ if year not in self._leagues: self._leagues[year] = leagues(year) return self._leagues[year]
Return all leagues in dict {id0: league0, id1: league1}. :params year: Year.
def minimal_selector(self, complete_selector): """Returns the minimal selector that uniquely matches `complete_selector`. Args: complete_selector: A complete selector stored in the map. Returns: A partial selector that unambiguously matches `complete_selector`. Raises: KeyError: If `complete_selector` is not in the map. """ if complete_selector not in self._selector_map: raise KeyError("No value with selector '{}'.".format(complete_selector)) selector_components = complete_selector.split('.') node = self._selector_tree start = None for i, component in enumerate(reversed(selector_components)): if len(node) == 1: if start is None: start = -i # Negative index, since we're iterating in reverse. else: start = None node = node[component] if len(node) > 1: # The selector is a substring of another selector. return complete_selector return '.'.join(selector_components[start:])
Returns the minimal selector that uniquely matches `complete_selector`. Args: complete_selector: A complete selector stored in the map. Returns: A partial selector that unambiguously matches `complete_selector`. Raises: KeyError: If `complete_selector` is not in the map.
def get_annotation_urls_and_checksums(species, release=None, ftp=None): """Get FTP URLs and checksums for Ensembl genome annotations. Parameters ---------- species : str or list of str The species or list of species for which to get genome annotations (e.g., "Homo_sapiens"). release : int, optional The release number to look up. If `None`, use latest release. [None] ftp : ftplib.FTP, optional The FTP connection to use. If `None`, the function will open and close its own connection using user "anonymous". """ ### type checks assert isinstance(species, (str, _oldstr)) or isinstance(species, Iterable) if release is not None: assert isinstance(release, int) if ftp is not None: assert isinstance(ftp, ftplib.FTP) ### open FTP connection if necessary close_connection = False ftp_server = 'ftp.ensembl.org' ftp_user = 'anonymous' if ftp is None: ftp = ftplib.FTP(ftp_server) ftp.login(ftp_user) close_connection = True ### determine release if necessary if release is None: # use latest release release = util.get_latest_release(ftp=ftp) species_data = OrderedDict() if isinstance(species, (str, _oldstr)): species_list = [species] else: species_list = species for spec in species_list: # get the GTF file URL # => since the naming scheme isn't consistent across species, # we're using a flexible scheme here to find the right file species_dir = '/pub/release-%d/gtf/%s' % (release, spec.lower()) data = [] ftp.dir(species_dir, data.append) gtf_file = [] for d in data: i = d.rindex(' ') fn = d[(i + 1):] if fn.endswith('.%d.gtf.gz' % release): gtf_file.append(fn) assert len(gtf_file) == 1 gtf_file = gtf_file[0] _LOGGER.debug('GTF file: %s', gtf_file) ### get the checksum for the GTF file checksum_url = '/'.join([species_dir, 'CHECKSUMS']) file_checksums = util.get_file_checksums(checksum_url, ftp=ftp) gtf_checksum = file_checksums[gtf_file] _LOGGER.debug('GTF file checksum: %d', gtf_checksum) gtf_url = 'ftp://%s%s/%s' %(ftp_server, species_dir, gtf_file) species_data[spec] = (gtf_url, gtf_checksum) # close FTP connection, if we opened it if close_connection: ftp.close() return species_data
Get FTP URLs and checksums for Ensembl genome annotations. Parameters ---------- species : str or list of str The species or list of species for which to get genome annotations (e.g., "Homo_sapiens"). release : int, optional The release number to look up. If `None`, use latest release. [None] ftp : ftplib.FTP, optional The FTP connection to use. If `None`, the function will open and close its own connection using user "anonymous".
def list_categories(self, package_keyname, **kwargs): """List the categories for the given package. :param str package_keyname: The package for which to get the categories. :returns: List of categories associated with the package """ get_kwargs = {} get_kwargs['mask'] = kwargs.get('mask', CATEGORY_MASK) if 'filter' in kwargs: get_kwargs['filter'] = kwargs['filter'] package = self.get_package_by_key(package_keyname, mask='id') categories = self.package_svc.getConfiguration(id=package['id'], **get_kwargs) return categories
List the categories for the given package. :param str package_keyname: The package for which to get the categories. :returns: List of categories associated with the package
def log_estimator_evaluation_result(self, eval_results): """Log the evaluation result for a estimator. The evaluate result is a directory that contains metrics defined in model_fn. It also contains a entry for global_step which contains the value of the global step when evaluation was performed. Args: eval_results: dict, the result of evaluate() from a estimator. """ if not isinstance(eval_results, dict): tf.logging.warning("eval_results should be directory for logging. Got %s", type(eval_results)) return global_step = eval_results[tf.GraphKeys.GLOBAL_STEP] for key in sorted(eval_results): if key != tf.GraphKeys.GLOBAL_STEP: self.log_metric(key, eval_results[key], global_step=global_step)
Log the evaluation result for a estimator. The evaluate result is a directory that contains metrics defined in model_fn. It also contains a entry for global_step which contains the value of the global step when evaluation was performed. Args: eval_results: dict, the result of evaluate() from a estimator.
def read(self, *args, **kwargs): """Reads the node as a file """ with self.open('r') as f: return f.read(*args, **kwargs)
Reads the node as a file
def load_df_state(path_csv: Path)->pd.DataFrame: '''load `df_state` from `path_csv` Parameters ---------- path_csv : Path path to the csv file that stores `df_state` produced by a supy run Returns ------- pd.DataFrame `df_state` produced by a supy run ''' df_state = pd.read_csv( path_csv, header=[0, 1], index_col=[0, 1], parse_dates=True, infer_datetime_format=True, ) return df_state
load `df_state` from `path_csv` Parameters ---------- path_csv : Path path to the csv file that stores `df_state` produced by a supy run Returns ------- pd.DataFrame `df_state` produced by a supy run
def impact_path(self, value): """Setter to impact path. :param value: The impact path. :type value: str """ self._impact_path = value if value is None: self.action_show_report.setEnabled(False) self.action_show_log.setEnabled(False) self.report_path = None self.log_path = None else: self.action_show_report.setEnabled(True) self.action_show_log.setEnabled(True) self.log_path = '%s.log.html' % self.impact_path self.report_path = '%s.report.html' % self.impact_path self.save_report_to_html() self.save_log_to_html() self.show_report()
Setter to impact path. :param value: The impact path. :type value: str
def parse_words(self): """Parse TextGrid word intervals. This method parses the word intervals in a TextGrid to extract each word and each word's start and end times in the audio recording. For each word, it instantiates the class Word(), with the word and its start and end times as attributes of that class instance. Further, it appends the class instance's attribute 'phones' for each phone that occurs in that word. (It does this by checking which phones' start and end times are subsumed by the start and end times of the word.) """ phones = self.parse_phones() words = [] for i in self.word_intervals: start = float(i[i.index('xmin = ')+7: i.index('xmin = ')+12].strip('\t').strip('\n')) end = float(i[i.index('xmax = ')+7: i.index('xmax = ')+12].strip('\t').strip('\n')) word = i[i.index('\"')+1:i.index("$")] words.append(Word(word, start, end)) for word in words: for phone in phones: if phone.start >= word.start and phone.end <= word.end: word.phones.append(phone) return words
Parse TextGrid word intervals. This method parses the word intervals in a TextGrid to extract each word and each word's start and end times in the audio recording. For each word, it instantiates the class Word(), with the word and its start and end times as attributes of that class instance. Further, it appends the class instance's attribute 'phones' for each phone that occurs in that word. (It does this by checking which phones' start and end times are subsumed by the start and end times of the word.)
def get_power_state(self, userid): """Get power status of a z/VM instance.""" LOG.debug('Querying power stat of %s' % userid) requestData = "PowerVM " + userid + " status" action = "query power state of '%s'" % userid with zvmutils.log_and_reraise_smt_request_failed(action): results = self._request(requestData) with zvmutils.expect_invalid_resp_data(results): status = results['response'][0].partition(': ')[2] return status
Get power status of a z/VM instance.
def output_file(self): """ If only one output file return it. Otherwise raise an exception. """ out_files = self.output_files if len(out_files) != 1: err_msg = "output_file property is only valid if there is a single" err_msg += " output file. Here there are " err_msg += "%d output files." %(len(out_files)) raise ValueError(err_msg) return out_files[0]
If only one output file return it. Otherwise raise an exception.
def _get_substitute_element(head, elt, ps): '''if elt matches a member of the head substitutionGroup, return the GED typecode. head -- ElementDeclaration typecode, elt -- the DOM element being parsed ps -- ParsedSoap Instance ''' if not isinstance(head, ElementDeclaration): return None return ElementDeclaration.getSubstitutionElement(head, elt, ps)
if elt matches a member of the head substitutionGroup, return the GED typecode. head -- ElementDeclaration typecode, elt -- the DOM element being parsed ps -- ParsedSoap Instance
def setTimer(self, timeout, description=None): """ Sets a timer. :param description: :param timeout: timeout in seconds :return: the timerId """ self.timerId += 1 timer = Timer(timeout, self.__timeoutHandler, (self.timerId, description)) timer.start() self.timers[self.timerId] = timer return self.timerId
Sets a timer. :param description: :param timeout: timeout in seconds :return: the timerId
def get_activity_query_session(self): """Gets the ``OsidSession`` associated with the activity query service. return: (osid.learning.ActivityQuerySession) - a ``ActivityQuerySession`` raise: OperationFailed - unable to complete request raise: Unimplemented - ``supports_activity_query()`` is ``false`` *compliance: optional -- This method must be implemented if ``supports_activity_query()`` is ``true``.* """ if not self.supports_activity_query(): raise errors.Unimplemented() # pylint: disable=no-member return sessions.ActivityQuerySession(runtime=self._runtime)
Gets the ``OsidSession`` associated with the activity query service. return: (osid.learning.ActivityQuerySession) - a ``ActivityQuerySession`` raise: OperationFailed - unable to complete request raise: Unimplemented - ``supports_activity_query()`` is ``false`` *compliance: optional -- This method must be implemented if ``supports_activity_query()`` is ``true``.*
def _combine(self, x, y): """Combines two constraints, raising an error if they are not compatible.""" if x is None or y is None: return x or y if x != y: raise ValueError('Incompatible set of constraints provided.') return x
Combines two constraints, raising an error if they are not compatible.
def validate_password_confirmation(self, value): """ password_confirmation check """ if value != self.initial_data['password']: raise serializers.ValidationError(_('Password confirmation mismatch')) return value
password_confirmation check
def greenfct(zsrc, zrec, lsrc, lrec, depth, etaH, etaV, zetaH, zetaV, lambd): r"""Calculate Green's function for TM and TE. This is a modified version of empymod.kernel.greenfct(). See the original version for more information. """ # GTM/GTE have shape (frequency, offset, lambda). # gamTM/gamTE have shape (frequency, offset, layer, lambda): for TM in [True, False]: # Define eta/zeta depending if TM or TE if TM: e_zH, e_zV, z_eH = etaH, etaV, zetaH # TM: zetaV not used else: e_zH, e_zV, z_eH = zetaH, zetaV, etaH # TE: etaV not used # Uppercase gamma Gam = np.sqrt((e_zH/e_zV)[:, None, :, None] * (lambd*lambd)[None, :, None, :] + (z_eH*e_zH)[:, None, :, None]) # Gamma in receiver layer lrecGam = Gam[:, :, lrec, :] # Reflection (coming from below (Rp) and above (Rm) rec) Rp, Rm = reflections(depth, e_zH, Gam, lrec, lsrc, False) # Field propagators # (Up- (Wu) and downgoing (Wd), in rec layer); Eq 74 if lrec != depth.size-1: # No upgoing field prop. if rec in last ddepth = depth[lrec + 1] - zrec Wu = np.exp(-lrecGam*ddepth) else: Wu = np.full_like(lrecGam, 0+0j) if lrec != 0: # No downgoing field propagator if rec in first ddepth = zrec - depth[lrec] Wd = np.exp(-lrecGam*ddepth) else: Wd = np.full_like(lrecGam, 0+0j) # Field at rec level (coming from below (Pu) and above (Pd) rec) Puu, Pud, Pdu, Pdd = fields(depth, Rp, Rm, Gam, lrec, lsrc, zsrc, TM) # Store in corresponding variable PT* = [T*uu, T*ud, T*du, T*dd] df = np.exp(-lrecGam*abs(zsrc - zrec)) # direct field fTM = Gam[:, :, lrec, :]/etaH[:, None, lrec, None] fTE = zetaH[:, None, lsrc, None]/Gam[:, :, lsrc, :] if TM: PTM = [Puu*Wu*fTM, Pud*Wu*fTM, Pdu*Wd*fTM, Pdd*Wd*fTM, -df*fTM] else: PTE = [Puu*Wu*fTE, Pud*Wu*fTE, Pdu*Wd*fTE, Pdd*Wd*fTE, df*fTE] # Return Green's functions return PTM, PTE
r"""Calculate Green's function for TM and TE. This is a modified version of empymod.kernel.greenfct(). See the original version for more information.
def graphcut_subprocesses(graphcut_function, graphcut_arguments, processes = None): """ Executes multiple graph cuts in parallel. This can result in a significant speed-up. Parameters ---------- graphcut_function : function The graph cut to use (e.g. `graphcut_stawiaski`). graphcut_arguments : tuple List of arguments to pass to the respective subprocesses resp. the ``graphcut_function``. processes : integer or None The number of processes to run simultaneously, if not supplied, will be the same as the number of processors. Returns ------- segmentations : tuple of ndarray The graph-cut segmentation results as list of boolean arraya. """ # initialize logger logger = Logger.getInstance() # check and eventually enhance input parameters if not processes: processes = multiprocessing.cpu_count() if not int == type(processes) or processes <= 0: raise ArgumentError('The number processes can not be zero or negative.') logger.debug('Executing graph cuts in {} subprocesses.'.format(multiprocessing.cpu_count())) # creates subprocess pool and execute pool = multiprocessing.Pool(processes) results = pool.map(graphcut_function, graphcut_arguments) return results
Executes multiple graph cuts in parallel. This can result in a significant speed-up. Parameters ---------- graphcut_function : function The graph cut to use (e.g. `graphcut_stawiaski`). graphcut_arguments : tuple List of arguments to pass to the respective subprocesses resp. the ``graphcut_function``. processes : integer or None The number of processes to run simultaneously, if not supplied, will be the same as the number of processors. Returns ------- segmentations : tuple of ndarray The graph-cut segmentation results as list of boolean arraya.
def update_scale(self, overflow): """dynamically update loss scale""" iter_since_rescale = self._num_steps - self._last_rescale_iter if overflow: self._last_overflow_iter = self._num_steps self._overflows_since_rescale += 1 percentage = self._overflows_since_rescale / float(iter_since_rescale) # we tolerate a certrain amount of NaNs before actually scaling it down if percentage >= self.tolerance: self.loss_scale /= self.scale_factor self._last_rescale_iter = self._num_steps self._overflows_since_rescale = 0 logging.info('DynamicLossScaler: overflow detected. set loss_scale = %s', self.loss_scale) elif (self._num_steps - self._last_overflow_iter) % self.scale_window == 0: self.loss_scale *= self.scale_factor self._last_rescale_iter = self._num_steps self._num_steps += 1
dynamically update loss scale
def category(self, categories): """Add categories assigned to this message :rtype: list(Category) """ if isinstance(categories, list): for c in categories: self.add_category(c) else: self.add_category(categories)
Add categories assigned to this message :rtype: list(Category)
def _find_package(self, root_package): """Finds package name of file :param root_package: root package :return: package name """ package = self.path.replace(root_package, "") if package.endswith(".py"): package = package[:-3] package = package.replace(os.path.sep, MODULE_SEP) root_package = get_folder_name(root_package) package = root_package + package # add root return package
Finds package name of file :param root_package: root package :return: package name
def compile_rcc(self, namespace, unknown): """Compile qt resource files :param namespace: namespace containing arguments from the launch parser :type namespace: Namespace :param unknown: list of unknown arguments :type unknown: list :returns: None :rtype: None :raises: None """ rccfile = namespace.rccfile.name qtcompile.compile_rcc(rccfile)
Compile qt resource files :param namespace: namespace containing arguments from the launch parser :type namespace: Namespace :param unknown: list of unknown arguments :type unknown: list :returns: None :rtype: None :raises: None
def set_level(self, level): """ A method to set all column values to one of the levels. :param str level: The level at which the column will be set (a string) :returns: H2OFrame with entries set to the desired level. """ return H2OFrame._expr(expr=ExprNode("setLevel", self, level), cache=self._ex._cache)
A method to set all column values to one of the levels. :param str level: The level at which the column will be set (a string) :returns: H2OFrame with entries set to the desired level.
def flatten(x): """flatten(sequence) -> list Returns a single, flat list which contains all elements retrieved from the sequence and all recursively contained sub-sequences (iterables). Examples: >>> [1, 2, [3,4], (5,6)] [1, 2, [3, 4], (5, 6)] >>> flatten([[[1,2,3], (42,None)], [4,5], [6], 7, MyVector(8,9,10)]) [1, 2, 3, 42, None, 4, 5, 6, 7, 8, 9, 10] """ for el in x: if hasattr(el, "__iter__") and not isinstance(el, (binary, unicode)): for els in flatten(el): yield els else: yield el
flatten(sequence) -> list Returns a single, flat list which contains all elements retrieved from the sequence and all recursively contained sub-sequences (iterables). Examples: >>> [1, 2, [3,4], (5,6)] [1, 2, [3, 4], (5, 6)] >>> flatten([[[1,2,3], (42,None)], [4,5], [6], 7, MyVector(8,9,10)]) [1, 2, 3, 42, None, 4, 5, 6, 7, 8, 9, 10]
def _place_ticks_vertical(self): """Display the ticks for a vertical slider.""" for tick, label in zip(self.ticks, self.ticklabels): y = self.convert_to_pixels(tick) label.place_configure(y=y)
Display the ticks for a vertical slider.
def hdrval(cls): """Construct dictionary mapping display column title to IterationStats entries. """ hdrmap = {'Itn': 'Iter'} hdrmap.update(cls.hdrval_objfun) hdrmap.update({'r': 'PrimalRsdl', 's': 'DualRsdl', u('ρ'): 'Rho'}) return hdrmap
Construct dictionary mapping display column title to IterationStats entries.
def engine_from_environment() -> Engine: """Returns an Engine instance configured using environment variables. If the environment variables are set, but incorrect, an authentication failure will occur when attempting to run jobs on the engine. Required Environment Variables: QUANTUM_ENGINE_PROJECT: The name of a google cloud project, with the quantum engine enabled, that you have access to. QUANTUM_ENGINE_API_KEY: An API key for the google cloud project named by QUANTUM_ENGINE_PROJECT. Raises: EnvironmentError: The environment variables are not set. """ api_key = os.environ.get(ENV_API_KEY) if not api_key: raise EnvironmentError( 'Environment variable {} is not set.'.format(ENV_API_KEY)) default_project_id = os.environ.get(ENV_DEFAULT_PROJECT_ID) return Engine(api_key=api_key, default_project_id=default_project_id)
Returns an Engine instance configured using environment variables. If the environment variables are set, but incorrect, an authentication failure will occur when attempting to run jobs on the engine. Required Environment Variables: QUANTUM_ENGINE_PROJECT: The name of a google cloud project, with the quantum engine enabled, that you have access to. QUANTUM_ENGINE_API_KEY: An API key for the google cloud project named by QUANTUM_ENGINE_PROJECT. Raises: EnvironmentError: The environment variables are not set.
def reduce_hierarchy(x, depth): """Reduce the hierarchy (depth by `|`) string to the specified level""" _x = x.split('|') depth = len(_x) + depth - 1 if depth < 0 else depth return '|'.join(_x[0:(depth + 1)])
Reduce the hierarchy (depth by `|`) string to the specified level
def unpack_rsp(cls, rsp_pb): """Convert from PLS response to user response""" if rsp_pb.retType != RET_OK: return RET_ERROR, rsp_pb.retMsg, None raw_order_list = rsp_pb.s2c.orderList order_list = [OrderListQuery.parse_order(rsp_pb, order) for order in raw_order_list] return RET_OK, "", order_list
Convert from PLS response to user response
def append_item(self, item): """ Add an item to the end of the menu before the exit item. Args: item (MenuItem): The item to be added. """ did_remove = self.remove_exit() item.menu = self self.items.append(item) if did_remove: self.add_exit()
Add an item to the end of the menu before the exit item. Args: item (MenuItem): The item to be added.
def _updateMinDutyCycles(self): """ Updates the minimum duty cycles defining normal activity for a column. A column with activity duty cycle below this minimum threshold is boosted. """ if self._globalInhibition or self._inhibitionRadius > self._numInputs: self._updateMinDutyCyclesGlobal() else: self._updateMinDutyCyclesLocal()
Updates the minimum duty cycles defining normal activity for a column. A column with activity duty cycle below this minimum threshold is boosted.
def getAssociation(self, assoc_handle, dumb, checkExpiration=True): """Get the association with the specified handle. @type assoc_handle: str @param dumb: Is this association used with dumb mode? @type dumb: bool @returns: the association, or None if no valid association with that handle was found. @returntype: L{openid.association.Association} """ # Hmm. We've created an interface that deals almost entirely with # assoc_handles. The only place outside the Signatory that uses this # (and thus the only place that ever sees Association objects) is # when creating a response to an association request, as it must have # the association's secret. if assoc_handle is None: raise ValueError("assoc_handle must not be None") if dumb: key = self._dumb_key else: key = self._normal_key assoc = self.store.getAssociation(key, assoc_handle) if assoc is not None and assoc.expiresIn <= 0: logging.info("requested %sdumb key %r is expired (by %s seconds)" % ((not dumb) and 'not-' or '', assoc_handle, assoc.expiresIn)) if checkExpiration: self.store.removeAssociation(key, assoc_handle) assoc = None return assoc
Get the association with the specified handle. @type assoc_handle: str @param dumb: Is this association used with dumb mode? @type dumb: bool @returns: the association, or None if no valid association with that handle was found. @returntype: L{openid.association.Association}
def get_urls(self): """ Returns a list of urls including all NestedSimpleRouter urls """ ret = super(SimpleRouter, self).get_urls() for router in self.nested_routers: ret.extend(router.get_urls()) return ret
Returns a list of urls including all NestedSimpleRouter urls
def generate_obj(self): """Generates the secret object, respecting existing information and user specified options""" secret_obj = {} if self.existing: secret_obj = deepcopy(self.existing) for key in self.keys: key_name = key['name'] if self.existing and \ key_name in self.existing and \ not key.get('overwrite'): LOG.debug("Not overwriting %s/%s", self.path, key_name) continue else: secret_obj[key_name] = generated_key(key) return secret_obj
Generates the secret object, respecting existing information and user specified options
def decrypt(receiver_prvhex: str, msg: bytes) -> bytes: """ Decrypt with eth private key Parameters ---------- receiver_pubhex: str Receiver's ethereum private key hex string msg: bytes Data to decrypt Returns ------- bytes Plain text """ pubkey = msg[0:65] # pubkey's length is 65 bytes encrypted = msg[65:] sender_public_key = hex2pub(pubkey.hex()) private_key = hex2prv(receiver_prvhex) aes_key = derive(private_key, sender_public_key) return aes_decrypt(aes_key, encrypted)
Decrypt with eth private key Parameters ---------- receiver_pubhex: str Receiver's ethereum private key hex string msg: bytes Data to decrypt Returns ------- bytes Plain text
def get_constant_state(self): """Read state that was written in "first_part" mode. Returns: a structure """ ret = self.constant_states[self.next_constant_state] self.next_constant_state += 1 return ret
Read state that was written in "first_part" mode. Returns: a structure
def _extract_number_of_taxa(self): """ sets `self.number_taxa` to the number of taxa as string """ n_taxa = dict() for i in self.seq_records: if i.gene_code not in n_taxa: n_taxa[i.gene_code] = 0 n_taxa[i.gene_code] += 1 number_taxa = sorted([i for i in n_taxa.values()], reverse=True)[0] self.number_taxa = str(number_taxa)
sets `self.number_taxa` to the number of taxa as string
def cur_space(self, name=None): """Set the current space to Space ``name`` and return it. If called without arguments, the current space is returned. Otherwise, the current space is set to the space named ``name`` and the space is returned. """ if name is None: return self._impl.model.currentspace.interface else: self._impl.model.currentspace = self._impl.spaces[name] return self.cur_space()
Set the current space to Space ``name`` and return it. If called without arguments, the current space is returned. Otherwise, the current space is set to the space named ``name`` and the space is returned.
def app_restart(name, profile, **kwargs): """ Restart application. Executes ```cocaine-tool app pause``` and ```cocaine-tool app start``` sequentially. It can be used to quickly change application profile. """ ctx = Context(**kwargs) ctx.execute_action('app:restart', **{ 'node': ctx.repo.create_secure_service('node'), 'locator': ctx.locator, 'name': name, 'profile': profile, })
Restart application. Executes ```cocaine-tool app pause``` and ```cocaine-tool app start``` sequentially. It can be used to quickly change application profile.
def put(self): """Re-import all templates, overwriting any local changes made""" try: _import_templates(force=True) return self.make_response('Imported templates') except: self.log.exception('Failed importing templates') return self.make_response('Failed importing templates', HTTP.SERVER_ERROR)
Re-import all templates, overwriting any local changes made
def axis_angle(self): """:obj:`numpy.ndarray` of float: The axis-angle representation for the rotation. """ qw, qx, qy, qz = self.quaternion theta = 2 * np.arccos(qw) omega = np.array([1,0,0]) if theta > 0: rx = qx / np.sqrt(1.0 - qw**2) ry = qy / np.sqrt(1.0 - qw**2) rz = qz / np.sqrt(1.0 - qw**2) omega = np.array([rx, ry, rz]) return theta * omega
:obj:`numpy.ndarray` of float: The axis-angle representation for the rotation.
def extract_interesting_date_ranges(returns): """ Extracts returns based on interesting events. See gen_date_range_interesting. Parameters ---------- returns : pd.Series Daily returns of the strategy, noncumulative. - See full explanation in tears.create_full_tear_sheet. Returns ------- ranges : OrderedDict Date ranges, with returns, of all valid events. """ returns_dupe = returns.copy() returns_dupe.index = returns_dupe.index.map(pd.Timestamp) ranges = OrderedDict() for name, (start, end) in PERIODS.items(): try: period = returns_dupe.loc[start:end] if len(period) == 0: continue ranges[name] = period except BaseException: continue return ranges
Extracts returns based on interesting events. See gen_date_range_interesting. Parameters ---------- returns : pd.Series Daily returns of the strategy, noncumulative. - See full explanation in tears.create_full_tear_sheet. Returns ------- ranges : OrderedDict Date ranges, with returns, of all valid events.
def get(self, endpoint='', url='', params=None, use_api_key=False): """Perform a get for a json API endpoint. :param string endpoint: Target endpoint. (Optional). :param string url: Override the endpoint and provide the full url (eg for pagination). (Optional). :param dict params: Provide parameters to pass to the request. (Optional). :return: Response json. :rtype: ``dict`` """ return self._request('get', endpoint, url, params=params, use_api_key=use_api_key)
Perform a get for a json API endpoint. :param string endpoint: Target endpoint. (Optional). :param string url: Override the endpoint and provide the full url (eg for pagination). (Optional). :param dict params: Provide parameters to pass to the request. (Optional). :return: Response json. :rtype: ``dict``
def read_zipfile(self, encoding='utf8'): """ READ FIRST FILE IN ZIP FILE :param encoding: :return: STRING """ from zipfile import ZipFile with ZipFile(self.abspath) as zipped: for num, zip_name in enumerate(zipped.namelist()): return zipped.open(zip_name).read().decode(encoding)
READ FIRST FILE IN ZIP FILE :param encoding: :return: STRING
def report_many(self, event_list, metadata=None, block=None): """ Reports all the given events to Alooma by formatting them properly and placing them in the buffer to be sent by the Sender instance :param event_list: A list of dicts / strings representing events :param metadata: (Optional) A dict with extra metadata to be attached to the event :param block: (Optional) If True, the function will block the thread until the event buffer has space for the event. If False, reported events are discarded if the queue is full. Defaults to None, which uses the global `block` parameter given in the `init`. :return: A list with tuples, each containing a failed event and its original index. An empty list means success """ failed_list = [] for index, event in enumerate(event_list): queued_successfully = self.report(event, metadata, block) if not queued_successfully: failed_list.append((index, event)) return failed_list
Reports all the given events to Alooma by formatting them properly and placing them in the buffer to be sent by the Sender instance :param event_list: A list of dicts / strings representing events :param metadata: (Optional) A dict with extra metadata to be attached to the event :param block: (Optional) If True, the function will block the thread until the event buffer has space for the event. If False, reported events are discarded if the queue is full. Defaults to None, which uses the global `block` parameter given in the `init`. :return: A list with tuples, each containing a failed event and its original index. An empty list means success
def _f_gene(sid, prefix="G_"): """Clips gene prefix from id.""" sid = sid.replace(SBML_DOT, ".") return _clip(sid, prefix)
Clips gene prefix from id.
def _recurse(data, obj): """Iterates over all children of the current object, gathers the contents contributing to the resulting PGFPlots file, and returns those. """ content = _ContentManager() for child in obj.get_children(): # Some patches are Spines, too; skip those entirely. # See <https://github.com/nschloe/matplotlib2tikz/issues/277>. if isinstance(child, mpl.spines.Spine): continue if isinstance(child, mpl.axes.Axes): ax = axes.Axes(data, child) if ax.is_colorbar: continue # add extra axis options if data["extra axis options [base]"]: ax.axis_options.extend(data["extra axis options [base]"]) data["current mpl axes obj"] = child data["current axes"] = ax # Run through the child objects, gather the content. data, children_content = _recurse(data, child) # populate content and add axis environment if desired if data["add axis environment"]: content.extend( ax.get_begin_code() + children_content + [ax.get_end_code(data)], 0 ) else: content.extend(children_content, 0) # print axis environment options, if told to show infos if data["show_info"]: print("=========================================================") print("These would have been the properties of the environment:") print("".join(ax.get_begin_code()[1:])) print("=========================================================") elif isinstance(child, mpl.lines.Line2D): data, cont = line2d.draw_line2d(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.image.AxesImage): data, cont = img.draw_image(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.patches.Patch): data, cont = patch.draw_patch(data, child) content.extend(cont, child.get_zorder()) elif isinstance( child, (mpl.collections.PatchCollection, mpl.collections.PolyCollection) ): data, cont = patch.draw_patchcollection(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.collections.PathCollection): data, cont = path.draw_pathcollection(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.collections.LineCollection): data, cont = line2d.draw_linecollection(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.collections.QuadMesh): data, cont = qmsh.draw_quadmesh(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, mpl.legend.Legend): data = legend.draw_legend(data, child) if data["legend colors"]: content.extend(data["legend colors"], 0) elif isinstance(child, (mpl.text.Text, mpl.text.Annotation)): data, cont = text.draw_text(data, child) content.extend(cont, child.get_zorder()) elif isinstance(child, (mpl.axis.XAxis, mpl.axis.YAxis)): pass else: warnings.warn( "matplotlib2tikz: Don't know how to handle object {}.".format( type(child) ) ) return data, content.flatten()
Iterates over all children of the current object, gathers the contents contributing to the resulting PGFPlots file, and returns those.
def patch_api_service(self, name, body, **kwargs): # noqa: E501 """patch_api_service # noqa: E501 partially update the specified APIService # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.patch_api_service(name, body, async_req=True) >>> result = thread.get() :param async_req bool :param str name: name of the APIService (required) :param UNKNOWN_BASE_TYPE body: (required) :param str pretty: If 'true', then the output is pretty printed. :param str dry_run: When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed :return: V1beta1APIService If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.patch_api_service_with_http_info(name, body, **kwargs) # noqa: E501 else: (data) = self.patch_api_service_with_http_info(name, body, **kwargs) # noqa: E501 return data
patch_api_service # noqa: E501 partially update the specified APIService # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.patch_api_service(name, body, async_req=True) >>> result = thread.get() :param async_req bool :param str name: name of the APIService (required) :param UNKNOWN_BASE_TYPE body: (required) :param str pretty: If 'true', then the output is pretty printed. :param str dry_run: When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed :return: V1beta1APIService If the method is called asynchronously, returns the request thread.
def mixin_function_or_method(target, routine, name=None, isbound=False): """Mixin a routine into the target. :param routine: routine to mix in target. :param str name: mixin name. Routine name by default. :param bool isbound: If True (False by default), the mixin result is a bound method to target. """ function = None if isfunction(routine): function = routine elif ismethod(routine): function = get_method_function(routine) else: raise Mixin.MixInError( "{0} must be a function or a method.".format(routine)) if name is None: name = routine.__name__ if not isclass(target) or isbound: _type = type(target) method_args = [function, target] if PY2: method_args += _type result = MethodType(*method_args) else: if PY2: result = MethodType(function, None, target) else: result = function Mixin.set_mixin(target, result, name) return result
Mixin a routine into the target. :param routine: routine to mix in target. :param str name: mixin name. Routine name by default. :param bool isbound: If True (False by default), the mixin result is a bound method to target.
def set_tag(self, ip_dest, next_hop, **kwargs): """Set the tag value for the specified route Args: ip_dest (string): The ip address of the destination in the form of A.B.C.D/E next_hop (string): The next hop interface or ip address **kwargs['next_hop_ip'] (string): The next hop address on destination interface **kwargs['distance'] (string): Administrative distance for this route **kwargs['tag'] (string): Route tag **kwargs['route_name'] (string): Route name Returns: True if the operation succeeds, otherwise False. Notes: Any existing route_name value must be included in call to set_tag, otherwise the tag will be reset by the call to EOS. """ # Call _set_route with the new tag information return self._set_route(ip_dest, next_hop, **kwargs)
Set the tag value for the specified route Args: ip_dest (string): The ip address of the destination in the form of A.B.C.D/E next_hop (string): The next hop interface or ip address **kwargs['next_hop_ip'] (string): The next hop address on destination interface **kwargs['distance'] (string): Administrative distance for this route **kwargs['tag'] (string): Route tag **kwargs['route_name'] (string): Route name Returns: True if the operation succeeds, otherwise False. Notes: Any existing route_name value must be included in call to set_tag, otherwise the tag will be reset by the call to EOS.
def get_submissions(self, url): """ Connects to Reddit and gets a JSON representation of submissions. This JSON data is then processed and returned. url: A url that requests for submissions should be sent to. """ response = self.client.get(url, params={'limit': self.options['limit']}) submissions = [x['data'] for x in response.json()['data']['children']] return submissions
Connects to Reddit and gets a JSON representation of submissions. This JSON data is then processed and returned. url: A url that requests for submissions should be sent to.
def distortImage(self, image): ''' opposite of 'correct' ''' image = imread(image) (imgHeight, imgWidth) = image.shape[:2] mapx, mapy = self.getDistortRectifyMap(imgWidth, imgHeight) return cv2.remap(image, mapx, mapy, cv2.INTER_LINEAR, borderValue=(0, 0, 0))
opposite of 'correct'
def peek_step(self, val: ArrayValue, sn: "DataNode") -> Tuple[Optional[Value], "DataNode"]: """Return entry value addressed by the receiver + its schema node. Args: val: Current value (array). sn: Current schema node. """ try: return val[self.index], sn except (IndexError, KeyError, TypeError): return None, sn
Return entry value addressed by the receiver + its schema node. Args: val: Current value (array). sn: Current schema node.
def untag(name, tag_name): """ Remove the given tag from the given metric. Return True if the metric was tagged, False otherwise """ with LOCK: by_tag = TAGS.get(tag_name, None) if not by_tag: return False try: by_tag.remove(name) # remove the tag if no associations left if not by_tag: TAGS.pop(tag_name) return True except KeyError: return False
Remove the given tag from the given metric. Return True if the metric was tagged, False otherwise
def _compute_subplot_domains(widths, spacing): """ Compute normalized domain tuples for a list of widths and a subplot spacing value Parameters ---------- widths: list of float List of the desired withs of each subplot. The length of this list is also the specification of the number of desired subplots spacing: float Spacing between subplots in normalized coordinates Returns ------- list of tuple of float """ # normalize widths widths_sum = float(sum(widths)) total_spacing = (len(widths) - 1) * spacing widths = [(w / widths_sum)*(1-total_spacing) for w in widths] domains = [] for c in range(len(widths)): domain_start = c * spacing + sum(widths[:c]) domain_stop = min(1, domain_start + widths[c]) domains.append((domain_start, domain_stop)) return domains
Compute normalized domain tuples for a list of widths and a subplot spacing value Parameters ---------- widths: list of float List of the desired withs of each subplot. The length of this list is also the specification of the number of desired subplots spacing: float Spacing between subplots in normalized coordinates Returns ------- list of tuple of float
def indication(self, pdu): """Send a message.""" if _debug: Node._debug("indication(%s) %r", self.name, pdu) # make sure we're connected if not self.lan: raise ConfigurationError("unbound node") # if the pduSource is unset, fill in our address, otherwise # leave it alone to allow for simulated spoofing if pdu.pduSource is None: pdu.pduSource = self.address elif (not self.spoofing) and (pdu.pduSource != self.address): raise RuntimeError("spoofing address conflict") # actual network delivery is a zero-delay task OneShotFunction(self.lan.process_pdu, pdu)
Send a message.
def add(self, child): """ Adds a typed child object to the component type. @param child: Child object to be added. """ if isinstance(child, FatComponent): self.add_child_component(child) else: Fat.add(self, child)
Adds a typed child object to the component type. @param child: Child object to be added.
def gene_filter(self, query, mongo_query): """ Adds gene-related filters to the query object Args: query(dict): a dictionary of query filters specified by the users mongo_query(dict): the query that is going to be submitted to the database Returns: mongo_query(dict): returned object contains gene and panel-related filters """ LOG.debug('Adding panel and genes-related parameters to the query') gene_query = [] if query.get('hgnc_symbols') and query.get('gene_panels'): gene_query.append({'hgnc_symbols': {'$in': query['hgnc_symbols']}}) gene_query.append({'panels': {'$in': query['gene_panels']}}) mongo_query['$or']=gene_query else: if query.get('hgnc_symbols'): hgnc_symbols = query['hgnc_symbols'] mongo_query['hgnc_symbols'] = {'$in': hgnc_symbols} LOG.debug("Adding hgnc_symbols: %s to query" % ', '.join(hgnc_symbols)) if query.get('gene_panels'): gene_panels = query['gene_panels'] mongo_query['panels'] = {'$in': gene_panels} return gene_query
Adds gene-related filters to the query object Args: query(dict): a dictionary of query filters specified by the users mongo_query(dict): the query that is going to be submitted to the database Returns: mongo_query(dict): returned object contains gene and panel-related filters
def start(self): """Start listening from stream""" if self.stream is None: from pyaudio import PyAudio, paInt16 self.pa = PyAudio() self.stream = self.pa.open( 16000, 1, paInt16, True, frames_per_buffer=self.chunk_size ) self._wrap_stream_read(self.stream) self.engine.start() self.running = True self.is_paused = False self.thread = Thread(target=self._handle_predictions) self.thread.daemon = True self.thread.start()
Start listening from stream
def about_axis(cls, center, angle, axis, invert=False): """Create transformation that represents a rotation about an axis Arguments: | ``center`` -- Point on the axis | ``angle`` -- Rotation angle | ``axis`` -- Rotation axis | ``invert`` -- When True, an inversion rotation is constructed [default=False] """ return Translation(center) * \ Rotation.from_properties(angle, axis, invert) * \ Translation(-center)
Create transformation that represents a rotation about an axis Arguments: | ``center`` -- Point on the axis | ``angle`` -- Rotation angle | ``axis`` -- Rotation axis | ``invert`` -- When True, an inversion rotation is constructed [default=False]
def par_y1step(i): r"""Minimise Augmented Lagrangian with respect to :math:`\mathbf{y}_{1,G_i}`, one of the disjoint problems of optimizing :math:`\mathbf{y}_1`. Parameters ---------- i : int Index of grouping to update """ global mp_Y1 grpind = slice(mp_grp[i], mp_grp[i+1]) XU1 = mp_X[grpind] + 1/mp_alpha*mp_U1[grpind] if mp_wl1.shape[mp_axisM] is 1: gamma = mp_lmbda/(mp_alpha**2*mp_rho)*mp_wl1 else: gamma = mp_lmbda/(mp_alpha**2*mp_rho)*mp_wl1[grpind] Y1 = sp.prox_l1(XU1, gamma) if mp_NonNegCoef: Y1[Y1 < 0.0] = 0.0 if mp_NoBndryCross: for n in range(len(mp_Nv)): Y1[(slice(None),) + (slice(None),)*n + (slice(1-mp_Dshp[n], None),)] = 0.0 mp_Y1[mp_grp[i]:mp_grp[i+1]] = Y1
r"""Minimise Augmented Lagrangian with respect to :math:`\mathbf{y}_{1,G_i}`, one of the disjoint problems of optimizing :math:`\mathbf{y}_1`. Parameters ---------- i : int Index of grouping to update
def pot_for_component(pot, q, component=1, reverse=False): """ q for secondaries should already be flipped (via q_for_component) """ # currently only used by legacy wrapper: consider moving/removing if component==1: return pot elif component==2: if reverse: return pot/q + 0.5*(q-1)/q else: return q*pot - 0.5 * (q-1) else: raise NotImplementedError
q for secondaries should already be flipped (via q_for_component)