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rhayes777/PyAutoFit
autofit/mapper/model_mapper.py
ModelMapper.prior_prior_model_name_dict
def prior_prior_model_name_dict(self): """ Returns ------- prior_prior_model_name_dict: {Prior: str} A dictionary mapping priors to the names of associated prior models. Each prior will only have one prior model name; if a prior is shared by two prior models then one of those prior model's names will be in this dictionary. """ prior_prior_model_name_dict = {prior_tuple.prior: prior_model_tuple.name for prior_model_tuple in self.flat_prior_model_tuples for prior_tuple in prior_model_tuple.prior_model.prior_tuples} prior_list_prior_model_name_dict = { prior_tuple.value: "{}_{}".format(list_prior_model_tuple.name, label_prior_model_tuple.name) for list_prior_model_tuple in self.list_prior_model_tuples for label_prior_model_tuple in list_prior_model_tuple.value.label_prior_model_tuples for prior_tuple in label_prior_model_tuple.value.prior_tuples} prior_prior_model_name_dict.update(prior_list_prior_model_name_dict) return prior_prior_model_name_dict
python
def prior_prior_model_name_dict(self): """ Returns ------- prior_prior_model_name_dict: {Prior: str} A dictionary mapping priors to the names of associated prior models. Each prior will only have one prior model name; if a prior is shared by two prior models then one of those prior model's names will be in this dictionary. """ prior_prior_model_name_dict = {prior_tuple.prior: prior_model_tuple.name for prior_model_tuple in self.flat_prior_model_tuples for prior_tuple in prior_model_tuple.prior_model.prior_tuples} prior_list_prior_model_name_dict = { prior_tuple.value: "{}_{}".format(list_prior_model_tuple.name, label_prior_model_tuple.name) for list_prior_model_tuple in self.list_prior_model_tuples for label_prior_model_tuple in list_prior_model_tuple.value.label_prior_model_tuples for prior_tuple in label_prior_model_tuple.value.prior_tuples} prior_prior_model_name_dict.update(prior_list_prior_model_name_dict) return prior_prior_model_name_dict
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src/IoticAgent/IOT/Point.py
Point.get_meta
def get_meta(self): """Get the metadata object for this Point Returns a [PointMeta](PointMeta.m.html#IoticAgent.IOT.PointMeta.PointMeta) object - OR - Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException) containing the error if the infrastructure detects a problem Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException) if there is a communications problem between you and the infrastructure """ rdf = self.get_meta_rdf(fmt='n3') return PointMeta(self, rdf, self._client.default_lang, fmt='n3')
python
def get_meta(self): """Get the metadata object for this Point Returns a [PointMeta](PointMeta.m.html#IoticAgent.IOT.PointMeta.PointMeta) object - OR - Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException) containing the error if the infrastructure detects a problem Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException) if there is a communications problem between you and the infrastructure """ rdf = self.get_meta_rdf(fmt='n3') return PointMeta(self, rdf, self._client.default_lang, fmt='n3')
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allenai/allennlp
allennlp/modules/token_embedders/embedding.py
_read_embeddings_from_text_file
def _read_embeddings_from_text_file(file_uri: str, embedding_dim: int, vocab: Vocabulary, namespace: str = "tokens") -> torch.FloatTensor: """ Read pre-trained word vectors from an eventually compressed text file, possibly contained inside an archive with multiple files. The text file is assumed to be utf-8 encoded with space-separated fields: [word] [dim 1] [dim 2] ... Lines that contain more numerical tokens than ``embedding_dim`` raise a warning and are skipped. The remainder of the docstring is identical to ``_read_pretrained_embeddings_file``. """ tokens_to_keep = set(vocab.get_index_to_token_vocabulary(namespace).values()) vocab_size = vocab.get_vocab_size(namespace) embeddings = {} # First we read the embeddings from the file, only keeping vectors for the words we need. logger.info("Reading pretrained embeddings from file") with EmbeddingsTextFile(file_uri) as embeddings_file: for line in Tqdm.tqdm(embeddings_file): token = line.split(' ', 1)[0] if token in tokens_to_keep: fields = line.rstrip().split(' ') if len(fields) - 1 != embedding_dim: # Sometimes there are funny unicode parsing problems that lead to different # fields lengths (e.g., a word with a unicode space character that splits # into more than one column). We skip those lines. Note that if you have # some kind of long header, this could result in all of your lines getting # skipped. It's hard to check for that here; you just have to look in the # embedding_misses_file and at the model summary to make sure things look # like they are supposed to. logger.warning("Found line with wrong number of dimensions (expected: %d; actual: %d): %s", embedding_dim, len(fields) - 1, line) continue vector = numpy.asarray(fields[1:], dtype='float32') embeddings[token] = vector if not embeddings: raise ConfigurationError("No embeddings of correct dimension found; you probably " "misspecified your embedding_dim parameter, or didn't " "pre-populate your Vocabulary") all_embeddings = numpy.asarray(list(embeddings.values())) embeddings_mean = float(numpy.mean(all_embeddings)) embeddings_std = float(numpy.std(all_embeddings)) # Now we initialize the weight matrix for an embedding layer, starting with random vectors, # then filling in the word vectors we just read. logger.info("Initializing pre-trained embedding layer") embedding_matrix = torch.FloatTensor(vocab_size, embedding_dim).normal_(embeddings_mean, embeddings_std) num_tokens_found = 0 index_to_token = vocab.get_index_to_token_vocabulary(namespace) for i in range(vocab_size): token = index_to_token[i] # If we don't have a pre-trained vector for this word, we'll just leave this row alone, # so the word has a random initialization. if token in embeddings: embedding_matrix[i] = torch.FloatTensor(embeddings[token]) num_tokens_found += 1 else: logger.debug("Token %s was not found in the embedding file. Initialising randomly.", token) logger.info("Pretrained embeddings were found for %d out of %d tokens", num_tokens_found, vocab_size) return embedding_matrix
python
def _read_embeddings_from_text_file(file_uri: str, embedding_dim: int, vocab: Vocabulary, namespace: str = "tokens") -> torch.FloatTensor: """ Read pre-trained word vectors from an eventually compressed text file, possibly contained inside an archive with multiple files. The text file is assumed to be utf-8 encoded with space-separated fields: [word] [dim 1] [dim 2] ... Lines that contain more numerical tokens than ``embedding_dim`` raise a warning and are skipped. The remainder of the docstring is identical to ``_read_pretrained_embeddings_file``. """ tokens_to_keep = set(vocab.get_index_to_token_vocabulary(namespace).values()) vocab_size = vocab.get_vocab_size(namespace) embeddings = {} # First we read the embeddings from the file, only keeping vectors for the words we need. logger.info("Reading pretrained embeddings from file") with EmbeddingsTextFile(file_uri) as embeddings_file: for line in Tqdm.tqdm(embeddings_file): token = line.split(' ', 1)[0] if token in tokens_to_keep: fields = line.rstrip().split(' ') if len(fields) - 1 != embedding_dim: # Sometimes there are funny unicode parsing problems that lead to different # fields lengths (e.g., a word with a unicode space character that splits # into more than one column). We skip those lines. Note that if you have # some kind of long header, this could result in all of your lines getting # skipped. It's hard to check for that here; you just have to look in the # embedding_misses_file and at the model summary to make sure things look # like they are supposed to. logger.warning("Found line with wrong number of dimensions (expected: %d; actual: %d): %s", embedding_dim, len(fields) - 1, line) continue vector = numpy.asarray(fields[1:], dtype='float32') embeddings[token] = vector if not embeddings: raise ConfigurationError("No embeddings of correct dimension found; you probably " "misspecified your embedding_dim parameter, or didn't " "pre-populate your Vocabulary") all_embeddings = numpy.asarray(list(embeddings.values())) embeddings_mean = float(numpy.mean(all_embeddings)) embeddings_std = float(numpy.std(all_embeddings)) # Now we initialize the weight matrix for an embedding layer, starting with random vectors, # then filling in the word vectors we just read. logger.info("Initializing pre-trained embedding layer") embedding_matrix = torch.FloatTensor(vocab_size, embedding_dim).normal_(embeddings_mean, embeddings_std) num_tokens_found = 0 index_to_token = vocab.get_index_to_token_vocabulary(namespace) for i in range(vocab_size): token = index_to_token[i] # If we don't have a pre-trained vector for this word, we'll just leave this row alone, # so the word has a random initialization. if token in embeddings: embedding_matrix[i] = torch.FloatTensor(embeddings[token]) num_tokens_found += 1 else: logger.debug("Token %s was not found in the embedding file. Initialising randomly.", token) logger.info("Pretrained embeddings were found for %d out of %d tokens", num_tokens_found, vocab_size) return embedding_matrix
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fuzeman/PyUPnP
pyupnp/lict.py
Lict.setdefault
def setdefault(self, k, d=None): """ D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D """ if k not in self._col_dict: self._set_key(k, d) return self._col_dict.get(k)
python
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horazont/aioxmpp
aioxmpp/xso/model.py
Attr.handle_missing
def handle_missing(self, instance, ctx): """ Handle a missing attribute on `instance`. This is called whenever no value for the attribute is found during parsing. The call to :meth:`missing` is independent of the value of `required`. If the `missing` callback is not :data:`None`, it is called with the `instance` and the `ctx` as arguments. If the returned value is not :data:`None`, it is used as the value of the attribute (validation takes place as if the value had been set from the code, not as if the value had been received from XML) and the handler returns. If the `missing` callback is :data:`None` or returns :data:`None`, the handling continues as normal: if `required` is true, a :class:`ValueError` is raised. """ if self.missing is not None: value = self.missing(instance, ctx) if value is not None: self._set_from_code(instance, value) return if self.default is _PropBase.NO_DEFAULT: raise ValueError("missing attribute {} on {}".format( tag_to_str(self.tag), tag_to_str(instance.TAG), ))
python
def handle_missing(self, instance, ctx): """ Handle a missing attribute on `instance`. This is called whenever no value for the attribute is found during parsing. The call to :meth:`missing` is independent of the value of `required`. If the `missing` callback is not :data:`None`, it is called with the `instance` and the `ctx` as arguments. If the returned value is not :data:`None`, it is used as the value of the attribute (validation takes place as if the value had been set from the code, not as if the value had been received from XML) and the handler returns. If the `missing` callback is :data:`None` or returns :data:`None`, the handling continues as normal: if `required` is true, a :class:`ValueError` is raised. """ if self.missing is not None: value = self.missing(instance, ctx) if value is not None: self._set_from_code(instance, value) return if self.default is _PropBase.NO_DEFAULT: raise ValueError("missing attribute {} on {}".format( tag_to_str(self.tag), tag_to_str(instance.TAG), ))
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Metatab/tableintuit
tableintuit/stats.py
Stats.run
def run(self): """ Run the stats. The source must yield Row proxies. """ self._func, self._func_code = self.build() def process_row(row): try: self._func(self._stats, row) except TypeError as e: raise TypeError("Failed for '{}'; {}".format(self._func_code, e)) except KeyError: raise KeyError( 'Failed to find key in row. headers = "{}", code = "{}" ' .format(list(row.keys()), self._func_code)) except Exception as e: raise type(e)( 'General exception in stats. headers = "{}", code = "{}": {} ' .format(list(row.keys()), self._func_code, e)) # Use all of the rows in the source if self._sample_size is None: for i, row in enumerate(self._source): process_row(row) # Use a sample of rows, evenly distributed though the source else: skip_rate = self._sample_size / self._n_rows i = 0 skip = skip_rate for j, row in enumerate(self._source): skip += skip_rate if skip >= 1: skip -= 1 i += 1 process_row(row) if i < 5000: # Since the hist bins aren't built until 5K row for k, v in self._stats.items(): v._build_hist_bins() return self
python
def run(self): """ Run the stats. The source must yield Row proxies. """ self._func, self._func_code = self.build() def process_row(row): try: self._func(self._stats, row) except TypeError as e: raise TypeError("Failed for '{}'; {}".format(self._func_code, e)) except KeyError: raise KeyError( 'Failed to find key in row. headers = "{}", code = "{}" ' .format(list(row.keys()), self._func_code)) except Exception as e: raise type(e)( 'General exception in stats. headers = "{}", code = "{}": {} ' .format(list(row.keys()), self._func_code, e)) # Use all of the rows in the source if self._sample_size is None: for i, row in enumerate(self._source): process_row(row) # Use a sample of rows, evenly distributed though the source else: skip_rate = self._sample_size / self._n_rows i = 0 skip = skip_rate for j, row in enumerate(self._source): skip += skip_rate if skip >= 1: skip -= 1 i += 1 process_row(row) if i < 5000: # Since the hist bins aren't built until 5K row for k, v in self._stats.items(): v._build_hist_bins() return self
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stevearc/dql
dql/engine.py
Engine._explain
def _explain(self, tree): """ Set up the engine to do a dry run of a query """ self._explaining = True self._call_list = [] old_call = self.connection.call def fake_call(command, **kwargs): """ Replacement for connection.call that logs args """ if command == "describe_table": return old_call(command, **kwargs) self._call_list.append((command, kwargs)) raise ExplainSignal self.connection.call = fake_call try: ret = self._run(tree[1]) try: list(ret) except TypeError: pass finally: self.connection.call = old_call self._explaining = False
python
def _explain(self, tree): """ Set up the engine to do a dry run of a query """ self._explaining = True self._call_list = [] old_call = self.connection.call def fake_call(command, **kwargs): """ Replacement for connection.call that logs args """ if command == "describe_table": return old_call(command, **kwargs) self._call_list.append((command, kwargs)) raise ExplainSignal self.connection.call = fake_call try: ret = self._run(tree[1]) try: list(ret) except TypeError: pass finally: self.connection.call = old_call self._explaining = False
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salt/utils/dns.py
_lookup_drill
def _lookup_drill(name, rdtype, timeout=None, servers=None, secure=None): ''' Use drill to lookup addresses :param name: Name of record to search :param rdtype: DNS record type :param timeout: command return timeout :param servers: [] of servers to use :return: [] of records or False if error ''' cmd = 'drill ' if secure: cmd += '-D -o ad ' cmd += '{0} {1} '.format(rdtype, name) if servers: cmd += ''.join(['@{0} '.format(srv) for srv in servers]) cmd = __salt__['cmd.run_all']( cmd, timeout=timeout, python_shell=False, output_loglevel='quiet') if cmd['retcode'] != 0: log.warning('drill returned (%s): %s', cmd['retcode'], cmd['stderr']) return False lookup_res = iter(cmd['stdout'].splitlines()) validated = False res = [] try: line = '' while 'ANSWER SECTION' not in line: line = next(lookup_res) while True: line = next(lookup_res) line = line.strip() if not line or line.startswith(';;'): break l_type, l_rec = line.split(None, 4)[-2:] if l_type == 'CNAME' and rdtype != 'CNAME': continue elif l_type == 'RRSIG': validated = True continue elif l_type != rdtype: raise ValueError('Invalid DNS type {}'.format(rdtype)) res.append(_data_clean(l_rec)) except StopIteration: pass if res and secure and not validated: return False else: return res
python
def _lookup_drill(name, rdtype, timeout=None, servers=None, secure=None): ''' Use drill to lookup addresses :param name: Name of record to search :param rdtype: DNS record type :param timeout: command return timeout :param servers: [] of servers to use :return: [] of records or False if error ''' cmd = 'drill ' if secure: cmd += '-D -o ad ' cmd += '{0} {1} '.format(rdtype, name) if servers: cmd += ''.join(['@{0} '.format(srv) for srv in servers]) cmd = __salt__['cmd.run_all']( cmd, timeout=timeout, python_shell=False, output_loglevel='quiet') if cmd['retcode'] != 0: log.warning('drill returned (%s): %s', cmd['retcode'], cmd['stderr']) return False lookup_res = iter(cmd['stdout'].splitlines()) validated = False res = [] try: line = '' while 'ANSWER SECTION' not in line: line = next(lookup_res) while True: line = next(lookup_res) line = line.strip() if not line or line.startswith(';;'): break l_type, l_rec = line.split(None, 4)[-2:] if l_type == 'CNAME' and rdtype != 'CNAME': continue elif l_type == 'RRSIG': validated = True continue elif l_type != rdtype: raise ValueError('Invalid DNS type {}'.format(rdtype)) res.append(_data_clean(l_rec)) except StopIteration: pass if res and secure and not validated: return False else: return res
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rbarrois/mpdlcd
mpdlcd/mpdhooks.py
MPDHook.handle
def handle(self, client, subhooks=()): """Handle a new update. Fetches new data from the client, then compares it to the previous lookup. Returns: (bool, new_data): whether changes occurred, and the new value. """ new_data = self.fetch(client) # Holds the list of updated fields. updated = {} if not subhooks: # We always want to compare to previous values. subhooks = [self.name] for subhook in subhooks: new_key = self.extract_key(new_data, subhook) if new_key != self.previous_keys.get(subhook): updated[subhook] = new_key if updated: logger.debug("Hook %s: data changed from %r to %r", self.name, self.previous_keys, updated) self.previous_keys.update(updated) return (True, new_data) return (False, None)
python
def handle(self, client, subhooks=()): """Handle a new update. Fetches new data from the client, then compares it to the previous lookup. Returns: (bool, new_data): whether changes occurred, and the new value. """ new_data = self.fetch(client) # Holds the list of updated fields. updated = {} if not subhooks: # We always want to compare to previous values. subhooks = [self.name] for subhook in subhooks: new_key = self.extract_key(new_data, subhook) if new_key != self.previous_keys.get(subhook): updated[subhook] = new_key if updated: logger.debug("Hook %s: data changed from %r to %r", self.name, self.previous_keys, updated) self.previous_keys.update(updated) return (True, new_data) return (False, None)
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XRDX/pyleap
pyleap/util.py
repeat
def repeat(f, dt=1/60): """ 重复执行函数f,时间间隔dt """ stop(f) pyglet.clock.schedule_interval(f, dt)
python
def repeat(f, dt=1/60): """ 重复执行函数f,时间间隔dt """ stop(f) pyglet.clock.schedule_interval(f, dt)
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重复执行函数f,时间间隔dt
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train
https://github.com/XRDX/pyleap/blob/234c722cfbe66814254ab0d8f67d16b0b774f4d5/pyleap/util.py#L13-L16
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mezz64/pyEmby
pyemby/server.py
EmbyServer.api_request
async def api_request(self, url, params): """Make api fetch request.""" request = None try: with async_timeout.timeout(DEFAULT_TIMEOUT, loop=self._event_loop): request = await self._api_session.get( url, params=params) if request.status != 200: _LOGGER.error('Error fetching Emby data: %s', request.status) return None request_json = await request.json() if 'error' in request_json: _LOGGER.error('Error converting Emby data to json: %s: %s', request_json['error']['code'], request_json['error']['message']) return None return request_json except (aiohttp.ClientError, asyncio.TimeoutError, ConnectionRefusedError) as err: _LOGGER.error('Error fetching Emby data: %s', err) return None
python
async def api_request(self, url, params): """Make api fetch request.""" request = None try: with async_timeout.timeout(DEFAULT_TIMEOUT, loop=self._event_loop): request = await self._api_session.get( url, params=params) if request.status != 200: _LOGGER.error('Error fetching Emby data: %s', request.status) return None request_json = await request.json() if 'error' in request_json: _LOGGER.error('Error converting Emby data to json: %s: %s', request_json['error']['code'], request_json['error']['message']) return None return request_json except (aiohttp.ClientError, asyncio.TimeoutError, ConnectionRefusedError) as err: _LOGGER.error('Error fetching Emby data: %s', err) return None
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train
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myusuf3/delorean
delorean/interface.py
range_monthly
def range_monthly(start=None, stop=None, timezone='UTC', count=None): """ This an alternative way to generating sets of Delorean objects with MONTHLY stops """ return stops(start=start, stop=stop, freq=MONTHLY, timezone=timezone, count=count)
python
def range_monthly(start=None, stop=None, timezone='UTC', count=None): """ This an alternative way to generating sets of Delorean objects with MONTHLY stops """ return stops(start=start, stop=stop, freq=MONTHLY, timezone=timezone, count=count)
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This an alternative way to generating sets of Delorean objects with MONTHLY stops
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train
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suds-community/suds
suds/bindings/binding.py
Binding.envelope
def envelope(self, header, body): """ Build the B{<Envelope/>} for a SOAP outbound message. @param header: The SOAP message B{header}. @type header: L{Element} @param body: The SOAP message B{body}. @type body: L{Element} @return: The SOAP envelope containing the body and header. @rtype: L{Element} """ env = Element("Envelope", ns=envns) env.addPrefix(Namespace.xsins[0], Namespace.xsins[1]) env.append(header) env.append(body) return env
python
def envelope(self, header, body): """ Build the B{<Envelope/>} for a SOAP outbound message. @param header: The SOAP message B{header}. @type header: L{Element} @param body: The SOAP message B{body}. @type body: L{Element} @return: The SOAP envelope containing the body and header. @rtype: L{Element} """ env = Element("Envelope", ns=envns) env.addPrefix(Namespace.xsins[0], Namespace.xsins[1]) env.append(header) env.append(body) return env
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train
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6,713
DistrictDataLabs/yellowbrick
yellowbrick/model_selection/validation_curve.py
ValidationCurve.fit
def fit(self, X, y=None): """ Fits the validation curve with the wrapped estimator and parameter array to the specified data. Draws training and test score curves and saves the scores to the visualizer. Parameters ---------- X : array-like, shape (n_samples, n_features) Training vector, where n_samples is the number of samples and n_features is the number of features. y : array-like, shape (n_samples) or (n_samples, n_features), optional Target relative to X for classification or regression; None for unsupervised learning. Returns ------- self : instance Returns the instance of the validation curve visualizer for use in pipelines and other sequential transformers. """ # arguments to pass to sk_validation_curve skvc_kwargs = { key: self.get_params()[key] for key in ( 'param_name', 'param_range', 'groups', 'cv', 'scoring', 'n_jobs', 'pre_dispatch', ) } # compute the validation curve and store scores curve = sk_validation_curve(self.estimator, X, y, **skvc_kwargs) self.train_scores_, self.test_scores_ = curve # compute the mean and standard deviation of the training data self.train_scores_mean_ = np.mean(self.train_scores_, axis=1) self.train_scores_std_ = np.std(self.train_scores_, axis=1) # compute the mean and standard deviation of the test data self.test_scores_mean_ = np.mean(self.test_scores_, axis=1) self.test_scores_std_ = np.std(self.test_scores_, axis=1) # draw the curves on the current axes self.draw() return self
python
def fit(self, X, y=None): """ Fits the validation curve with the wrapped estimator and parameter array to the specified data. Draws training and test score curves and saves the scores to the visualizer. Parameters ---------- X : array-like, shape (n_samples, n_features) Training vector, where n_samples is the number of samples and n_features is the number of features. y : array-like, shape (n_samples) or (n_samples, n_features), optional Target relative to X for classification or regression; None for unsupervised learning. Returns ------- self : instance Returns the instance of the validation curve visualizer for use in pipelines and other sequential transformers. """ # arguments to pass to sk_validation_curve skvc_kwargs = { key: self.get_params()[key] for key in ( 'param_name', 'param_range', 'groups', 'cv', 'scoring', 'n_jobs', 'pre_dispatch', ) } # compute the validation curve and store scores curve = sk_validation_curve(self.estimator, X, y, **skvc_kwargs) self.train_scores_, self.test_scores_ = curve # compute the mean and standard deviation of the training data self.train_scores_mean_ = np.mean(self.train_scores_, axis=1) self.train_scores_std_ = np.std(self.train_scores_, axis=1) # compute the mean and standard deviation of the test data self.test_scores_mean_ = np.mean(self.test_scores_, axis=1) self.test_scores_std_ = np.std(self.test_scores_, axis=1) # draw the curves on the current axes self.draw() return self
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gns3server/compute/base_node.py
BaseNode.create
def create(self): """ Creates the node. """ log.info("{module}: {name} [{id}] created".format(module=self.manager.module_name, name=self.name, id=self.id))
python
def create(self): """ Creates the node. """ log.info("{module}: {name} [{id}] created".format(module=self.manager.module_name, name=self.name, id=self.id))
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nginx.py
Container.add
def add(self, *args): """ Add object(s) to the Container. :param *args: Any objects to add to the Container. :returns: full list of Container's child objects """ self.children.extend(args) bump_child_depth(self, self._depth) return self.children
python
def add(self, *args): """ Add object(s) to the Container. :param *args: Any objects to add to the Container. :returns: full list of Container's child objects """ self.children.extend(args) bump_child_depth(self, self._depth) return self.children
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splunklib/searchcommands/search_command.py
SearchCommand.process
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python
def process(self, argv=sys.argv, ifile=sys.stdin, ofile=sys.stdout): """ Process data. :param argv: Command line arguments. :type argv: list or tuple :param ifile: Input data file. :type ifile: file :param ofile: Output data file. :type ofile: file :return: :const:`None` :rtype: NoneType """ if len(argv) > 1: self._process_protocol_v1(argv, ifile, ofile) else: self._process_protocol_v2(argv, ifile, ofile)
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editor/editor_widgets.py
ProjectConfigurationDialog.confirm_dialog
def confirm_dialog(self, emitter): """event called pressing on OK button. """ #here the user input is transferred to the dict, ready to use self.from_fields_to_dict() return super(ProjectConfigurationDialog,self).confirm_dialog(self)
python
def confirm_dialog(self, emitter): """event called pressing on OK button. """ #here the user input is transferred to the dict, ready to use self.from_fields_to_dict() return super(ProjectConfigurationDialog,self).confirm_dialog(self)
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tensor2tensor/utils/cloud_mlengine.py
_tar_and_copy
def _tar_and_copy(src_dir, target_dir): """Tar and gzip src_dir and copy to GCS target_dir.""" src_dir = src_dir.rstrip("/") target_dir = target_dir.rstrip("/") tmp_dir = tempfile.gettempdir().rstrip("/") src_base = os.path.basename(src_dir) shell_run( "tar --exclude=.git -zcf {tmp_dir}/{src_base}.tar.gz -C {src_dir} .", src_dir=src_dir, src_base=src_base, tmp_dir=tmp_dir) final_destination = "%s/%s.tar.gz" % (target_dir, src_base) shell_run( ("gsutil cp {tmp_dir}/{src_base}.tar.gz " "{final_destination}"), tmp_dir=tmp_dir, src_base=src_base, final_destination=final_destination) return final_destination
python
def _tar_and_copy(src_dir, target_dir): """Tar and gzip src_dir and copy to GCS target_dir.""" src_dir = src_dir.rstrip("/") target_dir = target_dir.rstrip("/") tmp_dir = tempfile.gettempdir().rstrip("/") src_base = os.path.basename(src_dir) shell_run( "tar --exclude=.git -zcf {tmp_dir}/{src_base}.tar.gz -C {src_dir} .", src_dir=src_dir, src_base=src_base, tmp_dir=tmp_dir) final_destination = "%s/%s.tar.gz" % (target_dir, src_base) shell_run( ("gsutil cp {tmp_dir}/{src_base}.tar.gz " "{final_destination}"), tmp_dir=tmp_dir, src_base=src_base, final_destination=final_destination) return final_destination
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wptools/query.py
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def set_status(self, action, target): """ Sets query status with format: "{domain} ({action}) {target}" """ try: target = unquote(target) except (AttributeError, TypeError): pass status = "%s (%s) %s" % (self.domain, action, target) status = status.strip().replace('\n', '') if len(status) >= self.MAXWIDTH: tail = '...' extent = self.MAXWIDTH - (len(tail) + self.RPAD) self.status = status[:extent] + tail else: self.status = status
python
def set_status(self, action, target): """ Sets query status with format: "{domain} ({action}) {target}" """ try: target = unquote(target) except (AttributeError, TypeError): pass status = "%s (%s) %s" % (self.domain, action, target) status = status.strip().replace('\n', '') if len(status) >= self.MAXWIDTH: tail = '...' extent = self.MAXWIDTH - (len(tail) + self.RPAD) self.status = status[:extent] + tail else: self.status = status
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check_manifest.py
strip_toplevel_name
def strip_toplevel_name(filelist): """Strip toplevel name from a file list. >>> strip_toplevel_name(['a', 'a/b', 'a/c', 'a/c/d']) ['b', 'c', 'c/d'] >>> strip_toplevel_name(['a/b', 'a/c', 'a/c/d']) ['b', 'c', 'c/d'] """ if not filelist: return filelist prefix = filelist[0] if '/' in prefix: prefix = prefix.partition('/')[0] + '/' names = filelist else: prefix = prefix + '/' names = filelist[1:] for name in names: if not name.startswith(prefix): raise Failure("File doesn't have the common prefix (%s): %s" % (name, prefix)) return [name[len(prefix):] for name in names]
python
def strip_toplevel_name(filelist): """Strip toplevel name from a file list. >>> strip_toplevel_name(['a', 'a/b', 'a/c', 'a/c/d']) ['b', 'c', 'c/d'] >>> strip_toplevel_name(['a/b', 'a/c', 'a/c/d']) ['b', 'c', 'c/d'] """ if not filelist: return filelist prefix = filelist[0] if '/' in prefix: prefix = prefix.partition('/')[0] + '/' names = filelist else: prefix = prefix + '/' names = filelist[1:] for name in names: if not name.startswith(prefix): raise Failure("File doesn't have the common prefix (%s): %s" % (name, prefix)) return [name[len(prefix):] for name in names]
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ec2/base.py
objects_base.get
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python
def get(cls, **kwargs): """ Generic get() for one item only >>> ec2.instances.get(name='production-web-01') <Instance: ...> """ things = cls.filter(**kwargs) if len(things) > 1: # Raise an exception if more than one object is matched raise cls.MultipleObjectsReturned elif len(things) == 0: # Rase an exception if no objects were matched raise cls.DoesNotExist return things[0]
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aerkalov/ebooklib
ebooklib/epub.py
EpubBook.get_item_with_href
def get_item_with_href(self, href): """ Returns item for defined HREF. >>> book.get_item_with_href('EPUB/document.xhtml') :Args: - href: HREF for the item we are searching for :Returns: Returns item object. Returns None if nothing was found. """ for item in self.get_items(): if item.get_name() == href: return item return None
python
def get_item_with_href(self, href): """ Returns item for defined HREF. >>> book.get_item_with_href('EPUB/document.xhtml') :Args: - href: HREF for the item we are searching for :Returns: Returns item object. Returns None if nothing was found. """ for item in self.get_items(): if item.get_name() == href: return item return None
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yamcs/yamcs-python
yamcs-client/yamcs/tmtc/model.py
Alarm.acknowledge_message
def acknowledge_message(self): """Comment provided when acknowledging the alarm.""" if (self.is_acknowledged and self._proto.acknowledgeInfo.HasField('acknowledgeMessage')): return self._proto.acknowledgeInfo.acknowledgeMessage return None
python
def acknowledge_message(self): """Comment provided when acknowledging the alarm.""" if (self.is_acknowledged and self._proto.acknowledgeInfo.HasField('acknowledgeMessage')): return self._proto.acknowledgeInfo.acknowledgeMessage return None
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iotile/coretools
iotilecore/iotile/core/dev/semver.py
SemanticVersionRange._check_insersection
def _check_insersection(self, version, ranges): """Check that a version is inside all of a list of ranges""" for ver_range in ranges: if not self._check_ver_range(version, ver_range): return False return True
python
def _check_insersection(self, version, ranges): """Check that a version is inside all of a list of ranges""" for ver_range in ranges: if not self._check_ver_range(version, ver_range): return False return True
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bjmorgan/lattice_mc
lattice_mc/lattice.py
Lattice.enforce_periodic_boundary_conditions
def enforce_periodic_boundary_conditions( self ): """ Ensure that all lattice sites are within the central periodic image of the simulation cell. Sites that are outside the central simulation cell are mapped back into this cell. Args: None Returns: None """ for s in self.sites: for i in range(3): if s.r[i] < 0.0: s.r[i] += self.cell_lengths[i] if s.r[i] > self.cell_lengths[i]: s.r[i] -= self.cell_lengths[i]
python
def enforce_periodic_boundary_conditions( self ): """ Ensure that all lattice sites are within the central periodic image of the simulation cell. Sites that are outside the central simulation cell are mapped back into this cell. Args: None Returns: None """ for s in self.sites: for i in range(3): if s.r[i] < 0.0: s.r[i] += self.cell_lengths[i] if s.r[i] > self.cell_lengths[i]: s.r[i] -= self.cell_lengths[i]
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bububa/pyTOP
pyTOP/simba.py
CampaignArea.get
def get(self, campaign_id, nick=None): '''xxxxx.xxxxx.campaign.area.get =================================== 取得一个推广计划的投放地域设置''' request = TOPRequest('xxxxx.xxxxx.campaign.area.get') request['campaign_id'] = campaign_id if nick!=None: request['nick'] = nick self.create(self.execute(request), fields=['success','result','success','result_code','result_message'], models={'result':CampaignArea}) return self.result
python
def get(self, campaign_id, nick=None): '''xxxxx.xxxxx.campaign.area.get =================================== 取得一个推广计划的投放地域设置''' request = TOPRequest('xxxxx.xxxxx.campaign.area.get') request['campaign_id'] = campaign_id if nick!=None: request['nick'] = nick self.create(self.execute(request), fields=['success','result','success','result_code','result_message'], models={'result':CampaignArea}) return self.result
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pyhamtools/dxcluster.py
decode_pc11_message
def decode_pc11_message(raw_string): """Decode PC11 message, which usually contains DX Spots""" data = {} spot = raw_string.split("^") data[const.FREQUENCY] = float(spot[1]) data[const.DX] = spot[2] data[const.TIME] = datetime.fromtimestamp(mktime(strptime(spot[3]+" "+spot[4][:-1], "%d-%b-%Y %H%M"))) data[const.COMMENT] = spot[5] data[const.SPOTTER] = spot[6] data["node"] = spot[7] data["raw_spot"] = raw_string return data
python
def decode_pc11_message(raw_string): """Decode PC11 message, which usually contains DX Spots""" data = {} spot = raw_string.split("^") data[const.FREQUENCY] = float(spot[1]) data[const.DX] = spot[2] data[const.TIME] = datetime.fromtimestamp(mktime(strptime(spot[3]+" "+spot[4][:-1], "%d-%b-%Y %H%M"))) data[const.COMMENT] = spot[5] data[const.SPOTTER] = spot[6] data["node"] = spot[7] data["raw_spot"] = raw_string return data
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sockeye/coverage.py
get_coverage
def get_coverage(config: CoverageConfig) -> 'Coverage': """ Returns a Coverage instance. :param config: Coverage configuration. :return: Instance of Coverage. """ if config.type == C.COVERAGE_COUNT or config.type == C.COVERAGE_FERTILITY: utils.check_condition(config.num_hidden == 1, "Count or fertility coverage requires coverage_num_hidden==1") if config.type == C.GRU_TYPE: return GRUCoverage(config.num_hidden, config.layer_normalization) elif config.type in {C.TANH, C.SIGMOID, C.RELU, C.SOFT_RELU}: return ActivationCoverage(config.num_hidden, config.type, config.layer_normalization) elif config.type == C.COVERAGE_COUNT: return CountCoverage() elif config.type == C.COVERAGE_FERTILITY: return FertilityCoverage(config.max_fertility) else: raise ValueError("Unknown coverage type %s" % config.type)
python
def get_coverage(config: CoverageConfig) -> 'Coverage': """ Returns a Coverage instance. :param config: Coverage configuration. :return: Instance of Coverage. """ if config.type == C.COVERAGE_COUNT or config.type == C.COVERAGE_FERTILITY: utils.check_condition(config.num_hidden == 1, "Count or fertility coverage requires coverage_num_hidden==1") if config.type == C.GRU_TYPE: return GRUCoverage(config.num_hidden, config.layer_normalization) elif config.type in {C.TANH, C.SIGMOID, C.RELU, C.SOFT_RELU}: return ActivationCoverage(config.num_hidden, config.type, config.layer_normalization) elif config.type == C.COVERAGE_COUNT: return CountCoverage() elif config.type == C.COVERAGE_FERTILITY: return FertilityCoverage(config.max_fertility) else: raise ValueError("Unknown coverage type %s" % config.type)
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parsyfiles/parsing_registries.py
ConversionFinder.get_all_conversion_chains
def get_all_conversion_chains(self, from_type: Type[Any] = JOKER, to_type: Type[Any] = JOKER)\ -> Tuple[List[Converter], List[Converter], List[Converter]]: """ Utility method to find all converters or conversion chains matching the provided query. :param from_type: a required type of input object, or JOKER for 'wildcard'(*) . WARNING: "from_type=AnyObject/object/Any" means "all converters able to source from anything", which is different from "from_type=JOKER" which means "all converters whatever their source type". :param to_type: a required type of output object, or JOKER for 'wildcard'(*) . WARNING: "to_type=AnyObject/object/Any" means "all converters able to produce any type of object", which is different from "to_type=JOKER" which means "all converters whatever type they are able to produce". :return: a tuple of lists of matching converters, by type of *dest_type* match : generic, approximate, exact """ pass
python
def get_all_conversion_chains(self, from_type: Type[Any] = JOKER, to_type: Type[Any] = JOKER)\ -> Tuple[List[Converter], List[Converter], List[Converter]]: """ Utility method to find all converters or conversion chains matching the provided query. :param from_type: a required type of input object, or JOKER for 'wildcard'(*) . WARNING: "from_type=AnyObject/object/Any" means "all converters able to source from anything", which is different from "from_type=JOKER" which means "all converters whatever their source type". :param to_type: a required type of output object, or JOKER for 'wildcard'(*) . WARNING: "to_type=AnyObject/object/Any" means "all converters able to produce any type of object", which is different from "to_type=JOKER" which means "all converters whatever type they are able to produce". :return: a tuple of lists of matching converters, by type of *dest_type* match : generic, approximate, exact """ pass
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def _z2deriv(self,R,z,phi=0.,t=0.): """ NAME: _z2deriv PURPOSE: evaluate the second vertical derivative for this potential INPUT: R - Galactocentric cylindrical radius z - vertical height phi - azimuth t - time OUTPUT: the second vertical derivative HISTORY: 2015-02-07 - Written - Bovy (IAS) """ return self._mn3[0].z2deriv(R,z,phi=phi,t=t)\ +self._mn3[1].z2deriv(R,z,phi=phi,t=t)\ +self._mn3[2].z2deriv(R,z,phi=phi,t=t)
python
def _z2deriv(self,R,z,phi=0.,t=0.): """ NAME: _z2deriv PURPOSE: evaluate the second vertical derivative for this potential INPUT: R - Galactocentric cylindrical radius z - vertical height phi - azimuth t - time OUTPUT: the second vertical derivative HISTORY: 2015-02-07 - Written - Bovy (IAS) """ return self._mn3[0].z2deriv(R,z,phi=phi,t=t)\ +self._mn3[1].z2deriv(R,z,phi=phi,t=t)\ +self._mn3[2].z2deriv(R,z,phi=phi,t=t)
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cloud-custodian/cloud-custodian
tools/c7n_logexporter/c7n_logexporter/exporter.py
size
def size(config, accounts=(), day=None, group=None, human=True, region=None): """size of exported records for a given day.""" config = validate.callback(config) destination = config.get('destination') client = boto3.Session().client('s3') day = parse(day) def export_size(client, account): paginator = client.get_paginator('list_objects_v2') count = 0 size = 0 session = get_session(account['role'], region) account_id = session.client('sts').get_caller_identity()['Account'] prefix = destination.get('prefix', '').rstrip('/') + '/%s' % account_id prefix = "%s/%s/%s" % (prefix, group, day.strftime("%Y/%m/%d")) account['account_id'] = account_id for page in paginator.paginate( Bucket=destination['bucket'], Prefix=prefix): for k in page.get('Contents', ()): size += k['Size'] count += 1 return (count, size) total_size = 0 accounts_report = [] logging.getLogger('botocore').setLevel(logging.ERROR) with ThreadPoolExecutor(max_workers=16) as w: futures = {} for account in config.get('accounts'): if accounts and account['name'] not in accounts: continue futures[w.submit(export_size, client, account)] = account for f in as_completed(futures): account = futures[f] count, size = f.result() account.pop('role') account.pop('groups') total_size += size if human: account['size'] = GetHumanSize(size) else: account['size'] = size account['count'] = count accounts_report.append(account) accounts_report.sort(key=operator.itemgetter('count'), reverse=True) print(tabulate(accounts_report, headers='keys')) log.info("total size:%s", GetHumanSize(total_size))
python
def size(config, accounts=(), day=None, group=None, human=True, region=None): """size of exported records for a given day.""" config = validate.callback(config) destination = config.get('destination') client = boto3.Session().client('s3') day = parse(day) def export_size(client, account): paginator = client.get_paginator('list_objects_v2') count = 0 size = 0 session = get_session(account['role'], region) account_id = session.client('sts').get_caller_identity()['Account'] prefix = destination.get('prefix', '').rstrip('/') + '/%s' % account_id prefix = "%s/%s/%s" % (prefix, group, day.strftime("%Y/%m/%d")) account['account_id'] = account_id for page in paginator.paginate( Bucket=destination['bucket'], Prefix=prefix): for k in page.get('Contents', ()): size += k['Size'] count += 1 return (count, size) total_size = 0 accounts_report = [] logging.getLogger('botocore').setLevel(logging.ERROR) with ThreadPoolExecutor(max_workers=16) as w: futures = {} for account in config.get('accounts'): if accounts and account['name'] not in accounts: continue futures[w.submit(export_size, client, account)] = account for f in as_completed(futures): account = futures[f] count, size = f.result() account.pop('role') account.pop('groups') total_size += size if human: account['size'] = GetHumanSize(size) else: account['size'] = size account['count'] = count accounts_report.append(account) accounts_report.sort(key=operator.itemgetter('count'), reverse=True) print(tabulate(accounts_report, headers='keys')) log.info("total size:%s", GetHumanSize(total_size))
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size of exported records for a given day.
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wbond/asn1crypto
asn1crypto/core.py
Sequence.native
def native(self): """ The native Python datatype representation of this value :return: An OrderedDict or None. If an OrderedDict, all child values are recursively converted to native representation also. """ if self.contents is None: return None if self._native is None: if self.children is None: self._parse_children(recurse=True) try: self._native = OrderedDict() for index, child in enumerate(self.children): if child.__class__ == tuple: child = _build(*child) self.children[index] = child try: name = self._fields[index][0] except (IndexError): name = str_cls(index) self._native[name] = child.native except (ValueError, TypeError) as e: self._native = None args = e.args[1:] e.args = (e.args[0] + '\n while parsing %s' % type_name(self),) + args raise e return self._native
python
def native(self): """ The native Python datatype representation of this value :return: An OrderedDict or None. If an OrderedDict, all child values are recursively converted to native representation also. """ if self.contents is None: return None if self._native is None: if self.children is None: self._parse_children(recurse=True) try: self._native = OrderedDict() for index, child in enumerate(self.children): if child.__class__ == tuple: child = _build(*child) self.children[index] = child try: name = self._fields[index][0] except (IndexError): name = str_cls(index) self._native[name] = child.native except (ValueError, TypeError) as e: self._native = None args = e.args[1:] e.args = (e.args[0] + '\n while parsing %s' % type_name(self),) + args raise e return self._native
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jonathf/chaospy
chaospy/poly/typing.py
toarray
def toarray(vari): """ Convert polynomial array into a numpy.asarray of polynomials. Args: vari (Poly, numpy.ndarray): Input data. Returns: (numpy.ndarray): A numpy array with ``Q.shape==A.shape``. Examples: >>> poly = cp.prange(3) >>> print(poly) [1, q0, q0^2] >>> array = cp.toarray(poly) >>> print(isinstance(array, numpy.ndarray)) True >>> print(array[1]) q0 """ if isinstance(vari, Poly): shape = vari.shape out = numpy.asarray( [{} for _ in range(numpy.prod(shape))], dtype=object ) core = vari.A.copy() for key in core.keys(): core[key] = core[key].flatten() for i in range(numpy.prod(shape)): if not numpy.all(core[key][i] == 0): out[i][key] = core[key][i] for i in range(numpy.prod(shape)): out[i] = Poly(out[i], vari.dim, (), vari.dtype) out = out.reshape(shape) return out return numpy.asarray(vari)
python
def toarray(vari): """ Convert polynomial array into a numpy.asarray of polynomials. Args: vari (Poly, numpy.ndarray): Input data. Returns: (numpy.ndarray): A numpy array with ``Q.shape==A.shape``. Examples: >>> poly = cp.prange(3) >>> print(poly) [1, q0, q0^2] >>> array = cp.toarray(poly) >>> print(isinstance(array, numpy.ndarray)) True >>> print(array[1]) q0 """ if isinstance(vari, Poly): shape = vari.shape out = numpy.asarray( [{} for _ in range(numpy.prod(shape))], dtype=object ) core = vari.A.copy() for key in core.keys(): core[key] = core[key].flatten() for i in range(numpy.prod(shape)): if not numpy.all(core[key][i] == 0): out[i][key] = core[key][i] for i in range(numpy.prod(shape)): out[i] = Poly(out[i], vari.dim, (), vari.dtype) out = out.reshape(shape) return out return numpy.asarray(vari)
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noseOfYeti/tokeniser/spec_codec.py
TokeniserCodec.register
def register(self): """Register spec codec""" # Assume utf8 encoding utf8 = encodings.search_function('utf8') class StreamReader(utf_8.StreamReader): """Used by cPython to deal with a spec file""" def __init__(sr, stream, *args, **kwargs): codecs.StreamReader.__init__(sr, stream, *args, **kwargs) data = self.dealwith(sr.stream.readline) sr.stream = StringIO(data) def decode(text, *args, **kwargs): """Used by pypy and pylint to deal with a spec file""" return_tuple = kwargs.get("return_tuple", True) if six.PY3: if hasattr(text, 'tobytes'): text = text.tobytes().decode('utf8') else: text = text.decode('utf8') buffered = StringIO(text) # Determine if we need to have imports for this string # It may be a fragment of the file has_spec = regexes['encoding_matcher'].search(buffered.readline()) no_imports = not has_spec buffered.seek(0) # Translate the text if six.PY2: utf8 = encodings.search_function('utf8') # Assume utf8 encoding reader = utf8.streamreader(buffered) else: reader = buffered data = self.dealwith(reader.readline, no_imports=no_imports) # If nothing was changed, then we want to use the original file/line # Also have to replace indentation of original line with indentation of new line # To take into account nested describes if text and not regexes['only_whitespace'].match(text): if regexes['whitespace'].sub('', text) == regexes['whitespace'].sub('', data): bad_indentation = regexes['leading_whitespace'].search(text).groups()[0] good_indentation = regexes['leading_whitespace'].search(data).groups()[0] data = '%s%s' % (good_indentation, text[len(bad_indentation):]) # If text is empty and data isn't, then we should return text if len(text) == 0 and len(data) == 1: if return_tuple: return "", 0 else: return "" # Return translated version and it's length if return_tuple: return data, len(data) else: return data incrementaldecoder = utf8.incrementaldecoder if six.PY3: def incremental_decode(decoder, *args, **kwargs): """Wrapper for decode from IncrementalDecoder""" kwargs["return_tuple"] = False return decode(*args, **kwargs) incrementaldecoder = type("IncrementalDecoder", (utf8.incrementaldecoder, ), {"decode": incremental_decode}) def search_function(s): """Determine if a file is of spec encoding and return special CodecInfo if it is""" if s != 'spec': return None return codecs.CodecInfo( name='spec' , encode=utf8.encode , decode=decode , streamreader=StreamReader , streamwriter=utf8.streamwriter , incrementalencoder=utf8.incrementalencoder , incrementaldecoder=incrementaldecoder ) # Do the register codecs.register(search_function)
python
def register(self): """Register spec codec""" # Assume utf8 encoding utf8 = encodings.search_function('utf8') class StreamReader(utf_8.StreamReader): """Used by cPython to deal with a spec file""" def __init__(sr, stream, *args, **kwargs): codecs.StreamReader.__init__(sr, stream, *args, **kwargs) data = self.dealwith(sr.stream.readline) sr.stream = StringIO(data) def decode(text, *args, **kwargs): """Used by pypy and pylint to deal with a spec file""" return_tuple = kwargs.get("return_tuple", True) if six.PY3: if hasattr(text, 'tobytes'): text = text.tobytes().decode('utf8') else: text = text.decode('utf8') buffered = StringIO(text) # Determine if we need to have imports for this string # It may be a fragment of the file has_spec = regexes['encoding_matcher'].search(buffered.readline()) no_imports = not has_spec buffered.seek(0) # Translate the text if six.PY2: utf8 = encodings.search_function('utf8') # Assume utf8 encoding reader = utf8.streamreader(buffered) else: reader = buffered data = self.dealwith(reader.readline, no_imports=no_imports) # If nothing was changed, then we want to use the original file/line # Also have to replace indentation of original line with indentation of new line # To take into account nested describes if text and not regexes['only_whitespace'].match(text): if regexes['whitespace'].sub('', text) == regexes['whitespace'].sub('', data): bad_indentation = regexes['leading_whitespace'].search(text).groups()[0] good_indentation = regexes['leading_whitespace'].search(data).groups()[0] data = '%s%s' % (good_indentation, text[len(bad_indentation):]) # If text is empty and data isn't, then we should return text if len(text) == 0 and len(data) == 1: if return_tuple: return "", 0 else: return "" # Return translated version and it's length if return_tuple: return data, len(data) else: return data incrementaldecoder = utf8.incrementaldecoder if six.PY3: def incremental_decode(decoder, *args, **kwargs): """Wrapper for decode from IncrementalDecoder""" kwargs["return_tuple"] = False return decode(*args, **kwargs) incrementaldecoder = type("IncrementalDecoder", (utf8.incrementaldecoder, ), {"decode": incremental_decode}) def search_function(s): """Determine if a file is of spec encoding and return special CodecInfo if it is""" if s != 'spec': return None return codecs.CodecInfo( name='spec' , encode=utf8.encode , decode=decode , streamreader=StreamReader , streamwriter=utf8.streamwriter , incrementalencoder=utf8.incrementalencoder , incrementaldecoder=incrementaldecoder ) # Do the register codecs.register(search_function)
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SoftLayer/managers/dedicated_host.py
DedicatedHostManager._get_item
def _get_item(self, package, flavor): """Returns the item for ordering a dedicated host.""" for item in package['items']: if item['keyName'] == flavor: return item raise SoftLayer.SoftLayerError("Could not find valid item for: '%s'" % flavor)
python
def _get_item(self, package, flavor): """Returns the item for ordering a dedicated host.""" for item in package['items']: if item['keyName'] == flavor: return item raise SoftLayer.SoftLayerError("Could not find valid item for: '%s'" % flavor)
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statik/utils.py
find_first_file_with_ext
def find_first_file_with_ext(base_paths, prefix, exts): """Runs through the given list of file extensions and returns the first file with the given base path and extension combination that actually exists. Args: base_paths: The base paths in which to search for files. prefix: The filename prefix of the file for which to search. exts: An ordered list of file extensions for which to search. Returns: On success, a 2-tuple containing the base path in which the file was found, and the extension of the file. On failure, returns (None, None). """ for base_path in base_paths: for ext in exts: filename = os.path.join(base_path, "%s%s" % (prefix, ext)) if os.path.exists(filename) and os.path.isfile(filename): logger.debug("Found first file with relevant extension: %s", filename) return base_path, ext logger.debug("No files found for prefix %s, extensions %s", prefix, ", ".join(exts)) return None, None
python
def find_first_file_with_ext(base_paths, prefix, exts): """Runs through the given list of file extensions and returns the first file with the given base path and extension combination that actually exists. Args: base_paths: The base paths in which to search for files. prefix: The filename prefix of the file for which to search. exts: An ordered list of file extensions for which to search. Returns: On success, a 2-tuple containing the base path in which the file was found, and the extension of the file. On failure, returns (None, None). """ for base_path in base_paths: for ext in exts: filename = os.path.join(base_path, "%s%s" % (prefix, ext)) if os.path.exists(filename) and os.path.isfile(filename): logger.debug("Found first file with relevant extension: %s", filename) return base_path, ext logger.debug("No files found for prefix %s, extensions %s", prefix, ", ".join(exts)) return None, None
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benchexec/check_cgroups.py
main
def main(argv=None): """ A simple command-line interface for the cgroups check of BenchExec. """ if argv is None: argv = sys.argv parser = argparse.ArgumentParser( fromfile_prefix_chars='@', description= """Check whether cgroups are available and can be used for BenchExec. Part of BenchExec: https://github.com/sosy-lab/benchexec/""") parser.add_argument("--wait", type=int, default=1, metavar="SECONDS", help='wait some time to ensure no process interferes with cgroups in the meantime (default: 1s)') parser.add_argument("--no-thread", action="store_true", help='run check on the main thread instead of a separate thread' + '(behavior of cgrulesengd differs depending on this)') options = parser.parse_args(argv[1:]) if options.no_thread: check_cgroup_availability(options.wait) else: check_cgroup_availability_in_thread(options)
python
def main(argv=None): """ A simple command-line interface for the cgroups check of BenchExec. """ if argv is None: argv = sys.argv parser = argparse.ArgumentParser( fromfile_prefix_chars='@', description= """Check whether cgroups are available and can be used for BenchExec. Part of BenchExec: https://github.com/sosy-lab/benchexec/""") parser.add_argument("--wait", type=int, default=1, metavar="SECONDS", help='wait some time to ensure no process interferes with cgroups in the meantime (default: 1s)') parser.add_argument("--no-thread", action="store_true", help='run check on the main thread instead of a separate thread' + '(behavior of cgrulesengd differs depending on this)') options = parser.parse_args(argv[1:]) if options.no_thread: check_cgroup_availability(options.wait) else: check_cgroup_availability_in_thread(options)
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dnanexus/dx-toolkit
src/python/dxpy/workflow_builder.py
_create_temporary_projects
def _create_temporary_projects(enabled_regions, args): """ Creates a temporary project needed to build an underlying workflow for a global workflow. Returns a dictionary with region names as keys and project IDs as values The regions in which projects will be created can be: i. regions specified in dxworkflow.json "regionalOptions" ii. regions specified as an argument to "dx build" iii. current context project, if None of the above are set If both args and dxworkflow.json specify regions, they must match. """ # Create one temp project in each region projects_by_region = {} # Project IDs by region for region in enabled_regions: try: project_input = {"name": "Temporary build project for dx build global workflow", "region": region} if args.bill_to: project_input["billTo"] = args.bill_to temp_project = dxpy.api.project_new(project_input)["id"] projects_by_region[region] = temp_project logger.debug("Created temporary project {} to build in".format(temp_project)) except: # Clean up any temp projects that might have been created if projects_by_region: dxpy.executable_builder.delete_temporary_projects(projects_by_region.values()) err_exit() return projects_by_region
python
def _create_temporary_projects(enabled_regions, args): """ Creates a temporary project needed to build an underlying workflow for a global workflow. Returns a dictionary with region names as keys and project IDs as values The regions in which projects will be created can be: i. regions specified in dxworkflow.json "regionalOptions" ii. regions specified as an argument to "dx build" iii. current context project, if None of the above are set If both args and dxworkflow.json specify regions, they must match. """ # Create one temp project in each region projects_by_region = {} # Project IDs by region for region in enabled_regions: try: project_input = {"name": "Temporary build project for dx build global workflow", "region": region} if args.bill_to: project_input["billTo"] = args.bill_to temp_project = dxpy.api.project_new(project_input)["id"] projects_by_region[region] = temp_project logger.debug("Created temporary project {} to build in".format(temp_project)) except: # Clean up any temp projects that might have been created if projects_by_region: dxpy.executable_builder.delete_temporary_projects(projects_by_region.values()) err_exit() return projects_by_region
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elastic/elasticsearch-py
elasticsearch/client/cat.py
CatClient.allocation
def allocation(self, node_id=None, params=None): """ Allocation provides a snapshot of how shards have located around the cluster and the state of disk usage. `<https://www.elastic.co/guide/en/elasticsearch/reference/current/cat-allocation.html>`_ :arg node_id: A comma-separated list of node IDs or names to limit the returned information :arg bytes: The unit in which to display byte values, valid choices are: 'b', 'k', 'kb', 'm', 'mb', 'g', 'gb', 't', 'tb', 'p', 'pb' :arg format: a short version of the Accept header, e.g. json, yaml :arg h: Comma-separated list of column names to display :arg help: Return help information, default False :arg local: Return local information, do not retrieve the state from master node (default: false) :arg master_timeout: Explicit operation timeout for connection to master node :arg s: Comma-separated list of column names or column aliases to sort by :arg v: Verbose mode. Display column headers, default False """ return self.transport.perform_request('GET', _make_path('_cat', 'allocation', node_id), params=params)
python
def allocation(self, node_id=None, params=None): """ Allocation provides a snapshot of how shards have located around the cluster and the state of disk usage. `<https://www.elastic.co/guide/en/elasticsearch/reference/current/cat-allocation.html>`_ :arg node_id: A comma-separated list of node IDs or names to limit the returned information :arg bytes: The unit in which to display byte values, valid choices are: 'b', 'k', 'kb', 'm', 'mb', 'g', 'gb', 't', 'tb', 'p', 'pb' :arg format: a short version of the Accept header, e.g. json, yaml :arg h: Comma-separated list of column names to display :arg help: Return help information, default False :arg local: Return local information, do not retrieve the state from master node (default: false) :arg master_timeout: Explicit operation timeout for connection to master node :arg s: Comma-separated list of column names or column aliases to sort by :arg v: Verbose mode. Display column headers, default False """ return self.transport.perform_request('GET', _make_path('_cat', 'allocation', node_id), params=params)
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bitesofcode/projexui
projexui/widgets/xlistwidget.py
XListWidget.resizeToContents
def resizeToContents(self): """ Resizes the list widget to fit its contents vertically. """ if self.count(): item = self.item(self.count() - 1) rect = self.visualItemRect(item) height = rect.bottom() + 8 height = max(28, height) self.setFixedHeight(height) else: self.setFixedHeight(self.minimumHeight())
python
def resizeToContents(self): """ Resizes the list widget to fit its contents vertically. """ if self.count(): item = self.item(self.count() - 1) rect = self.visualItemRect(item) height = rect.bottom() + 8 height = max(28, height) self.setFixedHeight(height) else: self.setFixedHeight(self.minimumHeight())
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Dallinger/Dallinger
dallinger/bots.py
BotBase.complete_experiment
def complete_experiment(self, status): """Sends worker status ('worker_complete' or 'worker_failed') to the experiment server. """ url = self.driver.current_url p = urllib.parse.urlparse(url) complete_url = "%s://%s/%s?participant_id=%s" complete_url = complete_url % (p.scheme, p.netloc, status, self.participant_id) self.driver.get(complete_url) logger.info("Forced call to %s: %s" % (status, complete_url))
python
def complete_experiment(self, status): """Sends worker status ('worker_complete' or 'worker_failed') to the experiment server. """ url = self.driver.current_url p = urllib.parse.urlparse(url) complete_url = "%s://%s/%s?participant_id=%s" complete_url = complete_url % (p.scheme, p.netloc, status, self.participant_id) self.driver.get(complete_url) logger.info("Forced call to %s: %s" % (status, complete_url))
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gcp_devrel/tools/requirements.py
read_requirements
def read_requirements(req_file): """Reads a requirements file. Args: req_file (str): Filename of requirements file """ items = list(parse_requirements(req_file, session={})) result = [] for item in items: # Get line number from item line_number = item.comes_from.split(req_file + ' (line ')[1][:-1] if item.req: item.req.marker = item.markers result.append((item.req, line_number)) else: result.append((item, line_number)) return result
python
def read_requirements(req_file): """Reads a requirements file. Args: req_file (str): Filename of requirements file """ items = list(parse_requirements(req_file, session={})) result = [] for item in items: # Get line number from item line_number = item.comes_from.split(req_file + ' (line ')[1][:-1] if item.req: item.req.marker = item.markers result.append((item.req, line_number)) else: result.append((item, line_number)) return result
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SOBotics/pyRedunda
pyRedunda/Redunda.py
Redunda.uploadFiles
def uploadFiles(self): """ Uploads all the files in 'filesToSync' """ for each_file in self.filesToSync: self.uploadFile(each_file["name"], each_file["ispickle"], each_file["at_home"])
python
def uploadFiles(self): """ Uploads all the files in 'filesToSync' """ for each_file in self.filesToSync: self.uploadFile(each_file["name"], each_file["ispickle"], each_file["at_home"])
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opencobra/memote
memote/support/consistency.py
find_metabolites_not_produced_with_open_bounds
def find_metabolites_not_produced_with_open_bounds(model): """ Return metabolites that cannot be produced with open exchange reactions. A perfect model should be able to produce each and every metabolite when all medium components are available. Parameters ---------- model : cobra.Model The metabolic model under investigation. Returns ------- list Those metabolites that could not be produced. """ mets_not_produced = list() helpers.open_exchanges(model) for met in model.metabolites: with model: exch = model.add_boundary( met, type="irrex", reaction_id="IRREX", lb=0, ub=1000) solution = helpers.run_fba(model, exch.id) if np.isnan(solution) or solution < TOLERANCE_THRESHOLD: mets_not_produced.append(met) return mets_not_produced
python
def find_metabolites_not_produced_with_open_bounds(model): """ Return metabolites that cannot be produced with open exchange reactions. A perfect model should be able to produce each and every metabolite when all medium components are available. Parameters ---------- model : cobra.Model The metabolic model under investigation. Returns ------- list Those metabolites that could not be produced. """ mets_not_produced = list() helpers.open_exchanges(model) for met in model.metabolites: with model: exch = model.add_boundary( met, type="irrex", reaction_id="IRREX", lb=0, ub=1000) solution = helpers.run_fba(model, exch.id) if np.isnan(solution) or solution < TOLERANCE_THRESHOLD: mets_not_produced.append(met) return mets_not_produced
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ic-labs/django-icekit
icekit/publishing/models.py
PublishingModel.clone_parler_translations
def clone_parler_translations(self, dst_obj): """ Clone each of the translations from an object and relate them to another. :param self: The object to get the translations from. :param dst_obj: The object to relate the new translations to. :return: None """ # Find all django-parler translation attributes on model translation_attrs = [] if hasattr(self, '_parler_meta'): for parler_meta in self._parler_meta: translation_attrs.append(parler_meta.rel_name) # Clone all django-parler translations via attributes for translation_attr in translation_attrs: # Clear any translations already cloned to published object # before we get here, which seems to happen via deepcopy() # sometimes. setattr(dst_obj, translation_attr, []) # Clone attribute's translations from source to destination for translation in getattr(self, translation_attr).all(): translation.pk = None translation.master = dst_obj translation.save()
python
def clone_parler_translations(self, dst_obj): """ Clone each of the translations from an object and relate them to another. :param self: The object to get the translations from. :param dst_obj: The object to relate the new translations to. :return: None """ # Find all django-parler translation attributes on model translation_attrs = [] if hasattr(self, '_parler_meta'): for parler_meta in self._parler_meta: translation_attrs.append(parler_meta.rel_name) # Clone all django-parler translations via attributes for translation_attr in translation_attrs: # Clear any translations already cloned to published object # before we get here, which seems to happen via deepcopy() # sometimes. setattr(dst_obj, translation_attr, []) # Clone attribute's translations from source to destination for translation in getattr(self, translation_attr).all(): translation.pk = None translation.master = dst_obj translation.save()
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train
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Microsoft/nni
examples/trials/ga_squad/graph.py
Graph.mutation
def mutation(self, only_add=False): ''' Mutation for a graph ''' types = [] if self.layer_num() < self.max_layer_num: types.append(0) types.append(1) if self.layer_num() > 5 and only_add is False: types.append(2) types.append(3) # 0 : add a layer , delete a edge # 1 : add a layer , change a edge # 2 : delete a layer, delete a edge # 3 : delete a layer, change a edge graph_type = random.choice(types) layer_type = random.choice([LayerType.attention.value,\ LayerType.self_attention.value, LayerType.rnn.value]) layers = copy.deepcopy(self.layers) cnt_try = 0 while True: layers_in = [] layers_out = [] layers_del = [] for i, layer in enumerate(layers): if layer.is_delete is False: if layer.graph_type != LayerType.output.value: layers_in.append(i) if layer.graph_type != LayerType.input.value: layers_out.append(i) if layer.graph_type != LayerType.output.value\ and layer.graph_type != LayerType.input.value: layers_del.append(i) if graph_type <= 1: new_id = len(layers) out = random.choice(layers_out) inputs = [] output = [out] pos = random.randint(0, len(layers[out].input) - 1) last_in = layers[out].input[pos] layers[out].input[pos] = new_id if graph_type == 0: layers[last_in].output.remove(out) if graph_type == 1: layers[last_in].output.remove(out) layers[last_in].output.append(new_id) inputs = [last_in] lay = Layer(graph_type=layer_type, inputs=inputs, output=output) while len(inputs) < lay.input_size: layer1 = random.choice(layers_in) inputs.append(layer1) layers[layer1].output.append(new_id) lay.input = inputs layers.append(lay) else: layer1 = random.choice(layers_del) for layer2 in layers[layer1].output: layers[layer2].input.remove(layer1) if graph_type == 2: random_in = random.choice(layers_in) else: random_in = random.choice(layers[layer1].input) layers[layer2].input.append(random_in) layers[random_in].output.append(layer2) for layer2 in layers[layer1].input: layers[layer2].output.remove(layer1) layers[layer1].is_delete = True if self.is_legal(layers): self.layers = layers break else: layers = copy.deepcopy(self.layers) cnt_try += 1
python
def mutation(self, only_add=False): ''' Mutation for a graph ''' types = [] if self.layer_num() < self.max_layer_num: types.append(0) types.append(1) if self.layer_num() > 5 and only_add is False: types.append(2) types.append(3) # 0 : add a layer , delete a edge # 1 : add a layer , change a edge # 2 : delete a layer, delete a edge # 3 : delete a layer, change a edge graph_type = random.choice(types) layer_type = random.choice([LayerType.attention.value,\ LayerType.self_attention.value, LayerType.rnn.value]) layers = copy.deepcopy(self.layers) cnt_try = 0 while True: layers_in = [] layers_out = [] layers_del = [] for i, layer in enumerate(layers): if layer.is_delete is False: if layer.graph_type != LayerType.output.value: layers_in.append(i) if layer.graph_type != LayerType.input.value: layers_out.append(i) if layer.graph_type != LayerType.output.value\ and layer.graph_type != LayerType.input.value: layers_del.append(i) if graph_type <= 1: new_id = len(layers) out = random.choice(layers_out) inputs = [] output = [out] pos = random.randint(0, len(layers[out].input) - 1) last_in = layers[out].input[pos] layers[out].input[pos] = new_id if graph_type == 0: layers[last_in].output.remove(out) if graph_type == 1: layers[last_in].output.remove(out) layers[last_in].output.append(new_id) inputs = [last_in] lay = Layer(graph_type=layer_type, inputs=inputs, output=output) while len(inputs) < lay.input_size: layer1 = random.choice(layers_in) inputs.append(layer1) layers[layer1].output.append(new_id) lay.input = inputs layers.append(lay) else: layer1 = random.choice(layers_del) for layer2 in layers[layer1].output: layers[layer2].input.remove(layer1) if graph_type == 2: random_in = random.choice(layers_in) else: random_in = random.choice(layers[layer1].input) layers[layer2].input.append(random_in) layers[random_in].output.append(layer2) for layer2 in layers[layer1].input: layers[layer2].output.remove(layer1) layers[layer1].is_delete = True if self.is_legal(layers): self.layers = layers break else: layers = copy.deepcopy(self.layers) cnt_try += 1
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libinput/event.py
TabletPadEvent.ring_position
def ring_position(self): """The current position of the ring, in degrees counterclockwise from the northern-most point of the ring in the tablet's current logical orientation. If the source is :attr:`~libinput.constant.TabletPadRingAxisSource.FINGER`, libinput sends a terminating event with a ring value of -1 when the finger is lifted from the ring. A caller may use this information to e.g. determine if kinetic scrolling should be triggered. For events not of type :attr:`~libinput.constant.EventType.TABLET_PAD_RING`, this property raises :exc:`AttributeError`. Returns: float: The current value of the the axis. -1 if the finger was lifted. Raises: AttributeError """ if self.type != EventType.TABLET_PAD_RING: raise AttributeError(_wrong_prop.format(self.type)) return self._libinput.libinput_event_tablet_pad_get_ring_position( self._handle)
python
def ring_position(self): """The current position of the ring, in degrees counterclockwise from the northern-most point of the ring in the tablet's current logical orientation. If the source is :attr:`~libinput.constant.TabletPadRingAxisSource.FINGER`, libinput sends a terminating event with a ring value of -1 when the finger is lifted from the ring. A caller may use this information to e.g. determine if kinetic scrolling should be triggered. For events not of type :attr:`~libinput.constant.EventType.TABLET_PAD_RING`, this property raises :exc:`AttributeError`. Returns: float: The current value of the the axis. -1 if the finger was lifted. Raises: AttributeError """ if self.type != EventType.TABLET_PAD_RING: raise AttributeError(_wrong_prop.format(self.type)) return self._libinput.libinput_event_tablet_pad_get_ring_position( self._handle)
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cackharot/suds-py3
suds/bindings/binding.py
Binding.get_fault
def get_fault(self, reply): """ Extract the fault from the specified soap reply. If I{faults} is True, an exception is raised. Otherwise, the I{unmarshalled} fault L{Object} is returned. This method is called when the server raises a I{web fault}. @param reply: A soap reply message. @type reply: str @return: A fault object. @rtype: tuple ( L{Element}, L{Object} ) """ reply = self.replyfilter(reply) sax = Parser() faultroot = sax.parse(string=reply) soapenv = faultroot.getChild('Envelope') soapbody = soapenv.getChild('Body') fault = soapbody.getChild('Fault') unmarshaller = self.unmarshaller(False) p = unmarshaller.process(fault) if self.options().faults: raise WebFault(p, faultroot) return (faultroot, p.detail)
python
def get_fault(self, reply): """ Extract the fault from the specified soap reply. If I{faults} is True, an exception is raised. Otherwise, the I{unmarshalled} fault L{Object} is returned. This method is called when the server raises a I{web fault}. @param reply: A soap reply message. @type reply: str @return: A fault object. @rtype: tuple ( L{Element}, L{Object} ) """ reply = self.replyfilter(reply) sax = Parser() faultroot = sax.parse(string=reply) soapenv = faultroot.getChild('Envelope') soapbody = soapenv.getChild('Body') fault = soapbody.getChild('Fault') unmarshaller = self.unmarshaller(False) p = unmarshaller.process(fault) if self.options().faults: raise WebFault(p, faultroot) return (faultroot, p.detail)
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DataDog/integrations-core
redisdb/datadog_checks/redisdb/redisdb.py
Redis._check_command_stats
def _check_command_stats(self, conn, tags): """Get command-specific statistics from redis' INFO COMMANDSTATS command """ try: command_stats = conn.info("commandstats") except Exception: self.warning('Could not retrieve command stats from Redis. INFO COMMANDSTATS only works with Redis >= 2.6.') return for key, stats in iteritems(command_stats): command = key.split('_', 1)[1] command_tags = tags + ['command:{}'.format(command)] # When `host:` is passed as a command, `calls` ends up having a leading `:` # see https://github.com/DataDog/integrations-core/issues/839 calls = stats.get('calls') if command != 'host' else stats.get(':calls') self.gauge('redis.command.calls', calls, tags=command_tags) self.gauge('redis.command.usec_per_call', stats['usec_per_call'], tags=command_tags)
python
def _check_command_stats(self, conn, tags): """Get command-specific statistics from redis' INFO COMMANDSTATS command """ try: command_stats = conn.info("commandstats") except Exception: self.warning('Could not retrieve command stats from Redis. INFO COMMANDSTATS only works with Redis >= 2.6.') return for key, stats in iteritems(command_stats): command = key.split('_', 1)[1] command_tags = tags + ['command:{}'.format(command)] # When `host:` is passed as a command, `calls` ends up having a leading `:` # see https://github.com/DataDog/integrations-core/issues/839 calls = stats.get('calls') if command != 'host' else stats.get(':calls') self.gauge('redis.command.calls', calls, tags=command_tags) self.gauge('redis.command.usec_per_call', stats['usec_per_call'], tags=command_tags)
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nion-software/nionswift
nion/swift/FilterPanel.py
TreeNode.insert_value
def insert_value(self, keys, value): """ Insert a value (data item) into this tree node and then its children. This will be called in response to a new data item being inserted into the document. Also updates the tree node's cumulative child count. """ self.count += 1 if not self.key: self.__value_reverse_mapping[value] = keys if len(keys) == 0: self.values.append(value) else: key = keys[0] index = bisect.bisect_left(self.children, TreeNode(key, reversed=self.reversed)) if index == len(self.children) or self.children[index].key != key: new_tree_node = TreeNode(key, list(), reversed=self.reversed) new_tree_node.child_inserted = self.child_inserted new_tree_node.child_removed = self.child_removed new_tree_node.tree_node_updated = self.tree_node_updated new_tree_node.__set_parent(self) self.children.insert(index, new_tree_node) if self.child_inserted: self.child_inserted(self, index, new_tree_node) child = self.children[index] child.insert_value(keys[1:], value) if self.tree_node_updated: self.tree_node_updated(child)
python
def insert_value(self, keys, value): """ Insert a value (data item) into this tree node and then its children. This will be called in response to a new data item being inserted into the document. Also updates the tree node's cumulative child count. """ self.count += 1 if not self.key: self.__value_reverse_mapping[value] = keys if len(keys) == 0: self.values.append(value) else: key = keys[0] index = bisect.bisect_left(self.children, TreeNode(key, reversed=self.reversed)) if index == len(self.children) or self.children[index].key != key: new_tree_node = TreeNode(key, list(), reversed=self.reversed) new_tree_node.child_inserted = self.child_inserted new_tree_node.child_removed = self.child_removed new_tree_node.tree_node_updated = self.tree_node_updated new_tree_node.__set_parent(self) self.children.insert(index, new_tree_node) if self.child_inserted: self.child_inserted(self, index, new_tree_node) child = self.children[index] child.insert_value(keys[1:], value) if self.tree_node_updated: self.tree_node_updated(child)
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mitsei/dlkit
dlkit/json_/learning/sessions.py
ActivityObjectiveBankAssignmentSession.unassign_activity_from_objective_bank
def unassign_activity_from_objective_bank(self, activity_id, objective_bank_id): """Removes a ``Activity`` from a ``ObjectiveBank``. arg: activity_id (osid.id.Id): the ``Id`` of the ``Activity`` arg: objective_bank_id (osid.id.Id): the ``Id`` of the ``ObjectiveBank`` raise: NotFound - ``activity_id`` or ``objective_bank_id`` not found or ``activity_id`` not mapped to ``objective_bank_id`` raise: NullArgument - ``activity_id`` or ``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.unassign_resource_from_bin mgr = self._get_provider_manager('LEARNING', local=True) lookup_session = mgr.get_objective_bank_lookup_session(proxy=self._proxy) lookup_session.get_objective_bank(objective_bank_id) # to raise NotFound self._unassign_object_from_catalog(activity_id, objective_bank_id)
python
def unassign_activity_from_objective_bank(self, activity_id, objective_bank_id): """Removes a ``Activity`` from a ``ObjectiveBank``. arg: activity_id (osid.id.Id): the ``Id`` of the ``Activity`` arg: objective_bank_id (osid.id.Id): the ``Id`` of the ``ObjectiveBank`` raise: NotFound - ``activity_id`` or ``objective_bank_id`` not found or ``activity_id`` not mapped to ``objective_bank_id`` raise: NullArgument - ``activity_id`` or ``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.unassign_resource_from_bin mgr = self._get_provider_manager('LEARNING', local=True) lookup_session = mgr.get_objective_bank_lookup_session(proxy=self._proxy) lookup_session.get_objective_bank(objective_bank_id) # to raise NotFound self._unassign_object_from_catalog(activity_id, objective_bank_id)
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thespacedoctor/rockAtlas
rockAtlas/phot/dophotMatch.py
dophotMatch._select_exposures_requiring_dophot_extraction
def _select_exposures_requiring_dophot_extraction( self, batch=10): """* select exposures requiring dophot extraction* **Key Arguments:** - ``batch`` -- the batch size of dophot file to process **Return:** - ``expnames`` -- the names of the expsoures in the batch - ``remaining`` -- the number of exposured remainging that require orbfit/dophot crossmatching """ self.log.info( 'starting the ``_select_exposures_requiring_dophot_extraction`` method') sqlQuery = u""" select expname, floor(mjd) as mjd from atlas_exposures where local_data = 1 and dophot_match = 0 and orbfit_positions = 1; """ % locals() rows = readquery( log=self.log, sqlQuery=sqlQuery, dbConn=self.atlasMoversDBConn, quiet=False ) remaining = len(rows) expnames = [] expnames[:] = [(r["expname"], int(r["mjd"])) for r in rows[:batch]] self.log.info( 'completed the ``_select_exposures_requiring_dophot_extraction`` method') return expnames, remaining
python
def _select_exposures_requiring_dophot_extraction( self, batch=10): """* select exposures requiring dophot extraction* **Key Arguments:** - ``batch`` -- the batch size of dophot file to process **Return:** - ``expnames`` -- the names of the expsoures in the batch - ``remaining`` -- the number of exposured remainging that require orbfit/dophot crossmatching """ self.log.info( 'starting the ``_select_exposures_requiring_dophot_extraction`` method') sqlQuery = u""" select expname, floor(mjd) as mjd from atlas_exposures where local_data = 1 and dophot_match = 0 and orbfit_positions = 1; """ % locals() rows = readquery( log=self.log, sqlQuery=sqlQuery, dbConn=self.atlasMoversDBConn, quiet=False ) remaining = len(rows) expnames = [] expnames[:] = [(r["expname"], int(r["mjd"])) for r in rows[:batch]] self.log.info( 'completed the ``_select_exposures_requiring_dophot_extraction`` method') return expnames, remaining
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pyfirmata/util.py
str_to_two_byte_iter
def str_to_two_byte_iter(string): """ Return a iter consisting of two byte chars from a string. """ bstring = string.encode() bytes = bytearray() for char in bstring: bytes.append(char) bytes.append(0) return bytes
python
def str_to_two_byte_iter(string): """ Return a iter consisting of two byte chars from a string. """ bstring = string.encode() bytes = bytearray() for char in bstring: bytes.append(char) bytes.append(0) return bytes
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ArchiveTeam/wpull
wpull/protocol/http/robots.py
RobotsTxtChecker.can_fetch
def can_fetch(self, request: Request, file=None) -> bool: '''Return whether the request can fetched. Args: request: Request. file: A file object to where the robots.txt contents are written. Coroutine. ''' try: return self.can_fetch_pool(request) except NotInPoolError: pass yield from self.fetch_robots_txt(request, file=file) return self.can_fetch_pool(request)
python
def can_fetch(self, request: Request, file=None) -> bool: '''Return whether the request can fetched. Args: request: Request. file: A file object to where the robots.txt contents are written. Coroutine. ''' try: return self.can_fetch_pool(request) except NotInPoolError: pass yield from self.fetch_robots_txt(request, file=file) return self.can_fetch_pool(request)
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backoff/_decorator.py
on_predicate
def on_predicate(wait_gen, predicate=operator.not_, max_tries=None, max_time=None, jitter=full_jitter, on_success=None, on_backoff=None, on_giveup=None, logger='backoff', **wait_gen_kwargs): """Returns decorator for backoff and retry triggered by predicate. Args: wait_gen: A generator yielding successive wait times in seconds. predicate: A function which when called on the return value of the target function will trigger backoff when considered truthily. If not specified, the default behavior is to backoff on falsey return values. max_tries: The maximum number of attempts to make before giving up. In the case of failure, the result of the last attempt will be returned. The default value of None means there is no limit to the number of tries. If a callable is passed, it will be evaluated at runtime and its return value used. max_time: The maximum total amount of time to try for before giving up. If this time expires, the result of the last attempt will be returned. If a callable is passed, it will be evaluated at runtime and its return value used. jitter: A function of the value yielded by wait_gen returning the actual time to wait. This distributes wait times stochastically in order to avoid timing collisions across concurrent clients. Wait times are jittered by default using the full_jitter function. Jittering may be disabled altogether by passing jitter=None. on_success: Callable (or iterable of callables) with a unary signature to be called in the event of success. The parameter is a dict containing details about the invocation. on_backoff: Callable (or iterable of callables) with a unary signature to be called in the event of a backoff. The parameter is a dict containing details about the invocation. on_giveup: Callable (or iterable of callables) with a unary signature to be called in the event that max_tries is exceeded. The parameter is a dict containing details about the invocation. logger: Name of logger or Logger object to log to. Defaults to 'backoff'. **wait_gen_kwargs: Any additional keyword args specified will be passed to wait_gen when it is initialized. Any callable args will first be evaluated and their return values passed. This is useful for runtime configuration. """ def decorate(target): # change names because python 2.x doesn't have nonlocal logger_ = logger if isinstance(logger_, basestring): logger_ = logging.getLogger(logger_) on_success_ = _config_handlers(on_success) on_backoff_ = _config_handlers(on_backoff, _log_backoff, logger_) on_giveup_ = _config_handlers(on_giveup, _log_giveup, logger_) retry = None if sys.version_info >= (3, 5): # pragma: python=3.5 import asyncio if asyncio.iscoroutinefunction(target): import backoff._async retry = backoff._async.retry_predicate elif _is_event_loop() and _is_current_task(): # Verify that sync version is not being run from coroutine # (that would lead to event loop hiccups). raise TypeError( "backoff.on_predicate applied to a regular function " "inside coroutine, this will lead to event loop " "hiccups. Use backoff.on_predicate on coroutines in " "asynchronous code.") if retry is None: retry = _sync.retry_predicate return retry(target, wait_gen, predicate, max_tries, max_time, jitter, on_success_, on_backoff_, on_giveup_, wait_gen_kwargs) # Return a function which decorates a target with a retry loop. return decorate
python
def on_predicate(wait_gen, predicate=operator.not_, max_tries=None, max_time=None, jitter=full_jitter, on_success=None, on_backoff=None, on_giveup=None, logger='backoff', **wait_gen_kwargs): """Returns decorator for backoff and retry triggered by predicate. Args: wait_gen: A generator yielding successive wait times in seconds. predicate: A function which when called on the return value of the target function will trigger backoff when considered truthily. If not specified, the default behavior is to backoff on falsey return values. max_tries: The maximum number of attempts to make before giving up. In the case of failure, the result of the last attempt will be returned. The default value of None means there is no limit to the number of tries. If a callable is passed, it will be evaluated at runtime and its return value used. max_time: The maximum total amount of time to try for before giving up. If this time expires, the result of the last attempt will be returned. If a callable is passed, it will be evaluated at runtime and its return value used. jitter: A function of the value yielded by wait_gen returning the actual time to wait. This distributes wait times stochastically in order to avoid timing collisions across concurrent clients. Wait times are jittered by default using the full_jitter function. Jittering may be disabled altogether by passing jitter=None. on_success: Callable (or iterable of callables) with a unary signature to be called in the event of success. The parameter is a dict containing details about the invocation. on_backoff: Callable (or iterable of callables) with a unary signature to be called in the event of a backoff. The parameter is a dict containing details about the invocation. on_giveup: Callable (or iterable of callables) with a unary signature to be called in the event that max_tries is exceeded. The parameter is a dict containing details about the invocation. logger: Name of logger or Logger object to log to. Defaults to 'backoff'. **wait_gen_kwargs: Any additional keyword args specified will be passed to wait_gen when it is initialized. Any callable args will first be evaluated and their return values passed. This is useful for runtime configuration. """ def decorate(target): # change names because python 2.x doesn't have nonlocal logger_ = logger if isinstance(logger_, basestring): logger_ = logging.getLogger(logger_) on_success_ = _config_handlers(on_success) on_backoff_ = _config_handlers(on_backoff, _log_backoff, logger_) on_giveup_ = _config_handlers(on_giveup, _log_giveup, logger_) retry = None if sys.version_info >= (3, 5): # pragma: python=3.5 import asyncio if asyncio.iscoroutinefunction(target): import backoff._async retry = backoff._async.retry_predicate elif _is_event_loop() and _is_current_task(): # Verify that sync version is not being run from coroutine # (that would lead to event loop hiccups). raise TypeError( "backoff.on_predicate applied to a regular function " "inside coroutine, this will lead to event loop " "hiccups. Use backoff.on_predicate on coroutines in " "asynchronous code.") if retry is None: retry = _sync.retry_predicate return retry(target, wait_gen, predicate, max_tries, max_time, jitter, on_success_, on_backoff_, on_giveup_, wait_gen_kwargs) # Return a function which decorates a target with a retry loop. return decorate
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GoogleCloudPlatform/datastore-ndb-python
ndb/metadata.py
Property.key_to_kind
def key_to_kind(cls, key): """Return the kind specified by a given __property__ key. Args: key: key whose kind name is requested. Returns: The kind specified by key. """ if key.kind() == Kind.KIND_NAME: return key.id() else: return key.parent().id()
python
def key_to_kind(cls, key): """Return the kind specified by a given __property__ key. Args: key: key whose kind name is requested. Returns: The kind specified by key. """ if key.kind() == Kind.KIND_NAME: return key.id() else: return key.parent().id()
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duniter/duniter-python-api
duniterpy/api/endpoint.py
ESCoreEndpoint.from_inline
def from_inline(cls: Type[ESCoreEndpointType], inline: str) -> ESCoreEndpointType: """ Return ESCoreEndpoint instance from endpoint string :param inline: Endpoint string :return: """ m = ESCoreEndpoint.re_inline.match(inline) if m is None: raise MalformedDocumentError(ESCoreEndpoint.API) server = m.group(1) port = int(m.group(2)) return cls(server, port)
python
def from_inline(cls: Type[ESCoreEndpointType], inline: str) -> ESCoreEndpointType: """ Return ESCoreEndpoint instance from endpoint string :param inline: Endpoint string :return: """ m = ESCoreEndpoint.re_inline.match(inline) if m is None: raise MalformedDocumentError(ESCoreEndpoint.API) server = m.group(1) port = int(m.group(2)) return cls(server, port)
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Robpol86/libnl
libnl/attr.py
nla_put_u16
def nla_put_u16(msg, attrtype, value): """Add 16 bit integer attribute to Netlink message. https://github.com/thom311/libnl/blob/libnl3_2_25/lib/attr.c#L588 Positional arguments: msg -- Netlink message (nl_msg class instance). attrtype -- attribute type (integer). value -- numeric value to store as payload (int() or c_uint16()). Returns: 0 on success or a negative error code. """ data = bytearray(value if isinstance(value, c_uint16) else c_uint16(value)) return nla_put(msg, attrtype, SIZEOF_U16, data)
python
def nla_put_u16(msg, attrtype, value): """Add 16 bit integer attribute to Netlink message. https://github.com/thom311/libnl/blob/libnl3_2_25/lib/attr.c#L588 Positional arguments: msg -- Netlink message (nl_msg class instance). attrtype -- attribute type (integer). value -- numeric value to store as payload (int() or c_uint16()). Returns: 0 on success or a negative error code. """ data = bytearray(value if isinstance(value, c_uint16) else c_uint16(value)) return nla_put(msg, attrtype, SIZEOF_U16, data)
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softlayer/softlayer-python
SoftLayer/CLI/helpers.py
resolve_id
def resolve_id(resolver, identifier, name='object'): """Resolves a single id using a resolver function. :param resolver: function that resolves ids. Should return None or a list of ids. :param string identifier: a string identifier used to resolve ids :param string name: the object type, to be used in error messages """ try: return int(identifier) except ValueError: pass # It was worth a shot ids = resolver(identifier) if len(ids) == 0: raise exceptions.CLIAbort("Error: Unable to find %s '%s'" % (name, identifier)) if len(ids) > 1: raise exceptions.CLIAbort( "Error: Multiple %s found for '%s': %s" % (name, identifier, ', '.join([str(_id) for _id in ids]))) return ids[0]
python
def resolve_id(resolver, identifier, name='object'): """Resolves a single id using a resolver function. :param resolver: function that resolves ids. Should return None or a list of ids. :param string identifier: a string identifier used to resolve ids :param string name: the object type, to be used in error messages """ try: return int(identifier) except ValueError: pass # It was worth a shot ids = resolver(identifier) if len(ids) == 0: raise exceptions.CLIAbort("Error: Unable to find %s '%s'" % (name, identifier)) if len(ids) > 1: raise exceptions.CLIAbort( "Error: Multiple %s found for '%s': %s" % (name, identifier, ', '.join([str(_id) for _id in ids]))) return ids[0]
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theislab/anndata
anndata/base.py
AnnDataFileManager._to_memory_mode
def _to_memory_mode(self): """Close the backing file, forget filename, *do* change to memory mode.""" self._adata.__X = self._adata.X[()] self._file.close() self._file = None self._filename = None
python
def _to_memory_mode(self): """Close the backing file, forget filename, *do* change to memory mode.""" self._adata.__X = self._adata.X[()] self._file.close() self._file = None self._filename = None
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Datary/scrapbag
scrapbag/files.py
is_remote_file_modified
def is_remote_file_modified(web_file, destination): """ Check if online file has been modified. Args: :web_file: online file to check. :destination: path of the offline file to compare. """ try: # check datetime of last modified in file. last_mod = web_file.headers.get('last-modified') if last_mod: web_file_time = time.strptime( web_file.headers.get( 'last-modified'), '%a, %d %b %Y %H:%M:%S %Z') else: web_file_time = time.gmtime() web_file_size = int(web_file.headers.get('content-length', -1)) if os.path.exists(destination): file_time = time.gmtime(os.path.getmtime(destination)) file_size = os.path.getsize(destination) if file_time >= web_file_time and file_size == web_file_size: return False except Exception as ex: msg = ('Fail checking if remote file is modified default returns TRUE' ' - {}'.format(ex)) logger.debug(msg) return True
python
def is_remote_file_modified(web_file, destination): """ Check if online file has been modified. Args: :web_file: online file to check. :destination: path of the offline file to compare. """ try: # check datetime of last modified in file. last_mod = web_file.headers.get('last-modified') if last_mod: web_file_time = time.strptime( web_file.headers.get( 'last-modified'), '%a, %d %b %Y %H:%M:%S %Z') else: web_file_time = time.gmtime() web_file_size = int(web_file.headers.get('content-length', -1)) if os.path.exists(destination): file_time = time.gmtime(os.path.getmtime(destination)) file_size = os.path.getsize(destination) if file_time >= web_file_time and file_size == web_file_size: return False except Exception as ex: msg = ('Fail checking if remote file is modified default returns TRUE' ' - {}'.format(ex)) logger.debug(msg) return True
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python
def bind(self, name): """ Bind a `Column` object to its name. """ return _BoundColumnDescr( dtype=self.dtype, missing_value=self.missing_value, name=name, doc=self.doc, metadata=self.metadata, )
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safe/gui/tools/wizard/step_fc35_explayer_from_canvas.py
StepFcExpLayerFromCanvas.selected_canvas_explayer
def selected_canvas_explayer(self): """Obtain the canvas exposure layer selected by user. :returns: The currently selected map layer in the list. :rtype: QgsMapLayer """ if self.lstCanvasExpLayers.selectedItems(): item = self.lstCanvasExpLayers.currentItem() else: return None try: layer_id = item.data(Qt.UserRole) except (AttributeError, NameError): layer_id = None # noinspection PyArgumentList layer = QgsProject.instance().mapLayer(layer_id) return layer
python
def selected_canvas_explayer(self): """Obtain the canvas exposure layer selected by user. :returns: The currently selected map layer in the list. :rtype: QgsMapLayer """ if self.lstCanvasExpLayers.selectedItems(): item = self.lstCanvasExpLayers.currentItem() else: return None try: layer_id = item.data(Qt.UserRole) except (AttributeError, NameError): layer_id = None # noinspection PyArgumentList layer = QgsProject.instance().mapLayer(layer_id) return layer
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thutils/common.py
dump_dict
def dump_dict(dict_input, indent=4): """ 辞書型変数を文字列に変換して返す """ dict_work = dict(dict_input) """ for key, value in six.iteritems(dict_input): if any([f(value) for f in (is_float, isDict, is_list_or_tuple)]): dict_work[key] = value continue try: dict_work[key] = str(value) except: dict_work[key] = str(type(value)) dict_work[key] = _convert_dump_dict(value) """ try: import json return json.dumps(dict_work, sort_keys=True, indent=indent) except ImportError: pass try: import simplejson as json return json.dumps(dict_work, sort_keys=True, indent=indent) except ImportError: pass try: import pprint return pprint.pformat(dict_work, indent=indent) except ImportError: pass return str(dict_work)
python
def dump_dict(dict_input, indent=4): """ 辞書型変数を文字列に変換して返す """ dict_work = dict(dict_input) """ for key, value in six.iteritems(dict_input): if any([f(value) for f in (is_float, isDict, is_list_or_tuple)]): dict_work[key] = value continue try: dict_work[key] = str(value) except: dict_work[key] = str(type(value)) dict_work[key] = _convert_dump_dict(value) """ try: import json return json.dumps(dict_work, sort_keys=True, indent=indent) except ImportError: pass try: import simplejson as json return json.dumps(dict_work, sort_keys=True, indent=indent) except ImportError: pass try: import pprint return pprint.pformat(dict_work, indent=indent) except ImportError: pass return str(dict_work)
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algorithms/sort/counting_sort.py
counting_sort
def counting_sort(arr): """ Counting_sort Sorting a array which has no element greater than k Creating a new temp_arr,where temp_arr[i] contain the number of element less than or equal to i in the arr Then placing the number i into a correct position in the result_arr return the result_arr Complexity: 0(n) """ m = min(arr) # in case there are negative elements, change the array to all positive element different = 0 if m < 0: # save the change, so that we can convert the array back to all positive number different = -m for i in range(len(arr)): arr[i] += -m k = max(arr) temp_arr = [0] * (k + 1) for i in range(0, len(arr)): temp_arr[arr[i]] = temp_arr[arr[i]] + 1 # temp_array[i] contain the times the number i appear in arr for i in range(1, k + 1): temp_arr[i] = temp_arr[i] + temp_arr[i - 1] # temp_array[i] contain the number of element less than or equal i in arr result_arr = arr.copy() # creating a result_arr an put the element in a correct positon for i in range(len(arr) - 1, -1, -1): result_arr[temp_arr[arr[i]] - 1] = arr[i] - different temp_arr[arr[i]] = temp_arr[arr[i]] - 1 return result_arr
python
def counting_sort(arr): """ Counting_sort Sorting a array which has no element greater than k Creating a new temp_arr,where temp_arr[i] contain the number of element less than or equal to i in the arr Then placing the number i into a correct position in the result_arr return the result_arr Complexity: 0(n) """ m = min(arr) # in case there are negative elements, change the array to all positive element different = 0 if m < 0: # save the change, so that we can convert the array back to all positive number different = -m for i in range(len(arr)): arr[i] += -m k = max(arr) temp_arr = [0] * (k + 1) for i in range(0, len(arr)): temp_arr[arr[i]] = temp_arr[arr[i]] + 1 # temp_array[i] contain the times the number i appear in arr for i in range(1, k + 1): temp_arr[i] = temp_arr[i] + temp_arr[i - 1] # temp_array[i] contain the number of element less than or equal i in arr result_arr = arr.copy() # creating a result_arr an put the element in a correct positon for i in range(len(arr) - 1, -1, -1): result_arr[temp_arr[arr[i]] - 1] = arr[i] - different temp_arr[arr[i]] = temp_arr[arr[i]] - 1 return result_arr
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ArduPilot/MAVProxy
MAVProxy/modules/mavproxy_restserver.py
mavlink_to_json
def mavlink_to_json(msg): '''Translate mavlink python messages in json string''' ret = '\"%s\": {' % msg._type for fieldname in msg._fieldnames: data = getattr(msg, fieldname) ret += '\"%s\" : \"%s\", ' % (fieldname, data) ret = ret[0:-2] + '}' return ret
python
def mavlink_to_json(msg): '''Translate mavlink python messages in json string''' ret = '\"%s\": {' % msg._type for fieldname in msg._fieldnames: data = getattr(msg, fieldname) ret += '\"%s\" : \"%s\", ' % (fieldname, data) ret = ret[0:-2] + '}' return ret
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DistrictDataLabs/yellowbrick
yellowbrick/cluster/icdm.py
InterclusterDistance._make_size_legend
def _make_size_legend(self): """ Draw a legend that shows relative sizes of the clusters at the 25th, 50th, and 75th percentile based on the current scoring metric. """ # Compute the size of the markers and scale them to our figure size # NOTE: the marker size is the area of the plot, we need to compute the # radius of the markers. areas = self._get_cluster_sizes() radii = np.sqrt(areas / np.pi) scaled = np.interp(radii, (radii.min(), radii.max()), (.1, 1)) # Compute the locations of the 25th, 50th, and 75th percentile scores indices = np.array([ percentile_index(self.scores_, p) for p in (25, 50, 75) ]) # Draw size circles annotated with the percentile score as the legend. for idx in indices: # TODO: should the size circle's center be hard coded like this? center = (-0.30, 1-scaled[idx]) c = Circle( center, scaled[idx], facecolor="none", edgecolor="#2e7193", linewidth=1.5, linestyle="--" ) self.lax.add_patch(c) # Add annotation to the size circle with the value of the score self.lax.annotate( self.scores_[idx], (-0.30, 1-(2*scaled[idx])), xytext=(1, 1-(2*scaled[idx])), arrowprops=dict(arrowstyle="wedge", color="#2e7193"), va='center', ha='center', ) # Draw size legend title self.lax.text(s="membership", x=0, y=1.2, va='center', ha='center') # Ensure the current axes is always the main axes after modifying the # inset axes and while drawing. plt.sca(self.ax)
python
def _make_size_legend(self): """ Draw a legend that shows relative sizes of the clusters at the 25th, 50th, and 75th percentile based on the current scoring metric. """ # Compute the size of the markers and scale them to our figure size # NOTE: the marker size is the area of the plot, we need to compute the # radius of the markers. areas = self._get_cluster_sizes() radii = np.sqrt(areas / np.pi) scaled = np.interp(radii, (radii.min(), radii.max()), (.1, 1)) # Compute the locations of the 25th, 50th, and 75th percentile scores indices = np.array([ percentile_index(self.scores_, p) for p in (25, 50, 75) ]) # Draw size circles annotated with the percentile score as the legend. for idx in indices: # TODO: should the size circle's center be hard coded like this? center = (-0.30, 1-scaled[idx]) c = Circle( center, scaled[idx], facecolor="none", edgecolor="#2e7193", linewidth=1.5, linestyle="--" ) self.lax.add_patch(c) # Add annotation to the size circle with the value of the score self.lax.annotate( self.scores_[idx], (-0.30, 1-(2*scaled[idx])), xytext=(1, 1-(2*scaled[idx])), arrowprops=dict(arrowstyle="wedge", color="#2e7193"), va='center', ha='center', ) # Draw size legend title self.lax.text(s="membership", x=0, y=1.2, va='center', ha='center') # Ensure the current axes is always the main axes after modifying the # inset axes and while drawing. plt.sca(self.ax)
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PMEAL/OpenPNM
openpnm/models/phases/vapor_pressure.py
antoine
def antoine(target, A, B, C, temperature='pore.temperature'): r""" Uses Antoine equation [1] to estimate vapor pressure of a pure component Parameters ---------- target : OpenPNM Object The object for which these values are being calculated. This controls the length of the calculated array, and also provides access to other necessary thermofluid properties. A, B, C : scalars Antoine vapor pressure coefficients for pure compounds. Since virtually all Antoine coefficients are reported for units of mmHg and C for historical reaons, this method assumes these A, B and C values are for mmHg and C, but converts all properties internally to return Pascals. temperature : string The dictionary key containing the phase temperature values in Kelvin [K]. Can be either pore or throat values. [1] Antoine, C. (1888), Vapor Pressure: a new relationship between pressure and temperature, Comptes Rendus des Séances de l'Académie des Sciences (in French) 107: 681–684, 778–780, 836–837 """ T = target[temperature] - 273.15 value = (10**(A-B/(C+T)))/760*101325 return value
python
def antoine(target, A, B, C, temperature='pore.temperature'): r""" Uses Antoine equation [1] to estimate vapor pressure of a pure component Parameters ---------- target : OpenPNM Object The object for which these values are being calculated. This controls the length of the calculated array, and also provides access to other necessary thermofluid properties. A, B, C : scalars Antoine vapor pressure coefficients for pure compounds. Since virtually all Antoine coefficients are reported for units of mmHg and C for historical reaons, this method assumes these A, B and C values are for mmHg and C, but converts all properties internally to return Pascals. temperature : string The dictionary key containing the phase temperature values in Kelvin [K]. Can be either pore or throat values. [1] Antoine, C. (1888), Vapor Pressure: a new relationship between pressure and temperature, Comptes Rendus des Séances de l'Académie des Sciences (in French) 107: 681–684, 778–780, 836–837 """ T = target[temperature] - 273.15 value = (10**(A-B/(C+T)))/760*101325 return value
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holgern/pyedflib
pyedflib/edfreader.py
EdfReader.getPhysicalMinimum
def getPhysicalMinimum(self,chn=None): """ Returns the minimum physical value of signal edfsignal. Parameters ---------- chn : int channel number Examples -------- >>> import pyedflib >>> f = pyedflib.data.test_generator() >>> f.getPhysicalMinimum(0)==-1000.0 True >>> f._close() >>> del f """ if chn is not None: if 0 <= chn < self.signals_in_file: return self.physical_min(chn) else: return 0 else: physMin = np.zeros(self.signals_in_file) for i in np.arange(self.signals_in_file): physMin[i] = self.physical_min(i) return physMin
python
def getPhysicalMinimum(self,chn=None): """ Returns the minimum physical value of signal edfsignal. Parameters ---------- chn : int channel number Examples -------- >>> import pyedflib >>> f = pyedflib.data.test_generator() >>> f.getPhysicalMinimum(0)==-1000.0 True >>> f._close() >>> del f """ if chn is not None: if 0 <= chn < self.signals_in_file: return self.physical_min(chn) else: return 0 else: physMin = np.zeros(self.signals_in_file) for i in np.arange(self.signals_in_file): physMin[i] = self.physical_min(i) return physMin
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Azure/blobxfer
blobxfer/operations/synccopy.py
SyncCopy._update_progress_bar
def _update_progress_bar(self): # type: (SyncCopy) -> None """Update progress bar :param SyncCopy self: this """ blobxfer.operations.progress.update_progress_bar( self._general_options, 'synccopy', self._synccopy_start_time, self._synccopy_total, self._synccopy_sofar, self._synccopy_bytes_total, self._synccopy_bytes_sofar, )
python
def _update_progress_bar(self): # type: (SyncCopy) -> None """Update progress bar :param SyncCopy self: this """ blobxfer.operations.progress.update_progress_bar( self._general_options, 'synccopy', self._synccopy_start_time, self._synccopy_total, self._synccopy_sofar, self._synccopy_bytes_total, self._synccopy_bytes_sofar, )
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reingart/pyafipws
wsctg.py
WSCTG.RechazarCTG
def RechazarCTG(self, carta_porte, ctg, motivo): "El Destino puede rechazar el CTG a través de la siguiente operatoria" response = self.client.rechazarCTG(request=dict( auth={ 'token': self.Token, 'sign': self.Sign, 'cuitRepresentado': self.Cuit, }, datosRechazarCTG={ 'cartaPorte': carta_porte, 'ctg': ctg, 'motivoRechazo': motivo, }))['response'] datos = response.get('datosResponse') self.__analizar_errores(response) if datos: self.CartaPorte = str(datos['cartaPorte']) self.NumeroCTG = str(datos['CTG']) self.FechaHora = str(datos['fechaHora']) self.CodigoOperacion = str(datos['codigoOperacion'])
python
def RechazarCTG(self, carta_porte, ctg, motivo): "El Destino puede rechazar el CTG a través de la siguiente operatoria" response = self.client.rechazarCTG(request=dict( auth={ 'token': self.Token, 'sign': self.Sign, 'cuitRepresentado': self.Cuit, }, datosRechazarCTG={ 'cartaPorte': carta_porte, 'ctg': ctg, 'motivoRechazo': motivo, }))['response'] datos = response.get('datosResponse') self.__analizar_errores(response) if datos: self.CartaPorte = str(datos['cartaPorte']) self.NumeroCTG = str(datos['CTG']) self.FechaHora = str(datos['fechaHora']) self.CodigoOperacion = str(datos['codigoOperacion'])
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third_party/miniboa-r42/miniboa/telnet.py
TelnetClient._note_reply_pending
def _note_reply_pending(self, option, state): """Record the status of requested Telnet options.""" if not self.telnet_opt_dict.has_key(option): self.telnet_opt_dict[option] = TelnetOption() self.telnet_opt_dict[option].reply_pending = state
python
def _note_reply_pending(self, option, state): """Record the status of requested Telnet options.""" if not self.telnet_opt_dict.has_key(option): self.telnet_opt_dict[option] = TelnetOption() self.telnet_opt_dict[option].reply_pending = state
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SUNCAT-Center/CatHub
cathub/cathubsqlite.py
CathubSQLite._initialize
def _initialize(self, con): """Set up tables in SQL""" if self.initialized: return SQLite3Database()._initialize(con) # ASE db initialization cur = con.execute( 'SELECT COUNT(*) FROM sqlite_master WHERE name="reaction"') if cur.fetchone()[0] == 0: # no reaction table for init_command in init_commands: con.execute(init_command) # Create tables con.commit() self.initialized = True
python
def _initialize(self, con): """Set up tables in SQL""" if self.initialized: return SQLite3Database()._initialize(con) # ASE db initialization cur = con.execute( 'SELECT COUNT(*) FROM sqlite_master WHERE name="reaction"') if cur.fetchone()[0] == 0: # no reaction table for init_command in init_commands: con.execute(init_command) # Create tables con.commit() self.initialized = True
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vpelletier/python-functionfs
examples/usbcat/device.py
USBCat.onEnable
def onEnable(self): """ The configuration containing this function has been enabled by host. Endpoints become working files, so submit some read operations. """ trace('onEnable') self._disable() self._aio_context.submit(self._aio_recv_block_list) self._real_onCanSend() self._enabled = True
python
def onEnable(self): """ The configuration containing this function has been enabled by host. Endpoints become working files, so submit some read operations. """ trace('onEnable') self._disable() self._aio_context.submit(self._aio_recv_block_list) self._real_onCanSend() self._enabled = True
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fjwCode/cerium
cerium/androiddriver.py
BaseAndroidDriver.find_element_by_name
def find_element_by_name(self, name, update=False) -> Elements: '''Finds an element by name. Args: name: The name of the element to be found. update: If the interface has changed, this option should be True. Returns: The element if it was found. Raises: NoSuchElementException - If the element wasn't found. Usage: element = driver.find_element_by_name('foo') ''' return self.find_element(by=By.NAME, value=name, update=update)
python
def find_element_by_name(self, name, update=False) -> Elements: '''Finds an element by name. Args: name: The name of the element to be found. update: If the interface has changed, this option should be True. Returns: The element if it was found. Raises: NoSuchElementException - If the element wasn't found. Usage: element = driver.find_element_by_name('foo') ''' return self.find_element(by=By.NAME, value=name, update=update)
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ejeschke/ginga
ginga/Bindings.py
ImageViewBindings.ms_panset
def ms_panset(self, viewer, event, data_x, data_y, msg=True): """An interactive way to set the pan position. The location (data_x, data_y) will be centered in the window. """ if self.canpan and (event.state == 'down'): self._panset(viewer, data_x, data_y, msg=msg) return True
python
def ms_panset(self, viewer, event, data_x, data_y, msg=True): """An interactive way to set the pan position. The location (data_x, data_y) will be centered in the window. """ if self.canpan and (event.state == 'down'): self._panset(viewer, data_x, data_y, msg=msg) return True
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mapbox/mapboxgl-jupyter
mapboxgl/viz.py
CircleViz.add_unique_template_variables
def add_unique_template_variables(self, options): """Update map template variables specific to circle visual""" options.update(dict( geojson_data=json.dumps(self.data, ensure_ascii=False), colorProperty=self.color_property, colorType=self.color_function_type, colorStops=self.color_stops, strokeWidth=self.stroke_width, strokeColor=self.stroke_color, radius=self.radius, defaultColor=self.color_default, highlightColor=self.highlight_color )) if self.vector_source: options.update(vectorColorStops=self.generate_vector_color_map())
python
def add_unique_template_variables(self, options): """Update map template variables specific to circle visual""" options.update(dict( geojson_data=json.dumps(self.data, ensure_ascii=False), colorProperty=self.color_property, colorType=self.color_function_type, colorStops=self.color_stops, strokeWidth=self.stroke_width, strokeColor=self.stroke_color, radius=self.radius, defaultColor=self.color_default, highlightColor=self.highlight_color )) if self.vector_source: options.update(vectorColorStops=self.generate_vector_color_map())
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googledatalab/pydatalab
google/datalab/bigquery/commands/_bigquery.py
_dataset_line
def _dataset_line(args): """Implements the BigQuery dataset magic subcommand used to operate on datasets The supported syntax is: %bq datasets <command> <args> Commands: {list, create, delete} Args: args: the optional arguments following '%bq datasets command'. """ if args['command'] == 'list': filter_ = args['filter'] if args['filter'] else '*' context = google.datalab.Context.default() if args['project']: context = google.datalab.Context(args['project'], context.credentials) return _render_list([str(dataset) for dataset in bigquery.Datasets(context) if fnmatch.fnmatch(str(dataset), filter_)]) elif args['command'] == 'create': try: bigquery.Dataset(args['name']).create(friendly_name=args['friendly']) except Exception as e: print('Failed to create dataset %s: %s' % (args['name'], e)) elif args['command'] == 'delete': try: bigquery.Dataset(args['name']).delete() except Exception as e: print('Failed to delete dataset %s: %s' % (args['name'], e))
python
def _dataset_line(args): """Implements the BigQuery dataset magic subcommand used to operate on datasets The supported syntax is: %bq datasets <command> <args> Commands: {list, create, delete} Args: args: the optional arguments following '%bq datasets command'. """ if args['command'] == 'list': filter_ = args['filter'] if args['filter'] else '*' context = google.datalab.Context.default() if args['project']: context = google.datalab.Context(args['project'], context.credentials) return _render_list([str(dataset) for dataset in bigquery.Datasets(context) if fnmatch.fnmatch(str(dataset), filter_)]) elif args['command'] == 'create': try: bigquery.Dataset(args['name']).create(friendly_name=args['friendly']) except Exception as e: print('Failed to create dataset %s: %s' % (args['name'], e)) elif args['command'] == 'delete': try: bigquery.Dataset(args['name']).delete() except Exception as e: print('Failed to delete dataset %s: %s' % (args['name'], e))
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ArchiveTeam/wpull
wpull/pipeline/session.py
ItemSession.set_status
def set_status(self, status: Status, increment_try_count: bool=True, filename: str=None): '''Mark the item with the given status. Args: status: a value from :class:`Status`. increment_try_count: if True, increment the ``try_count`` value ''' url = self.url_record.url assert not self._try_count_incremented, (url, status) if increment_try_count: self._try_count_incremented = True _logger.debug(__('Marking URL {0} status {1}.', url, status)) url_result = URLResult() url_result.filename = filename self.app_session.factory['URLTable'].check_in( url, status, increment_try_count=increment_try_count, url_result=url_result, ) self._processed = True
python
def set_status(self, status: Status, increment_try_count: bool=True, filename: str=None): '''Mark the item with the given status. Args: status: a value from :class:`Status`. increment_try_count: if True, increment the ``try_count`` value ''' url = self.url_record.url assert not self._try_count_incremented, (url, status) if increment_try_count: self._try_count_incremented = True _logger.debug(__('Marking URL {0} status {1}.', url, status)) url_result = URLResult() url_result.filename = filename self.app_session.factory['URLTable'].check_in( url, status, increment_try_count=increment_try_count, url_result=url_result, ) self._processed = True
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iDigBio/idigbio-python-client
idigbio/pandas_client.py
iDbApiPandas.search_records
def search_records(self, **kwargs): """ rq Search Query in iDigBio Query Format, using Record Query Fields sort field to sort on, pick from Record Query Fields fields a list of fields to return, specified using the fieldName parameter from Fields with type records fields_exclude a list of fields to exclude, specified using the fieldName parameter from Fields with type records limit max results offset skip results Returns idigbio record format (legacy api), plus additional top level keys with parsed index terms. Returns None on error. """ return self.__search_base(apifn=self.__api.search_records, **kwargs)
python
def search_records(self, **kwargs): """ rq Search Query in iDigBio Query Format, using Record Query Fields sort field to sort on, pick from Record Query Fields fields a list of fields to return, specified using the fieldName parameter from Fields with type records fields_exclude a list of fields to exclude, specified using the fieldName parameter from Fields with type records limit max results offset skip results Returns idigbio record format (legacy api), plus additional top level keys with parsed index terms. Returns None on error. """ return self.__search_base(apifn=self.__api.search_records, **kwargs)
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train
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major/supernova
supernova/supernova.py
execute_executable
def execute_executable(nova_args, env_vars): """ Executes the executable given by the user. Hey, I know this method has a silly name, but I write the code here and I'm silly. """ process = subprocess.Popen(nova_args, stdout=sys.stdout, stderr=subprocess.PIPE, env=env_vars) process.wait() return process
python
def execute_executable(nova_args, env_vars): """ Executes the executable given by the user. Hey, I know this method has a silly name, but I write the code here and I'm silly. """ process = subprocess.Popen(nova_args, stdout=sys.stdout, stderr=subprocess.PIPE, env=env_vars) process.wait() return process
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r0x0r/pywebview
webview/__init__.py
create_window
def create_window(title, url=None, js_api=None, width=800, height=600, resizable=True, fullscreen=False, min_size=(200, 100), strings={}, confirm_quit=False, background_color='#FFFFFF', text_select=False, frameless=False, debug=False): """ Create a web view window using a native GUI. The execution blocks after this function is invoked, so other program logic must be executed in a separate thread. :param title: Window title :param url: URL to load :param width: window width. Default is 800px :param height:window height. Default is 600px :param resizable True if window can be resized, False otherwise. Default is True :param fullscreen: True if start in fullscreen mode. Default is False :param min_size: a (width, height) tuple that specifies a minimum window size. Default is 200x100 :param strings: a dictionary with localized strings :param confirm_quit: Display a quit confirmation dialog. Default is False :param background_color: Background color as a hex string that is displayed before the content of webview is loaded. Default is white. :param text_select: Allow text selection on page. Default is False. :param frameless: Whether the window should have a frame. :return: The uid of the created window. """ valid_color = r'^#(?:[0-9a-fA-F]{3}){1,2}$' if not re.match(valid_color, background_color): raise ValueError('{0} is not a valid hex triplet color'.format(background_color)) # Check if starting up from main thread; if not, wait; finally raise exception if current_thread().name == 'MainThread': uid = 'master' if not _initialized: _initialize_imports() localization.update(strings) else: uid = 'child_' + uuid4().hex[:8] if not _webview_ready.wait(5): raise Exception('Call create_window from the main thread first') _webview_ready.clear() # Make API calls wait while the new window is created gui.create_window(uid, make_unicode(title), transform_url(url), width, height, resizable, fullscreen, min_size, confirm_quit, background_color, debug, js_api, text_select, frameless, _webview_ready) if uid == 'master': _webview_ready.clear() else: return uid
python
def create_window(title, url=None, js_api=None, width=800, height=600, resizable=True, fullscreen=False, min_size=(200, 100), strings={}, confirm_quit=False, background_color='#FFFFFF', text_select=False, frameless=False, debug=False): """ Create a web view window using a native GUI. The execution blocks after this function is invoked, so other program logic must be executed in a separate thread. :param title: Window title :param url: URL to load :param width: window width. Default is 800px :param height:window height. Default is 600px :param resizable True if window can be resized, False otherwise. Default is True :param fullscreen: True if start in fullscreen mode. Default is False :param min_size: a (width, height) tuple that specifies a minimum window size. Default is 200x100 :param strings: a dictionary with localized strings :param confirm_quit: Display a quit confirmation dialog. Default is False :param background_color: Background color as a hex string that is displayed before the content of webview is loaded. Default is white. :param text_select: Allow text selection on page. Default is False. :param frameless: Whether the window should have a frame. :return: The uid of the created window. """ valid_color = r'^#(?:[0-9a-fA-F]{3}){1,2}$' if not re.match(valid_color, background_color): raise ValueError('{0} is not a valid hex triplet color'.format(background_color)) # Check if starting up from main thread; if not, wait; finally raise exception if current_thread().name == 'MainThread': uid = 'master' if not _initialized: _initialize_imports() localization.update(strings) else: uid = 'child_' + uuid4().hex[:8] if not _webview_ready.wait(5): raise Exception('Call create_window from the main thread first') _webview_ready.clear() # Make API calls wait while the new window is created gui.create_window(uid, make_unicode(title), transform_url(url), width, height, resizable, fullscreen, min_size, confirm_quit, background_color, debug, js_api, text_select, frameless, _webview_ready) if uid == 'master': _webview_ready.clear() else: return uid
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codeinn/vcs
vcs/backends/hg/changeset.py
MercurialChangeset.parents
def parents(self): """ Returns list of parents changesets. """ return [self.repository.get_changeset(parent.rev()) for parent in self._ctx.parents() if parent.rev() >= 0]
python
def parents(self): """ Returns list of parents changesets. """ return [self.repository.get_changeset(parent.rev()) for parent in self._ctx.parents() if parent.rev() >= 0]
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lk-geimfari/mimesis
mimesis/random.py
Random.urandom
def urandom(*args: Any, **kwargs: Any) -> bytes: """Return a bytes object containing random bytes. :return: Bytes. """ return os.urandom(*args, **kwargs)
python
def urandom(*args: Any, **kwargs: Any) -> bytes: """Return a bytes object containing random bytes. :return: Bytes. """ return os.urandom(*args, **kwargs)
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MillionIntegrals/vel
vel/rl/algo/dqn.py
DeepQLearning.post_optimization_step
def post_optimization_step(self, batch_info, device, model, rollout): """ Steps to take after optimization has been done""" if batch_info.aggregate_batch_number % self.target_update_frequency == 0: self.target_model.load_state_dict(model.state_dict()) self.target_model.eval()
python
def post_optimization_step(self, batch_info, device, model, rollout): """ Steps to take after optimization has been done""" if batch_info.aggregate_batch_number % self.target_update_frequency == 0: self.target_model.load_state_dict(model.state_dict()) self.target_model.eval()
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CybOXProject/mixbox
mixbox/datautils.py
needkwargs
def needkwargs(*argnames): """Function decorator which checks that the decorated function is called with a set of required kwargs. Args: *argnames: String keyword argument names. Raises: ValueError: If a required kwarg is missing in the decorated function call. """ required = set(argnames) def decorator(func): def inner(*args, **kwargs): missing = required - set(kwargs) if missing: err = "%s kwargs are missing." % list(missing) raise ValueError(err) return func(*args, **kwargs) return inner return decorator
python
def needkwargs(*argnames): """Function decorator which checks that the decorated function is called with a set of required kwargs. Args: *argnames: String keyword argument names. Raises: ValueError: If a required kwarg is missing in the decorated function call. """ required = set(argnames) def decorator(func): def inner(*args, **kwargs): missing = required - set(kwargs) if missing: err = "%s kwargs are missing." % list(missing) raise ValueError(err) return func(*args, **kwargs) return inner return decorator
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pkkid/python-plexapi
plexapi/library.py
PhotoSection.sync
def sync(self, resolution, limit=None, **kwargs): """ Add current Music library section as sync item for specified device. See description of :func:`plexapi.library.LibrarySection.search()` for details about filtering / sorting and :func:`plexapi.library.LibrarySection.sync()` for details on syncing libraries and possible exceptions. Parameters: resolution (str): maximum allowed resolution for synchronized photos, see PHOTO_QUALITY_* values in the module :mod:`plexapi.sync`. limit (int): maximum count of tracks to sync, unlimited if `None`. Returns: :class:`plexapi.sync.SyncItem`: an instance of created syncItem. Example: .. code-block:: python from plexapi import myplex from plexapi.sync import PHOTO_QUALITY_HIGH c = myplex.MyPlexAccount() target = c.device('Plex Client') sync_items_wd = c.syncItems(target.clientIdentifier) srv = c.resource('Server Name').connect() section = srv.library.section('Photos') section.sync(PHOTO_QUALITY_HIGH, client=target, limit=100, sort='addedAt:desc', title='Fresh photos') """ from plexapi.sync import Policy, MediaSettings kwargs['mediaSettings'] = MediaSettings.createPhoto(resolution) kwargs['policy'] = Policy.create(limit) return super(PhotoSection, self).sync(**kwargs)
python
def sync(self, resolution, limit=None, **kwargs): """ Add current Music library section as sync item for specified device. See description of :func:`plexapi.library.LibrarySection.search()` for details about filtering / sorting and :func:`plexapi.library.LibrarySection.sync()` for details on syncing libraries and possible exceptions. Parameters: resolution (str): maximum allowed resolution for synchronized photos, see PHOTO_QUALITY_* values in the module :mod:`plexapi.sync`. limit (int): maximum count of tracks to sync, unlimited if `None`. Returns: :class:`plexapi.sync.SyncItem`: an instance of created syncItem. Example: .. code-block:: python from plexapi import myplex from plexapi.sync import PHOTO_QUALITY_HIGH c = myplex.MyPlexAccount() target = c.device('Plex Client') sync_items_wd = c.syncItems(target.clientIdentifier) srv = c.resource('Server Name').connect() section = srv.library.section('Photos') section.sync(PHOTO_QUALITY_HIGH, client=target, limit=100, sort='addedAt:desc', title='Fresh photos') """ from plexapi.sync import Policy, MediaSettings kwargs['mediaSettings'] = MediaSettings.createPhoto(resolution) kwargs['policy'] = Policy.create(limit) return super(PhotoSection, self).sync(**kwargs)
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saltstack/salt
salt/states/panos.py
download_software
def download_software(name, version=None, synch=False, check=False): ''' Ensures that a software version is downloaded. name: The name of the module function to execute. version(str): The software version to check. If this version is not already downloaded, it will attempt to download the file from Palo Alto. synch(bool): If true, after downloading the file it will be synched to its peer. check(bool): If true, the PANOS device will first attempt to pull the most recent software inventory list from Palo Alto. SLS Example: .. code-block:: yaml panos/version8.0.0: panos.download_software: - version: 8.0.0 - synch: False - check: True ''' ret = _default_ret(name) if check is True: __salt__['panos.check_software']() versions = __salt__['panos.get_software_info']()['result'] if 'sw-updates' not in versions \ or 'versions' not in versions['sw-updates'] \ or 'entry' not in versions['sw-updates']['versions']: ret.update({ 'comment': 'Software version is not found in the local software list.', 'result': False }) return ret for entry in versions['sw-updates']['versions']['entry']: if entry['version'] == version and entry['downloaded'] == "yes": ret.update({ 'comment': 'Software version is already downloaded.', 'result': True }) return ret ret.update({ 'changes': __salt__['panos.download_software_version'](version=version, synch=synch) }) versions = __salt__['panos.get_software_info']()['result'] if 'sw-updates' not in versions \ or 'versions' not in versions['sw-updates'] \ or 'entry' not in versions['sw-updates']['versions']: ret.update({ 'result': False }) return ret for entry in versions['sw-updates']['versions']['entry']: if entry['version'] == version and entry['downloaded'] == "yes": ret.update({ 'result': True }) return ret return ret
python
def download_software(name, version=None, synch=False, check=False): ''' Ensures that a software version is downloaded. name: The name of the module function to execute. version(str): The software version to check. If this version is not already downloaded, it will attempt to download the file from Palo Alto. synch(bool): If true, after downloading the file it will be synched to its peer. check(bool): If true, the PANOS device will first attempt to pull the most recent software inventory list from Palo Alto. SLS Example: .. code-block:: yaml panos/version8.0.0: panos.download_software: - version: 8.0.0 - synch: False - check: True ''' ret = _default_ret(name) if check is True: __salt__['panos.check_software']() versions = __salt__['panos.get_software_info']()['result'] if 'sw-updates' not in versions \ or 'versions' not in versions['sw-updates'] \ or 'entry' not in versions['sw-updates']['versions']: ret.update({ 'comment': 'Software version is not found in the local software list.', 'result': False }) return ret for entry in versions['sw-updates']['versions']['entry']: if entry['version'] == version and entry['downloaded'] == "yes": ret.update({ 'comment': 'Software version is already downloaded.', 'result': True }) return ret ret.update({ 'changes': __salt__['panos.download_software_version'](version=version, synch=synch) }) versions = __salt__['panos.get_software_info']()['result'] if 'sw-updates' not in versions \ or 'versions' not in versions['sw-updates'] \ or 'entry' not in versions['sw-updates']['versions']: ret.update({ 'result': False }) return ret for entry in versions['sw-updates']['versions']['entry']: if entry['version'] == version and entry['downloaded'] == "yes": ret.update({ 'result': True }) return ret return ret
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def add_star(self, component=None, **kwargs): """ Shortcut to :meth:`add_component` but with kind='star' """ kwargs.setdefault('component', component) return self.add_component('star', **kwargs)
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def add_star(self, component=None, **kwargs): """ Shortcut to :meth:`add_component` but with kind='star' """ kwargs.setdefault('component', component) return self.add_component('star', **kwargs)
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wdom/element.py
getElementsByClassName
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def getElementsByClassName(start_node: ParentNode, class_name: str ) -> NodeList: """Get child nodes which has ``class_name`` class attribute.""" classes = set(class_name.split(' ')) return getElementsBy( start_node, lambda node: classes.issubset(set(node.classList)) )
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gc3-uzh-ch/elasticluster
elasticluster/providers/openstack.py
OpenStackCloudProvider.start_instance
def start_instance(self, key_name, public_key_path, private_key_path, security_group, flavor, image_id, image_userdata, username=None, node_name=None, **kwargs): """Starts a new instance on the cloud using the given properties. The following tasks are done to start an instance: * establish a connection to the cloud web service * check ssh keypair and upload it if it does not yet exist. This is a locked process, since this function might be called in multiple threads and we only want the key to be stored once. * check if the security group exists * run the instance with the given properties :param str key_name: name of the ssh key to connect :param str public_key_path: path to ssh public key :param str private_key_path: path to ssh private key :param str security_group: firewall rule definition to apply on the instance :param str flavor: machine type to use for the instance :param str image_id: image type (os) to use for the instance :param str image_userdata: command to execute after startup :param str username: username for the given ssh key, default None :return: str - instance id of the started instance """ self._init_os_api() vm_start_args = {} log.debug("Checking keypair `%s` ...", key_name) with OpenStackCloudProvider.__node_start_lock: self._check_keypair(key_name, public_key_path, private_key_path) vm_start_args['key_name'] = key_name security_groups = [sg.strip() for sg in security_group.split(',')] self._check_security_groups(security_groups) vm_start_args['security_groups'] = security_groups # Check if the image id is present. if image_id not in [img.id for img in self._get_images()]: raise ImageError( "No image found with ID `{0}` in project `{1}` of cloud {2}" .format(image_id, self._os_tenant_name, self._os_auth_url)) vm_start_args['userdata'] = image_userdata # Check if the flavor exists flavors = [fl for fl in self._get_flavors() if fl.name == flavor] if not flavors: raise FlavorError( "No flavor found with name `{0}` in project `{1}` of cloud {2}" .format(flavor, self._os_tenant_name, self._os_auth_url)) flavor = flavors[0] availability_zone = kwargs.pop('availability_zone','') vm_start_args['availability_zone']=availability_zone network_ids = [net_id.strip() for net_id in kwargs.pop('network_ids', '').split(',')] if network_ids: nics = [{'net-id': net_id, 'v4-fixed-ip': ''} for net_id in network_ids ] log.debug("Specifying networks for node %s: %s", node_name, ', '.join([nic['net-id'] for nic in nics])) else: nics = None vm_start_args['nics'] = nics if 'boot_disk_size' in kwargs: # check if the backing volume is already there volume_name = '{name}-{id}'.format(name=node_name, id=image_id) if volume_name in [v.name for v in self._get_volumes()]: raise ImageError( "Volume `{0}` already exists in project `{1}` of cloud {2}" .format(volume_name, self._os_tenant_name, self._os_auth_url)) log.info('Creating volume `%s` to use as VM disk ...', volume_name) try: bds = int(kwargs['boot_disk_size']) if bds < 1: raise ValueError('non-positive int') except (ValueError, TypeError): raise ConfigurationError( "Invalid `boot_disk_size` specified:" " should be a positive integer, got {0} instead" .format(kwargs['boot_disk_size'])) volume = self.cinder_client.volumes.create( size=bds, name=volume_name, imageRef=image_id, volume_type=kwargs.pop('boot_disk_type')) # wait for volume to come up volume_available = False while not volume_available: for v in self._get_volumes(): if v.name == volume_name and v.status == 'available': volume_available = True break sleep(1) # FIXME: hard-coded waiting time # ok, use volume as VM disk vm_start_args['block_device_mapping'] = { # FIXME: is it possible that `vda` is not the boot disk? e.g. if # a non-paravirtualized kernel is being used? should we allow # to set the boot device as an image parameter? 'vda': ('{id}:::{delete_on_terminate}' .format(id=volume.id, delete_on_terminate=1)), } # due to some `nova_client.servers.create()` implementation weirdness, # the first three args need to be spelt out explicitly and cannot be # conflated into `**vm_start_args` vm = self.nova_client.servers.create(node_name, image_id, flavor, **vm_start_args) # allocate and attach a floating IP, if requested request_floating_ip = kwargs.get( 'request_floating_ip', self._request_floating_ip_default) if request_floating_ip: # wait for server to come up (otherwise floating IP can't be associated) log.info("Waiting for instance `%s` (%s) to come up ...", node_name, vm.id) max_wait = int(kwargs.get('max_wait', 300)) waited = 0 while waited < max_wait: if vm.status == 'ACTIVE': break if vm.status == 'ERROR': raise RuntimeError( "Failed to start VM {0}:" " OpenStack scheduling error." .format(vm.id)) vm = self.nova_client.servers.get(vm.id) # FIXME: Configurable poll interval sleep(3) waited += 3 else: raise RuntimeError( "VM {0} didn't come up in {1:d} seconds" .format(vm.id, max_wait)) # We need to list the floating IPs for this instance try: # python-novaclient <8.0.0 floating_ips = [ip for ip in self.nova_client.floating_ips.list() if ip.instance_id == vm.id] except AttributeError: floating_ips = ( self.neutron_client .list_floatingips(id=vm.id) .get('floating_ips', [])) # allocate new floating IP if none given if not floating_ips: if 'floating_network_id' in kwargs: floating_networks = [kwargs.pop('floating_network_id')] else: floating_networks = network_ids[:] ip_addr = self._allocate_address(vm, floating_networks) log.debug("VM `%s` was allocated floating IP: %r", vm.id, ip_addr) else: log.debug("VM `%s` already allocated floating IPs: %r", vm.id, floating_ips) self._instances[vm.id] = vm return vm.id
python
def start_instance(self, key_name, public_key_path, private_key_path, security_group, flavor, image_id, image_userdata, username=None, node_name=None, **kwargs): """Starts a new instance on the cloud using the given properties. The following tasks are done to start an instance: * establish a connection to the cloud web service * check ssh keypair and upload it if it does not yet exist. This is a locked process, since this function might be called in multiple threads and we only want the key to be stored once. * check if the security group exists * run the instance with the given properties :param str key_name: name of the ssh key to connect :param str public_key_path: path to ssh public key :param str private_key_path: path to ssh private key :param str security_group: firewall rule definition to apply on the instance :param str flavor: machine type to use for the instance :param str image_id: image type (os) to use for the instance :param str image_userdata: command to execute after startup :param str username: username for the given ssh key, default None :return: str - instance id of the started instance """ self._init_os_api() vm_start_args = {} log.debug("Checking keypair `%s` ...", key_name) with OpenStackCloudProvider.__node_start_lock: self._check_keypair(key_name, public_key_path, private_key_path) vm_start_args['key_name'] = key_name security_groups = [sg.strip() for sg in security_group.split(',')] self._check_security_groups(security_groups) vm_start_args['security_groups'] = security_groups # Check if the image id is present. if image_id not in [img.id for img in self._get_images()]: raise ImageError( "No image found with ID `{0}` in project `{1}` of cloud {2}" .format(image_id, self._os_tenant_name, self._os_auth_url)) vm_start_args['userdata'] = image_userdata # Check if the flavor exists flavors = [fl for fl in self._get_flavors() if fl.name == flavor] if not flavors: raise FlavorError( "No flavor found with name `{0}` in project `{1}` of cloud {2}" .format(flavor, self._os_tenant_name, self._os_auth_url)) flavor = flavors[0] availability_zone = kwargs.pop('availability_zone','') vm_start_args['availability_zone']=availability_zone network_ids = [net_id.strip() for net_id in kwargs.pop('network_ids', '').split(',')] if network_ids: nics = [{'net-id': net_id, 'v4-fixed-ip': ''} for net_id in network_ids ] log.debug("Specifying networks for node %s: %s", node_name, ', '.join([nic['net-id'] for nic in nics])) else: nics = None vm_start_args['nics'] = nics if 'boot_disk_size' in kwargs: # check if the backing volume is already there volume_name = '{name}-{id}'.format(name=node_name, id=image_id) if volume_name in [v.name for v in self._get_volumes()]: raise ImageError( "Volume `{0}` already exists in project `{1}` of cloud {2}" .format(volume_name, self._os_tenant_name, self._os_auth_url)) log.info('Creating volume `%s` to use as VM disk ...', volume_name) try: bds = int(kwargs['boot_disk_size']) if bds < 1: raise ValueError('non-positive int') except (ValueError, TypeError): raise ConfigurationError( "Invalid `boot_disk_size` specified:" " should be a positive integer, got {0} instead" .format(kwargs['boot_disk_size'])) volume = self.cinder_client.volumes.create( size=bds, name=volume_name, imageRef=image_id, volume_type=kwargs.pop('boot_disk_type')) # wait for volume to come up volume_available = False while not volume_available: for v in self._get_volumes(): if v.name == volume_name and v.status == 'available': volume_available = True break sleep(1) # FIXME: hard-coded waiting time # ok, use volume as VM disk vm_start_args['block_device_mapping'] = { # FIXME: is it possible that `vda` is not the boot disk? e.g. if # a non-paravirtualized kernel is being used? should we allow # to set the boot device as an image parameter? 'vda': ('{id}:::{delete_on_terminate}' .format(id=volume.id, delete_on_terminate=1)), } # due to some `nova_client.servers.create()` implementation weirdness, # the first three args need to be spelt out explicitly and cannot be # conflated into `**vm_start_args` vm = self.nova_client.servers.create(node_name, image_id, flavor, **vm_start_args) # allocate and attach a floating IP, if requested request_floating_ip = kwargs.get( 'request_floating_ip', self._request_floating_ip_default) if request_floating_ip: # wait for server to come up (otherwise floating IP can't be associated) log.info("Waiting for instance `%s` (%s) to come up ...", node_name, vm.id) max_wait = int(kwargs.get('max_wait', 300)) waited = 0 while waited < max_wait: if vm.status == 'ACTIVE': break if vm.status == 'ERROR': raise RuntimeError( "Failed to start VM {0}:" " OpenStack scheduling error." .format(vm.id)) vm = self.nova_client.servers.get(vm.id) # FIXME: Configurable poll interval sleep(3) waited += 3 else: raise RuntimeError( "VM {0} didn't come up in {1:d} seconds" .format(vm.id, max_wait)) # We need to list the floating IPs for this instance try: # python-novaclient <8.0.0 floating_ips = [ip for ip in self.nova_client.floating_ips.list() if ip.instance_id == vm.id] except AttributeError: floating_ips = ( self.neutron_client .list_floatingips(id=vm.id) .get('floating_ips', [])) # allocate new floating IP if none given if not floating_ips: if 'floating_network_id' in kwargs: floating_networks = [kwargs.pop('floating_network_id')] else: floating_networks = network_ids[:] ip_addr = self._allocate_address(vm, floating_networks) log.debug("VM `%s` was allocated floating IP: %r", vm.id, ip_addr) else: log.debug("VM `%s` already allocated floating IPs: %r", vm.id, floating_ips) self._instances[vm.id] = vm return vm.id
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entity/sync.py
_get_model_objs_to_sync
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python
def _get_model_objs_to_sync(model_ids_to_sync, model_objs_map, sync_all): """ Given the model IDs to sync, fetch all model objects to sync """ model_objs_to_sync = {} for ctype, model_ids_to_sync_for_ctype in model_ids_to_sync.items(): model_qset = entity_registry.entity_registry.get(ctype.model_class()).queryset if not sync_all: model_objs_to_sync[ctype] = model_qset.filter(id__in=model_ids_to_sync_for_ctype) else: model_objs_to_sync[ctype] = [ model_objs_map[ctype, model_id] for model_id in model_ids_to_sync_for_ctype ] return model_objs_to_sync
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def get_model_classes(self): """ Return all :class:`~fluent_contents.models.ContentItem` model classes which are exposed by plugins. """ self._import_plugins() return [plugin.model for plugin in self.plugins.values()]
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def get_model_classes(self): """ Return all :class:`~fluent_contents.models.ContentItem` model classes which are exposed by plugins. """ self._import_plugins() return [plugin.model for plugin in self.plugins.values()]
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gns3server/compute/vmware/vmware_vm.py
VMwareVM.adapter_type
def adapter_type(self, adapter_type): """ Sets the adapter type for this VMware VM instance. :param adapter_type: adapter type (string) """ self._adapter_type = adapter_type log.info("VMware VM '{name}' [{id}]: adapter type changed to {adapter_type}".format(name=self.name, id=self.id, adapter_type=adapter_type))
python
def adapter_type(self, adapter_type): """ Sets the adapter type for this VMware VM instance. :param adapter_type: adapter type (string) """ self._adapter_type = adapter_type log.info("VMware VM '{name}' [{id}]: adapter type changed to {adapter_type}".format(name=self.name, id=self.id, adapter_type=adapter_type))
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inginious/frontend/pages/course_admin/webdav.py
WebDavInfoPage.page
def page(self, course): """ Get all data and display the page """ if not self.webdav_host: raise web.notfound() url = self.webdav_host + "/" + course.get_id() username = self.user_manager.session_username() apikey = self.user_manager.session_api_key() return self.template_helper.get_renderer().course_admin.webdav(course, url, username, apikey)
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def page(self, course): """ Get all data and display the page """ if not self.webdav_host: raise web.notfound() url = self.webdav_host + "/" + course.get_id() username = self.user_manager.session_username() apikey = self.user_manager.session_api_key() return self.template_helper.get_renderer().course_admin.webdav(course, url, username, apikey)
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pandas/core/series.py
Series.update
def update(self, other): """ Modify Series in place using non-NA values from passed Series. Aligns on index. Parameters ---------- other : Series Examples -------- >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6])) >>> s 0 4 1 5 2 6 dtype: int64 >>> s = pd.Series(['a', 'b', 'c']) >>> s.update(pd.Series(['d', 'e'], index=[0, 2])) >>> s 0 d 1 b 2 e dtype: object >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6, 7, 8])) >>> s 0 4 1 5 2 6 dtype: int64 If ``other`` contains NaNs the corresponding values are not updated in the original Series. >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, np.nan, 6])) >>> s 0 4 1 2 2 6 dtype: int64 """ other = other.reindex_like(self) mask = notna(other) self._data = self._data.putmask(mask=mask, new=other, inplace=True) self._maybe_update_cacher()
python
def update(self, other): """ Modify Series in place using non-NA values from passed Series. Aligns on index. Parameters ---------- other : Series Examples -------- >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6])) >>> s 0 4 1 5 2 6 dtype: int64 >>> s = pd.Series(['a', 'b', 'c']) >>> s.update(pd.Series(['d', 'e'], index=[0, 2])) >>> s 0 d 1 b 2 e dtype: object >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6, 7, 8])) >>> s 0 4 1 5 2 6 dtype: int64 If ``other`` contains NaNs the corresponding values are not updated in the original Series. >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, np.nan, 6])) >>> s 0 4 1 2 2 6 dtype: int64 """ other = other.reindex_like(self) mask = notna(other) self._data = self._data.putmask(mask=mask, new=other, inplace=True) self._maybe_update_cacher()
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concise/legacy/concise.py
Concise.get_weights
def get_weights(self): """ Returns: dict: Model's trained weights. """ if self.is_trained() is False: # print("Model not fitted yet. Use object.fit() to fit the model.") return None var_res = self._var_res weights = self._var_res_to_weights(var_res) # save to the side weights["final_bias_fit"] = weights["final_bias"] weights["feature_weights_fit"] = weights["feature_weights"] return weights
python
def get_weights(self): """ Returns: dict: Model's trained weights. """ if self.is_trained() is False: # print("Model not fitted yet. Use object.fit() to fit the model.") return None var_res = self._var_res weights = self._var_res_to_weights(var_res) # save to the side weights["final_bias_fit"] = weights["final_bias"] weights["feature_weights_fit"] = weights["feature_weights"] return weights
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annayqho/TheCannon
TheCannon/find_continuum_pixels.py
_find_contpix
def _find_contpix(wl, fluxes, ivars, target_frac): """ Find continuum pix in spec, meeting a set target fraction Parameters ---------- wl: numpy ndarray rest-frame wavelength vector fluxes: numpy ndarray pixel intensities ivars: numpy ndarray inverse variances, parallel to fluxes target_frac: float the fraction of pixels in spectrum desired to be continuum Returns ------- contmask: boolean numpy ndarray True corresponds to continuum pixels """ print("Target frac: %s" %(target_frac)) bad1 = np.median(ivars, axis=0) == SMALL bad2 = np.var(ivars, axis=0) == 0 bad = np.logical_and(bad1, bad2) npixels = len(wl)-sum(bad) f_cut = 0.0001 stepsize = 0.0001 sig_cut = 0.0001 contmask = _find_contpix_given_cuts(f_cut, sig_cut, wl, fluxes, ivars) if npixels > 0: frac = sum(contmask)/float(npixels) else: frac = 0 while (frac < target_frac): f_cut += stepsize sig_cut += stepsize contmask = _find_contpix_given_cuts(f_cut, sig_cut, wl, fluxes, ivars) if npixels > 0: frac = sum(contmask)/float(npixels) else: frac = 0 if frac > 0.10*npixels: print("Warning: Over 10% of pixels identified as continuum.") print("%s out of %s pixels identified as continuum" %(sum(contmask), npixels)) print("Cuts: f_cut %s, sig_cut %s" %(f_cut, sig_cut)) return contmask
python
def _find_contpix(wl, fluxes, ivars, target_frac): """ Find continuum pix in spec, meeting a set target fraction Parameters ---------- wl: numpy ndarray rest-frame wavelength vector fluxes: numpy ndarray pixel intensities ivars: numpy ndarray inverse variances, parallel to fluxes target_frac: float the fraction of pixels in spectrum desired to be continuum Returns ------- contmask: boolean numpy ndarray True corresponds to continuum pixels """ print("Target frac: %s" %(target_frac)) bad1 = np.median(ivars, axis=0) == SMALL bad2 = np.var(ivars, axis=0) == 0 bad = np.logical_and(bad1, bad2) npixels = len(wl)-sum(bad) f_cut = 0.0001 stepsize = 0.0001 sig_cut = 0.0001 contmask = _find_contpix_given_cuts(f_cut, sig_cut, wl, fluxes, ivars) if npixels > 0: frac = sum(contmask)/float(npixels) else: frac = 0 while (frac < target_frac): f_cut += stepsize sig_cut += stepsize contmask = _find_contpix_given_cuts(f_cut, sig_cut, wl, fluxes, ivars) if npixels > 0: frac = sum(contmask)/float(npixels) else: frac = 0 if frac > 0.10*npixels: print("Warning: Over 10% of pixels identified as continuum.") print("%s out of %s pixels identified as continuum" %(sum(contmask), npixels)) print("Cuts: f_cut %s, sig_cut %s" %(f_cut, sig_cut)) return contmask
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https://github.com/annayqho/TheCannon/blob/8010a0a5dc9a3f9bb91efa79d7756f79b3c7ba9a/TheCannon/find_continuum_pixels.py#L37-L85
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etcher-be/emiz
emiz/avwx/core.py
get_taf_remarks
def get_taf_remarks(txt: str) -> (str, str): # type: ignore """ Returns report and remarks separated if found """ remarks_start = find_first_in_list(txt, TAF_RMK) if remarks_start == -1: return txt, '' remarks = txt[remarks_start:] txt = txt[:remarks_start].strip() return txt, remarks
python
def get_taf_remarks(txt: str) -> (str, str): # type: ignore """ Returns report and remarks separated if found """ remarks_start = find_first_in_list(txt, TAF_RMK) if remarks_start == -1: return txt, '' remarks = txt[remarks_start:] txt = txt[:remarks_start].strip() return txt, remarks
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https://github.com/etcher-be/emiz/blob/1c3e32711921d7e600e85558ffe5d337956372de/emiz/avwx/core.py#L165-L174