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rikdz/GraphWriter | f228420aa48697dfb7a1ced3a62f955031664ed3 | models/beam.py | python | Beam.dup_obj | (self,obj) | return new_obj | [] | def dup_obj(self,obj):
new_obj = beam_obj(None,None,None,None,None)
new_obj.words = [x for x in obj.words]
new_obj.score = obj.score
new_obj.prevent = obj.prevent
new_obj.firstwords = [x for x in obj.firstwords]
new_obj.isstart = obj.isstart
return new_obj | [
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... | https://github.com/rikdz/GraphWriter/blob/f228420aa48697dfb7a1ced3a62f955031664ed3/models/beam.py#L38-L45 | |||
tensorflow/tfx | b4a6b83269815ed12ba9df9e9154c7376fef2ea0 | tfx/examples/cifar10/cifar10_utils_native_keras.py | python | run_fn | (fn_args: FnArgs) | Train the model based on given args.
Args:
fn_args: Holds args used to train the model as name/value pairs.
Raises:
ValueError: if invalid inputs. | Train the model based on given args. | [
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] | def run_fn(fn_args: FnArgs):
"""Train the model based on given args.
Args:
fn_args: Holds args used to train the model as name/value pairs.
Raises:
ValueError: if invalid inputs.
"""
tf_transform_output = tft.TFTransformOutput(fn_args.transform_output)
train_dataset = _input_fn(
fn_args.train_files,
fn_args.data_accessor,
tf_transform_output,
is_train=True,
batch_size=_TRAIN_BATCH_SIZE)
eval_dataset = _input_fn(
fn_args.eval_files,
fn_args.data_accessor,
tf_transform_output,
is_train=False,
batch_size=_EVAL_BATCH_SIZE)
model, base_model = _build_keras_model()
absl.logging.info('Tensorboard logging to {}'.format(fn_args.model_run_dir))
# Write logs to path
tensorboard_callback = tf.keras.callbacks.TensorBoard(
log_dir=fn_args.model_run_dir, update_freq='batch')
# Our training regime has two phases: we first freeze the backbone and train
# the newly added classifier only, then unfreeze part of the backbone and
# fine-tune with classifier jointly.
steps_per_epoch = int(_TRAIN_DATA_SIZE / _TRAIN_BATCH_SIZE)
total_epochs = int(fn_args.train_steps / steps_per_epoch)
if _CLASSIFIER_EPOCHS > total_epochs:
raise ValueError('Classifier epochs is greater than the total epochs')
absl.logging.info('Start training the top classifier')
model.fit(
train_dataset,
epochs=_CLASSIFIER_EPOCHS,
steps_per_epoch=steps_per_epoch,
validation_data=eval_dataset,
validation_steps=fn_args.eval_steps,
callbacks=[tensorboard_callback])
absl.logging.info('Start fine-tuning the model')
# Unfreeze the top MobileNet layers and do joint fine-tuning
_freeze_model_by_percentage(base_model, 0.9)
# We need to recompile the model because layer properties have changed
model.compile(
loss='sparse_categorical_crossentropy',
optimizer=tf.keras.optimizers.RMSprop(lr=_FINETUNE_LEARNING_RATE),
metrics=['sparse_categorical_accuracy'])
model.summary(print_fn=absl.logging.info)
model.fit(
train_dataset,
initial_epoch=_CLASSIFIER_EPOCHS,
epochs=total_epochs,
steps_per_epoch=steps_per_epoch,
validation_data=eval_dataset,
validation_steps=fn_args.eval_steps,
callbacks=[tensorboard_callback])
# Prepare the TFLite model used for serving in MLKit
signatures = {
'serving_default':
_get_serve_image_fn(model).get_concrete_function(
tf.TensorSpec(
shape=[None, 224, 224, 3],
dtype=tf.float32,
name=_transformed_name(_IMAGE_KEY)))
}
temp_saving_model_dir = os.path.join(fn_args.serving_model_dir, 'temp')
model.save(temp_saving_model_dir, save_format='tf', signatures=signatures)
tfrw = rewriter_factory.create_rewriter(
rewriter_factory.TFLITE_REWRITER,
name='tflite_rewriter')
converters.rewrite_saved_model(temp_saving_model_dir,
fn_args.serving_model_dir, tfrw,
rewriter.ModelType.TFLITE_MODEL)
# Add necessary TFLite metadata to the model in order to use it within MLKit
# TODO(dzats@): Handle label map file path more properly, currently
# hard-coded.
tflite_model_path = os.path.join(fn_args.serving_model_dir,
_TFLITE_MODEL_NAME)
# TODO(dzats@): Extend the TFLite rewriter to be able to add TFLite metadata
#@ to the model.
_write_metadata(
model_path=tflite_model_path,
label_map_path=fn_args.custom_config['labels_path'],
mean=[127.5],
std=[127.5])
fileio.rmtree(temp_saving_model_dir) | [
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fedora-infra/bodhi | 2b1df12d85eb2e575d8e481a3936c4f92d1fe29a | bodhi/server/migrations/versions/5c86a3f9dc03_drop_support_for_cve_tracking.py | python | downgrade | () | Recreate the cves table and related association tables. | Recreate the cves table and related association tables. | [
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] | def downgrade():
"""Recreate the cves table and related association tables."""
op.create_table(
'cves',
sa.Column('id', sa.INTEGER(), server_default=sa.text("nextval('cves_id_seq'::regclass)"),
autoincrement=True, nullable=False),
sa.Column('cve_id', sa.VARCHAR(length=13), autoincrement=False, nullable=False),
sa.PrimaryKeyConstraint('id', name='cves_pkey'),
sa.UniqueConstraint('cve_id', name='cves_cve_id_key'),
postgresql_ignore_search_path=False)
op.create_table(
'bug_cve_table',
sa.Column('bug_id', sa.INTEGER(), autoincrement=False, nullable=True),
sa.Column('cve_id', sa.INTEGER(), autoincrement=False, nullable=True),
sa.ForeignKeyConstraint(['bug_id'], ['bugs.id'], name='bug_cve_table_bug_id_fkey'),
sa.ForeignKeyConstraint(['cve_id'], ['cves.id'], name='bug_cve_table_cve_id_fkey'))
op.create_table(
'update_cve_table',
sa.Column('update_id', sa.INTEGER(), autoincrement=False, nullable=True),
sa.Column('cve_id', sa.INTEGER(), autoincrement=False, nullable=True),
sa.ForeignKeyConstraint(['cve_id'], ['cves.id'], name='update_cve_table_cve_id_fkey'),
sa.ForeignKeyConstraint(['update_id'], ['updates.id'],
name='update_cve_table_update_id_fkey')) | [
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lovelylain/pyctp | fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d | example/pyctp2/trader/position.py | python | Position.volume_accomplished2 | (self) | return num_opened - num_closed | [] | def volume_accomplished2(self):
num_opened = self._get_accomplished2(self._open_orders)
num_closed = self._get_accomplished2(self._close_orders)
return num_opened - num_closed | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_vendored_deps/library/oc_adm_router.py | python | DeploymentConfig.update_env_var | (self, key, value) | return True | place an env in the env var list | place an env in the env var list | [
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] | def update_env_var(self, key, value):
'''place an env in the env var list'''
env_vars_array = self.get_env_vars()
idx = None
for env_idx, env_var in enumerate(env_vars_array):
if env_var['name'] == key:
idx = env_idx
break
if idx:
env_vars_array[idx]['value'] = value
else:
self.add_env_value(key, value)
return True | [
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python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/_pydecimal.py | python | Context.copy | (self) | return nc | Returns a deep copy from self. | Returns a deep copy from self. | [
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] | def copy(self):
"""Returns a deep copy from self."""
nc = Context(self.prec, self.rounding, self.Emin, self.Emax,
self.capitals, self.clamp,
self.flags.copy(), self.traps.copy(),
self._ignored_flags)
return nc | [
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tendenci/tendenci | 0f2c348cc0e7d41bc56f50b00ce05544b083bf1d | tendenci/apps/make_payments/utils.py | python | make_payment_inv_add | (user, make_payment, **kwargs) | return inv | [] | def make_payment_inv_add(user, make_payment, **kwargs):
inv = Invoice()
# field to be populated to invoice
inv.title = _("Make Payment Invoice")
inv.bill_to = make_payment.first_name + ' ' + make_payment.last_name
inv.bill_to_first_name = make_payment.first_name
inv.bill_to_last_name = make_payment.last_name
inv.bill_to_company = make_payment.company
inv.bill_to_address = '%s %s' % (make_payment.address,
make_payment.address2)
inv.bill_to_city = make_payment.city
inv.bill_to_state = make_payment.state
inv.bill_to_zip_code = make_payment.zip_code
inv.bill_to_country = make_payment.country
inv.bill_to_phone = make_payment.phone
inv.bill_to_email = make_payment.email
inv.ship_to = make_payment.first_name + ' ' + make_payment.last_name
inv.ship_to_first_name = make_payment.first_name
inv.ship_to_last_name = make_payment.last_name
inv.ship_to_company = make_payment.company
inv.ship_to_address = '%s %s' % (make_payment.address,
make_payment.address2)
inv.ship_to_city = make_payment.city or ''
inv.ship_to_state = make_payment.state or ''
inv.ship_to_zip_code = make_payment.zip_code or ''
inv.ship_to_country = make_payment.country or ''
inv.ship_to_phone = make_payment.phone or ''
inv.ship_to_email = make_payment.email or ''
inv.terms = "Due on Receipt"
inv.due_date = datetime.now()
inv.ship_date = datetime.now()
inv.message = 'Thank You.'
inv.status = True
inv.estimate = True
inv.status_detail = 'estimate'
inv.object_type = ContentType.objects.get(app_label=make_payment._meta.app_label, model=make_payment._meta.model_name)
inv.object_id = make_payment.id
inv.subtotal = make_payment.payment_amount
inv.total = make_payment.payment_amount
inv.balance = make_payment.payment_amount
if user and not user.is_anonymous:
inv.set_creator(user)
inv.set_owner(user)
inv.save(user)
# tender the invoice
inv.tender(user)
make_payment.invoice_id = inv.id
return inv | [
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SheffieldML/GPy | bb1bc5088671f9316bc92a46d356734e34c2d5c0 | GPy/inference/latent_function_inference/var_dtc_parallel.py | python | VarDTC_minibatch.inference_minibatch | (self, kern, X, Z, likelihood, Y) | return isEnd, (n_start,n_end), grad_dict | The second phase of inference: Computing the derivatives over a minibatch of Y
Compute: dL_dpsi0, dL_dpsi1, dL_dpsi2, dL_dthetaL
return a flag showing whether it reached the end of Y (isEnd) | The second phase of inference: Computing the derivatives over a minibatch of Y
Compute: dL_dpsi0, dL_dpsi1, dL_dpsi2, dL_dthetaL
return a flag showing whether it reached the end of Y (isEnd) | [
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"""
The second phase of inference: Computing the derivatives over a minibatch of Y
Compute: dL_dpsi0, dL_dpsi1, dL_dpsi2, dL_dthetaL
return a flag showing whether it reached the end of Y (isEnd)
"""
num_data, output_dim = Y.shape
if isinstance(X, VariationalPosterior):
uncertain_inputs = True
else:
uncertain_inputs = False
#see whether we've got a different noise variance for each datum
beta = 1./np.fmax(likelihood.variance, 1e-6)
het_noise = beta.size > 1
# VVT_factor is a matrix such that tdot(VVT_factor) = VVT...this is for efficiency!
#self.YYTfactor = beta*self.get_YYTfactor(Y)
if self.Y_speedup and not het_noise:
YYT_factor = self.get_YYTfactor(Y)
else:
YYT_factor = Y
n_start = self.batch_pos
batchsize = num_data if self.batchsize is None else self.batchsize
n_end = min(batchsize+n_start, num_data)
if n_end==num_data:
isEnd = True
self.batch_pos = 0
else:
isEnd = False
self.batch_pos = n_end
if batchsize==num_data:
Y_slice = YYT_factor
X_slice =X
else:
Y_slice = YYT_factor[n_start:n_end]
X_slice = X[n_start:n_end]
if not uncertain_inputs:
psi0 = kern.Kdiag(X_slice)
psi1 = kern.K(X_slice, Z)
psi2 = None
betapsi1 = np.einsum('n,nm->nm',beta,psi1)
elif het_noise:
psi0 = kern.psi0(Z, X_slice)
psi1 = kern.psi1(Z, X_slice)
psi2 = kern.psi2(Z, X_slice)
betapsi1 = np.einsum('n,nm->nm',beta,psi1)
if het_noise:
beta = beta[n_start] # assuming batchsize==1
betaY = beta*Y_slice
#======================================================================
# Load Intermediate Results
#======================================================================
dL_dpsi2R = self.midRes['dL_dpsi2R']
v = self.midRes['v']
#======================================================================
# Compute dL_dpsi
#======================================================================
dL_dpsi0 = -output_dim * (beta * np.ones((n_end-n_start,)))/2.
dL_dpsi1 = np.dot(betaY,v.T)
if uncertain_inputs:
dL_dpsi2 = beta* dL_dpsi2R
else:
dL_dpsi1 += np.dot(betapsi1,dL_dpsi2R)*2.
dL_dpsi2 = None
#======================================================================
# Compute dL_dthetaL
#======================================================================
if het_noise:
if uncertain_inputs:
psiR = np.einsum('mo,mo->',dL_dpsi2R,psi2)
else:
psiR = np.einsum('nm,no,mo->',psi1,psi1,dL_dpsi2R)
dL_dthetaL = ((np.square(betaY)).sum(axis=-1) + np.square(beta)*(output_dim*psi0)-output_dim*beta)/2. - np.square(beta)*psiR- (betaY*np.dot(betapsi1,v)).sum(axis=-1)
else:
if isEnd:
dL_dthetaL = self.midRes['dL_dthetaL']
else:
dL_dthetaL = 0.
if uncertain_inputs:
grad_dict = {'dL_dpsi0':dL_dpsi0,
'dL_dpsi1':dL_dpsi1,
'dL_dpsi2':dL_dpsi2,
'dL_dthetaL':dL_dthetaL}
else:
grad_dict = {'dL_dKdiag':dL_dpsi0,
'dL_dKnm':dL_dpsi1,
'dL_dthetaL':dL_dthetaL}
return isEnd, (n_start,n_end), grad_dict | [
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awslabs/autogluon | 7309118f2ab1c9519f25acf61a283a95af95842b | tabular/src/autogluon/tabular/models/fastainn/tabular_nn_fastai.py | python | NNFastAiTabularModel.__get_objective_func_to_monitor | (self, objective_func_name) | return objective_func_name_to_monitor | [] | def __get_objective_func_to_monitor(self, objective_func_name):
monitor_obj_func = {
**{k: m.name if hasattr(m, 'name') else m.__name__ for k, m in self.__get_metrics_map().items() if m is not None},
'log_loss': 'valid_loss'
}
objective_func_name_to_monitor = objective_func_name
if objective_func_name in monitor_obj_func:
objective_func_name_to_monitor = monitor_obj_func[objective_func_name]
return objective_func_name_to_monitor | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/tkinter/__init__.py | python | Listbox.itemconfigure | (self, index, cnf=None, **kw) | return self._configure(('itemconfigure', index), cnf, kw) | Configure resources of an ITEM.
The values for resources are specified as keyword arguments.
To get an overview about the allowed keyword arguments
call the method without arguments.
Valid resource names: background, bg, foreground, fg,
selectbackground, selectforeground. | Configure resources of an ITEM. | [
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"""Configure resources of an ITEM.
The values for resources are specified as keyword arguments.
To get an overview about the allowed keyword arguments
call the method without arguments.
Valid resource names: background, bg, foreground, fg,
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return self._configure(('itemconfigure', index), cnf, kw) | [
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] | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/tkinter/__init__.py#L2848-L2856 | |
mapillary/seamseg | 77195ff7829af6e3076caefe49c4c69c817e30d6 | seamseg/utils/misc.py | python | norm_act_from_config | (body_config) | return norm_act_static, norm_act_dynamic | Make normalization + activation function from configuration
Available normalization modes are:
- `bn`: Standard In-Place Batch Normalization
- `syncbn`: Synchronized In-Place Batch Normalization
- `syncbn+bn`: Synchronized In-Place Batch Normalization in the "static" part of the network, Standard In-Place
Batch Normalization in the "dynamic" parts
- `gn`: Group Normalization
- `syncbn+gn`: Synchronized In-Place Batch Normalization in the "static" part of the network, Group Normalization
in the "dynamic" parts
- `off`: No normalization (preserve scale and bias parameters)
The "static" part of the network includes the backbone, FPN and semantic segmentation components, while the
"dynamic" part of the network includes the RPN, detection and instance segmentation components. Note that this
distinction is due to historical reasons and for back-compatibility with the CVPR2019 pre-trained models.
Parameters
----------
body_config
Configuration object containing the following fields: `normalization_mode`, `activation`, `activation_slope`
and `gn_groups`
Returns
-------
norm_act_static : callable
Function that returns norm_act modules for the static parts of the network
norm_act_dynamic : callable
Function that returns norm_act modules for the dynamic parts of the network | Make normalization + activation function from configuration | [
"Make",
"normalization",
"+",
"activation",
"function",
"from",
"configuration"
] | def norm_act_from_config(body_config):
"""Make normalization + activation function from configuration
Available normalization modes are:
- `bn`: Standard In-Place Batch Normalization
- `syncbn`: Synchronized In-Place Batch Normalization
- `syncbn+bn`: Synchronized In-Place Batch Normalization in the "static" part of the network, Standard In-Place
Batch Normalization in the "dynamic" parts
- `gn`: Group Normalization
- `syncbn+gn`: Synchronized In-Place Batch Normalization in the "static" part of the network, Group Normalization
in the "dynamic" parts
- `off`: No normalization (preserve scale and bias parameters)
The "static" part of the network includes the backbone, FPN and semantic segmentation components, while the
"dynamic" part of the network includes the RPN, detection and instance segmentation components. Note that this
distinction is due to historical reasons and for back-compatibility with the CVPR2019 pre-trained models.
Parameters
----------
body_config
Configuration object containing the following fields: `normalization_mode`, `activation`, `activation_slope`
and `gn_groups`
Returns
-------
norm_act_static : callable
Function that returns norm_act modules for the static parts of the network
norm_act_dynamic : callable
Function that returns norm_act modules for the dynamic parts of the network
"""
mode = body_config["normalization_mode"]
activation = body_config["activation"]
slope = body_config.getfloat("activation_slope")
groups = body_config.getint("gn_groups")
if mode == "bn":
norm_act_static = norm_act_dynamic = partial(InPlaceABN, activation=activation, activation_param=slope)
elif mode == "syncbn":
norm_act_static = norm_act_dynamic = partial(InPlaceABNSync, activation=activation, activation_param=slope)
elif mode == "syncbn+bn":
norm_act_static = partial(InPlaceABNSync, activation=activation, activation_param=slope)
norm_act_dynamic = partial(InPlaceABN, activation=activation, activation_param=slope)
elif mode == "gn":
norm_act_static = norm_act_dynamic = partial(
ActivatedGroupNorm, num_groups=groups, activation=activation, activation_param=slope)
elif mode == "syncbn+gn":
norm_act_static = partial(InPlaceABNSync, activation=activation, activation_param=slope)
norm_act_dynamic = partial(ActivatedGroupNorm, num_groups=groups, activation=activation, activation_param=slope)
elif mode == "off":
norm_act_static = norm_act_dynamic = partial(ActivatedAffine, activation=activation, activation_param=slope)
else:
raise ValueError("Unrecognized normalization_mode {}, valid options: 'bn', 'syncbn', 'syncbn+bn', 'gn', "
"'syncbn+gn', 'off'".format(mode))
return norm_act_static, norm_act_dynamic | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/xml/sax/saxutils.py | python | XMLFilterBase.warning | (self, exception) | [] | def warning(self, exception):
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linuxscout/mishkal | 4f4ae0ebc2d6acbeb3de3f0303151ec7b54d2f76 | interfaces/web/lib/paste/wsgiwrappers.py | python | WSGIRequest.urlvars | (self) | Return any variables matched in the URL (e.g.,
``wsgiorg.routing_args``). | Return any variables matched in the URL (e.g.,
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] | def urlvars(self):
"""
Return any variables matched in the URL (e.g.,
``wsgiorg.routing_args``).
"""
if 'paste.urlvars' in self.environ:
return self.environ['paste.urlvars']
elif 'wsgiorg.routing_args' in self.environ:
return self.environ['wsgiorg.routing_args'][1]
else:
return {} | [
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emesene/emesene | 4548a4098310e21b16437bb36223a7f632a4f7bc | emesene/e3/xmpp/SleekXMPP/sleekxmpp/stanza/htmlim.py | python | HTMLIM.del_body | (self) | Remove the HTML body contents. | Remove the HTML body contents. | [
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] | def del_body(self):
"""Remove the HTML body contents."""
if self.parent is not None:
self.parent().xml.remove(self.xml) | [
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Azure/azure-linux-extensions | a42ef718c746abab2b3c6a21da87b29e76364558 | AzureMonitorAgent/agent.py | python | set_os_arch | () | Checks if the current system architecture is present in the SupportedArch set and replaces
the package name accordingly | Checks if the current system architecture is present in the SupportedArch set and replaces
the package name accordingly | [
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] | def set_os_arch():
"""
Checks if the current system architecture is present in the SupportedArch set and replaces
the package name accordingly
"""
global BundleFileName, SupportedArch
current_arch = platform.machine()
if current_arch in SupportedArch:
BundleFileName = BundleFileName.replace('x86_64', current_arch) | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | apps/rdbms/src/rdbms/views.py | python | execute_query | (request, design_id=None, query_history_id=None) | return render('execute.mako', request, {
'action': action,
'doc_id': json.dumps(design.id and design.doc.get().id or -1),
'design': design,
'autocomplete_base_url': reverse('rdbms:api_autocomplete_databases', kwargs={}),
'can_edit_name': design.id and not design.is_auto,
}) | View function for executing an arbitrary synchronously query. | View function for executing an arbitrary synchronously query. | [
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"."
] | def execute_query(request, design_id=None, query_history_id=None):
"""
View function for executing an arbitrary synchronously query.
"""
action = request.path
app_name = get_app_name(request)
query_type = beeswax_models.SavedQuery.TYPES_MAPPING[app_name]
design = safe_get_design(request, query_type, design_id)
return render('execute.mako', request, {
'action': action,
'doc_id': json.dumps(design.id and design.doc.get().id or -1),
'design': design,
'autocomplete_base_url': reverse('rdbms:api_autocomplete_databases', kwargs={}),
'can_edit_name': design.id and not design.is_auto,
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hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/modules/scanner/service_scan.py | python | service_scan.ftp_info | (self, ip) | [] | def ftp_info(self, ip):
con = FTP(ip)
banner = con.getwelcome()
# dump banner
for line in banner.split('\n'):
print '\t |-' + line
print '\t [+] Checking anonymous access...'
try:
con.login()
except:
print '\t [-] No anonymous access.'
con.close()
return
# get the logged in dir
data = con.pwd()
if data is not None:
print '\t [+] Anonymous access available.'
print '\t [+] Directory: ', data
con.close() | [
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hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/lib/libmproxy/contrib/html2text.py | python | HTML2Text.replaceEntities | (self, s) | [] | def replaceEntities(self, s):
s = s.group(1)
if s[0] == "#":
return self.charref(s[1:])
else: return self.entityref(s) | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/mimetools.py | python | Message.parsetype | (self) | [] | def parsetype(self):
str = self.typeheader
if str is None:
str = 'text/plain'
if ';' in str:
i = str.index(';')
self.plisttext = str[i:]
str = str[:i]
else:
self.plisttext = ''
fields = str.split('/')
for i in range(len(fields)):
fields[i] = fields[i].strip().lower()
self.type = '/'.join(fields)
self.maintype = fields[0]
self.subtype = '/'.join(fields[1:]) | [
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/beets/ui/__init__.py | python | CommonOptionsParser.add_album_option | (self, flags=('-a', '--album')) | Add a -a/--album option to match albums instead of tracks.
If used then the format option can auto-detect whether we're setting
the format for items or albums.
Sets the album property on the options extracted from the CLI. | Add a -a/--album option to match albums instead of tracks. | [
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] | def add_album_option(self, flags=('-a', '--album')):
"""Add a -a/--album option to match albums instead of tracks.
If used then the format option can auto-detect whether we're setting
the format for items or albums.
Sets the album property on the options extracted from the CLI.
"""
album = optparse.Option(*flags, action='store_true',
help=u'match albums instead of tracks')
self.add_option(album)
self._album_flags = set(flags) | [
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awslabs/deeplearning-benchmark | 3e9a906422b402869537f91056ae771b66487a8e | image_classification/predict_image.py | python | InferenceTesting.__getImage | (self) | return img | [] | def __getImage(self):
try:
fname = mx.test_utils.download(self.url)
except Exception as e:
print("Error in downloading the image {}".format(e))
img = cv2.cvtColor(cv2.imread(fname), cv2.COLOR_BGR2RGB)
if img is None:
return None
# convert into format (batch, RGB, width, height)
img = cv2.resize(img, (224, 224))
img = np.swapaxes(img, 0, 2)
img = np.swapaxes(img, 1, 2)
img = img[np.newaxis, :]
return img | [
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malicialab/avclass | 707c06e0a5e362b6a2f08e4cb1c6c81787c08a8d | avclass2/avclass2_update_module.py | python | Update.is_blacklisted_rel | (self, rel) | return (rel.t1 in self.blist) or (rel.t2 in self.blist) | Return true if relationship is blacklisted | Return true if relationship is blacklisted | [
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] | def is_blacklisted_rel(self, rel):
''' Return true if relationship is blacklisted '''
return (rel.t1 in self.blist) or (rel.t2 in self.blist) | [
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garywiz/chaperone | 9ff2c3a5b9c6820f8750320a564ea214042df06f | chaperone/cutil/notify.py | python | NotifyListener.is_client | (self) | return False | [] | def is_client(self):
return False | [
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] | https://github.com/garywiz/chaperone/blob/9ff2c3a5b9c6820f8750320a564ea214042df06f/chaperone/cutil/notify.py#L29-L30 | |||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/pip/_vendor/pkg_resources/__init__.py | python | Environment.__getitem__ | (self, project_name) | return self._distmap.get(distribution_key, []) | Return a newest-to-oldest list of distributions for `project_name`
Uses case-insensitive `project_name` comparison, assuming all the
project's distributions use their project's name converted to all
lowercase as their key. | Return a newest-to-oldest list of distributions for `project_name` | [
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] | def __getitem__(self, project_name):
"""Return a newest-to-oldest list of distributions for `project_name`
Uses case-insensitive `project_name` comparison, assuming all the
project's distributions use their project's name converted to all
lowercase as their key.
"""
distribution_key = project_name.lower()
return self._distmap.get(distribution_key, []) | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/nova/nova/virt/xenapi/agent.py | python | _call_agent | (session, instance, vm_ref, method, addl_args=None,
timeout=None) | Abstracts out the interaction with the agent xenapi plugin. | Abstracts out the interaction with the agent xenapi plugin. | [
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"."
] | def _call_agent(session, instance, vm_ref, method, addl_args=None,
timeout=None):
"""Abstracts out the interaction with the agent xenapi plugin."""
if addl_args is None:
addl_args = {}
if timeout is None:
timeout = CONF.agent_timeout
vm_rec = session.call_xenapi("VM.get_record", vm_ref)
args = {
'id': str(uuid.uuid4()),
'dom_id': vm_rec['domid'],
'timeout': str(timeout),
}
args.update(addl_args)
try:
ret = session.call_plugin('agent', method, args)
except session.XenAPI.Failure, e:
err_msg = e.details[-1].splitlines()[-1]
if 'TIMEOUT:' in err_msg:
LOG.error(_('TIMEOUT: The call to %(method)s timed out. '
'args=%(args)r'), locals(), instance=instance)
return {'returncode': 'timeout', 'message': err_msg}
elif 'NOT IMPLEMENTED:' in err_msg:
LOG.error(_('NOT IMPLEMENTED: The call to %(method)s is not'
' supported by the agent. args=%(args)r'),
locals(), instance=instance)
return {'returncode': 'notimplemented', 'message': err_msg}
else:
LOG.error(_('The call to %(method)s returned an error: %(e)s. '
'args=%(args)r'), locals(), instance=instance)
return {'returncode': 'error', 'message': err_msg}
return None
if isinstance(ret, dict):
return ret
try:
return jsonutils.loads(ret)
except TypeError:
LOG.error(_('The agent call to %(method)s returned an invalid'
' response: %(ret)r. path=%(path)s; args=%(args)r'),
locals(), instance=instance)
return {'returncode': 'error',
'message': 'unable to deserialize response'} | [
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/plecost/xgoogle/search.py | python | GoogleSearch._get_page | (self) | return self._page | [] | def _get_page(self):
return self._page | [
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/setuptools/py33compat.py | python | Bytecode_compat.__iter__ | (self) | Yield '(op,arg)' pair for each operation in code object 'code | Yield '(op,arg)' pair for each operation in code object 'code | [
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bytes = array.array('b', self.code.co_code)
eof = len(self.code.co_code)
ptr = 0
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ptr += 3
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long_type = six.integer_types[-1]
extended_arg = arg * long_type(65536)
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wger-project/wger | 3a17a2cf133d242d1f8c357faa53cf675a7b3223 | wger/core/models/language.py | python | Language.get_absolute_url | (self) | return reverse('core:language:view', kwargs={'pk': self.id}) | Returns the canonical URL to view a language | Returns the canonical URL to view a language | [
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jazzband/tablib | 94ffe67e50eb5bfd99d73a4f010e463478a98928 | src/tablib/core.py | python | Dataset.rpop | (self) | return cache | Removes and returns the last row of the :class:`Dataset`. | Removes and returns the last row of the :class:`Dataset`. | [
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kozistr/Awesome-GANs | b4b9a3b8c3fd1d32c864dc5655d80c0650aebee1 | awesome_gans/ebgan/ebgan_model.py | python | EBGAN.encoder | (self, x, reuse=None) | (64)4c2s - (128)4c2s - (256)4c2s
:param x: images
:param reuse: re-usable
:return: logits | (64)4c2s - (128)4c2s - (256)4c2s
:param x: images
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"""
(64)4c2s - (128)4c2s - (256)4c2s
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:param reuse: re-usable
:return: logits
"""
with tf.variable_scope('encoder', reuse=reuse):
x = t.conv2d(x, self.df_dim * 1, 4, 2, name='enc-conv2d-1')
x = tf.nn.leaky_relu(x)
x = t.conv2d(x, self.df_dim * 2, 4, 2, name='enc-conv2d-2')
x = t.batch_norm(x, name='enc-bn-1')
x = tf.nn.leaky_relu(x)
x = t.conv2d(x, self.df_dim * 4, 4, 2, name='enc-conv2d-3')
x = t.batch_norm(x, name='enc-bn-2')
x = tf.nn.leaky_relu(x)
return x | [
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mozillazg/pypy | 2ff5cd960c075c991389f842c6d59e71cf0cb7d0 | rpython/rtyper/lltypesystem/lltype.py | python | _ptr._expose | (self, offset, val) | return val | XXX A nice docstring here | XXX A nice docstring here | [
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google/ml-fairness-gym | 5b1cd336b844059aa4e4426b54d1f0e6b8c4c7e9 | environments/lending.py | python | BaseLendingEnv.render | (self, mode='human') | Renders the history and current state using matplotlib.
Args:
mode: string indicating the rendering mode. The only supported mode is
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"""Renders the history and current state using matplotlib.
Args:
mode: string indicating the rendering mode. The only supported mode is
`human`.
"""
if mode == 'human':
if self.state.params.applicant_distribution.dim != 2:
raise NotImplementedError(
'Cannot render if applicant features are not exactly 2 dimensional. '
'Got %d dimensional applicant features.' %
self.state.params.applicant_distribution.dim)
plt.figure(figsize=(12, 4))
plt.subplot(1, 2, 1)
plt.xlim(-2, 2)
plt.ylim(-2, 2)
plt.title('Applicant Features')
plt.xticks([], [])
plt.yticks([], [])
for state, action in self.history:
if action == 1:
x, y = state.applicant_features
color = 'r' if state.will_default else 'b'
plt.plot([x], [y], _MARKERS[state.group_id] + color, markersize=12)
plt.xlabel('Feature 1')
plt.ylabel('Feature 2')
x, y = self.state.applicant_features
plt.plot([x], [y], _MARKERS[self.state.group_id] + 'k', markersize=15)
plt.subplot(1, 2, 2)
plt.title('Cash')
plt.plot([state.bank_cash for state, _ in self.history] +
[self.state.bank_cash])
plt.ylabel('# loans available')
plt.xlabel('Time')
plt.tight_layout()
else:
super(BaseLendingEnv, self).render(mode) | [
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guoruoqian/DetNet_pytorch | 735e2c51eea0ee4e91d2ec3f28e441ac4e076551 | lib/model/rpn/bbox_transform.py | python | bbox_overlaps_batch | (anchors, gt_boxes) | return overlaps | anchors: (N, 4) ndarray of float
gt_boxes: (b, K, 5) ndarray of float
overlaps: (N, K) ndarray of overlap between boxes and query_boxes | anchors: (N, 4) ndarray of float
gt_boxes: (b, K, 5) ndarray of float | [
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"""
anchors: (N, 4) ndarray of float
gt_boxes: (b, K, 5) ndarray of float
overlaps: (N, K) ndarray of overlap between boxes and query_boxes
"""
batch_size = gt_boxes.size(0)
if anchors.dim() == 2:
N = anchors.size(0)
K = gt_boxes.size(1)
anchors = anchors.view(1, N, 4).expand(batch_size, N, 4).contiguous()
gt_boxes = gt_boxes[:,:,:4].contiguous()
gt_boxes_x = (gt_boxes[:,:,2] - gt_boxes[:,:,0] + 1)
gt_boxes_y = (gt_boxes[:,:,3] - gt_boxes[:,:,1] + 1)
gt_boxes_area = (gt_boxes_x * gt_boxes_y).view(batch_size, 1, K)
anchors_boxes_x = (anchors[:,:,2] - anchors[:,:,0] + 1)
anchors_boxes_y = (anchors[:,:,3] - anchors[:,:,1] + 1)
anchors_area = (anchors_boxes_x * anchors_boxes_y).view(batch_size, N, 1)
gt_area_zero = (gt_boxes_x == 1) & (gt_boxes_y == 1)
anchors_area_zero = (anchors_boxes_x == 1) & (anchors_boxes_y == 1)
boxes = anchors.view(batch_size, N, 1, 4).expand(batch_size, N, K, 4)
query_boxes = gt_boxes.view(batch_size, 1, K, 4).expand(batch_size, N, K, 4)
iw = (torch.min(boxes[:,:,:,2], query_boxes[:,:,:,2]) -
torch.max(boxes[:,:,:,0], query_boxes[:,:,:,0]) + 1)
iw[iw < 0] = 0
ih = (torch.min(boxes[:,:,:,3], query_boxes[:,:,:,3]) -
torch.max(boxes[:,:,:,1], query_boxes[:,:,:,1]) + 1)
ih[ih < 0] = 0
ua = anchors_area + gt_boxes_area - (iw * ih)
overlaps = iw * ih / ua
# mask the overlap here.
overlaps.masked_fill_(gt_area_zero.view(batch_size, 1, K).expand(batch_size, N, K), 0)
overlaps.masked_fill_(anchors_area_zero.view(batch_size, N, 1).expand(batch_size, N, K), -1)
elif anchors.dim() == 3:
N = anchors.size(1)
K = gt_boxes.size(1)
if anchors.size(2) == 4:
anchors = anchors[:,:,:4].contiguous()
else:
anchors = anchors[:,:,1:5].contiguous()
gt_boxes = gt_boxes[:,:,:4].contiguous()
gt_boxes_x = (gt_boxes[:,:,2] - gt_boxes[:,:,0] + 1)
gt_boxes_y = (gt_boxes[:,:,3] - gt_boxes[:,:,1] + 1)
gt_boxes_area = (gt_boxes_x * gt_boxes_y).view(batch_size, 1, K)
anchors_boxes_x = (anchors[:,:,2] - anchors[:,:,0] + 1)
anchors_boxes_y = (anchors[:,:,3] - anchors[:,:,1] + 1)
anchors_area = (anchors_boxes_x * anchors_boxes_y).view(batch_size, N, 1)
gt_area_zero = (gt_boxes_x == 1) & (gt_boxes_y == 1)
anchors_area_zero = (anchors_boxes_x == 1) & (anchors_boxes_y == 1)
boxes = anchors.view(batch_size, N, 1, 4).expand(batch_size, N, K, 4)
query_boxes = gt_boxes.view(batch_size, 1, K, 4).expand(batch_size, N, K, 4)
iw = (torch.min(boxes[:,:,:,2], query_boxes[:,:,:,2]) -
torch.max(boxes[:,:,:,0], query_boxes[:,:,:,0]) + 1)
iw[iw < 0] = 0
ih = (torch.min(boxes[:,:,:,3], query_boxes[:,:,:,3]) -
torch.max(boxes[:,:,:,1], query_boxes[:,:,:,1]) + 1)
ih[ih < 0] = 0
ua = anchors_area + gt_boxes_area - (iw * ih)
overlaps = iw * ih / ua
# mask the overlap here.
overlaps.masked_fill_(gt_area_zero.view(batch_size, 1, K).expand(batch_size, N, K), 0)
overlaps.masked_fill_(anchors_area_zero.view(batch_size, N, 1).expand(batch_size, N, K), -1)
else:
raise ValueError('anchors input dimension is not correct.')
return overlaps | [
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openstack/trove | be86b79119d16ee77f596172f43b0c97cb2617bd | trove/guestagent/common/configuration.py | python | ConfigurationManager.get_value | (self, key, section=None, default=None) | return self._value_cache.get(key, default) | Return the current value at a given key or 'default'. | Return the current value at a given key or 'default'. | [
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lbryio/lbry-sdk | f78e3825ca0f130834d3876a824f9d380501ced8 | lbry/wallet/server/session.py | python | LBRYElectrumX.transaction_broadcast | (self, raw_tx) | Broadcast a raw transaction to the network.
raw_tx: the raw transaction as a hexadecimal string | Broadcast a raw transaction to the network. | [
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"""Broadcast a raw transaction to the network.
raw_tx: the raw transaction as a hexadecimal string"""
# This returns errors as JSON RPC errors, as is natural
try:
hex_hash = await self.session_mgr.broadcast_transaction(raw_tx)
self.txs_sent += 1
self.mempool.wakeup.set()
self.logger.info(f'sent tx: {hex_hash}')
return hex_hash
except DaemonError as e:
error, = e.args
message = error['message']
self.logger.info(f'error sending transaction: {message}')
raise RPCError(BAD_REQUEST, 'the transaction was rejected by '
f'network rules.\n\n{message}\n[{raw_tx}]') | [
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XinJCheng/CSPN | b3e487bdcdcd8a63333656e69b3268698e543181 | cspn_pytorch/data_transform.py | python | Rotation.__call__ | (self, img) | return img.rotate(self.degrees, self.resample, self.expand, self.center) | img (PIL Image): Image to be rotated.
Returns:
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PIL Image: Rotated image. | [
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"""
img (PIL Image): Image to be rotated.
Returns:
PIL Image: Rotated image.
"""
if not _is_pil_image(img):
raise TypeError('img should be PIL Image. Got {}'.format(type(img)))
return img.rotate(self.degrees, self.resample, self.expand, self.center) | [
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iMoonLab/MeshNet | 70f9115a121cef71f62d774088771337c3beaf4b | models/layers.py | python | FaceRotateConvolution.__init__ | (self) | [] | def __init__(self):
super(FaceRotateConvolution, self).__init__()
self.rotate_mlp = nn.Sequential(
nn.Conv1d(6, 32, 1),
nn.BatchNorm1d(32),
nn.ReLU(),
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self.fusion_mlp = nn.Sequential(
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nn.BatchNorm1d(64),
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/data/owtable.py | python | TableSliceProxy.setRowSlice | (self, rowslice) | [] | def setRowSlice(self, rowslice):
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raise ValueError("invalid stride")
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self.beginResetModel()
self.__rowslice = rowslice
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microsoft/bistring | e23443e495f762967b09670b27bb1ff46ff4fef1 | python/bistring/_builder.py | python | BistrBuilder.current | (self) | return self._original.modified | The current string before modifications. | The current string before modifications. | [
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"""
The current string before modifications.
"""
return self._original.modified | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/django/forms/models.py | python | ModelChoiceIterator.choice | (self, obj) | return (self.field.prepare_value(obj), self.field.label_from_instance(obj)) | [] | def choice(self, obj):
return (self.field.prepare_value(obj), self.field.label_from_instance(obj)) | [
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misterch0c/shadowbroker | e3a069bea47a2c1009697941ac214adc6f90aa8d | windows/Resources/Python/Core/Lib/logging/handlers.py | python | NTEventLogHandler.emit | (self, record) | Emit a record.
Determine the message ID, event category and event type. Then
log the message in the NT event log. | Emit a record.
Determine the message ID, event category and event type. Then
log the message in the NT event log. | [
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"""
Emit a record.
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"""
if self._welu:
try:
id = self.getMessageID(record)
cat = self.getEventCategory(record)
type = self.getEventType(record)
msg = self.format(record)
self._welu.ReportEvent(self.appname, id, cat, type, [msg])
except (KeyboardInterrupt, SystemExit):
raise
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self.handleError(record) | [
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Te-k/harpoon | 654381fff282aacc7e3c8264fd4cead40eedf48d | harpoon/lib/koodous.py | python | Koodous.analysis | (self, hash) | return self._query("/" + hash + "/analysis") | [] | def analysis(self, hash):
return self._query("/" + hash + "/analysis") | [
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/v6_0/feature_availability/feature_availability_client.py | python | FeatureAvailabilityClient.get_all_feature_flags | (self, user_email=None) | return self._deserialize('[FeatureFlag]', self._unwrap_collection(response)) | GetAllFeatureFlags.
[Preview API] Retrieve a listing of all feature flags and their current states for a user
:param str user_email: The email of the user to check
:rtype: [FeatureFlag] | GetAllFeatureFlags.
[Preview API] Retrieve a listing of all feature flags and their current states for a user
:param str user_email: The email of the user to check
:rtype: [FeatureFlag] | [
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"""GetAllFeatureFlags.
[Preview API] Retrieve a listing of all feature flags and their current states for a user
:param str user_email: The email of the user to check
:rtype: [FeatureFlag]
"""
query_parameters = {}
if user_email is not None:
query_parameters['userEmail'] = self._serialize.query('user_email', user_email, 'str')
response = self._send(http_method='GET',
location_id='3e2b80f8-9e6f-441e-8393-005610692d9c',
version='6.0-preview.1',
query_parameters=query_parameters)
return self._deserialize('[FeatureFlag]', self._unwrap_collection(response)) | [
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/devops_sdk/released/work_item_tracking/work_item_tracking_client.py | python | WorkItemTrackingClient.get_update | (self, id, update_number, project=None) | return self._deserialize('WorkItemUpdate', response) | GetUpdate.
Returns a single update for a work item
:param int id:
:param int update_number:
:param str project: Project ID or project name
:rtype: :class:`<WorkItemUpdate> <azure.devops.v5_1.work_item_tracking.models.WorkItemUpdate>` | GetUpdate.
Returns a single update for a work item
:param int id:
:param int update_number:
:param str project: Project ID or project name
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"""GetUpdate.
Returns a single update for a work item
:param int id:
:param int update_number:
:param str project: Project ID or project name
:rtype: :class:`<WorkItemUpdate> <azure.devops.v5_1.work_item_tracking.models.WorkItemUpdate>`
"""
route_values = {}
if project is not None:
route_values['project'] = self._serialize.url('project', project, 'str')
if id is not None:
route_values['id'] = self._serialize.url('id', id, 'int')
if update_number is not None:
route_values['updateNumber'] = self._serialize.url('update_number', update_number, 'int')
response = self._send(http_method='GET',
location_id='6570bf97-d02c-4a91-8d93-3abe9895b1a9',
version='5.1',
route_values=route_values)
return self._deserialize('WorkItemUpdate', response) | [
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chaoss/grimoirelab-perceval | ba19bfd5e40bffdd422ca8e68526326b47f97491 | perceval/backends/core/gitlab.py | python | GitLab.fetch_items | (self, category, **kwargs) | return items | Fetch the items (issues or merge_requests)
:param category: the category of items to fetch
:param kwargs: backend arguments
:returns: a generator of items | Fetch the items (issues or merge_requests) | [
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] | def fetch_items(self, category, **kwargs):
"""Fetch the items (issues or merge_requests)
:param category: the category of items to fetch
:param kwargs: backend arguments
:returns: a generator of items
"""
from_date = kwargs['from_date']
if category == CATEGORY_ISSUE:
items = self.__fetch_issues(from_date)
else:
items = self.__fetch_merge_requests(from_date)
return items | [
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CJWorkbench/cjworkbench | e0b878d8ff819817fa049a4126efcbfcec0b50e6 | renderer/execute/renderprep.py | python | _Cleaner._ | (self, schema: ParamSchema.File, value: Optional[str]) | return value | Convert a `file` String-encoded UUID to a tempfile `pathlib.Path`.
The return value:
* Points to a temporary file containing all bytes
* Has the same suffix as the originally-uploaded file
* Will have its file deleted when it goes out of scope
If the file is in the database but does not exist on s3, return `None`. | Convert a `file` String-encoded UUID to a tempfile `pathlib.Path`. | [
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] | def _(self, schema: ParamSchema.File, value: Optional[str]) -> Optional[Path]:
"""Convert a `file` String-encoded UUID to a tempfile `pathlib.Path`.
The return value:
* Points to a temporary file containing all bytes
* Has the same suffix as the originally-uploaded file
* Will have its file deleted when it goes out of scope
If the file is in the database but does not exist on s3, return `None`.
"""
if value is None:
return None
try:
uploaded_file = UploadedFileModel.objects.get(
uuid=value, step_id=self.step_id
)
except UploadedFileModel.DoesNotExist:
return None
# UploadedFileModel.name may not be POSIX-compliant. We want the filename to
# have the same suffix as the original: that helps with filetype
# detection. We also put the UUID in the name so debug messages help
# devs find the original file.
safe_name = FilesystemUnsafeChars.sub("-", uploaded_file.name)
path = self.basedir / (value + "_" + safe_name)
self.exit_stack.enter_context(deferred_delete(path))
try:
# Overwrite the file
s3.download(s3.UserFilesBucket, uploaded_file.key, path)
except FileNotFoundError:
# tempfile will be deleted by self.exit_stack
return None
self.uploaded_files[value] = UploadedFile(
name=uploaded_file.name,
filename=path.name,
uploaded_at=uploaded_file.created_at,
)
return value | [
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ayoolaolafenwa/PixelLib | ae56003c416a98780141a1170c9d888fe9a31317 | pixellib/torchbackend/instance/engine/train_loop.py | python | TrainerBase.train | (self, start_iter: int, max_iter: int) | Args:
start_iter, max_iter (int): See docs above | Args:
start_iter, max_iter (int): See docs above | [
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"""
Args:
start_iter, max_iter (int): See docs above
"""
logger = logging.getLogger(__name__)
logger.info("Starting training from iteration {}".format(start_iter))
self.iter = self.start_iter = start_iter
self.max_iter = max_iter
with EventStorage(start_iter) as self.storage:
try:
self.before_train()
for self.iter in range(start_iter, max_iter):
self.before_step()
self.run_step()
self.after_step()
# self.iter == max_iter can be used by `after_train` to
# tell whether the training successfully finished or failed
# due to exceptions.
self.iter += 1
except Exception:
logger.exception("Exception during training:")
raise
finally:
self.after_train() | [
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tobegit3hub/deep_image_model | 8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e | java_predict_client/src/main/proto/tensorflow/python/ops/control_flow_grad.py | python | _EnterGrad | (op, grad) | return result | Gradients for an Enter are calculated using an Exit op.
For loop variables, grad is the gradient so just add an exit.
For loop invariants, we need to add an accumulator loop. | Gradients for an Enter are calculated using an Exit op. | [
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] | def _EnterGrad(op, grad):
"""Gradients for an Enter are calculated using an Exit op.
For loop variables, grad is the gradient so just add an exit.
For loop invariants, we need to add an accumulator loop.
"""
graph = ops.get_default_graph()
# pylint: disable=protected-access
grad_ctxt = graph._get_control_flow_context()
# pylint: enable=protected-access
if not grad_ctxt.back_prop:
# Skip gradient computation, if the attribute `back_prop` is false.
return grad
if grad_ctxt.grad_state is None:
# Pass the gradient grough if we are not in a gradient while context.
return grad
if op.get_attr("is_constant"):
# Add a gradient accumulator for each loop invariant.
if isinstance(grad, ops.Tensor):
result = grad_ctxt.AddBackPropAccumulator(op, grad)
elif isinstance(grad, ops.IndexedSlices):
result = grad_ctxt.AddBackPropIndexedSlicesAccumulator(op, grad)
else:
# TODO(yuanbyu, lukasr): Add support for SparseTensor.
raise TypeError("Type %s not supported" % type(grad))
else:
result = exit(grad)
grad_ctxt.ExitResult([result])
return result | [
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peeringdb/peeringdb | 47c6a699267b35663898f8d261159bdae9720f04 | peeringdb_server/mock.py | python | Mock.create | (self, reftag, **kwargs) | return obj | Create a new instance of model specified in `reftag`
Any arguments passed as kwargs will override mock field values.
Note: Unless there are no relationships passed in kwargs, required parent
objects will be automatically created as well.
Returns: The created instance. | Create a new instance of model specified in `reftag` | [
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] | def create(self, reftag, **kwargs):
"""
Create a new instance of model specified in `reftag`
Any arguments passed as kwargs will override mock field values.
Note: Unless there are no relationships passed in kwargs, required parent
objects will be automatically created as well.
Returns: The created instance.
"""
model = REFTAG_MAP.get(reftag)
data = {}
data.update(**kwargs)
# first we create any required parent relation ships
for field in model._meta.get_fields():
if field.name in data:
continue
if field.is_relation and field.many_to_one:
if hasattr(field.related_model, "ref_tag"):
data[field.name] = self.create(field.related_model.handleref.tag)
# then we set the other fields to mock values provided by this class
for field in model._meta.get_fields():
# field value specified alrady, skip
if field.name in data:
continue
# these we don't care about
if field.name in ["id", "logo", "version", "created", "updated"]:
continue
# if reftag == "ixlan" and field.name != "id":
# continue
# elif reftag != "ixlan":
# continue
# this we don't care about either
if field.name.find("geocode") == 0:
continue
# choice fields should automatically select a value from
# the available choices
#
# PDB choices often have Not Disclosed at index 0 and 1
# so we try index 2 first.
if (
not field.is_relation
and field.choices
and not hasattr(self, field.name)
):
try:
data[field.name] = field.choices[2][0]
except IndexError:
data[field.name] = field.choices[0][0]
# bool fields set to True
elif isinstance(field, models.BooleanField):
data[field.name] = True
# every other field
elif not field.is_relation:
# emails
if field.name.find("email") > -1:
data[field.name] = "test@peeringdb.com"
# phone numbers
elif field.name.find("phone") > -1:
data[field.name] = "+12065550199"
# URLs
elif field.name.find("url") > -1:
data[field.name] = "{}/{}".format(
self.website(data, reftag=reftag), field.name
)
# everything else is routed to the apropriate method
# with the same name as the field name
else:
data[field.name] = getattr(self, field.name)(data, reftag=reftag)
obj = model(**data)
obj.clean()
obj.save()
return obj | [
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | ext/github/Repository.py | python | Repository.edit | (
self,
name=None,
description=github.GithubObject.NotSet,
homepage=github.GithubObject.NotSet,
private=github.GithubObject.NotSet,
has_issues=github.GithubObject.NotSet,
has_projects=github.GithubObject.NotSet,
has_wiki=github.GithubObject.NotSet,
has_downloads=github.GithubObject.NotSet,
default_branch=github.GithubObject.NotSet,
allow_squash_merge=github.GithubObject.NotSet,
allow_merge_commit=github.GithubObject.NotSet,
allow_rebase_merge=github.GithubObject.NotSet,
archived=github.GithubObject.NotSet,
) | :calls: `PATCH /repos/:owner/:repo <http://developer.github.com/v3/repos>`_
:param name: string
:param description: string
:param homepage: string
:param private: bool
:param has_issues: bool
:param has_projects: bool
:param has_wiki: bool
:param has_downloads: bool
:param default_branch: string
:param allow_squash_merge: bool
:param allow_merge_commit: bool
:param allow_rebase_merge: bool
:param archived: bool. Unarchiving repositories is currently not supported through API (https://developer.github.com/v3/repos/#edit)
:rtype: None | :calls: `PATCH /repos/:owner/:repo <http://developer.github.com/v3/repos>`_
:param name: string
:param description: string
:param homepage: string
:param private: bool
:param has_issues: bool
:param has_projects: bool
:param has_wiki: bool
:param has_downloads: bool
:param default_branch: string
:param allow_squash_merge: bool
:param allow_merge_commit: bool
:param allow_rebase_merge: bool
:param archived: bool. Unarchiving repositories is currently not supported through API (https://developer.github.com/v3/repos/#edit)
:rtype: None | [
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":",
"... | def edit(
self,
name=None,
description=github.GithubObject.NotSet,
homepage=github.GithubObject.NotSet,
private=github.GithubObject.NotSet,
has_issues=github.GithubObject.NotSet,
has_projects=github.GithubObject.NotSet,
has_wiki=github.GithubObject.NotSet,
has_downloads=github.GithubObject.NotSet,
default_branch=github.GithubObject.NotSet,
allow_squash_merge=github.GithubObject.NotSet,
allow_merge_commit=github.GithubObject.NotSet,
allow_rebase_merge=github.GithubObject.NotSet,
archived=github.GithubObject.NotSet,
):
"""
:calls: `PATCH /repos/:owner/:repo <http://developer.github.com/v3/repos>`_
:param name: string
:param description: string
:param homepage: string
:param private: bool
:param has_issues: bool
:param has_projects: bool
:param has_wiki: bool
:param has_downloads: bool
:param default_branch: string
:param allow_squash_merge: bool
:param allow_merge_commit: bool
:param allow_rebase_merge: bool
:param archived: bool. Unarchiving repositories is currently not supported through API (https://developer.github.com/v3/repos/#edit)
:rtype: None
"""
if name is None:
name = self.name
assert isinstance(name, (str, six.text_type)), name
assert description is github.GithubObject.NotSet or isinstance(
description, (str, six.text_type)
), description
assert homepage is github.GithubObject.NotSet or isinstance(
homepage, (str, six.text_type)
), homepage
assert private is github.GithubObject.NotSet or isinstance(
private, bool
), private
assert has_issues is github.GithubObject.NotSet or isinstance(
has_issues, bool
), has_issues
assert has_projects is github.GithubObject.NotSet or isinstance(
has_projects, bool
), has_projects
assert has_wiki is github.GithubObject.NotSet or isinstance(
has_wiki, bool
), has_wiki
assert has_downloads is github.GithubObject.NotSet or isinstance(
has_downloads, bool
), has_downloads
assert default_branch is github.GithubObject.NotSet or isinstance(
default_branch, (str, six.text_type)
), default_branch
assert allow_squash_merge is github.GithubObject.NotSet or isinstance(
allow_squash_merge, bool
), allow_squash_merge
assert allow_merge_commit is github.GithubObject.NotSet or isinstance(
allow_merge_commit, bool
), allow_merge_commit
assert allow_rebase_merge is github.GithubObject.NotSet or isinstance(
allow_rebase_merge, bool
), allow_rebase_merge
assert archived is github.GithubObject.NotSet or (
isinstance(archived, bool) and archived is True
), archived
post_parameters = {
"name": name,
}
if description is not github.GithubObject.NotSet:
post_parameters["description"] = description
if homepage is not github.GithubObject.NotSet:
post_parameters["homepage"] = homepage
if private is not github.GithubObject.NotSet:
post_parameters["private"] = private
if has_issues is not github.GithubObject.NotSet:
post_parameters["has_issues"] = has_issues
if has_projects is not github.GithubObject.NotSet:
post_parameters["has_projects"] = has_projects
if has_wiki is not github.GithubObject.NotSet:
post_parameters["has_wiki"] = has_wiki
if has_downloads is not github.GithubObject.NotSet:
post_parameters["has_downloads"] = has_downloads
if default_branch is not github.GithubObject.NotSet:
post_parameters["default_branch"] = default_branch
if allow_squash_merge is not github.GithubObject.NotSet:
post_parameters["allow_squash_merge"] = allow_squash_merge
if allow_merge_commit is not github.GithubObject.NotSet:
post_parameters["allow_merge_commit"] = allow_merge_commit
if allow_rebase_merge is not github.GithubObject.NotSet:
post_parameters["allow_rebase_merge"] = allow_rebase_merge
if archived is not github.GithubObject.NotSet:
post_parameters["archived"] = archived
headers, data = self._requester.requestJsonAndCheck(
"PATCH", self.url, input=post_parameters
)
self._useAttributes(data) | [
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"Not... | https://github.com/pymedusa/Medusa/blob/1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38/ext/github/Repository.py#L1395-L1497 | ||
jsonpickle/jsonpickle | 1594d3fdb6717cb06d05c79e46f93330cc38eb36 | jsonpickle/pickler.py | python | _mktyperef | (obj) | return {tags.TYPE: util.importable_name(obj)} | Return a typeref dictionary
>>> _mktyperef(AssertionError) == {'py/type': 'builtins.AssertionError'}
True | Return a typeref dictionary | [
"Return",
"a",
"typeref",
"dictionary"
] | def _mktyperef(obj):
"""Return a typeref dictionary
>>> _mktyperef(AssertionError) == {'py/type': 'builtins.AssertionError'}
True
"""
return {tags.TYPE: util.importable_name(obj)} | [
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hubblestack/hubble | 763142474edcecdec5fd25591dc29c3536e8f969 | hubblestack/modules/win_status.py | python | uptime | (human_readable=False) | return str(uptime) if human_readable else uptime.total_seconds() | .. versionadded:: 2015.8.0
Return the system uptime for the machine
Args:
human_readable (bool):
Return uptime in human readable format if ``True``, otherwise
return seconds. Default is ``False``
.. note::
Human readable format is ``days, hours:min:sec``. Days will only
be displayed if more than 0
Returns:
str:
The uptime in seconds or human readable format depending on the
value of ``human_readable``
CLI Example:
.. code-block:: bash
salt '*' status.uptime
salt '*' status.uptime human_readable=True | .. versionadded:: 2015.8.0 | [
"..",
"versionadded",
"::",
"2015",
".",
"8",
".",
"0"
] | def uptime(human_readable=False):
'''
.. versionadded:: 2015.8.0
Return the system uptime for the machine
Args:
human_readable (bool):
Return uptime in human readable format if ``True``, otherwise
return seconds. Default is ``False``
.. note::
Human readable format is ``days, hours:min:sec``. Days will only
be displayed if more than 0
Returns:
str:
The uptime in seconds or human readable format depending on the
value of ``human_readable``
CLI Example:
.. code-block:: bash
salt '*' status.uptime
salt '*' status.uptime human_readable=True
'''
# Get startup time
startup_time = datetime.datetime.fromtimestamp(psutil.boot_time())
# Subtract startup time from current time to get the uptime of the system
uptime = datetime.datetime.now() - startup_time
return str(uptime) if human_readable else uptime.total_seconds() | [
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Qirky/FoxDot | 76318f9630bede48ff3994146ed644affa27bfa4 | FoxDot/lib/ServerManager.py | python | SCLangServerManager.set_midi_nudge | (self, value) | return | [] | def set_midi_nudge(self, value):
self.midi_nudge = value
return | [
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TengXiaoDai/DistributedCrawling | f5c2439e6ce68dd9b49bde084d76473ff9ed4963 | Lib/random.py | python | Random.vonmisesvariate | (self, mu, kappa) | return theta | Circular data distribution.
mu is the mean angle, expressed in radians between 0 and 2*pi, and
kappa is the concentration parameter, which must be greater than or
equal to zero. If kappa is equal to zero, this distribution reduces
to a uniform random angle over the range 0 to 2*pi. | Circular data distribution. | [
"Circular",
"data",
"distribution",
"."
] | def vonmisesvariate(self, mu, kappa):
"""Circular data distribution.
mu is the mean angle, expressed in radians between 0 and 2*pi, and
kappa is the concentration parameter, which must be greater than or
equal to zero. If kappa is equal to zero, this distribution reduces
to a uniform random angle over the range 0 to 2*pi.
"""
# mu: mean angle (in radians between 0 and 2*pi)
# kappa: concentration parameter kappa (>= 0)
# if kappa = 0 generate uniform random angle
# Based upon an algorithm published in: Fisher, N.I.,
# "Statistical Analysis of Circular Data", Cambridge
# University Press, 1993.
# Thanks to Magnus Kessler for a correction to the
# implementation of step 4.
random = self.random
if kappa <= 1e-6:
return TWOPI * random()
s = 0.5 / kappa
r = s + _sqrt(1.0 + s * s)
while 1:
u1 = random()
z = _cos(_pi * u1)
d = z / (r + z)
u2 = random()
if u2 < 1.0 - d * d or u2 <= (1.0 - d) * _exp(d):
break
q = 1.0 / r
f = (q + z) / (1.0 + q * z)
u3 = random()
if u3 > 0.5:
theta = (mu + _acos(f)) % TWOPI
else:
theta = (mu - _acos(f)) % TWOPI
return theta | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/site-packages/django/core/files/uploadhandler.py | python | load_handler | (path, *args, **kwargs) | return cls(*args, **kwargs) | Given a path to a handler, return an instance of that handler.
E.g.::
>>> load_handler('django.core.files.uploadhandler.TemporaryFileUploadHandler', request)
<TemporaryFileUploadHandler object at 0x...> | Given a path to a handler, return an instance of that handler. | [
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] | def load_handler(path, *args, **kwargs):
"""
Given a path to a handler, return an instance of that handler.
E.g.::
>>> load_handler('django.core.files.uploadhandler.TemporaryFileUploadHandler', request)
<TemporaryFileUploadHandler object at 0x...>
"""
i = path.rfind('.')
module, attr = path[:i], path[i+1:]
try:
mod = importlib.import_module(module)
except ImportError, e:
raise ImproperlyConfigured('Error importing upload handler module %s: "%s"' % (module, e))
except ValueError, e:
raise ImproperlyConfigured('Error importing upload handler module. Is FILE_UPLOAD_HANDLERS a correctly defined list or tuple?')
try:
cls = getattr(mod, attr)
except AttributeError:
raise ImproperlyConfigured('Module "%s" does not define a "%s" upload handler backend' % (module, attr))
return cls(*args, **kwargs) | [
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/twisted/twisted/names/client.py | python | lookupResponsibility | (name, timeout=None) | return getResolver().lookupResponsibility(name, timeout) | Perform an RP record lookup.
@type name: C{str}
@param name: DNS name to resolve.
@type timeout: Sequence of C{int}
@param timeout: Number of seconds after which to reissue the query.
When the last timeout expires, the query is considered failed.
@rtype: C{Deferred} | Perform an RP record lookup. | [
"Perform",
"an",
"RP",
"record",
"lookup",
"."
] | def lookupResponsibility(name, timeout=None):
"""
Perform an RP record lookup.
@type name: C{str}
@param name: DNS name to resolve.
@type timeout: Sequence of C{int}
@param timeout: Number of seconds after which to reissue the query.
When the last timeout expires, the query is considered failed.
@rtype: C{Deferred}
"""
return getResolver().lookupResponsibility(name, timeout) | [
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kozec/syncthing-gtk | 01eeeb9ed485232e145bf39d90142832e1c9751e | syncthing_gtk/foldereditor.py | python | FolderEditorDialog.mark_device | (self, nid) | Marks (checks) checkbox for specified device | Marks (checks) checkbox for specified device | [
"Marks",
"(",
"checks",
")",
"checkbox",
"for",
"specified",
"device"
] | def mark_device(self, nid):
""" Marks (checks) checkbox for specified device """
if "vdevices" in self: # ... only if there are checkboxes here
for child in self["vdevices"].get_children():
if child.get_tooltip_text() == nid:
l = child.get_children()[0] # Label in checkbox
l.set_markup("<b>%s</b>" % (l.get_label()))
child.set_active(True) | [
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MDAnalysis/mdanalysis | 3488df3cdb0c29ed41c4fb94efe334b541e31b21 | package/MDAnalysis/core/groups.py | python | SegmentGroup.n_atoms | (self) | return len(self.atoms) | Number of atoms present in the :class:`SegmentGroup`, including
duplicate segments (and thus, duplicate atoms).
Equivalent to ``len(self.atoms)``. | Number of atoms present in the :class:`SegmentGroup`, including
duplicate segments (and thus, duplicate atoms). | [
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] | def n_atoms(self):
"""Number of atoms present in the :class:`SegmentGroup`, including
duplicate segments (and thus, duplicate atoms).
Equivalent to ``len(self.atoms)``.
"""
return len(self.atoms) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/sqlalchemy/orm/instrumentation.py | python | ClassManager.__init__ | (self, class_) | [] | def __init__(self, class_):
self.class_ = class_
self.info = {}
self.new_init = None
self.local_attrs = {}
self.originals = {}
self._bases = [mgr for mgr in [
manager_of_class(base)
for base in self.class_.__bases__
if isinstance(base, type)
] if mgr is not None]
for base in self._bases:
self.update(base)
self.dispatch._events._new_classmanager_instance(class_, self)
# events._InstanceEventsHold.populate(class_, self)
for basecls in class_.__mro__:
mgr = manager_of_class(basecls)
if mgr is not None:
self.dispatch._update(mgr.dispatch)
self.manage()
self._instrument_init()
if '__del__' in class_.__dict__:
util.warn("__del__() method on class %s will "
"cause unreachable cycles and memory leaks, "
"as SQLAlchemy instrumentation often creates "
"reference cycles. Please remove this method." %
class_) | [
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feliam/pysymemu | ad02e52122099d537372eb4d11fd5024b8a3857f | cpu.py | python | Cpu.JNZ | (cpu, target) | Jumps short if not zero.
@param cpu: current CPU.
@param target: destination operand. | Jumps short if not zero. | [
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] | def JNZ(cpu, target):
'''
Jumps short if not zero.
@param cpu: current CPU.
@param target: destination operand.
'''
cpu.JNE(target) | [
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xolox/python-humanfriendly | 6758ac61f906cd8528682003070a57febe4ad3cf | humanfriendly/prompts.py | python | prompt_for_confirmation | (question, default=None, padding=True) | Prompt the user for confirmation.
:param question: The text that explains what the user is confirming (a string).
:param default: The default value (a boolean) or :data:`None`.
:param padding: Refer to the documentation of :func:`prompt_for_input()`.
:returns: - If the user enters 'yes' or 'y' then :data:`True` is returned.
- If the user enters 'no' or 'n' then :data:`False` is returned.
- If the user doesn't enter any text or standard input is not
connected to a terminal (which makes it impossible to prompt
the user) the value of the keyword argument ``default`` is
returned (if that value is not :data:`None`).
:raises: - Any exceptions raised by :func:`retry_limit()`.
- Any exceptions raised by :func:`prompt_for_input()`.
When `default` is :data:`False` and the user doesn't enter any text an
error message is printed and the prompt is repeated:
>>> prompt_for_confirmation("Are you sure?")
<BLANKLINE>
Are you sure? [y/n]
<BLANKLINE>
Error: Please enter 'yes' or 'no' (there's no default choice).
<BLANKLINE>
Are you sure? [y/n]
The same thing happens when the user enters text that isn't recognized:
>>> prompt_for_confirmation("Are you sure?")
<BLANKLINE>
Are you sure? [y/n] about what?
<BLANKLINE>
Error: Please enter 'yes' or 'no' (the text 'about what?' is not recognized).
<BLANKLINE>
Are you sure? [y/n] | Prompt the user for confirmation. | [
"Prompt",
"the",
"user",
"for",
"confirmation",
"."
] | def prompt_for_confirmation(question, default=None, padding=True):
"""
Prompt the user for confirmation.
:param question: The text that explains what the user is confirming (a string).
:param default: The default value (a boolean) or :data:`None`.
:param padding: Refer to the documentation of :func:`prompt_for_input()`.
:returns: - If the user enters 'yes' or 'y' then :data:`True` is returned.
- If the user enters 'no' or 'n' then :data:`False` is returned.
- If the user doesn't enter any text or standard input is not
connected to a terminal (which makes it impossible to prompt
the user) the value of the keyword argument ``default`` is
returned (if that value is not :data:`None`).
:raises: - Any exceptions raised by :func:`retry_limit()`.
- Any exceptions raised by :func:`prompt_for_input()`.
When `default` is :data:`False` and the user doesn't enter any text an
error message is printed and the prompt is repeated:
>>> prompt_for_confirmation("Are you sure?")
<BLANKLINE>
Are you sure? [y/n]
<BLANKLINE>
Error: Please enter 'yes' or 'no' (there's no default choice).
<BLANKLINE>
Are you sure? [y/n]
The same thing happens when the user enters text that isn't recognized:
>>> prompt_for_confirmation("Are you sure?")
<BLANKLINE>
Are you sure? [y/n] about what?
<BLANKLINE>
Error: Please enter 'yes' or 'no' (the text 'about what?' is not recognized).
<BLANKLINE>
Are you sure? [y/n]
"""
# Generate the text for the prompt.
prompt_text = prepare_prompt_text(question, bold=True)
# Append the valid replies (and default reply) to the prompt text.
hint = "[Y/n]" if default else "[y/N]" if default is not None else "[y/n]"
prompt_text += " %s " % prepare_prompt_text(hint, color=HIGHLIGHT_COLOR)
# Loop until a valid response is given.
logger.debug("Requesting interactive confirmation from terminal: %r", ansi_strip(prompt_text).rstrip())
for attempt in retry_limit():
reply = prompt_for_input(prompt_text, '', padding=padding, strip=True)
if reply.lower() in ('y', 'yes'):
logger.debug("Confirmation granted by reply (%r).", reply)
return True
elif reply.lower() in ('n', 'no'):
logger.debug("Confirmation denied by reply (%r).", reply)
return False
elif (not reply) and default is not None:
logger.debug("Default choice selected by empty reply (%r).",
"granted" if default else "denied")
return default
else:
details = ("the text '%s' is not recognized" % reply
if reply else "there's no default choice")
logger.debug("Got %s reply (%s), retrying (%i/%i) ..",
"invalid" if reply else "empty", details,
attempt, MAX_ATTEMPTS)
warning("{indent}Error: Please enter 'yes' or 'no' ({details}).",
indent=' ' if padding else '', details=details) | [
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/IronPython/27/Lib/_strptime.py | python | _strptime | (data_string, format="%a %b %d %H:%M:%S %Y") | return (time.struct_time((year, month, day,
hour, minute, second,
weekday, julian, tz)), fraction) | Return a time struct based on the input string and the format string. | Return a time struct based on the input string and the format string. | [
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"""Return a time struct based on the input string and the format string."""
global _TimeRE_cache, _regex_cache
with _cache_lock:
locale_time = _TimeRE_cache.locale_time
if (_getlang() != locale_time.lang or
time.tzname != locale_time.tzname or
time.daylight != locale_time.daylight):
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_regex_cache.clear()
locale_time = _TimeRE_cache.locale_time
if len(_regex_cache) > _CACHE_MAX_SIZE:
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format_regex = _regex_cache.get(format)
if not format_regex:
try:
format_regex = _TimeRE_cache.compile(format)
# KeyError raised when a bad format is found; can be specified as
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except KeyError, err:
bad_directive = err.args[0]
if bad_directive == "\\":
bad_directive = "%"
del err
raise ValueError("'%s' is a bad directive in format '%s'" %
(bad_directive, format))
# IndexError only occurs when the format string is "%"
except IndexError:
raise ValueError("stray %% in format '%s'" % format)
_regex_cache[format] = format_regex
found = format_regex.match(data_string)
if not found:
raise ValueError("time data %r does not match format %r" %
(data_string, format))
if len(data_string) != found.end():
raise ValueError("unconverted data remains: %s" %
data_string[found.end():])
year = None
month = day = 1
hour = minute = second = fraction = 0
tz = -1
# Default to -1 to signify that values not known; not critical to have,
# though
week_of_year = -1
week_of_year_start = -1
# weekday and julian defaulted to None so as to signal need to calculate
# values
weekday = julian = None
found_dict = found.groupdict()
for group_key in found_dict.iterkeys():
# Directives not explicitly handled below:
# c, x, X
# handled by making out of other directives
# U, W
# worthless without day of the week
if group_key == 'y':
year = int(found_dict['y'])
# Open Group specification for strptime() states that a %y
#value in the range of [00, 68] is in the century 2000, while
#[69,99] is in the century 1900
if year <= 68:
year += 2000
else:
year += 1900
elif group_key == 'Y':
year = int(found_dict['Y'])
elif group_key == 'm':
month = int(found_dict['m'])
elif group_key == 'B':
month = locale_time.f_month.index(found_dict['B'].lower())
elif group_key == 'b':
month = locale_time.a_month.index(found_dict['b'].lower())
elif group_key == 'd':
day = int(found_dict['d'])
elif group_key == 'H':
hour = int(found_dict['H'])
elif group_key == 'I':
hour = int(found_dict['I'])
ampm = found_dict.get('p', '').lower()
# If there was no AM/PM indicator, we'll treat this like AM
if ampm in ('', locale_time.am_pm[0]):
# We're in AM so the hour is correct unless we're
# looking at 12 midnight.
# 12 midnight == 12 AM == hour 0
if hour == 12:
hour = 0
elif ampm == locale_time.am_pm[1]:
# We're in PM so we need to add 12 to the hour unless
# we're looking at 12 noon.
# 12 noon == 12 PM == hour 12
if hour != 12:
hour += 12
elif group_key == 'M':
minute = int(found_dict['M'])
elif group_key == 'S':
second = int(found_dict['S'])
elif group_key == 'f':
s = found_dict['f']
# Pad to always return microseconds.
s += "0" * (6 - len(s))
fraction = int(s)
elif group_key == 'A':
weekday = locale_time.f_weekday.index(found_dict['A'].lower())
elif group_key == 'a':
weekday = locale_time.a_weekday.index(found_dict['a'].lower())
elif group_key == 'w':
weekday = int(found_dict['w'])
if weekday == 0:
weekday = 6
else:
weekday -= 1
elif group_key == 'j':
julian = int(found_dict['j'])
elif group_key in ('U', 'W'):
week_of_year = int(found_dict[group_key])
if group_key == 'U':
# U starts week on Sunday.
week_of_year_start = 6
else:
# W starts week on Monday.
week_of_year_start = 0
elif group_key == 'Z':
# Since -1 is default value only need to worry about setting tz if
# it can be something other than -1.
found_zone = found_dict['Z'].lower()
for value, tz_values in enumerate(locale_time.timezone):
if found_zone in tz_values:
# Deal with bad locale setup where timezone names are the
# same and yet time.daylight is true; too ambiguous to
# be able to tell what timezone has daylight savings
if (time.tzname[0] == time.tzname[1] and
time.daylight and found_zone not in ("utc", "gmt")):
break
else:
tz = value
break
leap_year_fix = False
if year is None and month == 2 and day == 29:
year = 1904 # 1904 is first leap year of 20th century
leap_year_fix = True
elif year is None:
year = 1900
# If we know the week of the year and what day of that week, we can figure
# out the Julian day of the year.
if julian is None and week_of_year != -1 and weekday is not None:
week_starts_Mon = True if week_of_year_start == 0 else False
julian = _calc_julian_from_U_or_W(year, week_of_year, weekday,
week_starts_Mon)
if julian <= 0:
year -= 1
yday = 366 if calendar.isleap(year) else 365
julian += yday
# Cannot pre-calculate datetime_date() since can change in Julian
# calculation and thus could have different value for the day of the week
# calculation.
if julian is None:
# Need to add 1 to result since first day of the year is 1, not 0.
julian = datetime_date(year, month, day).toordinal() - \
datetime_date(year, 1, 1).toordinal() + 1
else: # Assume that if they bothered to include Julian day it will
# be accurate.
datetime_result = datetime_date.fromordinal((julian - 1) + datetime_date(year, 1, 1).toordinal())
year = datetime_result.year
month = datetime_result.month
day = datetime_result.day
if weekday is None:
weekday = datetime_date(year, month, day).weekday()
if leap_year_fix:
# the caller didn't supply a year but asked for Feb 29th. We couldn't
# use the default of 1900 for computations. We set it back to ensure
# that February 29th is smaller than March 1st.
year = 1900
return (time.struct_time((year, month, day,
hour, minute, second,
weekday, julian, tz)), fraction) | [
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gxcuizy/Python | 72167d12439a615a8fd4b935eae1fb6516ed4e69 | 从零学Python-掘金活动/day22/matplotlib_use.py | python | fun_8 | () | Image 图片 | Image 图片 | [
"Image",
"图片"
] | def fun_8():
"""Image 图片"""
# 用这样 3x3 的 2D-array 来表示点的颜色
a = numpy.array(
[0.313660827978, 0.365348418405, 0.423733120134, 0.365348418405, 0.439599930621, 0.525083754405, 0.423733120134,
0.525083754405, 0.651536351379]).reshape(3, 3)
pyplot.imshow(a, interpolation='nearest', cmap='bone', origin='lower')
pyplot.colorbar(shrink=.92)
# 去掉xy的刻度
pyplot.xticks(())
pyplot.yticks(())
# 显示图像
pyplot.show() | [
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roam-qgis/Roam | 6bfa836a2735f611b7f26de18ae4a4581f7e83ef | src/configmanager/ui/layerwidgets.py | python | InfoNode.update_panel_status | (self, *args) | Update if the SQL panel is enabled or disable if the source is SQL Server or SQLite. | Update if the SQL panel is enabled or disable if the source is SQL Server or SQLite. | [
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"""
Update if the SQL panel is enabled or disable if the source is SQL Server or SQLite.
"""
layer = self.layer
if not layer:
self.queryframe.setEnabled(False)
return False
source = layer.source()
name = layer.dataProvider().name()
if ".sqlite" in source or name == "mssql" and layer.isValid():
keys = layer.primaryKeyAttributes()
fields = layer.fields()
if keys:
fieldnames = " + ".join(fields[key].name() for key in keys)
elif fields.count() > 0:
fieldnames = fields.at(0).name()
else:
fieldnames = ""
self.keyColumnLabel.setText(fieldnames)
self.queryframe.setEnabled(True)
self.queryframe.show()
return True
else:
self.keyColumnLabel.setText("")
self.queryframe.setEnabled(False)
self.queryframe.hide()
return False | [
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fab-jul/imgcomp-cvpr | f03ce0bfa846f7ba1bf9b7ba415b082efe5c192c | code/inputpipeline.py | python | InputPipeline.get_batch | (self) | return self._batch | [] | def get_batch(self):
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brainix/pottery | 0a57ef51949e13f10ffbe5a8b499ea9cb1909ffc | pottery/base.py | python | Primitive.key | (self) | return self.__key | [] | def key(self) -> str:
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/distributions/gmm.py | python | GMM.__mul__ | (self, other) | return self.multiply(other) | r"""
Multiply two GMMs, or a GMM by a Gaussian, matrix, or float. See the `multiply` method for more information.
Warnings: the multiplication of two GMMs performed here is NOT the one that multiply the components
element-wise. For this one, have a look at `multiply_element_wise` method, or the `__and__` operator.
Args:
other (GMM, Gaussian, torch.float[D,D], float): GMM, Gaussian, or square matrix (to rotate or scale), or float
Returns:
GMM: resulting GMM | r"""
Multiply two GMMs, or a GMM by a Gaussian, matrix, or float. See the `multiply` method for more information. | [
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r"""
Multiply two GMMs, or a GMM by a Gaussian, matrix, or float. See the `multiply` method for more information.
Warnings: the multiplication of two GMMs performed here is NOT the one that multiply the components
element-wise. For this one, have a look at `multiply_element_wise` method, or the `__and__` operator.
Args:
other (GMM, Gaussian, torch.float[D,D], float): GMM, Gaussian, or square matrix (to rotate or scale), or float
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"""
return self.multiply(other) | [
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autotest/autotest | 4614ae5f550cc888267b9a419e4b90deb54f8fae | client/harness.py | python | harness.run_complete | (self) | A run within this job is completing (all done) | A run within this job is completing (all done) | [
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ClusterHQ/flocker | eaa586248986d7cd681c99c948546c2b507e44de | flocker/control/_model.py | python | DeploymentState.update_node | (self, node_state) | return self.transform(["nodes", updated_node.uuid], updated_node) | Create new ``DeploymentState`` based on this one which updates an
existing ``NodeState`` with any known information from the given
``NodeState``. Attributes which are set to ``None` on the given
update, indicating ignorance, will not be changed in the result.
The given ``NodeState`` will simply be added if it doesn't represent a
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comparison).
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this ``DeploymentState``.
:return DeploymentState: Updated with new ``NodeState``. | Create new ``DeploymentState`` based on this one which updates an
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Create new ``DeploymentState`` based on this one which updates an
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``NodeState``. Attributes which are set to ``None` on the given
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original_node = self.nodes.get(node_state.uuid)
if original_node is None:
return self.transform(["nodes", node_state.uuid], node_state)
updated_node = original_node.evolver()
for key, value in node_state.items():
if value is not None:
updated_node = updated_node.set(key, value)
updated_node = updated_node.persistent()
return self.transform(["nodes", updated_node.uuid], updated_node) | [
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spectacles/CodeComplice | 8ca8ee4236f72b58caa4209d2fbd5fa56bd31d62 | libs/langinfo.py | python | LangInfo.__init__ | (self, db) | [] | def __init__(self, db):
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/tarfile.py | python | _LowLevelFile.read | (self, size) | return os.read(self.fd, size) | [] | def read(self, size):
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.5/django/contrib/gis/gdal/geomtype.py | python | OGRGeomType.__eq__ | (self, other) | Does an equivalence test on the OGR type with the given
other OGRGeomType, the short-hand string, or the integer. | Does an equivalence test on the OGR type with the given
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return self.num == other.num
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deanishe/alfred-fakeum | 12a7e64d9c099c0f11416ee99fae064d6360aab2 | src/libs/faker/providers/address/ja_JP/__init__.py | python | Provider.town | (self) | return self.random_element(self.towns) | :example '浅草' | :example '浅草' | [
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chromium/web-page-replay | 472351e1122bb1beb936952c7e75ae58bf8a69f1 | third_party/dns/message.py | python | Message.want_dnssec | (self, wanted=True) | Enable or disable 'DNSSEC desired' flag in requests.
@param wanted: Is DNSSEC desired? If True, EDNS is enabled if
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@type wanted: bool
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JetBrains/python-skeletons | 95ad24b666e475998e5d1cc02ed53a2188036167 | numpy/core/__init__.py | python | generic.trace | (self, *args, **kwargs) | Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest. | Not implemented (virtual attribute) | [
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"""
Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
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The corresponding attribute of the derived class of interest.
"""
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sabnzbd/sabnzbd | 52d21e94d3cc6e30764a833fe2a256783d1a8931 | sabnzbd/scheduler.py | python | enable_server | (server) | Enable server (scheduler only) | Enable server (scheduler only) | [
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except:
logging.warning(T("Trying to set status of non-existing server %s"), server)
return
config.save_config()
sabnzbd.Downloader.update_server(server, server) | [
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adobe/antialiased-cnns | b27a34a26f3ab039113d44d83c54d0428598ac9c | antialiased_cnns/resnet.py | python | conv3x3 | (in_planes, out_planes, stride=1, groups=1, dilation=1) | return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=dilation, groups=groups, bias=False, dilation=dilation) | 3x3 convolution with padding | 3x3 convolution with padding | [
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"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
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mesonbuild/meson | a22d0f9a0a787df70ce79b05d0c45de90a970048 | mesonbuild/compilers/mixins/clike.py | python | CLikeCompiler.compiler_args | (self, args: T.Optional[T.Iterable[str]] = None) | return CLikeCompilerArgs(self, args) | [] | def compiler_args(self, args: T.Optional[T.Iterable[str]] = None) -> CLikeCompilerArgs:
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return CLikeCompilerArgs(self, args) | [
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stepjam/PyRep | d778d5d4ffa3be366d4e699f6e2941553fd47ecc | pyrep/objects/shape.py | python | Shape.add_force_and_torque | (self, force: np.ndarray, torque: np.ndarray,
reset_force: bool = False,
reset_torque: bool = False) | Adds a force and/or torque to a shape object that is dynamically
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Added forces and torques are cumulative.
:param force: The force (in absolute coordinates) to add.
:param torque: The torque (in absolute coordinates) to add.
:param reset_force: Clears the accumulated force.
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reset_force: bool = False,
reset_torque: bool = False) -> None:
"""
Adds a force and/or torque to a shape object that is dynamically
enabled. Forces are applied at the center of mass.
Added forces and torques are cumulative.
:param force: The force (in absolute coordinates) to add.
:param torque: The torque (in absolute coordinates) to add.
:param reset_force: Clears the accumulated force.
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"""
h = self._handle
if reset_force:
h |= sim.sim_handleflag_resetforce
if reset_torque:
h |= sim.sim_handleflag_resettorque
sim.simAddForceAndTorque(h,
None if force is None else list(force),
None if torque is None else list(torque)) | [
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Azure/azure-linux-extensions | a42ef718c746abab2b3c6a21da87b29e76364558 | Common/libpsutil/py2.6-glibc-2.12-pre/psutil/_pswindows.py | python | net_connections | (kind, _pid=-1) | return ret | Return socket connections. If pid == -1 return system-wide
connections (as opposed to connections opened by one process only). | Return socket connections. If pid == -1 return system-wide
connections (as opposed to connections opened by one process only). | [
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"""Return socket connections. If pid == -1 return system-wide
connections (as opposed to connections opened by one process only).
"""
if kind not in conn_tmap:
raise ValueError("invalid %r kind argument; choose between %s"
% (kind, ', '.join([repr(x) for x in conn_tmap])))
families, types = conn_tmap[kind]
rawlist = cext.net_connections(_pid, families, types)
ret = []
for item in rawlist:
fd, fam, type, laddr, raddr, status, pid = item
status = TCP_STATUSES[status]
if _pid == -1:
nt = _common.sconn(fd, fam, type, laddr, raddr, status, pid)
else:
nt = _common.pconn(fd, fam, type, laddr, raddr, status)
ret.append(nt)
return ret | [
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limodou/ulipad | 4c7d590234f39cac80bb1d36dca095b646e287fb | mixins/ShellWindow.py | python | NEInterpreter.push | (self, command) | return more | Send command to the interpreter to be executed.
Because this may be called recursively, we append a new list
onto the commandBuffer list and then append commands into
that. If the passed in command is part of a multi-line
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"""Send command to the interpreter to be executed.
Because this may be called recursively, we append a new list
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that. If the passed in command is part of a multi-line
command we keep appending the pieces to the last list in
commandBuffer until we have a complete command. If not, we
delete that last list."""
if isinstance(command, types.UnicodeType):
command = command.encode(common.defaultencoding)
if not self.more:
try: del self.commandBuffer[-1]
except IndexError: pass
if not self.more: self.commandBuffer.append([])
self.commandBuffer[-1].append(command)
source = os.linesep.join(self.commandBuffer[-1])
more = self.more = self.runsource(source)
dispatcher.send(signal='Interpreter.push', sender=self,
command=command, more=more, source=source)
return more | [
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ctxis/canape | 5f0e03424577296bcc60c2008a60a98ec5307e4b | CANAPE.Scripting/Lib/logging/__init__.py | python | Manager.setLoggerClass | (self, klass) | Set the class to be used when instantiating a logger with this Manager. | Set the class to be used when instantiating a logger with this Manager. | [
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"""
Set the class to be used when instantiating a logger with this Manager.
"""
if klass != Logger:
if not issubclass(klass, Logger):
raise TypeError("logger not derived from logging.Logger: "
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knipknap/exscript | a20e83ae3a78ea7e5ba25f07c1d9de4e9b961e83 | Exscript/protocols/telnetlib.py | python | Telnet.read_lazy | (self) | return self.read_very_lazy() | Process and return data that's already in the queues (lazy).
Raise EOFError if connection closed and no data available.
Return '' if no cooked data available otherwise. Don't block
unless in the midst of an IAC sequence. | Process and return data that's already in the queues (lazy). | [
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Raise EOFError if connection closed and no data available.
Return '' if no cooked data available otherwise. Don't block
unless in the midst of an IAC sequence.
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/geometry/line.py | python | LinearEntity.is_similar | (self, other) | return _norm(*self.coefficients) == _norm(*other.coefficients) | Return True if self and other are contained in the same line.
Examples
========
>>> from sympy import Point, Line
>>> p1, p2, p3 = Point(0, 1), Point(3, 4), Point(2, 3)
>>> l1 = Line(p1, p2)
>>> l2 = Line(p1, p3)
>>> l1.is_similar(l2)
True | Return True if self and other are contained in the same line. | [
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"""
Return True if self and other are contained in the same line.
Examples
========
>>> from sympy import Point, Line
>>> p1, p2, p3 = Point(0, 1), Point(3, 4), Point(2, 3)
>>> l1 = Line(p1, p2)
>>> l2 = Line(p1, p3)
>>> l1.is_similar(l2)
True
"""
def _norm(a, b, c):
if a != 0:
return 1, b/a, c/a
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BigBrotherBot/big-brother-bot | 848823c71413c86e7f1ff9584f43e08d40a7f2c0 | b3/plugins/customcommands/__init__.py | python | CustomcommandsPlugin._validate_cmd_template | (self, template) | Makes sure a command template is correct.
Raise ValueError if invalid. | Makes sure a command template is correct.
Raise ValueError if invalid. | [
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"""
Makes sure a command template is correct.
Raise ValueError if invalid.
"""
assert template is not None
if template.strip() == '':
raise ValueError("command template cannot be blank")
if template.count("<ARG:") > 1:
raise ValueError("command template cannot have more than one 'ARG' placeholder") | [
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ramusus/kinopoiskpy | e49b41eff7ae4252987636ec14c060109a50fad6 | kinopoisk/utils.py | python | Manager.get_url_with_params | (self, query) | return 'http://www.kinopoisk.ru/index.php', {'kp_query': query} | [] | def get_url_with_params(self, query):
return 'http://www.kinopoisk.ru/index.php', {'kp_query': query} | [
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google/vimdoc | 58b7b8b0c0d153ca3f689928f64c20953c14ded0 | vimdoc/output.py | python | Helpfile.Print | (self, line, end='\n', wide=False) | Outputs a line to the file. | Outputs a line to the file. | [
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if not wide:
assert len(line) <= self.WIDTH
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learningequality/kolibri | d056dbc477aaf651ab843caa141a6a1e0a491046 | kolibri/utils/server.py | python | get_status | () | return pid, LISTEN_ADDRESS, listen_port | Tries to get the PID of a running server.
The behavior is also quite redundant given that `kolibri start` should
always create a PID file, and if its been started directly with the
runserver command, then its up to the developer to know what's happening.
:returns: (PID, address, port), where address is not currently detected in
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listening on several IPs.
:raises: NotRunning | Tries to get the PID of a running server. | [
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"""
Tries to get the PID of a running server.
The behavior is also quite redundant given that `kolibri start` should
always create a PID file, and if its been started directly with the
runserver command, then its up to the developer to know what's happening.
:returns: (PID, address, port), where address is not currently detected in
a valid way because it's not configurable, and we might be
listening on several IPs.
:raises: NotRunning
"""
# PID file exists and startup has finished, check if it is running
pid, port, _, status = _read_pid_file(PID_FILE)
if status not in IS_RUNNING:
raise NotRunning(status)
if status == STATUS_STARTING_UP:
try:
wait_for_occupied_port(LISTEN_ADDRESS, port)
except OSError:
raise NotRunning(STATUS_FAILED_TO_START)
if status == STATUS_SHUTTING_DOWN:
try:
wait_for_free_port(LISTEN_ADDRESS, port)
except OSError:
raise NotRunning(STATUS_UNCLEAN_SHUTDOWN)
raise NotRunning(STATUS_STOPPED)
# PID file exists, but process is dead
if pid is None or not pid_exists(pid):
raise NotRunning(STATUS_UNCLEAN_SHUTDOWN) # Unclean shutdown
listen_port = port
prefix = (
conf.OPTIONS["Deployment"]["URL_PATH_PREFIX"]
if conf.OPTIONS["Deployment"]["URL_PATH_PREFIX"] == "/"
else "/" + conf.OPTIONS["Deployment"]["URL_PATH_PREFIX"]
)
check_url = "http://{}:{}{}status/".format("127.0.0.1", listen_port, prefix)
if conf.OPTIONS["Server"]["CHERRYPY_START"]:
try:
# Timeout is 3 seconds, we don't want the status command to be slow
# TODO: Using 127.0.0.1 is a hardcode default from Kolibri, it could
# be configurable
# TODO: HTTP might not be the protocol if server has SSL
response = requests.get(check_url, timeout=3)
except (requests.exceptions.ReadTimeout, requests.exceptions.ConnectionError):
raise NotRunning(STATUS_NOT_RESPONDING)
except (requests.exceptions.RequestException):
raise NotRunning(STATUS_UNCLEAN_SHUTDOWN)
if response.status_code == 404:
raise NotRunning(STATUS_UNKNOWN_INSTANCE) # Unknown HTTP server
if response.status_code != 200:
# Probably a mis-configured kolibri
sys.stderr.write("---Debug information---\n")
sys.stderr.write(response.text)
sys.stderr.write("\n-----------------------\n")
raise NotRunning(STATUS_SERVER_CONFIGURATION_ERROR)
else:
try:
requests.get(check_url, timeout=3)
except (requests.exceptions.ReadTimeout, requests.exceptions.ConnectionError):
raise NotRunning(STATUS_NOT_RESPONDING)
except (requests.exceptions.RequestException):
return pid, "", ""
return pid, LISTEN_ADDRESS, listen_port | [
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... | https://github.com/learningequality/kolibri/blob/d056dbc477aaf651ab843caa141a6a1e0a491046/kolibri/utils/server.py#L817-L894 | |
pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | medusa/tv/series.py | python | SeriesIdentifier.from_id | (cls, indexer, indexer_id) | return SeriesIdentifier(indexer, indexer_id) | Create SeriesIdentifier from tuple (indexer, indexer_id). | Create SeriesIdentifier from tuple (indexer, indexer_id). | [
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] | def from_id(cls, indexer, indexer_id):
"""Create SeriesIdentifier from tuple (indexer, indexer_id)."""
return SeriesIdentifier(indexer, indexer_id) | [
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/visualize/owviolinplot.py | python | BoxItem._create_box_plot | (data: np.ndarray) | return min_, q25, q75, max_ | [] | def _create_box_plot(data: np.ndarray) -> Tuple:
if data.size == 0:
return (0,) * 4
q25, q75 = np.percentile(data, [25, 75])
whisker_lim = 1.5 * stats.iqr(data)
min_ = np.min(data[data >= (q25 - whisker_lim)])
max_ = np.max(data[data <= (q75 + whisker_lim)])
return min_, q25, q75, max_ | [
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peterbrittain/asciimatics | 9a490faddf484ee5b9b845316f921f5888b23b18 | samples/terminal.py | python | Terminal._add_stream | (self, value) | Process any output from the TTY. | Process any output from the TTY. | [
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Process any output from the TTY.
"""
lines = value.split("\n")
for i, line in enumerate(lines):
self._parser.reset(line, self._current_colours)
for offset, command, params in self._parser.parse():
if command == Parser.DISPLAY_TEXT:
# Just display the text... allowing for line wrapping.
if self._cursor_x + len(params) > self._w:
part_1 = params[:self._w - self._cursor_x]
part_2 = params[self._w - self._cursor_x:]
self._print_at(part_1, self._cursor_x, self._cursor_y)
self._print_at(part_2, 0, self._cursor_y + 1)
self._cursor_x = len(part_2)
self._cursor_y += 1
if self._cursor_y - self._canvas.start_line >= self._h:
self._canvas.scroll()
else:
self._print_at(params, self._cursor_x, self._cursor_y)
self._cursor_x += len(params)
elif command == Parser.CHANGE_COLOURS:
# Change current text colours.
self._current_colours = params
elif command == Parser.NEXT_TAB:
# Move to next tab stop - hard-coded to default of 8 characters.
self._cursor_x = (self._cursor_x // 8) * 8 + 8
elif command == Parser.MOVE_RELATIVE:
# Move cursor relative to current position.
self._cursor_x += params[0]
self._cursor_y += params[1]
if self._cursor_y < self._canvas.start_line:
self._canvas.scroll(self._cursor_y - self._canvas.start_line)
elif command == Parser.MOVE_ABSOLUTE:
# Move cursor relative to specified absolute position.
if params[0] is not None:
self._cursor_x = params[0]
if params[1] is not None:
self._cursor_y = params[1] + self._canvas.start_line
elif command == Parser.DELETE_LINE:
# Delete some/all of the current line.
if params == 0:
self._print_at(" " * (self._w - self._cursor_x), self._cursor_x, self._cursor_y)
elif params == 1:
self._print_at(" " * self._cursor_x, 0, self._cursor_y)
elif params == 2:
self._print_at(" " * self._w, 0, self._cursor_y)
elif command == Parser.DELETE_CHARS:
# Delete n characters under the cursor.
for x in range(self._cursor_x, self._w):
if x + params < self._w:
cell = self._canvas.get_from(x + params, self._cursor_y)
else:
cell = (ord(" "),
self._current_colours[0],
self._current_colours[1],
self._current_colours[2])
self._canvas.print_at(
chr(cell[0]), x, self._cursor_y, colour=cell[1], attr=cell[2], bg=cell[3])
elif command == Parser.SHOW_CURSOR:
# Show/hide the cursor.
self._show_cursor = params
elif command == Parser.CLEAR_SCREEN:
# Clear the screen.
self._canvas.clear_buffer(
self._current_colours[0], self._current_colours[1], self._current_colours[2])
# Move to next line, scrolling buffer as needed.
if i != len(lines) - 1:
self._cursor_x = 0
self._cursor_y += 1
if self._cursor_y - self._canvas.start_line >= self._h:
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spacetx/starfish | 0e879d995d5c49b6f5a842e201e3be04c91afc7e | starfish/core/spots/AssignTargets/_base.py | python | AssignTargetsAlgorithm.run | (
self,
masks: BinaryMaskCollection,
decoded_intensity_table: DecodedIntensityTable,
verbose: bool = False,
in_place: bool = False,
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self,
masks: BinaryMaskCollection,
decoded_intensity_table: DecodedIntensityTable,
verbose: bool = False,
in_place: bool = False,
) -> DecodedIntensityTable:
"""Performs target (e.g. gene) assignment given the spots and the regions."""
raise NotImplementedError() | [
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ym2011/ScanBackdoor | 3a10de49c3ebd90c2f0eb62304877e00d2a52396 | scan.py | python | Version | () | [] | def Version():
print 'scan 0.02 BASE' | [
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] | https://github.com/ym2011/ScanBackdoor/blob/3a10de49c3ebd90c2f0eb62304877e00d2a52396/scan.py#L19-L20 | ||||
plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/barpolar/marker/colorbar/_title.py | python | Title.side | (self) | return self["side"] | Determines the location of color bar's title with respect to
the color bar. Defaults to "top" when `orientation` if "v" and
defaults to "right" when `orientation` if "h". Note that the
title's location used to be set by the now deprecated
`titleside` attribute.
The 'side' property is an enumeration that may be specified as:
- One of the following enumeration values:
['right', 'top', 'bottom']
Returns
-------
Any | Determines the location of color bar's title with respect to
the color bar. Defaults to "top" when `orientation` if "v" and
defaults to "right" when `orientation` if "h". Note that the
title's location used to be set by the now deprecated
`titleside` attribute.
The 'side' property is an enumeration that may be specified as:
- One of the following enumeration values:
['right', 'top', 'bottom'] | [
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"""
Determines the location of color bar's title with respect to
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defaults to "right" when `orientation` if "h". Note that the
title's location used to be set by the now deprecated
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The 'side' property is an enumeration that may be specified as:
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return self["side"] | [
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maas/maas | db2f89970c640758a51247c59bf1ec6f60cf4ab5 | src/provisioningserver/utils/network.py | python | IPRangeStatistics.available_percentage | (self) | return float(self.num_available) / float(self.total_addresses) | Returns the utilization percentage for this set of addresses.
:return:float | Returns the utilization percentage for this set of addresses.
:return:float | [
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] | def available_percentage(self):
"""Returns the utilization percentage for this set of addresses.
:return:float"""
return float(self.num_available) / float(self.total_addresses) | [
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wucng/TensorExpand | 4ea58f64f5c5082b278229b799c9f679536510b7 | TensorExpand/Object detection/faster rcnn/CharlesShang-TFFRCNN-master/lib/datasets/nthu.py | python | nthu.image_path_at | (self, i) | return self.image_path_from_index(self.image_index[i]) | Return the absolute path to image i in the image sequence. | Return the absolute path to image i in the image sequence. | [
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"i",
"in",
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"."
] | def image_path_at(self, i):
"""
Return the absolute path to image i in the image sequence.
"""
return self.image_path_from_index(self.image_index[i]) | [
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ceph/ceph-deploy | a16316fc4dd364135b11226df42d9df65c0c60a2 | ceph_deploy/mon.py | python | get_mon_initial_members | (args, error_on_empty=False, _cfg=None) | return mon_initial_members | Read the Ceph config file and return the value of mon_initial_members
Optionally, a NeedHostError can be raised if the value is None. | Read the Ceph config file and return the value of mon_initial_members
Optionally, a NeedHostError can be raised if the value is None. | [
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] | def get_mon_initial_members(args, error_on_empty=False, _cfg=None):
"""
Read the Ceph config file and return the value of mon_initial_members
Optionally, a NeedHostError can be raised if the value is None.
"""
if _cfg:
cfg = _cfg
else:
cfg = conf.ceph.load(args)
mon_initial_members = cfg.safe_get('global', 'mon_initial_members')
if not mon_initial_members:
if error_on_empty:
raise exc.NeedHostError(
'could not find `mon initial members` defined in ceph.conf'
)
else:
mon_initial_members = re.split(r'[,\s]+', mon_initial_members)
return mon_initial_members | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/modulefinder.py | python | ModuleFinder.replace_paths_in_code | (self, co) | return types.CodeType(co.co_argcount, co.co_nlocals, co.co_stacksize,
co.co_flags, co.co_code, tuple(consts), co.co_names,
co.co_varnames, new_filename, co.co_name,
co.co_firstlineno, co.co_lnotab,
co.co_freevars, co.co_cellvars) | [] | def replace_paths_in_code(self, co):
new_filename = original_filename = os.path.normpath(co.co_filename)
for f, r in self.replace_paths:
if original_filename.startswith(f):
new_filename = r + original_filename[len(f):]
break
if self.debug and original_filename not in self.processed_paths:
if new_filename != original_filename:
self.msgout(2, "co_filename %r changed to %r" \
% (original_filename,new_filename,))
else:
self.msgout(2, "co_filename %r remains unchanged" \
% (original_filename,))
self.processed_paths.append(original_filename)
consts = list(co.co_consts)
for i in range(len(consts)):
if isinstance(consts[i], type(co)):
consts[i] = self.replace_paths_in_code(consts[i])
return types.CodeType(co.co_argcount, co.co_nlocals, co.co_stacksize,
co.co_flags, co.co_code, tuple(consts), co.co_names,
co.co_varnames, new_filename, co.co_name,
co.co_firstlineno, co.co_lnotab,
co.co_freevars, co.co_cellvars) | [
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CheckPointSW/Karta | b845928487b50a5b41acd532ae0399177a4356aa | src/thumbs_up/utils/switch_table.py | python | SwitchIdentifier.isSwitchCase | (self, ea) | return ea in self._switch_case_cases | Check if the given address is the beginning of a seen switch case.
Args:
ea (int): effective address to be checked
Return Value:
True iff the given address matches the beginning of a seen switch case | Check if the given address is the beginning of a seen switch case. | [
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] | def isSwitchCase(self, ea):
"""Check if the given address is the beginning of a seen switch case.
Args:
ea (int): effective address to be checked
Return Value:
True iff the given address matches the beginning of a seen switch case
"""
return ea in self._switch_case_cases | [
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sony/nnabla-examples | 068be490aacf73740502a1c3b10f8b2d15a52d32 | language-modeling/BERT-finetuning/external/processors.py | python | DataProcessor.get_dev_examples | (self, data_dir) | Gets a collection of `InputExample`s for the dev set. | Gets a collection of `InputExample`s for the dev set. | [
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"""Gets a collection of `InputExample`s for the dev set."""
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