body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
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def __init__(self, is_chief, num_ps_replicas, ensemble_handle, center_bias, examples_per_layer, learner_config, features, logits_dimension, loss_reduction=losses.Reduction.SUM_OVER_NONZERO_WEIGHTS, feature_columns=None, use_core_columns=False, output_leaf_index=False, output_leaf_index_modes=None, num_quantiles=100):
... | -1,757,462,702,641,173,800 | Construct a new GradientBoostedDecisionTreeModel function.
Args:
is_chief: Whether to build the chief graph.
num_ps_replicas: Number of parameter server replicas, can be 0.
ensemble_handle: A handle to the ensemble variable.
center_bias: Whether to center the bias before growing trees.
examples_per_layer: Nu... | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | __init__ | JustinACoder/H22-GR3-UnrealAI | python | def __init__(self, is_chief, num_ps_replicas, ensemble_handle, center_bias, examples_per_layer, learner_config, features, logits_dimension, loss_reduction=losses.Reduction.SUM_OVER_NONZERO_WEIGHTS, feature_columns=None, use_core_columns=False, output_leaf_index=False, output_leaf_index_modes=None, num_quantiles=100):
... |
def _predict_and_return_dict(self, ensemble_handle, ensemble_stamp, mode):
'Runs prediction and returns a dictionary of the prediction results.\n\n Args:\n ensemble_handle: ensemble resource handle.\n ensemble_stamp: stamp of ensemble resource.\n mode: learn.ModeKeys.TRAIN or EVAL or INFER.\n\n ... | 531,411,416,396,902,140 | Runs prediction and returns a dictionary of the prediction results.
Args:
ensemble_handle: ensemble resource handle.
ensemble_stamp: stamp of ensemble resource.
mode: learn.ModeKeys.TRAIN or EVAL or INFER.
Returns:
a dictionary of prediction results -
ENSEMBLE_STAMP, PREDICTION, PARTITION_IDS,
NUM_LAY... | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _predict_and_return_dict | JustinACoder/H22-GR3-UnrealAI | python | def _predict_and_return_dict(self, ensemble_handle, ensemble_stamp, mode):
'Runs prediction and returns a dictionary of the prediction results.\n\n Args:\n ensemble_handle: ensemble resource handle.\n ensemble_stamp: stamp of ensemble resource.\n mode: learn.ModeKeys.TRAIN or EVAL or INFER.\n\n ... |
def predict(self, mode):
'Returns predictions given the features and mode.\n\n Args:\n mode: Mode the graph is running in (train|predict|eval).\n\n Returns:\n A dict of predictions tensors.\n\n Raises:\n ValueError: if features is not valid.\n '
input_deps = ((self._dense_floats + sel... | 1,914,042,199,805,028,600 | Returns predictions given the features and mode.
Args:
mode: Mode the graph is running in (train|predict|eval).
Returns:
A dict of predictions tensors.
Raises:
ValueError: if features is not valid. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | predict | JustinACoder/H22-GR3-UnrealAI | python | def predict(self, mode):
'Returns predictions given the features and mode.\n\n Args:\n mode: Mode the graph is running in (train|predict|eval).\n\n Returns:\n A dict of predictions tensors.\n\n Raises:\n ValueError: if features is not valid.\n '
input_deps = ((self._dense_floats + sel... |
def update_stats(self, loss, predictions_dict):
'Update the accumulators with stats from this batch.\n\n Args:\n loss: A scalar tensor representing average loss of examples.\n predictions_dict: Dictionary of Rank 2 `Tensor` representing information\n about predictions per example.\n\n Retur... | -2,046,874,659,883,087,400 | Update the accumulators with stats from this batch.
Args:
loss: A scalar tensor representing average loss of examples.
predictions_dict: Dictionary of Rank 2 `Tensor` representing information
about predictions per example.
Returns:
Three values:
- An op that adds a new tree to the ensemble, and
- ... | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | update_stats | JustinACoder/H22-GR3-UnrealAI | python | def update_stats(self, loss, predictions_dict):
'Update the accumulators with stats from this batch.\n\n Args:\n loss: A scalar tensor representing average loss of examples.\n predictions_dict: Dictionary of Rank 2 `Tensor` representing information\n about predictions per example.\n\n Retur... |
def increment_step_counter_and_maybe_update_ensemble(self, predictions_dict, training_state):
'Increments number of visited examples and grows the ensemble.\n\n If the number of visited examples reaches the target examples_per_layer,\n ensemble is updated.\n\n Args:\n predictions_dict: Dictionary of R... | 1,781,436,108,389,791,700 | Increments number of visited examples and grows the ensemble.
If the number of visited examples reaches the target examples_per_layer,
ensemble is updated.
Args:
predictions_dict: Dictionary of Rank 2 `Tensor` representing information
about predictions per example.
training_state: `dict` returned by update_... | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | increment_step_counter_and_maybe_update_ensemble | JustinACoder/H22-GR3-UnrealAI | python | def increment_step_counter_and_maybe_update_ensemble(self, predictions_dict, training_state):
'Increments number of visited examples and grows the ensemble.\n\n If the number of visited examples reaches the target examples_per_layer,\n ensemble is updated.\n\n Args:\n predictions_dict: Dictionary of R... |
def make_update_ensemble_fn(self, ensemble_stamp, training_state, dropout_seed, class_id):
'A method to create the function which updates the tree ensemble.'
learning_rate_tuner = self._learner_config.learning_rate_tuner.WhichOneof('tuner')
if ((learning_rate_tuner == 'fixed') or (learning_rate_tuner == 'dr... | -8,148,777,286,915,548,000 | A method to create the function which updates the tree ensemble. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | make_update_ensemble_fn | JustinACoder/H22-GR3-UnrealAI | python | def make_update_ensemble_fn(self, ensemble_stamp, training_state, dropout_seed, class_id):
learning_rate_tuner = self._learner_config.learning_rate_tuner.WhichOneof('tuner')
if ((learning_rate_tuner == 'fixed') or (learning_rate_tuner == 'dropout')):
tuner = getattr(self._learner_config.learning_ra... |
def train(self, loss, predictions_dict, labels):
'Updates the accumalator stats and grows the ensemble.\n\n Args:\n loss: A scalar tensor representing average loss of examples.\n predictions_dict: Dictionary of Rank 2 `Tensor` representing information\n about predictions per example.\n la... | -7,892,417,426,828,169,000 | Updates the accumalator stats and grows the ensemble.
Args:
loss: A scalar tensor representing average loss of examples.
predictions_dict: Dictionary of Rank 2 `Tensor` representing information
about predictions per example.
labels: Rank 2 `Tensor` representing labels per example. Has no effect
on th... | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | train | JustinACoder/H22-GR3-UnrealAI | python | def train(self, loss, predictions_dict, labels):
'Updates the accumalator stats and grows the ensemble.\n\n Args:\n loss: A scalar tensor representing average loss of examples.\n predictions_dict: Dictionary of Rank 2 `Tensor` representing information\n about predictions per example.\n la... |
def _get_weights(self, hessian_shape, hessians):
'Derives weights to be used based on hessians and multiclass strategy.'
if (hessian_shape == tensor_shape.scalar()):
weights = hessians
elif (len(hessian_shape.dims) == 1):
weights = math_ops.reduce_sum(hessians, axis=1)
else:
weig... | 4,915,859,988,237,479,000 | Derives weights to be used based on hessians and multiclass strategy. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _get_weights | JustinACoder/H22-GR3-UnrealAI | python | def _get_weights(self, hessian_shape, hessians):
if (hessian_shape == tensor_shape.scalar()):
weights = hessians
elif (len(hessian_shape.dims) == 1):
weights = math_ops.reduce_sum(hessians, axis=1)
else:
weights = math_ops.trace(hessians)
return weights |
def _full_hessian(self, grads, predictions):
'Prepares hessians for full-hessian multiclass strategy.'
gradients_list = array_ops.unstack(grads, num=self._logits_dimension, axis=1)
hessian_rows = []
for row in range(self._logits_dimension):
hessian_row = gradients_impl.gradients(gradients_list[r... | -7,186,014,364,833,011,000 | Prepares hessians for full-hessian multiclass strategy. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _full_hessian | JustinACoder/H22-GR3-UnrealAI | python | def _full_hessian(self, grads, predictions):
gradients_list = array_ops.unstack(grads, num=self._logits_dimension, axis=1)
hessian_rows = []
for row in range(self._logits_dimension):
hessian_row = gradients_impl.gradients(gradients_list[row], predictions, name=('Hessian_%d' % row), colocate_gra... |
def _diagonal_hessian(self, grads, predictions):
'Prepares hessians for diagonal-hessian multiclass mode.'
diag_hessian_list = []
gradients_list = array_ops.unstack(grads, num=self._logits_dimension, axis=1)
for (row, row_grads) in enumerate(gradients_list):
hessian_row = gradients_impl.gradient... | 4,202,547,455,968,546,300 | Prepares hessians for diagonal-hessian multiclass mode. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _diagonal_hessian | JustinACoder/H22-GR3-UnrealAI | python | def _diagonal_hessian(self, grads, predictions):
diag_hessian_list = []
gradients_list = array_ops.unstack(grads, num=self._logits_dimension, axis=1)
for (row, row_grads) in enumerate(gradients_list):
hessian_row = gradients_impl.gradients(row_grads, predictions, name=('Hessian_%d' % row), colo... |
def _get_replica_device_setter(self, worker_device):
'Creates a replica device setter.'
ps_tasks = self._num_ps_replicas
ps_ops = ['Variable', 'VariableV2', 'DecisionTreeEnsembleResourceHandleOp', 'StatsAccumulatorScalarResourceHandleOp', 'StatsAccumulatorTensorResourceHandleOp']
ps_strategy = _OpRoundR... | 501,583,640,530,627,840 | Creates a replica device setter. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _get_replica_device_setter | JustinACoder/H22-GR3-UnrealAI | python | def _get_replica_device_setter(self, worker_device):
ps_tasks = self._num_ps_replicas
ps_ops = ['Variable', 'VariableV2', 'DecisionTreeEnsembleResourceHandleOp', 'StatsAccumulatorScalarResourceHandleOp', 'StatsAccumulatorTensorResourceHandleOp']
ps_strategy = _OpRoundRobinStrategy(ps_ops, ps_tasks)
... |
def _make_update_bias_stats_fn(self, ensemble_stamp, predictions, gradients, bias_stats_accumulator):
'A method to create the function which updates the bias stats.'
def _update_bias_stats():
'A method to update the bias stats.'
grads_sum = math_ops.reduce_sum(gradients, 0)
hess = gradi... | -705,706,515,454,461,800 | A method to create the function which updates the bias stats. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _make_update_bias_stats_fn | JustinACoder/H22-GR3-UnrealAI | python | def _make_update_bias_stats_fn(self, ensemble_stamp, predictions, gradients, bias_stats_accumulator):
def _update_bias_stats():
'A method to update the bias stats.'
grads_sum = math_ops.reduce_sum(gradients, 0)
hess = gradients_impl.gradients(grads_sum, predictions, name='Hessians', co... |
def _update_ensemble():
'A method to update the tree ensemble.'
next_ensemble_stamp = (ensemble_stamp + 1)
(_, _, _, bias_grads, bias_hess) = training_state.bias_stats_accumulator.flush(ensemble_stamp, next_ensemble_stamp)
are_splits_ready_list = []
partition_ids_list = []
gains_list = []
sp... | -781,230,400,113,602,400 | A method to update the tree ensemble. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _update_ensemble | JustinACoder/H22-GR3-UnrealAI | python | def _update_ensemble():
next_ensemble_stamp = (ensemble_stamp + 1)
(_, _, _, bias_grads, bias_hess) = training_state.bias_stats_accumulator.flush(ensemble_stamp, next_ensemble_stamp)
are_splits_ready_list = []
partition_ids_list = []
gains_list = []
split_info_list = []
for handler in t... |
def _update_bias_stats():
'A method to update the bias stats.'
grads_sum = math_ops.reduce_sum(gradients, 0)
hess = gradients_impl.gradients(grads_sum, predictions, name='Hessians', colocate_gradients_with_ops=False, gate_gradients=0, aggregation_method=None)[0]
hess_sum = math_ops.reduce_sum(hess, 0)
... | -5,184,848,394,841,910,000 | A method to update the bias stats. | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/contrib/boosted_trees/python/training/functions/gbdt_batch.py | _update_bias_stats | JustinACoder/H22-GR3-UnrealAI | python | def _update_bias_stats():
grads_sum = math_ops.reduce_sum(gradients, 0)
hess = gradients_impl.gradients(grads_sum, predictions, name='Hessians', colocate_gradients_with_ops=False, gate_gradients=0, aggregation_method=None)[0]
hess_sum = math_ops.reduce_sum(hess, 0)
partition_ids = math_ops.range(se... |
def __init__(self, transfer_id=None):
'UpdateIndirectPartnerAccountResponse - a model defined in huaweicloud sdk'
super().__init__()
self._transfer_id = None
self.discriminator = None
if (transfer_id is not None):
self.transfer_id = transfer_id | 8,037,283,255,066,327,000 | UpdateIndirectPartnerAccountResponse - a model defined in huaweicloud sdk | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | __init__ | Lencof/huaweicloud-sdk-python-v3 | python | def __init__(self, transfer_id=None):
super().__init__()
self._transfer_id = None
self.discriminator = None
if (transfer_id is not None):
self.transfer_id = transfer_id |
@property
def transfer_id(self):
'Gets the transfer_id of this UpdateIndirectPartnerAccountResponse.\n\n 事务流水ID，只有成功响应才会返回。\n\n :return: The transfer_id of this UpdateIndirectPartnerAccountResponse.\n :rtype: str\n '
return self._transfer_id | -3,009,237,835,561,159,700 | Gets the transfer_id of this UpdateIndirectPartnerAccountResponse.
事务流水ID，只有成功响应才会返回。
:return: The transfer_id of this UpdateIndirectPartnerAccountResponse.
:rtype: str | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | transfer_id | Lencof/huaweicloud-sdk-python-v3 | python | @property
def transfer_id(self):
'Gets the transfer_id of this UpdateIndirectPartnerAccountResponse.\n\n 事务流水ID，只有成功响应才会返回。\n\n :return: The transfer_id of this UpdateIndirectPartnerAccountResponse.\n :rtype: str\n '
return self._transfer_id |
@transfer_id.setter
def transfer_id(self, transfer_id):
'Sets the transfer_id of this UpdateIndirectPartnerAccountResponse.\n\n 事务流水ID，只有成功响应才会返回。\n\n :param transfer_id: The transfer_id of this UpdateIndirectPartnerAccountResponse.\n :type: str\n '
self._transfer_id = transfer_id | 3,366,307,169,122,716,000 | Sets the transfer_id of this UpdateIndirectPartnerAccountResponse.
事务流水ID，只有成功响应才会返回。
:param transfer_id: The transfer_id of this UpdateIndirectPartnerAccountResponse.
:type: str | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | transfer_id | Lencof/huaweicloud-sdk-python-v3 | python | @transfer_id.setter
def transfer_id(self, transfer_id):
'Sets the transfer_id of this UpdateIndirectPartnerAccountResponse.\n\n 事务流水ID，只有成功响应才会返回。\n\n :param transfer_id: The transfer_id of this UpdateIndirectPartnerAccountResponse.\n :type: str\n '
self._transfer_id = transfer_id |
def to_dict(self):
'Returns the model properties as a dict'
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
e... | 2,594,216,033,120,720,000 | Returns the model properties as a dict | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | to_dict | Lencof/huaweicloud-sdk-python-v3 | python | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
... |
def to_str(self):
'Returns the string representation of the model'
return pprint.pformat(self.to_dict()) | 5,849,158,643,760,736,000 | Returns the string representation of the model | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | to_str | Lencof/huaweicloud-sdk-python-v3 | python | def to_str(self):
return pprint.pformat(self.to_dict()) |
def __repr__(self):
'For `print` and `pprint`'
return self.to_str() | -8,960,031,694,814,905,000 | For `print` and `pprint` | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | __repr__ | Lencof/huaweicloud-sdk-python-v3 | python | def __repr__(self):
return self.to_str() |
def __eq__(self, other):
'Returns true if both objects are equal'
if (not isinstance(other, UpdateIndirectPartnerAccountResponse)):
return False
return (self.__dict__ == other.__dict__) | -5,450,993,162,929,922,000 | Returns true if both objects are equal | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | __eq__ | Lencof/huaweicloud-sdk-python-v3 | python | def __eq__(self, other):
if (not isinstance(other, UpdateIndirectPartnerAccountResponse)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'Returns true if both objects are not equal'
return (not (self == other)) | 7,764,124,047,908,058,000 | Returns true if both objects are not equal | huaweicloud-sdk-bss/huaweicloudsdkbss/v2/model/update_indirect_partner_account_response.py | __ne__ | Lencof/huaweicloud-sdk-python-v3 | python | def __ne__(self, other):
return (not (self == other)) |
def set_segment_redundancy(alarm):
'\n Set lost_redundancy to segment when redundant object is down\n :param alarm:\n :return:\n '
if alarm.root:
return
mo = alarm.managed_object
seg = mo.segment
if (seg.is_redundant and (not seg.lost_redundancy)):
u = mo.data.uplinks
... | 4,618,587,306,445,554,000 | Set lost_redundancy to segment when redundant object is down
:param alarm:
:return: | fm/handlers/alarm/segment.py | set_segment_redundancy | sbworth/getnoc | python | def set_segment_redundancy(alarm):
'\n Set lost_redundancy to segment when redundant object is down\n :param alarm:\n :return:\n '
if alarm.root:
return
mo = alarm.managed_object
seg = mo.segment
if (seg.is_redundant and (not seg.lost_redundancy)):
u = mo.data.uplinks
... |
def check_segment_redundancy(alarm):
'\n Reset lost_redundancy from segment when all redundant objects\n are up\n :param alarm:\n :return:\n '
mo = alarm.managed_object
seg = mo.segment
if ((not seg.is_redundant) or (not seg.lost_redundancy)):
return
u = mo.data.uplinks
if... | 5,985,817,990,810,562,000 | Reset lost_redundancy from segment when all redundant objects
are up
:param alarm:
:return: | fm/handlers/alarm/segment.py | check_segment_redundancy | sbworth/getnoc | python | def check_segment_redundancy(alarm):
'\n Reset lost_redundancy from segment when all redundant objects\n are up\n :param alarm:\n :return:\n '
mo = alarm.managed_object
seg = mo.segment
if ((not seg.is_redundant) or (not seg.lost_redundancy)):
return
u = mo.data.uplinks
if... |
def decompose(S, n_components=None, transformer=None, sort=False, fit=True, **kwargs):
"Decompose a feature matrix.\n\n Given a spectrogram `S`, produce a decomposition into `components`\n and `activations` such that `S ~= components.dot(activations)`.\n\n By default, this is done with with non-negative ma... | -4,230,850,838,342,372,400 | Decompose a feature matrix.
Given a spectrogram `S`, produce a decomposition into `components`
and `activations` such that `S ~= components.dot(activations)`.
By default, this is done with with non-negative matrix factorization (NMF),
but any `sklearn.decomposition`-type object will work.
Parameters
----------
S : ... | librosa/decompose.py | decompose | ElisaIzrailova/librosa | python | def decompose(S, n_components=None, transformer=None, sort=False, fit=True, **kwargs):
"Decompose a feature matrix.\n\n Given a spectrogram `S`, produce a decomposition into `components`\n and `activations` such that `S ~= components.dot(activations)`.\n\n By default, this is done with with non-negative ma... |
@cache(level=30)
def hpss(S, kernel_size=31, power=2.0, mask=False, margin=1.0):
'Median-filtering harmonic percussive source separation (HPSS).\n\n If `margin = 1.0`, decomposes an input spectrogram `S = H + P`\n where `H` contains the harmonic components,\n and `P` contains the percussive components.\n\n... | -601,029,398,121,857,800 | Median-filtering harmonic percussive source separation (HPSS).
If `margin = 1.0`, decomposes an input spectrogram `S = H + P`
where `H` contains the harmonic components,
and `P` contains the percussive components.
If `margin > 1.0`, decomposes an input spectrogram `S = H + P + R`
where `R` contains residual component... | librosa/decompose.py | hpss | ElisaIzrailova/librosa | python | @cache(level=30)
def hpss(S, kernel_size=31, power=2.0, mask=False, margin=1.0):
'Median-filtering harmonic percussive source separation (HPSS).\n\n If `margin = 1.0`, decomposes an input spectrogram `S = H + P`\n where `H` contains the harmonic components,\n and `P` contains the percussive components.\n\n... |
@cache(level=30)
def nn_filter(S, rec=None, aggregate=None, axis=(- 1), **kwargs):
'Filtering by nearest-neighbors.\n\n Each data point (e.g, spectrogram column) is replaced\n by aggregating its nearest neighbors in feature space.\n\n This can be useful for de-noising a spectrogram or feature matrix.\n\n ... | 6,552,659,050,913,915,000 | Filtering by nearest-neighbors.
Each data point (e.g, spectrogram column) is replaced
by aggregating its nearest neighbors in feature space.
This can be useful for de-noising a spectrogram or feature matrix.
The non-local means method [1]_ can be recovered by providing a
weighted recurrence matrix as input and speci... | librosa/decompose.py | nn_filter | ElisaIzrailova/librosa | python | @cache(level=30)
def nn_filter(S, rec=None, aggregate=None, axis=(- 1), **kwargs):
'Filtering by nearest-neighbors.\n\n Each data point (e.g, spectrogram column) is replaced\n by aggregating its nearest neighbors in feature space.\n\n This can be useful for de-noising a spectrogram or feature matrix.\n\n ... |
def __nn_filter_helper(R_data, R_indices, R_ptr, S, aggregate):
'Nearest-neighbor filter helper function.\n\n This is an internal function, not for use outside of the decompose module.\n\n It applies the nearest-neighbor filter to S, assuming that the first index\n corresponds to observations.\n\n Param... | 8,874,733,337,976,750,000 | Nearest-neighbor filter helper function.
This is an internal function, not for use outside of the decompose module.
It applies the nearest-neighbor filter to S, assuming that the first index
corresponds to observations.
Parameters
----------
R_data, R_indices, R_ptr : np.ndarrays
The `data`, `indices`, and `indp... | librosa/decompose.py | __nn_filter_helper | ElisaIzrailova/librosa | python | def __nn_filter_helper(R_data, R_indices, R_ptr, S, aggregate):
'Nearest-neighbor filter helper function.\n\n This is an internal function, not for use outside of the decompose module.\n\n It applies the nearest-neighbor filter to S, assuming that the first index\n corresponds to observations.\n\n Param... |
def __init__(self, *args, **kwds):
'\n Constructor. Any message fields that are implicitly/explicitly\n set to None will be assigned a default value. The recommend\n use is keyword arguments as this is more robust to future message\n changes. You cannot mix in-order arguments and keyword arguments.\n\n... | 3,792,384,007,490,749,000 | Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
The available fields are:
model_name,joint_trajectory,model_... | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | __init__ | Filipe-Douglas-Slam/slam_lidar_kinect | python | def __init__(self, *args, **kwds):
'\n Constructor. Any message fields that are implicitly/explicitly\n set to None will be assigned a default value. The recommend\n use is keyword arguments as this is more robust to future message\n changes. You cannot mix in-order arguments and keyword arguments.\n\n... |
def _get_types(self):
'\n internal API method\n '
return self._slot_types | 840,424,092,067,405,300 | internal API method | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | _get_types | Filipe-Douglas-Slam/slam_lidar_kinect | python | def _get_types(self):
'\n \n '
return self._slot_types |
def serialize(self, buff):
'\n serialize message into buffer\n :param buff: buffer, ``StringIO``\n '
try:
_x = self.model_name
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.encode('utf-8')
length = len(_x)
buff.write(struct.pack(... | 8,435,202,572,428,503,000 | serialize message into buffer
:param buff: buffer, ``StringIO`` | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | serialize | Filipe-Douglas-Slam/slam_lidar_kinect | python | def serialize(self, buff):
'\n serialize message into buffer\n :param buff: buffer, ``StringIO``\n '
try:
_x = self.model_name
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.encode('utf-8')
length = len(_x)
buff.write(struct.pack(... |
def deserialize(self, str):
'\n unpack serialized message in str into this message instance\n :param str: byte array of serialized message, ``str``\n '
try:
if (self.joint_trajectory is None):
self.joint_trajectory = trajectory_msgs.msg.JointTrajectory()
if (self.model_pose ... | 71,315,805,887,924,400 | unpack serialized message in str into this message instance
:param str: byte array of serialized message, ``str`` | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | deserialize | Filipe-Douglas-Slam/slam_lidar_kinect | python | def deserialize(self, str):
'\n unpack serialized message in str into this message instance\n :param str: byte array of serialized message, ``str``\n '
try:
if (self.joint_trajectory is None):
self.joint_trajectory = trajectory_msgs.msg.JointTrajectory()
if (self.model_pose ... |
def serialize_numpy(self, buff, numpy):
'\n serialize message with numpy array types into buffer\n :param buff: buffer, ``StringIO``\n :param numpy: numpy python module\n '
try:
_x = self.model_name
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.e... | -8,851,787,001,122,039,000 | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | serialize_numpy | Filipe-Douglas-Slam/slam_lidar_kinect | python | def serialize_numpy(self, buff, numpy):
'\n serialize message with numpy array types into buffer\n :param buff: buffer, ``StringIO``\n :param numpy: numpy python module\n '
try:
_x = self.model_name
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.e... |
def deserialize_numpy(self, str, numpy):
'\n unpack serialized message in str into this message instance using numpy for array types\n :param str: byte array of serialized message, ``str``\n :param numpy: numpy python module\n '
try:
if (self.joint_trajectory is None):
self.joint... | 1,277,172,783,877,668,600 | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | deserialize_numpy | Filipe-Douglas-Slam/slam_lidar_kinect | python | def deserialize_numpy(self, str, numpy):
'\n unpack serialized message in str into this message instance using numpy for array types\n :param str: byte array of serialized message, ``str``\n :param numpy: numpy python module\n '
try:
if (self.joint_trajectory is None):
self.joint... |
def __init__(self, *args, **kwds):
'\n Constructor. Any message fields that are implicitly/explicitly\n set to None will be assigned a default value. The recommend\n use is keyword arguments as this is more robust to future message\n changes. You cannot mix in-order arguments and keyword arguments.\n\n... | -2,537,933,800,810,868,700 | Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
The available fields are:
success,status_message
:param arg... | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | __init__ | Filipe-Douglas-Slam/slam_lidar_kinect | python | def __init__(self, *args, **kwds):
'\n Constructor. Any message fields that are implicitly/explicitly\n set to None will be assigned a default value. The recommend\n use is keyword arguments as this is more robust to future message\n changes. You cannot mix in-order arguments and keyword arguments.\n\n... |
def _get_types(self):
'\n internal API method\n '
return self._slot_types | 840,424,092,067,405,300 | internal API method | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | _get_types | Filipe-Douglas-Slam/slam_lidar_kinect | python | def _get_types(self):
'\n \n '
return self._slot_types |
def serialize(self, buff):
'\n serialize message into buffer\n :param buff: buffer, ``StringIO``\n '
try:
buff.write(_get_struct_B().pack(self.success))
_x = self.status_message
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.encode('utf-8')
... | 4,799,889,647,904,635,000 | serialize message into buffer
:param buff: buffer, ``StringIO`` | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | serialize | Filipe-Douglas-Slam/slam_lidar_kinect | python | def serialize(self, buff):
'\n serialize message into buffer\n :param buff: buffer, ``StringIO``\n '
try:
buff.write(_get_struct_B().pack(self.success))
_x = self.status_message
length = len(_x)
if (python3 or (type(_x) == unicode)):
_x = _x.encode('utf-8')
... |
def deserialize(self, str):
'\n unpack serialized message in str into this message instance\n :param str: byte array of serialized message, ``str``\n '
try:
end = 0
start = end
end += 1
(self.success,) = _get_struct_B().unpack(str[start:end])
self.success = bool(... | -5,420,559,687,702,289,000 | unpack serialized message in str into this message instance
:param str: byte array of serialized message, ``str`` | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | deserialize | Filipe-Douglas-Slam/slam_lidar_kinect | python | def deserialize(self, str):
'\n unpack serialized message in str into this message instance\n :param str: byte array of serialized message, ``str``\n '
try:
end = 0
start = end
end += 1
(self.success,) = _get_struct_B().unpack(str[start:end])
self.success = bool(... |
def serialize_numpy(self, buff, numpy):
'\n serialize message with numpy array types into buffer\n :param buff: buffer, ``StringIO``\n :param numpy: numpy python module\n '
try:
buff.write(_get_struct_B().pack(self.success))
_x = self.status_message
length = len(_x)
i... | -4,722,480,347,249,835,000 | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | serialize_numpy | Filipe-Douglas-Slam/slam_lidar_kinect | python | def serialize_numpy(self, buff, numpy):
'\n serialize message with numpy array types into buffer\n :param buff: buffer, ``StringIO``\n :param numpy: numpy python module\n '
try:
buff.write(_get_struct_B().pack(self.success))
_x = self.status_message
length = len(_x)
i... |
def deserialize_numpy(self, str, numpy):
'\n unpack serialized message in str into this message instance using numpy for array types\n :param str: byte array of serialized message, ``str``\n :param numpy: numpy python module\n '
try:
end = 0
start = end
end += 1
(self... | -8,541,184,696,130,646,000 | unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module | files/catkin_ws/devel/lib/python2.7/dist-packages/gazebo_msgs/srv/_SetJointTrajectory.py | deserialize_numpy | Filipe-Douglas-Slam/slam_lidar_kinect | python | def deserialize_numpy(self, str, numpy):
'\n unpack serialized message in str into this message instance using numpy for array types\n :param str: byte array of serialized message, ``str``\n :param numpy: numpy python module\n '
try:
end = 0
start = end
end += 1
(self... |
def onehot_encode_seq(sequence, m=0, padding=False):
'Converts a given IUPAC DNA sequence to a one-hot \n encoded DNA sequence. \n '
import numpy as np
import torch
valid_keys = ['a', 'c', 'g', 't', 'u', 'n', 'r', 'y', 's', 'w', 'k', 'm']
nucs = {'a': 0, 'c': 1, 'g': 2, 't': 3, 'u': 3}
if ... | 4,279,557,635,030,340,600 | Converts a given IUPAC DNA sequence to a one-hot
encoded DNA sequence. | bin/scover_utils.py | onehot_encode_seq | jacobhepkema/scover | python | def onehot_encode_seq(sequence, m=0, padding=False):
'Converts a given IUPAC DNA sequence to a one-hot \n encoded DNA sequence. \n '
import numpy as np
import torch
valid_keys = ['a', 'c', 'g', 't', 'u', 'n', 'r', 'y', 's', 'w', 'k', 'm']
nucs = {'a': 0, 'c': 1, 'g': 2, 't': 3, 'u': 3}
if ... |
def save_meme(motifs_ppm_dict, output_file='found_motifs.meme'):
"Saves the found PPMs (given as dictionary) to a file that's\n compatible with MEME suite applications.\n "
import pandas as pd
meme_string = ['MEME version 4', '', 'ALPHABET= ACGT', '', 'strands: + -', '']
for (idx, key) in enumerat... | -4,665,332,980,607,600,000 | Saves the found PPMs (given as dictionary) to a file that's
compatible with MEME suite applications. | bin/scover_utils.py | save_meme | jacobhepkema/scover | python | def save_meme(motifs_ppm_dict, output_file='found_motifs.meme'):
"Saves the found PPMs (given as dictionary) to a file that's\n compatible with MEME suite applications.\n "
import pandas as pd
meme_string = ['MEME version 4', , 'ALPHABET= ACGT', , 'strands: + -', ]
for (idx, key) in enumerate(moti... |
def align_conv_filters(model, input_seqs, m, train_ind):
'Aligns the convolutional filters of a given scover model back\n to the given input sequences at the given indices. \n '
import numpy as np
import torch
from tqdm import trange
activation_seqs = input_seqs[train_ind]
with torch.no_gr... | 611,642,633,021,770,500 | Aligns the convolutional filters of a given scover model back
to the given input sequences at the given indices. | bin/scover_utils.py | align_conv_filters | jacobhepkema/scover | python | def align_conv_filters(model, input_seqs, m, train_ind):
'Aligns the convolutional filters of a given scover model back\n to the given input sequences at the given indices. \n '
import numpy as np
import torch
from tqdm import trange
activation_seqs = input_seqs[train_ind]
with torch.no_gr... |
def randomize_sequences(sequences):
'Randomly permutes a set of DNA sequences.\n '
import random
shuffled_seqs = []
for seq in sequences:
shuffled_seqs.append(''.join(random.sample(seq, len(seq))))
return shuffled_seqs | 5,263,260,572,859,589,000 | Randomly permutes a set of DNA sequences. | bin/scover_utils.py | randomize_sequences | jacobhepkema/scover | python | def randomize_sequences(sequences):
'\n '
import random
shuffled_seqs = []
for seq in sequences:
shuffled_seqs.append(.join(random.sample(seq, len(seq))))
return shuffled_seqs |
def check_response_errors(response, session):
'\n Checks status of response response and throws appropriate error.\n '
if (response['status'] != 'ok'):
from wi.utils.auth import logout
error_code = response['status']
error_msg = get_error(error_code)
raise RestErrorExceptio... | -1,008,439,569,765,546,400 | Checks status of response response and throws appropriate error. | src/wi/utils/__init__.py | check_response_errors | cc1-cloud/cc1 | python | def check_response_errors(response, session):
'\n \n '
if (response['status'] != 'ok'):
from wi.utils.auth import logout
error_code = response['status']
error_msg = get_error(error_code)
raise RestErrorException(error_msg)
return response |
def get_dict_from_list(list_of_dicts, key_value, key='id'):
'\n Returns dictionary with key: @prm{key} equal to @prm{key_value} from a\n list of dictionaries: @prm{list_of_dicts}.\n '
for dictionary in list_of_dicts:
if (dictionary.get(key) == None):
raise Exception((('No key: ' + k... | -5,721,012,959,760,796,000 | Returns dictionary with key: @prm{key} equal to @prm{key_value} from a
list of dictionaries: @prm{list_of_dicts}. | src/wi/utils/__init__.py | get_dict_from_list | cc1-cloud/cc1 | python | def get_dict_from_list(list_of_dicts, key_value, key='id'):
'\n Returns dictionary with key: @prm{key} equal to @prm{key_value} from a\n list of dictionaries: @prm{list_of_dicts}.\n '
for dictionary in list_of_dicts:
if (dictionary.get(key) == None):
raise Exception((('No key: ' + k... |
def get_dicts_from_list(list_of_dicts, list_of_key_values, key='id'):
'\n Returns list of dictionaries with keys: @prm{key} equal to one from list\n @prm{list_of_key_values} from a list of dictionaries: @prm{list_of_dicts}.\n '
ret = []
for dictionary in list_of_dicts:
if (dictionary.get(ke... | -8,346,077,972,838,045,000 | Returns list of dictionaries with keys: @prm{key} equal to one from list
@prm{list_of_key_values} from a list of dictionaries: @prm{list_of_dicts}. | src/wi/utils/__init__.py | get_dicts_from_list | cc1-cloud/cc1 | python | def get_dicts_from_list(list_of_dicts, list_of_key_values, key='id'):
'\n Returns list of dictionaries with keys: @prm{key} equal to one from list\n @prm{list_of_key_values} from a list of dictionaries: @prm{list_of_dicts}.\n '
ret = []
for dictionary in list_of_dicts:
if (dictionary.get(ke... |
def ParseOption():
'Parse command line options.'
parser = optparse.OptionParser()
parser.add_option('--qtdir', dest='qtdir')
parser.add_option('--target', dest='target')
(opts, _) = parser.parse_args()
return opts | 4,984,111,987,636,987,000 | Parse command line options. | src/build_tools/change_reference_mac.py | ParseOption | dancerj/mozc | python | def ParseOption():
parser = optparse.OptionParser()
parser.add_option('--qtdir', dest='qtdir')
parser.add_option('--target', dest='target')
(opts, _) = parser.parse_args()
return opts |
def fix(val):
'strip off _: from nodeIDs... as they are not valid NCNames'
if val.startswith('_:'):
return val[2:]
else:
return val | -7,506,203,427,036,628,000 | strip off _: from nodeIDs... as they are not valid NCNames | rdflib/plugins/serializers/rdfxml.py | fix | GreenfishK/rdflib | python | def fix(val):
if val.startswith('_:'):
return val[2:]
else:
return val |
def dmsp_map_interpolate_NN_smooth_great_circle(lat_dmsp, lon_dmsp, lat_map, lon_map, Obs_map, k=5, tol=1.5):
'\n generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance\n '
tol = np.deg2rad(tol)
dmsp_points = np.deg2rad(np.hstack((la... | -6,599,027,326,757,895,000 | generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance | LBH_to_eflux/helper_funcs.py | dmsp_map_interpolate_NN_smooth_great_circle | jali7001/LBH_to_E_flux | python | def dmsp_map_interpolate_NN_smooth_great_circle(lat_dmsp, lon_dmsp, lat_map, lon_map, Obs_map, k=5, tol=1.5):
'\n \n '
tol = np.deg2rad(tol)
dmsp_points = np.deg2rad(np.hstack((lat_dmsp.flatten().reshape((- 1), 1), lon_dmsp.flatten().reshape((- 1), 1))))
map_points = np.deg2rad(np.hstack((lat_map.... |
def latlt2polar(lat, lt, hemisphere):
'\n Converts an array of latitude and lt points to polar for a top-down dialplot (latitude in degrees, LT in hours)\n i.e. makes latitude the radial quantity and MLT the azimuthal \n\n get the radial displacement (referenced to down from northern pole if we want to do ... | -7,718,299,923,529,573,000 | Converts an array of latitude and lt points to polar for a top-down dialplot (latitude in degrees, LT in hours)
i.e. makes latitude the radial quantity and MLT the azimuthal
get the radial displacement (referenced to down from northern pole if we want to do a top down on the north,
or up from south pole if visa-vers... | LBH_to_eflux/helper_funcs.py | latlt2polar | jali7001/LBH_to_E_flux | python | def latlt2polar(lat, lt, hemisphere):
'\n Converts an array of latitude and lt points to polar for a top-down dialplot (latitude in degrees, LT in hours)\n i.e. makes latitude the radial quantity and MLT the azimuthal \n\n get the radial displacement (referenced to down from northern pole if we want to do ... |
def polar2dial(ax):
'\n Turns a matplotlib axes polar plot into a dial plot\n '
ax.set_theta_zero_location('S')
theta_label_values = ((np.array([0.0, 3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0]) * 180.0) / 12)
theta_labels = [('%d:00' % int(((th / 180.0) * 12))) for th in theta_label_values.flatten().t... | 4,135,101,090,055,548,400 | Turns a matplotlib axes polar plot into a dial plot | LBH_to_eflux/helper_funcs.py | polar2dial | jali7001/LBH_to_E_flux | python | def polar2dial(ax):
'\n \n '
ax.set_theta_zero_location('S')
theta_label_values = ((np.array([0.0, 3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0]) * 180.0) / 12)
theta_labels = [('%d:00' % int(((th / 180.0) * 12))) for th in theta_label_values.flatten().tolist()]
ax.set_thetagrids(theta_label_values, ... |
def dmsp_map_interpolate(X_dmsp, Y_dmsp, X_map, Y_map, tolerance=0.5):
'\n generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance\n '
indices = scipy.interpolate.griddata((X_map, Y_map), np.arange(len(X_map.flatten())), (X_dmsp, Y_dmsp),... | 2,021,138,743,614,363,400 | generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance | LBH_to_eflux/helper_funcs.py | dmsp_map_interpolate | jali7001/LBH_to_E_flux | python | def dmsp_map_interpolate(X_dmsp, Y_dmsp, X_map, Y_map, tolerance=0.5):
'\n \n '
indices = scipy.interpolate.griddata((X_map, Y_map), np.arange(len(X_map.flatten())), (X_dmsp, Y_dmsp), method='nearest')
mask = ((abs((X_map[indices] - X_dmsp)) < tolerance) & (abs((Y_map[indices] - Y_dmsp)) < tolerance))... |
def dmsp_map_interpolate_NN_smooth(X_dmsp, Y_dmsp, X_map, Y_map, Obs_map, k=5, tol=3):
'\n generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance\n '
dmsp_points = np.hstack((X_dmsp.flatten().reshape((- 1), 1), Y_dmsp.flatten().reshape((... | 9,011,506,937,454,772,000 | generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance | LBH_to_eflux/helper_funcs.py | dmsp_map_interpolate_NN_smooth | jali7001/LBH_to_E_flux | python | def dmsp_map_interpolate_NN_smooth(X_dmsp, Y_dmsp, X_map, Y_map, Obs_map, k=5, tol=3):
'\n \n '
dmsp_points = np.hstack((X_dmsp.flatten().reshape((- 1), 1), Y_dmsp.flatten().reshape((- 1), 1)))
map_points = np.hstack((X_map.flatten().reshape((- 1), 1), Y_map.flatten().reshape((- 1), 1)))
N_points ... |
def dmsp_map_interpolate_NN_smooth_great_circle(lat_dmsp, lon_dmsp, lat_map, lon_map, Obs_map, k=5, tol=1.5):
'\n generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance\n '
tol = np.deg2rad(tol)
dmsp_points = np.deg2rad(np.hstack((la... | -6,599,027,326,757,895,000 | generic function to spatially interpolate with the SSJ data using nearest neighbors using some arbirtary distance tolerance | LBH_to_eflux/helper_funcs.py | dmsp_map_interpolate_NN_smooth_great_circle | jali7001/LBH_to_E_flux | python | def dmsp_map_interpolate_NN_smooth_great_circle(lat_dmsp, lon_dmsp, lat_map, lon_map, Obs_map, k=5, tol=1.5):
'\n \n '
tol = np.deg2rad(tol)
dmsp_points = np.deg2rad(np.hstack((lat_dmsp.flatten().reshape((- 1), 1), lon_dmsp.flatten().reshape((- 1), 1))))
map_points = np.deg2rad(np.hstack((lat_map.... |
def create_host_template(resource_root, name, cluster_name):
'\n Create a host template.\n @param resource_root: The root Resource object.\n @param name: Host template name\n @param cluster_name: Cluster name\n @return: An ApiHostTemplate object for the created host template.\n @since: API v3\n '
apitemp... | 7,939,236,683,972,800,000 | Create a host template.
@param resource_root: The root Resource object.
@param name: Host template name
@param cluster_name: Cluster name
@return: An ApiHostTemplate object for the created host template.
@since: API v3 | python/src/cm_api/endpoints/host_templates.py | create_host_template | AnniDu/cm_api | python | def create_host_template(resource_root, name, cluster_name):
'\n Create a host template.\n @param resource_root: The root Resource object.\n @param name: Host template name\n @param cluster_name: Cluster name\n @return: An ApiHostTemplate object for the created host template.\n @since: API v3\n '
apitemp... |
def get_host_template(resource_root, name, cluster_name):
'\n Lookup a host template by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @return: An ApiHostTemplate object.\n @since: API v3\n '
retur... | 8,255,752,173,159,167,000 | Lookup a host template by name in the specified cluster.
@param resource_root: The root Resource object.
@param name: Host template name.
@param cluster_name: Cluster name.
@return: An ApiHostTemplate object.
@since: API v3 | python/src/cm_api/endpoints/host_templates.py | get_host_template | AnniDu/cm_api | python | def get_host_template(resource_root, name, cluster_name):
'\n Lookup a host template by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @return: An ApiHostTemplate object.\n @since: API v3\n '
retur... |
def get_all_host_templates(resource_root, cluster_name='default'):
'\n Get all host templates in a cluster.\n @param cluster_name: Cluster name.\n @return: ApiList of ApiHostTemplate objects for all host templates in a cluster.\n @since: API v3\n '
return call(resource_root.get, (HOST_TEMPLATES_PATH % (clu... | -7,250,237,421,090,976,000 | Get all host templates in a cluster.
@param cluster_name: Cluster name.
@return: ApiList of ApiHostTemplate objects for all host templates in a cluster.
@since: API v3 | python/src/cm_api/endpoints/host_templates.py | get_all_host_templates | AnniDu/cm_api | python | def get_all_host_templates(resource_root, cluster_name='default'):
'\n Get all host templates in a cluster.\n @param cluster_name: Cluster name.\n @return: ApiList of ApiHostTemplate objects for all host templates in a cluster.\n @since: API v3\n '
return call(resource_root.get, (HOST_TEMPLATES_PATH % (clu... |
def delete_host_template(resource_root, name, cluster_name):
'\n Delete a host template identified by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @return: The deleted ApiHostTemplate object.\n @since... | 6,140,958,390,686,519,000 | Delete a host template identified by name in the specified cluster.
@param resource_root: The root Resource object.
@param name: Host template name.
@param cluster_name: Cluster name.
@return: The deleted ApiHostTemplate object.
@since: API v3 | python/src/cm_api/endpoints/host_templates.py | delete_host_template | AnniDu/cm_api | python | def delete_host_template(resource_root, name, cluster_name):
'\n Delete a host template identified by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @return: The deleted ApiHostTemplate object.\n @since... |
def update_host_template(resource_root, name, cluster_name, api_host_template):
'\n Update a host template identified by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @param api_host_template: The updat... | -5,353,111,303,949,854,000 | Update a host template identified by name in the specified cluster.
@param resource_root: The root Resource object.
@param name: Host template name.
@param cluster_name: Cluster name.
@param api_host_template: The updated host template.
@return: The updated ApiHostTemplate.
@since: API v3 | python/src/cm_api/endpoints/host_templates.py | update_host_template | AnniDu/cm_api | python | def update_host_template(resource_root, name, cluster_name, api_host_template):
'\n Update a host template identified by name in the specified cluster.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @param api_host_template: The updat... |
def apply_host_template(resource_root, name, cluster_name, host_ids, start_roles):
'\n Apply a host template identified by name on the specified hosts and\n optionally start them.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @param... | 7,267,557,606,698,993,000 | Apply a host template identified by name on the specified hosts and
optionally start them.
@param resource_root: The root Resource object.
@param name: Host template name.
@param cluster_name: Cluster name.
@param host_ids: List of host ids.
@param start_roles: Whether to start the created roles or not.
@return: An Api... | python/src/cm_api/endpoints/host_templates.py | apply_host_template | AnniDu/cm_api | python | def apply_host_template(resource_root, name, cluster_name, host_ids, start_roles):
'\n Apply a host template identified by name on the specified hosts and\n optionally start them.\n @param resource_root: The root Resource object.\n @param name: Host template name.\n @param cluster_name: Cluster name.\n @param... |
def rename(self, new_name):
'\n Rename a host template.\n @param new_name: New host template name.\n @return: An ApiHostTemplate object.\n '
update = copy.copy(self)
update.name = new_name
return self._do_update(update) | 6,840,494,761,294,532,000 | Rename a host template.
@param new_name: New host template name.
@return: An ApiHostTemplate object. | python/src/cm_api/endpoints/host_templates.py | rename | AnniDu/cm_api | python | def rename(self, new_name):
'\n Rename a host template.\n @param new_name: New host template name.\n @return: An ApiHostTemplate object.\n '
update = copy.copy(self)
update.name = new_name
return self._do_update(update) |
def set_role_config_groups(self, role_config_group_refs):
'\n Updates the role config groups in a host template.\n @param role_config_group_refs: List of role config group refs.\n @return: An ApiHostTemplate object.\n '
update = copy.copy(self)
update.roleConfigGroupRefs = role_config_group_refs... | 3,588,990,677,251,294,700 | Updates the role config groups in a host template.
@param role_config_group_refs: List of role config group refs.
@return: An ApiHostTemplate object. | python/src/cm_api/endpoints/host_templates.py | set_role_config_groups | AnniDu/cm_api | python | def set_role_config_groups(self, role_config_group_refs):
'\n Updates the role config groups in a host template.\n @param role_config_group_refs: List of role config group refs.\n @return: An ApiHostTemplate object.\n '
update = copy.copy(self)
update.roleConfigGroupRefs = role_config_group_refs... |
def apply_host_template(self, host_ids, start_roles):
'\n Apply a host template identified by name on the specified hosts and\n optionally start them.\n @param host_ids: List of host ids.\n @param start_roles: Whether to start the created roles or not.\n @return: An ApiCommand object.\n '
retu... | 4,150,363,049,570,062,300 | Apply a host template identified by name on the specified hosts and
optionally start them.
@param host_ids: List of host ids.
@param start_roles: Whether to start the created roles or not.
@return: An ApiCommand object. | python/src/cm_api/endpoints/host_templates.py | apply_host_template | AnniDu/cm_api | python | def apply_host_template(self, host_ids, start_roles):
'\n Apply a host template identified by name on the specified hosts and\n optionally start them.\n @param host_ids: List of host ids.\n @param start_roles: Whether to start the created roles or not.\n @return: An ApiCommand object.\n '
retu... |
async def begin_delete(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller[None]:
"Deletes the specified network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n :param network_interface_name: The ... | 8,094,789,127,094,718,000 | Deletes the specified network interface.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:keyword callable cls: A custom type or function that will be passed the direct respons... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | begin_delete | AriZavala2/azure-sdk-for-python | python | async def begin_delete(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller[None]:
"Deletes the specified network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n :param network_interface_name: The ... |
async def get(self, resource_group_name: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterface':
'Gets information about the specified network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n ... | -970,889,739,739,060,600 | Gets information about the specified network interface.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:param expand: Expands referenced resources.
:type expand: str
:keyword ... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | get | AriZavala2/azure-sdk-for-python | python | async def get(self, resource_group_name: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterface':
'Gets information about the specified network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n ... |
async def begin_create_or_update(self, resource_group_name: str, network_interface_name: str, parameters: '_models.NetworkInterface', **kwargs) -> AsyncLROPoller['_models.NetworkInterface']:
"Creates or updates a network interface.\n\n :param resource_group_name: The name of the resource group.\n :typ... | 6,187,002,099,064,935,000 | Creates or updates a network interface.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:param parameters: Parameters supplied to the create or update network interface operati... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | begin_create_or_update | AriZavala2/azure-sdk-for-python | python | async def begin_create_or_update(self, resource_group_name: str, network_interface_name: str, parameters: '_models.NetworkInterface', **kwargs) -> AsyncLROPoller['_models.NetworkInterface']:
"Creates or updates a network interface.\n\n :param resource_group_name: The name of the resource group.\n :typ... |
async def begin_update_tags(self, resource_group_name: str, network_interface_name: str, parameters: '_models.TagsObject', **kwargs) -> AsyncLROPoller['_models.NetworkInterface']:
"Updates a network interface tags.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_... | 3,031,527,886,410,133,500 | Updates a network interface tags.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:param parameters: Parameters supplied to update network interface tags.
:type parameters: ~az... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | begin_update_tags | AriZavala2/azure-sdk-for-python | python | async def begin_update_tags(self, resource_group_name: str, network_interface_name: str, parameters: '_models.TagsObject', **kwargs) -> AsyncLROPoller['_models.NetworkInterface']:
"Updates a network interface tags.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_... |
def list_all(self, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a subscription.\n\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: An iterator like instance of either NetworkInterfaceListResult or... | -2,660,559,911,661,629,400 | Gets all network interfaces in a subscription.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either NetworkInterfaceListResult or the result of cls(response)
:rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.network.v2018_07_01.... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | list_all | AriZavala2/azure-sdk-for-python | python | def list_all(self, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a subscription.\n\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: An iterator like instance of either NetworkInterfaceListResult or... |
def list(self, resource_group_name: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a resource group.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n :keyword callable cls: A custom type or... | -4,022,185,835,828,412,000 | Gets all network interfaces in a resource group.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either NetworkInterfaceListResult or the result of c... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | list | AriZavala2/azure-sdk-for-python | python | def list(self, resource_group_name: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a resource group.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n :keyword callable cls: A custom type or... |
async def begin_get_effective_route_table(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller['_models.EffectiveRouteListResult']:
"Gets all route tables applied to a network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resourc... | 8,000,999,916,194,996,000 | Gets all route tables applied to a network interface.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:keyword callable cls: A custom type or function that will be passed the d... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | begin_get_effective_route_table | AriZavala2/azure-sdk-for-python | python | async def begin_get_effective_route_table(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller['_models.EffectiveRouteListResult']:
"Gets all route tables applied to a network interface.\n\n :param resource_group_name: The name of the resource group.\n :type resourc... |
async def begin_list_effective_network_security_groups(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller['_models.EffectiveNetworkSecurityGroupListResult']:
"Gets all network security groups applied to a network interface.\n\n :param resource_group_name: The name of the... | 8,632,860,345,684,696,000 | Gets all network security groups applied to a network interface.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param network_interface_name: The name of the network interface.
:type network_interface_name: str
:keyword callable cls: A custom type or function that will be p... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | begin_list_effective_network_security_groups | AriZavala2/azure-sdk-for-python | python | async def begin_list_effective_network_security_groups(self, resource_group_name: str, network_interface_name: str, **kwargs) -> AsyncLROPoller['_models.EffectiveNetworkSecurityGroupListResult']:
"Gets all network security groups applied to a network interface.\n\n :param resource_group_name: The name of the... |
def list_virtual_machine_scale_set_vm_network_interfaces(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets information about all network interfaces in a virtual machine in a virtual machine scale\n ... | -555,309,031,031,284,400 | Gets information about all network interfaces in a virtual machine in a virtual machine scale
set.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_machine_scale_set_name: The name of the virtual machine scale set.
:type virtual_machine_scale_set_name: str
:para... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | list_virtual_machine_scale_set_vm_network_interfaces | AriZavala2/azure-sdk-for-python | python | def list_virtual_machine_scale_set_vm_network_interfaces(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets information about all network interfaces in a virtual machine in a virtual machine scale\n ... |
def list_virtual_machine_scale_set_network_interfaces(self, resource_group_name: str, virtual_machine_scale_set_name: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a virtual machine scale set.\n\n :param resource_group_name: The name of the resource gr... | -4,041,946,283,772,427,000 | Gets all network interfaces in a virtual machine scale set.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_machine_scale_set_name: The name of the virtual machine scale set.
:type virtual_machine_scale_set_name: str
:keyword callable cls: A custom type or func... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | list_virtual_machine_scale_set_network_interfaces | AriZavala2/azure-sdk-for-python | python | def list_virtual_machine_scale_set_network_interfaces(self, resource_group_name: str, virtual_machine_scale_set_name: str, **kwargs) -> AsyncIterable['_models.NetworkInterfaceListResult']:
'Gets all network interfaces in a virtual machine scale set.\n\n :param resource_group_name: The name of the resource gr... |
async def get_virtual_machine_scale_set_network_interface(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterface':
'Get the specified network interface in a virtual machine scale ... | -1,541,610,260,864,576,800 | Get the specified network interface in a virtual machine scale set.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_machine_scale_set_name: The name of the virtual machine scale set.
:type virtual_machine_scale_set_name: str
:param virtualmachine_index: The vir... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | get_virtual_machine_scale_set_network_interface | AriZavala2/azure-sdk-for-python | python | async def get_virtual_machine_scale_set_network_interface(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterface':
'Get the specified network interface in a virtual machine scale ... |
def list_virtual_machine_scale_set_ip_configurations(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> AsyncIterable['_models.NetworkInterfaceIPConfigurationListResult']:
'Get the specified network in... | -2,000,844,739,091,031,600 | Get the specified network interface ip configuration in a virtual machine scale set.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_machine_scale_set_name: The name of the virtual machine scale set.
:type virtual_machine_scale_set_name: str
:param virtualmachi... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | list_virtual_machine_scale_set_ip_configurations | AriZavala2/azure-sdk-for-python | python | def list_virtual_machine_scale_set_ip_configurations(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, expand: Optional[str]=None, **kwargs) -> AsyncIterable['_models.NetworkInterfaceIPConfigurationListResult']:
'Get the specified network in... |
async def get_virtual_machine_scale_set_ip_configuration(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, ip_configuration_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterfaceIPConfiguration':
'Get the specified net... | 4,947,045,084,881,894,000 | Get the specified network interface ip configuration in a virtual machine scale set.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_machine_scale_set_name: The name of the virtual machine scale set.
:type virtual_machine_scale_set_name: str
:param virtualmachi... | sdk/network/azure-mgmt-network/azure/mgmt/network/v2018_07_01/aio/operations/_network_interfaces_operations.py | get_virtual_machine_scale_set_ip_configuration | AriZavala2/azure-sdk-for-python | python | async def get_virtual_machine_scale_set_ip_configuration(self, resource_group_name: str, virtual_machine_scale_set_name: str, virtualmachine_index: str, network_interface_name: str, ip_configuration_name: str, expand: Optional[str]=None, **kwargs) -> '_models.NetworkInterfaceIPConfiguration':
'Get the specified net... |
def supersample(clip, d, n_frames):
'Replaces each frame at time t by the mean of `n_frames` equally spaced frames\n taken in the interval [t-d, t+d]. This results in motion blur.\n '
def filter(get_frame, t):
timings = np.linspace((t - d), (t + d), n_frames)
frame_average = np.mean((1.0 ... | -8,634,872,168,947,782,000 | Replaces each frame at time t by the mean of `n_frames` equally spaced frames
taken in the interval [t-d, t+d]. This results in motion blur. | moviepy/video/fx/supersample.py | supersample | va6996/moviepy | python | def supersample(clip, d, n_frames):
'Replaces each frame at time t by the mean of `n_frames` equally spaced frames\n taken in the interval [t-d, t+d]. This results in motion blur.\n '
def filter(get_frame, t):
timings = np.linspace((t - d), (t + d), n_frames)
frame_average = np.mean((1.0 ... |
def _get_filesystem_space_available(self) -> int:
'\n Abort a configuration -- discards any loaded config\n\n Args:\n N/A\n\n Returns:\n None\n\n Raises:\n FailedToDetermineDeviceState: if unable to fetch file filesystem bytes available\n\n '
f... | 4,290,810,500,748,125,000 | Abort a configuration -- discards any loaded config
Args:
N/A
Returns:
None
Raises:
FailedToDetermineDeviceState: if unable to fetch file filesystem bytes available | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | _get_filesystem_space_available | m1009d/scrapli_cfg | python | def _get_filesystem_space_available(self) -> int:
'\n Abort a configuration -- discards any loaded config\n\n Args:\n N/A\n\n Returns:\n None\n\n Raises:\n FailedToDetermineDeviceState: if unable to fetch file filesystem bytes available\n\n '
f... |
def _determine_file_prompt_mode(self) -> FilePromptMode:
'\n Determine the device file prompt mode\n\n Args:\n N/A\n\n Returns:\n FilePromptMode: enum representing file prompt mode\n\n Raises:\n FailedToDetermineDeviceState: if unable to fetch file prompt... | 4,494,592,894,372,750,000 | Determine the device file prompt mode
Args:
N/A
Returns:
FilePromptMode: enum representing file prompt mode
Raises:
FailedToDetermineDeviceState: if unable to fetch file prompt mode | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | _determine_file_prompt_mode | m1009d/scrapli_cfg | python | def _determine_file_prompt_mode(self) -> FilePromptMode:
'\n Determine the device file prompt mode\n\n Args:\n N/A\n\n Returns:\n FilePromptMode: enum representing file prompt mode\n\n Raises:\n FailedToDetermineDeviceState: if unable to fetch file prompt... |
def _delete_candidate_config(self) -> Response:
'\n Delete candidate config from the filesystem\n\n Args:\n N/A\n\n Returns:\n Response: response from deleting the candidate config\n\n Raises:\n N/A\n\n '
file_prompt_mode = self._determine_file... | -3,679,154,330,024,867,300 | Delete candidate config from the filesystem
Args:
N/A
Returns:
Response: response from deleting the candidate config
Raises:
N/A | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | _delete_candidate_config | m1009d/scrapli_cfg | python | def _delete_candidate_config(self) -> Response:
'\n Delete candidate config from the filesystem\n\n Args:\n N/A\n\n Returns:\n Response: response from deleting the candidate config\n\n Raises:\n N/A\n\n '
file_prompt_mode = self._determine_file... |
def load_config(self, config: str, replace: bool=False, **kwargs: Any) -> ScrapliCfgResponse:
'\n Load configuration to a device\n\n Supported kwargs:\n auto_clean: automatically "clean" any data that would be in a configuration from a\n "get_config" operation that would prev... | -8,690,298,349,246,840,000 | Load configuration to a device
Supported kwargs:
auto_clean: automatically "clean" any data that would be in a configuration from a
"get_config" operation that would prevent loading a config -- for example, things
like the "Building Configuration" lines in IOSXE output, etc.. Defaults to `True`
Ar... | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | load_config | m1009d/scrapli_cfg | python | def load_config(self, config: str, replace: bool=False, **kwargs: Any) -> ScrapliCfgResponse:
'\n Load configuration to a device\n\n Supported kwargs:\n auto_clean: automatically "clean" any data that would be in a configuration from a\n "get_config" operation that would prev... |
def save_config(self) -> Response:
'\n Save the config -- "copy run start"!\n\n Args:\n N/A\n\n Returns:\n Response: scrapli response object\n\n Raises:\n N/A\n\n '
file_prompt_mode = self._determine_file_prompt_mode()
if (file_prompt_mode... | 2,636,294,837,735,312,000 | Save the config -- "copy run start"!
Args:
N/A
Returns:
Response: scrapli response object
Raises:
N/A | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | save_config | m1009d/scrapli_cfg | python | def save_config(self) -> Response:
'\n Save the config -- "copy run start"!\n\n Args:\n N/A\n\n Returns:\n Response: scrapli response object\n\n Raises:\n N/A\n\n '
file_prompt_mode = self._determine_file_prompt_mode()
if (file_prompt_mode... |
def _commit_config_merge(self, file_prompt_mode: Optional[FilePromptMode]=None) -> Response:
'\n Commit the configuration in merge mode\n\n Args:\n file_prompt_mode: optionally provide the file prompt mode, if its None we will fetch it\n to decide if we need to use interact... | 8,629,980,584,191,336,000 | Commit the configuration in merge mode
Args:
file_prompt_mode: optionally provide the file prompt mode, if its None we will fetch it
to decide if we need to use interactive mode or not
Returns:
Response: scrapli response object
Raises:
N/A | scrapli_cfg/platform/core/cisco_iosxe/sync_platform.py | _commit_config_merge | m1009d/scrapli_cfg | python | def _commit_config_merge(self, file_prompt_mode: Optional[FilePromptMode]=None) -> Response:
'\n Commit the configuration in merge mode\n\n Args:\n file_prompt_mode: optionally provide the file prompt mode, if its None we will fetch it\n to decide if we need to use interact... |
@Metadata.property
def name(self):
'\n Returns:\n str?: package name\n '
return self.get('name') | 5,820,657,966,021,142,000 | Returns:
str?: package name | frictionless/package.py | name | augusto-herrmann/frictionless-py | python | @Metadata.property
def name(self):
'\n Returns:\n str?: package name\n '
return self.get('name') |
@Metadata.property
def id(self):
'\n Returns:\n str?: package id\n '
return self.get('id') | 8,748,339,723,644,212,000 | Returns:
str?: package id | frictionless/package.py | id | augusto-herrmann/frictionless-py | python | @Metadata.property
def id(self):
'\n Returns:\n str?: package id\n '
return self.get('id') |
@Metadata.property
def licenses(self):
'\n Returns:\n dict?: package licenses\n '
return self.get('licenses') | -8,123,081,130,484,642,000 | Returns:
dict?: package licenses | frictionless/package.py | licenses | augusto-herrmann/frictionless-py | python | @Metadata.property
def licenses(self):
'\n Returns:\n dict?: package licenses\n '
return self.get('licenses') |
@Metadata.property
def profile(self):
'\n Returns:\n str: package profile\n '
return self.get('profile', config.DEFAULT_PACKAGE_PROFILE) | 1,270,557,999,987,451,100 | Returns:
str: package profile | frictionless/package.py | profile | augusto-herrmann/frictionless-py | python | @Metadata.property
def profile(self):
'\n Returns:\n str: package profile\n '
return self.get('profile', config.DEFAULT_PACKAGE_PROFILE) |
@Metadata.property
def title(self):
'\n Returns:\n str?: package title\n '
return self.get('title') | -277,341,525,452,260,380 | Returns:
str?: package title | frictionless/package.py | title | augusto-herrmann/frictionless-py | python | @Metadata.property
def title(self):
'\n Returns:\n str?: package title\n '
return self.get('title') |
@Metadata.property
def description(self):
'\n Returns:\n str?: package description\n '
return self.get('description') | 3,847,154,689,001,268,000 | Returns:
str?: package description | frictionless/package.py | description | augusto-herrmann/frictionless-py | python | @Metadata.property
def description(self):
'\n Returns:\n str?: package description\n '
return self.get('description') |
@Metadata.property
def homepage(self):
'\n Returns:\n str?: package homepage\n '
return self.get('homepage') | 7,836,316,663,488,343,000 | Returns:
str?: package homepage | frictionless/package.py | homepage | augusto-herrmann/frictionless-py | python | @Metadata.property
def homepage(self):
'\n Returns:\n str?: package homepage\n '
return self.get('homepage') |
@Metadata.property
def version(self):
'\n Returns:\n str?: package version\n '
return self.get('version') | 7,422,947,098,319,725,000 | Returns:
str?: package version | frictionless/package.py | version | augusto-herrmann/frictionless-py | python | @Metadata.property
def version(self):
'\n Returns:\n str?: package version\n '
return self.get('version') |
@Metadata.property
def sources(self):
'\n Returns:\n dict[]?: package sources\n '
return self.get('sources') | 1,385,391,418,121,966,300 | Returns:
dict[]?: package sources | frictionless/package.py | sources | augusto-herrmann/frictionless-py | python | @Metadata.property
def sources(self):
'\n Returns:\n dict[]?: package sources\n '
return self.get('sources') |
@Metadata.property
def contributors(self):
'\n Returns:\n dict[]?: package contributors\n '
return self.get('contributors') | -3,563,835,736,333,918,000 | Returns:
dict[]?: package contributors | frictionless/package.py | contributors | augusto-herrmann/frictionless-py | python | @Metadata.property
def contributors(self):
'\n Returns:\n dict[]?: package contributors\n '
return self.get('contributors') |
@Metadata.property
def keywords(self):
'\n Returns:\n str[]?: package keywords\n '
return self.get('keywords') | -7,563,408,634,650,146,000 | Returns:
str[]?: package keywords | frictionless/package.py | keywords | augusto-herrmann/frictionless-py | python | @Metadata.property
def keywords(self):
'\n Returns:\n str[]?: package keywords\n '
return self.get('keywords') |
@Metadata.property
def image(self):
'\n Returns:\n str?: package image\n '
return self.get('image') | -6,807,587,785,999,051,000 | Returns:
str?: package image | frictionless/package.py | image | augusto-herrmann/frictionless-py | python | @Metadata.property
def image(self):
'\n Returns:\n str?: package image\n '
return self.get('image') |
@Metadata.property
def created(self):
'\n Returns:\n str?: package created\n '
return self.get('created') | 329,250,756,673,019,840 | Returns:
str?: package created | frictionless/package.py | created | augusto-herrmann/frictionless-py | python | @Metadata.property
def created(self):
'\n Returns:\n str?: package created\n '
return self.get('created') |
@Metadata.property(cache=False, write=False)
def hashing(self):
'\n Returns:\n str: package hashing\n '
return self.__hashing | 9,121,979,823,706,777,000 | Returns:
str: package hashing | frictionless/package.py | hashing | augusto-herrmann/frictionless-py | python | @Metadata.property(cache=False, write=False)
def hashing(self):
'\n Returns:\n str: package hashing\n '
return self.__hashing |
@Metadata.property(cache=False, write=False)
def basepath(self):
'\n Returns:\n str: package basepath\n '
return self.__basepath | -6,273,207,310,273,945,000 | Returns:
str: package basepath | frictionless/package.py | basepath | augusto-herrmann/frictionless-py | python | @Metadata.property(cache=False, write=False)
def basepath(self):
'\n Returns:\n str: package basepath\n '
return self.__basepath |
@Metadata.property(cache=False, write=False)
def onerror(self):
'\n Returns:\n ignore|warn|raise: on error bahaviour\n '
return self.__onerror | -2,288,389,652,372,572,400 | Returns:
ignore|warn|raise: on error bahaviour | frictionless/package.py | onerror | augusto-herrmann/frictionless-py | python | @Metadata.property(cache=False, write=False)
def onerror(self):
'\n Returns:\n ignore|warn|raise: on error bahaviour\n '
return self.__onerror |
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