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Functions142 in github.com/NetManAIOps/OmniAnomaly

⨍ Functions 142◇ Types & classes 13
Methodlog_prob_step
(self, _, t)
omni_anomaly/recurrent_distribution.py:55
Methodmodel
Get the :class:`OmniAnomaly` model instance. Returns: OmniAnomaly: The :class:`OmniAnomaly` model instance.
omni_anomaly/prediction.py:72
Methodmodel
Get the :class:`OmniAnomaly` model instance. Returns: OmniAnomaly: The :class:`OmniAnomaly` model instance.
omni_anomaly/training.py:175
MethodobjFun
(X, f, jac)
omni_anomaly/spot.py:248
MethodobjFun
(X, f, jac)
omni_anomaly/spot.py:732
MethodobjFun
(X, f, jac)
omni_anomaly/spot.py:1242
MethodobjFun
(X, f, jac)
omni_anomaly/spot.py:1732
Methodp_z
Get :math:`p(z)`, the prior distribution of `z`. Returns: Distribution: The distribution instance.
omni_anomaly/vae.py:184
Methodplot
Plot the results of given by the run Parameters ---------- run_results : dict results given by t
omni_anomaly/spot.py:980
Methodplot
Plot the results given by the run Parameters ---------- run_results : dict results given by the
omni_anomaly/spot.py:1458
Methodplot
Plot the results given by the run Parameters ---------- run_results : dict results given by the
omni_anomaly/spot.py:1988
Methodprob
(self, given, group_ndims=0, name=None)
omni_anomaly/recurrent_distribution.py:159
Methodreconstruct
Sample reconstructed `x` from :math:`p(x|h(z))`, where `z` is (are) sampled from :math:`q(z|h(x))` using the specified observation `x
omni_anomaly/vae.py:430
Methodrun
Run biSPOT on the stream Parameters ---------- with_alarm : bool (default = True) If False, SPOT will
omni_anomaly/spot.py:890
Methodrun
Run biSPOT on the stream Parameters ---------- with_alarm : bool (default = True) If False, SPOT will
omni_anomaly/spot.py:1389
Methodrun
Run biDSPOT on the stream Parameters ---------- with_alarm : bool (default = True) If False, SPOT will
omni_anomaly/spot.py:1890
Methodsample
(self, n_samples=None, is_reparameterized=None, group_ndims=0, compute_density=False, name=None
omni_anomaly/wrapper.py:52
Methodsample
(self, n_samples=1024, is_reparameterized=None, group_ndims=0, compute_density=False, name=None
omni_anomaly/recurrent_distribution.py:88
Methodsample_step
(self, a, t)
omni_anomaly/recurrent_distribution.py:37
Functionsoftplus_std
(inputs, units, epsilon, name)
omni_anomaly/wrapper.py:79
Methodu
(s)
omni_anomaly/spot.py:310
Methodu
(s)
omni_anomaly/spot.py:794
Methodu
(s)
omni_anomaly/spot.py:1304
Methodu
(s)
omni_anomaly/spot.py:1794
Methodv
(s)
omni_anomaly/spot.py:313
Methodv
(s)
omni_anomaly/spot.py:797
Methodv
(s)
omni_anomaly/spot.py:1307
Methodv
(s)
omni_anomaly/spot.py:1797
Methodvae
Get the VAE object of this :class:`OmniAnomaly` model. Returns: VAE: The VAE object of this model.
omni_anomaly/model.py:109
Methodvalue_shape
(self)
omni_anomaly/wrapper.py:39
Methodvalue_shape
(self)
omni_anomaly/recurrent_distribution.py:24
Methodw
(Y, t)
omni_anomaly/spot.py:316
Methodw
(Y, t)
omni_anomaly/spot.py:800
Methodw
(Y, t)
omni_anomaly/spot.py:1310
Methodw
(Y, t)
omni_anomaly/spot.py:1800
Methodwindow_length
(self)
omni_anomaly/model.py:119
Functionwrap_params_net
(inputs, h_for_dist, mean_layer, std_layer)
omni_anomaly/wrapper.py:124
Functionwrap_params_net_srnn
(inputs, h_for_dist)
omni_anomaly/wrapper.py:133
Methodx_dims
Get the number of `x` dimensions.
omni_anomaly/model.py:99
Methodx_group_ndims
Get the `group_ndims` for `x`.
omni_anomaly/vae.py:239
Methodz_dims
Get the number of `z` dimensions.
omni_anomaly/model.py:104
Methodz_group_ndims
Get the `group_ndims` for `z`.
omni_anomaly/vae.py:234
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