class VAMPNetModel¶

class deeptime.decomposition.deep.VAMPNetModel(lobe: ~torch.nn.modules.module.Module, lobe_timelagged: ~typing.Optional[~torch.nn.modules.module.Module] = None, dtype=<class 'numpy.float32'>, device=None)¶

A VAMPNet model which can be fit to data optimizing for one of the implemented VAMP scores.

Parameters:

lobe (torch.nn.Module) – One of the lobes of the VAMPNet. See also deeptime.util.torch.MLP.
lobe_timelagged (torch.nn.Module, optional, default=None) – The timelagged lobe. Can be left None, in which case the lobes are shared.
dtype (data type, default=np.float32) – The data type for which operations should be performed. Leads to an appropriate cast within fit and transform methods.
device (device, default=None) – The device for the lobe(s). Can be None which defaults to CPU.

See also

VAMPNet: The corresponding estimator.

Attributes

`lobe`	The instantaneous lobe.
`lobe_timelagged`	The timelagged lobe.

Methods

`copy`()	Makes a deep copy of this model.
`get_params`([deep])	Get the parameters.
`set_params`(**params)	Set the parameters of this estimator.
`transform`(data[, instantaneous])	Transforms data through the instantaneous or time-shifted network lobe.

__call__(*args, **kwargs)¶: Call self as a function.

copy() → Model¶

Makes a deep copy of this model.

Returns:: A new copy of this model.
Return type:: copy

get_params(deep=False)¶

Get the parameters.

Returns:: params – Parameter names mapped to their values.
Return type:: mapping of string to any

set_params(**params)¶

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:: **params (dict) – Estimator parameters.
Returns:: self – Estimator instance.
Return type:: object

transform(data, instantaneous: bool = True, **kwargs)¶

Transforms data through the instantaneous or time-shifted network lobe.

Parameters:

data (numpy array or torch tensor) – The data to transform.
instantaneous (bool, default=True) – Whether to use the instantaneous lobe or the time-shifted lobe for transformation.
**kwargs – Ignored kwargs for api compatibility.

Returns:

transform – List of numpy array or numpy array containing transformed data.

Return type:

array_like

property lobe: Module¶

The instantaneous lobe.

Returns:: lobe
Return type:: nn.Module

property lobe_timelagged: Module¶

The timelagged lobe. Might be equal to lobe.

Returns:: lobe_timelagged
Return type:: nn.Module