LevelSSM

class LevelSSM[source]

Bases: etna.models.nn.deepstate.state_space_model.SSM

Class for Level State Space Model.

Inherited-members

Methods

emission_coeff(datetime_index)

Emission coefficient matrix.

generate_datetime_index(timestamps)

Generate datetime index to use in the State Space Model.

innovation_coeff(datetime_index)

Innovation coefficient matrix.

latent_dim()

Dimension of the latent space.

set_params(**params)

Return new object instance with modified parameters.

to_dict()

Collect all information about etna object in dict.

transition_coeff(datetime_index)

Transition coefficient matrix.

emission_coeff(datetime_index: torch.Tensor) torch.Tensor[source]

Emission coefficient matrix.

Parameters

datetime_index (torch.Tensor) – Tensor with the index values. Values should be from 0 to seasonal period.

Returns

Emission coefficient matrix.

Return type

torch.Tensor

generate_datetime_index(timestamps: numpy.ndarray) numpy.ndarray[source]

Generate datetime index to use in the State Space Model.

Parameters

timestamps (numpy.ndarray) – Array with timestamps.

Returns

Datetime index for State Space Model.

Return type

numpy.ndarray

innovation_coeff(datetime_index: torch.Tensor) torch.Tensor[source]

Innovation coefficient matrix.

Parameters

datetime_index (torch.Tensor) – Tensor with the index values. Values should be from 0 to seasonal period.

Returns

Innovation coefficient matrix.

Return type

torch.Tensor

latent_dim() int[source]

Dimension of the latent space.

Returns

Dimension of the latent space.

Return type

int

set_params(**params: dict) etna.core.mixins.TMixin

Return new object instance with modified parameters.

Method also allows to change parameters of nested objects within the current object. For example, it is possible to change parameters of a model in a Pipeline.

Nested parameters are expected to be in a <component_1>.<...>.<parameter> form, where components are separated by a dot.

Parameters
  • **params – Estimator parameters

  • self (etna.core.mixins.TMixin) –

  • params (dict) –

Returns

New instance with changed parameters

Return type

etna.core.mixins.TMixin

Examples

>>> from etna.pipeline import Pipeline
>>> from etna.models import NaiveModel
>>> from etna.transforms import AddConstTransform
>>> model = model=NaiveModel(lag=1)
>>> transforms = [AddConstTransform(in_column="target", value=1)]
>>> pipeline = Pipeline(model, transforms=transforms, horizon=3)
>>> pipeline.set_params(**{"model.lag": 3, "transforms.0.value": 2})
Pipeline(model = NaiveModel(lag = 3, ), transforms = [AddConstTransform(in_column = 'target', value = 2, inplace = True, out_column = None, )], horizon = 3, )
to_dict()

Collect all information about etna object in dict.

transition_coeff(datetime_index: torch.Tensor) torch.Tensor[source]

Transition coefficient matrix.

Parameters

datetime_index (torch.Tensor) – Tensor with the index values. Values should be from 0 to seasonal period.

Returns

Transition coefficient matrix.

Return type

torch.Tensor