leaspy.models.linear

Classes

LinearInitializationMixin	Compute initial values for model parameters.
LinearModel	Manifold model for multiple variables of interest (linear formulation).

Module Contents

class LinearInitializationMixin

Compute initial values for model parameters.

class LinearModel(name, **kwargs)

Bases: LinearInitializationMixin, leaspy.models.riemanian_manifold.RiemanianManifoldModel

Manifold model for multiple variables of interest (linear formulation).

Parameters:

name (str)

get_variables_specs()

Return the specifications of the variables (latent variables, derived variables, model ‘parameters’) that are part of the model.

Returns:

:class:`~leaspy.variables.specs.NamedVariables

A dictionary-like object mapping variable names to their specifications.

Return type:

NamedVariables

static metric(*, g)

Compute the metric tensor for the model.

Parameters:

gtorch.Tensor

Input tensor with values of the population parameter g for each feature.

Returns:

torch.Tensor

A tensor of ones with the same shape as g.

Parameters:

g (Tensor)

Return type:

Tensor

classmethod model_with_sources(*, rt, space_shifts, metric, v0, g)

Return the model output when sources(spatial components) are present.

Parameters:

rttorch.Tensor

The reparametrized time.

space_shiftstorch.Tensor

The values of the space-shifts

metricAny

The metric tensor used for computing the spatial/temporal influence.

v0Any

The values of the population parameter v0 for each feature.

gAny

The values of the population parameter g for each feature.

Returns:

torch.Tensor

The model output with contribution from sources.

Parameters:

• rt (Tensor)

• space_shifts (Tensor)

Return type:

Tensor