tsgm.models.sts

Module Contents

class STS(model: tensorflow_probability.sts.StructuralTimeSeries = None)[source]

Class for training and generating from a structural time series model.

Initializes a new instance of the STS class.

Parameters:

model (tfp.sts.StructuralTimeSeriesModel or None) – Structural time series model to use. If None, default model is used.

train(ds: tsgm.dataset.Dataset, num_variational_steps: int = 200, steps_forw: int = 10) → None[source]

Trains the structural time series model.

Parameters:

  • ds (tsgm.dataset.Dataset) – Dataset containing time series data.

  • num_variational_steps (int) – Number of variational optimization steps, defaults to 200.

  • steps_forw (int) – Number of steps to forecast, defaults to 10.

elbo_loss() → float[source]

Returns the evidence lower bound (ELBO) loss from training.

Returns:

The value of the ELBO loss.

Return type:

float

generate(num_samples: int) → tsgm.types.Tensor[source]

Generates samples from the trained model.

Parameters:

num_samples (int) – Number of samples to generate.

Returns:

Generated samples.

Return type:

tsgm.types.Tensor