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Addressing issue 347: time varying weights in LGSSM #356

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Feb 1, 2024
Merged

Addressing issue 347: time varying weights in LGSSM #356

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11 changes: 10 additions & 1 deletion dynamax/linear_gaussian_ssm/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@
from typing_extensions import Protocol

from dynamax.ssm import SSM
from dynamax.linear_gaussian_ssm.inference import lgssm_filter, lgssm_smoother, lgssm_posterior_sample
from dynamax.linear_gaussian_ssm.inference import lgssm_joint_sample, lgssm_filter, lgssm_smoother, lgssm_posterior_sample
from dynamax.linear_gaussian_ssm.inference import ParamsLGSSM, ParamsLGSSMInitial, ParamsLGSSMDynamics, ParamsLGSSMEmissions
from dynamax.linear_gaussian_ssm.inference import PosteriorGSSMFiltered, PosteriorGSSMSmoothed
from dynamax.parameters import ParameterProperties, ParameterSet
Expand Down Expand Up @@ -198,6 +198,15 @@ def emission_distribution(
if self.has_emissions_bias:
mean += params.emissions.bias
return MVN(mean, params.emissions.cov)

def sample(
self,
params: ParamsLGSSM,
key: PRNGKey,
num_timesteps: int,
inputs: Optional[Float[Array, "ntime input_dim"]] = None
) -> PosteriorGSSMFiltered:
return lgssm_joint_sample(params, key, num_timesteps, inputs)

def marginal_log_prob(
self,
Expand Down
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