hierarchical_flow_tools.models¶
Provides some out-of-the-box use of hierarchical-flow-tools with other packages.
Module Contents¶
Classes¶
Model class for use with the nessai package for parameter estimation. |
- class hierarchical_flow_tools.models.NessaiModel(names: list, bounds: list, flow_likelihood: hierarchical_flow_tools.likelihood.FlowLikelihood)¶
Bases:
nessai.model.ModelModel class for use with the nessai package for parameter estimation.
- Parameters:
- nameslist
A list of label strings for each parameter.
- boundsdict
A dict of the prior bounds, assuming uniform priors on all parameters.
- flowlikeFlowLikelihood
The FlowLikelihood class to use for the log_likelihood calls.
- unpack_live_point(x)¶
Unpacks a live point to a torch tensor for use in the log_likelihood.
- Parameters:
- xstructured_array
The live points to be unpacked into a torch tensor.
- Returns:
- Tensor
The unpacked live points.
- log_prior(x)¶
Returns log of prior given a live point assuming uniform priors on each parameter.
- Parameters:
- xstructured array
the live points for which to evaluate the prior probability.
- Returns:
- ndarray
the log_prior probabilities
- log_likelihood(x)¶
Log likelihood wrapper that calls the FlowLikelihood.log_likelihood method.
- Parameters:
- xstructured array
the live points for which to evaluate the prior probability.
- Returns:
- ndarray
The resulting log_likelihoods, cast to a numpy array for compatibility with nessai.