nessai.flows.distributions#
Distributions to use as the ‘base distribution’ for normalising flows.
Classes#
A multivariate Normal with zero mean and specified covariance. |
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Wrapper for ResampledGaussian. |
Module Contents#
- class nessai.flows.distributions.MultivariateNormal(shape, var=1)#
Bases:
glasflow.nflows.distributions.DistributionA multivariate Normal with zero mean and specified covariance.
- Parameters:
- shapetuple
Shape of distribution, this is used to determine the number of dimensions.
- varfloat, optional
Variance of the distribution.
- class nessai.flows.distributions.ResampledGaussian(shape: int | tuple, acceptance_fn: Callable, eps: float = 0.05, truncation: int = 100, trainable: bool = False)#
Bases:
glasflow.distributions.ResampledGaussianWrapper for ResampledGaussian.
Adds methods needed in nessai.
- end_iteration#
Function to be called at the end of an iteration.
For LARS this updates the estimate of the normalisation constant independently of the other parameters in the flow.
- finalise(n_samples: int = 10000, n_batches: int = 10) None#
Finalise the estimate of the normalisation constant.