types

jaxns.internals.types

Module Contents

float_type[source]
int_type[source]
complex_type[source]
PRNGKey[source]
FloatArray[source]
IntArray[source]
BoolArray[source]
LikelihoodType[source]
RandomVariableType[source]
MeasureType[source]
LikelihoodInputType[source]
UType[source]
XType[source]
class EvidenceCalculation[source]

Bases: NamedTuple

Contains a running estimate of evidence and related quantities.

log_L: FloatArray[source]
log_X_mean: FloatArray[source]
log_X2_mean: FloatArray[source]
log_Z_mean: FloatArray[source]
log_ZX_mean: FloatArray[source]
log_Z2_mean: FloatArray[source]
log_dZ_mean: FloatArray[source]
log_dZ2_mean: FloatArray[source]
class TerminationCondition[source]

Bases: NamedTuple

Contains the termination conditions for the nested sampling run.

Parameters:

  • ess – The effective sample size, if the ESS (Kish’s estimate) is greater than this the run will terminate.

  • evidence_uncert – The uncertainty in the evidence, if the uncertainty is less than this the run will terminate.

  • live_evidence_frac – Depreceated use dlogZ.

  • dlogZ – Terminate if log(Z_current + Z_remaining) - log(Z_current) < dlogZ. Default log(1 + 1e-2)

  • max_samples – Terminate if the number of samples exceeds this.

  • max_num_likelihood_evaluations – Terminate if the number of likelihood evaluations exceeds this.

  • log_L_contour – Terminate if this log(L) contour is reached. A contour is reached if any dead point has log(L) > log_L_contour. Uncollected live points are not considered.

  • efficiency_threshold – Terminate if the efficiency (num_samples / num_likelihood_evaluations) is less than this, for the last shrinkage iteration.

ess: FloatArray | None[source]
evidence_uncert: FloatArray | None[source]
live_evidence_frac: FloatArray | None[source]
dlogZ: FloatArray | None[source]
max_samples: IntArray | None[source]
max_num_likelihood_evaluations: IntArray | None[source]
log_L_contour: FloatArray | None[source]
efficiency_threshold: FloatArray | None[source]
__and__(other)[source]
__or__(other)[source]
class NestedSamplerResults[source]

Bases: NamedTuple

Results of the nested sampling run.

log_Z_mean: FloatArray[source]
log_Z_uncert: FloatArray[source]
ESS: FloatArray[source]
H_mean: FloatArray[source]
samples: XType[source]
parametrised_samples: XType[source]
U_samples: UType[source]
log_L_samples: FloatArray[source]
log_dp_mean: FloatArray[source]
log_X_mean: FloatArray[source]
log_posterior_density: FloatArray[source]
num_live_points_per_sample: IntArray[source]
num_likelihood_evaluations_per_sample: IntArray[source]
total_num_samples: IntArray[source]
total_phantom_samples: IntArray[source]
total_num_likelihood_evaluations: IntArray[source]
log_efficiency: FloatArray[source]
termination_reason: IntArray[source]
class StaticStandardNestedSamplerState[source]

Bases: NamedTuple

key: PRNGKey[source]
next_sample_idx: IntArray[source]
sample_collection: StaticStandardSampleCollection[source]
front_idx: IntArray[source]