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rxmc 0.1.dev1+g31863d2da documentation

Installation
Design: the stacked covariance model
A ground-up rxmc: declare, then compile
Recipes
Bugs and inconsistencies found during the architecture review
- API Reference
- Examples

GitHub

Installation
Design: the stacked covariance model
A ground-up rxmc: declare, then compile
Recipes
Bugs and inconsistencies found during the architecture review
API Reference
Examples

GitHub

Section Navigation

rxmc.config.CalibrationConfig
rxmc.config.ParameterConfig

rxmc.priors.IndependentPrior
rxmc.priors.TruncatedNormalPrior

rxmc.constraint.Constraint
rxmc.evidence.Evidence
rxmc.observation.Observation
rxmc.params.Parameter
rxmc.physical_model.PhysicalModel
rxmc.physical_model.Polynomial

rxmc.transforms.Transform
rxmc.transforms.as_transform
rxmc.transforms.identity
rxmc.transforms.log
rxmc.transforms.exp
rxmc.transforms.scale
rxmc.transforms.per_observation_scaling

rxmc.covariance.Term
rxmc.covariance.TermContext
rxmc.covariance.statistical_term
rxmc.covariance.normalization_term
rxmc.covariance.offset_term
rxmc.covariance.noise_term
rxmc.covariance.noise_fraction_term
rxmc.covariance.model_error_term
rxmc.covariance.systematic_term
rxmc.covariance.kernel_term
rxmc.covariance.ones
rxmc.covariance.ym
rxmc.covariance.averaging
rxmc.covariance.x_basis
rxmc.covariance.exp_growth
rxmc.covariance.constant_amplitude
rxmc.covariance.exp_growth_amplitude
rxmc.covariance.stacked_supports
rxmc.covariance.ConstraintCovariance
rxmc.covariance.StackContext

rxmc.likelihood_model.Likelihood
rxmc.likelihood_model.GaussianLikelihood
rxmc.likelihood_model.StudentT
rxmc.likelihood_model.Chi2
rxmc.likelihood_model.mahalanobis_distance_sqr_cholesky
rxmc.likelihood_model.log_likelihood

rxmc.predictive.predictive_band
rxmc.predictive.gp_posterior_predictive
rxmc.predictive.total_predictive_band

rxmc.model_comparison.predictive_draws
rxmc.model_comparison.coverage_curve
rxmc.model_comparison.coverage_error
rxmc.model_comparison.sharpness
rxmc.model_comparison.heldout_log_predictive
rxmc.model_comparison.log_posterior_predictive
rxmc.model_comparison.logz_summary
rxmc.model_comparison.compare_logz
rxmc.model_comparison.log_jacobian
rxmc.model_comparison.split_samples

rxmc.walker.Walker
rxmc.param_sampling.Sampler
rxmc.param_sampling.MetropolisHastingsSampler
rxmc.param_sampling.AdaptiveMetropolisSampler
rxmc.param_sampling.BatchedAdaptiveMetropolisSampler
rxmc.proposal.ProposalDistribution
rxmc.proposal.NormalProposalDistribution
rxmc.proposal.HalfNormalProposalDistribution
rxmc.proposal.LogspaceNormalProposalDistribution

rxmc.metropolis_hastings.metropolis_hastings
rxmc.adaptive_metropolis.adaptive_metropolis

rxmc.elastic_diffxs_observation.ElasticDifferentialXSObservation
rxmc.elastic_diffxs_observation.momentum_transfer
rxmc.elastic_diffxs_model.ElasticDifferentialXSModel
rxmc.ias_pn_observation.IsobaricAnalogPNObservation
rxmc.ias_pn_model.IsobaricAnalogPNXSModel

API Reference
rxmc.covariance.averaging

rxmc.covariance.averaging#

rxmc.covariance.averaging(c: TermContext) → ndarray[source]#: 0.5 * (y + ym) — the averaging model-error basis.

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averaging()

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