swiftemulator.backend.emulator_generator module

Emulator generation object.

class swiftemulator.backend.emulator_generator.EmulatorGenerator(model_specification: swiftemulator.backend.model_specification.ModelSpecification, model_parameters: swiftemulator.backend.model_parameters.ModelParameters)[source]

Bases: object

Generator for emulators for individual scaling relations.

Parameters

  • model_specification (ModelSpecification) – Full instance of the model specification.

  • model_parameters (ModelParameters) – Full instance of the model parameters.

Notes

The required initialisation parameters are shared amongst all emulators that the emulator generator produces.

model_specification: swiftemulator.backend.model_specification.ModelSpecification
model_parameters: swiftemulator.backend.model_parameters.ModelParameters
create_gaussian_process_emulator(model_values: swiftemulator.backend.model_values.ModelValues) → swiftemulator.emulators.gaussian_process.GaussianProcessEmulator[source]

Creates an individual emulator for an individual scaling relation described by the provided model_values.

Parameters

  • model_values – The model values structure for this given scaling relation. This specifies the training data for the emulator.

  • ModelValues – The model values structure for this given scaling relation. This specifies the training data for the emulator.

Returns

The built and trained emulator ready for prediction steps.

Return type

emulator, GaussianProcessEmulator

create_gaussian_process_emulator_mcmc(model_values: swiftemulator.backend.model_values.ModelValues) → swiftemulator.emulators.gaussian_process_mcmc.GaussianProcessEmulatorMCMC[source]

Creates the object needed for the hyperparameter_investigator function

Parameters

  • model_values – The model values structure for this given scaling relation. This specifies the training data for the emulator.

  • ModelValues – The model values structure for this given scaling relation. This specifies the training data for the emulator.

Returns

The built emulator ready for analysis of hyperparameters

Return type

emulator, GaussianProcessEmulatorMCMC

create_gaussian_process_emulator_bins(model_values: swiftemulator.backend.model_values.ModelValues) → swiftemulator.emulators.gaussian_process_bins.GaussianProcessEmulatorBins[source]

Creates the object needed for the binned emulator

Parameters

  • model_values – The model values structure for this given scaling relation. This specifies the training data for the emulator.

  • ModelValues – The model values structure for this given scaling relation. This specifies the training data for the emulator.

Returns

The built emulator ready for analysis of hyperparameters

Return type

emulator, GaussianProcessEmulatorMCMC

create_linear_model_emulator(model_values: swiftemulator.backend.model_values.ModelValues) → swiftemulator.emulators.linear_model.LinearModelEmulator[source]

Creates an individual emulator for an individual scaling relation described by the provided model_values.

Parameters

  • model_values – The model values structure for this given scaling relation. This specifies the training data for the emulator.

  • ModelValues – The model values structure for this given scaling relation. This specifies the training data for the emulator.

Returns

The built and trained emulator ready for prediction steps.

Return type

emulator, LinearModelEmulator