eradiate.experiments.Experiment#

class eradiate.experiments.Experiment(measures=_Nothing.NOTHING, integrator=_Nothing.NOTHING)[source]#

Bases: abc.ABC

Base class for experiment simulations.

Parameters

measures (list of Measure or list of dict or Measure or dict, default: MultiDistantMeasure()) – List of measure specifications. The passed list may contain dictionaries, which will be interpreted by measure_factory. Optionally, a single Measure or dictionary specification may be passed and will automatically be wrapped into a list.
integrator (Integrator or dict, default: PathIntegrator()) – Monte Carlo integration algorithm specification. This parameter can be specified as a dictionary which will be interpreted by integrator_factory.

Fields

measures (list of Measure) – List of measure specifications.

classmethod from_dict(d)[source]#

Instantiate from a dictionary. The default implementation raises an exception.

Parameters: d (dict) – Dictionary to be converted to an Experiment.
Returns: Experiment

abstract kernel_dict(ctx)[source]#

Return a dictionary suitable for kernel scene configuration.

Parameters: ctx (KernelDictContext) – A context data structure containing parameters relevant for kernel dictionary generation.
Returns: KernelDict – Kernel dictionary which can be loaded as a Mitsuba object.

kernel_dicts(measure)[source]#

A generator which returns kernel dictionaries (and the associated context) relevant to a given measure.

Parameters

measure (Measure or int) – Measure for which kernel dictionaries are to be generated. Alternatively, the index in the self.measure list can be passed.

Yields

kernel_dict (KernelDict) – Generated kernel dictionary.
ctx (KernelDictContext) – Context used to generate kernel_dict.

abstract pipeline(*measures)[source]#

Request post-processing pipeline for a given measure.

Parameters: *measures (Measure or int) – One or several measures for which to get a post-processing pipeline. If integer values are passed, they are used to query the measure list.
Returns: pipelines (Pipeline or tuple of Pipeline) – If a single measure is passed, a single Pipeline instance is returned; if multiple measures are passed, a tuple of pipelines is returned.

postprocess(*measures, pipeline_kwargs=None)[source]#

Post-process raw results stored in a measure’s results field. This requires a successful execution of process(). Post-processed results are stored in self.results.

Parameters

*measures (Measure or int) – One or several measures for which to perform post-processing. Alternatively, indexes in the measure array can be passed. If no value is passed, all measures are processed.
pipeline_kwargs (dict, optional) – A dictionary of pipeline keyword arguments forwarded to Pipeline.transform().

Raises

ValueError – If measure.results is None, i.e. if process() has not been successfully run.