eradiate.experiments.AtmosphereExperiment

class eradiate.experiments.AtmosphereExperiment(measures=NOTHING, integrator=AUTO, results=NOTHING, default_spectral_set=AUTO, quad_spec=NOTHING, extra_objects=None, illumination=NOTHING, geometry='plane_parallel', atmosphere=NOTHING, surface=NOTHING)

Bases: EarthObservationExperiment

Simulate radiation in a one-dimensional scene. This experiment approximates a one-dimensional setup using a 3D geometry set up to reproduce the effect of invariances typical of 1D geometries. It supports the so-called plane parallel and spherical shell geometries.

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 or AUTO, default: AUTO) – Monte Carlo integration algorithm specification. This parameter can be specified as a dictionary which will be interpreted by integrator_factory.The integrator defaults to AUTO, which will choose the appropriate integrator depending on the experiment’s configuration.

• default_spectral_set (BinSet or WavelengthSet or AUTO, default: AUTO) – Default spectral set. This attribute is used to set the default value for spectral_set.If the value is AUTO, the default spectral set is selected based on the active mode. Otherwise, the value must be a BinSet or WavelengthSet instance.

• extra_objects (dict or None, default: None) – Dictionary of extra objects to be added to the scene. The keys of this dictionary are used to identify the objects in the kernel dictionary.

• illumination (DirectionalIllumination or ConstantIllumination or dict, default: DirectionalIllumination()) – Illumination specification. This parameter can be specified as a dictionary which will be interpreted by illumination_factory.

• geometry (str or dict or SceneGeometry, default: "plane_parallel") – Problem geometry. Can be specified as a simple string ("plane_parallel" or "spherical_shell"), a dictionary interpreted by SceneGeometry.convert(), or a SceneGeometry instance.

• atmosphere (Atmosphere or dict or None, default: HomogeneousAtmosphere()) – Atmosphere specification. If set to None, no atmosphere will be added. This parameter can be specified as a dictionary which will be interpreted by atmosphere_factory.

• surface (BasicSurface or BSDF or dict, optional, default: BasicSurface(bsdf=LambertianBSDF())) – Surface specification. If set to None, no surface will be added. This parameter can be specified as a dictionary which will be interpreted by surface_factory and bsdf_factory.

Fields:

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

• integrator (Integrator or AUTO) – Monte Carlo integration algorithm specification.

• default_spectral_set (BinSet or WavelengthSet) – Default spectral set.

• extra_objects (dict) – Dictionary of extra objects to be added to the scene.

• illumination (AbstractDirectionalIllumination or ConstantIllumination) – Illumination specification.

• geometry (PlaneParallelGeometry or SphericalShellGeometry) – Problem geometry.

• atmosphere (Atmosphere or None) – Atmosphere specification.

• surface (BasicSurface or None) – Surface specification.

Notes

• A post-initialisation step will constrain the measure setup if a distant measure is used and set the target to [0, 0, 0].

• This experiment supports arbitrary measure positioning, except for MultiRadiancemeterMeasure, for which subsensor origins are required to be either all inside or all outside of the atmosphere. If an unsuitable configuration is detected, a ValueError will be raised during initialization.

clear()

Clear previous experiment results and reset internal state.

init()

Generate kernel dictionary and initialise Mitsuba scene.

pipeline(measure)

Return the post-processing pipeline for a given measure.

Parameters:

measure (Measure or int) – Measure for which the pipeline is generated.

Returns:

hamilton.driver.Driver

postprocess()

Post-process raw results and store them in results.

process(spp=0, seed_state=None)

Run simulation and collect raw results.

Parameters:

• spp (int, optional) – Sample count. If set to 0, the value set in the original scene definition takes precedence.

• seed_state (SeedState, optional) – Seed state used to generate seeds to initialize Mitsuba’s RNG at every iteration of the parametric loop. If unset, Eradiate’s root seed state is used.

spectral_indices(measure_index)

Generate spectral indices for a given measure.

Parameters:

measure_index (int) – Measure index for which spectral indices are generated.

Yields:

SpectralIndex – Spectral index.

property context_init

Return a single context used for scene initialization.

property contexts

Return a list of contexts used for processing.

property results

Post-processed simulation results.

Returns:

dict[str, Dataset] – Dictionary mapping measure IDs to xarray datasets.

property scene

Return a scene object used for kernel dictionary template and parameter table generation.

property spectral_set

A dictionary mapping measure index to the associated spectral set.