eradiate.scenes.measure.Measure
eradiate.scenes.measure.Measure#
- class eradiate.scenes.measure.Measure(id='measure', spectral_cfg=_Nothing.NOTHING, spp=1000, split_spp=None)[source]#
Bases:
eradiate.scenes.core.SceneElement
,abc.ABC
Abstract base class for all measure scene elements.
- Parameters
id (
str
, optional, default:"measure"
) – User-defined object identifier.spectral_cfg (
MeasureSpectralConfig
ordict
, default:MeasureSpectralConfig.new()
) – Spectral configuration of the measure. Must match the current operational mode. Can be passed as a dictionary, which will be interpreted byMeasureSpectralConfig.from_dict()
.spp (
int
, default:1000
) – Number of samples per pixel.split_spp (
int
, optional) – If set, this measure will be split into multiple sensors, each with a sample count lower or equal to split_spp. This parameter should be used in single-precision modes when the sample count is higher than 100,000 (very high sample count might result in floating point number precision issues otherwise).
- Fields
spectral_cfg (
MeasureSpectralConfig
) – Spectral configuration of the measure.spp (
int
) – Number of samples per pixel.split_spp (
int
) – If set, this measure will be split into multiple sensors, each with a sample count lower or equal to split_spp.
See also
Notes
Raw results stored in the results field as nested dictionaries with the following structure:
{ spectral_key_0: dict_0, spectral_key_1: dict_1, ... }
Keys are spectral loop indexes; values are nested dictionaries produced by
mitsuba_run()
.- abstract kernel_dict(ctx)#
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.
- property sensor_dims#
List of sensor dimension labels.
- Type
tuple of str