wf_psf.data.handlers
Field-specific dataset preprocessing handlers.
This module defines specialized transformation handlers used during schema-driven dataset conversion. Handlers encapsulate field-level preprocessing logic that cannot be performed through generic tensor conversion alone.
Handlers are registered through DatasetSchema definitions and
invoked dynamically by dataset converters during training, evaluation,
or inference workflows.
Typical responsibilities include:
Spectral energy distribution (SED) preprocessing
Instrument-specific tensor transformations
Physics-aware feature conversion
Domain-specific data normalization
Handlers receive both raw dataset values and runtime conversion contexts, allowing preprocessing operations to access external dependencies such as PSF simulators or instrument configuration objects without coupling these concerns to the converter itself.
Notes
The handler system is intentionally extensible and designed to support additional scientific domains and instrument pipelines beyond the current Euclid-specific workflows.
Functions
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Process SEDS handler. |
- wf_psf.data.handlers.process_seds_handler(converter, dataset, sed_context)[source]
Process SEDS handler.
- Parameters:
converter (TensorFlowDataSetConverter) – TensorFlow dataset converter instance
dataset (array_like) – Array of SEDS, shape (N, n_wavelengths) or similar
sed_context (SEDContext) – Context object containing parameters required for SED processing