BinConvolutionEntry#

class exo_skryer.registry_bandpass.BinConvolutionEntry(method: str, wavelengths: ndarray, weights: ndarray, norm: float, indices: Tuple[int, int], bin_edges: Tuple[float, float])[source]#

Bases: object

Holds information needed to convolve a single observational bin at runtime. Note: During preprocessing, all arrays are NumPy (CPU) They get converted to JAX (device) only at the final cache creation step All arrays kept as float64 for maximum accuracy in bandpass convolution

Attributes Summary

`bin_edges`
`indices`
`method`
`norm`
`wavelengths`
`weights`

Attributes Documentation

bin_edges: Tuple[float, float] = <dataclasses._MISSING_TYPE object>#

indices: Tuple[int, int] = <dataclasses._MISSING_TYPE object>#

method: str = <dataclasses._MISSING_TYPE object>#

norm: float = <dataclasses._MISSING_TYPE object>#

wavelengths: ndarray = <dataclasses._MISSING_TYPE object>#

weights: ndarray = <dataclasses._MISSING_TYPE object>#