httomolibgpu.prep.normalize

httomolibgpu.prep.normalize#

Modules for raw projection data normalization

httomolibgpu.prep.normalize.dark_flat_field_correction(data: <cp.ndarray>, flats: <cp.ndarray>, darks: <cp.ndarray>, flats_multiplier: float = 1.0, darks_multiplier: float = 1.0, cutoff: float = 10.0) → <cp.ndarray>[source]#

Normalize raw projection data using the flat and dark field projections.

Parameters:

  • data (cp.ndarray) – Projection data as a CuPy array.

  • flats (cp.ndarray) – 3D flat field data as a CuPy array.

  • darks (cp.ndarray) – 3D dark field data as a CuPy array.

  • flats_multiplier (float) – A multiplier to apply to flats, can work as an intensity compensation constant.

  • darks_multiplier (float) – A multiplier to apply to darks, can work as an intensity compensation constant.

  • cutoff (float) –

    Permitted maximum value for the normalised data.

    Returns

  • -------

  • cp.ndarray – Normalised by dark/flat fields 3D tomographic data as a CuPy array.

httomolibgpu.prep.normalize.minus_log(data: <cp.ndarray>) → <cp.ndarray>[source]#

Apply -log(data) operation

Parameters:

data (cp.ndarray) – Data as a CuPy array.

Returns:

data after -log(data)

Return type:

cp.ndarray

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