coil_combine

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coil_combine#

pulserver.mrd.coil_combine()[source]#

Combine the coil axis of a stack of coil images.

With sensitivity maps, returns the matched filter sum(conj(s) * x), complex and not normalised by the map energy. Without maps, returns the root sum of squares, real.

Parameters:

  • coil_images – NumPy or Torch array with coils along coil_axis.

  • coil_maps – Sensitivities broadcastable against coil_images.

  • coil_axis – Coil axis; the default fits (..., coil, y, x).

Returns:

coil_images without coil_axis.

Return type:

array

Examples

>>> import numpy as np
>>> from pulserver.mrd import coil_combine
>>> coil_images = np.ones((4, 8, 8), dtype=complex)
>>> float(coil_combine(coil_images)[0, 0])
2.0
>>> maps = np.full((4, 8, 8), 0.5, dtype=complex)
>>> complex(coil_combine(coil_images, maps)[0, 0])
(2+0j)
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