decode_context

drizzle.utils.decode_context(context, x, y)[source]

Get 0-based indices of input images that contributed to (resampled) output pixel with coordinates x and y.

Parameters:

  • context (numpy.ndarray) – A 3D ~numpy.ndarray of integral data type.

  • x (int, list of integers, numpy.ndarray of integers) – X-coordinate of pixels to decode (3rd index into the context array)

  • y (int, list of integers, numpy.ndarray of integers) – Y-coordinate of pixels to decode (2nd index into the context array)

Returns:

  • A list of numpy.ndarray objects each containing indices of input images

  • that have contributed to an output pixel with coordinates x and y.

  • The length of returned list is equal to the number of input coordinate

  • arrays x and y.

Examples

An example context array for an output image of array shape (5, 6) obtained by resampling 80 input images.

>>> import numpy as np
>>> from drizzle.utils import decode_context
>>> ctx = np.array(
...     [[[0, 0, 0, 0, 0, 0],
...       [0, 0, 0, 36196864, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 537920000, 0, 0, 0]],
...      [[0, 0, 0, 0, 0, 0,],
...       [0, 0, 0, 67125536, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 163856, 0, 0, 0]],
...      [[0, 0, 0, 0, 0, 0],
...       [0, 0, 0, 8203, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 0, 0, 0, 0],
...       [0, 0, 32865, 0, 0, 0]]],
...     dtype=np.int32
... )
>>> decode_context(ctx, [3, 2], [1, 4])
[array([ 9, 12, 14, 19, 21, 25, 37, 40, 46, 58, 64, 65, 67, 77]),
 array([ 9, 20, 29, 36, 47, 49, 64, 69, 70, 79])]