slmsuite.holography.analysis.image_positions

image_positions(images, grid=None, normalize=True, nansum=False)

Computes the two first order moments, equivalent to spot position \(\left<x\right>\) relative to image center, for a stack of images. Specifically, returns \(M_{10}\) and \(M_{01}\).

Parameters:

• images (numpy.ndarray) – A matrix in the style of the output of take(), with shape (image_count, h, w), where (h, w) is the width and height of the 2D images and image_count is the number of images. A single image is interpreted correctly as (1, h, w) even if (h, w) is passed.

• grid (float OR (float, float) OR (array_like, array_like) OR None) –

  If None (the default), the moment is reported in pixels of the image. However, the user may specify other units:

  • Providing the scaling factor between pixels and the desired units as a float or an anisotropic (float, float). This corresponds to the pixel’s \(\Delta x\), \(\Delta y\).

  • Providing lists of length w and h as a tuple as the grid dimension.

  • Providing full grids of shape (w, h) in each direction. Note that this case is the most general, and can lead to a rotated grid if a transformed grid is provided.

• normalize (bool) – Whether to normalize images. If False, normalization is assumed to have been precomputed.

• nansum (bool) – Whether to use numpy.nansum() in place of numpy.sum().

Returns:

Stack of \(M_{10}\), \(M_{01}\) in an array of shape (2, image_count).

Return type:

numpy.ndarray