PYME.Analysis.Colocalisation.edtColoc module¶

PYME.Analysis.Colocalisation.edtColoc.imageDensityAtDistance(A, mask, voxelsize=None, bins=100, roi_mask=None)

Calculates the distribution of a label at varying distances from a mask. Negative distances are on the inside of the mask.

Parameters: A - intensity image mask - binary mask voxelsize - size of the pixels/voxels - should be either a constant, or an iterable

with a length equal to the number of dimensions in the data

bins - either a number of bins, or an array of bin edges

Returns: bn - number of pixels in distance bin bm - mean intensity in distance bin bins - the bin edges

PYME.Analysis.Colocalisation.edtColoc.pointDensityAtDistance(points, mask, voxelsize, maskOffset, bins=100)

Calculates the distribution of a label at varying distances from a mask. Negative distances are on the inside of the mask.

Parameters: points - array containing point coordinates mask - binary mask voxelsize - size of the pixels/voxels in mask - should be an iterable

with a length equal to the number of dimensions in the data
maskOffset - iterable with lengh equal to number of dims giving coordinates (in point space)
or the 0th pixel in the mask

bins - either a number of bins, or an array of bin edges

Returns: bn - integrated intensity in distance bin bm - mean intensity in distance bin bins - the bin edges