helper

Functions

add_poisson_noise(image)

Given a data array, add poisson type noise :type image: numpy.ndarray :param image: :return: image with poisson noise added

generate_projections(data, angles[, …])

Given a data cube a list of angles, create a projection through the cube for each of those angles at the given spectral order.

good_mosaics()

I found that there are a number of mosaics in the “mosaics.download()” function that are not 6000px wide, and so they are not useful for the tests I am doing, as the image_setup below requires 6000px.

image_setup(fits_file, x_range, y_range, …)

Sets up an image for use in MART from a given FITS file.

result_to_moments(recovered, …[, wscale, axis])

Classes

Moments(intensity, shift, width, skew, metadata)