generate_projections

esis.data.inversion.mart.helper.generate_projections(data, angles, spectral_order=1, poisson_noise=False, rotation_kwargs={'mode': 'nearest', 'order': 3, 'prefilter': False, 'reshape': False}, projection_shape=None)

Given a data cube a list of angles, create a projection through the cube for each of those angles at the given spectral order. :type poisson_noise: bool :param poisson_noise: if True, add poisson noise to the projection :type data: numpy.ndarray :param data: :type angles: astropy.units.Quantity :param angles: array of angles, must be astropy.units.Quantity, as the forward model takes this as an input :type spectral_order: int :param spectral_order: :rtype: numpy.ndarray :return:

Parameters
Return type

numpy.ndarray