pymf.filter_map_cmmf

pymf.filter_map_cmmf(images, sources, spec, response, noise_maps=None, sigma_noise=None, no_cross=False, global_cross=False)

Computes and applies a constrained matched multifilter to a set of multi-frequency map. The filter is build from provided spatial and spectral source templates and the cross spectrum of a set of maps at different frequencies.

Parameters:

images: 3D float array

Data cube containing the input images that are provided at n_f frequencies. The dimensions are supposed to be n_f * n_x * n_y, where n_x and n_y are the number of pixels along the * and y axis of the images.

sources: 3D or 4D float array

Source templates of the n_c components. Can either be a n_c * n_x * n_y data cube or alternatively a hypercube of dimensions n_c * n_f * n_x * n_y if each image comes at a different spatial resolution.

spec: 2D float array

SEDs of the sources. Needs to be provided at the same n_f frequencies as the input images. Dimensions are n_c * n_f.

response: float array

Array containing the desired response of the filter to each provided source template.

noise_maps: 3D float array, optional

Data cube containing provided noise maps that will be used to compute noise power spectrum matrix. Otherwise the noise power spectrum matrix is directly computed from the images. noise_maps need to have the same dimensions as images. Default: None

sigma_noise: float array, optional

Array containing the standard deviation of the noise for the n_f maps. Does allow the analytic computation of the noise power spectrum. Useful for tests with white noise. Default: None

no_cross: bool, optional

If True the frequency-to-frequency covariance of the n_f maps will be ignored, i.e. non-diagonal elements of the noise power spectrum matrix are set to zero. Default: False

global_cross: bool, optional

If set to True, the cross power of the maps is computed globally (i.e. averaged over the full maps / all scales). If False, the cross power is computed at each spatial frequency. Default: False

Returns:

filtered_image: 2D float array

Linear combination of the images convolved with the computed constrained matched multifilter.

filter_ft: 3D float array

Data cube containing the 2D window functions of the constrained matched multifilter.

noise: float

Noise level of the filtered map.