FieldsMap

class mpdaf.MUSE.FieldsMap(filename=None, nfields=None, **kwargs)

Bases: object

Class to work with the mosaic field map.

Parameters:

filename : str

Name of the FITS file containing the field map. Use extname='FIELDMAP' to read the field map from an extension the MUSE data cube.

nfields : int

Number of fields.

Methods Summary

compute_weights()	Return a list of weight maps (one per fields).
get_FSF(y, x, kernels[, weights])	Return the local FSF.
get_field_mask(field_name)	Return an array with non-zeros values for pixels matching a field.
get_pixel_fields(y, x)	Return a list of fields that cover a given pixel (y, x).
get_pixel_fields_indexes(y, x)	Return a list of fields indexes (between 0 and nfields) that cover a given pixel (y, x).
variable_PSF_convolution(img, kernels[, weights])	Function used for the convolution of an image by a set of PSF.

Methods Documentation

compute_weights()

Return a list of weight maps (one per fields). The weight gives the influence of the field for each pixel. In the overlap area the weight changes linearly to have a smooth transition.

get_FSF(y, x, kernels, weights=None)

Return the local FSF.

Parameters:

y : integer

Pixel coordinate along the y-axis.

x : integer

Pixel coordinate along the x-axis.

kernels : list of np.array

List of FSF.

weights : list of np.array

List of corresponding weights maps. Computed by compute_weights by default.

get_field_mask(field_name)

Return an array with non-zeros values for pixels matching a field.

field_name can be an integer (between 1 and nfields+1) or a string (e.g. UDF-03).

get_pixel_fields(y, x)

Return a list of fields that cover a given pixel (y, x).

get_pixel_fields_indexes(y, x)

Return a list of fields indexes (between 0 and nfields) that cover a given pixel (y, x).

variable_PSF_convolution(img, kernels, weights=None)

Function used for the convolution of an image by a set of PSF.

We use shift-variant blur techniques to model the variation of the PSF.

Reference: Denis, L. Thiebaut E., Soulez F., Becker J.-M. and Mourya R.

‘Fast approximations of shift-variant blur’, International Journal of Computer Vision, Springer Verlag, 115(3), 253-278 (2015)

Parameters:

img : np.array

Image to convolve.

kernels : list(np.array)

List of convolution kernels.

weights : list of np.array

List of corresponding weights maps. Computed by compute_weights by default.