CubeMosaic¶

class
mpdaf.obj.
CubeMosaic
(files, output_wcs, **kwargs)[source]¶ Bases:
mpdaf.obj.CubeList
Manages a list of cubes and handles the combination to make a mosaic.
To run the combination, all the cubes must be on the same WCS grid. The values from the
CRPIX
keywords will be used as offsets to put each cube inside the combined cube. The shape and WCS grid of the output cube is determined using from a FITS file specified with theoutput_wcs
argument (same principle as the MUSE pipeline).This class inherits from
mpdaf.obj.CubeList
, but not all the combination commands are available: currently onlyCubeMosaic.pycombine
is implemented.Parameters: files : list of str
List of cubes FITS filenames.
output_wcs : str
Path to a cube FITS file, this cube is used to define the output cube: shape, WCS and unit are needed, it must have the same WCS grid as the input cubes.
Attributes
files (list of str) List of cubes FITS filenames. nfiles (int) Number of files. shape (array of 3 integers) Lengths of data in Z and Y and X (python notation (nz,ny,nx)). wcs ( mpdaf.obj.WCS
) World coordinates.wave ( mpdaf.obj.WaveCoord
) Wavelength coordinatesunit (str) Possible data unit type. None by default. Attributes Summary
checkers
Methods Summary
check_compatibility
()Checks if all cubes are compatible. check_dim
()Checks if all cubes have same dimensions. check_wcs
()Checks if all cubes use the same projection. combine
()This method is not implemented for CubeMosaic. info
([verbose])Print information. median
()This method is not implemented for CubeMosaic. pycombine
([nmax, nclip, var, nstop, nl, …])Combines cubes in a single data cube using sigma clipped mean. pymedian
()This method is not implemented for CubeMosaic. save_combined_cube
(data[, var, method, …])Attributes Documentation

checkers
= ('check_dim', 'check_wcs')¶
Methods Documentation

check_compatibility
()¶ Checks if all cubes are compatible.

pycombine
(nmax=2, nclip=5.0, var='propagate', nstop=2, nl=None, header=None, mad=False)[source]¶ Combines cubes in a single data cube using sigma clipped mean.
This is less optimized but more flexible version, compared to
CubeList.combine
. It is useful mostly forCubeMosaic
, where we need to shift the individual cubes into the output one.Parameters: nmax : int
Maximum number of clipping iterations.
nclip : float or tuple of float
Number of sigma at which to clip. Single clipping parameter or lower / upper clipping parameters.
nstop : int
If the number of not rejected pixels is less than this number, the clipping iterations stop.
var : {‘propagate’, ‘stat_mean’, ‘stat_one’}
propagate
: the variance is the sum of the variances of the N individual exposures divided by N**2.
stat_mean
: the variance of each combined pixel is computed as the variance derived from the comparison of the N individual exposures divided N1.
stat_one
: the variance of each combined pixel is computed as the variance derived from the comparison of the N individual exposures.
mad : bool
Use MAD (median absolute deviation) statistics for sigmaclipping.
Returns: cube :
Cube
The merged cube.
expmap:
mpdaf.obj.Cube
Exposure map data cube which counts the number of exposures used for the combination of each pixel.
statpix:
astropy.table.Table
Table that gives the number of NaN pixels and rejected pixels per exposures (columns are FILENAME, NPIX_NAN and NPIX_REJECTED).
rejmap:
Cube
Cube which contains the number of rejected values for each pixel.

save_combined_cube
(data, var=None, method='', keywords=None, expnb=None, unit=None, header=None)¶
