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
 Attributes
 files
list
ofstr
List of cubes FITS filenames.
 nfiles
int
Number of files.
 shape
array
of 3integers
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 coordinates
 unit
str
Possible data unit type. None by default.
 files
Attributes Summary
Methods Summary
check_compatibility
(self)Checks if all cubes are compatible.
check_dim
(self)Checks if all cubes have same dimensions.
check_wcs
(self)Checks if all cubes use the same projection.
combine
(self)This method is not implemented for CubeMosaic.
info
(self[, verbose])Print information.
median
(self)This method is not implemented for CubeMosaic.
pycombine
(self[, nmax, nclip, var, nstop, …])Combines cubes in a single data cube using sigma clipped mean.
pymedian
(self)This method is not implemented for CubeMosaic.
save_combined_cube
(self, data[, var, …])Attributes Documentation

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

check_compatibility
(self)¶ Checks if all cubes are compatible.

pycombine
(self, 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
ortuple
offloat
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.
 madbool
Use MAD (median absolute deviation) statistics for sigmaclipping.
 nmax
 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.
 cube

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