CubeList¶
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class
mpdaf.obj.
CubeList
(files, scalelist=None)[source]¶ Bases:
object
Manages a list of cubes and handles the combination.
To run the combination, all the cubes must have the same dimensions and be on the same WCS grid.
Parameters: files : list of str
List of cubes FITS filenames.
scalelist: list of float, optional
List of scales to be applied to each cube.
Attributes
files (list of str) List of cubes FITS filenames. nfiles (int) Number of files. scales (list of doubles) List of scales shape (tuple) 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 have same world coordinates. combine
([nmax, nclip, nstop, var, mad, header])combines cubes in a single data cube using sigma clipped mean. info
([verbose])Print information. median
([header])Combines cubes in a single data cube using median. pycombine
([nmax, nclip, var, nstop, nl, header])pymedian
([header])save_combined_cube
(data[, var, method, ...])Attributes Documentation
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checkers
= ('check_dim', 'check_wcs')¶
Methods Documentation
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combine
(nmax=2, nclip=5.0, nstop=2, var='propagate', mad=False, header=None)[source]¶ combines cubes in a single data cube using sigma clipped mean.
Parameters: nmax : int
maximum number of clipping iterations
nclip : float or (float,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 : str
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 N-1.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 sigma-clipping
Returns: out :
Cube
,mpdaf.obj.Cube
, astropy.tablecube, expmap, statpix
cube
will contain the merged cubeexpmap
will contain an exposure map data cube which counts the number of exposures used for the combination of each pixel.statpix
is a table that will give the number of Nan pixels and rejected pixels per exposures (columns are FILENAME, NPIX_NAN and NPIX_REJECTED)
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median
(header=None)[source]¶ Combines cubes in a single data cube using median.
Returns: out :
Cube
,mpdaf.obj.Cube
, Tablecube, expmap, statpix
cube
will contain the merged cubeexpmap
will contain an exposure map data cube which counts the number of exposures used for the combination of each pixel.statpix
is a table that will give the number of Nan pixels pixels per exposures (columns are FILENAME and NPIX_NAN)
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