- sherpa.astro.ui.unpack_table(filename, ncols=2, colkeys=None, dstype=<class 'sherpa.data.Data1D'>)
Unpack a FITS binary file into a data structure.
filename – Identify the file to read: a file name, or a data structure representing the data to use, as used by the I/O backend in use by Sherpa: a
TABLECratefor crates, as used by CIAO, or a list of AstroPy HDU objects.
ncols (int, optional) – The number of columns to read in (the first
ncolscolumns in the file). The meaning of the columns is determined by the
colkeys (array of str, optional) – An array of the column name to read in. The default is
dstype (optional) – The data class to use. The default is
Data1Dand it is expected to be derived from
The class of the returned object is controlled by the
- Return type
Load a FITS binary file as a data set.
Set a data set.
Unpack an ASCII file into a data structure.
Read in the first two columns of the file, as the independent (X) and dependent (Y) columns of a data set:
>>> d = unpack_table('sources.fits')
Read in the first three columns (the third column is taken to be the error on the dependent variable):
>>> d = unpack_table('sources.fits', ncols=3)
Read in from columns ‘RMID’ and ‘SUR_BRI’:
>>> d = unpack_table('rprof.fits', colkeys=['RMID', 'SUR_BRI'])
The first three columns are taken to be the two independent axes of a two-dimensional data set (
x1) and the dependent value (
>>> d = unpack_table('fields.fits', ncols=3, ... dstype=sherpa.astro.data.Data2D)
When using the Crates I/O library, the file name can include CIAO Data Model syntax, such as column selection. This can also be done using the
colkeysparameter, as shown above:
>>> d = unpack_table('rprof.fits[cols rmid,sur_bri,sur_bri_err]', ... ncols=3)