Last modified: December 2020

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/load_table.html
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AHELP for CIAO 4.13 Sherpa v1

load_table

Context: data

Synopsis

Load a FITS binary file as a data set.

Syntax

load_table(id, filename=None, ncols=2, colkeys=None, dstype=Data1D)

id - int or str, optional
ncols - int, optional
colkeys - array of str, optional
dstype - optional

Examples

Example 1

Read in the first two columns of the file, as the independent (X) and dependent (Y) columns of the default data set:

>>> load_table('sources.fits')

Example 2

Read in the first three columns (the third column is taken to be the error on the dependent variable):

>>> load_table('sources.fits', ncols=3)

Example 3

Read in from columns 'RMID' and 'SUR_BRI' into data set 'prof':

>>> load_table('prof', 'rprof.fits',
...            colkeys=['RMID', 'SUR_BRI'])

Example 4

The first three columns are taken to be the two independent axes of a two-dimensional data set ( x0 and x1 ) and the dependent value ( y ):

>>> load_table('fields.fits', ncols=3,
...            dstype=sherpa.astro.data.Data2D)

Example 5

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 colkeys parameter, as shown above:

>>> load_table('prof',
...            'rprof.fits[cols rmid,sur_bri,sur_bri_err]',
...            ncols=3)

Example 6

Read in a data set using Crates:

>>> cr = pycrates.read_file('table.fits')
>>> load_table(cr)

Example 7

Read in a data set using AstroPy:

>>> hdus = astropy.io.fits.open('table.fits')
>>> load_table(hdus)

PARAMETERS

The parameters for this function are:

Parameter Definition
id The identifier for the data set to use. If not given then the default identifier is used, as returned by `get_default_id` .
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 tablecrate for crates, as used by CIAO, or a list of AstroPy HDU objects.
ncols The number of columns to read in (the first ncols columns in the file). The meaning of the columns is determined by the dstype parameter.
colkeys An array of the column name to read in. The default is none .
dstype The data class to use. The default is `Data1D` .

Notes

The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the `filename` parameter. If given two un-named arguments, then they are interpreted as the `id` and `filename` parameters, respectively. The remaining parameters are expected to be given as named arguments.

The column order for the different data types are as follows, where x indicates an independent axis and y the dependent axis:

Identifier Required Fields Optional Fields
Data1D x, y statistical error, systematic error
Data1DInt xlo, xhi, y statistical error, systematic error
Data2D x0, x1, y shape, statistical error, systematic error
Data2DInt x0lo, x1lo, x0hi, x1hi, y shape, statistical error, systematic error

Bugs

See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.

See Also

data
dataspace1d, dataspace2d, datastack, fake, load_arf, load_arrays, load_ascii, load_bkg, load_bkg_arf, load_bkg_rmf, load_data, load_grouping, load_image, load_multi_arfs, load_multi_rmfs, load_pha, load_quality, load_rmf, load_staterror, load_syserror, pack_image, pack_pha, pack_table, unpack_arf, unpack_arrays, unpack_ascii, unpack_bkg, unpack_data, unpack_image, unpack_pha, unpack_rmf, unpack_table
filtering
load_filter
info
get_default_id, list_bkg_ids, list_data_ids
modeling
add_model, add_user_pars, load_table_model, load_template_interpolator, load_template_model, load_user_model, save_model, save_source
saving
save_arrays, save_data, save_delchi, save_error, save_filter, save_grouping, save_image, save_pha, save_quality, save_resid, save_staterror, save_syserror, save_table
statistics
load_user_stat