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load_table( [id], filename|TABLECrate,
[ncols=2,colkeys=None,dstype=Data1D] )
The load_table command loads tabular data from a FITS table, a
column-based text file, or a TABLECrate object.
The load_ascii command is similar to load_table, but allows
the user to specify the comment character and column separator
used in the input file
("ahelp load_ascii").
-
id - the id of the dataset to use; if not given, uses the default dataset id (id=1 by default, see "ahelp get_default_id")
-
filename|TABLECrate - the name of the file (with path) or
TABLECrate which contains the data
-
ncols - number of columns to read; default=2
-
colkeys - list of column names;
default=None
-
dstype - dataset type: Data1D, Data1DInt, Data2D, Data2DInt;
default=Data1D
The columns to load are specified by a Data Model filter
on the filename or the colkeys option of the load_table
command, as shown in the examples. Vector columns are
separated to form two dstype columns when the file is loaded.
If no columns are specified, the first two columns in the file
are read by default. If column names are not included in the
file, Sherpa calls them "col1", "col2", etc.
The columns must be listed in the order required by the
dataset type:
-
Data1D: x, y,
staterror=None,
syserror=None
-
Data1DInt: xlo, xhi, y,
staterror=None,
syserror=None
-
Data2D: x0, x1, y,
shape=None,
staterror=None,
syserror=None
-
Data2DInt: x0lo, x1lo, x0hi, x1hi, y,
shape=None,
staterror=None,
syserror=None
While possible, it is not recommended that load_table be
used with images (2D dstypes), PHA files, or ARF and RMF
response files. For these cases, use the load command
specific to the filetype instead (e.g. load_image).
sherpa> load_table("rprofile_mid.fits[cols RMID,SUR_BRI,SUR_BRI_ERR]")
sherpa> load_table("rprofile_mid.fits",
colkeys=["RMID","SUR_BRI","SUR_BRI_ERR"])
These commands are equivalent ways of loading x=RMID,
y=SUR_BRI, and staterror=SUR_BRI_ERR from
rprofile_mid.fits, a radial profile for which the midpoint
of the annular regions has been calculated.
sherpa> load_table("rprof", "rprofile.fits[cols
R,SUR_BRI,SUR_BRI_ERR]", dstype=Data1DInt)
sherpa> load_table("rprof", "rprofile.fits",
colkeys=["R","SUR_BRI","SUR_BRI_ERR"], dstype=Data1DInt)
Two ways of loading a radial profile as dataset id "rprof".
The Data1DInt dstype is used in this example so that the
column R, a vector column containing the annulus radii, is
loaded as xlo=R[0], xhi=R[1]; the remaining columns are
y=SUR_BRI, and staterror=SUR_BRI_ERR.
sherpa> load_table(1, "tbl.fits", colkeys=["x", "y", "net_error"])
Three columns are read from the file tbl.fits.
sherpa> load_table(2, "input.dat", ncols=2, colkeys=["col1", "col5"])
Columns "col1" and "col5" are read from the file input.dat
and assigned as dataset id 2.
sherpa> tabcr = read_file("data.tab")
sherpa> load_table(tabcr)
Tabular data is read into a TABLECrate (named "tabcr") from
data.tab. The table is then loaded into Sherpa from the
crate, using the default options.
- py.sherpa
-
add_user_pars,
dataspace1d,
dataspace2d,
get_default_id,
list_bkg_ids,
list_data_ids,
load_arf,
load_arrays,
load_ascii,
load_bkg,
load_bkg_arf,
load_bkg_rmf,
load_data,
load_image,
load_multi_arfs,
load_multi_rmfs,
load_pha,
load_rmf,
load_table_model,
load_user_model,
pack_image,
pack_pha,
pack_table,
save_data,
save_image,
save_pha,
save_table,
unpack_arf,
unpack_arrays,
unpack_ascii,
unpack_bkg,
unpack_data,
unpack_image,
unpack_pha,
unpack_rmf,
unpack_table
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