get_axes
- sherpa.astro.ui.get_axes(id=None, bkg_id=None)
Return information about the independent axes of a data set.
This function returns the coordinates of each point, or pixel, in the data set. The
get_indep
function may be be preferred in some situations.- Parameters:
id (int or str, optional) – The identifier for the data set to use. If not given then the default identifier is used, as returned by
get_default_id
.bkg_id (int or str, optional) – Set if the values returned should be from the given background component, instead of the source data set.
- Returns:
axis – The independent axis values. The differences to
get_dep
that this represents the “alternate grid” for the axis. For PHA data, this is the energy grid (E_MIN and E_MAX). For image data it is an array for each axis, of the length of the axis, using the current coordinate system for the data set.- Return type:
tuple of arrays
- Raises:
sherpa.utils.err.IdentifierErr – If the data set does not exist.
See also
get_indep
Return the independent axis of a data set.
list_data_ids
List the identifiers for the loaded data sets.
Examples
For 1D data sets, the “alternate” view is the same as the independent axis:
>>> load_arrays(1, [10, 15, 19], [4, 5, 9], Data1D) >>> get_indep() array([10, 15, 19]) >>> get_axes() array([10, 15, 19])
For a PHA data set, the approximate energy grid of the channels is returned (this is determined by the EBOUNDS extension of the RMF).
>>> load_pha('core', 'src.pi') read ARF file src.arf read RMF file src.rmf read background file src_bkg.pi >>> (chans,) = get_indep() >>> (elo, ehi) = get_axes() >>> chans[0:5] array([ 1., 2., 3., 4., 5.]) >>> elo[0:5] array([ 0.0073, 0.0146, 0.0292, 0.0438, 0.0584]) >>> ehi[0:5] array([ 0.0146, 0.0292, 0.0438, 0.0584, 0.073 ])
The image has 101 columns by 108 rows. The
get_indep
function returns one-dimensional arrays, for the full dataset, whereasget_axes
returns values for the individual axis:>>> load_image('img', 'img.fits') >>> get_data('img').shape (108, 101) >>> set_coord('img', 'physical') >>> (x0, x1) = get_indep('img') >>> (a0, a1) = get_axes('img') >>> (x0.size, x1.size) (10908, 10908) >>> (a0.size, a1.size) (101, 108) >>> np.all(x0[:101] == a0) True >>> np.all(x1[::101] == a1) True