Last modified: December 2024

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/contour.html
AHELP for CIAO 4.17 Sherpa

contour

Context: visualization

Synopsis

Create a contour plot for an image data set.

Syntax

contour(*args, **kwargs)

Description

Create one or more contour plots, depending on the arguments it is set: a plot type, followed by an optional data set identifier, and this can be repeated. If no data set identifier is given for a plot type, the default identifier - as returned by `get_default_id` - is used. This is for 2D data sets.


Examples

Example 1

>>> contour('data')

Example 2

>>> contour('data', 1, 'data', 2)

Example 3

>>> contour('data', 'model')

Example 4

>>> contour('data', 'model', 'fit', 'resid')

Example 5

>>> contour('data', 'model', alpha=0.7)

Example 6

Use a single column rather than single row to display the contour plots:

>>> contour('data', 'model', cols=1)

PARAMETERS

The parameters for this function are:

Parameter Definition
args The contour-plot names and identifiers.
rows The number of rows and columns (if set).
cols The number of rows and columns (if set).
kwargs The plot arguments applied to each contour plot.

Notes

The supported plot types depend on the data set type, and include the following list. There are also individual functions, with contour_ prepended to the plot type, such as `contour_data` and the `contour_fit_resid` variant:

Item Definition
data The data.
fit Contours of the data and the source model.
fit_resid Two plots: the first is the contours of the data and the source model and the second is the residuals.
kernel The kernel.
model The source model including any PSF convolution set by `set_psf` .
psf The PSF.
ratio Contours of the ratio image, formed by dividing the data by the model.
resid Contours of the residual image, formed by subtracting the model from the data.
source The source model (without any PSF convolution set by `set_psf` ).

The keyword arguments are sent to each plot (so care must be taken to ensure they are valid for all plots).

Changes in CIAO

Changed in CIAO 4.17

The keyword arguments can now be set per plot by using a sequence of values. The layout can be changed with the rows and cols arguments and the automatic calculation no longer forces two rows. Handling of the overcontour flag has been improved.

Changed in CIAO 4.13

Keyword arguments, such as alpha, can be sent to each plot.


Bugs

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

See Also

data
copy_data, dataspace1d, dataspace2d, datastack, delete_data, fake, get_axes, get_bkg_chisqr_plot, get_bkg_delchi_plot, get_bkg_fit_plot, get_bkg_model_plot, get_bkg_plot, get_bkg_ratio_plot, get_bkg_resid_plot, get_bkg_source_plot, get_counts, get_data, get_data_contour, get_data_contour_prefs, get_data_image, get_data_plot, get_data_plot_prefs, get_dep, get_dims, get_error, get_quality, get_specresp, get_staterror, get_syserror, group, group_adapt, group_adapt_snr, group_bins, group_counts, group_snr, group_width, load_ascii, load_data, load_grouping, load_image, load_quality, pack_image, set_data, set_quality, ungroup, unpack_ascii, unpack_data, unpack_image
filtering
get_filter, load_filter, set_filter
info
get_default_id, list_data_ids, list_response_ids
modeling
clean, image_model, image_model_component, image_source, image_source_component
plotting
get_split_plot, plot_data, set_xlinear, set_xlog, set_ylinear, set_ylog
psfs
contour_kernel, contour_psf, image_kernel
saving
save_error, save_filter, save_grouping, save_quality, save_staterror, save_syserror
utilities
calc_data_sum, calc_data_sum2d, calc_ftest, calc_kcorr, calc_mlr, calc_model_sum2d, calc_source_sum2d, get_rate
visualization
contour_data, contour_fit, contour_fit_resid, contour_model, contour_ratio, contour_resid, contour_source, histogram1d, histogram2d, image_close, image_data, image_deleteframes, image_fit, image_getregion, image_open, image_ratio, image_resid, image_setregion, image_xpaget, image_xpaset, rebin