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Open a contour plot in ChIPS
contour(contour1, [id1] ... [contourn, idn])
The contour() function opens contour plots in ChIPS to allow
the user to visualize contours of a data set,
model, fit, fit residuals, data-to-model ratio, or PSF, by
dataset id.
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contour1 ... contourn - the type of contour ('data', 'fit', etc.)
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id1 ... idn - the id of the dataset to use for each contour;
if not given, uses the default dataset id (id=1 by default, see "ahelp get_default_id")
sherpa> contour( "data", 3)
A contour plot of data set 3 is visualized in ChIPS with this command.
sherpa> contour( "data", "model", "fit", "resid" )
Here, a combination contour plot displays the data, model,
fit, and fit residuals of the default data set in separate
tiles of the ChIPS display, all to the same scale.
sherpa> contour( "data", "bkg", "model", "bkg")
Contour plots of background data set "bkg" and its assigned
model are sent to ChIPS for visualization.
- py.sherpa
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calc_data_sum,
calc_data_sum2d,
calc_ftest,
calc_kcorr,
calc_mlr,
calc_model_sum2d,
calc_source_sum2d,
clean,
contour_data,
contour_fit,
contour_fit_resid,
contour_model,
contour_psf,
contour_ratio,
contour_resid,
contour_source,
copy_data,
dataspace1d,
dataspace2d,
delete_data,
get_axes,
get_bkg_plot,
get_counts,
get_data,
get_data_plot,
get_default_id,
get_dep,
get_dims,
get_error,
get_filter,
get_rate,
get_ratio,
get_resid,
get_specresp,
group,
histogram1d,
histogram2d,
image_close,
image_data,
image_deleteframes,
image_fit,
image_getregion,
image_model,
image_open,
image_ratio,
image_resid,
image_setregion,
image_source,
image_xpaget,
image_xpaset,
list_data_ids,
list_response_ids,
load_ascii,
load_data,
load_image,
pack_image,
plot_data,
rebin,
set_data,
ungroup,
unpack_ascii,
unpack_data,
unpack_image
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