plot
- sherpa.astro.ui.plot(*args, **kwargs)
Create one or more plot types.
The plot function creates one or more plots, depending on the arguments it is sent: a plot type, followed by optional identifiers, 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.Changed in version 4.15.0: A number of labels, such as “bkgfit”, are marked as deprecated and using them will cause a warning message to be displayed, indicating the new label to use.
Changed in version 4.12.2: Keyword arguments, such as alpha and ylog, can be sent to each plot.
- Raises
sherpa.utils.err.ArgumentErr – The label is invalid.
See also
get_default_id
Return the default data set identifier.
sherpa.astro.ui.set_analysis
Set the units used when fitting and displaying spectral data.
set_xlinear
New plots will display a linear X axis.
set_xlog
New plots will display a logarithmically-scaled X axis.
set_ylinear
New plots will display a linear Y axis.
set_ylog
New plots will display a logarithmically-scaled Y axis.
Notes
The supported plot types depend on the data set type, and include the following list. There are also individual functions, with
plot_
prepended to the plot type, such asplot_data
. There are also several multiple-plot commands, such asplot_fit_ratio
,plot_fit_resid
, andplot_fit_delchi
.arf
The ARF for the data set (only for
DataPHA
data sets).bkg
The background.
bkg_chisqr
The chi-squared statistic calculated for each bin when fitting the background.
bkg_delchi
The residuals for each bin, calculated as (data-model) divided by the error, for the background.
bkg_fit
The data (as points) and the convolved model (as a line), for the background data set.
bkg_model
The convolved background model.
bkg_ratio
The residuals for each bin, calculated as data/model, for the background data set.
bkg_resid
The residuals for each bin, calculated as (data-model), for the background data set.
bkg_source
The un-convolved background model.
chisqr
The chi-squared statistic calculated for each bin.
data
The data (which may be background subtracted).
delchi
The residuals for each bin, calculated as (data-model) divided by the error.
fit
The data (as points) and the convolved model (as a line).
kernel
The PSF kernel associated with the data set.
model
The convolved model.
model_component
Part of the full model expression (convolved).
order
Plot the model for a selected response
psf
The unfiltered PSF kernel associated with the data set.
ratio
The residuals for each bin, calculated as data/model.
resid
The residuals for each bin, calculated as (data-model).
source
The un-convolved model.
source_component
Part of the full model expression (un-convolved).
The plots can be specialized for a particular data type, such as the
set_analysis
command controlling the units used for PHA data sets.See the documentation for the individual routines for information on how to configure the plots.
The plot capabilities depend on what plotting backend, if any, is installed. If there is none available, a warning message will be displayed when
sherpa.ui
orsherpa.astro.ui
is imported, and theplot
set of commands will not create any plots. The choice of back end is made by changing theoptions.plot_pkg
setting in the Sherpa configuration file.The keyword arguments are sent to each plot (so care must be taken to ensure they are valid for all plots).
Examples
Plot the data for the default data set. This is the same as
plot_data
.>>> plot("data")
Plot the data for data set 2.
>>> plot("data", 2)
Plot the data and ARF for the default data set, in two seaparate plots.
>>> plot("data", "arf")
Plot the fit (data and model) for data sets 1 and 2, in two separate plots.
>>> plot("fit", 1, "fit", 2)
Plot the fit (data and model) for data sets “fit” and “jet”, in two separate plots.
>>> plot("fit", "nucleus", "fit", "jet")
Draw the data and model plots both with a log-scale for the y axis:
>>> plot("data", "model", ylog=True)
Plot the backgrounds for dataset 1 using the “up” and “down” components (in this case the background identifier):
>>> plot("bkg", 1, "up", "bkg", 1, "down")