How can I create multiple plots in the same window? 

In the following we assume you have two data sets loaded with ids of 1 (i.e. the default) and 2, that you have done the following

sherpa> set_xlog()
sherpa> set_ylog()

and that fits have been made to both data sets.

If you wish to display multiple datasets in the same plot window then you can use the plot command; for example if you have two datasets with ids of 1 and 2 then:

sherpa> plot("data", 1, "data", 2)

will display each data set in a separate plot in the same window (Figure 1).

Figure 1: Plotting multiple data sets

Figure 1: Plotting multiple data sets

The default layout of the plots is not guaranteed to be free of overlaps of plot elements, such as the X-axis label of the top plot and the title of the second plot.

Parameters can be applied to all plots, such as setting the X-axis to a linear scale:

sherpa> plot("data", 1, "data", 2, xlog=False)

You can display more than two plots, for instance (Figure 2):

sherpa> plot('fit', 1, 'fit', 2, 'delchi', 1, 'delchi', 2)

Figure 2: Plotting fit and residuals

Figure 2: Plotting fit and residuals

The overlapping of labels is present and the Y axes of the plots are also not the same, which makes cross comparison difficult.

The spacing and layout of the plots can be adjusted using Matplotlib.

Plot options can be specified for all plots (when a scalar, such as a single color):

sherpa> plot('fit', 'fit', 2, color='black')

Figure 3: Changing plot properties

Figure 3: Changing plot properties

Plot options can also per per-plot, and each plot can have a different number of datasets (this is new in CIAO 4.18 ). In this example. the first two plots are set to the data and models for datasets 1 and 2, and the last (bottom) plot is the residuals for both datasets. The colors of this last plot are set so that the residual plot color matches the fit results.

sherpa> col1 = 'gray'
sherpa> col2 = 'green'
sherpa> colors = [col1, col2, [col1, col2]]
sherpa> plot('fit', 'fit', 2, 'resid', [1, 2], color=colors, cols=1)

Figure 4: Multiple color settings

Figure 4: Multiple color settings

If more than two plots are created then the default is to pick a multi-column display. This can be over-ridden by setting the cols or rows argument (or both). In this case setting cols=1 ensures the display uses a single column rather than a 2 by 2 grid such as used in Figure 2.

A version of this plot is also included in the using Matplotlib FAQ entry.

New in CIAO 4.18 is the use of the ids argument to apply a set of identifiers to each plot type. For example, a fit and residual plot (Figure 5) can be generated with:

sherpa> plot('fit', 'resid', ids=[1, 2], alpha=0.5)

Figure 5: Using the ids argument

Figure 5: Using the ids argument

A version of this plot is also included in the using Matplotlib FAQ entry.