Make one or more plots to the current plot device (see setplot device).
Syntax: plot <plot type> [ <plot type>]
<plot type> is a keyword describing the various plots allowed.Any of the options counts, data, or ldata can be followedby a second option, which should be one of chisq, delchi, ratio, residuals, or none. If one of these second options is given, then a two-pane plot is drawn with the first option in the upper pane and the second option in the lower. (see also iplot)
Plot only the background spectra (with folded model, if defined). To plot both the data and background spectra, use plot data with the setplot background option.
Plot contributions to chisq. The contribution is plotted +ve or –ve depending on whether the residual is +ve or –ve.
Plot a two-dimensional fit-statistic contour plot of the last steppar run.
plot contour [ <min fit stat> [ <# levels> [ <levels>]]]
where <min fit stat> is the minimum fit statistic relative to which the delta fit statistic is calculated, <# levels> is the number of contour levels to use and <levels> := <level1> ... <levelN> are the contour levels in the deltafit statistic. contour will plot the fit statistic grid calculated by the last steppar command (which should have gridded on two parameters). A small plus sign “+” will be drawn on the plot at the parameter values corresponding to the minimum found by the most recent fit.
The fit statistic confidence contours are often drawn based on a relatively small grid (i.e., 5x5). To understand fully what these plots are telling you, it is useful to know a couple of points concerning how the software chooses the location of the contour lines. The contour plot is drawn based only on the information contained in the sample grid. For example, if the minimum fit statistic occurs when parameter 1 equal 2.25 and you use steppar 1 1.0 5.0 4, then the grid values closest to the minimum are 2.0 and 3.0.This could mean that there are no grid points where delta-fit statistic is less than your lowest level (which defaults to 1.0). As a result, the lowest contour will not be drawn. This effect can be minimized by always selecting a steppar range that causes XSPEC to step very close to the true minima.
For the above example, using steppar 1 1.25 5.25 4, would have been a better selection. The location of a contour line between grid points is designated using a linear interpolation.Since the fit statistic surface is often quadratic, a linear interpolation will result in the lines being drawn inside the true location of the contour.The combination of this and the previous effect sometimes will result in the minimum found by the fit command lying outside the region enclosed by the lowest contour level.
Examples:
XSPEC12> steppar 2 0.5 1. 4 3 1. 2. 4
//create a grid for parameters 2 and 3
XSPEC12> plot contour
//Plot out a grid with three contours with
// delta fit statistic of 2.3, 4.61 and 9.21
XSPEC12> plot cont,,4,1.,2.3,4.61,9.21
//same as above, but with a delta fit statistic = 1 contour.}
Plot the data (with the folded model, if defined) with the y-axis being numbers of counts in each bin.
Plot the data (with the folded model, if defined).
Plot the residuals in terms of sigmas with error bars of size one.
Plot the relative contributions of plasma at different temperatures for multi-temperature models. This is not very clever at the moment and only plots the last model calculated.
Plot the current incident model spectrum in E2f(E) (Note: This is NOT the same as an “unfolded” spectrum.) or, if wavelength plotting has been set, l2f(l). The contributions of the various additive components also are plotted.
Plot the unfolded spectrum and the model in E2f(E) or, if wavelength plotting has been set, l2f(l). The contributions to the model of the various additive components are also plotted. This corresponds to the n–fn plot beloved of AGN researchers. WARNING ! This plot is not model-independent and your unfolded model points will move if the model is changed.
Plot the total response efficiency versus incident photon energy. Only currently noticed channels are included in the calculation of the efficiency.
Plot the current incident model spectrum in Ef(E)[E2f(E)] (Note: This is NOT the same as an unfolded spectrum.) or, if wavelength plotting has been set, lf(l),l2f(l). The contributions of the various additive components also are plotted.
Plot the unfolded spectrum and the model in Ef(E), )[E2f(E)] or, if wavelength plotting has been set, lf(l), l2f(l). The contributions to the model of the various additive components also are plotted.WARNING ! This plot is not model-independent and your unfolded model points will move if the model is changed.
Integrated counts and folded model. The integrated counts are normalized to unity.
Plot the insensitivity of the current spectrum to changes in the incident spectra (experimental).
Plot the data (with the folded model, if defined) with a logarithmic y-axis indicating the count spectrum
Plot the data (with the folded model, if defined) with a logarithmic y-axis.
Plot the probability distribution from the results of the most recently run margin command. (Must be a 1-D or 2-D distribution.)
Plot a Monte Carlo Markov chain. Chains must be currently loaded (see chain command), and <par 1> and <par 2> are parameter identifiers of the form [<model name>:]n where n is an integer, specifying the parameter columns in the chain file to serve as the X and Y axes respectively. To select the fit-statistic column, enter ‘0’ for the <par > value.
Plot the current incident model spectrum (Note: This is NOT the same as an unfolded spectrum.) The contributions of the various additive components also are plotted. New for XSPEC12: if using a named model, the model name must be given as an additional argument to plot model.
Plot the data divided by the folded model.
Plot the data minus the folded model.
Plot the sensitivity of the current spectrum to changes in the incident spectra (experimental).
A pretty plot of the data and residuals against both channels and energy.
Plot the unfolded spectrum and the model. The contributions to the model of the various additive components also are plotted. WARNING ! This plot is not model-independent and your unfolded model points will move if the model is changed.