Accessing simulation results

In this tutorial we explain how to access GISAS simulation results, how to plot the simulated detector 2D intensity map as a color map and how to export the result into various formats.

SimulationResult object

The detector intensity in BornAgain can be retrieved via special object of SimulationResult type.

simulation = GISASSimulation()
simulation.setDetectorParameters(20, -1.0*deg, 1.0*deg, 10, 0.0*deg, 1.0*deg)
simulation.setSample(sample)
simulation.runSimulation()

result = simulation.result()

SimulationResult object allows

  • Export of intensity data into numpy array.
  • Immediate plotting of intensity data as color map using plot utils provided by BornAgain installation.
  • Convertion of intensity data into one of supported external formats for the later processing in the software of user’s choice.

Export to numpy array

The user can convert a SimulationResult object into a numpy array and proceed with it in the manner he is more comfortable with. In the code snippet below the method array() returns a numpy array of the same shape as the detector pixel array. The method numpy.savetxt from the numpy library saves the data to an ASCII file.

arr = simulation.result().array()
numpy.savetxt("intensity.txt", arr)

Plotting simulation results

BornAgain provides few convenient functions to plot simulation result as color map. Internally they are using not more than matplotlib routines. The function plot_simulation_result makes a plot and holds the graphics, while plot_colormap makes the plot and let the program continue to allow more plots on same figure, for example.

The code snippet below gives few examples

result = simulation.result()

# plot color map with automatic axes labels and min/max calculated
ba.plot_simulation_result(result)

# plot color map with custom labels and min/max defined.
ba.plot_colormap(result, zmin=1e-04, zmax=1e+05, xlabel="")

Histogram2D object

It is possible to convert SimulationResult to BornAgain’s Histogram2D object. It allows to perform some additional data treatment tasks:

  • Histogram clipping to draw only the region of interest
  • Slicing of 2D histograms into 1D histograms
  • Creation of relative difference histograms, and many other

In the code snippet below simulation results are converted to Histogram2D object with axes converted into Q-space, then it is cropped to the region of interest, plotted and then saved to disk into BornAgain internal format.

hist = simulation.result().histogram2d(units=ba.AxesUnits.QSPACE)
hist = hist.crop(-1.0, 0.5, 1.0, 1.0)
ba.plot_histogram(hist)
hist.save("result.int.gz")

Additional information can be found in the following pages: