repair tests

Examples/specular/BeamFullDivergence.py

@@ -22,15 +22,16 @@ def get_sample():
     return std_samples.alternating_layers()
 
 
-def get_simulation(sample, scan_size=500):
+def get_simulation(sample, **simargs):
     """
     Returns a specular simulation with beam and detector defined.
     """
+    n = simargs['n']
 
     alpha_distr = ba.RangedDistributionGaussian(n_points, n_sig)
     wavelength_distr = ba.RangedDistributionGaussian(n_points, n_sig)
 
-    scan = ba.AlphaScan(wavelength, scan_size, alpha_i_min, alpha_i_max)
+    scan = ba.AlphaScan(wavelength, n, alpha_i_min, alpha_i_max)
     scan.setAbsoluteAngularResolution(alpha_distr, d_ang)
     scan.setAbsoluteWavelengthResolution(wavelength_distr, d_wl)
 
@@ -42,7 +43,7 @@ def get_simulation(sample, scan_size=500):
 
 
 if __name__ == '__main__':
-    plotargs, simargs = bp.kwargs_from_cmdline(sim_n=0)
+    plotargs, simargs = bp.kwargs_from_cmdline(sim_n=500)
     sample = get_sample()
     simulation = get_simulation(sample, **simargs)
     result = simulation.simulate()

Examples/varia/GratingMC.py

@@ -4,6 +4,7 @@ Simulation of grating using very long boxes and 1D lattice.
 Monte-carlo integration is used to get rid of
 large-particle form factor oscillations.
 """
+import sys
 import bornagain as ba
 from bornagain import angstrom, ba_plot as bp, deg, micrometer, nm
 from matplotlib import pyplot as plt
@@ -63,26 +64,29 @@ def get_simulation(sample, **simargs):
     return simulation
 
 
-def run_simulation():
+if __name__ == '__main__':
     """
     Runs simulation and returns intensity map.
     """
+    plotargs, simargs = bp.kwargs_from_cmdline(sim_n=200)
     sample = get_sample()
-    simulation = get_simulation(sample)
+    simulation = get_simulation(sample, **simargs)
     if not "__no_terminal__" in globals():
         simulation.setTerminalProgressMonitor()
-    simulation.simulate()
-    return simulation.result()
-
+    result = simulation.simulate()
+    datfile = plotargs.pop('datfile', None)
+    if datfile:
+        ba.IntensityDataIOFactory.writeSimulationResult(result, datfile)
+    histogram = result.histogram2d()
+    bp.plot_histogram(histogram)
 
-def simulate_and_plot():
-    result = run_simulation().histogram2d()
-    bp.plot_histogram(result)
 
-    peaks = ba.FindPeaks(result, 2, "nomarkov", 0.001)
+    peaks = ba.FindPeaks(histogram, 2, "nomarkov", 0.001)
     xpeaks = [peak[0] for peak in peaks]
     ypeaks = [peak[1] for peak in peaks]
     print(peaks)
+    if not plotargs.pop('plot', 'on') in ['on']:
+        sys.exit(0)
     plt.plot(xpeaks,
              ypeaks,
              linestyle='None',
@@ -90,7 +94,3 @@ def simulate_and_plot():
              color='white',
              markersize=10)
     plt.show()
-
-
-if __name__ == '__main__':
-    simulate_and_plot()