MonteCarlo integration functional test

Examples/python/simulation/ex04_ComplexShapes/LargeParticlesFormFactor.py

@@ -12,8 +12,6 @@ from bornagain import *
 
 phi_min, phi_max = -2.0, 2.0
 alpha_min, alpha_max = 0.0, 2.0
-scale = 1
-
 default_cylinder_radius = 10*nanometer
 default_cylinder_height = 20*nanometer
 

Tests/FunctionalTests/TestPyCore/CMakeLists.txt

@@ -27,6 +27,7 @@ set(list_of_tests
     "ripple2_asym.py"
     "ripple1.py"
     "customformfactor.py"
+    "montecarlo_integration.py"
 )
 
 set(list_of_cpp_python_tests

Tests/FunctionalTests/TestPyCore/montecarlo_integration.py

+# Monte-Carlo integration functional test
+# Testing very large cylinders
+import sys
+import os
+import numpy
+import cmath
+from utils import get_reference_data
+
+sys.path.append(os.path.abspath(
+                os.path.join(os.path.split(__file__)[0],
+                '..', '..', '..', 'lib')))
+
+
+from libBornAgainCore import *
+
+phi_min, phi_max = -2.0, 2.0
+alpha_min, alpha_max = 0.0, 2.0
+default_cylinder_radius = 10*nanometer
+default_cylinder_height = 20*nanometer
+scale = 100
+
+
+def get_sample(cylinder_radius, cylinder_height):
+    """
+    Build and return the sample to calculate cylinder formfactor in Distorted Wave Born Approximation
+    for given cylinder_radius and cylinder_height
+    """
+    # defining materials
+    m_ambience = HomogeneousMaterial("Air", 0.0, 0.0)
+    m_substrate = HomogeneousMaterial("Substrate", 6e-6, 2e-8)
+    m_particle = HomogeneousMaterial("Particle", 6e-4, 2e-8)
+
+    # collection of particles
+    cylinder_ff = FormFactorCylinder(cylinder_radius, cylinder_height)
+    cylinder = Particle(m_particle, cylinder_ff)
+    particle_layout = ParticleLayout()
+    particle_layout.addParticle(cylinder, 0.0, 1.0)
+
+    air_layer = Layer(m_ambience)
+    air_layer.addLayout(particle_layout)
+    substrate_layer = Layer(m_substrate)
+
+    multi_layer = MultiLayer()
+    multi_layer.addLayer(air_layer)
+    multi_layer.addLayer(substrate_layer)
+    return multi_layer
+
+
+def get_simulation():
+    """
+    Create and return GISAXS simulation with beam and detector defined.
+    """
+    simulation = Simulation()
+    simulation.setDetectorParameters(50, phi_min*degree, phi_max*degree, 100, alpha_min*degree, alpha_max*degree)
+    simulation.setBeamParameters(1.0*angstrom, 0.2*degree, 0.0*degree)
+    sim_pars = SimulationParameters()
+    sim_pars.m_mc_integration = True
+    sim_pars.m_mc_points = 50
+    simulation.setSimulationParameters(sim_pars)
+    return simulation
+
+
+
+def run_simulation():
+    """
+    Run simulation and plot results
+    """
+    sample = get_sample(default_cylinder_radius*scale, default_cylinder_height*scale)
+    simulation = get_simulation()
+    simulation.setSample(sample)
+    simulation.runSimulation()
+    result = simulation.getIntensityData()
+    return result
+
+
+def run_test():
+    """
+    run test and analyse test results
+    """
+    result = run_simulation()
+    reference = get_reference_data('montecarlo_integration.int.gz')
+    diff = IntensityDataFunctions.getRelativeDifference(result, reference)
+    status = "OK"
+    if diff > 2e-10 or numpy.isnan(diff):
+        status = "FAILED"
+    return "MonteCarloIntegration", "Test of Monte-Carlo integration", diff, status
+
+
+if __name__ == '__main__':
+    name, description, diff, status = run_test()
+    print name, description, diff, status
+    if "FAILED" in status:
+        exit(1)
+