add RealLifeSpecular.py example

auto/Examples/fit/specular/RealLifeSpecular.py

+#!/usr/bin/env python3
+"""
+Basic real-life example of fitting specular data.
+The sample consists of single Ni film on SiO2 substrate.
+"""
+
+import math
+import bornagain as ba, os
+from bornagain import nm, deg, ba_fitmonitor
+
+
+def load_data():
+    datadir = os.getenv('BA_DATA_DIR', '')
+    fname = os.path.join(datadir, "specular/MLZ-TREFF-Ni58.txt")
+
+    flags = ba.ImportSettings1D("qz (1/angstrom)", "#", "", 1, 2)
+    return ba.readData1D(fname, ba.csv1D, flags)
+
+
+def get_sample(P):
+    # Materials
+    vacuum = ba.MaterialBySLD()
+    material_Ni_58 = ba.MaterialBySLD("Ni", 9.408e-06, 0)
+    material_SiO2 = ba.MaterialBySLD("SiO2", 2.0704e-06, 0)
+
+    # Layers and interfaces
+    layer_Ni = ba.Layer(material_Ni_58, P["thickness"])
+    roughness_Ni = ba.LayerRoughness(P["sigma_Ni"])
+    
+    substrate = ba.Layer(material_SiO2)  
+    roughness_Substrate = ba.LayerRoughness(P["sigma_Substrate"])
+
+    sample = ba.MultiLayer()
+    sample.addLayer(ba.Layer(vacuum))
+    sample.addLayerWithTopRoughness(layer_Ni, roughness_Ni)
+    sample.addLayerWithTopRoughness(substrate, roughness_Substrate)
+
+    return sample
+
+
+def get_simulation(P):
+    scan = ba.QzScan(data.xAxis())
+    
+    # Finite resolution due to beam divergence
+    n_samples = 5
+    rel_sampling_width = 2.0
+    res_distr = ba.DistributionGaussian(0, 1, n_samples, rel_sampling_width)
+    
+    wavelength = 0.473*nm
+    res_alpha = 0.006*deg
+    res_q = 4*math.pi*res_alpha/wavelength
+    scan.setAbsoluteQResolution(res_distr, res_q)
+    
+    sample = get_sample(P)
+    simulation = ba.SpecularSimulation(scan, sample)    
+    simulation.setBackground(ba.ConstantBackground(1e-4))
+
+    return simulation
+
+
+if __name__ == '__main__':
+    data = load_data()
+
+    P = ba.Parameters()
+    P.add("thickness", 59*nm, min=50*nm, max=100*nm)
+    P.add("sigma_Ni", 2*nm, min=0.01*nm, max=3*nm)
+    P.add("sigma_Substrate", 2.5*nm, min=0.01*nm, max=3*nm)
+
+    fit_objective = ba.FitObjective()
+    fit_objective.addFitPair(get_simulation, data, 1)
+    fit_objective.setObjectiveMetric("log", "l2")
+
+    fit_objective.initPrint(50)
+    plot_observer = ba_fitmonitor.PlotterSpecular(pause=0.001)
+    fit_objective.initPlot(50, plot_observer)
+
+    minimizer = ba.Minimizer()
+    
+    # Main minimization
+    minimizer.setMinimizer("Genetic", "",
+                            "MaxIterations=5;PopSize=300")                           
+    result = minimizer.minimize(fit_objective.evaluate, P)
+    fit_objective.finalize(result)
+    
+    # Polish results with another minimizer    
+    best_P_so_far = result.parameters()
+    minimizer.setMinimizer("Minuit2", "Migrad",
+                            "MaxFunctionCalls=0")
+    result = minimizer.minimize(fit_objective.evaluate, best_P_so_far)
+    fit_objective.finalize(result)
+
+    plot_observer.show()

auto/MiniExamples/fit/specular/RealLifeSpecular.py

+#!/usr/bin/env python3
+"""
+Basic real-life example of fitting specular data.
+The sample consists of single Ni film on SiO2 substrate.
+"""
+
+import math
+import bornagain as ba, os
+from bornagain import nm, deg, ba_fitmonitor
+
+
+def load_data():
+    datadir = os.getenv('BA_DATA_DIR', '')
+    fname = os.path.join(datadir, "specular/MLZ-TREFF-Ni58.txt")
+
+    flags = ba.ImportSettings1D("qz (1/angstrom)", "#", "", 1, 2)
+    return ba.readData1D(fname, ba.csv1D, flags)
+
+
+def get_sample(P):
+    # Materials
+    vacuum = ba.MaterialBySLD()
+    material_Ni_58 = ba.MaterialBySLD("Ni", 9.408e-06, 0)
+    material_SiO2 = ba.MaterialBySLD("SiO2", 2.0704e-06, 0)
+
+    # Layers and interfaces
+    layer_Ni = ba.Layer(material_Ni_58, P["thickness"])
+    roughness_Ni = ba.LayerRoughness(P["sigma_Ni"])
+    
+    substrate = ba.Layer(material_SiO2)  
+    roughness_Substrate = ba.LayerRoughness(P["sigma_Substrate"])
+
+    sample = ba.MultiLayer()
+    sample.addLayer(ba.Layer(vacuum))
+    sample.addLayerWithTopRoughness(layer_Ni, roughness_Ni)
+    sample.addLayerWithTopRoughness(substrate, roughness_Substrate)
+
+    return sample
+
+
+def get_simulation(P):
+    scan = ba.QzScan(data.xAxis())
+    
+    # Finite resolution due to beam divergence
+    n_samples = 5
+    rel_sampling_width = 2.0
+    res_distr = ba.DistributionGaussian(0, 1, n_samples, rel_sampling_width)
+    
+    wavelength = 0.473*nm
+    res_alpha = 0.006*deg
+    res_q = 4*math.pi*res_alpha/wavelength
+    scan.setAbsoluteQResolution(res_distr, res_q)
+    
+    sample = get_sample(P)
+    simulation = ba.SpecularSimulation(scan, sample)    
+    simulation.setBackground(ba.ConstantBackground(1e-4))
+
+    return simulation
+
+
+if __name__ == '__main__':
+    data = load_data()
+
+    P = ba.Parameters()
+    P.add("thickness", 59*nm, min=50*nm, max=100*nm)
+    P.add("sigma_Ni", 2*nm, min=0.01*nm, max=3*nm)
+    P.add("sigma_Substrate", 2.5*nm, min=0.01*nm, max=3*nm)
+
+    fit_objective = ba.FitObjective()
+    fit_objective.addFitPair(get_simulation, data, 1)
+    fit_objective.setObjectiveMetric("log", "l2")
+
+    fit_objective.initPrint(50)
+    plot_observer = ba_fitmonitor.PlotterSpecular(pause=0.001)
+    fit_objective.initPlot(50, plot_observer)
+
+    minimizer = ba.Minimizer()
+    
+    # Main minimization
+    minimizer.setMinimizer("Genetic", "",
+                            "MaxIterations=1;PopSize=10")                           
+    result = minimizer.minimize(fit_objective.evaluate, P)
+    fit_objective.finalize(result)
+    
+    # Polish results with another minimizer    
+    best_P_so_far = result.parameters()
+    minimizer.setMinimizer("Minuit2", "Migrad",
+                            "MaxFunctionCalls=10")
+    result = minimizer.minimize(fit_objective.evaluate, best_P_so_far)
+    fit_objective.finalize(result)
+
+    plot_observer.show()

rawEx/fit/specular/RealLifeSpecular.py

+#!/usr/bin/env python3
+"""
+Basic real-life example of fitting specular data.
+The sample consists of single Ni film on SiO2 substrate.
+"""
+
+import math
+import bornagain as ba, os
+from bornagain import nm, deg, ba_fitmonitor
+
+
+def load_data():
+    datadir = os.getenv('BA_DATA_DIR', '')
+    fname = os.path.join(datadir, "specular/MLZ-TREFF-Ni58.txt")
+
+    flags = ba.ImportSettings1D("qz (1/angstrom)", "#", "", 1, 2)
+    return ba.readData1D(fname, ba.csv1D, flags)
+
+
+def get_sample(P):
+    # Materials
+    vacuum = ba.MaterialBySLD()
+    material_Ni_58 = ba.MaterialBySLD("Ni", 9.408e-06, 0)
+    material_SiO2 = ba.MaterialBySLD("SiO2", 2.0704e-06, 0)
+
+    # Layers and interfaces
+    layer_Ni = ba.Layer(material_Ni_58, P["thickness"])
+    roughness_Ni = ba.LayerRoughness(P["sigma_Ni"])
+    
+    substrate = ba.Layer(material_SiO2)  
+    roughness_Substrate = ba.LayerRoughness(P["sigma_Substrate"])
+
+    sample = ba.MultiLayer()
+    sample.addLayer(ba.Layer(vacuum))
+    sample.addLayerWithTopRoughness(layer_Ni, roughness_Ni)
+    sample.addLayerWithTopRoughness(substrate, roughness_Substrate)
+
+    return sample
+
+
+def get_simulation(P):
+    scan = ba.QzScan(data.xAxis())
+    
+    # Finite resolution due to beam divergence
+    n_samples = 5
+    rel_sampling_width = 2.0
+    res_distr = ba.DistributionGaussian(0, 1, n_samples, rel_sampling_width)
+    
+    wavelength = 0.473*nm
+    res_alpha = 0.006*deg
+    res_q = 4*math.pi*res_alpha/wavelength
+    scan.setAbsoluteQResolution(res_distr, res_q)
+    
+    sample = get_sample(P)
+    simulation = ba.SpecularSimulation(scan, sample)    
+    simulation.setBackground(ba.ConstantBackground(1e-4))
+
+    return simulation
+
+
+if __name__ == '__main__':
+    data = load_data()
+
+    P = ba.Parameters()
+    P.add("thickness", 59*nm, min=50*nm, max=100*nm)
+    P.add("sigma_Ni", 2*nm, min=0.01*nm, max=3*nm)
+    P.add("sigma_Substrate", 2.5*nm, min=0.01*nm, max=3*nm)
+
+    fit_objective = ba.FitObjective()
+    fit_objective.addFitPair(get_simulation, data, 1)
+    fit_objective.setObjectiveMetric("log", "l2")
+
+    fit_objective.initPrint(50)
+    plot_observer = ba_fitmonitor.PlotterSpecular(pause=0.001)
+    fit_objective.initPlot(50, plot_observer)
+
+    minimizer = ba.Minimizer()
+    
+    # Main minimization
+    minimizer.setMinimizer("Genetic", "",
+                            "<%= sm ? "MaxIterations=1;PopSize=10" :
+                            "MaxIterations=5;PopSize=300" %>")                           
+    result = minimizer.minimize(fit_objective.evaluate, P)
+    fit_objective.finalize(result)
+    
+    # Polish results with another minimizer    
+    best_P_so_far = result.parameters()
+    minimizer.setMinimizer("Minuit2", "Migrad",
+                            "MaxFunctionCalls=<%= sm ? 10 : 0 %>")
+    result = minimizer.minimize(fit_objective.evaluate, best_P_so_far)
+    fit_objective.finalize(result)
+
+    plot_observer.show()