convert fit_gisas

auto/Examples/fit/scatter2d/fit_gisas.py

@@ -13,13 +13,13 @@ from bornagain import ba_fitmonitor
 from matplotlib import pyplot as plt
 
 
-def run_fitting():
+if __name__ == '__main__':
     datadir = os.getenv('BA_DATA_DIR', '')
-    data = np.loadtxt(os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz"),
-                           dtype=float)
+    fname = os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz")
+    data = ba.readData2D(fname, ba.csv2D)
 
     fit_objective = ba.FitObjective()
-    fit_objective.addSimulationAndData(model.get_simulation, data)
+    fit_objective.addFitPair(model.get_simulation, data)
 
     fit_objective.initPrint(10)  # Print on every 10th iteration.
     observer = ba_fitmonitor.PlotterGISAS()
@@ -39,8 +39,4 @@ def run_fitting():
 
     # Save simulation image corresponding to the best fit parameters
     np.savetxt("fit.txt", fit_objective.simulationResult().npArray())
-
-
-if __name__ == '__main__':
-    run_fitting()
     plt.show()

auto/MiniExamples/fit/scatter2d/fit_gisas.py

@@ -13,13 +13,13 @@ from bornagain import ba_fitmonitor
 from matplotlib import pyplot as plt
 
 
-def run_fitting():
+if __name__ == '__main__':
     datadir = os.getenv('BA_DATA_DIR', '')
-    data = np.loadtxt(os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz"),
-                           dtype=float)
+    fname = os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz")
+    data = ba.readData2D(fname, ba.csv2D)
 
     fit_objective = ba.FitObjective()
-    fit_objective.addSimulationAndData(model.get_simulation, data)
+    fit_objective.addFitPair(model.get_simulation, data)
 
     fit_objective.initPrint(10)  # Print on every 10th iteration.
     observer = ba_fitmonitor.PlotterGISAS()
@@ -39,8 +39,4 @@ def run_fitting():
 
     # Save simulation image corresponding to the best fit parameters
     np.savetxt("fit.txt", fit_objective.simulationResult().npArray())
-
-
-if __name__ == '__main__':
-    run_fitting()
     plt.show()

rawEx/fit/scatter2d/fit_gisas.py

@@ -13,13 +13,13 @@ from bornagain import ba_fitmonitor
 from matplotlib import pyplot as plt
 
 
-def run_fitting():
+if __name__ == '__main__':
     datadir = os.getenv('BA_DATA_DIR', '')
-    data = np.loadtxt(os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz"),
-                           dtype=float)
+    fname = os.path.join(datadir, "scatter2d/faked_gisas1.dat.gz")
+    data = ba.readData2D(fname, ba.csv2D)
 
     fit_objective = ba.FitObjective()
-    fit_objective.addSimulationAndData(model.get_simulation, data)
+    fit_objective.addFitPair(model.get_simulation, data)
 
     fit_objective.initPrint(10)  # Print on every 10th iteration.
     observer = ba_fitmonitor.PlotterGISAS()
@@ -39,8 +39,4 @@ def run_fitting():
 
     # Save simulation image corresponding to the best fit parameters
     np.savetxt("fit.txt", fit_objective.simulationResult().npArray())
-
-
-if __name__ == '__main__':
-    run_fitting()
     plt.show()