replaced ranged distributions in untested fit examples

Examples/fit/specular/Honeycomb_fit.py

@@ -77,10 +77,7 @@ def get_sample(parameters, sign, ms150=1):
 
 def get_simulation(q_axis, parameters, sign, ms150=False):
 
-    n_points = 25
-    n_sig = 3.0
-
-    q_distr = ba.RangedDistributionGaussian(n_points, n_sig)
+    q_distr = ba.DistributionGaussian(0., 1., 25, 3.)
 
     dq = parameters["dq"]*q_axis
     scan = ba.QzScan(q_axis)

Examples/fit/specular/Pt_layer_fit.py

@@ -64,8 +64,8 @@ def get_simulation(q_axis, parameters):
     n_sig = 4.0
     n_samples = 25
 
-    distr = ba.RangedDistributionGaussian(n_samples, n_sig)
-    scan.setAbsoluteQResolution(distr, parameters["q_res/q"])
+    distr = ba.DistributionGaussian(0., parameters["q_res/q"], 25, 4.)
+    scan.setAbsoluteQResolution(distr)
 
     simulation = ba.SpecularSimulation(scan, sample)
 

Examples/fit/specular/RealLifeReflectometryFitting.py

@@ -93,7 +93,7 @@ def create_simulation(sample, arg_dict, bin_start, bin_end):
     Creates and returns specular simulation
     """
     wavelength = 1.54*ba.angstrom
-    alpha_distr = ba.RangedDistributionGaussian(0, arg_dict["divergence"]{}
+    alpha_distr = ba.DistributionGaussian(0, arg_dict["divergence"])
     footprint = ba.FootprintGauss(arg_dict["footprint_factor"])
 
     scan = ba.AlphaScan(wavelength, get_real_data_axis(bin_start, bin_end))