corr line length

Examples/fit/gisas2d/gisas_fake1.py

@@ -21,7 +21,8 @@ def fake_data():
 
     # Draw noisy data
     np.random.seed(0)
-    data = np.random.normal(theory, np.sqrt(theory)) + np.random.poisson(bg, theory.shape)
+    data = np.random.normal(theory, np.sqrt(theory)) + np.random.poisson(
+        bg, theory.shape)
 
     # Save to numpy
     np.savetxt("gisas-model1.txt.gz", data)

Examples/fit/gisas2d/gisas_fit2d.py

@@ -17,8 +17,9 @@ def run_fitting():
     fit_objective = ba.FitObjective()
     fit_objective.addSimulationAndData(model.get_simulation, real_data)
 
-    fit_objective.initPrint(10) # Print on every 10th iteration.
-    fit_objective.initPlot(10) # Plot on every 10th iteration. Will slow down the fit.
+    fit_objective.initPrint(10)  # Print on every 10th iteration.
+    fit_objective.initPlot(
+        10)  # Plot on every 10th iteration. Will slow down the fit.
 
     minimizer = ba.Minimizer()
     params = model.start_parameters_1()

Examples/fit/gisas2d/gisas_model1.py

@@ -6,7 +6,6 @@ Dilute cylinders on a substrate.
 import bornagain as ba
 from bornagain import deg, nm
 
-
 mat_vacuum = ba.HomogeneousMaterial("Vacuum", 0, 0)
 mat_substrate = ba.HomogeneousMaterial("Substrate", 6e-6, 2e-8)
 mat_particle = ba.HomogeneousMaterial("Particle", 6e-4, 2e-8)
@@ -33,13 +32,15 @@ def get_sample(params):
 
 
 def get_simulation(params):
-    beam = ba.Beam(10**params['lg(intensity)'], 0.1*nm, ba.Direction(0.2*deg, 0))
+    beam = ba.Beam(10**params['lg(intensity)'], 0.1*nm,
+                   ba.Direction(0.2*deg, 0))
     det = ba.SphericalDetector(100, -1.5*deg, 1.5*deg, 100, 0, 3*deg)
     sample = get_sample(params)
 
     simulation = ba.GISASSimulation(beam, sample, det)
     if 'lg(background)' in params:
-        simulation.setBackground(ba.ConstantBackground(10**params['lg(background)']))
+        simulation.setBackground(
+            ba.ConstantBackground(10**params['lg(background)']))
 
     return simulation