diff --git a/rawEx/fit/specular/Pt_layer_fit.py b/rawEx/fit/specular/Pt_layer_fit.py
index 2ceedd5df1fe8a538829fc8a77604e6ec864770a..a86ffcaab708b0fdb8936e4129ae8d5cde5b0eb8 100755
--- a/rawEx/fit/specular/Pt_layer_fit.py
+++ b/rawEx/fit/specular/Pt_layer_fit.py
@@ -10,6 +10,7 @@ band of roughly 4-7 Ã… in 100 steps of 2theta.
 
 import bornagain as ba, numpy as np, os, matplotlib.pyplot as plt
 from bornagain import angstrom
+from bornagain.numpyutil import Arrayf64Converter as dac
 
 datadir = os.getenv('BA_DATA_DIR', '')
 
@@ -38,7 +39,7 @@ def get_sample(P):
 
     r_si = ba.LayerRoughness(si_autocorr, interlayer)
     r_pt = ba.LayerRoughness(pt_autocorr, interlayer)
-    
+
     sample = ba.MultiLayer()
     sample.addLayer(ambient_layer)
     sample.addLayerWithTopRoughness(layer, r_pt)
@@ -70,10 +71,10 @@ def plot(q, r, data, P):
     fig = plt.figure()
     ax = fig.add_subplot(111)
 
-    ax.errorbar(data.npXcenters(),
-                data.npArray(),
+    ax.errorbar(dac.npArray(data.xCenters()),
+                dac.asNpArray(data.dataArray()),
                 # xerr=data.xxx, TODO restore
-                yerr=data.npErrors(),
+                yerr=dac.asNpArray(data.errors()),
                 label="R",
                 fmt='.',
                 markersize=1.,
@@ -134,7 +135,8 @@ if __name__ == '__main__':
 
     # Initial plot
 
-    r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
+    res = get_simulation(qzs, initialP | fixedP).simulate()
+    r = dac.asNpArray(res.dataArray())
     plot(qzs, r, data, initialP)
 
     # Restrict data to given q range
@@ -147,7 +149,8 @@ if __name__ == '__main__':
     fit_objective.setObjectiveMetric("chi2")
     fit_objective.initPrint(10)
     fit_objective.addFitPair(
-        lambda P: get_simulation(data.npXcenters(), P | fixedP), data, 1)
+        lambda P: get_simulation(
+            dac.npArray(data.xCenters()), P | fixedP), data, 1)
 
     P = ba.Parameters()
     for name, p in startPnB.items():
@@ -164,7 +167,8 @@ if __name__ == '__main__':
     print("Fit Result:")
     print(finalP)
 
-    r = get_simulation(qzs, finalP | fixedP).simulate().npArray()
+    res = get_simulation(qzs, finalP | fixedP).simulate()
+    r = dac.asNpArray(res.dataArray())
     plot(qzs, r, data, finalP)
 
     plt.show()