From 5a29865248d3580846582d5ab54c1c9ce3b83e71 Mon Sep 17 00:00:00 2001
From: AlQuemist <alquemist@Lyriks>
Date: Mon, 19 Aug 2024 13:53:49 +0200
Subject: [PATCH] fx rawEx/fit/specular/Honeycomb_fit.py
---
rawEx/fit/specular/Honeycomb_fit.py | 17 +++++++++--------
1 file changed, 9 insertions(+), 8 deletions(-)
diff --git a/rawEx/fit/specular/Honeycomb_fit.py b/rawEx/fit/specular/Honeycomb_fit.py
index c9d542e1d91..598aadf8726 100755
--- a/rawEx/fit/specular/Honeycomb_fit.py
+++ b/rawEx/fit/specular/Honeycomb_fit.py
@@ -9,6 +9,7 @@ data without spin-flip for performance reasons.
import bornagain as ba, numpy as np, os, matplotlib.pyplot as plt, scipy
from bornagain import angstrom, sample_tools as st
+from bornagain.numpyutil import Arrayf64Converter as dac
datadir = os.getenv('BA_DATA_DIR', '')
@@ -49,13 +50,13 @@ def get_sample(P, sign, T):
l_Si = ba.Layer(material_Si)
interlayer_model = ba.ErfInterlayer()
-
+
rPyOx_autocorr = ba.K_CorrelationModel(P["rPyOx"]*angstrom)
rPy2_autocorr = ba.K_CorrelationModel(P["rPy2"]*angstrom)
rPy1_autocorr = ba.K_CorrelationModel(P["rPy1"]*angstrom)
rSiO2_autocorr = ba.K_CorrelationModel(P["rSiO2"]*angstrom)
rSi_autocorr = ba.K_CorrelationModel(P["rSi"]*angstrom)
-
+
rPyOx = ba.LayerRoughness(rPyOx_autocorr, interlayer_model)
rPy2 = ba.LayerRoughness(rPy2_autocorr, interlayer_model)
rPy1 = ba.LayerRoughness(rPy1_autocorr, interlayer_model)
@@ -87,7 +88,7 @@ def run_simulation(qaxis, P, *, sign, T):
simulation = ba.SpecularSimulation(scan, sample)
simulation.setBackground(ba.ConstantBackground(5e-7))
- return simulation.simulate().npArray()
+ return dac.npArray(simulation.simulate().dataArray())
####################################################################
# Experimental data
@@ -113,9 +114,9 @@ def plot(q, rs, data, shifts, labels):
for r, exp, shift, l in zip(rs, data, shifts, labels):
- ax.errorbar(exp.npXcenters(),
- exp.npArray()/shift,
- yerr=exp.npErrors()/shift,
+ ax.errorbar(dac.npArray(exp.xCenters()),
+ dac.asNpArray(exp.dataArray()) / shift,
+ yerr=dac.asNpArray(exp.errors()) / shift,
fmt='.',
markersize=0.75,
linewidth=0.5)
@@ -230,8 +231,8 @@ if __name__ == '__main__':
# Fit
- qaxes = [d.npXcenters() for d in data]
- rdata = [d.npArray() for d in data]
+ qaxes = [dac.npArray(d.xCenters()) for d in data]
+ rdata = [dac.asNpArray(d.dataArray()) for d in data]
def par_dict(*args):
return {name: value for name, value in zip(freeParNames, *args)} | fixedP
--
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