From d74f27e246d25b5ddc806c560d484cdba3d88082 Mon Sep 17 00:00:00 2001
From: "Joachim Wuttke (o)" <j.wuttke@fz-juelich.de>
Date: Fri, 22 Sep 2023 10:08:48 +0200
Subject: [PATCH] convert fit_gisas
---
auto/Examples/fit/scatter2d/fit_gisas.py | 12 ++++--------
auto/MiniExamples/fit/scatter2d/fit_gisas.py | 12 ++++--------
rawEx/fit/scatter2d/fit_gisas.py | 12 ++++--------
3 files changed, 12 insertions(+), 24 deletions(-)
diff --git a/auto/Examples/fit/scatter2d/fit_gisas.py b/auto/Examples/fit/scatter2d/fit_gisas.py
index 4bde6077dbf..253788863da 100755
--- a/auto/Examples/fit/scatter2d/fit_gisas.py
+++ b/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()
diff --git a/auto/MiniExamples/fit/scatter2d/fit_gisas.py b/auto/MiniExamples/fit/scatter2d/fit_gisas.py
index 89e6dd4f10d..d890ab2ed42 100755
--- a/auto/MiniExamples/fit/scatter2d/fit_gisas.py
+++ b/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()
diff --git a/rawEx/fit/scatter2d/fit_gisas.py b/rawEx/fit/scatter2d/fit_gisas.py
index 00f88586971..bdba0108255 100755
--- a/rawEx/fit/scatter2d/fit_gisas.py
+++ b/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()
--
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