From 31381d375bb432d0b2e882af22e59ac214e8f34a Mon Sep 17 00:00:00 2001
From: Joachim Wuttke <j.wuttke@fz-juelich.de>
Date: Tue, 26 Sep 2023 10:14:37 +0200
Subject: [PATCH] Datafield::crop[2] no longer delete error bars
---
Device/Data/Datafield.cpp | 16 +++++++++++-----
auto/Examples/fit/specular/Pt_layer_fit.py | 8 +++++++-
auto/MiniExamples/fit/specular/Pt_layer_fit.py | 8 +++++++-
rawEx/fit/specular/Pt_layer_fit.py | 6 ++++++
4 files changed, 31 insertions(+), 7 deletions(-)
diff --git a/Device/Data/Datafield.cpp b/Device/Data/Datafield.cpp
index 08038dc68f1..6ab5ce4a88b 100644
--- a/Device/Data/Datafield.cpp
+++ b/Device/Data/Datafield.cpp
@@ -273,14 +273,20 @@ Datafield* Datafield::crop(double xmin, double xmax) const
{
const auto xclipped = std::make_unique<Scale>(xAxis().clipped(xmin, xmax));
- std::vector<double> out(size());
+ const size_t N = size();
+ std::vector<double> out(N);
+ std::vector<double> errout(hasErrorSigmas() ? N : 0);
size_t iout = 0;
- for (size_t i = 0; i < size(); ++i) {
+ for (size_t i = 0; i < N; ++i) {
const double x = frame().projectedCoord(i, 0);
- if (xclipped->rangeComprises(x))
- out[iout++] = m_values[i];
+ if (xclipped->rangeComprises(x)) {
+ out[iout] = m_values[i];
+ if (hasErrorSigmas())
+ errout[iout] = m_errSigmas[i];
+ ++iout;
+ }
}
- return new Datafield(frame().clone(), out);
+ return new Datafield(frame().clone(), out, errout);
}
#ifdef BORNAGAIN_PYTHON
diff --git a/auto/Examples/fit/specular/Pt_layer_fit.py b/auto/Examples/fit/specular/Pt_layer_fit.py
index 81b1a746674..bd4f17520fe 100755
--- a/auto/Examples/fit/specular/Pt_layer_fit.py
+++ b/auto/Examples/fit/specular/Pt_layer_fit.py
@@ -104,7 +104,7 @@ if __name__ == '__main__':
}
startPnB = {
- "intensity": (1., 0.7, 1.3),
+ "intensity": (1., 0.8, 1.2),
"q_offset": (0.01, -0.02, 0.02),
"q_res/q": (0.01, 0, 0.02),
"t_pt/nm": (50, 45, 55),
@@ -125,9 +125,15 @@ if __name__ == '__main__':
flags = ba.ImportSettings1D("q (1/angstrom)", "#", "", 1, 2, 3, 4)
data = ba.readData1D(fpath, ba.csv1D, flags)
+ # Initial plot
+
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
+ # Restrict data to given q range
+
+ data = data.crop(qmin, qmax)
+
# Fit:
fit_objective = ba.FitObjective()
diff --git a/auto/MiniExamples/fit/specular/Pt_layer_fit.py b/auto/MiniExamples/fit/specular/Pt_layer_fit.py
index 4f3bba2f104..3a32ac836a5 100755
--- a/auto/MiniExamples/fit/specular/Pt_layer_fit.py
+++ b/auto/MiniExamples/fit/specular/Pt_layer_fit.py
@@ -104,7 +104,7 @@ if __name__ == '__main__':
}
startPnB = {
- "intensity": (1., 0.7, 1.3),
+ "intensity": (1., 0.8, 1.2),
"q_offset": (0.01, -0.02, 0.02),
"q_res/q": (0.01, 0, 0.02),
"t_pt/nm": (50, 45, 55),
@@ -125,9 +125,15 @@ if __name__ == '__main__':
flags = ba.ImportSettings1D("q (1/angstrom)", "#", "", 1, 2, 3, 4)
data = ba.readData1D(fpath, ba.csv1D, flags)
+ # Initial plot
+
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
+ # Restrict data to given q range
+
+ data = data.crop(qmin, qmax)
+
# Fit:
fit_objective = ba.FitObjective()
diff --git a/rawEx/fit/specular/Pt_layer_fit.py b/rawEx/fit/specular/Pt_layer_fit.py
index 70a25952906..bae2abf7f92 100755
--- a/rawEx/fit/specular/Pt_layer_fit.py
+++ b/rawEx/fit/specular/Pt_layer_fit.py
@@ -125,9 +125,15 @@ if __name__ == '__main__':
flags = ba.ImportSettings1D("q (1/angstrom)", "#", "", 1, 2, 3, 4)
data = ba.readData1D(fpath, ba.csv1D, flags)
+ # Initial plot
+
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
+ # Restrict data to given q range
+
+ data = data.crop(qmin, qmax)
+
# Fit:
fit_objective = ba.FitObjective()
--
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