From 5790124cd24cf8e30d3e67f1d50df093f5bacec7 Mon Sep 17 00:00:00 2001
From: Dmitry Yurov <d.yurov@fz-juelich.de>
Date: Wed, 24 Jan 2018 13:45:04 +0100
Subject: [PATCH] Replace R, T coefficients with getIntensityData in
examples/PyPersistence
Redmine: #1860
---
.../SpecularSimulation.py | 39 ++--
.../Python/PyPersistence/example_template.py | 9 +-
.../PyPersist/SpecularSimulation.ref.int.gz | Bin 0 -> 3861 bytes
.../PyPersist/SpecularSimulation.ref.yaml | 169 ------------------
4 files changed, 13 insertions(+), 204 deletions(-)
create mode 100644 Tests/ReferenceData/PyPersist/SpecularSimulation.ref.int.gz
delete mode 100644 Tests/ReferenceData/PyPersist/SpecularSimulation.ref.yaml
diff --git a/Examples/python/simulation/ex05_BeamAndDetector/SpecularSimulation.py b/Examples/python/simulation/ex05_BeamAndDetector/SpecularSimulation.py
index 753b16af8b3..e9e9e74afb9 100644
--- a/Examples/python/simulation/ex05_BeamAndDetector/SpecularSimulation.py
+++ b/Examples/python/simulation/ex05_BeamAndDetector/SpecularSimulation.py
@@ -1,5 +1,6 @@
"""
-R and T coefficients in multilayer, ba.Specular simulation.
+Basic example of specular simulation with BornAgain.
+
"""
import numpy
import bornagain as ba
@@ -60,40 +61,22 @@ def run_simulation():
simulation = get_simulation()
simulation.setSample(sample)
simulation.runSimulation()
- return simulation
+ return simulation.getIntensityData()
-def rt_coefficients(simulation):
+def plot(data):
"""
- Returns refraction/transmission coefficients for all layers
- """
- rf = [[abs(c) for c in simulation.getScalarR(i)] for i in range(22)]
- tf = [[abs(c) for c in simulation.getScalarT(i)] for i in range(22)]
- return rf, tf
-
-
-def plot(simulation):
- """
- Plots results for several selected layers
+ Plots data for several selected layers
"""
from matplotlib import pyplot as plt
plt.figure(figsize=(12.80, 10.24))
- alpha_angles = simulation.getAlphaAxis().getBinCenters()
- rf, tf = rt_coefficients(simulation)
-
- selected_layers = [0, 1, 20, 21]
- nplot = 1
- for layer_index in selected_layers:
- plt.subplot(2, 2, nplot)
- plt.ylim(ymax=50.0, ymin=1e-06)
- plt.xlabel(r'$\alpha_f$ (rad)', fontsize=16)
- plt.semilogy(alpha_angles, [numpy.abs(coeff) for coeff in rf[layer_index]])
- plt.semilogy(alpha_angles, [numpy.abs(coeff) for coeff in tf[layer_index]])
- plt.legend(['|R| layer #'+str(layer_index),
- '|T| layer #'+str(layer_index)],
- loc='upper right')
- nplot += 1
+ axis = data.getXaxis().getBinCenters()
+ intensities = data.getArray()
+
+ plt.xlabel(r'$\alpha_f$ (rad)', fontsize=16)
+ plt.semilogy(axis, intensities)
+ plt.legend(['Detector signal'], loc='upper right')
plt.show()
diff --git a/Tests/Functional/Python/PyPersistence/example_template.py b/Tests/Functional/Python/PyPersistence/example_template.py
index 7217af2bd39..dca78a4d069 100644
--- a/Tests/Functional/Python/PyPersistence/example_template.py
+++ b/Tests/Functional/Python/PyPersistence/example_template.py
@@ -94,13 +94,8 @@ def run_simulation():
def save(data, filename):
- if "SpecularSimulation" == example_name:
- filename += ".ref"
- R, T = example.rt_coefficients(data)
- ba.yamlDump(filename, { "coeff_R": ba.FlowSeq(R[0]), "coeff_T": ba.FlowSeq(T[0])})
- else:
- filename += ".ref.int.gz"
- ba.IntensityDataIOFactory.writeIntensityData(data, filename)
+ filename += ".ref.int.gz"
+ ba.IntensityDataIOFactory.writeIntensityData(data, filename)
print("example_template.py -> Writing results in '{0}'".format(filename))
diff --git a/Tests/ReferenceData/PyPersist/SpecularSimulation.ref.int.gz b/Tests/ReferenceData/PyPersist/SpecularSimulation.ref.int.gz
new file mode 100644
index 0000000000000000000000000000000000000000..8a27aa0b48ff9f7553667dfb0c58ad53a31a3866
GIT binary patch
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diff --git a/Tests/ReferenceData/PyPersist/SpecularSimulation.ref.yaml b/Tests/ReferenceData/PyPersist/SpecularSimulation.ref.yaml
deleted file mode 100644
index 621dd1a93ba..00000000000
--- a/Tests/ReferenceData/PyPersist/SpecularSimulation.ref.yaml
+++ /dev/null
@@ -1,169 +0,0 @@
-coeff_R: [0.9999999999999999, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9999999999999999,
- 0.9999999999999999, 0.9999999999999999, 1.0, 0.9999999999999999, 1.0,
- 1.0, 0.9999999999999999, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9999999999999999,
- 0.9999999999999999, 0.9999999999999999, 1.0, 1.0, 1.0, 1.0, 0.9999999999999999,
- 0.9999999999999999, 0.9999999999999999, 1.0, 1.0, 1.0, 0.9999999999999999,
- 1.0, 0.9999999999999999, 0.9999999999999999, 0.9999999999999999, 0.9999999999999999,
- 0.9999999999999999, 1.0, 0.9999999999999999, 1.0, 1.0000000000000004,
- 0.9999999999999999, 0.9999999999999999, 0.9999999999999998, 1.0000000000000002,
- 1.0, 1.0, 1.0, 0.9999999999999999, 1.0000000000000002, 1.0, 0.9999999999999998,
- 0.9999999999999996, 1.0, 0.9999999999999994, 1.0000000000000004, 0.9999999999999999,
- 0.9999999999999999, 1.0, 1.0000000000000024, 1.0000000000000002, 1.0000000000000004,
- 1.0000000000000002, 1.0000000000000022, 1.0000000000000009, 1.0, 0.9999999999999977,
- 0.9999999999999998, 0.9999999999999992, 1.0000000000000002, 1.0000000000000018,
- 1.0000000000000004, 1.0000000000000022, 0.9408565417010387, 0.6779246262665817,
- 0.3565945640479917, 0.29016630866245147, 0.4950233862236306, 0.566779253078876,
- 0.5229896540190951, 0.3541228638910584, 0.0424291611668904, 0.31467602786162446,
- 0.5688671685591417, 0.709135129365976, 0.7829273570620663, 0.822071773682782,
- 0.8413853460874068, 0.8467193359425769, 0.839101655583846, 0.8159178662175125,
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- 0.17800464916443712, 0.1097764348748101, 0.19444488750199332, 0.24488502749094393,
- 0.24519689493216745, 0.20524188378701702, 0.14141251190129817, 0.08648251443534473,
- 0.09446296571506048, 0.13418005864598076, 0.15803187087051535, 0.1555571518971163,
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- 0.0322581236789725, 0.03626105055912253, 0.03403232119706857, 0.02623736369520121,
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- 0.00455525333238069, 0.00957182548367653, 0.018534501773255625, 0.02404645883992693,
- 0.025015474293477113, 0.02141371969991941, 0.014113716612383512, 0.005001731437462994,
- 0.00645492907639501, 0.014677562774181394, 0.020172714583371717, 0.02180398931765262,
- 0.019389458099625785, 0.013542104052502684, 0.005646230762606025, 0.004213214006965864,
- 0.011636230597258315, 0.0169858752762739, 0.01906326651684945, 0.017576764406415615,
- 0.012939644206051594, 0.006223004975897401, 0.002644053167834545, 0.009135268182141347,
- 0.014272801656098656, 0.01666493557818406, 0.015934917510437685, 0.012336938685885838,
- 0.006718238124976238, 0.0020309651123403675, 0.00707275276631176, 0.011925401141023329,
- 0.014528477261618686, 0.01443154998332441, 0.01178064929603868, 0.007339153330898732,
- 0.0035119434698231006, 0.006256391660687734, 0.010489672402097062, 0.013089141395091706,
- 0.013372916744894284, 0.011305570214604193, 0.00734175101824913, 0.002497147633281148,
- 0.003605107327609267, 0.007966613681042034, 0.010859270489398004, 0.011693863563582615,
- 0.010369147240403206, 0.0071925411430207266, 0.0028025106429405058,
- 0.001967406336992195, 0.006225996024273826, 0.0092205928063671, 0.010445604708842225,
- 0.009734743217467161, 0.007279327090509078, 0.003586685884585773, 0.0007858936111734445,
- 0.004682775708025566, 0.007702468872757423, 0.009246544418535764, 0.009078865035886428,
- 0.007283332709593935, 0.004241327778791796, 0.0007337553463310687, 0.003275900171964574,
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--
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