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Commit 74bb1bb7 authored by Wuttke, Joachim's avatar Wuttke, Joachim
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rm remnant of example AccessingSimulationResults

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Tests/Examples/CMakeLists.txt
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...@@ -196,7 +196,6 @@ test_example(varia/TransmissionVsAlpha 2e-10) ...@@ -196,7 +196,6 @@ test_example(varia/TransmissionVsAlpha 2e-10)
test_example(varia/TransmissionVsDepth 2e-10) test_example(varia/TransmissionVsDepth 2e-10)
test_example(varia/TransmittedModulus 2e-10) test_example(varia/TransmittedModulus 2e-10)
test_example(varia/Resonator 2e-10) test_example(varia/Resonator 2e-10)
# TODO disabled while refactoring scales&coords: test_example(varia/AccessingSimulationResults 2e-10)
run_example(varia/MaterialProfile) run_example(varia/MaterialProfile)
run_example(varia/MaterialProfileWithParticles) run_example(varia/MaterialProfileWithParticles)
......
auto/Examples/varia/AccessingSimulationResults.py deleted 100755 → 0
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#!/usr/bin/env python3
"""
Extended example for simulation results treatment (cropping, slicing, exporting)
"""
import math
import random
import bornagain as ba
from bornagain import angstrom, ba_plot as bp, deg, nm, std_samples
from matplotlib import pyplot as plt
import datetime
def get_sample():
return std_samples.cylinders()
def get_simulation(sample):
"""
A GISAXS simulation with beam and detector defined.
"""
beam = ba.Beam(1e5, 1*angstrom, 0.2*deg)
n = 200
det = ba.SphericalDetector(n, -2*deg, 2*deg, n, 0, 2*deg)
simulation = ba.ScatteringSimulation(beam, sample, det)
return simulation
def get_noisy_image(field):
"""
Returns clone of input field filled with additional noise
"""
result = field.clone()
noise_factor = 2.0
for i in range(0, result.size()):
amplitude = field.valAt(i)
sigma = noise_factor*math.sqrt(amplitude)
noisy_amplitude = random.gauss(amplitude, sigma)
result.setAt(i, noisy_amplitude)
return result
def plot_histogram(field, **kwargs):
bp.plot_histogram(field,
xlabel=r'$\varphi_f ^{\circ}$',
ylabel=r'$\alpha_{\rm f} ^{\circ}$',
zlabel="",
**kwargs)
def plot_slices(noisy):
"""
Plot 1D slices along y-axis at certain x-axis values.
"""
plt.yscale('log')
# projection along Y, slice at fixed x-value
proj1 = noisy.yProjection(0)
plt.plot(proj1.axis(0).binCenters(),
proj1.flatVector(),
label=r'$\varphi=0.0^{\circ}$')
# projection along Y, slice at fixed x-value
proj2 = noisy.yProjection(0.5) # slice at fixed value
plt.plot(proj2.axis(0).binCenters(),
proj2.flatVector(),
label=r'$\varphi=0.5^{\circ}$')
# projection along Y for all X values between [xlow, xup], averaged
proj3 = noisy.yProjection(0.41, 0.59)
plt.plot(proj3.axis(0).binCenters(),
proj3.flatVector(),
label=r'$<\varphi>=0.5^{\circ}$')
plt.xlim(proj1.axis(0).min(), proj1.axis(0).max())
plt.ylim(proj1.maxVal()*3e-6, proj1.maxVal()*3)
plt.xlabel(r'$\alpha_{\rm f} ^{\circ}$', fontsize=16)
plt.legend(loc='upper right')
def plot(field):
"""
Demonstrates modified data plots.
"""
plt.subplots(2, 2, figsize=(12.80, 10.24))
plt.subplot(2, 2, 1)
bp.plot_histogram(field)
plt.title("Intensity as heatmap")
plt.subplot(2, 2, 2)
crop = field.crop(-1, 0.5, 1, 1)
bp.plot_histogram(crop)
plt.title("Cropping")
plt.subplot(2, 2, 3)
noisy = get_noisy_image(field)
reldiff = ba.relativeDifferenceField(noisy, field).npArray()
bp.plot_array(reldiff, intensity_min=1e-03, intensity_max=10)
plt.title("Relative difference")
plt.subplot(2, 2, 4)
plot_slices(noisy)
plt.title("Various slicing of 2D into 1D")
plt.tight_layout()
if __name__ == '__main__':
sample = get_sample()
simulation = get_simulation(sample)
result = simulation.simulate()
if bp.datfile:
ba.writeDatafield(result, bp.datfile + ".int")
# Other supported extensions are .tif and .txt.
# Besides compression .gz, we support .bz2, and uncompressed.
plot(result)
bp.show_or_export()
auto/MiniExamples/varia/AccessingSimulationResults.py deleted 100755 → 0
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#!/usr/bin/env python3
"""
Extended example for simulation results treatment (cropping, slicing, exporting)
"""
import math
import random
import bornagain as ba
from bornagain import angstrom, ba_plot as bp, deg, nm, std_samples
from matplotlib import pyplot as plt
import datetime
def get_sample():
return std_samples.cylinders()
def get_simulation(sample):
"""
A GISAXS simulation with beam and detector defined.
"""
beam = ba.Beam(1e5, 1*angstrom, 0.2*deg)
n = 50
det = ba.SphericalDetector(n, -2*deg, 2*deg, n, 0, 2*deg)
simulation = ba.ScatteringSimulation(beam, sample, det)
return simulation
def get_noisy_image(field):
"""
Returns clone of input field filled with additional noise
"""
result = field.clone()
noise_factor = 2.0
for i in range(0, result.size()):
amplitude = field.valAt(i)
sigma = noise_factor*math.sqrt(amplitude)
noisy_amplitude = random.gauss(amplitude, sigma)
result.setAt(i, noisy_amplitude)
return result
def plot_histogram(field, **kwargs):
bp.plot_histogram(field,
xlabel=r'$\varphi_f ^{\circ}$',
ylabel=r'$\alpha_{\rm f} ^{\circ}$',
zlabel="",
**kwargs)
def plot_slices(noisy):
"""
Plot 1D slices along y-axis at certain x-axis values.
"""
plt.yscale('log')
# projection along Y, slice at fixed x-value
proj1 = noisy.yProjection(0)
plt.plot(proj1.axis(0).binCenters(),
proj1.flatVector(),
label=r'$\varphi=0.0^{\circ}$')
# projection along Y, slice at fixed x-value
proj2 = noisy.yProjection(0.5) # slice at fixed value
plt.plot(proj2.axis(0).binCenters(),
proj2.flatVector(),
label=r'$\varphi=0.5^{\circ}$')
# projection along Y for all X values between [xlow, xup], averaged
proj3 = noisy.yProjection(0.41, 0.59)
plt.plot(proj3.axis(0).binCenters(),
proj3.flatVector(),
label=r'$<\varphi>=0.5^{\circ}$')
plt.xlim(proj1.axis(0).min(), proj1.axis(0).max())
plt.ylim(proj1.maxVal()*3e-6, proj1.maxVal()*3)
plt.xlabel(r'$\alpha_{\rm f} ^{\circ}$', fontsize=16)
plt.legend(loc='upper right')
def plot(field):
"""
Demonstrates modified data plots.
"""
plt.subplots(2, 2, figsize=(12.80, 10.24))
plt.subplot(2, 2, 1)
bp.plot_histogram(field)
plt.title("Intensity as heatmap")
plt.subplot(2, 2, 2)
crop = field.crop(-1, 0.5, 1, 1)
bp.plot_histogram(crop)
plt.title("Cropping")
plt.subplot(2, 2, 3)
noisy = get_noisy_image(field)
reldiff = ba.relativeDifferenceField(noisy, field).npArray()
bp.plot_array(reldiff, intensity_min=1e-03, intensity_max=10)
plt.title("Relative difference")
plt.subplot(2, 2, 4)
plot_slices(noisy)
plt.title("Various slicing of 2D into 1D")
plt.tight_layout()
if __name__ == '__main__':
sample = get_sample()
simulation = get_simulation(sample)
result = simulation.simulate()
if bp.datfile:
ba.writeDatafield(result, bp.datfile + ".int")
# Other supported extensions are .tif and .txt.
# Besides compression .gz, we support .bz2, and uncompressed.
plot(result)
bp.show_or_export()
hugo/content/ex/result/export/_index.md
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...@@ -81,7 +81,6 @@ hist.save("result.int.gz") ...@@ -81,7 +81,6 @@ hist.save("result.int.gz")
Additional information can be found in the following pages: Additional information can be found in the following pages:
* [Accessing simulation results example](/ex/result/export/more.md)
* [Plotting with axes in different units](/ex/result/export/axes-in-different-units) * [Plotting with axes in different units](/ex/result/export/axes-in-different-units)
* [SimulationResult C++ class reference](http://apps.jcns.fz-juelich.de/doxy/BornAgain/classSimulationResult.html) * [SimulationResult C++ class reference](http://apps.jcns.fz-juelich.de/doxy/BornAgain/classSimulationResult.html)
* [Histogram1D C++ class reference](http://apps.jcns.fz-juelich.de/doxy/BornAgain/classHistogram1D.html) * [Histogram1D C++ class reference](http://apps.jcns.fz-juelich.de/doxy/BornAgain/classHistogram1D.html)
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hugo/content/ex/result/export/more.md deleted 100644 → 0
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+++
title = "Accessing simulation results"
weight = 10
+++
### Accessing simulation results
This is an extended example for the further treatment of simulation results: accessing the results, plotting, cropping, slicing and exporting. This serves as a supporting example to the [Accessing simulation results
](/py/export/_index.md) tutorial.
* The standard [Cylinders in DWBA](/ex/sim/gisas) sample
is used for running the simulation.
* The simulation results are retrieved as a `Histogram2D` object and then processed in various functions to achieve a resulting image.
{{< galleryscg >}}
{{< figscg src="/img/auto/varia/AccessingSimulationResults.png" width="670px" caption="Intensity images">}}
{{< /galleryscg >}}
{{< show-ex file="varia/AccessingSimulationResults.py" >}}
rawEx/varia/AccessingSimulationResults.py deleted 100755 → 0
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#!/usr/bin/env python3
"""
Extended example for simulation results treatment (cropping, slicing, exporting)
"""
import math
import random
import bornagain as ba
from bornagain import angstrom, ba_plot as bp, deg, nm, std_samples
from matplotlib import pyplot as plt
import datetime
def get_sample():
return std_samples.cylinders()
def get_simulation(sample):
"""
A GISAXS simulation with beam and detector defined.
"""
beam = ba.Beam(1e5, 1*angstrom, 0.2*deg)
n = <%= sm ? 50 : 200 %>
det = ba.SphericalDetector(n, -2*deg, 2*deg, n, 0, 2*deg)
simulation = ba.ScatteringSimulation(beam, sample, det)
return simulation
def get_noisy_image(field):
"""
Returns clone of input field filled with additional noise
"""
result = field.clone()
noise_factor = 2.0
for i in range(0, result.size()):
amplitude = field.valAt(i)
sigma = noise_factor*math.sqrt(amplitude)
noisy_amplitude = random.gauss(amplitude, sigma)
result.setAt(i, noisy_amplitude)
return result
def plot_histogram(field, **kwargs):
bp.plot_histogram(field,
xlabel=r'$\varphi_f ^{\circ}$',
ylabel=r'$\alpha_{\rm f} ^{\circ}$',
zlabel="",
**kwargs)
def plot_slices(noisy):
"""
Plot 1D slices along y-axis at certain x-axis values.
"""
plt.yscale('log')
# projection along Y, slice at fixed x-value
proj1 = noisy.yProjection(0)
plt.plot(proj1.axis(0).binCenters(),
proj1.flatVector(),
label=r'$\varphi=0.0^{\circ}$')
# projection along Y, slice at fixed x-value
proj2 = noisy.yProjection(0.5) # slice at fixed value
plt.plot(proj2.axis(0).binCenters(),
proj2.flatVector(),
label=r'$\varphi=0.5^{\circ}$')
# projection along Y for all X values between [xlow, xup], averaged
proj3 = noisy.yProjection(0.41, 0.59)
plt.plot(proj3.axis(0).binCenters(),
proj3.flatVector(),
label=r'$<\varphi>=0.5^{\circ}$')
plt.xlim(proj1.axis(0).min(), proj1.axis(0).max())
plt.ylim(proj1.maxVal()*3e-6, proj1.maxVal()*3)
plt.xlabel(r'$\alpha_{\rm f} ^{\circ}$', fontsize=16)
plt.legend(loc='upper right')
def plot(field):
"""
Demonstrates modified data plots.
"""
plt.subplots(2, 2, figsize=(12.80, 10.24))
plt.subplot(2, 2, 1)
bp.plot_histogram(field)
plt.title("Intensity as heatmap")
plt.subplot(2, 2, 2)
crop = field.crop(-1, 0.5, 1, 1)
bp.plot_histogram(crop)
plt.title("Cropping")
plt.subplot(2, 2, 3)
noisy = get_noisy_image(field)
reldiff = ba.relativeDifferenceField(noisy, field).npArray()
bp.plot_array(reldiff, intensity_min=1e-03, intensity_max=10)
plt.title("Relative difference")
plt.subplot(2, 2, 4)
plot_slices(noisy)
plt.title("Various slicing of 2D into 1D")
plt.tight_layout()
if __name__ == '__main__':
sample = get_sample()
simulation = get_simulation(sample)
result = simulation.simulate()
if bp.datfile:
ba.writeDatafield(result, bp.datfile + ".int")
# Other supported extensions are .tif and .txt.
# Besides compression .gz, we support .bz2, and uncompressed.
plot(result)
bp.show_or_export()
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