def testPlotAvgPatternLegacy(self):
""" Check we can plot the average diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(
input_path=TestUtilities.generateTestFilePath('diffr_0.1'))
analyzer.plotPattern(operation=numpy.mean)
if RENDER_PLOT:
plt.show()
def main():
analyzer = DiffractionAnalysis(input_path=input_path,
pattern_indices=pattern_indices,
poissonize=True)
parameters = diffractionParameters(input_path)
nx, ny = parameters["geom"]["mask"].shape
mask = parameters["geom"]["mask"]
nx, ny = mask.shape
beamstop = 20
mask[nx // 2 - beamstop // 2:nx // 2 + beamstop // 2 + 1,
ny // 2 - beamstop // 2:ny // 2 + beamstop // 2 + 1]
analyzer.mask = mask
pattern = numpy.mean([p for p in analyzer.patterns_iterator], axis=0)
qs, intensities = azimuthalIntegration(pattern,
diffractionParameters(input_path))
plt.plot(qs, intensities)
plt.xlabel(r"$2\theta$ (deg)")
plt.ylabel("Intensity (arb. units)")
plt.tight_layout()
plt.show()
def testPlotOnePattern(self):
""" Check we can plot one diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices=4)
analyzer.plotPattern()
if RENDER_PLOT:
plt.show()
def main(args=None):
# Setup the object.
analyzer = DiffractionAnalysis(
input_path=args.input_path,
pattern_indices=eval(args.pattern_indices),
poissonize=eval(args.poissonize),
)
# Plot if requested.
if args.plot:
analyzer.plotPattern(
logscale=args.logscale,
operation=eval(args.operation),
)
# Plot if requested.
if args.radial:
analyzer.plotRadialProjection(
logscale=args.logscale,
operation=eval(args.operation),
)
if args.statistics:
analyzer.statistics()
plt.show()
# Animate if requested.
if args.animation_filename:
analyzer.animatePatterns(output_path=args.animation_filename)
print "Animated gif saved to %s." % (
analyzer._DiffractionAnalysis__animation_output_path)
def testPlotSumPatternLogscale(self):
""" Check we can plot one diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
poissonize=False)
analyzer.plotPattern(operation=numpy.sum, logscale=True)
if RENDER_PLOT:
plt.show()
def testPlotAvgSequenceInt(self):
""" Check we can plot the avg over a subset of patterns given as list of ints."""
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices=[1, 3, 6])
analyzer.plotPattern(operation=numpy.mean)
if RENDER_PLOT:
plt.show()
def testPlotOnePatternLegacy(self):
""" Check we can plot one diffraction pattern from a v0.1 dir as a color map. """
analyzer = DiffractionAnalysis(
input_path=TestUtilities.generateTestFilePath('diffr_0.1'),
pattern_indices=4)
analyzer.plotPattern(operation=None)
if RENDER_PLOT:
plt.show()
def testShannonPixelPhoton(self):
""" Check if we can get the average number of photons per shannon pixel at a certain resolution"""
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices="all",
poissonize=True)
# Get the number of photons per shannon pixel at the resolution of 10 angstrom
analyzer.shannonPixelPhoton(10)
def testOneNumpyPattern(self):
""" Check if we can getting the numpy array of one snapshot """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices=1,
poissonize=True)
self.assertEqual(analyzer.npattern, 1)
pattern_one = analyzer.numpyPattern()
self.assertEqual(pattern_one.shape, (81, 81))
def testWholeNumpyPattern(self):
""" Check if we can getting the numpy array of the whole set of diffraction patterns """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices="all",
poissonize=True)
self.assertEqual(analyzer.npattern, 1000)
patterns = analyzer.numpyPattern()
self.assertEqual(patterns.shape, (1000, 81, 81))
def testRadialProjection(self):
""" Check that we can get two plots (resetting the iterator works.)"""
analyzer = DiffractionAnalysis(input_path=self.__test_data, pattern_indices="all", poissonize=True)
analyzer.logscale = False
analyzer.plotRadialProjection()
analyzer.plotRadialProjection(logscale=True)
analyzer.plotRadialProjection(operation=numpy.std)
def testGetQMap(self):
""" Check the 2D reciprocal space mapping """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices="all",
poissonize=True)
qMap = analyzer.qMap
def testSolidAngles(self):
""" Check getting solid angles mapping """
analyzer = DiffractionAnalysis(input_path=self.__test_data,
pattern_indices="all",
poissonize=True)
sa = analyzer.solidAngles
def testPlotAndStatistics(self):
""" Check that we can get two plots (resetting the iterator works.)"""
analyzer = DiffractionAnalysis(input_path=self.__test_data, pattern_indices="all", poissonize=True)
analyzer.logscale = True
analyzer.plotPattern(logscale=True)
analyzer.statistics()
def testShapedConstructionDefaults(self):
""" Testing the construction of the class with non-default parameters. """
# Construct the object.
analyzer = DiffractionAnalysis(input_path=self.__test_data, )
self.assertIsInstance(analyzer, DiffractionAnalysis)
self.assertIsInstance(analyzer, AbstractAnalysis)
self.assertIsInstance(analyzer, object)
self.assertIsInstance(analyzer.input_path, str)
self.assertEqual(analyzer.input_path, self.__test_data)
self.assertTrue(analyzer.poissonize)
self.assertEqual(analyzer.pattern_indices, "all")
def testAnimatePatterns(self):
""" Test the animation feature. """
# Setup the analyser with a sequence of patterns.
analyzer = DiffractionAnalysis(
input_path=self.__test_data,
pattern_indices=list(range(1, 11)),
)
# Check exceptions on faulty path.
self.assertRaises(TypeError,
analyzer.animatePatterns,
output_path=["not", "a", "path"])
self.assertRaises(IOError,
analyzer.animatePatterns,
output_path="/users/home/myself/animation.gif")
# Check default behaviour.
analyzer.animatePatterns(output_path=None)
# Check output is present.
animation_out_path = 'animated_patterns.gif'
self.__files_to_remove.append(animation_out_path)
self.assertIn(animation_out_path, os.listdir(os.getcwd()))
# Check path is stored on object.
self.assertEqual(analyzer._DiffractionAnalysis__animation_output_path,
os.path.join(os.getcwd(), animation_out_path))
# Check exception on overwrite.
self.assertRaises(IOError,
analyzer.animatePatterns,
output_path=animation_out_path)
# Execute with parameter.
animation_out_path = 'animation2.gif'
self.__files_to_remove.append(animation_out_path)
analyzer.animatePatterns(output_path=animation_out_path)
# Check path is stored on object.
self.assertEqual(analyzer._DiffractionAnalysis__animation_output_path,
os.path.join(os.getcwd(), animation_out_path))
# Check file is present.
self.assertIn(animation_out_path, os.listdir(os.getcwd()))
def plot_diffr_vs_detector(self):
""" Compare patterns before and after detector sim. """
# Cleanup.
#self.__files_to_remove.append('5mzd.pdb')
#self.__files_to_remove.append('diffr.h5')
#self.__dirs_to_remove.append('diffr')
# Avoid crash due to multiple instances of G4RunManager
del self._detector
# Setup detector geometry.
detector_panel = DetectorPanel(
ranges={
'fast_scan_min': 0,
'fast_scan_max': 511,
'slow_scan_min': 0,
'slow_scan_max': 511
},
pixel_size=2.2e-4 * Units.meter,
photon_response=1.0,
distance_from_interaction_plane=0.13 * Units.meter,
corners={
'x': -256,
'y': -256
},
)
detector_geometry = DetectorGeometry(panels=[detector_panel])
# Setup photon beam.
beam = PhotonBeamParameters(
photon_energy=4.96e3 * Units.electronvolt,
beam_diameter_fwhm=1.0e-6 * Units.meter,
pulse_energy=1.0e-3 * Units.joule,
photon_energy_relative_bandwidth=0.001,
divergence=1e-3 * Units.radian,
photon_energy_spectrum_type="SASE",
)
# Setup and run the diffraction sim.
diffraction_parameters = SingFELPhotonDiffractorParameters(
uniform_rotation=None,
calculate_Compton=False,
number_of_diffraction_patterns=1,
detector_geometry=detector_geometry,
beam_parameters=beam,
sample="5mzd.pdb",
forced_mpi_command='mpirun -np 1',
)
photon_diffractor = SingFELPhotonDiffractor(
parameters=diffraction_parameters,
output_path='diffr',
)
photon_diffractor.backengine()
photon_diffractor.saveH5()
analysis1 = DiffractionAnalysis(photon_diffractor.output_path,
pattern_indices=[1],
poissonize=True)
analysis1.plotPattern(
operation=None,
logscale=False,
)
parameters = XCSITPhotonDetectorParameters(
detector_type="AGIPDSPB",
patterns=[0],
)
detector = XCSITPhotonDetector(
parameters=parameters,
input_path="diffr.h5",
output_path="detector_out.h5",
)
detector._readH5()
detector.backengine()
detector.saveH5()
# Weak test Check we have photons in the signal.
pattern = h5py.File("detector_out.h5", 'r')['data/0000001/data'].value
analysis2 = DiffractionAnalysis(detector.output_path,
pattern_indices=[1],
poissonize=True)
analysis2.plotPattern(
operation=None,
logscale=False,
)
mpl.pyplot.show()
sig_arr = linear(diffr_data, *sigs_popt)
diffr_noise = np.random.normal(diffr_data * mu, sig_arr)
return diffr_noise
def getPopt(sigs):
"""Get the fitting parametters for predicting sigmas"""
xdata = np.arange(len(sigs))
ydata = sigs
my_fitting = curve_fitting(linear, xdata, ydata)
return my_fitting.popt
# %%
diffr_data = '/gpfs/exfel/data/user/juncheng/EMCProject/src/controller/s10/diffr.h5'
diffr_analyzer = DiffractionAnalysis(diffr_data, 1, poissonize=False)
diffr_pattern = diffr_analyzer.numpyPattern()
# %%
def linear(x, a, b):
return a * x + b
def func_sq(x, a, b, c):
return a * x**2 + b * x + c
# mu, sigs_popt, diffr_fn, emc_out
fwhms = np.array([49.3, 56.4, 66.4])
sigs = fwhms / 2.355
def testPlotRMSPattern(self):
""" Check we can plot the rms diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(input_path=self.__test_data)
analyzer.plotPattern(operation=numpy.std)
plt.show()
def testPlotPatternDefault(self):
""" Check we the sum image of all patterns is plotted by default. """
analyzer = DiffractionAnalysis(input_path=self.__test_data)
analyzer.plotPattern()
plt.show()
def testPlotOnePatternPoissonized(self):
""" Check we can plot one diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(input_path=self.__test_data, pattern_indices=1)
analyzer.plotPattern()
plt.show()
def testPlotAvgPattern(self):
""" Check we can plot the average diffraction pattern as a color map. """
analyzer = DiffractionAnalysis(input_path=self.__test_data)
analyzer.plotPattern(operation=numpy.mean)
if RENDER_PLOT:
plt.show()
def SimExRead(idxs):
diffr_analyzer = DiffractionAnalysis(diffr_data, idxs, poissonize=False)
diffr_pattern = diffr_analyzer.numpyPattern()
