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))
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
mu = 92.1 #ADU/photon
def SimExRead(idxs):
diffr_analyzer = DiffractionAnalysis(diffr_data, idxs, poissonize=False)
diffr_pattern = diffr_analyzer.numpyPattern()
