def PRTF(O, I, B=0, mask=None):
"""
As defined in: High-resolution ab initio three-dimensional x-ray
diffraction microscopy Vol. 23, No. 5 / May 2006 / J. Opt. Soc. Am. A
"""
O = np.fft.fftn(O)
M = np.sqrt(np.abs(O)**2 + B)
amp = (np.sqrt(I) + 1.0e-10)
if mask is not None:
amp[~mask] = M[~mask]
prtf = M / amp
prtf = np.clip(prtf, 0.0, 3.0)
rav_prtf = rad_av(prtf, is_fft_shifted=True)
return prtf, rav_prtf
def PSD(O, I):
Oh = np.fft.fftn(O)
rad_av_I = rad_av(I, is_fft_shifted=True)
rad_av_intensity = rad_av(np.abs(Oh)**2, is_fft_shifted=True)
rad_av_phase = rad_av(np.angle(Oh), is_fft_shifted=True)
return rad_av_intensity, rad_av_I, rad_av_phase
import sys, os
sys.path.append(os.path.abspath('.'))
from src import era
if __name__ == '__main__':
fnam = sys.argv[1]
# read the h5 file
diff, diff_ret, support, support_ret, \
good_pix, solid_unit, solid_units_ret, \
emods, econs, efids, T, T_rav, B_rav = io_utils.read_output_h5(fnam)
pow = 1.0
# display the radial average of the data
diff_rav = noise.rad_av(diff * good_pix)
plot = pg.plot(diff_rav**pow)
# display the radial average of the retrieved diff
diff_ret = np.abs(np.fft.fftn(solid_units_ret[0]))**2
diff_ret_rav = noise.rad_av(diff_ret) + B_rav
plot.plot(diff_rav**pow, pen=pg.mkPen('b'))
# display the radial average of the background
plot.plot(B_rav**pow, pen=pg.mkPen('g'))
# display the radial average of the background
plot.plot(noise.rad_av(diff_ret)**pow, pen=pg.mkPen('r'))
########### Make a large background filled with the radial average
i = np.fft.fftfreq(diff.shape[0]) * diff.shape[0]
import sys, os
sys.path.append(os.path.abspath('.'))
from src import era
if __name__ == '__main__':
fnam = sys.argv[1]
# read the h5 file
diff, diff_ret, support, support_ret, \
good_pix, solid_unit, solid_units_ret, \
emods, econs, efids, T, T_rav, B_rav = io_utils.read_output_h5(fnam)
pow = 1.0
# display the radial average of the data
diff_rav = noise.rad_av(diff * good_pix)
plot = pg.plot(diff_rav**pow)
# display the radial average of the retrieved diff
diff_ret = np.abs(np.fft.fftn(solid_units_ret[0]))**2
diff_ret_rav = noise.rad_av(diff_ret) + B_rav
plot.plot(diff_rav**pow, pen=pg.mkPen('b'))
# display the radial average of the background
plot.plot(B_rav**pow, pen=pg.mkPen('g'))
# display the radial average of the background
plot.plot(noise.rad_av(diff_ret)**pow, pen=pg.mkPen('r'))
########### Make a large background filled with the radial average