def frm_fourier_constrained_vol(vf, mf, vg, mg):
radius = vf.sizeX() / 2 - 3 # intepolation in the outer part is nonsense
b = 32
from pytom.basic.fourier import fft, ifft, ftshift, iftshift
vf = ftshift(reducedToFull(fft(iftshift(vf, inplace=False))),
inplace=False)
vg = ftshift(reducedToFull(fft(iftshift(vg, inplace=False))),
inplace=False)
vfr = real(vf)
vfi = imag(vf)
vgr = real(vg)
vgi = imag(vg)
res = np.zeros((2 * b, 2 * b, 2 * b))
for r in xrange(1, radius + 1):
corr = frm_fourier_constrained_corr(vol2sf(vfr, r,
b), vol2sf(vfi, r, b), mf,
vol2sf(vgr, r, b),
vol2sf(vgi, r, b), mg, True)
res += corr * (r**2)
return res
dummy4 = frm_corr(mf, mg)
res = dummy1 / ((dummy2 * dummy3)**0.5 * dummy4)
return res
dist = []
dist2 = []
for i in xrange(100):
phi = np.random.randint(360)
psi = np.random.randint(360)
the = np.random.randint(180)
rotateSpline(v, v2, phi, psi, the)
sf = vol2sf(v, r, b)
sf = sf * wedge
sf2 = vol2sf(v2, r, b)
sf2 = sf2 * wedge
res = bart_way(sf2, wedge, sf, wedge)
ang = frm_find_best_angle(res, b)
dist.append(rotation_distance([phi, psi, the], ang))
res = frm_constrained_corr(sf2, wedge, sf, wedge)
ang = frm_find_best_angle(res, b)
dist2.append(rotation_distance([phi, psi, the], ang))
print dist[-1], dist2[-1]
print 'Diff: ', np.max(dist), np.mean(dist), np.min(dist), np.std(dist)
# rotateSpline(v, v2, phi, psi, the) # fv2 = ftshift(reducedToFull(fft(iftshift(v2)))) # res = frm_fourier_corr(vol2sf(real(fv2), r, b), vol2sf(imag(fv2), r, b), vol2sf(real(fv1), r, b), vol2sf(imag(fv1), r, b)) # 2. rotate real and imag parts seperately and feed into the frm_fourier_corr fr = real(fv1) fi = imag(fv1) # rotateSpline(v, v2, phi, psi, the) # fv2 = ftshift(reducedToFull(fft(iftshift(v2)))) # fr2 = real(fv2) # fi2 = imag(fv2) fr2 = vol(fr); rotateSpline(fr, fr2, phi, psi, the) fi2 = vol(fi); rotateSpline(fi, fi2, phi, psi, the) fr = np.array(vol2sf(fr, r, b)) fi = np.array(vol2sf(fi, r, b)) fr2 = np.array(vol2sf(fr2, r, b)) fi2 = np.array(vol2sf(fi2, r, b)) fr2 = fr2 * w fi2 = fi2 * w res = frm_fourier_corr(fr2, fi2, fr, fi, return_real=True) # 3. add two volumes and get the final result # res = frm_constrained_corr(fr2, w, fr, m) + frm_constrained_corr(fi2, w, fi, m) ang = frm_find_best_angle(res, b) dist.append(rotation_distance(ang, [phi, psi, the]))
import numpy as np
from sh.soft import *
from sh.frm import *
from pytom.tools.maths import rotation_distance
from pytom_volume import *
from sh.vol2sf import vol2sf
b = 16
v = read('/fs/home/ychen/matlab/template/binning/temp80SRibosome_bin2.em')
v2 = vol(v)
r = 8
for i in xrange(100):
phi = np.random.randint(360)
psi = np.random.randint(360)
the = np.random.randint(180)
f = vol2sf(v, r, b)
rotateSpline(v, v2, phi, psi, the)
g = vol2sf(v2, r, b)
# 1. the soft way
res = soft_corr(g, f)
ang = soft_find_best_angle(res, b)
# 2. the frm way
# res = frm_corr(g, f)
# ang2 = frm_find_best_angle(res, b)
print rotation_distance(ang, [phi, psi, the]) #, rotation_distance(ang2, [phi, psi, the]), rotation_distance(ang, ang2)
t = timing()
t.start()
dist = []
dist2 = []
for i in xrange(100):
phi = np.random.randint(360)
psi = np.random.randint(360)
the = np.random.randint(180)
rotateSpline(
v, v2, phi, psi, the
) # you cannot expect very high accuracy, since we are using spline interpolation here
sf = np.array(vol2sf(v, r, b))
sf = sf * wedge
sf2 = np.array(vol2sf(v2, r, b))
sf2 = sf2 * wedge
res = frm_corr(sf2, sf)
ang = frm_find_best_angle(res, b)
dist.append(rotation_distance([phi, psi, the], ang))
res = frm_constrained_corr(sf2, wedge, sf, wedge)
ang = frm_find_best_angle(res, b)
dist2.append(rotation_distance([phi, psi, the], ang))
# print 'Diff: ', np.max(dist), np.mean(dist), np.min(dist), np.std(dist)
# print 'Diff2: ', np.max(dist2), np.mean(dist2), np.min(dist2), np.std(dist2)
from sh.frm import *
from sh.vol2sf import vol2sf
import numpy as np
from pytom.tools.maths import rotation_distance
from sh.soft import *
v = read('/fs/home/ychen/matlab/template/binning/temp80SRibosome_bin2.em')
r = 8
b = 32
start = -60
end = 60
wedge = create_wedge_sf(start, end, b)
# m1 = wedge+0.001
whole = np.ones(4 * b**2)
sf = np.array(vol2sf(v, r, b))
sf = sf - np.min(sf) + 1. # set all values above 1
# sf = sf / m1
# sf = create_wedge_sf(start, end, b, 1, 10)
sf2 = sf * wedge
res = frm_corr(sf2, sf)
ang = frm_find_best_angle(res, b)
print ang, rotation_distance([0, 0, 0], ang)
# print res.max(), res[0][b][b]
res = frm_constrained_corr(sf2, wedge, sf, whole)
ang = frm_find_best_angle(res, b)
print ang, rotation_distance([0, 0, 0], ang)
from sh.vol2sf import vol2sf
from pytom_volume import *
v = read('/fs/home/ychen/matlab/template/binning/temp80SRibosome_bin2.em')
r = 8
b = 32
for i in xrange(1000):
sf = vol2sf(v, r, b)
