def gen_rings_ctf( prjref, nx, ctf, numr):
"""
Convert set of ffts of projections to Fourier rings with additional multiplication by a ctf
The command returns list of rings
"""
from math import sin, cos, pi
from fundamentals import fft
from alignment import ringwe
from filter import filt_ctf
mode = "F"
wr_four = ringwe(numr, "F")
cnx = nx//2 + 1
cny = nx//2 + 1
qv = pi/180.0
refrings = [] # list of (image objects) reference projections in Fourier representation
for i in range( len(prjref) ):
cimage = Util.Polar2Dm(filt_ctf(prjref[i], ctf, True) , cnx, cny, numr, mode) # currently set to quadratic....
Util.Normalize_ring(cimage, numr, 0 )
Util.Frngs(cimage, numr)
Util.Applyws(cimage, numr, wr_four)
refrings.append(cimage)
phi = prjref[i].get_attr('phi')
theta = prjref[i].get_attr('theta')
psi = prjref[i].get_attr('psi')
n1 = sin(theta*qv)*cos(phi*qv)
n2 = sin(theta*qv)*sin(phi*qv)
n3 = cos(theta*qv)
refrings[i].set_attr_dict( {"n1":n1, "n2":n2, "n3":n3, "phi": phi, "theta": theta,"psi": psi} )
return refrings
def gen_rings_ctf( prjref, nx, ctf, numr):
"""
Convert set of ffts of projections to Fourier rings with additional multiplication by a ctf
The command returns list of rings
"""
from math import sin, cos, pi
from fundamentals import fft
from alignment import ringwe
from filter import filt_ctf
mode = "F"
wr_four = ringwe(numr, "F")
cnx = nx//2 + 1
cny = nx//2 + 1
qv = pi/180.0
refrings = [] # list of (image objects) reference projections in Fourier representation
for i in xrange( len(prjref) ):
cimage = Util.Polar2Dm(filt_ctf(prjref[i], ctf, True) , cnx, cny, numr, mode) # currently set to quadratic....
Util.Normalize_ring(cimage, numr)
Util.Frngs(cimage, numr)
Util.Applyws(cimage, numr, wr_four)
refrings.append(cimage)
phi = prjref[i].get_attr('phi')
theta = prjref[i].get_attr('theta')
psi = prjref[i].get_attr('psi')
n1 = sin(theta*qv)*cos(phi*qv)
n2 = sin(theta*qv)*sin(phi*qv)
n3 = cos(theta*qv)
refrings[i].set_attr_dict( {"n1":n1, "n2":n2, "n3":n3, "phi": phi, "theta": theta,"psi": psi} )
return refrings
def prepare_refringsHelical( volft, kb, nx, delta, ref_a, oplane, sym, numr, MPI=False):
"""
prepare projections for helical processing
rotation 180 degrees inplane & specified out-of-plane
"""
from alignment import ringwe, Applyws
from projection import prgs
from math import sin, cos, pi
from applications import MPI_start_end
from utilities import bcast_list_to_all, bcast_number_to_all, reduce_EMData_to_root, bcast_EMData_to_all
import re
# convert csym to integer:
sym = int(re.sub("\D", "", sym))
# generate list of Eulerian angles for reference projections
# phi, theta, psi
mode = "F"
ref_angles = []
inplane=int((179.99/sym)/delta) + 1
# first create 0 and positive out-of-plane tilts
i = 0
while i < oplane:
for j in xrange(inplane):
t = j*delta
ref_angles.append([t,90.0+i,90.0])
i+=delta
# negative out of plane rotation
i = -(delta)
while i > -(oplane):
for j in xrange(inplane):
t = j*delta
ref_angles.append([t,90.0+i,90.0])
i-=delta
wr_four = ringwe(numr, mode)
cnx = nx//2 + 1
cny = nx//2 + 1
qv = pi/180.
num_ref = len(ref_angles)
if MPI:
from mpi import mpi_comm_rank, mpi_comm_size, MPI_COMM_WORLD
myid = mpi_comm_rank( MPI_COMM_WORLD )
ncpu = mpi_comm_size( MPI_COMM_WORLD )
else:
ncpu = 1
myid = 0
from applications import MPI_start_end
ref_start,ref_end = MPI_start_end( num_ref, ncpu, myid )
refrings = [] # list of (image objects) reference projections in Fourier representation
sizex = numr[ len(numr)-2 ] + numr[ len(numr)-1 ] - 1
for i in xrange(num_ref):
prjref = EMData()
prjref.set_size(sizex, 1, 1)
refrings.append(prjref)
for i in xrange(ref_start, ref_end):
prjref = prgs(volft, kb, [ref_angles[i][0], ref_angles[i][1], ref_angles[i][2], 0.0, 0.0])
cimage = Util.Polar2Dm(prjref, cnx, cny, numr, mode) # currently set to quadratic....
Util.Normalize_ring(cimage, numr)
Util.Frngs(cimage, numr)
Applyws(cimage, numr, wr_four)
refrings[i] = cimage
if MPI:
from utilities import bcast_EMData_to_all
for i in xrange(num_ref):
for j in xrange(ncpu):
ref_start,ref_end = MPI_start_end(num_ref,ncpu,j)
if i >= ref_start and i < ref_end: rootid = j
bcast_EMData_to_all( refrings[i], myid, rootid )
for i in xrange(len(ref_angles)):
n1 = sin(ref_angles[i][1]*qv)*cos(ref_angles[i][0]*qv)
n2 = sin(ref_angles[i][1]*qv)*sin(ref_angles[i][0]*qv)
n3 = cos(ref_angles[i][1]*qv)
refrings[i].set_attr_dict( {"n1":n1, "n2":n2, "n3":n3} )
refrings[i].set_attr("phi", ref_angles[i][0])
refrings[i].set_attr("theta", ref_angles[i][1])
refrings[i].set_attr("psi", ref_angles[i][2])
return refrings
def compare(compare_ref_free, outfile_repro,ref_free_output,yrng, xrng, rstep,nx,apix,ref_free_cutoff, nproc, myid, main_node):
from alignment import Numrinit, ringwe, Applyws
from random import seed, randint
from utilities import get_params2D, set_params2D, model_circle, inverse_transform2, combine_params2
from fundamentals import rot_shift2D
from mpi import MPI_COMM_WORLD, mpi_barrier, mpi_bcast, MPI_INT
from statistics import fsc_mask
from filter import fit_tanh
from numpy import array
fout = "%s.hdf" % ref_free_output
frc_out = "%s_frc" % ref_free_output
res_out = "%s_res" % ref_free_output
nima = EMUtil.get_image_count(compare_ref_free)
image_start, image_end = MPI_start_end(nima, nproc, myid)
ima = EMData()
ima.read_image(compare_ref_free, image_start)
last_ring = nx/2-2
first_ring = 1
mask = model_circle(last_ring, nx, nx)
refi = []
numref = EMUtil.get_image_count(outfile_repro)
cnx = nx/2 +1
cny = cnx
mode = "F"
numr = Numrinit(first_ring, last_ring, rstep, mode)
wr = ringwe(numr, mode)
ima.to_zero()
for j in xrange(numref):
temp = EMData()
temp.read_image(outfile_repro, j)
# even, odd, numer of even, number of images. After frc, totav
refi.append(temp)
# for each node read its share of data
data = EMData.read_images(compare_ref_free, range(image_start, image_end))
for im in xrange(image_start, image_end):
data[im-image_start].set_attr('ID', im)
set_params2D(data[im-image_start],[0,0,0,0,1])
ringref = []
for j in xrange(numref):
refi[j].process_inplace("normalize.mask", {"mask":mask, "no_sigma":1}) # normalize reference images to N(0,1)
cimage = Util.Polar2Dm(refi[j], cnx, cny, numr, mode)
Util.Frngs(cimage, numr)
Applyws(cimage, numr, wr)
ringref.append(cimage)
if myid == main_node: seed(1000)
data_shift = []
frc = []
res = []
for im in xrange(image_start, image_end):
alpha, sx, sy, mirror, scale = get_params2D(data[im-image_start])
alphai, sxi, syi, scalei = inverse_transform2(alpha, sx, sy, 1.0)
# normalize
data[im-image_start].process_inplace("normalize.mask", {"mask":mask, "no_sigma":1}) # subtract average under the mask
# align current image to the reference
[angt, sxst, syst, mirrort, xiref, peakt] = Util.multiref_polar_ali_2d(data[im-image_start], ringref, xrng, yrng, 1, mode, numr, cnx+sxi, cny+syi)
iref = int(xiref)
[alphan, sxn, syn, mn] = combine_params2(0.0, -sxi, -syi, 0, angt, sxst, syst, (int)(mirrort))
set_params2D(data[im-image_start], [alphan, sxn, syn, int(mn), scale])
temp = rot_shift2D(data[im-image_start], alphan, sxn, syn, mn)
temp.set_attr('assign',iref)
tfrc = fsc_mask(temp,refi[iref],mask = mask)
temp.set_attr('frc',tfrc[1])
res = fit_tanh(tfrc)
temp.set_attr('res',res)
data_shift.append(temp)
for node in xrange(nproc):
if myid == node:
for image in data_shift:
image.write_image(fout,-1)
refindex = image.get_attr('assign')
refi[refindex].write_image(fout,-1)
mpi_barrier(MPI_COMM_WORLD)
rejects = []
if myid == main_node:
a = EMData()
index = 0
frc = []
res = []
temp = []
classes = []
for im in xrange(nima):
a.read_image(fout, index)
frc.append(a.get_attr("frc"))
if ref_free_cutoff != -1: classes.append(a.get_attr("class_ptcl_idxs"))
tmp = a.get_attr("res")
temp.append(tmp[0])
res.append("%12f" %(apix/tmp[0]))
res.append("\n")
index = index + 2
res_num = array(temp)
mean_score = res_num.mean(axis=0)
std_score = res_num.std(axis=0)
std = std_score / 2
if ref_free_cutoff !=-1:
cutoff = mean_score - std * ref_free_cutoff
reject = res_num < cutoff
index = 0
for i in reject:
if i: rejects.extend(classes[index])
index = index + 1
rejects.sort()
length = mpi_bcast(len(rejects),1,MPI_INT,main_node, MPI_COMM_WORLD)
rejects = mpi_bcast(rejects,length , MPI_INT, main_node, MPI_COMM_WORLD)
del a
fout_frc = open(frc_out,'w')
fout_res = open(res_out,'w')
fout_res.write("".join(res))
temp = zip(*frc)
datstrings = []
for i in temp:
for j in i:
datstrings.append(" %12f" % (j))
datstrings.append("\n")
fout_frc.write("".join(datstrings))
fout_frc.close()
del refi
del ringref
return rejects
def compare(compare_ref_free, outfile_repro, ref_free_output, yrng, xrng,
rstep, nx, apix, ref_free_cutoff, nproc, myid, main_node):
from alignment import Numrinit, ringwe, Applyws
from random import seed, randint
from utilities import get_params2D, set_params2D, model_circle, inverse_transform2, combine_params2
from fundamentals import rot_shift2D
from mpi import MPI_COMM_WORLD, mpi_barrier, mpi_bcast, MPI_INT
from statistics import fsc_mask
from filter import fit_tanh
from numpy import array
fout = "%s.hdf" % ref_free_output
frc_out = "%s_frc" % ref_free_output
res_out = "%s_res" % ref_free_output
nima = EMUtil.get_image_count(compare_ref_free)
image_start, image_end = MPI_start_end(nima, nproc, myid)
ima = EMData()
ima.read_image(compare_ref_free, image_start)
last_ring = nx / 2 - 2
first_ring = 1
mask = model_circle(last_ring, nx, nx)
refi = []
numref = EMUtil.get_image_count(outfile_repro)
cnx = nx / 2 + 1
cny = cnx
mode = "F"
numr = Numrinit(first_ring, last_ring, rstep, mode)
wr = ringwe(numr, mode)
ima.to_zero()
for j in xrange(numref):
temp = EMData()
temp.read_image(outfile_repro, j)
# even, odd, numer of even, number of images. After frc, totav
refi.append(temp)
# for each node read its share of data
data = EMData.read_images(compare_ref_free, range(image_start, image_end))
for im in xrange(image_start, image_end):
data[im - image_start].set_attr('ID', im)
set_params2D(data[im - image_start], [0, 0, 0, 0, 1])
ringref = []
for j in xrange(numref):
refi[j].process_inplace("normalize.mask", {
"mask": mask,
"no_sigma": 1
}) # normalize reference images to N(0,1)
cimage = Util.Polar2Dm(refi[j], cnx, cny, numr, mode)
Util.Frngs(cimage, numr)
Applyws(cimage, numr, wr)
ringref.append(cimage)
if myid == main_node: seed(1000)
data_shift = []
frc = []
res = []
for im in xrange(image_start, image_end):
alpha, sx, sy, mirror, scale = get_params2D(data[im - image_start])
alphai, sxi, syi, scalei = inverse_transform2(alpha, sx, sy, 1.0)
# normalize
data[im - image_start].process_inplace("normalize.mask", {
"mask": mask,
"no_sigma": 1
}) # subtract average under the mask
# align current image to the reference
[angt, sxst, syst, mirrort, xiref,
peakt] = Util.multiref_polar_ali_2d(data[im - image_start], ringref,
xrng, yrng, 1, mode, numr,
cnx + sxi, cny + syi)
iref = int(xiref)
[alphan, sxn, syn, mn] = combine_params2(0.0, -sxi, -syi, 0, angt,
sxst, syst, (int)(mirrort))
set_params2D(data[im - image_start],
[alphan, sxn, syn, int(mn), scale])
temp = rot_shift2D(data[im - image_start], alphan, sxn, syn, mn)
temp.set_attr('assign', iref)
tfrc = fsc_mask(temp, refi[iref], mask=mask)
temp.set_attr('frc', tfrc[1])
res = fit_tanh(tfrc)
temp.set_attr('res', res)
data_shift.append(temp)
for node in xrange(nproc):
if myid == node:
for image in data_shift:
image.write_image(fout, -1)
refindex = image.get_attr('assign')
refi[refindex].write_image(fout, -1)
mpi_barrier(MPI_COMM_WORLD)
rejects = []
if myid == main_node:
a = EMData()
index = 0
frc = []
res = []
temp = []
classes = []
for im in xrange(nima):
a.read_image(fout, index)
frc.append(a.get_attr("frc"))
if ref_free_cutoff != -1:
classes.append(a.get_attr("class_ptcl_idxs"))
tmp = a.get_attr("res")
temp.append(tmp[0])
res.append("%12f" % (apix / tmp[0]))
res.append("\n")
index = index + 2
res_num = array(temp)
mean_score = res_num.mean(axis=0)
std_score = res_num.std(axis=0)
std = std_score / 2
if ref_free_cutoff != -1:
cutoff = mean_score - std * ref_free_cutoff
reject = res_num < cutoff
index = 0
for i in reject:
if i: rejects.extend(classes[index])
index = index + 1
rejects.sort()
length = mpi_bcast(len(rejects), 1, MPI_INT, main_node,
MPI_COMM_WORLD)
rejects = mpi_bcast(rejects, length, MPI_INT, main_node,
MPI_COMM_WORLD)
del a
fout_frc = open(frc_out, 'w')
fout_res = open(res_out, 'w')
fout_res.write("".join(res))
temp = zip(*frc)
datstrings = []
for i in temp:
for j in i:
datstrings.append(" %12f" % (j))
datstrings.append("\n")
fout_frc.write("".join(datstrings))
fout_frc.close()
del refi
del ringref
return rejects
