def errors_per_image(params, avgtrans, thresherr=1.0, radius=1.0):
#print "errors per image"
# We have average parameters and transformed parameters
# Find errors per image
ll = len(params)
nn = len(params[0])
perr = [None] * nn
for k in xrange(nn):
#
nas = [0.0, 0.0, 0.0]
r1, r2, r3 = getfvec(avgtrans[k][0], avgtrans[k][1])
sacos = 0.0
sder = 0.0
ser3 = 0.0
for i in xrange(ll):
#print i,fifi[i]
d = max_3D_pixel_error(params[i][k], avgtrans[k], r=radius)
#if(d>10.): print " LARGE ERROR",k,i,d,fifi[i], avgtrans[k]
ser3 += d
n1, n2, n3 = getfvec(params[i][k][0], params[i][k][1])
sacos += lacos(n1 * r1 + n2 * r2 + n3 * r3)
sder += pixel_error_2D(params[i][k][2:], avgtrans[k][2:], r=1.0)
# average deviation in radians
sacos /= ll
sare = tan(sacos)
sder /= ll
ser3 /= ll
#print k, ser3, sare, sder
perr[k] = [ser3, sacos, sare, sder]
#write_text_row(perr, 'per.txt')
#perr = [perr[k][1] <= thresherr for k in xrange(nn)]
return perr
def errors_per_image(params, avgtrans, thresherr=1.0, radius = 1.0): #print "errors per image" # We have average parameters and transformed parameters # Find errors per image ll = len(params) nn = len(params[0]) perr = [None]*nn for k in xrange(nn): # nas = [0.0,0.0,0.0] r1,r2,r3 = getfvec(avgtrans[k][0],avgtrans[k][1]) sacos = 0.0 sder = 0.0 ser3 = 0.0 for i in xrange(ll): #print i,fifi[i] d = max_3D_pixel_error(params[i][k], avgtrans[k], r=radius) #if(d>10.): print " LARGE ERROR",k,i,d,fifi[i], avgtrans[k] ser3 += d n1,n2,n3 = getfvec(params[i][k][0],params[i][k][1]) sacos += acos( min(1.0, n1*r1+n2*r2+n3*r3) ) sder += pixel_error_2D(params[i][k][2:], avgtrans[k][2:], r = 1.0) # average deviation in radians sacos /= ll sare = tan(sacos) sder /= ll ser3 /= ll #print k, ser3, sare, sder perr[k] = [ser3, sacos, sare, sder] #write_text_row(perr, 'per.txt') #perr = [perr[k][1] <= thresherr for k in xrange(nn)] return perr
def average_trans(params):
# Compute average projection params and pixel errors
from utilities import getfvec
from pixel_error import max_3D_pixel_error
from math import sqrt, degrees, radians, acos
nn = lem(params[0])
avgtrans = [None] * nn
pixer = [0.0] * nn
for j in xrange(nn):
nas = [0.0, 0.0, 0.0]
if (sym == 1):
#pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(ll):
n1, n2, n3 = getfvec(params[i][j][0], params[i][j][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1, m2, m3 = getfvec(params[0][j][0], params[0][j][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
for i in xrange(1, ll):
qnom = -1.e10
for j in xrange(-1, 2, 1):
t1, t2, t3 = getfvec(params[i][j][0] + j * qsym,
params[i][j][1])
nom = t1 * m1 + t2 * m2 + t3 * m3
if (nom > qnom):
qnom = nom
n1 = t1
n2 = t2
n3 = t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print(qnom, n1, n2, n3, nas)
# To get the correct pixer phi angle has to be taken from the above!!
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if (nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2] / nom)) % 360.0
if (sym > 1 and ntheta > 90.0):
nphi = (degrees(atan2(nas[1], nas[0])) - 180.0) % qsym + 180.0
else:
nphi = degrees(atan2(nas[1], nas[0])) % qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform([params[ii][j][2:] for ii in xrange(ll)])
avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
return avgtrans
def average_trans(params): # Compute average projection params and pixel errors from utilities import getfvec from pixel_error import max_3D_pixel_error from math import sqrt, degrees, radians, acos nn = lem(params[0]) avgtrans = [None]*nn pixer = [0.0]*nn for j in xrange(nn): nas = [0.0,0.0,0.0] if( sym == 1): #pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius) for i in xrange(ll): n1,n2,n3 = getfvec(params[i][j][0],params[i][j][1]) nas[0] += n1 nas[1] += n2 nas[2] += n3 else: m1,m2,m3 = getfvec(params[0][j][0],params[0][j][1]) nas[0] = m1 nas[1] = m2 nas[2] = m3 for i in xrange(1,ll): qnom = -1.e10 for j in xrange(-1,2,1): t1,t2,t3 = getfvec(params[i][j][0]+j*qsym,params[i][j][1]) nom = t1*m1 + t2*m2 + t3*m3 if(nom > qnom): qnom = nom n1=t1 n2=t2 n3=t3 #if(k == 2): # print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom nas[0] += n1 nas[1] += n2 nas[2] += n3 print qnom, n1,n2,n3,nas # To get the correct pixer phi angle has to be taken from the above!! nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2) if(nom < 1.e-6): nphi = 0.0 ntheta = 0.0 else: ntheta = degrees(acos(nas[2]/nom))%360.0 if(sym>1 and ntheta>90.0): nphi = (degrees(atan2( nas[1], nas[0] ))-180.0)%qsym + 180.0 else: nphi = degrees(atan2( nas[1], nas[0] ))%qsym #print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta) twod = average2dtransform([params[ii][j][2:] for ii in xrange(ll)]) avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]] return avgtrans
def errors_per_image_original(nn,
qt,
asi,
avgtrans,
thresherr=1.0,
radius=1.0):
#print "errors per image"
# We have average parameters and transformed parameters
# Find errors per image
# Find outliers, remove them, repeat calculations
perr = [None] * nn
for k in xrange(nn):
lin = k // (nn // 4)
#
fifi = []
for j in xrange(6):
if (asi[lin][j] != -10):
#print " fff ",k,lin,j,asi[lin][j],qt[j][k]
fifi.append(qt[j][k])
assert (len(fifi) == 3)
nas = [0.0, 0.0, 0.0]
r1, r2, r3 = getfvec(avgtrans[k][0], avgtrans[k][1])
sacos = 0.0
sder = 0.0
ser3 = 0.0
for i in xrange(3):
#print i,fifi[i]
d = max_3D_pixel_error(fifi[i], avgtrans[k], r=radius)
#if(d>10.): print " LARGE ERROR",k,i,d,fifi[i], avgtrans[k]
ser3 += d
n1, n2, n3 = getfvec(fifi[i][0], fifi[i][1])
sacos += lacos(n1 * r1 + n2 * r2 + n3 * r3)
sder += pixel_error_2D(fifi[i][2:], avgtrans[k][2:], r=1.0)
# average deviation in radians
sacos /= 3.0
sare = tan(sacos)
sder /= 3.0
ser3 /= 3
#print k, ser3, sare, sder
perr[k] = [k, ser3, sacos, sare, sder]
#write_text_row(perr, 'per.txt')
perr = [perr[k][1] <= thresherr for k in xrange(nn)]
return perr
def errors_per_image_original(nn, qt, asi, avgtrans, thresherr=1.0, radius = 1.0): #print "errors per image" # We have average parameters and transformed parameters # Find errors per image # Find outliers, remove them, repeat calculations perr = [None]*nn for k in xrange(nn): lin = k//(nn//4) # fifi = [] for j in xrange(6): if(asi[lin][j] != -10): #print " fff ",k,lin,j,asi[lin][j],qt[j][k] fifi.append(qt[j][k]) assert(len(fifi) == 3) nas = [0.0,0.0,0.0] r1,r2,r3 = getfvec(avgtrans[k][0],avgtrans[k][1]) sacos = 0.0 sder = 0.0 ser3 = 0.0 for i in xrange(3): #print i,fifi[i] d = max_3D_pixel_error(fifi[i], avgtrans[k], r=radius) #if(d>10.): print " LARGE ERROR",k,i,d,fifi[i], avgtrans[k] ser3 += d n1,n2,n3 = getfvec(fifi[i][0],fifi[i][1]) sacos += acos(min(1.0,n1*r1+n2*r2+n3*r3)) sder += pixel_error_2D(fifi[i][2:], avgtrans[k][2:], r = 1.0) # average deviation in radians sacos /= 3.0 sare = tan(sacos) sder /= 3.0 ser3 /= 3 #print k, ser3, sare, sder perr[k] = [k, ser3, sacos, sare, sder] #write_text_row(perr, 'per.txt') perr = [perr[k][1] <= thresherr for k in xrange(nn)] return perr
def main():
arglist = []
for arg in sys.argv:
arglist.append(arg)
progname = os.path.basename(arglist[0])
usage = progname + " stack outdir --phase=1 --ou=outer_radius|sxconsistency.py --phase=3 newlocal/main000 --ou=133 --thresherr=3.0 --params=paramsa outgrouparms"
parser = OptionParser(usage, version=SPARXVERSION)
parser.add_option(
"--phase",
type="int",
default=1,
help=
"Phase =1 prepares resampled stacks, =2 analyzes consistency of orientation parameters"
)
parser.add_option("--ou",
type="int",
default=-1,
help="outer radius for calculation of pixel error")
parser.add_option("--sym",
type="string",
default="c1",
help="symmetry of the refined structure")
parser.add_option(
"--thresherr",
type="float",
default=1.0,
help="Threshold for accpetable orientation errors (in pixels)")
parser.add_option(
"--ndigits",
type="int",
default=1,
help="Accuracy for checking whether parameters are identical")
parser.add_option("--chunk",
type="string",
default="",
help="Root of of four chunk files with indeces")
parser.add_option(
"--params",
type="string",
default="",
help="Root of of six parameter file names with refinement results")
(options, args) = parser.parse_args(arglist[1:])
global_def.BATCH = True
if options.phase == 1 and len(args) == 2:
inputbdb = args[0]
outdir = args[1]
nn = EMUtil.get_image_count(inputbdb)
t = range(nn)
shuffle(t)
chunks = []
for i in xrange(4):
# I use the MPI function here just to easily get the balanced load
j, k = MPI_start_end(nn, 4, i)
chunks.append(t[j:k])
chunks[i].sort()
write_text_file(chunks[i], os.path.join(outdir,
'chunk%01d.txt' % i))
del t
write_text_file([len(chunks[i]) for i in xrange(4)],
os.path.join(outdir, 'chunklengths.txt'))
"""
pt = [[None]]*6
ll=0
for i in xrange(3):
for j in xrange(i+1,4):
pt[ll] = chunks[i]+chunks[j]
ll+=1
for i in xrange(6):
listfile = os.path.join(outdir,'lili%01d.txt'%i)
write_text_file(pt[i],listfile)
outbdb = "bdb:"+ os.path.join(outdir,"X%01d"%i)
cmd = '{} {} {} {}'.format('e2bdb.py', inputbdb, '--makevstack='+outbdb, '--list='+listfile)
subprocess.call(cmd, shell=True)
"""
# Run 6 programs
elif options.phase == 2 and len(args) == 2:
outdir = args[0]
howmanythesame = args[1]
ndigits = options.ndigits #for chc5 1, for ribo 4#4.0
prms = []
for i in xrange(6):
prms.append(
read_text_row(
os.path.join(outdir, options.params + "%01d.txt" % i)))
for j in xrange(len(prms[-1])):
for k in xrange(5):
prms[-1][j][k] = round(prms[-1][j][k], ndigits)
nn = 2 * len(prms[0])
n4 = nn // 4
qt = [[[-1.0]] * nn for i in xrange(6)]
ll = 0
for i in xrange(3):
for j in xrange(i + 1, 4):
qt[ll][i * n4:(i + 1) * n4] = prms[ll][:n4]
qt[ll][j * n4:(j + 1) * n4] = prms[ll][n4:]
ll += 1
thesame = 0
for ll in xrange(len(qt[0])):
rw = []
for j in xrange(6):
if (len(qt[j][ll]) > 1): rw.append(qt[j][ll])
isame = True
for j in xrange(3):
if (rw[0][j] != rw[1][j]):
isame = False
#print ll,rw[0][j], rw[1][j]
break
if (rw[0][j] != rw[2][j]):
isame = False
#print ll,rw[0][j], rw[2][j]
break
if isame: thesame += 1
qt = float(thesame) / nn
print("Proportion of the same orientations ", qt)
write_text_file([qt], os.path.join(outdir, howmanythesame))
######### PHASE 3
elif options.phase == 3 and len(args) == 2:
outdir = args[0]
outgrouparms = args[1]
radius = options.ou
thresherr = options.thresherr #for chc5 1, for ribo 4#4.0
sym = int(options.sym[1:])
qsym = 360.0 / sym
blocks = ['A', 'B', 'C', 'D']
params = {}
ll = 0
for i in xrange(3):
for j in xrange(i + 1, 4):
params[chr(65 + i) + chr(48 + ll)] = []
params[chr(65 + j) + chr(48 + ll)] = []
ll += 1
chunks = {}
chunklengths = {}
for i in xrange(4):
chunks[chr(65 + i)] = map(
int,
read_text_file(
os.path.join(outdir, options.chunk + "%01d.txt" % i)))
chunklengths[chr(65 + i)] = len(chunks[chr(65 + i)])
for i in xrange(6):
prms = read_text_row(
os.path.join(outdir, options.params + "%01d.txt" % i))
for q in blocks:
if q + chr(48 + i) in params:
params[q + chr(48 + i)] = prms[:chunklengths[q]]
del prms[:chunklengths[q]]
pairs = [["A0", "A1"], ["B3", "B4"], ["C1", "C5"], ["D2", "D4"]]
lefts = ["A2", "B0", "C3", "D5"]
# Compute average projection params and pixel errors
avgtrans = {}
pixer = {}
for i, q in enumerate(pairs):
avgtrans[q[0][0]] = [0.0] * chunklengths[q[0][0]]
pixer[q[0][0]] = [0.0] * chunklengths[q[0][0]]
for j in xrange(chunklengths[q[0][0]]):
fifi = [params[q[0]][j], params[q[1]][j]]
nas = [0.0, 0.0, 0.0]
if (sym == 1):
pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0],
fifi[1],
r=radius)
for i in xrange(2):
n1, n2, n3 = getfvec(fifi[i][0], fifi[i][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1, m2, m3 = getfvec(fifi[0][0], fifi[0][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
#if(k == 2):
# print "XXXX"
# print fifi[0],nas
for i in xrange(1, 2):
qnom = -1.e10
for j in xrange(-1, 2, 1):
t1, t2, t3 = getfvec(fifi[i][0] + j * qsym,
fifi[i][1])
nom = t1 * m1 + t2 * m2 + t3 * m3
if (nom > qnom):
qnom = nom
n1 = t1
n2 = t2
n3 = t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print(qnom, n1, n2, n3, nas)
# To get the correct pixer phi angle has to be taken from the above!!
pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0],
fifi[1],
r=radius)
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if (nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2] / nom)) % 360.0
if (sym > 1 and ntheta > 90.0):
nphi = (degrees(atan2(nas[1], nas[0])) -
180.0) % qsym + 180.0
else:
nphi = degrees(atan2(nas[1], nas[0])) % qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform([fifi[0][2:], fifi[1][2:]])
avgtrans[q[0][0]][j] = [
nphi, ntheta, twod[0], twod[1], twod[2]
]
perr = {}
tgood = 0
for q in blocks:
perr[q] = [True] * chunklengths[q]
for k in xrange(chunklengths[q]):
if (pixer[q][k] > thresherr): perr[q][k] = False
if perr[q][k]: tgood += 1
if (tgood < 4):
print(
" No good images within the pixel error threshold specified"
)
exit()
print(" tgood ", tgood)
hi = hist_list(
[pixer[q][k] for q in blocks for k in xrange(chunklengths[q])], 16)
for i in xrange(len(hi[0])):
print("%4d %12.3f %12.0f " % (i, hi[0][i], hi[1][i]))
# Finished, store average orientation params and table of good images
# store lists of good images for each group
# blocks is indexed by first letter
good = [[] for i in xrange(4)]
bad = [[] for i in xrange(4)]
for i, q in enumerate(blocks):
for k in xrange(chunklengths[q]):
#deprt = max_3D_pixel_error(params[lefts[i]][k],avgtrans[q][k],r=radius)
if perr[q][k]:
good[i].append(chunks[q][k])
#[chunks[q][k],pixer[q][k],deprt, params[pairs[i][0]][k],params[pairs[i][1]][k],params[lefts[i]][k],avgtrans[q][k] ])
else:
bad[i].append(chunks[q][k])
#[chunks[q][k],pixer[q][k],deprt, params[pairs[i][0]][k],params[pairs[i][1]][k],params[lefts[i]][k],avgtrans[q][k]])
write_text_file(good[i], os.path.join(outdir,
"newgood%01d.txt" % i))
write_text_file(bad[i], os.path.join(outdir, "newbad%01d.txt" % i))
# write out parameters, for those in pairs write out average, for leftouts leave them as they were
# These parameters refer to the original X files.
ll = 0
for m in xrange(6):
if q + chr(48 + m) in params:
prmsgood = []
prmsbad = []
try:
j = lefts.index(q + chr(48 + m))
for k in xrange(chunklengths[q]):
if perr[q][k]:
prmsgood.append(params[q + chr(48 + m)][k])
else:
prmsbad.append(params[q + chr(48 + m)][k])
except:
for k in xrange(chunklengths[q]):
if perr[q][k]:
prmsgood.append(avgtrans[q][k])
else:
prmsbad.append(avgtrans[q][k])
write_text_row(
prmsgood,
os.path.join(outdir,
"params-newgood%01d%01d.txt" % (i, ll)))
write_text_row(
prmsbad,
os.path.join(outdir,
"params-newbad%01d%01d.txt" % (i, ll)))
ll += 1
# Generate newlili files from newgood, these contain original numbering of the total single file
ll = 0
for i in xrange(3):
for j in xrange(i + 1, 4):
write_text_file(good[i] + good[j],
os.path.join(outdir, "newlili%01d.txt" % ll))
ll += 1
# write out parameters, for those in pairs write out average, for leftouts leave them as they were
# These parameters refer to the original X files.
for i in xrange(6):
prms = []
for q in blocks:
if q + chr(48 + i) in params:
try:
j = lefts.index(q + chr(48 + i))
prms += params[q + chr(48 + i)]
except:
prms += avgtrans[q]
write_text_row(prms,
os.path.join(outdir, outgrouparms + "%01d.txt" % i))
# Write chunklengths
chunklengths = [len(good[i]) for i in xrange(4)]
write_text_file(chunklengths, os.path.join(outdir, "chunklengths.txt"))
"""
# We do not use consecutive numbering anymore
# Generate newx files from newgood, these contain consecutive (with gaps) numbering that allows to generate truncated X files from the previous X files
ll = 0
for i in xrange(3):
firstblock = []
l = len(perr[blocks[i]])
for k in xrange(l):
if perr[blocks[i]][k]:
firstblock.append(k)
for j in xrange(i+1,4):
secondblock = []
for k in xrange(len(perr[blocks[j]])):
if perr[blocks[j]][k]:
secondblock.append(k+l)
write_text_file( firstblock + secondblock, os.path.join(outdir,"goodX%01d.txt"%ll) )
ll += 1
del good,bad,firstblock,secondblock,perr
"""
"""
0 1 2 3 4 5
A A A = = =
B = = B B =
= C = C = C
= = D = D D
"""
elif options.phase == 4 and len(args) == 1:
outdir = args[0]
bp = 'badparams'
#outgrouparms= args[1]
radius = options.ou
thresherr = options.thresherr
sym = int(options.sym[1:])
qsym = 360.0 / sym
#params = [[None for i in xrange(3)] for j in xrange(4)]
ll = 3 # this is hardwired as we have three groups. however, I would like to keep the code general.
for jj in xrange(4):
params = [None for ii in xrange(ll)]
newbad = map(int, read_text_file(options.params + "%01d.txt" % jj))
nn = len(newbad)
for ii in xrange(ll):
params[ii] = read_text_row(
os.path.join(outdir, bp + "%01d%01d.txt" % (jj, ii)))
assert (nn == len(params[ii]))
# Compute average projection params and pixel errors
avgtrans = [None] * nn
pixer = [0.0] * nn
for j in xrange(nn):
nas = [0.0, 0.0, 0.0]
if (sym == 1):
#pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(ll):
n1, n2, n3 = getfvec(params[i][j][0], params[i][j][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1, m2, m3 = getfvec(params[0][j][0], params[0][j][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
for i in xrange(1, ll):
qnom = -1.e10
for j in xrange(-1, 2, 1):
t1, t2, t3 = getfvec(params[i][j][0] + j * qsym,
params[i][j][1])
nom = t1 * m1 + t2 * m2 + t3 * m3
if (nom > qnom):
qnom = nom
n1 = t1
n2 = t2
n3 = t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print(qnom, n1, n2, n3, nas)
# To get the correct pixer phi angle has to be taken from the above!!
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if (nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2] / nom)) % 360.0
if (sym > 1 and ntheta > 90.0):
nphi = (degrees(atan2(nas[1], nas[0])) -
180.0) % qsym + 180.0
else:
nphi = degrees(atan2(nas[1], nas[0])) % qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform(
[params[ii][j][2:] for ii in xrange(ll)])
avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
perr = errors_per_image(params, avgtrans, thresherr, radius)
rescued = []
rejects = []
for j in xrange(nn):
#print chr(65+jj),j,perr[j][0],[[params[m][j][i] for i in xrange(2)] for m in xrange(ll)]
if (perr[j][0] <= thresherr): rescued.append([newbad[j], j])
else: rejects.append([newbad[j], j])
if (len(rescued) == 0):
write_text_row([-1, -1],
os.path.join(outdir, "rescued%01d.txt" % jj))
else:
write_text_row(rescued,
os.path.join(outdir, "rescued%01d.txt" % jj))
# We also have to write params.
if (len(rescued) != 0):
for ii in xrange(ll):
write_text_row(
[
params[ii][rescued[k][1]]
for k in xrange(len(rescued))
],
os.path.join(outdir,
"params-rescued%01d%01d.txt" % (jj, ii)))
if (len(rejects) == 0):
write_text_row([-1, -1],
os.path.join(outdir,
'rejects' + "%01d.txt" % jj))
else:
write_text_row(
rejects, os.path.join(outdir, 'rejects' + "%01d.txt" % jj))
if (len(rejects) != 0):
for ii in xrange(ll):
write_text_row(
[
params[ii][rejects[k][1]]
for k in xrange(len(rejects))
],
os.path.join(outdir,
"params-rejects%01d%01d.txt" % (jj, ii)))
hi = hist_list([perr[j][0] for j in xrange(nn)], 16)
print("Pixel errors for BAD GROUP ", chr(65 + jj))
for ii in xrange(len(hi[0])):
print("%4d %12.3f %12.0f " % (ii, hi[0][ii], hi[1][ii]))
elif options.phase == 5 and len(args) == 1:
# This version is for meridien refinement. There are simply three full sets of params.
outdir = args[0]
bp = 'badparams'
#outgrouparms= args[1]
radius = options.ou
thresherr = options.thresherr
sym = int(options.sym[1:])
qsym = 360.0 / sym
#params = [[None for i in xrange(3)] for j in xrange(4)]
ll = 3 # this is hardwired as we have three groups. however, I would like to keep the code general.
for jj in xrange(1):
params = [None for ii in xrange(ll)]
#newbad = map(int, read_text_file(options.params+"%01d.txt"%jj) )
#nn = len(newbad)
for ii in xrange(ll):
params[ii] = read_text_row(
os.path.join(outdir, "params%01d.txt" % (ii)))
#assert(nn == len(params[ii]) )
nn = len(params[0])
newbad = range(nn)
# Compute average projection params and pixel errors
avgtrans = [None] * nn
pixer = [0.0] * nn
for j in xrange(nn):
nas = [0.0, 0.0, 0.0]
if (sym == 1):
#pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(ll):
n1, n2, n3 = getfvec(params[i][j][0], params[i][j][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1, m2, m3 = getfvec(params[0][j][0], params[0][j][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
for i in xrange(1, ll):
qnom = -1.e10
for j in xrange(-1, 2, 1):
t1, t2, t3 = getfvec(params[i][j][0] + j * qsym,
params[i][j][1])
nom = t1 * m1 + t2 * m2 + t3 * m3
if (nom > qnom):
qnom = nom
n1 = t1
n2 = t2
n3 = t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print(qnom, n1, n2, n3, nas)
# To get the correct pixer phi angle has to be taken from the above!!
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if (nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2] / nom)) % 360.0
if (sym > 1 and ntheta > 90.0):
nphi = (degrees(atan2(nas[1], nas[0])) -
180.0) % qsym + 180.0
else:
nphi = degrees(atan2(nas[1], nas[0])) % qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform(
[params[ii][j][2:] for ii in xrange(ll)])
avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
write_text_row(avgtrans, os.path.join(outdir, "avgtrans.txt"))
perr = errors_per_image(params, avgtrans, thresherr, radius)
rescued = []
rejects = []
for j in xrange(nn):
#print chr(65+jj),j,perr[j][0],[[params[m][j][i] for i in xrange(2)] for m in xrange(ll)]
if (perr[j][0] <= thresherr): rescued.append([newbad[j], j])
else: rejects.append([newbad[j], j])
if (len(rescued) == 0):
write_text_row([-1, -1],
os.path.join(outdir, "rescued%01d.txt" % jj))
else:
write_text_row(rescued,
os.path.join(outdir, "rescued%01d.txt" % jj))
# We also have to write params.
if (len(rescued) != 0):
for ii in xrange(ll):
write_text_row(
[
params[ii][rescued[k][1]]
for k in xrange(len(rescued))
],
os.path.join(outdir,
"params-rescued%01d%01d.txt" % (jj, ii)))
if (len(rejects) == 0):
write_text_row([-1, -1],
os.path.join(outdir,
'rejects' + "%01d.txt" % jj))
else:
write_text_row(
rejects, os.path.join(outdir, 'rejects' + "%01d.txt" % jj))
if (len(rejects) != 0):
for ii in xrange(ll):
write_text_row(
[
params[ii][rejects[k][1]]
for k in xrange(len(rejects))
],
os.path.join(outdir,
"params-rejects%01d%01d.txt" % (jj, ii)))
hi = hist_list([perr[j][0] for j in xrange(nn)], 16)
print("Pixel errors for BAD GROUP ", chr(65 + jj))
for ii in xrange(len(hi[0])):
print("%4d %12.3f %12.0f " % (ii, hi[0][ii], hi[1][ii]))
else:
print("Usage: ")
print("""
Phase 1: sxconsistency.py --phase=1 bdb:data outdir
output files are:
in directory outdir: lili0.txt to lili5.txt contain indices of images in resampled six groups
bdb:dataX0 to bdb:dataX5 are metafiles containing six resampled groups of images derived from bdb:data
Phase 2 sxconsistency.py --phase=2 outdir --ndigits=1 --params=paramsb howmanythesame.txt
outdir - directory containing files lili0.txt to lili5.txt produced in phase 1
--params=master/main/params - Root of of six parameter file names with refinement results, the actual names should be
master/main/params0.txt to master/main/params5.txt
output files:
howmanythesame.txt - contains one number, a ratio of number of images that did not change orientations
to the total number of images
Phase 3: sxconsistency.py --phase=3 outdir --ou=133 --thresherr=3.0 --params=paramsa outgrouparms
input files:
outdir - directory containing files lili0.txt to lili5.txt produced in phase 1
--params=master/main/params - Root of of six parameter file names with refinement results, the actual names should be
master/main/params0.txt to master/main/params5.txt
output files:
outgrouparms*.txt - Root of of six parameters files with average 3D orientation parameters computed from six runs, can be imported into bdb:data
The next two files contain the original image numbers refering to the top bdb.
outdir/newgood.txt - Text file with indices of images whose orientation parameters arrors are below specified thresherr (to be kept)
outdir/bad.txt - Text file with indices of images whose orientation parameters arrors are above specified thresherr (to be rejected)
Phase 4: sxconsistency.py --phase=4 outdir --ou=133 --thresherr=3.0 --params=master/main001/newbad
input files:
outdir - directory containing files badparamsij.txt i= 0,3, j=0,2, which resulted from three alignments of four badchunk images
--params= - Root of four files with original indices of bad images, they will be read and a subset corresponding to rescued ones will be outputed
output files:
rescued*.txt - four files with indices of accepted images from badchunk.
rejects*.txt - four files with indices of rejected images from badchunk.
There are two columns: [number in original bdb:chunk, number in bdb:newbad]
""")
print("Please run '" + progname + " -h' for detailed options")
global_def.BATCH = False
def main():
arglist = []
for arg in sys.argv: arglist.append( arg )
progname = os.path.basename(arglist[0])
usage = progname + " stack outdir --phase=1 --ou=outer_radius|sxconsistency.py --phase=3 newlocal/main000 --ou=133 --thresherr=3.0 --params=paramsa outgrouparms"
parser = OptionParser(usage,version=SPARXVERSION)
parser.add_option("--phase", type= "int", default= 1, help="Phase =1 prepares resampled stacks, =2 analyzes consistency of orientation parameters")
parser.add_option("--ou", type= "int", default= -1, help="outer radius for calculation of pixel error")
parser.add_option("--sym", type="string", default= "c1", help="symmetry of the refined structure")
parser.add_option("--thresherr", type="float", default=1.0, help="Threshold for accpetable orientation errors (in pixels)")
parser.add_option("--ndigits", type="int", default=1, help="Accuracy for checking whether parameters are identical")
parser.add_option("--chunk", type="string", default="", help="Root of of four chunk files with indeces")
parser.add_option("--params", type="string", default="", help="Root of of six parameter file names with refinement results")
(options, args) = parser.parse_args(arglist[1:])
global_def.BATCH = True
if options.phase == 1 and len(args) == 2:
inputbdb = args[0]
outdir = args[1]
nn = EMUtil.get_image_count(inputbdb)
t = range(nn)
shuffle(t)
chunks = []
for i in xrange(4):
# I use the MPI function here just to easily get the balanced load
j,k = MPI_start_end(nn, 4, i)
chunks.append(t[j:k])
chunks[i].sort()
write_text_file(chunks[i],os.path.join(outdir,'chunk%01d.txt'%i))
del t
write_text_file([ len(chunks[i]) for i in xrange(4) ],os.path.join(outdir,'chunklengths.txt'))
"""
pt = [[None]]*6
ll=0
for i in xrange(3):
for j in xrange(i+1,4):
pt[ll] = chunks[i]+chunks[j]
ll+=1
for i in xrange(6):
listfile = os.path.join(outdir,'lili%01d.txt'%i)
write_text_file(pt[i],listfile)
outbdb = "bdb:"+ os.path.join(outdir,"X%01d"%i)
cmd = '{} {} {} {}'.format('e2bdb.py', inputbdb, '--makevstack='+outbdb, '--list='+listfile)
subprocess.call(cmd, shell=True)
"""
# Run 6 programs
elif options.phase == 2 and len(args) == 2:
outdir = args[0]
howmanythesame = args[1]
ndigits = options.ndigits #for chc5 1, for ribo 4#4.0
prms = []
for i in xrange(6):
prms.append( read_text_row(os.path.join(outdir,options.params+"%01d.txt"%i)) )
for j in xrange(len(prms[-1])):
for k in xrange(5):
prms[-1][j][k] = round(prms[-1][j][k], ndigits)
nn = 2*len(prms[0])
n4 = nn//4
qt=[[[-1.0]]*nn for i in xrange(6)]
ll=0
for i in xrange(3):
for j in xrange(i+1,4):
qt[ll][i*n4:(i+1)*n4]=prms[ll][:n4]
qt[ll][j*n4:(j+1)*n4]=prms[ll][n4:]
ll+=1
thesame = 0
for ll in xrange(len(qt[0])):
rw = []
for j in xrange(6):
if(len(qt[j][ll]) > 1): rw.append(qt[j][ll])
isame = True
for j in xrange(3):
if(rw[0][j] != rw[1][j]):
isame = False
#print ll,rw[0][j], rw[1][j]
break
if(rw[0][j] != rw[2][j]):
isame = False
#print ll,rw[0][j], rw[2][j]
break
if isame: thesame += 1
qt = float(thesame)/nn
print "Proportion of the same orientations ",qt
write_text_file([qt], os.path.join(outdir,howmanythesame) )
######### PHASE 3
elif options.phase == 3 and len(args) == 2:
outdir = args[0]
outgrouparms= args[1]
radius = options.ou
thresherr = options.thresherr #for chc5 1, for ribo 4#4.0
sym = int(options.sym[1:])
qsym = 360.0/sym
blocks = ['A','B','C','D']
params = {}
ll = 0
for i in xrange(3):
for j in xrange(i+1,4):
params[chr(65+i)+chr(48+ll)]=[]
params[chr(65+j)+chr(48+ll)]=[]
ll+=1
chunks = {}
chunklengths = {}
for i in xrange(4):
chunks[chr(65+i)] = map(int,read_text_file(os.path.join(outdir,options.chunk+"%01d.txt"%i)))
chunklengths[chr(65+i)] = len(chunks[chr(65+i)])
for i in xrange(6):
prms = read_text_row(os.path.join(outdir,options.params+"%01d.txt"%i))
for q in blocks:
if params.has_key(q+chr(48+i)):
params[q+chr(48+i)] = prms[:chunklengths[q]]
del prms[:chunklengths[q]]
pairs = [["A0","A1"],["B3","B4"],["C1","C5"],["D2","D4"]]
lefts = ["A2","B0","C3","D5"]
# Compute average projection params and pixel errors
avgtrans = {}
pixer = {}
for i,q in enumerate(pairs):
avgtrans[q[0][0]] = [0.0]*chunklengths[q[0][0]]
pixer[q[0][0]] = [0.0]*chunklengths[q[0][0]]
for j in xrange(chunklengths[q[0][0]]):
fifi = [ params[q[0]][j], params[q[1]][j] ]
nas = [0.0,0.0,0.0]
if( sym == 1):
pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(2):
n1,n2,n3 = getfvec(fifi[i][0],fifi[i][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1,m2,m3 = getfvec(fifi[0][0],fifi[0][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
#if(k == 2):
# print "XXXX"
# print fifi[0],nas
for i in xrange(1,2):
qnom = -1.e10
for j in xrange(-1,2,1):
t1,t2,t3 = getfvec(fifi[i][0]+j*qsym,fifi[i][1])
nom = t1*m1 + t2*m2 + t3*m3
if(nom > qnom):
qnom = nom
n1=t1
n2=t2
n3=t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print qnom, n1,n2,n3,nas
# To get the correct pixer phi angle has to be taken from the above!!
pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if(nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2]/nom))%360.0
if(sym>1 and ntheta>90.0): nphi = (degrees(atan2( nas[1], nas[0] ))-180.0)%qsym + 180.0
else: nphi = degrees(atan2( nas[1], nas[0] ))%qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform([fifi[0][2:],fifi[1][2:]])
avgtrans[q[0][0]][j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
perr = {}
tgood = 0
for q in blocks:
perr[q] = [True]*chunklengths[q]
for k in xrange(chunklengths[q]):
if(pixer[q][k] > thresherr): perr[q][k] = False
if perr[q][k]: tgood += 1
if(tgood < 4):
print " No good images within the pixel error threshold specified"
exit()
print " tgood ", tgood
hi = hist_list([pixer[q][k] for q in blocks for k in xrange(chunklengths[q]) ],16)
for i in xrange(len(hi[0])):
print "%4d %12.3f %12.0f "%(i,hi[0][i],hi[1][i])
# Finished, store average orientation params and table of good images
# store lists of good images for each group
# blocks is indexed by first letter
good = [[] for i in xrange(4)]
bad = [[] for i in xrange(4)]
for i,q in enumerate(blocks):
for k in xrange(chunklengths[q]):
#deprt = max_3D_pixel_error(params[lefts[i]][k],avgtrans[q][k],r=radius)
if perr[q][k]:
good[i].append(chunks[q][k])
#[chunks[q][k],pixer[q][k],deprt, params[pairs[i][0]][k],params[pairs[i][1]][k],params[lefts[i]][k],avgtrans[q][k] ])
else:
bad[i].append(chunks[q][k])
#[chunks[q][k],pixer[q][k],deprt, params[pairs[i][0]][k],params[pairs[i][1]][k],params[lefts[i]][k],avgtrans[q][k]])
write_text_file( good[i], os.path.join(outdir,"newgood%01d.txt"%i) )
write_text_file( bad[i], os.path.join(outdir,"newbad%01d.txt"%i) )
# write out parameters, for those in pairs write out average, for leftouts leave them as they were
# These parameters refer to the original X files.
ll = 0
for m in xrange(6):
if params.has_key(q+chr(48+m)):
prmsgood = []
prmsbad = []
try:
j = lefts.index(q+chr(48+m))
for k in xrange(chunklengths[q]):
if perr[q][k]:
prmsgood.append(params[q+chr(48+m)][k])
else:
prmsbad.append(params[q+chr(48+m)][k])
except:
for k in xrange(chunklengths[q]):
if perr[q][k]:
prmsgood.append(avgtrans[q][k])
else:
prmsbad.append(avgtrans[q][k])
write_text_row(prmsgood, os.path.join(outdir,"params-newgood%01d%01d.txt"%(i,ll)))
write_text_row(prmsbad, os.path.join(outdir, "params-newbad%01d%01d.txt"%(i,ll)))
ll += 1
# Generate newlili files from newgood, these contain original numbering of the total single file
ll = 0
for i in xrange(3):
for j in xrange(i+1,4):
write_text_file( good[i] + good[j], os.path.join(outdir,"newlili%01d.txt"%ll) )
ll += 1
# write out parameters, for those in pairs write out average, for leftouts leave them as they were
# These parameters refer to the original X files.
for i in xrange(6):
prms = []
for q in blocks:
if params.has_key(q+chr(48+i)):
try:
j = lefts.index(q+chr(48+i))
prms += params[q+chr(48+i)]
except:
prms += avgtrans[q]
write_text_row(prms, os.path.join(outdir,outgrouparms+"%01d.txt"%i))
# Write chunklengths
chunklengths = [len(good[i]) for i in xrange(4)]
write_text_file(chunklengths, os.path.join(outdir,"chunklengths.txt") )
"""
# We do not use consecutive numbering anymore
# Generate newx files from newgood, these contain consecutive (with gaps) numbering that allows to generate truncated X files from the previous X files
ll = 0
for i in xrange(3):
firstblock = []
l = len(perr[blocks[i]])
for k in xrange(l):
if perr[blocks[i]][k]:
firstblock.append(k)
for j in xrange(i+1,4):
secondblock = []
for k in xrange(len(perr[blocks[j]])):
if perr[blocks[j]][k]:
secondblock.append(k+l)
write_text_file( firstblock + secondblock, os.path.join(outdir,"goodX%01d.txt"%ll) )
ll += 1
del good,bad,firstblock,secondblock,perr
"""
"""
0 1 2 3 4 5
A A A = = =
B = = B B =
= C = C = C
= = D = D D
"""
elif options.phase == 4 and len(args) == 1:
outdir = args[0]
bp = 'badparams'
#outgrouparms= args[1]
radius = options.ou
thresherr = options.thresherr
sym = int(options.sym[1:])
qsym = 360.0/sym
#params = [[None for i in xrange(3)] for j in xrange(4)]
ll = 3 # this is hardwired as we have three groups. however, I would like to keep the code general.
for jj in xrange(4):
params = [None for ii in xrange(ll)]
newbad = map(int, read_text_file(options.params+"%01d.txt"%jj) )
nn = len(newbad)
for ii in xrange(ll):
params[ii] = read_text_row(os.path.join(outdir,bp+"%01d%01d.txt"%(jj,ii)))
assert(nn == len(params[ii]) )
# Compute average projection params and pixel errors
avgtrans = [None]*nn
pixer = [0.0]*nn
for j in xrange(nn):
nas = [0.0,0.0,0.0]
if( sym == 1):
#pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(ll):
n1,n2,n3 = getfvec(params[i][j][0],params[i][j][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1,m2,m3 = getfvec(params[0][j][0],params[0][j][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
for i in xrange(1,ll):
qnom = -1.e10
for j in xrange(-1,2,1):
t1,t2,t3 = getfvec(params[i][j][0]+j*qsym,params[i][j][1])
nom = t1*m1 + t2*m2 + t3*m3
if(nom > qnom):
qnom = nom
n1=t1
n2=t2
n3=t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print qnom, n1,n2,n3,nas
# To get the correct pixer phi angle has to be taken from the above!!
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if(nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2]/nom))%360.0
if(sym>1 and ntheta>90.0): nphi = (degrees(atan2( nas[1], nas[0] ))-180.0)%qsym + 180.0
else: nphi = degrees(atan2( nas[1], nas[0] ))%qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform([params[ii][j][2:] for ii in xrange(ll)])
avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
perr = errors_per_image(params, avgtrans, thresherr, radius )
rescued = []
rejects = []
for j in xrange(nn):
#print chr(65+jj),j,perr[j][0],[[params[m][j][i] for i in xrange(2)] for m in xrange(ll)]
if( perr[j][0] <= thresherr ): rescued.append([newbad[j],j])
else: rejects.append([newbad[j],j])
if( len(rescued) == 0 ): write_text_row([-1,-1], os.path.join(outdir,"rescued%01d.txt"%jj))
else: write_text_row(rescued, os.path.join(outdir,"rescued%01d.txt"%jj))
# We also have to write params.
if( len(rescued) != 0 ):
for ii in xrange(ll): write_text_row([params[ii][rescued[k][1]] for k in xrange(len(rescued))] , os.path.join(outdir,"params-rescued%01d%01d.txt"%(jj,ii)))
if( len(rejects) == 0 ): write_text_row([-1,-1], os.path.join(outdir,'rejects'+"%01d.txt"%jj))
else: write_text_row(rejects, os.path.join(outdir,'rejects'+"%01d.txt"%jj))
if( len(rejects) != 0 ):
for ii in xrange(ll): write_text_row([params[ii][rejects[k][1]] for k in xrange(len(rejects))] , os.path.join(outdir,"params-rejects%01d%01d.txt"%(jj,ii)))
hi = hist_list([perr[j][0] for j in xrange(nn) ], 16)
print "Pixel errors for BAD GROUP ",chr(65+jj)
for ii in xrange(len(hi[0])):
print "%4d %12.3f %12.0f "%(ii,hi[0][ii],hi[1][ii])
elif options.phase == 5 and len(args) == 1:
# This version is for meridien refinement. There are simply three full sets of params.
outdir = args[0]
bp = 'badparams'
#outgrouparms= args[1]
radius = options.ou
thresherr = options.thresherr
sym = int(options.sym[1:])
qsym = 360.0/sym
#params = [[None for i in xrange(3)] for j in xrange(4)]
ll = 3 # this is hardwired as we have three groups. however, I would like to keep the code general.
for jj in xrange(1):
params = [None for ii in xrange(ll)]
#newbad = map(int, read_text_file(options.params+"%01d.txt"%jj) )
#nn = len(newbad)
for ii in xrange(ll):
params[ii] = read_text_row(os.path.join(outdir,"params%01d.txt"%(ii)))
#assert(nn == len(params[ii]) )
nn = len(params[0])
newbad = range(nn)
# Compute average projection params and pixel errors
avgtrans = [None]*nn
pixer = [0.0]*nn
for j in xrange(nn):
nas = [0.0,0.0,0.0]
if( sym == 1):
#pixer[q[0][0]][j] = max_3D_pixel_error(fifi[0], fifi[1], r=radius)
for i in xrange(ll):
n1,n2,n3 = getfvec(params[i][j][0],params[i][j][1])
nas[0] += n1
nas[1] += n2
nas[2] += n3
else:
m1,m2,m3 = getfvec(params[0][j][0],params[0][j][1])
nas[0] = m1
nas[1] = m2
nas[2] = m3
for i in xrange(1,ll):
qnom = -1.e10
for j in xrange(-1,2,1):
t1,t2,t3 = getfvec(params[i][j][0]+j*qsym,params[i][j][1])
nom = t1*m1 + t2*m2 + t3*m3
if(nom > qnom):
qnom = nom
n1=t1
n2=t2
n3=t3
#if(k == 2):
# print ' t1,t2,t3 ',fifi[i][0]+j*qsym,fifi[i][1],t1,t2,t3,nom,qnom
nas[0] += n1
nas[1] += n2
nas[2] += n3
print qnom, n1,n2,n3,nas
# To get the correct pixer phi angle has to be taken from the above!!
nom = sqrt(nas[0]**2 + nas[1]**2 + nas[2]**2)
if(nom < 1.e-6):
nphi = 0.0
ntheta = 0.0
else:
ntheta = degrees(acos(nas[2]/nom))%360.0
if(sym>1 and ntheta>90.0): nphi = (degrees(atan2( nas[1], nas[0] ))-180.0)%qsym + 180.0
else: nphi = degrees(atan2( nas[1], nas[0] ))%qsym
#print "FIFI %4d %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f"%(k,fifi[0][0],fifi[0][1],fifi[1][0],fifi[1][1],fifi[2][0],fifi[2][1],nphi,ntheta)
twod = average2dtransform([params[ii][j][2:] for ii in xrange(ll)])
avgtrans[j] = [nphi, ntheta, twod[0], twod[1], twod[2]]
write_text_row(avgtrans, os.path.join(outdir,"avgtrans.txt"))
perr = errors_per_image(params, avgtrans, thresherr, radius )
rescued = []
rejects = []
for j in xrange(nn):
#print chr(65+jj),j,perr[j][0],[[params[m][j][i] for i in xrange(2)] for m in xrange(ll)]
if( perr[j][0] <= thresherr ): rescued.append([newbad[j],j])
else: rejects.append([newbad[j],j])
if( len(rescued) == 0 ): write_text_row([-1,-1], os.path.join(outdir,"rescued%01d.txt"%jj))
else: write_text_row(rescued, os.path.join(outdir,"rescued%01d.txt"%jj))
# We also have to write params.
if( len(rescued) != 0 ):
for ii in xrange(ll): write_text_row([params[ii][rescued[k][1]] for k in xrange(len(rescued))] , os.path.join(outdir,"params-rescued%01d%01d.txt"%(jj,ii)))
if( len(rejects) == 0 ): write_text_row([-1,-1], os.path.join(outdir,'rejects'+"%01d.txt"%jj))
else: write_text_row(rejects, os.path.join(outdir,'rejects'+"%01d.txt"%jj))
if( len(rejects) != 0 ):
for ii in xrange(ll): write_text_row([params[ii][rejects[k][1]] for k in xrange(len(rejects))] , os.path.join(outdir,"params-rejects%01d%01d.txt"%(jj,ii)))
hi = hist_list([perr[j][0] for j in xrange(nn) ], 16)
print "Pixel errors for BAD GROUP ",chr(65+jj)
for ii in xrange(len(hi[0])):
print "%4d %12.3f %12.0f "%(ii,hi[0][ii],hi[1][ii])
else:
print "Usage: "
print """
Phase 1: sxconsistency.py --phase=1 bdb:data outdir
output files are:
in directory outdir: lili0.txt to lili5.txt contain indices of images in resampled six groups
bdb:dataX0 to bdb:dataX5 are metafiles containing six resampled groups of images derived from bdb:data
Phase 2 sxconsistency.py --phase=2 outdir --ndigits=1 --params=paramsb howmanythesame.txt
outdir - directory containing files lili0.txt to lili5.txt produced in phase 1
--params=master/main/params - Root of of six parameter file names with refinement results, the actual names should be
master/main/params0.txt to master/main/params5.txt
output files:
howmanythesame.txt - contains one number, a ratio of number of images that did not change orientations
to the total number of images
Phase 3: sxconsistency.py --phase=3 outdir --ou=133 --thresherr=3.0 --params=paramsa outgrouparms
input files:
outdir - directory containing files lili0.txt to lili5.txt produced in phase 1
--params=master/main/params - Root of of six parameter file names with refinement results, the actual names should be
master/main/params0.txt to master/main/params5.txt
output files:
outgrouparms*.txt - Root of of six parameters files with average 3D orientation parameters computed from six runs, can be imported into bdb:data
The next two files contain the original image numbers refering to the top bdb.
outdir/newgood.txt - Text file with indices of images whose orientation parameters arrors are below specified thresherr (to be kept)
outdir/bad.txt - Text file with indices of images whose orientation parameters arrors are above specified thresherr (to be rejected)
Phase 4: sxconsistency.py --phase=4 outdir --ou=133 --thresherr=3.0 --params=master/main001/newbad
input files:
outdir - directory containing files badparamsij.txt i= 0,3, j=0,2, which resulted from three alignments of four badchunk images
--params= - Root of four files with original indices of bad images, they will be read and a subset corresponding to rescued ones will be outputed
output files:
rescued*.txt - four files with indices of accepted images from badchunk.
rejects*.txt - four files with indices of rejected images from badchunk.
There are two columns: [number in original bdb:chunk, number in bdb:newbad]
"""
print "Please run '" + progname + " -h' for detailed options"
global_def.BATCH = False
