def vomq(classavgstack, classmap, classdoc, log=None, verbose=False):
"""
Separate particles according to class assignment.
Arguments:
classavgstack : Input image stack
classmap : Output class-to-particle lookup table. Each (long) line contains particles assigned to a class, one file for all classes
classdoc : Output lists of particles assigned to a class, one file per class
mode : Mode, viper (pre-existing angles for each input image), projmatch (angles from internal projection-matching)
log : instance of Logger class
verbose : (boolean) Whether to write additional information to screen
"""
# Generate class-to-particle lookup table
print_log_msg(
"Exporting members of stack %s to class map %s" %
(classavgstack, classmap), log, verbose)
cmd = "sp_header.py %s --params=members --export=%s" % (classavgstack,
classmap)
print_log_msg(cmd, log, verbose)
header(classavgstack, 'members', fexport=classmap)
counter = 0
# Loop through classes
with open(classmap) as r:
for idx, line in enumerate(r.readlines()):
with open(classdoc.format(idx), 'w') as w:
w.write('\n'.join(line[1:-3].split(', ')))
counter += 1
print_log_msg("Wrote %s class selection files\n" % counter, log, verbose)
def main():
arglist = []
for arg in sys.argv:
arglist.append( arg )
progname = os.path.basename( arglist[0] )
usage = progname + " stack --params='parm1 parm2 parm3 ...' --zero --one --set=number --randomize --rand_alpha --import=file --export=file --print --backup --suffix --restore --delete"
parser = OptionParser(usage, version=SPARXVERSION)
parser.add_option("--params", type="string", default=None, help="parameter list")
parser.add_option("--zero", action="store_true", default=False, help="set parameter to zero")
parser.add_option("--one", action="store_true", default=False, help="set parameter to one")
parser.add_option("--set", type="float", default=0.0, help="set parameter to a value (different from 0.0)")
parser.add_option("--randomize", action="store_true", default=False, help="set parameter to randomized value")
parser.add_option("--rand_alpha", action="store_true", default=False, help="set all angles to randomized value")
parser.add_option("--import", type="string", dest="fimport", default=None, help="import parameters from file")
parser.add_option("--export", type="string", dest="fexport", default=None, help="export parameters to file")
parser.add_option("--print", action="store_true", dest="fprint", default=False, help="print parameters")
parser.add_option("--backup", action="store_true", default=False, help="backup parameters")
parser.add_option("--suffix", type="string", default="_backup", help="suffix for xform name in backup")
parser.add_option("--restore", action="store_true", default=False, help="restore parameters")
parser.add_option("--delete", action="store_true", default=False, help="delete parameters")
parser.add_option("--consecutive", action="store_true", default=False, help="set selected parameter to consecutive integers starting from 0")
parser.add_option("--list", type="string", default=None, help="Indices list containing the same amount of rows as the import file")
(options,args) = parser.parse_args( arglist[1:] )
if not options.fprint:
sp_global_def.print_timestamp( "Start" )
sp_global_def.write_command()
if len(args) != 1 :
sxprint( "Usage: " + usage )
ERROR( "Invalid number of parameters provided. Please see usage information above." )
return
if options.params == None:
sxprint( "Usage: " + usage )
ERROR( "No parameters provided. Please see usage information above." )
return
if sp_global_def.CACHE_DISABLE:
from sp_utilities import disable_bdb_cache
disable_bdb_cache()
from sp_applications import header
header(args[0], options.params, options.zero, options.one, options.set, options.randomize, options.rand_alpha, options.fimport, options.fexport, \
options.fprint, options.backup, options.suffix, options.restore, options.delete, options.consecutive, options.list)
if not options.fprint:
sp_global_def.print_timestamp( "Finish" )
def main_proj_compare(classavgstack,
reconfile,
outdir,
options,
mode='viper',
prjmethod='trilinear',
classangles=None,
partangles=None,
selectdoc=None,
verbose=False,
displayYN=False):
"""
Main function overseeing various projection-comparison modes.
Arguments:
classavgstack : Input image stack
reconfile : Map of which to generate projections (an optionally perform alignment)
outdir : Output directory
mode : Mode, viper (pre-existing angles for each input image), projmatch (angles from internal projection-matching)
verbose : (boolean) Whether to write additional information to screen
options : (list) Command-line options, run 'sxproj_compare.py -h' for an exhaustive list
classangles : Angles and shifts for each input class average
partangles : Angles and shifts for each particle (mode meridien)
selectdoc : Selection file for included images
prjmethod : Interpolation method to use
displayYN : (boolean) Whether to automatically open montage
"""
# Expand path for outputs
refprojstack = os.path.join(outdir, 'refproj.hdf')
refanglesdoc = os.path.join(outdir, 'refangles.txt')
outaligndoc = os.path.join(outdir, 'docalign2d.txt')
# If not an input, will create an output, in modes projmatch
if classangles == None:
classangles = os.path.join(outdir, 'docangles.txt')
# You need either input angles (mode viper) or to calculate them on the fly (mode projmatch)
if mode == 'viper':
sp_global_def.ERROR(
"\nERROR!! Input alignment parameters not specified.",
__file__, 1)
sxprint('Type %s --help to see available options\n' %
os.path.basename(__file__))
exit()
# Check if inputs exist
check(classavgstack, verbose=verbose)
check(reconfile, verbose=verbose)
if verbose: sxprint('')
# Check that dimensions of images and volume agree (maybe rescale volume)
voldim = EMAN2.EMData(reconfile).get_xsize()
imgdim = EMAN2.EMData(classavgstack, 0).get_xsize()
if voldim != imgdim:
sp_global_def.ERROR(
"\nERROR!! Dimension of input volume doesn't match that of image stack: %s vs. %s"
% (voldim, imgdim), __file__, 1)
scale = float(
imgdim
) / voldim # only approximate, since full-sized particle radius is arbitrary
msg = 'The command to resize the volume will be of the form:\n'
msg += 'e2proc3d.py %s resized_vol.hdf --scale=%1.5f --clip=%s,%s,%s\n' % (
reconfile, scale, imgdim, imgdim, imgdim)
msg += 'Check the file in the ISAC directory named "README_shrink_ratio.txt" for confirmation.\n'
sxprint(msg)
exit()
# Here if you want to be fancy, there should be an option to chose the projection method,
# the mechanism can be copied from sxproject3d.py PAP
if prjmethod == 'trilinear':
method_num = 1
elif prjmethod == 'gridding':
method_num = -1
elif prjmethod == 'nn':
method_num = 0
else:
sp_global_def.ERROR(
"\nERROR!! Valid projection methods are: trilinear (default), gridding, and nn (nearest neighbor).",
__file__, 1)
sxprint('Usage:\n%s' % USAGE)
exit()
# Set output directory and log file name
log, verbose = prepare_outdir_log(outdir, verbose)
# In case class averages include discarded images, apply selection file
if mode == 'viper':
if selectdoc:
goodavgs, extension = os.path.splitext(
os.path.basename(classavgstack))
newclasses = os.path.join(outdir, goodavgs + "_kept" + extension)
# e2proc2d appends to existing files, so rename existing output
if os.path.exists(newclasses):
renamefile = newclasses + '.bak'
print_log_msg(
"Selected-classes stack %s exists, renaming to %s" %
(newclasses, renamefile), log, verbose)
print_log_msg("mv %s %s\n" % (newclasses, renamefile), log,
verbose)
os.rename(newclasses, renamefile)
print_log_msg(
'Creating subset of %s to %s based on selection list %s' %
(classavgstack, newclasses, selectdoc), log, verbose)
cmd = "e2proc2d.py %s %s --list=%s" % (classavgstack, newclasses,
selectdoc)
print_log_msg(cmd, log, verbose)
os.system(cmd)
sxprint('')
# Update class-averages
classavgstack = newclasses
# align de novo to reference map
if mode == 'projmatch':
# Generate reference projections
print_log_msg(
'Projecting %s to output %s using an increment of %s degrees using %s symmetry'
% (reconfile, refprojstack, options.delta, options.symmetry), log,
verbose)
cmd = 'sxproject3d.py %s %s --delta=%s --method=S --phiEqpsi=Minus --symmetry=%s' % (
reconfile, refprojstack, options.delta, options.symmetry)
if options.prjmethod == 'trilinear': cmd += ' --trilinear'
cmd += '\n'
print_log_msg(cmd, log, verbose)
project3d(reconfile,
refprojstack,
delta=options.delta,
symmetry=options.symmetry)
# Export projection angles
print_log_msg(
"Exporting projection angles from %s to %s" %
(refprojstack, refanglesdoc), log, verbose)
cmd = "sp_header.py %s --params=xform.projection --import=%s\n" % (
refprojstack, refanglesdoc)
print_log_msg(cmd, log, verbose)
header(refprojstack, 'xform.projection', fexport=refanglesdoc)
# Perform multi-reference alignment
if options.align == 'ali2d':
projdir = os.path.join(
outdir, 'Projdir') # used if input angles no provided
if os.path.isdir(projdir):
print_log_msg('Removing pre-existing directory %s' % projdir,
log, verbose)
print_log_msg('rm -r %s\n' % projdir, log, verbose)
shutil.rmtree(
projdir) # os.rmdir only removes empty directories
# Zero out alignment parameters in header
print_log_msg(
'Zeroing out alignment parameters in header of %s' %
classavgstack, log, verbose)
cmd = 'sxheader.py %s --params xform.align2d --zero\n' % classavgstack
print_log_msg(cmd, log, verbose)
header(classavgstack, 'xform.align2d', zero=True)
# Perform multi-reference alignment
msg = 'Aligning images in %s to projections %s with a radius of %s and a maximum allowed shift of %s' % (
classavgstack, refprojstack, options.matchrad,
options.matchshift)
print_log_msg(msg, log, verbose)
cmd = 'sxmref_ali2d.py %s %s %s --ou=%s --xr=%s --yr=%s\n' % (
classavgstack, refprojstack, projdir, options.matchrad,
options.matchshift, options.matchshift)
print_log_msg(cmd, log, verbose)
mref_ali2d(classavgstack,
refprojstack,
projdir,
ou=options.matchrad,
xrng=options.matchshift,
yrng=options.matchshift)
# Export alignment parameters
print_log_msg(
'Exporting angles from %s into %s' %
(classavgstack, classangles), log, verbose)
cmd = "sp_header.py %s --params=xform.align2d --export=%s\n" % (
classavgstack, classangles)
print_log_msg(cmd, log, verbose)
header(classavgstack, 'xform.align2d', fexport=classangles)
# By default, use AP SH
else:
apsh(refprojstack,
classavgstack,
outangles=classangles,
refanglesdoc=refanglesdoc,
outaligndoc=outaligndoc,
outerradius=options.matchrad,
maxshift=options.matchshift,
ringstep=options.matchstep,
log=log,
verbose=verbose)
# Diagnostic
alignlist = read_text_row(
classangles) # contain 2D alignment parameters
nimg1 = EMAN2.EMUtil.get_image_count(classavgstack)
assert len(alignlist) == nimg1, "MRK_DEBUG"
# Get alignment parameters from MERIDIEN
if mode == 'meridien':
continueTF = True # Will proceed unless some information is missing
if not partangles:
sp_global_def.ERROR(
"\nERROR!! Input alignment parameters not provided.", __file__,
1)
continueTF = False
if not continueTF:
sxprint('Type %s --help to see available options\n' %
os.path.basename(__file__))
exit()
if not options.classdocs or options.outliers:
classdir = os.path.join(outdir, 'Byclass')
if not os.path.isdir(classdir): os.makedirs(classdir)
if options.outliers:
goodclassparttemplate = os.path.join(
classdir, 'goodpartsclass{0:03d}.txt')
else:
goodclassparttemplate = None
if not options.classdocs:
classmap = os.path.join(classdir, 'classmap.txt')
classdoc = os.path.join(classdir, 'docclass{0:03d}.txt')
options.classdocs = os.path.join(classdir, 'docclass*.txt')
# Separate particles by class
vomq(classavgstack,
classmap,
classdoc,
log=log,
verbose=verbose)
mode_meridien(reconfile,
classavgstack,
options.classdocs,
partangles,
selectdoc,
options.refineshift,
options.refinerad,
classangles,
outaligndoc,
interpolation_method=method_num,
outliers=options.outliers,
goodclassparttemplate=goodclassparttemplate,
alignopt=options.align,
ringstep=options.refinestep,
log=log,
verbose=verbose)
# Import Euler angles
print_log_msg(
"Importing parameter information into %s from %s" %
(classavgstack, classangles), log, verbose)
cmd = "sp_header.py %s --params=xform.projection --import=%s\n" % (
classavgstack, classangles)
print_log_msg(cmd, log, verbose)
header(classavgstack, 'xform.projection', fimport=classangles)
# Make comparison stack between class averages (images 0,2,4,...) and re-projections (images 1,3,5,...)
compstack = compare_projs(reconfile,
classavgstack,
classangles,
outdir,
interpolation_method=method_num,
log=log,
verbose=verbose)
# Optionally pop up e2display
if displayYN:
sxprint('Opening montage')
cmd = "e2display.py %s\n" % compstack
sxprint(cmd)
os.system(cmd)
sxprint("Done!")
def main():
def params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror):
# the final ali2d parameters already combine shifts operation first and rotation operation second for parameters converted from 3D
if mirror:
m = 1
alpha, sx, sy, scalen = compose_transform2(0, s2x, s2y, 1.0,
540.0 - psi, 0, 0, 1.0)
else:
m = 0
alpha, sx, sy, scalen = compose_transform2(0, s2x, s2y, 1.0,
360.0 - psi, 0, 0, 1.0)
return alpha, sx, sy, m
progname = os.path.basename(sys.argv[0])
usage = progname + " prj_stack --ave2D= --var2D= --ave3D= --var3D= --img_per_grp= --fl= --aa= --sym=symmetry --CTF"
parser = OptionParser(usage, version=SPARXVERSION)
parser.add_option("--output_dir",
type="string",
default="./",
help="Output directory")
parser.add_option("--ave2D",
type="string",
default=False,
help="Write to the disk a stack of 2D averages")
parser.add_option("--var2D",
type="string",
default=False,
help="Write to the disk a stack of 2D variances")
parser.add_option("--ave3D",
type="string",
default=False,
help="Write to the disk reconstructed 3D average")
parser.add_option("--var3D",
type="string",
default=False,
help="Compute 3D variability (time consuming!)")
parser.add_option(
"--img_per_grp",
type="int",
default=100,
help="Number of neighbouring projections.(Default is 100)")
parser.add_option(
"--no_norm",
action="store_true",
default=False,
help="Do not use normalization.(Default is to apply normalization)")
#parser.add_option("--radius", type="int" , default=-1 , help="radius for 3D variability" )
parser.add_option(
"--npad",
type="int",
default=2,
help=
"Number of time to pad the original images.(Default is 2 times padding)"
)
parser.add_option("--sym",
type="string",
default="c1",
help="Symmetry. (Default is no symmetry)")
parser.add_option(
"--fl",
type="float",
default=0.0,
help=
"Low pass filter cutoff in absolute frequency (0.0 - 0.5) and is applied to decimated images. (Default - no filtration)"
)
parser.add_option(
"--aa",
type="float",
default=0.02,
help=
"Fall off of the filter. Use default value if user has no clue about falloff (Default value is 0.02)"
)
parser.add_option("--CTF",
action="store_true",
default=False,
help="Use CFT correction.(Default is no CTF correction)")
#parser.add_option("--MPI" , action="store_true", default=False, help="use MPI version")
#parser.add_option("--radiuspca", type="int" , default=-1 , help="radius for PCA" )
#parser.add_option("--iter", type="int" , default=40 , help="maximum number of iterations (stop criterion of reconstruction process)" )
#parser.add_option("--abs", type="float" , default=0.0 , help="minimum average absolute change of voxels' values (stop criterion of reconstruction process)" )
#parser.add_option("--squ", type="float" , default=0.0 , help="minimum average squared change of voxels' values (stop criterion of reconstruction process)" )
parser.add_option(
"--VAR",
action="store_true",
default=False,
help="Stack of input consists of 2D variances (Default False)")
parser.add_option(
"--decimate",
type="float",
default=0.25,
help="Image decimate rate, a number less than 1. (Default is 0.25)")
parser.add_option(
"--window",
type="int",
default=0,
help=
"Target image size relative to original image size. (Default value is zero.)"
)
#parser.add_option("--SND", action="store_true", default=False, help="compute squared normalized differences (Default False)")
#parser.add_option("--nvec", type="int" , default=0 , help="Number of eigenvectors, (Default = 0 meaning no PCA calculated)")
parser.add_option(
"--symmetrize",
action="store_true",
default=False,
help="Prepare input stack for handling symmetry (Default False)")
parser.add_option("--overhead",
type="float",
default=0.5,
help="python overhead per CPU.")
(options, args) = parser.parse_args()
#####
from mpi import mpi_comm_rank, mpi_comm_size, mpi_recv, MPI_COMM_WORLD
from mpi import mpi_barrier, mpi_reduce, mpi_bcast, mpi_send, MPI_FLOAT, MPI_SUM, MPI_INT, MPI_MAX
#from mpi import *
from sp_applications import MPI_start_end
from sp_reconstruction import recons3d_em, recons3d_em_MPI
from sp_reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI
from sp_utilities import print_begin_msg, print_end_msg, print_msg
from sp_utilities import read_text_row, get_image, get_im, wrap_mpi_send, wrap_mpi_recv
from sp_utilities import bcast_EMData_to_all, bcast_number_to_all
from sp_utilities import get_symt
# This is code for handling symmetries by the above program. To be incorporated. PAP 01/27/2015
from EMAN2db import db_open_dict
# Set up global variables related to bdb cache
if sp_global_def.CACHE_DISABLE:
from sp_utilities import disable_bdb_cache
disable_bdb_cache()
# Set up global variables related to ERROR function
sp_global_def.BATCH = True
# detect if program is running under MPI
RUNNING_UNDER_MPI = "OMPI_COMM_WORLD_SIZE" in os.environ
if RUNNING_UNDER_MPI: sp_global_def.MPI = True
if options.output_dir == "./":
current_output_dir = os.path.abspath(options.output_dir)
else:
current_output_dir = options.output_dir
if options.symmetrize:
if mpi.mpi_comm_size(MPI_COMM_WORLD) > 1:
ERROR("Cannot use more than one CPU for symmetry preparation")
if not os.path.exists(current_output_dir):
os.makedirs(current_output_dir)
sp_global_def.write_command(current_output_dir)
from sp_logger import Logger, BaseLogger_Files
if os.path.exists(os.path.join(current_output_dir, "log.txt")):
os.remove(os.path.join(current_output_dir, "log.txt"))
log_main = Logger(BaseLogger_Files())
log_main.prefix = os.path.join(current_output_dir, "./")
instack = args[0]
sym = options.sym.lower()
if (sym == "c1"):
ERROR("There is no need to symmetrize stack for C1 symmetry")
line = ""
for a in sys.argv:
line += " " + a
log_main.add(line)
if (instack[:4] != "bdb:"):
#if output_dir =="./": stack = "bdb:data"
stack = "bdb:" + current_output_dir + "/data"
delete_bdb(stack)
junk = cmdexecute("sp_cpy.py " + instack + " " + stack)
else:
stack = instack
qt = EMUtil.get_all_attributes(stack, 'xform.projection')
na = len(qt)
ts = get_symt(sym)
ks = len(ts)
angsa = [None] * na
for k in range(ks):
#Qfile = "Q%1d"%k
#if options.output_dir!="./": Qfile = os.path.join(options.output_dir,"Q%1d"%k)
Qfile = os.path.join(current_output_dir, "Q%1d" % k)
#delete_bdb("bdb:Q%1d"%k)
delete_bdb("bdb:" + Qfile)
#junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
junk = cmdexecute("e2bdb.py " + stack + " --makevstack=bdb:" +
Qfile)
#DB = db_open_dict("bdb:Q%1d"%k)
DB = db_open_dict("bdb:" + Qfile)
for i in range(na):
ut = qt[i] * ts[k]
DB.set_attr(i, "xform.projection", ut)
#bt = ut.get_params("spider")
#angsa[i] = [round(bt["phi"],3)%360.0, round(bt["theta"],3)%360.0, bt["psi"], -bt["tx"], -bt["ty"]]
#write_text_row(angsa, 'ptsma%1d.txt'%k)
#junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
#junk = cmdexecute("sxheader.py bdb:Q%1d --params=xform.projection --import=ptsma%1d.txt"%(k,k))
DB.close()
#if options.output_dir =="./": delete_bdb("bdb:sdata")
delete_bdb("bdb:" + current_output_dir + "/" + "sdata")
#junk = cmdexecute("e2bdb.py . --makevstack=bdb:sdata --filt=Q")
sdata = "bdb:" + current_output_dir + "/" + "sdata"
sxprint(sdata)
junk = cmdexecute("e2bdb.py " + current_output_dir +
" --makevstack=" + sdata + " --filt=Q")
#junk = cmdexecute("ls EMAN2DB/sdata*")
#a = get_im("bdb:sdata")
a = get_im(sdata)
a.set_attr("variabilitysymmetry", sym)
#a.write_image("bdb:sdata")
a.write_image(sdata)
else:
from sp_fundamentals import window2d
myid = mpi_comm_rank(MPI_COMM_WORLD)
number_of_proc = mpi_comm_size(MPI_COMM_WORLD)
main_node = 0
shared_comm = mpi_comm_split_type(MPI_COMM_WORLD, MPI_COMM_TYPE_SHARED,
0, MPI_INFO_NULL)
myid_on_node = mpi_comm_rank(shared_comm)
no_of_processes_per_group = mpi_comm_size(shared_comm)
masters_from_groups_vs_everything_else_comm = mpi_comm_split(
MPI_COMM_WORLD, main_node == myid_on_node, myid_on_node)
color, no_of_groups, balanced_processor_load_on_nodes = get_colors_and_subsets(main_node, MPI_COMM_WORLD, myid, \
shared_comm, myid_on_node, masters_from_groups_vs_everything_else_comm)
overhead_loading = options.overhead * number_of_proc
#memory_per_node = options.memory_per_node
#if memory_per_node == -1.: memory_per_node = 2.*no_of_processes_per_group
keepgoing = 1
current_window = options.window
current_decimate = options.decimate
if len(args) == 1: stack = args[0]
else:
sxprint("Usage: " + usage)
sxprint("Please run \'" + progname + " -h\' for detailed options")
ERROR(
"Invalid number of parameters used. Please see usage information above."
)
return
t0 = time()
# obsolete flags
options.MPI = True
#options.nvec = 0
options.radiuspca = -1
options.iter = 40
options.abs = 0.0
options.squ = 0.0
if options.fl > 0.0 and options.aa == 0.0:
ERROR("Fall off has to be given for the low-pass filter",
myid=myid)
#if options.VAR and options.SND:
# ERROR( "Only one of var and SND can be set!",myid=myid )
if options.VAR and (options.ave2D or options.ave3D or options.var2D):
ERROR(
"When VAR is set, the program cannot output ave2D, ave3D or var2D",
myid=myid)
#if options.SND and (options.ave2D or options.ave3D):
# ERROR( "When SND is set, the program cannot output ave2D or ave3D", myid=myid )
#if options.nvec > 0 :
# ERROR( "PCA option not implemented", myid=myid )
#if options.nvec > 0 and options.ave3D == None:
# ERROR( "When doing PCA analysis, one must set ave3D", myid=myid )
if current_decimate > 1.0 or current_decimate < 0.0:
ERROR("Decimate rate should be a value between 0.0 and 1.0",
myid=myid)
if current_window < 0.0:
ERROR("Target window size should be always larger than zero",
myid=myid)
if myid == main_node:
img = get_image(stack, 0)
nx = img.get_xsize()
ny = img.get_ysize()
if (min(nx, ny) < current_window): keepgoing = 0
keepgoing = bcast_number_to_all(keepgoing, main_node, MPI_COMM_WORLD)
if keepgoing == 0:
ERROR(
"The target window size cannot be larger than the size of decimated image",
myid=myid)
import string
options.sym = options.sym.lower()
# if global_def.CACHE_DISABLE:
# from utilities import disable_bdb_cache
# disable_bdb_cache()
# global_def.BATCH = True
if myid == main_node:
if not os.path.exists(current_output_dir):
os.makedirs(current_output_dir
) # Never delete output_dir in the program!
img_per_grp = options.img_per_grp
#nvec = options.nvec
radiuspca = options.radiuspca
from sp_logger import Logger, BaseLogger_Files
#if os.path.exists(os.path.join(options.output_dir, "log.txt")): os.remove(os.path.join(options.output_dir, "log.txt"))
log_main = Logger(BaseLogger_Files())
log_main.prefix = os.path.join(current_output_dir, "./")
if myid == main_node:
line = ""
for a in sys.argv:
line += " " + a
log_main.add(line)
log_main.add("-------->>>Settings given by all options<<<-------")
log_main.add("Symmetry : %s" % options.sym)
log_main.add("Input stack : %s" % stack)
log_main.add("Output_dir : %s" % current_output_dir)
if options.ave3D:
log_main.add("Ave3d : %s" % options.ave3D)
if options.var3D:
log_main.add("Var3d : %s" % options.var3D)
if options.ave2D:
log_main.add("Ave2D : %s" % options.ave2D)
if options.var2D:
log_main.add("Var2D : %s" % options.var2D)
if options.VAR: log_main.add("VAR : True")
else: log_main.add("VAR : False")
if options.CTF: log_main.add("CTF correction : True ")
else: log_main.add("CTF correction : False ")
log_main.add("Image per group : %5d" % options.img_per_grp)
log_main.add("Image decimate rate : %4.3f" % current_decimate)
log_main.add("Low pass filter : %4.3f" % options.fl)
current_fl = options.fl
if current_fl == 0.0: current_fl = 0.5
log_main.add(
"Current low pass filter is equivalent to cutoff frequency %4.3f for original image size"
% round((current_fl * current_decimate), 3))
log_main.add("Window size : %5d " % current_window)
log_main.add("sx3dvariability begins")
symbaselen = 0
if myid == main_node:
nima = EMUtil.get_image_count(stack)
img = get_image(stack)
nx = img.get_xsize()
ny = img.get_ysize()
nnxo = nx
nnyo = ny
if options.sym != "c1":
imgdata = get_im(stack)
try:
i = imgdata.get_attr("variabilitysymmetry").lower()
if (i != options.sym):
ERROR(
"The symmetry provided does not agree with the symmetry of the input stack",
myid=myid)
except:
ERROR(
"Input stack is not prepared for symmetry, please follow instructions",
myid=myid)
from sp_utilities import get_symt
i = len(get_symt(options.sym))
if ((nima / i) * i != nima):
ERROR(
"The length of the input stack is incorrect for symmetry processing",
myid=myid)
symbaselen = nima / i
else:
symbaselen = nima
else:
nima = 0
nx = 0
ny = 0
nnxo = 0
nnyo = 0
nima = bcast_number_to_all(nima)
nx = bcast_number_to_all(nx)
ny = bcast_number_to_all(ny)
nnxo = bcast_number_to_all(nnxo)
nnyo = bcast_number_to_all(nnyo)
if current_window > max(nx, ny):
ERROR("Window size is larger than the original image size")
if current_decimate == 1.:
if current_window != 0:
nx = current_window
ny = current_window
else:
if current_window == 0:
nx = int(nx * current_decimate + 0.5)
ny = int(ny * current_decimate + 0.5)
else:
nx = int(current_window * current_decimate + 0.5)
ny = nx
symbaselen = bcast_number_to_all(symbaselen)
# check FFT prime number
from sp_fundamentals import smallprime
is_fft_friendly = (nx == smallprime(nx))
if not is_fft_friendly:
if myid == main_node:
log_main.add(
"The target image size is not a product of small prime numbers"
)
log_main.add("Program adjusts the input settings!")
### two cases
if current_decimate == 1.:
nx = smallprime(nx)
ny = nx
current_window = nx # update
if myid == main_node:
log_main.add("The window size is updated to %d." %
current_window)
else:
if current_window == 0:
nx = smallprime(int(nx * current_decimate + 0.5))
current_decimate = float(nx) / nnxo
ny = nx
if (myid == main_node):
log_main.add("The decimate rate is updated to %f." %
current_decimate)
else:
nx = smallprime(
int(current_window * current_decimate + 0.5))
ny = nx
current_window = int(nx / current_decimate + 0.5)
if (myid == main_node):
log_main.add("The window size is updated to %d." %
current_window)
if myid == main_node:
log_main.add("The target image size is %d" % nx)
if radiuspca == -1: radiuspca = nx / 2 - 2
if myid == main_node:
log_main.add("%-70s: %d\n" % ("Number of projection", nima))
img_begin, img_end = MPI_start_end(nima, number_of_proc, myid)
"""
if options.SND:
from sp_projection import prep_vol, prgs
from sp_statistics import im_diff
from sp_utilities import get_im, model_circle, get_params_proj, set_params_proj
from sp_utilities import get_ctf, generate_ctf
from sp_filter import filt_ctf
imgdata = EMData.read_images(stack, range(img_begin, img_end))
if options.CTF:
vol = recons3d_4nn_ctf_MPI(myid, imgdata, 1.0, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
else:
vol = recons3d_4nn_MPI(myid, imgdata, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
bcast_EMData_to_all(vol, myid)
volft, kb = prep_vol(vol)
mask = model_circle(nx/2-2, nx, ny)
varList = []
for i in xrange(img_begin, img_end):
phi, theta, psi, s2x, s2y = get_params_proj(imgdata[i-img_begin])
ref_prj = prgs(volft, kb, [phi, theta, psi, -s2x, -s2y])
if options.CTF:
ctf_params = get_ctf(imgdata[i-img_begin])
ref_prj = filt_ctf(ref_prj, generate_ctf(ctf_params))
diff, A, B = im_diff(ref_prj, imgdata[i-img_begin], mask)
diff2 = diff*diff
set_params_proj(diff2, [phi, theta, psi, s2x, s2y])
varList.append(diff2)
mpi_barrier(MPI_COMM_WORLD)
"""
if options.VAR: # 2D variance images have no shifts
#varList = EMData.read_images(stack, range(img_begin, img_end))
from EMAN2 import Region
for index_of_particle in range(img_begin, img_end):
image = get_im(stack, index_of_proj)
if current_window > 0:
varList.append(
fdecimate(
window2d(image, current_window, current_window),
nx, ny))
else:
varList.append(fdecimate(image, nx, ny))
else:
from sp_utilities import bcast_number_to_all, bcast_list_to_all, send_EMData, recv_EMData
from sp_utilities import set_params_proj, get_params_proj, params_3D_2D, get_params2D, set_params2D, compose_transform2
from sp_utilities import model_blank, nearest_proj, model_circle, write_text_row, wrap_mpi_gatherv
from sp_applications import pca
from sp_statistics import avgvar, avgvar_ctf, ccc
from sp_filter import filt_tanl
from sp_morphology import threshold, square_root
from sp_projection import project, prep_vol, prgs
from sets import Set
from sp_utilities import wrap_mpi_recv, wrap_mpi_bcast, wrap_mpi_send
import numpy as np
if myid == main_node:
t1 = time()
proj_angles = []
aveList = []
tab = EMUtil.get_all_attributes(stack, 'xform.projection')
for i in range(nima):
t = tab[i].get_params('spider')
phi = t['phi']
theta = t['theta']
psi = t['psi']
x = theta
if x > 90.0: x = 180.0 - x
x = x * 10000 + psi
proj_angles.append([x, t['phi'], t['theta'], t['psi'], i])
t2 = time()
log_main.add(
"%-70s: %d\n" %
("Number of neighboring projections", img_per_grp))
log_main.add("...... Finding neighboring projections\n")
log_main.add("Number of images per group: %d" % img_per_grp)
log_main.add("Now grouping projections")
proj_angles.sort()
proj_angles_list = np.full((nima, 4), 0.0, dtype=np.float32)
for i in range(nima):
proj_angles_list[i][0] = proj_angles[i][1]
proj_angles_list[i][1] = proj_angles[i][2]
proj_angles_list[i][2] = proj_angles[i][3]
proj_angles_list[i][3] = proj_angles[i][4]
else:
proj_angles_list = 0
proj_angles_list = wrap_mpi_bcast(proj_angles_list, main_node,
MPI_COMM_WORLD)
proj_angles = []
for i in range(nima):
proj_angles.append([
proj_angles_list[i][0], proj_angles_list[i][1],
proj_angles_list[i][2],
int(proj_angles_list[i][3])
])
del proj_angles_list
proj_list, mirror_list = nearest_proj(proj_angles, img_per_grp,
range(img_begin, img_end))
all_proj = Set()
for im in proj_list:
for jm in im:
all_proj.add(proj_angles[jm][3])
all_proj = list(all_proj)
index = {}
for i in range(len(all_proj)):
index[all_proj[i]] = i
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
log_main.add("%-70s: %.2f\n" %
("Finding neighboring projections lasted [s]",
time() - t2))
log_main.add("%-70s: %d\n" %
("Number of groups processed on the main node",
len(proj_list)))
log_main.add("Grouping projections took: %12.1f [m]" %
((time() - t2) / 60.))
log_main.add("Number of groups on main node: ", len(proj_list))
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
log_main.add("...... Calculating the stack of 2D variances \n")
# Memory estimation. There are two memory consumption peaks
# peak 1. Compute ave, var;
# peak 2. Var volume reconstruction;
# proj_params = [0.0]*(nima*5)
aveList = []
varList = []
#if nvec > 0: eigList = [[] for i in range(nvec)]
dnumber = len(
all_proj) # all neighborhood set for assigned to myid
pnumber = len(proj_list) * 2. + img_per_grp # aveList and varList
tnumber = dnumber + pnumber
vol_size2 = nx**3 * 4. * 8 / 1.e9
vol_size1 = 2. * nnxo**3 * 4. * 8 / 1.e9
proj_size = nnxo * nnyo * len(
proj_list) * 4. * 2. / 1.e9 # both aveList and varList
orig_data_size = nnxo * nnyo * 4. * tnumber / 1.e9
reduced_data_size = nx * nx * 4. * tnumber / 1.e9
full_data = np.full((number_of_proc, 2), -1., dtype=np.float16)
full_data[myid] = orig_data_size, reduced_data_size
if myid != main_node:
wrap_mpi_send(full_data, main_node, MPI_COMM_WORLD)
if myid == main_node:
for iproc in range(number_of_proc):
if iproc != main_node:
dummy = wrap_mpi_recv(iproc, MPI_COMM_WORLD)
full_data[np.where(dummy > -1)] = dummy[np.where(
dummy > -1)]
del dummy
mpi_barrier(MPI_COMM_WORLD)
full_data = wrap_mpi_bcast(full_data, main_node, MPI_COMM_WORLD)
# find the CPU with heaviest load
minindx = np.argsort(full_data, 0)
heavy_load_myid = minindx[-1][1]
total_mem = sum(full_data)
if myid == main_node:
if current_window == 0:
log_main.add(
"Nx: current image size = %d. Decimated by %f from %d"
% (nx, current_decimate, nnxo))
else:
log_main.add(
"Nx: current image size = %d. Windowed to %d, and decimated by %f from %d"
% (nx, current_window, current_decimate, nnxo))
log_main.add("Nproj: number of particle images.")
log_main.add("Navg: number of 2D average images.")
log_main.add("Nvar: number of 2D variance images.")
log_main.add(
"Img_per_grp: user defined image per group for averaging = %d"
% img_per_grp)
log_main.add(
"Overhead: total python overhead memory consumption = %f"
% overhead_loading)
log_main.add("Total memory) = 4.0*nx^2*(nproj + navg +nvar+ img_per_grp)/1.0e9 + overhead: %12.3f [GB]"%\
(total_mem[1] + overhead_loading))
del full_data
mpi_barrier(MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add(
"Begin reading and preprocessing images on processor. Wait... "
)
ttt = time()
#imgdata = EMData.read_images(stack, all_proj)
imgdata = [None for im in range(len(all_proj))]
for index_of_proj in range(len(all_proj)):
#image = get_im(stack, all_proj[index_of_proj])
if (current_window > 0):
imgdata[index_of_proj] = fdecimate(
window2d(get_im(stack, all_proj[index_of_proj]),
current_window, current_window), nx, ny)
else:
imgdata[index_of_proj] = fdecimate(
get_im(stack, all_proj[index_of_proj]), nx, ny)
if (current_decimate > 0.0 and options.CTF):
ctf = imgdata[index_of_proj].get_attr("ctf")
ctf.apix = ctf.apix / current_decimate
imgdata[index_of_proj].set_attr("ctf", ctf)
if myid == heavy_load_myid and index_of_proj % 100 == 0:
log_main.add(" ...... %6.2f%% " %
(index_of_proj / float(len(all_proj)) * 100.))
mpi_barrier(MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add("All_proj preprocessing cost %7.2f m" %
((time() - ttt) / 60.))
log_main.add("Wait untill reading on all CPUs done...")
'''
imgdata2 = EMData.read_images(stack, range(img_begin, img_end))
if options.fl > 0.0:
for k in xrange(len(imgdata2)):
imgdata2[k] = filt_tanl(imgdata2[k], options.fl, options.aa)
if options.CTF:
vol = recons3d_4nn_ctf_MPI(myid, imgdata2, 1.0, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
else:
vol = recons3d_4nn_MPI(myid, imgdata2, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
if myid == main_node:
vol.write_image("vol_ctf.hdf")
print_msg("Writing to the disk volume reconstructed from averages as : %s\n"%("vol_ctf.hdf"))
del vol, imgdata2
mpi_barrier(MPI_COMM_WORLD)
'''
from sp_applications import prepare_2d_forPCA
from sp_utilities import model_blank
from EMAN2 import Transform
if not options.no_norm:
mask = model_circle(nx / 2 - 2, nx, nx)
if options.CTF:
from sp_utilities import pad
from sp_filter import filt_ctf
from sp_filter import filt_tanl
if myid == heavy_load_myid:
log_main.add("Start computing 2D aveList and varList. Wait...")
ttt = time()
inner = nx // 2 - 4
outer = inner + 2
xform_proj_for_2D = [None for i in range(len(proj_list))]
for i in range(len(proj_list)):
ki = proj_angles[proj_list[i][0]][3]
if ki >= symbaselen: continue
mi = index[ki]
dpar = Util.get_transform_params(imgdata[mi],
"xform.projection", "spider")
phiM, thetaM, psiM, s2xM, s2yM = dpar["phi"], dpar[
"theta"], dpar[
"psi"], -dpar["tx"] * current_decimate, -dpar[
"ty"] * current_decimate
grp_imgdata = []
for j in range(img_per_grp):
mj = index[proj_angles[proj_list[i][j]][3]]
cpar = Util.get_transform_params(imgdata[mj],
"xform.projection",
"spider")
alpha, sx, sy, mirror = params_3D_2D_NEW(
cpar["phi"], cpar["theta"], cpar["psi"],
-cpar["tx"] * current_decimate,
-cpar["ty"] * current_decimate, mirror_list[i][j])
if thetaM <= 90:
if mirror == 0:
alpha, sx, sy, scale = compose_transform2(
alpha, sx, sy, 1.0, phiM - cpar["phi"], 0.0,
0.0, 1.0)
else:
alpha, sx, sy, scale = compose_transform2(
alpha, sx, sy, 1.0, 180 - (phiM - cpar["phi"]),
0.0, 0.0, 1.0)
else:
if mirror == 0:
alpha, sx, sy, scale = compose_transform2(
alpha, sx, sy, 1.0, -(phiM - cpar["phi"]), 0.0,
0.0, 1.0)
else:
alpha, sx, sy, scale = compose_transform2(
alpha, sx, sy, 1.0,
-(180 - (phiM - cpar["phi"])), 0.0, 0.0, 1.0)
imgdata[mj].set_attr(
"xform.align2d",
Transform({
"type": "2D",
"alpha": alpha,
"tx": sx,
"ty": sy,
"mirror": mirror,
"scale": 1.0
}))
grp_imgdata.append(imgdata[mj])
if not options.no_norm:
for k in range(img_per_grp):
ave, std, minn, maxx = Util.infomask(
grp_imgdata[k], mask, False)
grp_imgdata[k] -= ave
grp_imgdata[k] /= std
if options.fl > 0.0:
for k in range(img_per_grp):
grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl,
options.aa)
# Because of background issues, only linear option works.
if options.CTF:
ave, var = aves_wiener(grp_imgdata,
SNR=1.0e5,
interpolation_method="linear")
else:
ave, var = ave_var(grp_imgdata)
# Switch to std dev
# threshold is not really needed,it is just in case due to numerical accuracy something turns out negative.
var = square_root(threshold(var))
set_params_proj(ave, [phiM, thetaM, 0.0, 0.0, 0.0])
set_params_proj(var, [phiM, thetaM, 0.0, 0.0, 0.0])
aveList.append(ave)
varList.append(var)
xform_proj_for_2D[i] = [phiM, thetaM, 0.0, 0.0, 0.0]
'''
if nvec > 0:
eig = pca(input_stacks=grp_imgdata, subavg="", mask_radius=radiuspca, nvec=nvec, incore=True, shuffle=False, genbuf=True)
for k in range(nvec):
set_params_proj(eig[k], [phiM, thetaM, 0.0, 0.0, 0.0])
eigList[k].append(eig[k])
"""
if myid == 0 and i == 0:
for k in xrange(nvec):
eig[k].write_image("eig.hdf", k)
"""
'''
if (myid == heavy_load_myid) and (i % 100 == 0):
log_main.add(" ......%6.2f%% " %
(i / float(len(proj_list)) * 100.))
del imgdata, grp_imgdata, cpar, dpar, all_proj, proj_angles, index
if not options.no_norm: del mask
if myid == main_node: del tab
# At this point, all averages and variances are computed
mpi_barrier(MPI_COMM_WORLD)
if (myid == heavy_load_myid):
log_main.add("Computing aveList and varList took %12.1f [m]" %
((time() - ttt) / 60.))
xform_proj_for_2D = wrap_mpi_gatherv(xform_proj_for_2D, main_node,
MPI_COMM_WORLD)
if (myid == main_node):
write_text_row([str(entry) for entry in xform_proj_for_2D],
os.path.join(current_output_dir, "params.txt"))
del xform_proj_for_2D
mpi_barrier(MPI_COMM_WORLD)
if options.ave2D:
from sp_fundamentals import fpol
from sp_applications import header
if myid == main_node:
log_main.add("Compute ave2D ... ")
km = 0
for i in range(number_of_proc):
if i == main_node:
for im in range(len(aveList)):
aveList[im].write_image(
os.path.join(current_output_dir,
options.ave2D), km)
km += 1
else:
nl = mpi_recv(1, MPI_INT, i,
SPARX_MPI_TAG_UNIVERSAL,
MPI_COMM_WORLD)
nl = int(nl[0])
for im in range(nl):
ave = recv_EMData(i, im + i + 70000)
"""
nm = mpi_recv(1, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
nm = int(nm[0])
members = mpi_recv(nm, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('members', map(int, members))
members = mpi_recv(nm, MPI_FLOAT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('pix_err', map(float, members))
members = mpi_recv(3, MPI_FLOAT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('refprojdir', map(float, members))
"""
tmpvol = fpol(ave, nx, nx, 1)
tmpvol.write_image(
os.path.join(current_output_dir,
options.ave2D), km)
km += 1
else:
mpi_send(len(aveList), 1, MPI_INT, main_node,
SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
for im in range(len(aveList)):
send_EMData(aveList[im], main_node, im + myid + 70000)
"""
members = aveList[im].get_attr('members')
mpi_send(len(members), 1, MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
mpi_send(members, len(members), MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
members = aveList[im].get_attr('pix_err')
mpi_send(members, len(members), MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
try:
members = aveList[im].get_attr('refprojdir')
mpi_send(members, 3, MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
except:
mpi_send([-999.0,-999.0,-999.0], 3, MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
"""
if myid == main_node:
header(os.path.join(current_output_dir, options.ave2D),
params='xform.projection',
fimport=os.path.join(current_output_dir,
"params.txt"))
mpi_barrier(MPI_COMM_WORLD)
if options.ave3D:
from sp_fundamentals import fpol
t5 = time()
if myid == main_node: log_main.add("Reconstruct ave3D ... ")
ave3D = recons3d_4nn_MPI(myid,
aveList,
symmetry=options.sym,
npad=options.npad)
bcast_EMData_to_all(ave3D, myid)
if myid == main_node:
if current_decimate != 1.0:
ave3D = resample(ave3D, 1. / current_decimate)
ave3D = fpol(ave3D, nnxo, nnxo,
nnxo) # always to the orignal image size
set_pixel_size(ave3D, 1.0)
ave3D.write_image(
os.path.join(current_output_dir, options.ave3D))
log_main.add("Ave3D reconstruction took %12.1f [m]" %
((time() - t5) / 60.0))
log_main.add("%-70s: %s\n" %
("The reconstructed ave3D is saved as ",
options.ave3D))
mpi_barrier(MPI_COMM_WORLD)
del ave, var, proj_list, stack, alpha, sx, sy, mirror, aveList
'''
if nvec > 0:
for k in range(nvec):
if myid == main_node:log_main.add("Reconstruction eigenvolumes", k)
cont = True
ITER = 0
mask2d = model_circle(radiuspca, nx, nx)
while cont:
#print "On node %d, iteration %d"%(myid, ITER)
eig3D = recons3d_4nn_MPI(myid, eigList[k], symmetry=options.sym, npad=options.npad)
bcast_EMData_to_all(eig3D, myid, main_node)
if options.fl > 0.0:
eig3D = filt_tanl(eig3D, options.fl, options.aa)
if myid == main_node:
eig3D.write_image(os.path.join(options.outpout_dir, "eig3d_%03d.hdf"%(k, ITER)))
Util.mul_img( eig3D, model_circle(radiuspca, nx, nx, nx) )
eig3Df, kb = prep_vol(eig3D)
del eig3D
cont = False
icont = 0
for l in range(len(eigList[k])):
phi, theta, psi, s2x, s2y = get_params_proj(eigList[k][l])
proj = prgs(eig3Df, kb, [phi, theta, psi, s2x, s2y])
cl = ccc(proj, eigList[k][l], mask2d)
if cl < 0.0:
icont += 1
cont = True
eigList[k][l] *= -1.0
u = int(cont)
u = mpi_reduce([u], 1, MPI_INT, MPI_MAX, main_node, MPI_COMM_WORLD)
icont = mpi_reduce([icont], 1, MPI_INT, MPI_SUM, main_node, MPI_COMM_WORLD)
if myid == main_node:
u = int(u[0])
log_main.add(" Eigenvector: ",k," number changed ",int(icont[0]))
else: u = 0
u = bcast_number_to_all(u, main_node)
cont = bool(u)
ITER += 1
del eig3Df, kb
mpi_barrier(MPI_COMM_WORLD)
del eigList, mask2d
'''
if options.ave3D: del ave3D
if options.var2D:
from sp_fundamentals import fpol
from sp_applications import header
if myid == main_node:
log_main.add("Compute var2D...")
km = 0
for i in range(number_of_proc):
if i == main_node:
for im in range(len(varList)):
tmpvol = fpol(varList[im], nx, nx, 1)
tmpvol.write_image(
os.path.join(current_output_dir,
options.var2D), km)
km += 1
else:
nl = mpi_recv(1, MPI_INT, i,
SPARX_MPI_TAG_UNIVERSAL,
MPI_COMM_WORLD)
nl = int(nl[0])
for im in range(nl):
ave = recv_EMData(i, im + i + 70000)
tmpvol = fpol(ave, nx, nx, 1)
tmpvol.write_image(
os.path.join(current_output_dir,
options.var2D), km)
km += 1
else:
mpi_send(len(varList), 1, MPI_INT, main_node,
SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
for im in range(len(varList)):
send_EMData(varList[im], main_node, im + myid +
70000) # What with the attributes??
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
from sp_applications import header
header(os.path.join(current_output_dir, options.var2D),
params='xform.projection',
fimport=os.path.join(current_output_dir,
"params.txt"))
mpi_barrier(MPI_COMM_WORLD)
if options.var3D:
if myid == main_node: log_main.add("Reconstruct var3D ...")
t6 = time()
# radiusvar = options.radius
# if( radiusvar < 0 ): radiusvar = nx//2 -3
res = recons3d_4nn_MPI(myid,
varList,
symmetry=options.sym,
npad=options.npad)
#res = recons3d_em_MPI(varList, vol_stack, options.iter, radiusvar, options.abs, True, options.sym, options.squ)
if myid == main_node:
from sp_fundamentals import fpol
if current_decimate != 1.0:
res = resample(res, 1. / current_decimate)
res = fpol(res, nnxo, nnxo, nnxo)
set_pixel_size(res, 1.0)
res.write_image(os.path.join(current_output_dir,
options.var3D))
log_main.add(
"%-70s: %s\n" %
("The reconstructed var3D is saved as ", options.var3D))
log_main.add("Var3D reconstruction took %f12.1 [m]" %
((time() - t6) / 60.0))
log_main.add("Total computation time %f12.1 [m]" %
((time() - t0) / 60.0))
log_main.add("sx3dvariability finishes")
if RUNNING_UNDER_MPI:
sp_global_def.MPI = False
sp_global_def.BATCH = False
def main():
def params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror):
# the final ali2d parameters already combine shifts operation first and rotation operation second for parameters converted from 3D
if mirror:
m = 1
alpha, sx, sy, scalen = sp_utilities.compose_transform2(
0, s2x, s2y, 1.0, 540.0 - psi, 0, 0, 1.0)
else:
m = 0
alpha, sx, sy, scalen = sp_utilities.compose_transform2(
0, s2x, s2y, 1.0, 360.0 - psi, 0, 0, 1.0)
return alpha, sx, sy, m
progname = optparse.os.path.basename(sys.argv[0])
usage = (
progname +
" prj_stack --ave2D= --var2D= --ave3D= --var3D= --img_per_grp= --fl= --aa= --sym=symmetry --CTF"
)
parser = optparse.OptionParser(usage, version=sp_global_def.SPARXVERSION)
parser.add_option("--output_dir",
type="string",
default="./",
help="Output directory")
parser.add_option(
"--ave2D",
type="string",
default=False,
help="Write to the disk a stack of 2D averages",
)
parser.add_option(
"--var2D",
type="string",
default=False,
help="Write to the disk a stack of 2D variances",
)
parser.add_option(
"--ave3D",
type="string",
default=False,
help="Write to the disk reconstructed 3D average",
)
parser.add_option(
"--var3D",
type="string",
default=False,
help="Compute 3D variability (time consuming!)",
)
parser.add_option(
"--img_per_grp",
type="int",
default=100,
help="Number of neighbouring projections.(Default is 100)",
)
parser.add_option(
"--no_norm",
action="store_true",
default=False,
help="Do not use normalization.(Default is to apply normalization)",
)
# parser.add_option("--radius", type="int" , default=-1 , help="radius for 3D variability" )
parser.add_option(
"--npad",
type="int",
default=2,
help=
"Number of time to pad the original images.(Default is 2 times padding)",
)
parser.add_option("--sym",
type="string",
default="c1",
help="Symmetry. (Default is no symmetry)")
parser.add_option(
"--fl",
type="float",
default=0.0,
help=
"Low pass filter cutoff in absolute frequency (0.0 - 0.5) and is applied to decimated images. (Default - no filtration)",
)
parser.add_option(
"--aa",
type="float",
default=0.02,
help=
"Fall off of the filter. Use default value if user has no clue about falloff (Default value is 0.02)",
)
parser.add_option(
"--CTF",
action="store_true",
default=False,
help="Use CFT correction.(Default is no CTF correction)",
)
# parser.add_option("--MPI" , action="store_true", default=False, help="use MPI version")
# parser.add_option("--radiuspca", type="int" , default=-1 , help="radius for PCA" )
# parser.add_option("--iter", type="int" , default=40 , help="maximum number of iterations (stop criterion of reconstruction process)" )
# parser.add_option("--abs", type="float" , default=0.0 , help="minimum average absolute change of voxels' values (stop criterion of reconstruction process)" )
# parser.add_option("--squ", type="float" , default=0.0 , help="minimum average squared change of voxels' values (stop criterion of reconstruction process)" )
parser.add_option(
"--VAR",
action="store_true",
default=False,
help="Stack of input consists of 2D variances (Default False)",
)
parser.add_option(
"--decimate",
type="float",
default=0.25,
help="Image decimate rate, a number less than 1. (Default is 0.25)",
)
parser.add_option(
"--window",
type="int",
default=0,
help=
"Target image size relative to original image size. (Default value is zero.)",
)
# parser.add_option("--SND", action="store_true", default=False, help="compute squared normalized differences (Default False)")
# parser.add_option("--nvec", type="int" , default=0 , help="Number of eigenvectors, (Default = 0 meaning no PCA calculated)")
parser.add_option(
"--symmetrize",
action="store_true",
default=False,
help="Prepare input stack for handling symmetry (Default False)",
)
parser.add_option("--overhead",
type="float",
default=0.5,
help="python overhead per CPU.")
(options, args) = parser.parse_args()
#####
# from mpi import *
# This is code for handling symmetries by the above program. To be incorporated. PAP 01/27/2015
# Set up global variables related to bdb cache
if sp_global_def.CACHE_DISABLE:
sp_utilities.disable_bdb_cache()
# Set up global variables related to ERROR function
sp_global_def.BATCH = True
# detect if program is running under MPI
RUNNING_UNDER_MPI = "OMPI_COMM_WORLD_SIZE" in optparse.os.environ
if RUNNING_UNDER_MPI:
sp_global_def.MPI = True
if options.output_dir == "./":
current_output_dir = optparse.os.path.abspath(options.output_dir)
else:
current_output_dir = options.output_dir
if options.symmetrize:
if mpi.mpi_comm_size(mpi.MPI_COMM_WORLD) > 1:
sp_global_def.ERROR(
"Cannot use more than one CPU for symmetry preparation")
if not optparse.os.path.exists(current_output_dir):
optparse.os.makedirs(current_output_dir)
sp_global_def.write_command(current_output_dir)
if optparse.os.path.exists(
optparse.os.path.join(current_output_dir, "log.txt")):
optparse.os.remove(
optparse.os.path.join(current_output_dir, "log.txt"))
log_main = sp_logger.Logger(sp_logger.BaseLogger_Files())
log_main.prefix = optparse.os.path.join(current_output_dir, "./")
instack = args[0]
sym = options.sym.lower()
if sym == "c1":
sp_global_def.ERROR(
"There is no need to symmetrize stack for C1 symmetry")
line = ""
for a in sys.argv:
line += " " + a
log_main.add(line)
if instack[:4] != "bdb:":
# if output_dir =="./": stack = "bdb:data"
stack = "bdb:" + current_output_dir + "/data"
sp_utilities.delete_bdb(stack)
junk = sp_utilities.cmdexecute("sp_cpy.py " + instack + " " +
stack)
else:
stack = instack
qt = EMAN2_cppwrap.EMUtil.get_all_attributes(stack, "xform.projection")
na = len(qt)
ts = sp_utilities.get_symt(sym)
ks = len(ts)
angsa = [None] * na
for k in range(ks):
# Qfile = "Q%1d"%k
# if options.output_dir!="./": Qfile = os.path.join(options.output_dir,"Q%1d"%k)
Qfile = optparse.os.path.join(current_output_dir, "Q%1d" % k)
# delete_bdb("bdb:Q%1d"%k)
sp_utilities.delete_bdb("bdb:" + Qfile)
# junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
junk = sp_utilities.cmdexecute("e2bdb.py " + stack +
" --makevstack=bdb:" + Qfile)
# DB = db_open_dict("bdb:Q%1d"%k)
DB = EMAN2db.db_open_dict("bdb:" + Qfile)
for i in range(na):
ut = qt[i] * ts[k]
DB.set_attr(i, "xform.projection", ut)
# bt = ut.get_params("spider")
# angsa[i] = [round(bt["phi"],3)%360.0, round(bt["theta"],3)%360.0, bt["psi"], -bt["tx"], -bt["ty"]]
# write_text_row(angsa, 'ptsma%1d.txt'%k)
# junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
# junk = cmdexecute("sxheader.py bdb:Q%1d --params=xform.projection --import=ptsma%1d.txt"%(k,k))
DB.close()
# if options.output_dir =="./": delete_bdb("bdb:sdata")
sp_utilities.delete_bdb("bdb:" + current_output_dir + "/" + "sdata")
# junk = cmdexecute("e2bdb.py . --makevstack=bdb:sdata --filt=Q")
sdata = "bdb:" + current_output_dir + "/" + "sdata"
sp_global_def.sxprint(sdata)
junk = sp_utilities.cmdexecute("e2bdb.py " + current_output_dir +
" --makevstack=" + sdata + " --filt=Q")
# junk = cmdexecute("ls EMAN2DB/sdata*")
# a = get_im("bdb:sdata")
a = sp_utilities.get_im(sdata)
a.set_attr("variabilitysymmetry", sym)
# a.write_image("bdb:sdata")
a.write_image(sdata)
else:
myid = mpi.mpi_comm_rank(mpi.MPI_COMM_WORLD)
number_of_proc = mpi.mpi_comm_size(mpi.MPI_COMM_WORLD)
main_node = 0
shared_comm = mpi.mpi_comm_split_type(mpi.MPI_COMM_WORLD,
mpi.MPI_COMM_TYPE_SHARED, 0,
mpi.MPI_INFO_NULL)
myid_on_node = mpi.mpi_comm_rank(shared_comm)
no_of_processes_per_group = mpi.mpi_comm_size(shared_comm)
masters_from_groups_vs_everything_else_comm = mpi.mpi_comm_split(
mpi.MPI_COMM_WORLD, main_node == myid_on_node, myid_on_node)
color, no_of_groups, balanced_processor_load_on_nodes = sp_utilities.get_colors_and_subsets(
main_node,
mpi.MPI_COMM_WORLD,
myid,
shared_comm,
myid_on_node,
masters_from_groups_vs_everything_else_comm,
)
overhead_loading = options.overhead * number_of_proc
# memory_per_node = options.memory_per_node
# if memory_per_node == -1.: memory_per_node = 2.*no_of_processes_per_group
keepgoing = 1
current_window = options.window
current_decimate = options.decimate
if len(args) == 1:
stack = args[0]
else:
sp_global_def.sxprint("Usage: " + usage)
sp_global_def.sxprint("Please run '" + progname +
" -h' for detailed options")
sp_global_def.ERROR(
"Invalid number of parameters used. Please see usage information above."
)
return
t0 = time.time()
# obsolete flags
options.MPI = True
# options.nvec = 0
options.radiuspca = -1
options.iter = 40
options.abs = 0.0
options.squ = 0.0
if options.fl > 0.0 and options.aa == 0.0:
sp_global_def.ERROR(
"Fall off has to be given for the low-pass filter", myid=myid)
# if options.VAR and options.SND:
# ERROR( "Only one of var and SND can be set!",myid=myid )
if options.VAR and (options.ave2D or options.ave3D or options.var2D):
sp_global_def.ERROR(
"When VAR is set, the program cannot output ave2D, ave3D or var2D",
myid=myid,
)
# if options.SND and (options.ave2D or options.ave3D):
# ERROR( "When SND is set, the program cannot output ave2D or ave3D", myid=myid )
# if options.nvec > 0 :
# ERROR( "PCA option not implemented", myid=myid )
# if options.nvec > 0 and options.ave3D == None:
# ERROR( "When doing PCA analysis, one must set ave3D", myid=myid )
if current_decimate > 1.0 or current_decimate < 0.0:
sp_global_def.ERROR(
"Decimate rate should be a value between 0.0 and 1.0",
myid=myid)
if current_window < 0.0:
sp_global_def.ERROR(
"Target window size should be always larger than zero",
myid=myid)
if myid == main_node:
img = sp_utilities.get_image(stack, 0)
nx = img.get_xsize()
ny = img.get_ysize()
if min(nx, ny) < current_window:
keepgoing = 0
keepgoing = sp_utilities.bcast_number_to_all(keepgoing, main_node,
mpi.MPI_COMM_WORLD)
if keepgoing == 0:
sp_global_def.ERROR(
"The target window size cannot be larger than the size of decimated image",
myid=myid,
)
options.sym = options.sym.lower()
# if global_def.CACHE_DISABLE:
# from utilities import disable_bdb_cache
# disable_bdb_cache()
# global_def.BATCH = True
if myid == main_node:
if not optparse.os.path.exists(current_output_dir):
optparse.os.makedirs(
current_output_dir
) # Never delete output_dir in the program!
img_per_grp = options.img_per_grp
# nvec = options.nvec
radiuspca = options.radiuspca
# if os.path.exists(os.path.join(options.output_dir, "log.txt")): os.remove(os.path.join(options.output_dir, "log.txt"))
log_main = sp_logger.Logger(sp_logger.BaseLogger_Files())
log_main.prefix = optparse.os.path.join(current_output_dir, "./")
if myid == main_node:
line = ""
for a in sys.argv:
line += " " + a
log_main.add(line)
log_main.add("-------->>>Settings given by all options<<<-------")
log_main.add("Symmetry : %s" % options.sym)
log_main.add("Input stack : %s" % stack)
log_main.add("Output_dir : %s" % current_output_dir)
if options.ave3D:
log_main.add("Ave3d : %s" % options.ave3D)
if options.var3D:
log_main.add("Var3d : %s" % options.var3D)
if options.ave2D:
log_main.add("Ave2D : %s" % options.ave2D)
if options.var2D:
log_main.add("Var2D : %s" % options.var2D)
if options.VAR:
log_main.add("VAR : True")
else:
log_main.add("VAR : False")
if options.CTF:
log_main.add("CTF correction : True ")
else:
log_main.add("CTF correction : False ")
log_main.add("Image per group : %5d" % options.img_per_grp)
log_main.add("Image decimate rate : %4.3f" % current_decimate)
log_main.add("Low pass filter : %4.3f" % options.fl)
current_fl = options.fl
if current_fl == 0.0:
current_fl = 0.5
log_main.add(
"Current low pass filter is equivalent to cutoff frequency %4.3f for original image size"
% round((current_fl * current_decimate), 3))
log_main.add("Window size : %5d " % current_window)
log_main.add("sx3dvariability begins")
symbaselen = 0
if myid == main_node:
nima = EMAN2_cppwrap.EMUtil.get_image_count(stack)
img = sp_utilities.get_image(stack)
nx = img.get_xsize()
ny = img.get_ysize()
nnxo = nx
nnyo = ny
if options.sym != "c1":
imgdata = sp_utilities.get_im(stack)
try:
i = imgdata.get_attr("variabilitysymmetry").lower()
if i != options.sym:
sp_global_def.ERROR(
"The symmetry provided does not agree with the symmetry of the input stack",
myid=myid,
)
except:
sp_global_def.ERROR(
"Input stack is not prepared for symmetry, please follow instructions",
myid=myid,
)
i = len(sp_utilities.get_symt(options.sym))
if (old_div(nima, i)) * i != nima:
sp_global_def.ERROR(
"The length of the input stack is incorrect for symmetry processing",
myid=myid,
)
symbaselen = old_div(nima, i)
else:
symbaselen = nima
else:
nima = 0
nx = 0
ny = 0
nnxo = 0
nnyo = 0
nima = sp_utilities.bcast_number_to_all(nima)
nx = sp_utilities.bcast_number_to_all(nx)
ny = sp_utilities.bcast_number_to_all(ny)
nnxo = sp_utilities.bcast_number_to_all(nnxo)
nnyo = sp_utilities.bcast_number_to_all(nnyo)
if current_window > max(nx, ny):
sp_global_def.ERROR(
"Window size is larger than the original image size")
if current_decimate == 1.0:
if current_window != 0:
nx = current_window
ny = current_window
else:
if current_window == 0:
nx = int(nx * current_decimate + 0.5)
ny = int(ny * current_decimate + 0.5)
else:
nx = int(current_window * current_decimate + 0.5)
ny = nx
symbaselen = sp_utilities.bcast_number_to_all(symbaselen)
# check FFT prime number
is_fft_friendly = nx == sp_fundamentals.smallprime(nx)
if not is_fft_friendly:
if myid == main_node:
log_main.add(
"The target image size is not a product of small prime numbers"
)
log_main.add("Program adjusts the input settings!")
### two cases
if current_decimate == 1.0:
nx = sp_fundamentals.smallprime(nx)
ny = nx
current_window = nx # update
if myid == main_node:
log_main.add("The window size is updated to %d." %
current_window)
else:
if current_window == 0:
nx = sp_fundamentals.smallprime(
int(nx * current_decimate + 0.5))
current_decimate = old_div(float(nx), nnxo)
ny = nx
if myid == main_node:
log_main.add("The decimate rate is updated to %f." %
current_decimate)
else:
nx = sp_fundamentals.smallprime(
int(current_window * current_decimate + 0.5))
ny = nx
current_window = int(old_div(nx, current_decimate) + 0.5)
if myid == main_node:
log_main.add("The window size is updated to %d." %
current_window)
if myid == main_node:
log_main.add("The target image size is %d" % nx)
if radiuspca == -1:
radiuspca = old_div(nx, 2) - 2
if myid == main_node:
log_main.add("%-70s: %d\n" % ("Number of projection", nima))
img_begin, img_end = sp_applications.MPI_start_end(
nima, number_of_proc, myid)
"""Multiline Comment0"""
"""
Comments from adnan, replace index_of_proj to index_of_particle, index_of_proj was not defined
also varList is not defined not made an empty list there
"""
if options.VAR: # 2D variance images have no shifts
varList = []
# varList = EMData.read_images(stack, range(img_begin, img_end))
for index_of_particle in range(img_begin, img_end):
image = sp_utilities.get_im(stack, index_of_particle)
if current_window > 0:
varList.append(
sp_fundamentals.fdecimate(
sp_fundamentals.window2d(image, current_window,
current_window),
nx,
ny,
))
else:
varList.append(sp_fundamentals.fdecimate(image, nx, ny))
else:
if myid == main_node:
t1 = time.time()
proj_angles = []
aveList = []
tab = EMAN2_cppwrap.EMUtil.get_all_attributes(
stack, "xform.projection")
for i in range(nima):
t = tab[i].get_params("spider")
phi = t["phi"]
theta = t["theta"]
psi = t["psi"]
x = theta
if x > 90.0:
x = 180.0 - x
x = x * 10000 + psi
proj_angles.append([x, t["phi"], t["theta"], t["psi"], i])
t2 = time.time()
log_main.add(
"%-70s: %d\n" %
("Number of neighboring projections", img_per_grp))
log_main.add("...... Finding neighboring projections\n")
log_main.add("Number of images per group: %d" % img_per_grp)
log_main.add("Now grouping projections")
proj_angles.sort()
proj_angles_list = numpy.full((nima, 4),
0.0,
dtype=numpy.float32)
for i in range(nima):
proj_angles_list[i][0] = proj_angles[i][1]
proj_angles_list[i][1] = proj_angles[i][2]
proj_angles_list[i][2] = proj_angles[i][3]
proj_angles_list[i][3] = proj_angles[i][4]
else:
proj_angles_list = 0
proj_angles_list = sp_utilities.wrap_mpi_bcast(
proj_angles_list, main_node, mpi.MPI_COMM_WORLD)
proj_angles = []
for i in range(nima):
proj_angles.append([
proj_angles_list[i][0],
proj_angles_list[i][1],
proj_angles_list[i][2],
int(proj_angles_list[i][3]),
])
del proj_angles_list
proj_list, mirror_list = sp_utilities.nearest_proj(
proj_angles, img_per_grp, range(img_begin, img_end))
all_proj = []
for im in proj_list:
for jm in im:
all_proj.append(proj_angles[jm][3])
all_proj = list(set(all_proj))
index = {}
for i in range(len(all_proj)):
index[all_proj[i]] = i
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == main_node:
log_main.add("%-70s: %.2f\n" %
("Finding neighboring projections lasted [s]",
time.time() - t2))
log_main.add("%-70s: %d\n" %
("Number of groups processed on the main node",
len(proj_list)))
log_main.add("Grouping projections took: %12.1f [m]" %
(old_div((time.time() - t2), 60.0)))
log_main.add("Number of groups on main node: ", len(proj_list))
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == main_node:
log_main.add("...... Calculating the stack of 2D variances \n")
# Memory estimation. There are two memory consumption peaks
# peak 1. Compute ave, var;
# peak 2. Var volume reconstruction;
# proj_params = [0.0]*(nima*5)
aveList = []
varList = []
# if nvec > 0: eigList = [[] for i in range(nvec)]
dnumber = len(
all_proj) # all neighborhood set for assigned to myid
pnumber = len(proj_list) * 2.0 + img_per_grp # aveList and varList
tnumber = dnumber + pnumber
vol_size2 = old_div(nx**3 * 4.0 * 8, 1.0e9)
vol_size1 = old_div(2.0 * nnxo**3 * 4.0 * 8, 1.0e9)
proj_size = old_div(nnxo * nnyo * len(proj_list) * 4.0 * 2.0,
1.0e9) # both aveList and varList
orig_data_size = old_div(nnxo * nnyo * 4.0 * tnumber, 1.0e9)
reduced_data_size = old_div(nx * nx * 4.0 * tnumber, 1.0e9)
full_data = numpy.full((number_of_proc, 2),
-1.0,
dtype=numpy.float16)
full_data[myid] = orig_data_size, reduced_data_size
if myid != main_node:
sp_utilities.wrap_mpi_send(full_data, main_node,
mpi.MPI_COMM_WORLD)
if myid == main_node:
for iproc in range(number_of_proc):
if iproc != main_node:
dummy = sp_utilities.wrap_mpi_recv(
iproc, mpi.MPI_COMM_WORLD)
full_data[numpy.where(dummy > -1)] = dummy[numpy.where(
dummy > -1)]
del dummy
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
full_data = sp_utilities.wrap_mpi_bcast(full_data, main_node,
mpi.MPI_COMM_WORLD)
# find the CPU with heaviest load
minindx = numpy.argsort(full_data, 0)
heavy_load_myid = minindx[-1][1]
total_mem = sum(full_data)
if myid == main_node:
if current_window == 0:
log_main.add(
"Nx: current image size = %d. Decimated by %f from %d"
% (nx, current_decimate, nnxo))
else:
log_main.add(
"Nx: current image size = %d. Windowed to %d, and decimated by %f from %d"
% (nx, current_window, current_decimate, nnxo))
log_main.add("Nproj: number of particle images.")
log_main.add("Navg: number of 2D average images.")
log_main.add("Nvar: number of 2D variance images.")
log_main.add(
"Img_per_grp: user defined image per group for averaging = %d"
% img_per_grp)
log_main.add(
"Overhead: total python overhead memory consumption = %f"
% overhead_loading)
log_main.add(
"Total memory) = 4.0*nx^2*(nproj + navg +nvar+ img_per_grp)/1.0e9 + overhead: %12.3f [GB]"
% (total_mem[1] + overhead_loading))
del full_data
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add(
"Begin reading and preprocessing images on processor. Wait... "
)
ttt = time.time()
# imgdata = EMData.read_images(stack, all_proj)
imgdata = [None for im in range(len(all_proj))]
for index_of_proj in range(len(all_proj)):
# image = get_im(stack, all_proj[index_of_proj])
if current_window > 0:
imgdata[index_of_proj] = sp_fundamentals.fdecimate(
sp_fundamentals.window2d(
sp_utilities.get_im(stack,
all_proj[index_of_proj]),
current_window,
current_window,
),
nx,
ny,
)
else:
imgdata[index_of_proj] = sp_fundamentals.fdecimate(
sp_utilities.get_im(stack, all_proj[index_of_proj]),
nx, ny)
if current_decimate > 0.0 and options.CTF:
ctf = imgdata[index_of_proj].get_attr("ctf")
ctf.apix = old_div(ctf.apix, current_decimate)
imgdata[index_of_proj].set_attr("ctf", ctf)
if myid == heavy_load_myid and index_of_proj % 100 == 0:
log_main.add(
" ...... %6.2f%% " %
(old_div(index_of_proj, float(len(all_proj))) * 100.0))
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add("All_proj preprocessing cost %7.2f m" % (old_div(
(time.time() - ttt), 60.0)))
log_main.add("Wait untill reading on all CPUs done...")
"""Multiline Comment1"""
if not options.no_norm:
mask = sp_utilities.model_circle(old_div(nx, 2) - 2, nx, nx)
if myid == heavy_load_myid:
log_main.add("Start computing 2D aveList and varList. Wait...")
ttt = time.time()
inner = old_div(nx, 2) - 4
outer = inner + 2
xform_proj_for_2D = [None for i in range(len(proj_list))]
for i in range(len(proj_list)):
ki = proj_angles[proj_list[i][0]][3]
if ki >= symbaselen:
continue
mi = index[ki]
dpar = EMAN2_cppwrap.Util.get_transform_params(
imgdata[mi], "xform.projection", "spider")
phiM, thetaM, psiM, s2xM, s2yM = (
dpar["phi"],
dpar["theta"],
dpar["psi"],
-dpar["tx"] * current_decimate,
-dpar["ty"] * current_decimate,
)
grp_imgdata = []
for j in range(img_per_grp):
mj = index[proj_angles[proj_list[i][j]][3]]
cpar = EMAN2_cppwrap.Util.get_transform_params(
imgdata[mj], "xform.projection", "spider")
alpha, sx, sy, mirror = params_3D_2D_NEW(
cpar["phi"],
cpar["theta"],
cpar["psi"],
-cpar["tx"] * current_decimate,
-cpar["ty"] * current_decimate,
mirror_list[i][j],
)
if thetaM <= 90:
if mirror == 0:
alpha, sx, sy, scale = sp_utilities.compose_transform2(
alpha, sx, sy, 1.0, phiM - cpar["phi"], 0.0,
0.0, 1.0)
else:
alpha, sx, sy, scale = sp_utilities.compose_transform2(
alpha,
sx,
sy,
1.0,
180 - (phiM - cpar["phi"]),
0.0,
0.0,
1.0,
)
else:
if mirror == 0:
alpha, sx, sy, scale = sp_utilities.compose_transform2(
alpha, sx, sy, 1.0, -(phiM - cpar["phi"]), 0.0,
0.0, 1.0)
else:
alpha, sx, sy, scale = sp_utilities.compose_transform2(
alpha,
sx,
sy,
1.0,
-(180 - (phiM - cpar["phi"])),
0.0,
0.0,
1.0,
)
imgdata[mj].set_attr(
"xform.align2d",
EMAN2_cppwrap.Transform({
"type": "2D",
"alpha": alpha,
"tx": sx,
"ty": sy,
"mirror": mirror,
"scale": 1.0,
}),
)
grp_imgdata.append(imgdata[mj])
if not options.no_norm:
for k in range(img_per_grp):
ave, std, minn, maxx = EMAN2_cppwrap.Util.infomask(
grp_imgdata[k], mask, False)
grp_imgdata[k] -= ave
grp_imgdata[k] = old_div(grp_imgdata[k], std)
if options.fl > 0.0:
for k in range(img_per_grp):
grp_imgdata[k] = sp_filter.filt_tanl(
grp_imgdata[k], options.fl, options.aa)
# Because of background issues, only linear option works.
if options.CTF:
ave, var = sp_statistics.aves_wiener(
grp_imgdata, SNR=1.0e5, interpolation_method="linear")
else:
ave, var = sp_statistics.ave_var(grp_imgdata)
# Switch to std dev
# threshold is not really needed,it is just in case due to numerical accuracy something turns out negative.
var = sp_morphology.square_root(sp_morphology.threshold(var))
sp_utilities.set_params_proj(ave,
[phiM, thetaM, 0.0, 0.0, 0.0])
sp_utilities.set_params_proj(var,
[phiM, thetaM, 0.0, 0.0, 0.0])
aveList.append(ave)
varList.append(var)
xform_proj_for_2D[i] = [phiM, thetaM, 0.0, 0.0, 0.0]
"""Multiline Comment2"""
if (myid == heavy_load_myid) and (i % 100 == 0):
log_main.add(" ......%6.2f%% " %
(old_div(i, float(len(proj_list))) * 100.0))
del imgdata, grp_imgdata, cpar, dpar, all_proj, proj_angles, index
if not options.no_norm:
del mask
if myid == main_node:
del tab
# At this point, all averages and variances are computed
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add("Computing aveList and varList took %12.1f [m]" %
(old_div((time.time() - ttt), 60.0)))
xform_proj_for_2D = sp_utilities.wrap_mpi_gatherv(
xform_proj_for_2D, main_node, mpi.MPI_COMM_WORLD)
if myid == main_node:
sp_utilities.write_text_row(
[str(entry) for entry in xform_proj_for_2D],
optparse.os.path.join(current_output_dir, "params.txt"),
)
del xform_proj_for_2D
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if options.ave2D:
if myid == main_node:
log_main.add("Compute ave2D ... ")
km = 0
for i in range(number_of_proc):
if i == main_node:
for im in range(len(aveList)):
aveList[im].write_image(
optparse.os.path.join(
current_output_dir, options.ave2D),
km,
)
km += 1
else:
nl = mpi.mpi_recv(
1,
mpi.MPI_INT,
i,
sp_global_def.SPARX_MPI_TAG_UNIVERSAL,
mpi.MPI_COMM_WORLD,
)
nl = int(nl[0])
for im in range(nl):
ave = sp_utilities.recv_EMData(
i, im + i + 70000)
"""Multiline Comment3"""
tmpvol = sp_fundamentals.fpol(ave, nx, nx, 1)
tmpvol.write_image(
optparse.os.path.join(
current_output_dir, options.ave2D),
km,
)
km += 1
else:
mpi.mpi_send(
len(aveList),
1,
mpi.MPI_INT,
main_node,
sp_global_def.SPARX_MPI_TAG_UNIVERSAL,
mpi.MPI_COMM_WORLD,
)
for im in range(len(aveList)):
sp_utilities.send_EMData(aveList[im], main_node,
im + myid + 70000)
"""Multiline Comment4"""
if myid == main_node:
sp_applications.header(
optparse.os.path.join(current_output_dir,
options.ave2D),
params="xform.projection",
fimport=optparse.os.path.join(current_output_dir,
"params.txt"),
)
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if options.ave3D:
t5 = time.time()
if myid == main_node:
log_main.add("Reconstruct ave3D ... ")
ave3D = sp_reconstruction.recons3d_4nn_MPI(
myid, aveList, symmetry=options.sym, npad=options.npad)
sp_utilities.bcast_EMData_to_all(ave3D, myid)
if myid == main_node:
if current_decimate != 1.0:
ave3D = sp_fundamentals.resample(
ave3D, old_div(1.0, current_decimate))
ave3D = sp_fundamentals.fpol(
ave3D, nnxo, nnxo,
nnxo) # always to the orignal image size
sp_utilities.set_pixel_size(ave3D, 1.0)
ave3D.write_image(
optparse.os.path.join(current_output_dir,
options.ave3D))
log_main.add("Ave3D reconstruction took %12.1f [m]" %
(old_div((time.time() - t5), 60.0)))
log_main.add("%-70s: %s\n" %
("The reconstructed ave3D is saved as ",
options.ave3D))
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
del ave, var, proj_list, stack, alpha, sx, sy, mirror, aveList
"""Multiline Comment5"""
if options.ave3D:
del ave3D
if options.var2D:
if myid == main_node:
log_main.add("Compute var2D...")
km = 0
for i in range(number_of_proc):
if i == main_node:
for im in range(len(varList)):
tmpvol = sp_fundamentals.fpol(
varList[im], nx, nx, 1)
tmpvol.write_image(
optparse.os.path.join(
current_output_dir, options.var2D),
km,
)
km += 1
else:
nl = mpi.mpi_recv(
1,
mpi.MPI_INT,
i,
sp_global_def.SPARX_MPI_TAG_UNIVERSAL,
mpi.MPI_COMM_WORLD,
)
nl = int(nl[0])
for im in range(nl):
ave = sp_utilities.recv_EMData(
i, im + i + 70000)
tmpvol = sp_fundamentals.fpol(ave, nx, nx, 1)
tmpvol.write_image(
optparse.os.path.join(
current_output_dir, options.var2D),
km,
)
km += 1
else:
mpi.mpi_send(
len(varList),
1,
mpi.MPI_INT,
main_node,
sp_global_def.SPARX_MPI_TAG_UNIVERSAL,
mpi.MPI_COMM_WORLD,
)
for im in range(len(varList)):
sp_utilities.send_EMData(
varList[im], main_node,
im + myid + 70000) # What with the attributes??
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if myid == main_node:
sp_applications.header(
optparse.os.path.join(current_output_dir,
options.var2D),
params="xform.projection",
fimport=optparse.os.path.join(current_output_dir,
"params.txt"),
)
mpi.mpi_barrier(mpi.MPI_COMM_WORLD)
if options.var3D:
if myid == main_node:
log_main.add("Reconstruct var3D ...")
t6 = time.time()
# radiusvar = options.radius
# if( radiusvar < 0 ): radiusvar = nx//2 -3
res = sp_reconstruction.recons3d_4nn_MPI(myid,
varList,
symmetry=options.sym,
npad=options.npad)
# res = recons3d_em_MPI(varList, vol_stack, options.iter, radiusvar, options.abs, True, options.sym, options.squ)
if myid == main_node:
if current_decimate != 1.0:
res = sp_fundamentals.resample(
res, old_div(1.0, current_decimate))
res = sp_fundamentals.fpol(res, nnxo, nnxo, nnxo)
sp_utilities.set_pixel_size(res, 1.0)
res.write_image(os.path.join(current_output_dir,
options.var3D))
log_main.add(
"%-70s: %s\n" %
("The reconstructed var3D is saved as ", options.var3D))
log_main.add("Var3D reconstruction took %f12.1 [m]" % (old_div(
(time.time() - t6), 60.0)))
log_main.add("Total computation time %f12.1 [m]" % (old_div(
(time.time() - t0), 60.0)))
log_main.add("sx3dvariability finishes")
if RUNNING_UNDER_MPI:
sp_global_def.MPI = False
sp_global_def.BATCH = False
def separate_class(classavgstack, instack, options, outdir='.', verbose=False):
"""
Main function overseeing various projection-comparison modes.
Arguments:
classavgstack : Input image stack
classmap : Class-to-particle lookup table. Each (long) line contains particles assigned to a class, one file for all classes
options : (list) Command-line options, run 'sxproj_compare.py -h' for an exhaustive list
outdir : Output directory
verbose : (boolean) Whether to write additional information to screen
"""
# Set output directory and log file name
prepare_outdir(outdir, verbose)
write_command(outdir)
log, verbose = prepare_log(outdir, verbose)
prepare_outdir(os.path.join(outdir, DOCFILEDIR))
# Set filename for copy of input BDB
bdb_path = os.path.join(outdir, 'EMAN2DB', BIGSTACKCOPY + '.bdb')
if os.path.exists(bdb_path):
os.remove(bdb_path) # will otherwise merge with pre-existing file
stackcp = 'bdb:' + outdir + '#' + BIGSTACKCOPY
# Expand paths for outputs
classmap = os.path.join(outdir, DOCFILEDIR, CLASSMAPFILE)
classdoc_template = os.path.join(outdir, DOCFILEDIR,
CLASSDOCPREFIX + '{0:03d}.txt')
class_init_bdb_template = os.path.join(outdir, CLASSORIGPREFIX + '{0:03d}')
class_filt_bdb_template = os.path.join(outdir,
CLASSFINALPREFIX + '{0:03d}')
if options.align_isac_dir or options.filtrad or options.shrink:
prepare_outdir(os.path.join(outdir, STACKFILEDIR))
outali = os.path.join(outdir, STACKFILEDIR,
ALIGNSTACKPREFIX + '{0:03d}' + options.format)
outflt = os.path.join(outdir, STACKFILEDIR,
FILTSTACKPREFIX + '{0:03d}' + options.format)
if options.align_isac_dir:
chains_params = os.path.join(options.align_isac_dir,
'chains_params.txt')
classed_imgs = os.path.join(options.align_isac_dir,
'processed_images.txt')
num_classes = EMUtil.get_image_count(classavgstack)
# Generate class-to-particle lookup table and class-selection lists
vomq(classavgstack, classmap, classdoc_template, log=log, verbose=verbose)
if options.filtrad:
if options.apix:
filtrad = options.apix / options.filtrad
else:
filtrad = options.filtrad
print_log_msg("Will low-pass filter to %s px^-1" % options.filtrad,
log, verbose)
if options.shrink:
print_log_msg(
"Will downsample stacks by a factor of %s" % options.shrink, log,
verbose)
if options.nvec != None and options.align_isac_dir == None:
sp_global_def.ERROR(
"\nERROR!! To compute eigenimages, need to specify --align_isac_dir",
__file__, 1)
exit()
if options.nvec:
print_log_msg('Writing %s eigenimages per class' % options.nvec, log,
verbose)
tot_parts = 0
if options.align_isac_dir:
if options.debug:
num_tot_images = EMUtil.get_image_count(instack)
print('num_tot_images', num_tot_images)
if os.path.basename(
classavgstack
) == 'ordered_class_averages.hdf' and os.path.exists(chains_params):
# Make substack with processed images
print_log_msg(
"Making substack %s from original stack %s using subset in %s"
% (stackcp, instack, classed_imgs), log, verbose)
cmd = "e2bdb.py %s --makevstack %s --list %s" % (instack, stackcp,
classed_imgs)
else:
# Simply copy image stack
print_log_msg(
"Copying %s to virtual stack %s" % (instack, stackcp), log,
verbose)
cmd = "e2bdb.py %s --makevstack %s" % (instack, stackcp)
print_log_msg(cmd, log, verbose)
os.system(cmd)
# Combine alignment parameters
combined_params_file = os.path.join(outdir, COMBINEDPARAMS)
combine_isac_params(options.align_isac_dir, classavgstack,
chains_params, classed_imgs, classdoc_template,
combined_params_file, log, verbose)
# Import alignment parameters
cmd = "sp_header.py %s --params=xform.align2d --import=%s\n" % (
stackcp, combined_params_file)
print_log_msg(cmd, log, verbose)
header(stackcp, 'xform.align2d', fimport=combined_params_file)
if options.debug:
test_params_file = os.path.join(outdir, TESTPARAMSOUT)
print_log_msg("Writing imported parameters to %s" %
test_params_file)
header(stackcp, 'xform.align2d', fexport=test_params_file)
stack2split = stackcp
# If not aligning images
else:
stack2split = instack
print_log_msg("Writing %s class stacks" % num_classes, log, verbose)
if options.align_isac_dir:
print_log_msg('Writing aligned images', log, verbose)
# Loop through classes
for class_num in xrange(num_classes):
# No aligned images
if not options.align_isac_dir:
# Write class stack
cmd = "e2bdb.py %s --makevstack bdb:%s --list %s" % (
stack2split, class_init_bdb_template.format(class_num),
classdoc_template.format(class_num))
print_log_msg(cmd, log, verbose)
os.system(cmd)
num_class_imgs = EMUtil.get_image_count(
'bdb:' + class_init_bdb_template.format(class_num))
tot_parts += num_class_imgs
# Optional filtered stack
if options.filtrad or options.shrink:
cmd = "e2proc2d.py bdb:%s %s --inplace" % (
class_init_bdb_template.format(class_num),
outflt.format(class_num))
# --inplace overwrites existing images
if options.filtrad:
cmd = cmd + " --process=filter.lowpass.gauss:cutoff_freq=%s" % filtrad
if options.shrink:
cmd = cmd + " --meanshrink=%s" % options.shrink
print_log_msg(cmd, log, verbose)
os.system(cmd)
# Optionally apply alignment
else:
# Write class stack
class_init_bdb_name = 'bdb:' + class_init_bdb_template.format(
class_num)
cmd = "e2bdb.py %s --makevstack %s --list %s" % (
stack2split, class_init_bdb_name,
classdoc_template.format(class_num))
print_log_msg(cmd, log, verbose)
os.system(cmd)
# Set filenames
aligned_stack_path = outali.format(class_num)
class_filt_bdb_name = 'bdb:' + class_filt_bdb_template.format(
class_num)
# PCA works better if application of alignment parameters is done internally.
# So, alignment will be applied afterward.
if options.debug and class_num == 0:
verbosity = True
else:
verbosity = False
if options.nvec != None:
num_class_imgs = filter_shrink(class_init_bdb_name,
aligned_stack_path,
class_filt_bdb_name,
alignYN=False,
filtrad=filtrad,
shrink=options.shrink,
verbose=verbosity)
tmp_classavg, class_stack_list = prepare_2d_forPCA(
class_filt_bdb_name, mode='a', CTF=False)
eig_list = pca(class_stack_list, nvec=options.nvec)
montage_file = os.path.join(outdir, 'stkeigen.hdf')
avg_img, var_img = ave_var(
class_filt_bdb_name
) # needs to be a BDB, aligned_stack_obj didn't work
# Not computing eigenimages
else:
eig_list = []
montage_file = os.path.join(outdir, 'stkavgvar.hdf')
avg_img, var_img = ave_var(
class_init_bdb_name
) # needs to be a BDB, aligned_stack_obj didn't work
montage_list = [avg_img] + [var_img] + eig_list
montage_row = montage_scale(montage_list, scale=True)
montage_row.write_image(montage_file, class_num)
# Apply alignments
num_class_imgs = filter_shrink(class_init_bdb_name,
aligned_stack_path,
class_filt_bdb_name,
alignYN=True,
filtrad=filtrad,
shrink=options.shrink,
verbose=verbosity)
tot_parts += num_class_imgs
print_log_msg("Done! Separated %s particles from %s classes\n" %
(tot_parts, num_classes), log, verbose) #=True)