def do_volume_mrk02(ref_data): """ data - projections (scattered between cpus) or the volume. If volume, just do the volume processing options - the same for all cpus return - volume the same for all cpus """ from EMAN2 import Util from mpi import mpi_comm_rank, mpi_comm_size, MPI_COMM_WORLD from filter import filt_table from reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI from utilities import bcast_EMData_to_all, bcast_number_to_all, model_blank from fundamentals import rops_table, fftip, fft import types # Retrieve the function specific input arguments from ref_data data = ref_data[0] Tracker = ref_data[1] iter = ref_data[2] mpi_comm = ref_data[3] # # For DEBUG # print "Type of data %s" % (type(data)) # print "Type of Tracker %s" % (type(Tracker)) # print "Type of iter %s" % (type(iter)) # print "Type of mpi_comm %s" % (type(mpi_comm)) if(mpi_comm == None): mpi_comm = MPI_COMM_WORLD myid = mpi_comm_rank(mpi_comm) nproc = mpi_comm_size(mpi_comm) try: local_filter = Tracker["local_filter"] except: local_filter = False #========================================================================= # volume reconstruction if( type(data) == types.ListType ): if Tracker["constants"]["CTF"]: vol = recons3d_4nn_ctf_MPI(myid, data, Tracker["constants"]["snr"], \ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm, smearstep = Tracker["smearstep"]) else: vol = recons3d_4nn_MPI (myid, data,\ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm) else: vol = data if myid == 0: from morphology import threshold from filter import filt_tanl, filt_btwl from utilities import model_circle, get_im import types nx = vol.get_xsize() if(Tracker["constants"]["mask3D"] == None): mask3D = model_circle(int(Tracker["constants"]["radius"]*float(nx)/float(Tracker["constants"]["nnxo"])+0.5), nx, nx, nx) elif(Tracker["constants"]["mask3D"] == "auto"): from utilities import adaptive_mask mask3D = adaptive_mask(vol) else: if( type(Tracker["constants"]["mask3D"]) == types.StringType ): mask3D = get_im(Tracker["constants"]["mask3D"]) else: mask3D = (Tracker["constants"]["mask3D"]).copy() nxm = mask3D.get_xsize() if( nx != nxm): from fundamentals import rot_shift3D mask3D = Util.window(rot_shift3D(mask3D,scale=float(nx)/float(nxm)),nx,nx,nx) nxm = mask3D.get_xsize() assert(nx == nxm) stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) vol = threshold(vol) Util.mul_img(vol, mask3D) if( Tracker["PWadjustment"] ): from utilities import read_text_file, write_text_file rt = read_text_file( Tracker["PWadjustment"] ) fftip(vol) ro = rops_table(vol) # Here unless I am mistaken it is enough to take the beginning of the reference pw. for i in xrange(1,len(ro)): ro[i] = (rt[i]/ro[i])**Tracker["upscale"] #write_text_file(rops_table(filt_table( vol, ro),1),"foo.txt") if Tracker["constants"]["sausage"]: ny = vol.get_ysize() y = float(ny) from math import exp for i in xrange(len(ro)): ro[i] *= \ (1.0+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.10)/0.025)**2)+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.215)/0.025)**2)) if local_filter: # skip low-pass filtration vol = fft( filt_table( vol, ro) ) else: if( type(Tracker["lowpass"]) == types.ListType ): vol = fft( filt_table( filt_table(vol, Tracker["lowpass"]), ro) ) else: vol = fft( filt_table( filt_tanl(vol, Tracker["lowpass"], Tracker["falloff"]), ro) ) del ro else: if Tracker["constants"]["sausage"]: ny = vol.get_ysize() y = float(ny) ro = [0.0]*(ny//2+2) from math import exp for i in xrange(len(ro)): ro[i] = \ (1.0+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.10)/0.025)**2)+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.215)/0.025)**2)) fftip(vol) filt_table(vol, ro) del ro if not local_filter: if( type(Tracker["lowpass"]) == types.ListType ): vol = filt_table(vol, Tracker["lowpass"]) else: vol = filt_tanl(vol, Tracker["lowpass"], Tracker["falloff"]) if Tracker["constants"]["sausage"]: vol = fft(vol) if local_filter: from morphology import binarize if(myid == 0): nx = mask3D.get_xsize() else: nx = 0 nx = bcast_number_to_all(nx, source_node = 0) # only main processor needs the two input volumes if(myid == 0): mask = binarize(mask3D, 0.5) locres = get_im(Tracker["local_filter"]) lx = locres.get_xsize() if(lx != nx): if(lx < nx): from fundamentals import fdecimate, rot_shift3D mask = Util.window(rot_shift3D(mask,scale=float(lx)/float(nx)),lx,lx,lx) vol = fdecimate(vol, lx,lx,lx) else: ERROR("local filter cannot be larger than input volume","user function",1) stat = Util.infomask(vol, mask, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) else: lx = 0 locres = model_blank(1,1,1) vol = model_blank(1,1,1) lx = bcast_number_to_all(lx, source_node = 0) if( myid != 0 ): mask = model_blank(lx,lx,lx) bcast_EMData_to_all(mask, myid, 0, comm=mpi_comm) from filter import filterlocal vol = filterlocal( locres, vol, mask, Tracker["falloff"], myid, 0, nproc) if myid == 0: if(lx < nx): from fundamentals import fpol vol = fpol(vol, nx,nx,nx) vol = threshold(vol) vol = filt_btwl(vol, 0.38, 0.5)# This will have to be corrected. Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) else: vol = model_blank(nx,nx,nx) else: if myid == 0: #from utilities import write_text_file #write_text_file(rops_table(vol,1),"goo.txt") stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) vol = threshold(vol) vol = filt_btwl(vol, 0.38, 0.5)# This will have to be corrected. Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) # broadcast volume bcast_EMData_to_all(vol, myid, 0, comm=mpi_comm) #========================================================================= return vol
def compute_padding_average(map, mask): volume_stats_outside_mask = Util.infomask(map, mask, False) average_padding_intensity = volume_stats_outside_mask[0] return average_padding_intensity
def do_volume_mrk03(ref_data): """ data - projections (scattered between cpus) or the volume. If volume, just do the volume processing options - the same for all cpus return - volume the same for all cpus """ from EMAN2 import Util from mpi import mpi_comm_rank, mpi_comm_size, MPI_COMM_WORLD from filter import filt_table from reconstruction import recons3d_4nn_MPI, recons3d_4nnw_MPI # recons3d_4nn_ctf_MPI from utilities import bcast_EMData_to_all, bcast_number_to_all, model_blank from fundamentals import rops_table, fftip, fft import types # Retrieve the function specific input arguments from ref_data data = ref_data[0] Tracker = ref_data[1] iter = ref_data[2] mpi_comm = ref_data[3] # # For DEBUG # print "Type of data %s" % (type(data)) # print "Type of Tracker %s" % (type(Tracker)) # print "Type of iter %s" % (type(iter)) # print "Type of mpi_comm %s" % (type(mpi_comm)) if(mpi_comm == None): mpi_comm = MPI_COMM_WORLD myid = mpi_comm_rank(mpi_comm) nproc = mpi_comm_size(mpi_comm) try: local_filter = Tracker["local_filter"] except: local_filter = False #========================================================================= # volume reconstruction if( type(data) == types.ListType ): if Tracker["constants"]["CTF"]: #vol = recons3d_4nn_ctf_MPI(myid, data, Tracker["constants"]["snr"], \ # symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm, smearstep = Tracker["smearstep"]) vol = recons3d_4nnw_MPI(myid, data, Tracker["bckgnoise"], Tracker["constants"]["snr"], \ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm, smearstep = Tracker["smearstep"]) else: vol = recons3d_4nn_MPI (myid, data,\ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm) else: vol = data if myid == 0: from morphology import threshold from filter import filt_tanl, filt_btwl from utilities import model_circle, get_im import types nx = vol.get_xsize() if(Tracker["constants"]["mask3D"] == None): mask3D = model_circle(int(Tracker["constants"]["radius"]*float(nx)/float(Tracker["constants"]["nnxo"])+0.5), nx, nx, nx) elif(Tracker["constants"]["mask3D"] == "auto"): from utilities import adaptive_mask mask3D = adaptive_mask(vol) else: if( type(Tracker["constants"]["mask3D"]) == types.StringType ): mask3D = get_im(Tracker["constants"]["mask3D"]) else: mask3D = (Tracker["constants"]["mask3D"]).copy() nxm = mask3D.get_xsize() if( nx != nxm): from fundamentals import rot_shift3D mask3D = Util.window(rot_shift3D(mask3D,scale=float(nx)/float(nxm)),nx,nx,nx) nxm = mask3D.get_xsize() assert(nx == nxm) stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) vol = threshold(vol) Util.mul_img(vol, mask3D) if not local_filter: if( type(Tracker["lowpass"]) == types.ListType ): vol = filt_table(vol, Tracker["lowpass"]) else: vol = filt_tanl(vol, Tracker["lowpass"], Tracker["falloff"]) if local_filter: from morphology import binarize if(myid == 0): nx = mask3D.get_xsize() else: nx = 0 nx = bcast_number_to_all(nx, source_node = 0) # only main processor needs the two input volumes if(myid == 0): mask = binarize(mask3D, 0.5) locres = get_im(Tracker["local_filter"]) lx = locres.get_xsize() if(lx != nx): if(lx < nx): from fundamentals import fdecimate, rot_shift3D mask = Util.window(rot_shift3D(mask,scale=float(lx)/float(nx)),lx,lx,lx) vol = fdecimate(vol, lx,lx,lx) else: ERROR("local filter cannot be larger than input volume","user function",1) stat = Util.infomask(vol, mask, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) else: lx = 0 locres = model_blank(1,1,1) vol = model_blank(1,1,1) lx = bcast_number_to_all(lx, source_node = 0) if( myid != 0 ): mask = model_blank(lx,lx,lx) bcast_EMData_to_all(mask, myid, 0, comm=mpi_comm) from filter import filterlocal vol = filterlocal( locres, vol, mask, Tracker["falloff"], myid, 0, nproc) if myid == 0: if(lx < nx): from fundamentals import fpol vol = fpol(vol, nx,nx,nx) vol = threshold(vol) Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) else: vol = model_blank(nx,nx,nx) """ else: if myid == 0: #from utilities import write_text_file #write_text_file(rops_table(vol,1),"goo.txt") stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0/stat[1]) vol = threshold(vol) Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) """ # broadcast volume bcast_EMData_to_all(vol, myid, 0, comm=mpi_comm) #========================================================================= return vol
def do_volume_mrk02(ref_data): """ data - projections (scattered between cpus) or the volume. If volume, just do the volume processing options - the same for all cpus return - volume the same for all cpus """ from EMAN2 import Util from mpi import mpi_comm_rank, mpi_comm_size, MPI_COMM_WORLD from filter import filt_table from reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI from utilities import bcast_EMData_to_all, bcast_number_to_all, model_blank from fundamentals import rops_table, fftip, fft import types # Retrieve the function specific input arguments from ref_data data = ref_data[0] Tracker = ref_data[1] iter = ref_data[2] mpi_comm = ref_data[3] # # For DEBUG # print "Type of data %s" % (type(data)) # print "Type of Tracker %s" % (type(Tracker)) # print "Type of iter %s" % (type(iter)) # print "Type of mpi_comm %s" % (type(mpi_comm)) if (mpi_comm == None): mpi_comm = MPI_COMM_WORLD myid = mpi_comm_rank(mpi_comm) nproc = mpi_comm_size(mpi_comm) try: local_filter = Tracker["local_filter"] except: local_filter = False #========================================================================= # volume reconstruction if (type(data) == types.ListType): if Tracker["constants"]["CTF"]: vol = recons3d_4nn_ctf_MPI(myid, data, Tracker["constants"]["snr"], \ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm, smearstep = Tracker["smearstep"]) else: vol = recons3d_4nn_MPI (myid, data,\ symmetry=Tracker["constants"]["sym"], npad=Tracker["constants"]["npad"], mpi_comm=mpi_comm) else: vol = data if myid == 0: from morphology import threshold from filter import filt_tanl, filt_btwl from utilities import model_circle, get_im import types nx = vol.get_xsize() if (Tracker["constants"]["mask3D"] == None): mask3D = model_circle( int(Tracker["constants"]["radius"] * float(nx) / float(Tracker["constants"]["nnxo"]) + 0.5), nx, nx, nx) elif (Tracker["constants"]["mask3D"] == "auto"): from utilities import adaptive_mask mask3D = adaptive_mask(vol) else: if (type(Tracker["constants"]["mask3D"]) == types.StringType): mask3D = get_im(Tracker["constants"]["mask3D"]) else: mask3D = (Tracker["constants"]["mask3D"]).copy() nxm = mask3D.get_xsize() if (nx != nxm): from fundamentals import rot_shift3D mask3D = Util.window( rot_shift3D(mask3D, scale=float(nx) / float(nxm)), nx, nx, nx) nxm = mask3D.get_xsize() assert (nx == nxm) stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0 / stat[1]) vol = threshold(vol) Util.mul_img(vol, mask3D) if (Tracker["PWadjustment"]): from utilities import read_text_file, write_text_file rt = read_text_file(Tracker["PWadjustment"]) fftip(vol) ro = rops_table(vol) # Here unless I am mistaken it is enough to take the beginning of the reference pw. for i in xrange(1, len(ro)): ro[i] = (rt[i] / ro[i])**Tracker["upscale"] #write_text_file(rops_table(filt_table( vol, ro),1),"foo.txt") if Tracker["constants"]["sausage"]: ny = vol.get_ysize() y = float(ny) from math import exp for i in xrange(len(ro)): ro[i] *= \ (1.0+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.10)/0.025)**2)+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.215)/0.025)**2)) if local_filter: # skip low-pass filtration vol = fft(filt_table(vol, ro)) else: if (type(Tracker["lowpass"]) == types.ListType): vol = fft( filt_table(filt_table(vol, Tracker["lowpass"]), ro)) else: vol = fft( filt_table( filt_tanl(vol, Tracker["lowpass"], Tracker["falloff"]), ro)) del ro else: if Tracker["constants"]["sausage"]: ny = vol.get_ysize() y = float(ny) ro = [0.0] * (ny // 2 + 2) from math import exp for i in xrange(len(ro)): ro[i] = \ (1.0+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.10)/0.025)**2)+1.0*exp(-(((i/y/Tracker["constants"]["pixel_size"])-0.215)/0.025)**2)) fftip(vol) filt_table(vol, ro) del ro if not local_filter: if (type(Tracker["lowpass"]) == types.ListType): vol = filt_table(vol, Tracker["lowpass"]) else: vol = filt_tanl(vol, Tracker["lowpass"], Tracker["falloff"]) if Tracker["constants"]["sausage"]: vol = fft(vol) if local_filter: from morphology import binarize if (myid == 0): nx = mask3D.get_xsize() else: nx = 0 nx = bcast_number_to_all(nx, source_node=0) # only main processor needs the two input volumes if (myid == 0): mask = binarize(mask3D, 0.5) locres = get_im(Tracker["local_filter"]) lx = locres.get_xsize() if (lx != nx): if (lx < nx): from fundamentals import fdecimate, rot_shift3D mask = Util.window( rot_shift3D(mask, scale=float(lx) / float(nx)), lx, lx, lx) vol = fdecimate(vol, lx, lx, lx) else: ERROR("local filter cannot be larger than input volume", "user function", 1) stat = Util.infomask(vol, mask, False) vol -= stat[0] Util.mul_scalar(vol, 1.0 / stat[1]) else: lx = 0 locres = model_blank(1, 1, 1) vol = model_blank(1, 1, 1) lx = bcast_number_to_all(lx, source_node=0) if (myid != 0): mask = model_blank(lx, lx, lx) bcast_EMData_to_all(mask, myid, 0, comm=mpi_comm) from filter import filterlocal vol = filterlocal(locres, vol, mask, Tracker["falloff"], myid, 0, nproc) if myid == 0: if (lx < nx): from fundamentals import fpol vol = fpol(vol, nx, nx, nx) vol = threshold(vol) vol = filt_btwl(vol, 0.38, 0.5) # This will have to be corrected. Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) else: vol = model_blank(nx, nx, nx) else: if myid == 0: #from utilities import write_text_file #write_text_file(rops_table(vol,1),"goo.txt") stat = Util.infomask(vol, mask3D, False) vol -= stat[0] Util.mul_scalar(vol, 1.0 / stat[1]) vol = threshold(vol) vol = filt_btwl(vol, 0.38, 0.5) # This will have to be corrected. Util.mul_img(vol, mask3D) del mask3D # vol.write_image('toto%03d.hdf'%iter) # broadcast volume bcast_EMData_to_all(vol, myid, 0, comm=mpi_comm) #========================================================================= return vol