def main(): progname = os.path.basename(sys.argv[0]) usage = progname + " input_stack output_stack average --avg --CTF" parser = OptionParser(usage, version=SPARXVERSION) parser.add_option( "--avg", action="store_true", default=True, help= " Subtract averages computed within corners of individual images, default False" ) parser.add_option( "--CTF", action="store_true", default=False, help=" Consider CTF correction during the alignment, dafault False") (options, args) = parser.parse_args() if len(args) != 3: print("usage: " + usage) print("Please run '" + progname + " -h' for detailed options") else: if global_def.CACHE_DISABLE: from utilities import disable_bdb_cache disable_bdb_cache() from applications import prepare_2d_forPCA global_def.BATCH = True prepare_2d_forPCA(args[0], args[1], args[2], options.avg, options.CTF) global_def.BATCH = False
def main(): progname = os.path.basename(sys.argv[0]) usage = progname + " input_stack output_stack average --avg --CTF" parser = OptionParser(usage,version=SPARXVERSION) parser.add_option("--avg", action="store_true", default=True, help=" Subtract averages computed within corners of individual images, default False") parser.add_option("--CTF", action="store_true", default=False, help=" Consider CTF correction during the alignment, dafault False") (options, args) = parser.parse_args() if len(args) != 3: print "usage: " + usage print "Please run '" + progname + " -h' for detailed options" else: if global_def.CACHE_DISABLE: from utilities import disable_bdb_cache disable_bdb_cache() from applications import prepare_2d_forPCA global_def.BATCH = True prepare_2d_forPCA(args[0], args[1], args[2], options.avg, options.CTF) global_def.BATCH = False
def main(): def params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror): 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=15. --aa=0.01 --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=10, help="number of neighbouring projections") parser.add_option("--no_norm", action="store_true", default=False, help="do not use 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") parser.add_option("--sym", type="string", default="c1", help="symmetry") parser.add_option( "--fl", type="float", default=0.0, help= "cutoff freqency in absolute frequency (0.0-0.5). (Default - no filtration)" ) parser.add_option( "--aa", type="float", default=0.0, help= "fall off of the filter. Put 0.01 if user has no clue about falloff (Default - no filtration)" ) parser.add_option("--CTF", action="store_true", default=False, help="use CFT correction") parser.add_option("--VERBOSE", action="store_true", default=False, help="Long output for debugging") #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 on input consists of 2D variances (Default False)") parser.add_option( "--decimate", type="float", default=1.0, help= "image decimate rate, a number larger (expand image) or less (shrink image) than 1. default is 1" ) parser.add_option( "--window", type="int", default=0, help= "reduce images to a small image size without changing pixel_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)") (options, args) = parser.parse_args() ##### from mpi import mpi_init, 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 applications import MPI_start_end from reconstruction import recons3d_em, recons3d_em_MPI from reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI from utilities import print_begin_msg, print_end_msg, print_msg from utilities import read_text_row, get_image, get_im from utilities import bcast_EMData_to_all, bcast_number_to_all from 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 global_def.CACHE_DISABLE: from utilities import disable_bdb_cache disable_bdb_cache() # Set up global variables related to ERROR function 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: global_def.MPI = True if options.symmetrize: if RUNNING_UNDER_MPI: try: sys.argv = mpi_init(len(sys.argv), sys.argv) try: number_of_proc = mpi_comm_size(MPI_COMM_WORLD) if (number_of_proc > 1): ERROR( "Cannot use more than one CPU for symmetry prepration", "sx3dvariability", 1) except: pass except: pass if options.output_dir != "./" and not os.path.exists( options.output_dir): os.mkdir(options.output_dir) # Input #instack = "Clean_NORM_CTF_start_wparams.hdf" #instack = "bdb:data" from 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(options.output_dir, "./") instack = args[0] sym = options.sym.lower() if (sym == "c1"): ERROR("There is no need to symmetrize stack for C1 symmetry", "sx3dvariability", 1) line = "" for a in sys.argv: line += " " + a log_main.add(line) if (instack[:4] != "bdb:"): if output_dir == "./": stack = "bdb:data" else: stack = "bdb:" + options.output_dir + "/data" delete_bdb(stack) junk = cmdexecute("sxcpy.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 xrange(ks): #Qfile = "Q%1d"%k if options.output_dir != "./": Qfile = os.path.join(options.output_dir, "Q%1d" % k) else: Qfile = os.path.join(options.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 xrange(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") else: delete_bdb("bdb:" + options.output_dir + "/" + "sdata") #junk = cmdexecute("e2bdb.py . --makevstack=bdb:sdata --filt=Q") sdata = "bdb:" + options.output_dir + "/" + "sdata" print(sdata) junk = cmdexecute("e2bdb.py " + options.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: sys.argv = mpi_init(len(sys.argv), sys.argv) myid = mpi_comm_rank(MPI_COMM_WORLD) number_of_proc = mpi_comm_size(MPI_COMM_WORLD) main_node = 0 if len(args) == 1: stack = args[0] else: print(("usage: " + usage)) print(("Please run '" + progname + " -h' for detailed options")) return 1 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", "sx3dvariability", 1, myid) if options.VAR and options.SND: ERROR("Only one of var and SND can be set!", "sx3dvariability", myid) exit() 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", "sx3dvariability", 1, myid) exit() #if options.SND and (options.ave2D or options.ave3D): # ERROR("When SND is set, the program cannot output ave2D or ave3D", "sx3dvariability", 1, myid) # exit() if options.nvec > 0: ERROR("PCA option not implemented", "sx3dvariability", 1, myid) exit() if options.nvec > 0 and options.ave3D == None: ERROR("When doing PCA analysis, one must set ave3D", "sx3dvariability", myid=myid) exit() 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 options.output_dir != "./" and not os.path.exists( options.output_dir): os.mkdir(options.output_dir) img_per_grp = options.img_per_grp nvec = options.nvec radiuspca = options.radiuspca from 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(options.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("instack :" + stack) log_main.add("output_dir :" + options.output_dir) log_main.add("var3d :" + options.var3D) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" #print_begin_msg("sx3dvariability") msg = "sx3dvariability" log_main.add(msg) print(line, msg) msg = ("%-70s: %s\n" % ("Input stack", stack)) log_main.add(msg) print(line, msg) symbaselen = 0 if myid == main_node: nima = EMUtil.get_image_count(stack) img = get_image(stack) nx = img.get_xsize() ny = img.get_ysize() 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", "sx3dvariability", myid=myid) except: ERROR( "Input stack is not prepared for symmetry, please follow instructions", "sx3dvariability", myid=myid) from 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", "sx3dvariability", myid=myid) symbaselen = nima / i else: symbaselen = nima else: nima = 0 nx = 0 ny = 0 nima = bcast_number_to_all(nima) nx = bcast_number_to_all(nx) ny = bcast_number_to_all(ny) Tracker = {} Tracker["total_stack"] = nima if options.decimate == 1.: if options.window != 0: nx = options.window ny = options.window else: if options.window == 0: nx = int(nx * options.decimate) ny = int(ny * options.decimate) else: nx = int(options.window * options.decimate) ny = nx Tracker["nx"] = nx Tracker["ny"] = ny Tracker["nz"] = nx symbaselen = bcast_number_to_all(symbaselen) if radiuspca == -1: radiuspca = nx / 2 - 2 if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = "%-70s: %d\n" % ("Number of projection", nima) log_main.add(msg) print(line, msg) img_begin, img_end = MPI_start_end(nima, number_of_proc, myid) """ if options.SND: from projection import prep_vol, prgs from statistics import im_diff from utilities import get_im, model_circle, get_params_proj, set_params_proj from utilities import get_ctf, generate_ctf from 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: #varList = EMData.read_images(stack, range(img_begin, img_end)) varList = [] this_image = EMData() for index_of_particle in xrange(img_begin, img_end): this_image.read_image(stack, index_of_particle) varList.append( image_decimate_window_xform_ctf(this_image, options.decimate, options.window, options.CTF)) else: from utilities import bcast_number_to_all, bcast_list_to_all, send_EMData, recv_EMData from utilities import set_params_proj, get_params_proj, params_3D_2D, get_params2D, set_params2D, compose_transform2 from utilities import model_blank, nearest_proj, model_circle from applications import pca from statistics import avgvar, avgvar_ctf, ccc from filter import filt_tanl from morphology import threshold, square_root from projection import project, prep_vol, prgs from sets import Set if myid == main_node: t1 = time() proj_angles = [] aveList = [] tab = EMUtil.get_all_attributes(stack, 'xform.projection') for i in xrange(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() line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = "%-70s: %d\n" % ("Number of neighboring projections", img_per_grp) log_main.add(msg) print(line, msg) msg = "...... Finding neighboring projections\n" log_main.add(msg) print(line, msg) if options.VERBOSE: msg = "Number of images per group: %d" % img_per_grp log_main.add(msg) print(line, msg) msg = "Now grouping projections" log_main.add(msg) print(line, msg) proj_angles.sort() proj_angles_list = [0.0] * (nima * 4) if myid == main_node: for i in xrange(nima): proj_angles_list[i * 4] = proj_angles[i][1] proj_angles_list[i * 4 + 1] = proj_angles[i][2] proj_angles_list[i * 4 + 2] = proj_angles[i][3] proj_angles_list[i * 4 + 3] = proj_angles[i][4] proj_angles_list = bcast_list_to_all(proj_angles_list, myid, main_node) proj_angles = [] for i in xrange(nima): proj_angles.append([ proj_angles_list[i * 4], proj_angles_list[i * 4 + 1], proj_angles_list[i * 4 + 2], int(proj_angles_list[i * 4 + 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) if options.VERBOSE: print("On node %2d, number of images needed to be read = %5d" % (myid, len(all_proj))) index = {} for i in xrange(len(all_proj)): index[all_proj[i]] = i mpi_barrier(MPI_COMM_WORLD) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("%-70s: %.2f\n" % ("Finding neighboring projections lasted [s]", time() - t2)) log_main.add(msg) print(msg) msg = ("%-70s: %d\n" % ("Number of groups processed on the main node", len(proj_list))) log_main.add(msg) print(line, msg) if options.VERBOSE: print("Grouping projections took: ", (time() - t2) / 60, "[min]") print("Number of groups on main node: ", len(proj_list)) mpi_barrier(MPI_COMM_WORLD) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("...... calculating the stack of 2D variances \n") log_main.add(msg) print(line, msg) if options.VERBOSE: print("Now calculating the stack of 2D variances") proj_params = [0.0] * (nima * 5) aveList = [] varList = [] if nvec > 0: eigList = [[] for i in xrange(nvec)] if options.VERBOSE: print("Begin to read images on processor %d" % (myid)) ttt = time() #imgdata = EMData.read_images(stack, all_proj) imgdata = [] for index_of_proj in xrange(len(all_proj)): #img = EMData() #img.read_image(stack, all_proj[index_of_proj]) dmg = image_decimate_window_xform_ctf( get_im(stack, all_proj[index_of_proj]), options.decimate, options.window, options.CTF) #print dmg.get_xsize(), "init" imgdata.append(dmg) if options.VERBOSE: print("Reading images on processor %d done, time = %.2f" % (myid, time() - ttt)) print("On processor %d, we got %d images" % (myid, len(imgdata))) mpi_barrier(MPI_COMM_WORLD) ''' 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 applications import prepare_2d_forPCA from utilities import model_blank for i in xrange(len(proj_list)): ki = proj_angles[proj_list[i][0]][3] if ki >= symbaselen: continue mi = index[ki] phiM, thetaM, psiM, s2xM, s2yM = get_params_proj(imgdata[mi]) grp_imgdata = [] for j in xrange(img_per_grp): mj = index[proj_angles[proj_list[i][j]][3]] phi, theta, psi, s2x, s2y = get_params_proj(imgdata[mj]) alpha, sx, sy, mirror = params_3D_2D_NEW( phi, theta, psi, s2x, s2y, mirror_list[i][j]) if thetaM <= 90: if mirror == 0: alpha, sx, sy, scale = compose_transform2( alpha, sx, sy, 1.0, phiM - phi, 0.0, 0.0, 1.0) else: alpha, sx, sy, scale = compose_transform2( alpha, sx, sy, 1.0, 180 - (phiM - phi), 0.0, 0.0, 1.0) else: if mirror == 0: alpha, sx, sy, scale = compose_transform2( alpha, sx, sy, 1.0, -(phiM - phi), 0.0, 0.0, 1.0) else: alpha, sx, sy, scale = compose_transform2( alpha, sx, sy, 1.0, -(180 - (phiM - phi)), 0.0, 0.0, 1.0) set_params2D(imgdata[mj], [alpha, sx, sy, mirror, 1.0]) grp_imgdata.append(imgdata[mj]) #print grp_imgdata[j].get_xsize(), imgdata[mj].get_xsize() if not options.no_norm: #print grp_imgdata[j].get_xsize() mask = model_circle(nx / 2 - 2, nx, nx) for k in xrange(img_per_grp): ave, std, minn, maxx = Util.infomask( grp_imgdata[k], mask, False) grp_imgdata[k] -= ave grp_imgdata[k] /= std del mask if options.fl > 0.0: from filter import filt_ctf, filt_table from fundamentals import fft, window2d nx2 = 2 * nx ny2 = 2 * ny if options.CTF: from utilities import pad for k in xrange(img_per_grp): grp_imgdata[k] = window2d( fft( filt_tanl( filt_ctf( fft( pad(grp_imgdata[k], nx2, ny2, 1, 0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa)), nx, ny) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) else: for k in xrange(img_per_grp): grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) else: from utilities import pad, read_text_file from filter import filt_ctf, filt_table from fundamentals import fft, window2d nx2 = 2 * nx ny2 = 2 * ny if options.CTF: from utilities import pad for k in xrange(img_per_grp): grp_imgdata[k] = window2d( fft( filt_ctf(fft( pad(grp_imgdata[k], nx2, ny2, 1, 0.0)), grp_imgdata[k].get_attr("ctf"), binary=1)), nx, ny) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) ''' if i < 10 and myid == main_node: for k in xrange(10): grp_imgdata[k].write_image("grp%03d.hdf"%i, k) ''' """ if myid == main_node and i==0: for pp in xrange(len(grp_imgdata)): grp_imgdata[pp].write_image("pp.hdf", pp) """ ave, grp_imgdata = prepare_2d_forPCA(grp_imgdata) """ if myid == main_node and i==0: for pp in xrange(len(grp_imgdata)): grp_imgdata[pp].write_image("qq.hdf", pp) """ var = model_blank(nx, ny) for q in grp_imgdata: Util.add_img2(var, q) Util.mul_scalar(var, 1.0 / (len(grp_imgdata) - 1)) # Switch to std dev var = square_root(threshold(var)) #if options.CTF: ave, var = avgvar_ctf(grp_imgdata, mode="a") #else: ave, var = avgvar(grp_imgdata, mode="a") """ if myid == main_node: ave.write_image("avgv.hdf",i) var.write_image("varv.hdf",i) """ 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) if options.VERBOSE: print("%5.2f%% done on processor %d" % (i * 100.0 / len(proj_list), myid)) if nvec > 0: eig = pca(input_stacks=grp_imgdata, subavg="", mask_radius=radiuspca, nvec=nvec, incore=True, shuffle=False, genbuf=True) for k in xrange(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) """ del imgdata # To this point, all averages, variances, and eigenvectors are computed if options.ave2D: from fundamentals import fpol if myid == main_node: km = 0 for i in xrange(number_of_proc): if i == main_node: for im in xrange(len(aveList)): aveList[im].write_image( os.path.join(options.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 xrange(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, Tracker["nx"], Tracker["nx"], 1) tmpvol.write_image( os.path.join(options.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 xrange(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 options.ave3D: from fundamentals import fpol if options.VERBOSE: print("Reconstructing 3D average volume") ave3D = recons3d_4nn_MPI(myid, aveList, symmetry=options.sym, npad=options.npad) bcast_EMData_to_all(ave3D, myid) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" ave3D = fpol(ave3D, Tracker["nx"], Tracker["nx"], Tracker["nx"]) ave3D.write_image( os.path.join(options.output_dir, options.ave3D)) msg = ("%-70s: %s\n" % ( "Writing to the disk volume reconstructed from averages as", options.ave3D)) log_main.add(msg) print(line, msg) del ave, var, proj_list, stack, phi, theta, psi, s2x, s2y, alpha, sx, sy, mirror, aveList if nvec > 0: for k in xrange(nvec): if options.VERBOSE: print("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 xrange(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: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" u = int(u[0]) msg = (" Eigenvector: ", k, " number changed ", int(icont[0])) log_main.add(msg) print(line, msg) 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 fundamentals import fpol if myid == main_node: km = 0 for i in xrange(number_of_proc): if i == main_node: for im in xrange(len(varList)): tmpvol = fpol(varList[im], Tracker["nx"], Tracker["nx"], 1) tmpvol.write_image( os.path.join(options.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 xrange(nl): ave = recv_EMData(i, im + i + 70000) tmpvol = fpol(ave, Tracker["nx"], Tracker["nx"], 1) tmpvol.write_image( os.path.join(options.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 xrange(len(varList)): send_EMData(varList[im], main_node, im + myid + 70000) # What with the attributes?? mpi_barrier(MPI_COMM_WORLD) if options.var3D: if myid == main_node and options.VERBOSE: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("Reconstructing 3D variability volume") log_main.add(msg) print(line, msg) 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 fundamentals import fpol res = fpol(res, Tracker["nx"], Tracker["nx"], Tracker["nx"]) res.write_image(os.path.join(options.output_dir, options.var3D)) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("%-70s: %.2f\n" % ("Reconstructing 3D variability took [s]", time() - t6)) log_main.add(msg) print(line, msg) if options.VERBOSE: print("Reconstruction took: %.2f [min]" % ((time() - t6) / 60)) if myid == main_node: line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("%-70s: %.2f\n" % ("Total time for these computations [s]", time() - t0)) print(line, msg) log_main.add(msg) if options.VERBOSE: print("Total time for these computations: %.2f [min]" % ((time() - t0) / 60)) line = strftime("%Y-%m-%d_%H:%M:%S", localtime()) + " =>" msg = ("sx3dvariability") print(line, msg) log_main.add(msg) from mpi import mpi_finalize mpi_finalize() if RUNNING_UNDER_MPI: global_def.MPI = False global_def.BATCH = False
def main(): def params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror): 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=0.2 --aa=0.1 --sym=symmetry --CTF" parser = OptionParser(usage, version=SPARXVERSION) 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=10 , help="number of neighbouring projections") parser.add_option("--no_norm", action="store_true", default=False, help="do not use normalization") parser.add_option("--radiusvar", type="int" , default=-1 , help="radius for 3D var" ) parser.add_option("--npad", type="int" , default=2 , help="number of time to pad the original images") parser.add_option("--sym" , type="string" , default="c1" , help="symmetry") parser.add_option("--fl", type="float" , default=0.0 , help="stop-band frequency (Default - no filtration)") parser.add_option("--aa", type="float" , default=0.0 , help="fall off of the filter (Default - no filtration)") parser.add_option("--CTF", action="store_true", default=False, help="use CFT correction") parser.add_option("--VERBOSE", action="store_true", default=False, help="Long output for debugging") #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 on input consists of 2D variances (Default False)") parser.add_option("--decimate", type="float", default=1.0, help="image decimate rate, a number large than 1. default is 1") parser.add_option("--window", type="int", default=0, help="reduce images to a small image size without changing pixel_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)") (options,args) = parser.parse_args() ##### from mpi import mpi_init, mpi_comm_rank, mpi_comm_size, mpi_recv, MPI_COMM_WORLD, MPI_TAG_UB from mpi import mpi_barrier, mpi_reduce, mpi_bcast, mpi_send, MPI_FLOAT, MPI_SUM, MPI_INT, MPI_MAX from applications import MPI_start_end from reconstruction import recons3d_em, recons3d_em_MPI from reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI from utilities import print_begin_msg, print_end_msg, print_msg from utilities import read_text_row, get_image, get_im from utilities import bcast_EMData_to_all, bcast_number_to_all from 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 if options.symmetrize : try: sys.argv = mpi_init(len(sys.argv), sys.argv) try: number_of_proc = mpi_comm_size(MPI_COMM_WORLD) if( number_of_proc > 1 ): ERROR("Cannot use more than one CPU for symmetry prepration","sx3dvariability",1) except: pass except: pass # Input #instack = "Clean_NORM_CTF_start_wparams.hdf" #instack = "bdb:data" instack = args[0] sym = options.sym if( sym == "c1" ): ERROR("Thre is no need to symmetrize stack for C1 symmetry","sx3dvariability",1) if(instack[:4] !="bdb:"): stack = "bdb:data" delete_bdb(stack) cmdexecute("sxcpy.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 xrange(ks): delete_bdb("bdb:Q%1d"%k) cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k) DB = db_open_dict("bdb:Q%1d"%k) for i in xrange(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) #cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k) #cmdexecute("sxheader.py bdb:Q%1d --params=xform.projection --import=ptsma%1d.txt"%(k,k)) DB.close() delete_bdb("bdb:sdata") cmdexecute("e2bdb.py . --makevstack=bdb:sdata --filt=Q") #cmdexecute("ls EMAN2DB/sdata*") a = get_im("bdb:sdata") a.set_attr("variabilitysymmetry",sym) a.write_image("bdb:sdata") else: sys.argv = mpi_init(len(sys.argv), sys.argv) myid = mpi_comm_rank(MPI_COMM_WORLD) number_of_proc = mpi_comm_size(MPI_COMM_WORLD) main_node = 0 if len(args) == 1: stack = args[0] else: print( "usage: " + usage) print( "Please run '" + progname + " -h' for detailed options") return 1 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", "sx3dvariability", 1, myid) if options.VAR and options.SND: ERROR("Only one of var and SND can be set!", "sx3dvariability", myid) exit() 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", "sx3dvariability", 1, myid) exit() #if options.SND and (options.ave2D or options.ave3D): # ERROR("When SND is set, the program cannot output ave2D or ave3D", "sx3dvariability", 1, myid) # exit() if options.nvec > 0 : ERROR("PCA option not implemented", "sx3dvariability", 1, myid) exit() if options.nvec > 0 and options.ave3D == None: ERROR("When doing PCA analysis, one must set ave3D", "sx3dvariability", myid=myid) exit() 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: print_begin_msg("sx3dvariability") print_msg("%-70s: %s\n"%("Input stack", stack)) img_per_grp = options.img_per_grp nvec = options.nvec radiuspca = options.radiuspca symbaselen = 0 if myid == main_node: nima = EMUtil.get_image_count(stack) img = get_image(stack) nx = img.get_xsize() ny = img.get_ysize() if options.sym != "c1" : imgdata = get_im(stack) try: i = imgdata.get_attr("variabilitysymmetry") if(i != options.sym): ERROR("The symmetry provided does not agree with the symmetry of the input stack", "sx3dvariability", myid=myid) except: ERROR("Input stack is not prepared for symmetry, please follow instructions", "sx3dvariability", myid=myid) from 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", "sx3dvariability", myid=myid) symbaselen = nima/i else: symbaselen = nima else: nima = 0 nx = 0 ny = 0 nima = bcast_number_to_all(nima) nx = bcast_number_to_all(nx) ny = bcast_number_to_all(ny) Tracker ={} Tracker["nx"] =nx Tracker["ny"] =ny Tracker["total_stack"]=nima if options.decimate==1.: if options.window !=0: nx = options.window ny = options.window else: if options.window ==0: nx = int(nx/options.decimate) ny = int(ny/options.decimate) else: nx = int(options.window/options.decimate) ny = nx symbaselen = bcast_number_to_all(symbaselen) if radiuspca == -1: radiuspca = nx/2-2 if myid == main_node: print_msg("%-70s: %d\n"%("Number of projection", nima)) img_begin, img_end = MPI_start_end(nima, number_of_proc, myid) """ if options.SND: from projection import prep_vol, prgs from statistics import im_diff from utilities import get_im, model_circle, get_params_proj, set_params_proj from utilities import get_ctf, generate_ctf from 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: #varList = EMData.read_images(stack, range(img_begin, img_end)) varList = [] this_image = EMData() for index_of_particle in xrange(img_begin,img_end): this_image.read_image(stack,index_of_particle) varList.append(image_decimate_window_xform_ctf(img,options.decimate,options.window,options.CTF)) else: from utilities import bcast_number_to_all, bcast_list_to_all, send_EMData, recv_EMData from utilities import set_params_proj, get_params_proj, params_3D_2D, get_params2D, set_params2D, compose_transform2 from utilities import model_blank, nearest_proj, model_circle from applications import pca from statistics import avgvar, avgvar_ctf, ccc from filter import filt_tanl from morphology import threshold, square_root from projection import project, prep_vol, prgs from sets import Set if myid == main_node: t1 = time() proj_angles = [] aveList = [] tab = EMUtil.get_all_attributes(stack, 'xform.projection') for i in xrange(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() print_msg("%-70s: %d\n"%("Number of neighboring projections", img_per_grp)) print_msg("...... Finding neighboring projections\n") if options.VERBOSE: print "Number of images per group: ", img_per_grp print "Now grouping projections" proj_angles.sort() proj_angles_list = [0.0]*(nima*4) if myid == main_node: for i in xrange(nima): proj_angles_list[i*4] = proj_angles[i][1] proj_angles_list[i*4+1] = proj_angles[i][2] proj_angles_list[i*4+2] = proj_angles[i][3] proj_angles_list[i*4+3] = proj_angles[i][4] proj_angles_list = bcast_list_to_all(proj_angles_list, myid, main_node) proj_angles = [] for i in xrange(nima): proj_angles.append([proj_angles_list[i*4], proj_angles_list[i*4+1], proj_angles_list[i*4+2], int(proj_angles_list[i*4+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) if options.VERBOSE: print "On node %2d, number of images needed to be read = %5d"%(myid, len(all_proj)) index = {} for i in xrange(len(all_proj)): index[all_proj[i]] = i mpi_barrier(MPI_COMM_WORLD) if myid == main_node: print_msg("%-70s: %.2f\n"%("Finding neighboring projections lasted [s]", time()-t2)) print_msg("%-70s: %d\n"%("Number of groups processed on the main node", len(proj_list))) if options.VERBOSE: print "Grouping projections took: ", (time()-t2)/60 , "[min]" print "Number of groups on main node: ", len(proj_list) mpi_barrier(MPI_COMM_WORLD) if myid == main_node: print_msg("...... calculating the stack of 2D variances \n") if options.VERBOSE: print "Now calculating the stack of 2D variances" proj_params = [0.0]*(nima*5) aveList = [] varList = [] if nvec > 0: eigList = [[] for i in xrange(nvec)] if options.VERBOSE: print "Begin to read images on processor %d"%(myid) ttt = time() #imgdata = EMData.read_images(stack, all_proj) img = EMData() imgdata = [] for index_of_proj in xrange(len(all_proj)): img.read_image(stack, all_proj[index_of_proj]) dmg = image_decimate_window_xform_ctf(img,options.decimate,options.window,options.CTF) #print dmg.get_xsize(), "init" imgdata.append(dmg) if options.VERBOSE: print "Reading images on processor %d done, time = %.2f"%(myid, time()-ttt) print "On processor %d, we got %d images"%(myid, len(imgdata)) mpi_barrier(MPI_COMM_WORLD) ''' 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 applications import prepare_2d_forPCA from utilities import model_blank for i in xrange(len(proj_list)): ki = proj_angles[proj_list[i][0]][3] if ki >= symbaselen: continue mi = index[ki] phiM, thetaM, psiM, s2xM, s2yM = get_params_proj(imgdata[mi]) grp_imgdata = [] for j in xrange(img_per_grp): mj = index[proj_angles[proj_list[i][j]][3]] phi, theta, psi, s2x, s2y = get_params_proj(imgdata[mj]) alpha, sx, sy, mirror = params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror_list[i][j]) if thetaM <= 90: if mirror == 0: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, phiM-phi, 0.0, 0.0, 1.0) else: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, 180-(phiM-phi), 0.0, 0.0, 1.0) else: if mirror == 0: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, -(phiM-phi), 0.0, 0.0, 1.0) else: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, -(180-(phiM-phi)), 0.0, 0.0, 1.0) set_params2D(imgdata[mj], [alpha, sx, sy, mirror, 1.0]) grp_imgdata.append(imgdata[mj]) #print grp_imgdata[j].get_xsize(), imgdata[mj].get_xsize() if not options.no_norm: #print grp_imgdata[j].get_xsize() mask = model_circle(nx/2-2, nx, nx) for k in xrange(img_per_grp): ave, std, minn, maxx = Util.infomask(grp_imgdata[k], mask, False) grp_imgdata[k] -= ave grp_imgdata[k] /= std del mask if options.fl > 0.0: from filter import filt_ctf, filt_table from fundamentals import fft, window2d nx2 = 2*nx ny2 = 2*ny if options.CTF: from utilities import pad for k in xrange(img_per_grp): grp_imgdata[k] = window2d(fft( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa) ),nx,ny) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) else: for k in xrange(img_per_grp): grp_imgdata[k] = filt_tanl( grp_imgdata[k], options.fl, options.aa) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) else: from utilities import pad, read_text_file from filter import filt_ctf, filt_table from fundamentals import fft, window2d nx2 = 2*nx ny2 = 2*ny if options.CTF: from utilities import pad for k in xrange(img_per_grp): grp_imgdata[k] = window2d( fft( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1) ) , nx,ny) #grp_imgdata[k] = window2d(fft( filt_table( filt_tanl( filt_ctf(fft(pad(grp_imgdata[k], nx2, ny2, 1,0.0)), grp_imgdata[k].get_attr("ctf"), binary=1), options.fl, options.aa), fifi) ),nx,ny) #grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa) ''' if i < 10 and myid == main_node: for k in xrange(10): grp_imgdata[k].write_image("grp%03d.hdf"%i, k) ''' """ if myid == main_node and i==0: for pp in xrange(len(grp_imgdata)): grp_imgdata[pp].write_image("pp.hdf", pp) """ ave, grp_imgdata = prepare_2d_forPCA(grp_imgdata) """ if myid == main_node and i==0: for pp in xrange(len(grp_imgdata)): grp_imgdata[pp].write_image("qq.hdf", pp) """ var = model_blank(nx,ny) for q in grp_imgdata: Util.add_img2( var, q ) Util.mul_scalar( var, 1.0/(len(grp_imgdata)-1)) # Switch to std dev var = square_root(threshold(var)) #if options.CTF: ave, var = avgvar_ctf(grp_imgdata, mode="a") #else: ave, var = avgvar(grp_imgdata, mode="a") """ if myid == main_node: ave.write_image("avgv.hdf",i) var.write_image("varv.hdf",i) """ 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) if options.VERBOSE: print "%5.2f%% done on processor %d"%(i*100.0/len(proj_list), myid) if nvec > 0: eig = pca(input_stacks=grp_imgdata, subavg="", mask_radius=radiuspca, nvec=nvec, incore=True, shuffle=False, genbuf=True) for k in xrange(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) """ del imgdata # To this point, all averages, variances, and eigenvectors are computed if options.ave2D: from fundamentals import fpol if myid == main_node: km = 0 for i in xrange(number_of_proc): if i == main_node : for im in xrange(len(aveList)): aveList[im].write_image(options.ave2D, km) km += 1 else: nl = mpi_recv(1, MPI_INT, i, MPI_TAG_UB, MPI_COMM_WORLD) nl = int(nl[0]) for im in xrange(nl): ave = recv_EMData(i, im+i+70000) """ nm = mpi_recv(1, MPI_INT, i, MPI_TAG_UB, MPI_COMM_WORLD) nm = int(nm[0]) members = mpi_recv(nm, MPI_INT, i, MPI_TAG_UB, MPI_COMM_WORLD) ave.set_attr('members', map(int, members)) members = mpi_recv(nm, MPI_FLOAT, i, MPI_TAG_UB, MPI_COMM_WORLD) ave.set_attr('pix_err', map(float, members)) members = mpi_recv(3, MPI_FLOAT, i, MPI_TAG_UB, MPI_COMM_WORLD) ave.set_attr('refprojdir', map(float, members)) """ tmpvol=fpol(ave, Tracker["nx"],Tracker["nx"],Tracker["nx"]) tmpvol.write_image(options.ave2D, km) km += 1 else: mpi_send(len(aveList), 1, MPI_INT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) for im in xrange(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, MPI_TAG_UB, MPI_COMM_WORLD) mpi_send(members, len(members), MPI_INT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) members = aveList[im].get_attr('pix_err') mpi_send(members, len(members), MPI_FLOAT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) try: members = aveList[im].get_attr('refprojdir') mpi_send(members, 3, MPI_FLOAT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) except: mpi_send([-999.0,-999.0,-999.0], 3, MPI_FLOAT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) """ if options.ave3D: from fundamentals import fpol if options.VERBOSE: print "Reconstructing 3D average volume" ave3D = recons3d_4nn_MPI(myid, aveList, symmetry=options.sym, npad=options.npad) bcast_EMData_to_all(ave3D, myid) if myid == main_node: ave3D=fpol(ave3D,Tracker["nx"],Tracker["nx"],Tracker["nx"]) ave3D.write_image(options.ave3D) print_msg("%-70s: %s\n"%("Writing to the disk volume reconstructed from averages as", options.ave3D)) del ave, var, proj_list, stack, phi, theta, psi, s2x, s2y, alpha, sx, sy, mirror, aveList if nvec > 0: for k in xrange(nvec): if options.VERBOSE: print "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("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 xrange(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]) print " 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 fundamentals import fpol if myid == main_node: km = 0 for i in xrange(number_of_proc): if i == main_node : for im in xrange(len(varList)): tmpvol=fpol(varList[im], Tracker["nx"], Tracker["nx"],1) tmpvol.write_image(options.var2D, km) km += 1 else: nl = mpi_recv(1, MPI_INT, i, MPI_TAG_UB, MPI_COMM_WORLD) nl = int(nl[0]) for im in xrange(nl): ave = recv_EMData(i, im+i+70000) tmpvol=fpol(ave, Tracker["nx"], Tracker["nx"],1) tmpvol.write_image(options.var2D, km) km += 1 else: mpi_send(len(varList), 1, MPI_INT, main_node, MPI_TAG_UB, MPI_COMM_WORLD) for im in xrange(len(varList)): send_EMData(varList[im], main_node, im+myid+70000)# What with the attributes?? mpi_barrier(MPI_COMM_WORLD) if options.var3D: if myid == main_node and options.VERBOSE: print "Reconstructing 3D variability volume" t6 = time() radiusvar = options.radiusvar 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 fundamentals import fpol res =fpol(res, Tracker["nx"], Tracker["nx"], Tracker["nx"]) res.write_image(options.var3D) if myid == main_node: print_msg("%-70s: %.2f\n"%("Reconstructing 3D variability took [s]", time()-t6)) if options.VERBOSE: print "Reconstruction took: %.2f [min]"%((time()-t6)/60) if myid == main_node: print_msg("%-70s: %.2f\n"%("Total time for these computations [s]", time()-t0)) if options.VERBOSE: print "Total time for these computations: %.2f [min]"%((time()-t0)/60) print_end_msg("sx3dvariability") global_def.BATCH = False from mpi import mpi_finalize mpi_finalize()