def label_fusion(target_path, atlas_img_path_list, atlas_lab_path_list, out_file, probabilities, params_list): out_dir = os.path.dirname(out_file) out_name = os.path.basename(out_file).split(os.extsep, 1)[0] if params_list[0] == 'Joint': jointfusion_path = os.path.join(os.environ['ANTSPATH'], 'jointfusion') prob_dir = os.path.join(out_dir, out_name) prob_path = os.path.join(prob_dir, 'prob%d.nii.gz') cmdline = [jointfusion_path, '3', '1'] cmdline += ['-g'] + atlas_img_path_list cmdline += ['-tg', target_path] cmdline += ['-l'] + atlas_lab_path_list cmdline += ['-m', 'Joint'] cmdline += [item for sublist in zip(['-rp', '-rs'], params_list[1:]) for item in sublist] if probabilities: os.makedirs(prob_dir) cmdline += ['-p', prob_path] cmdline += [out_file] else: python_path = os.path.join(os.environ['HOME'], 'anaconda', 'envs', 'sitkpy', 'bin', 'python') mod_path = os.path.join(os.environ['HOME'], 'CODE', 'mod_py') nlwv_path = os.path.join(mod_path, 'pblf_py.py') cmdline = [python_path, '-u', nlwv_path] cmdline += ['--atlas_img_list'] + atlas_img_path_list cmdline += ['--target_img', target_path] cmdline += ['--atlas_lab_list'] + atlas_lab_path_list cmdline += ['--method'] + params_list[:2] cmdline += [item for sublist in zip(['--patch_radius', '--search_radius', '--fusion_radius', '--struct_sim', '--normalization',], params_list[2:]) for item in sublist] if probabilities: cmdline += ['--probabilities'] cmdline += ['--out_file', out_file] # launch qsub_launcher = Launcher(' '.join(cmdline)) qsub_launcher.name = "{}_joint".format(out_name) qsub_launcher.folder = out_dir # qsub_launcher.queue = 'short.q' qsub_launcher.queue = 'default.q' return qsub_launcher.run()
] cmdline += [ os.path.join(in_dir, in_files_list[i]), os.path.join(in2_dir, in2_files_list[i2]) ] if args.mask_file is not None: cmdline += [ os.path.join(tmp_dir, os.path.basename(args.mask_file[0])) ] job_name = "{0}X{1}".format(RID_1 + '_' + sampleid_1, RID_2 + '_' + sampleid_2) qsub_launcher = Launcher(' '.join(cmdline)) qsub_launcher.name = job_name qsub_launcher.folder = tmp_dir qsub_launcher.queue = "short.q" job_id = qsub_launcher.run() if is_hpc: wait_jobs += [job_id] n_jobs += 1 list_of_jobs.append((job_name, i, i2)) # Wait for the jobs to finish (in cluster) if is_hpc and n_total_jobs <= n_jobs: print("Waiting for registration jobs to finish...") call(wait_jobs) n_jobs = 0 wait_jobs = [
args.reg_dir[0], file_name + args.in_deform_intfix[0] + '1InverseWarp.nii.gz') ] cmdline += [ '--output', os.path.join(args.out_dir[0], file.split('.nii.gz')[0] + args.out_suffix[0]) ] # # launch print "Launching warping of file {}".format(file) qsub_launcher = Launcher(' '.join(cmdline)) qsub_launcher.name = file.split('.nii.gz')[0] qsub_launcher.folder = args.out_dir[0] qsub_launcher.queue = 'short.q' job_id = qsub_launcher.run() if is_hpc: wait_jobs += [job_id] # Wait for the jobs to finish (in cluster) if is_hpc: print "Waiting for warping jobs to finish..." call(wait_jobs) print "Warping finished."
out_path = img_file.replace(in_dir, args.out_dir[0]) if not os.path.exists(os.path.dirname(out_path)): os.makedirs(os.path.dirname(out_path)) cmdline = [n4_path, '--image-dimensionality', '3'] cmdline += ['--input-image', img_file] cmdline += ['--shrink-factor', '3'] cmdline += ['--convergence', '50x50x30x20', '1e-6'] cmdline += ['--bspline-fitting', '300'] cmdline += ['--output', out_path] print("Launching N4 for {}".format(img_file)) qsub_launcher = Launcher(' '.join(cmdline)) qsub_launcher.name = os.path.splitext(os.path.basename(img_file))[0] qsub_launcher.folder = os.path.dirname(out_path) qsub_launcher.queue = 'short' job_id = qsub_launcher.run() njobs = njobs + 1 if is_hpc: wait_jobs += [job_id] if is_hpc and njobs >= n_total_jobs: print("Limit found. Wait for jobs to finish...") call(wait_jobs) njobs = 0 wait_jobs = [ os.path.join(os.environ['ANTSSCRIPTS'], "waitForSlurmJobs.pl"), '0', '10' ]