def parse_args(): """Parse incoming args. :return argparse.Namespace: args""" parser = common.get_default_parser("PyGame fractal viewer") parser.add_argument( "-t", "--terminate", action="store_true", help="terminate window exactly after rendering.") return parser.parse_args()
tag=tag, show=show, host=host) downloaded.append(obj) if not preserve_ccdb_structure: print("Printing") for i in downloaded: j = i.split("/")[-2] j = os.path.join(out_path, f"{j}.root") print(i, "->", j) os.rename(i, j) if __name__ == "__main__": parser = get_default_parser( "Fetch data from CCDB" "Basic example: `./fetch_output.py qc/TOF/MO/TaskRaw/hDiagnostic`") parser.add_argument( 'ccdb_path', metavar='path_to_object', type=str, help= 'Path of the object in the CCDB repository. If a `.txt` file is passed the all the file input is downloaded' ) parser.add_argument( '--timestamp', "-t", metavar='object_timestamp', type=str, default=["-1"], nargs="+",
nnet.cuda() criterion = nn.CrossEntropyLoss() optimizer = th.optim.Adam(nnet.parameters(), lr=args.learning_rate) train_dataset = THCHS30(root=args.data_dir, data_type='train', left_context=left_context, right_context=right_context, model_type='cnn') train_loader = data.DataLoader(dataset=train_dataset, batch_size=args.min_batch, shuffle=True, num_workers=6) test_dataset = THCHS30(root=args.data_dir, data_type='test', left_context=left_context, right_context=right_context, model_type='cnn') test_loader = data.DataLoader(dataset=test_dataset, batch_size=args.min_batch, shuffle=True, num_workers=6) cross_validate(-1, nnet, test_dataset, test_loader) for epoch in range(args.num_epochs): common.train_one_epoch(nnet, criterion, optimizer, train_loader) cross_validate(epoch, nnet, test_dataset, test_loader) th.save(nnet, common..join_path(args.checkout_dir, 'cnn.{}.pkl'.format(epoch + 1))) if __name__ == '__main__': parser = argparse.ArgumentParser( description="""Trains a simple CNN acoustic model using CE loss function""", formatter_class=argparse.ArgumentDefaultsHelpFormatter, conflict_handler='resolve', parents=[common.get_default_parser()]) args = parser.parse_args() print(args) train(args)
msg("Merging", len(files_per_type[i]), "files to", merged_file) run_cmd( f"hadd -j {njobs} -f {merged_file} `cat {merge_file_list}`", log_file=merge_file_list.replace(".txt", ".log"), time_it=True, comment=f"Merging to {merged_file}") if len(merged_files) == 0: warning_msg("Merged no files") else: msg("Merging completed, merged:", *merged_files, color=bcolors.BOKGREEN) if __name__ == "__main__": parser = get_default_parser(description="Runner for O2 analyses") parser.add_argument( "modes", type=str, nargs="+", help="Running modes, as defined in the input configuration file") parser.add_argument( "--input", "-i", type=str, nargs="+", default=["listfiles.txt"], help= "Input file, can be in form of a list of AODs or a list of text files with the list of AODs" ) parser.add_argument("--out_path",
bunched_aod_names[fn] = { "out_aod": out_aod, "file_index": i, "total_files": len(bunched_files), "input_size": bunched_sizes[i] } run_in_parallel(jobs, run_merge, list(bunched_aod_names.keys()), job_message="Running AOD merging", linearize_single_core=True) if __name__ == "__main__": parser = get_default_parser(__doc__) parser.add_argument("input_files", type=str, nargs="+", help="Input files to merge") parser.add_argument( "--max_bunch_size", "--max", "-m", default=1000, type=float, help="Approximate maximum size of the bunch to merge in MB") parser.add_argument("--output_path", "-o", default="./", type=str,
run_cmd(f"mv {summaryfile} {output_path}") run_cmd(f"ln -s {os.path.join(output_path, summaryfile)} ./") if qa: msg(" --- running test analysis", color=bcolors.HEADER) run_cmd( f"./diagnostic_tools/doanalysis.py TrackQA RICH TOF -i {output_list_file} -M 25 -B 25" ) if tof_mismatch == 1: # TOF mismatch in create mode run_cmd( f"hadd -j {njobs} -f tofMM.root tof_mismatch_template_DF_*.root && rm tof_mismatch_template_DF_*.root" ) if __name__ == "__main__": parser = get_default_parser(description=__doc__) parser.add_argument( "configuration_file", type=str, help= "Input configuration file e.g. you can use the provided default_configfile.ini or variations of it." ) parser.add_argument( "--entry", "-e", type=str, default="DEFAULT", help= "Entry in the configuration file, e.g. the INEL or CCBAR entries in the configuration file." ) parser.add_argument(
copyfile(i) elif args.command == "copylist": for i in input_files: copylist(i, jobs=args.jobs) elif args.command == "copied": for i in input_files: print(copied(i)) elif args.command == "merge_aod": for i in input_files: merge_aod(i, input_file=args.what) else: warning_msg("Did not do anything") if __name__ == "__main__": parser = get_default_parser(description=__doc__, njobs=False) parser.add_argument( "input_files", type=str, # nargs="+", help="List of files in .txt file or files to download") # parser.add_argument("--input_files", "--input", "-i", type=str,# nargs="+", # default=[], # help="List of files in .txt file or files to download") subparsers = parser.add_subparsers(dest='command', help='sub-commands') def add_subp(fn, g=None): if g is None: g = subparsers.add_parser(fn.__name__, help=fn.__doc__) a = inspect.getfullargspec(fn) for i, j in enumerate(a.args): d = a.defaults[i]