def train(ctx, config, classifier_config, model, n_fold, seed, plot, diagnostics, overwrite): """ Train a classifier from `scikit-learn` on YATSM output and save result to file <model>. Dataset configuration is specified by <yatsm_config> and classifier and classifier parameters are specified by <classifier_config>. """ if not model.endswith('.pkl'): model += '.pkl' if os.path.isfile(model) and not overwrite: logger.error('<model> exists and --overwrite was not specified') raise click.Abort() if seed: np.random.seed(seed) # Parse YATSM config dataset_config, yatsm_config = parse_config_file(config) if not dataset_config['training_image'] or \ not os.path.isfile(dataset_config['training_image']): logger.error('Training data image {f} does not exist'.format( f=dataset_config['training_image'])) raise click.Abort() # Parse classifier config algorithm_helper = classifiers.ini_to_algorthm(classifier_config) main(dataset_config, yatsm_config, algorithm_helper, model, diagnostics, n_fold, plot)
logger.error('Must specify integer for --kfold') sys.exit(1) if args['--seed']: np.random.seed(int(args['--seed'])) make_plots = args['--plot'] plt.style.use('ggplot') run_diagnostics = args['--diagnostics'] if args['--verbose']: logger.setLevel(logging.DEBUG) if args['--quiet']: logger.setLevel(logging.WARNING) # Parse YATSM config dataset_config, yatsm_config = parse_config_file(yatsm_config_file) if not dataset_config['training_image'] or \ not os.path.isfile(dataset_config['training_image']): logger.error('Training data image {f} does not exist'.format( f=dataset_config['training_image'])) sys.exit(1) # Parse classifier config algorithm_helper = classifiers.ini_to_algorthm(classifier_config_file) main(dataset_config, yatsm_config, algorithm_helper, model_filename, run_diagnostics=run_diagnostics)
if args['--seed']: np.random.seed(int(args['--seed'])) make_plots = args['--plot'] plt.style.use('ggplot') run_diagnostics = args['--diagnostics'] if args['--verbose']: logger.setLevel(logging.DEBUG) if args['--quiet']: logger.setLevel(logging.WARNING) # Parse YATSM config dataset_config, yatsm_config = parse_config_file(yatsm_config_file) if not dataset_config['training_image'] or \ not os.path.isfile(dataset_config['training_image']): logger.error('Training data image {f} does not exist'.format( f=dataset_config['training_image'])) sys.exit(1) # Parse classifier config algorithm_helper = classifiers.ini_to_algorthm(classifier_config_file) main(dataset_config, yatsm_config, algorithm_helper, model_filename, run_diagnostics=run_diagnostics)