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)
