parser.add_argument('-o',
'--output',
dest='output',
required=False,
action='store',
default=None,
help='Output directory.')
opts = parser.parse_args()
if opts.output == None:
outdir = tempfile.mkdtemp(dir=os.curdir, prefix='out')
logger.info('Output directory %s', outdir)
else:
outdir = opts.output
if not os.path.exists(outdir):
tsh.makedirs(outdir)
config = tsh.read_config(opts, __file__)
basename = os.path.splitext(os.path.basename(opts.model))[0]
propagator = read_propagatorfile(opts.model)
cv_results = propagator['meta']['cv_results']
data = {}
for score, params, cm in cv_results:
key = tuple(params.items())
if key not in data:
data[key] = []
data[key] += [score]
all_param_keys = sorted(data.keys())
data = tsh.dict_values(data, all_param_keys)
plt.errorbar(range(len(all_param_keys)),
np.mean(data, axis=1),
fmt='ro',
yerr=np.std(data, axis=1))
parser = argparse.ArgumentParser(description='Computes features for all the input data.')
parser.add_argument('-c', '--config', dest='config', required=False, action='store', default=None, help='Path to the config file')
parser.add_argument('-m', '--method', dest='method', required=True, action='store', choices=method_table.keys(), default=None, help='Method name.')
parser.add_argument('-a', '--args', dest='args', required=False, action='store', default=None, help='Method arguments file.')
parser.add_argument('-l', '--list', dest='list', required=True, action='store', default=None, help='List file.')
parser.add_argument('-j', '--jobs', dest='jobs', required=False, action='store', default=None, type=int, help='Number of parallel processes.')
parser.add_argument('-o', '--output', dest='output', required=False, action='store', default=None, help='Output directory.')
opts = parser.parse_args()
if opts.output == None:
outdir = tempfile.mkdtemp(dir=os.curdir, prefix='out')
logger.info('Output directory %s', outdir)
else:
outdir = opts.output
if not os.path.exists(outdir):
tsh.makedirs(outdir)
inputname = os.path.splitext(os.path.basename(opts.list))[0]
if opts.list.endswith('.gz'):
inputname = os.path.splitext(inputname)[0]
outputname = os.path.join(outdir, inputname + '-feats.csv.gz')
if os.path.exists(outputname):
logger.info('Skipping file %s, already exists.', outputname)
else:
config = tsh.read_config(opts, __file__)
meta, data = read_listfile(opts.list)
args = meta
if opts.args != None:
args.update(read_argsfile(opts.args))
args, features = compute_features(opts.method, args, data, input_name=inputname, n_jobs=opts.jobs, output_dir=outdir)
clean_args(args)
write_listfile(outputname, features, input_name=inputname, **args)