Mercurial > repos > bgruening > sklearn_label_encoder
view label_encoder.py @ 8:e8d6b4acb7c6 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
author | bgruening |
---|---|
date | Mon, 02 Oct 2023 09:40:02 +0000 |
parents | 108141350edb |
children |
line wrap: on
line source
import argparse import json import warnings import numpy as np import pandas as pd from sklearn.preprocessing import LabelEncoder def main(inputs, infile, outfile): """ Parameter --------- input : str File path to galaxy tool parameter infile : str File paths of input vector outfile : str File path to output vector """ warnings.simplefilter("ignore") with open(inputs, "r") as param_handler: params = json.load(param_handler) input_header = params["header0"] header = "infer" if input_header else None input_vector = pd.read_csv(infile, sep="\t", header=header) le = LabelEncoder() output_vector = le.fit_transform(input_vector) np.savetxt(outfile, output_vector, fmt="%d", delimiter="\t") if __name__ == "__main__": aparser = argparse.ArgumentParser() aparser.add_argument("-i", "--inputs", dest="inputs", required=True) aparser.add_argument("-y", "--infile", dest="infile") aparser.add_argument("-o", "--outfile", dest="outfile") args = aparser.parse_args() main(args.inputs, args.infile, args.outfile)