sklearn_stacking_ensemble_models: label

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"

comparison

equal deleted inserted replaced

-:2d890789ac48
+:0380f10c4e04
+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)

Mercurial > repos > bgruening > sklearn_stacking_ensemble_models