diff options
| -rw-r--r-- | quikr_train.py | 43 |
1 files changed, 32 insertions, 11 deletions
diff --git a/quikr_train.py b/quikr_train.py index 2076f5a..0d407dd 100644 --- a/quikr_train.py +++ b/quikr_train.py @@ -1,25 +1,46 @@ -#from scipy.sparse import * +""" +The Quikr Train Script +""" + import numpy as np +import os import sys from subprocess import * import platform +import argparse + + -# You can call this script independently, and will save the -# trained matrix as a numpy file. -# example: python quikr-train.py input.fasta 6 trained_matrix.npy +def main(): + """ + You can call this script independently, and will save the + trained matrix as a numpy file. + example: python quikr-train.py input.fasta 6 trained_matrix.npy + """ + parser = argparse.ArgumentParser(description= + " quikr_train returns a custom trained matrix that can be used with \ + the quikr function. \n You must supply a kmer. \n ") -def main(argv): - input_file_location = argv[1] - kmer = argv[2] - output_file_location = argv[3] + parser.add_argument("-i", "--input", help="path to the database", required=True) + parser.add_argument("-i", "--output", help="path to output", required=True) + parser.add_argument("-k", "--kmer", type=int, help="specifies which kmer to use", required=True) + + args = parser.parse_args() + + if not os.path.isfile(args.input): + parser.error( "Input database not found") # call the quikr train function, save the output with np.save - matrix = quikr_train(argv[1], argv[2]) - np.save(output_file_location, matrix) + matrix = quikr_train(args.input, args.kmer) + + np.save(args.output, matrix) return 0 def quikr_train(input_file_location, kmer): + """ + Takes a input fasta file, and kmer, returns a custom trained matrix + """ print "input fasta training file: " + input_file_location @@ -47,4 +68,4 @@ def quikr_train(input_file_location, kmer): if __name__ == "__main__": - sys.exit(main(sys.argv)) + sys.exit(main()) |