diff options
| author | Calvin <calvin@EESI> | 2013-03-11 12:40:47 -0400 | 
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| committer | Calvin <calvin@EESI> | 2013-03-11 12:40:47 -0400 | 
| commit | 3f0c33ff93dea10b2f79c8c2101431e251b8b928 (patch) | |
| tree | 46e2a43535d3aa0d768ec0841bdbe4957651ba7b /src/quikr | |
| parent | 4ca6f92ceb4b2f8c504431cf56f8a6135187a61c (diff) | |
move python stuff to python directory
Diffstat (limited to 'src/quikr')
| -rwxr-xr-x | src/quikr | 48 | 
1 files changed, 0 insertions, 48 deletions
| diff --git a/src/quikr b/src/quikr deleted file mode 100755 index bac01ca..0000000 --- a/src/quikr +++ /dev/null @@ -1,48 +0,0 @@ -#!/usr/bin/python -import sys -import os -import argparse -import quikr -import numpy as np - -def main(): - -    parser = argparse.ArgumentParser(description= -    "Quikr returns the estimated frequencies of batcteria present when given a \ -    input FASTA file. \n \ -    A default trained matrix will be used if none is supplied \n \ -    You must supply a kmer and default lambda if using a custom trained \ -    matrix.") - -    parser.add_argument("-f", "--fasta", help="fasta file", required=True) -    parser.add_argument("-o", "--output", help="output path (csv output)", required=True) -    parser.add_argument("-t", "--trained-matrix", help="trained matrix", required=True) -    parser.add_argument("-l", "--lamb", type=int, help="the default lambda value is 10,000") -    parser.add_argument("-k", "--kmer", type=int, required=True, -        help="specifies which kmer to use, must be used with a custom trained database") - - -    args = parser.parse_args() -     -    # our default lambda is 10,000 -    lamb = 10000 - -    # Make sure our input exist -    if not os.path.isfile(args.fasta): -        parser.error( "Input fasta file not found") - -    if not os.path.isfile(args.trained_matrix): -        parser.error("Custom trained matrix not found") -     -    # use alternative lambda -    if args.lamb is not None: -        lamb = args.lamb -     -    trained_matrix = quikr.load_trained_matrix_from_file(args.trained_matrix) -    xstar = quikr.calculate_estimated_frequencies(args.fasta, trained_matrix, args.kmer, lamb) - -    np.savetxt(args.output, xstar, delimiter=",", fmt="%f") -    return 0 - -if __name__ == "__main__": -    sys.exit(main()) | 
