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())