#!/usr/bin/env 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")
    parser.add_argument("-f", "--fasta", help="the sample's fasta file of NGS READS", required=True)
    parser.add_argument("-o", "--output", help="OTU_FRACTION_PRESENT, a vector \
    representing the percentage of database sequence's presence in a sequence. (csv output)", required=True)
    parser.add_argument("-s", "--sensing-matrix", help="the sensing matrix", required=True)
    parser.add_argument("-l", "--lamb", type=int, help="the lambda size. (default is 10,000")
    parser.add_argument("-k", "--kmer", type=int, required=True,
        help="specifies the size of the kmer to use (the default is 6)")

    args = parser.parse_args()
    
    # our default lambda is 10,000
    lamb = 10000
    # our default kmer size is 6
    kmer = 6

    # 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.sensing_matrix):
        parser.error("Custom sensing matrix not found")
    
    # use alternative lambda
    if args.lamb is not None:
        lamb = args.lamb
    
    # use alternative kmer
    if args.kmer is not None:
        kmer = args.kmer

    sensing_matrix = quikr.load_sensing_matrix_from_file(args.sensing_matrix)
    xstar = quikr.calculate_estimated_frequencies(args.fasta, sensing_matrix, kmer, lamb)

    np.savetxt(args.output, xstar, delimiter=",", fmt="%f")
    return 0

if __name__ == "__main__":
    sys.exit(main())