#!/usr/local/bin/python3

import argparse
from SCNIC.within_correls import within_correls
from SCNIC.between_correls import between_correls
from SCNIC.module import module_maker

__author__ = 'shafferm'

"""Entry to both module_maker and between_correls, only holds main and args are passed to the corresponding program"""


def main():
    """Things"""
    parser = argparse.ArgumentParser()

    subparsers = parser.add_subparsers()
    within_corr = subparsers.add_parser("within", help="Find pairwise correlations within a table",
                                        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    make_modules = subparsers.add_parser("modules", help="Make modules on a network",
                                         formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    between_corr = subparsers.add_parser("between", help="Find correlations between two tables",
                                         formatter_class=argparse.ArgumentDefaultsHelpFormatter)

    # parser for making correlation network with a single biom table
    within_corr.add_argument("-i", "--input", help="location of input biom file", required=True)
    within_corr.add_argument("-o", "--output", help="output directory")
    within_corr.add_argument("-m", "--correl_method", help="correlation method", default="sparcc")
    within_corr.add_argument("-a", "--p_adjust", help="p-value adjustment", default="bh")
    within_corr.add_argument("-s", "--min_sample", help="minimum number of samples present in", type=int)
    within_corr.add_argument("--procs", help="number of processors to use", default=1, type=int)
    within_corr.add_argument("-f", "--force", help="force overwrite output folder if it already exists", default=False,
                             action="store_true")
    within_corr.add_argument("--sparcc_filter", help="filter as described in SparCC paper", default=False,
                             action="store_true")
    within_corr.add_argument("--sparcc_p", help="Calculate p-value for sparCC R value", type=int)
    within_corr.add_argument("--verbose", help="give verbose messages to STDOUT", default=False, action="store_true")
    within_corr.set_defaults(func=within_correls)

    # parser for finding modules in a correlation network
    make_modules.add_argument("-i", "--input", help="location of input distance matrix", required=True)
    make_modules.add_argument("-o", "--output", help="output directory")
    make_modules.add_argument("--prefix", help="prefix for module names in collapsed file", default="module_")
    make_modules.add_argument("--min_p", help="minimum p-value to determine edges, p must have been calculated",
                              type=float)
    make_modules.add_argument("--min_r", help="minimum correlation value to determine edges", type=float)
    make_modules.add_argument("--table", help="biom table usede to make network to be collapsed")
    make_modules.add_argument("-v", "--verbose", help="give verbose messages to STDOUT")
    make_modules.set_defaults(func=module_maker)

    # parser for building a bipartite correlation network between two data types
    between_corr.add_argument("-1", "--table1", help="table to be correlated", required=True)
    between_corr.add_argument("-2", "--table2", help="second table to be correlated", required=True)
    between_corr.add_argument("-o", "--output", help="output file location")
    between_corr.add_argument("-m", "--correl_method", help="correlation method", default="spearman")
    between_corr.add_argument("-a", "--p_adjust", help="p-value adjustment", default="bh")
    between_corr.add_argument("-s", "--min_sample", help="minimum number of samples present in", type=int)
    between_corr.add_argument("--min_p", help="minimum p-value to determine edges", type=float)
    between_corr.add_argument("--min_r", help="minimum R to determine edges", type=float)
    between_corr.add_argument("--sparcc_filter", help="filter using parameters from SparCC publication", default=False,
                              action="store_true")
    between_corr.add_argument("--procs", help="number of processors to use", default=1, type=int)
    between_corr.add_argument("-f", "--force", help="force overwrite output folder if it already exists", default=False,
                              action="store_true")
    between_corr.set_defaults(func=between_correls)

    args = parser.parse_args()
    args.func(args)


if __name__ == "__main__":
    main()

#!/usr/local/bin/python3

import argparse
from SCNIC.within_correls import within_correls
from SCNIC.between_correls import between_correls
from SCNIC.module import module_maker

__author__ = 'shafferm'

"""Entry to both module_maker and between_correls, only holds main and args are passed to the corresponding program"""


def main():
    """Things"""
    parser = argparse.ArgumentParser()

    subparsers = parser.add_subparsers()
    within_corr = subparsers.add_parser("within", help="Find pairwise correlations within a table",
                                        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    make_modules = subparsers.add_parser("modules", help="Make modules on a network",
                                         formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    between_corr = subparsers.add_parser("between", help="Find correlations between two tables",
                                         formatter_class=argparse.ArgumentDefaultsHelpFormatter)

    # parser for making correlation network with a single biom table
    within_corr.add_argument("-i", "--input", help="location of input biom file", required=True)
    within_corr.add_argument("-o", "--output", help="output directory")
    within_corr.add_argument("-m", "--correl_method", help="correlation method", default="sparcc")
    within_corr.add_argument("-a", "--p_adjust", help="p-value adjustment", default="bh")
    within_corr.add_argument("-s", "--min_sample", help="minimum number of samples present in", type=int)
    within_corr.add_argument("--procs", help="number of processors to use", default=1, type=int)
    within_corr.add_argument("-f", "--force", help="force overwrite output folder if it already exists", default=False,
                             action="store_true")
    within_corr.add_argument("--sparcc_filter", help="filter as described in SparCC paper", default=False,
                             action="store_true")
    within_corr.add_argument("--sparcc_p", help="Calculate p-value for sparCC R value", type=int)
    within_corr.add_argument("--verbose", help="give verbose messages to STDOUT", default=False, action="store_true")
    within_corr.set_defaults(func=within_correls)

    # parser for finding modules in a correlation network
    make_modules.add_argument("-i", "--input", help="location of input distance matrix", required=True)
    make_modules.add_argument("-o", "--output", help="output directory")
    make_modules.add_argument("--prefix", help="prefix for module names in collapsed file", default="module_")
    make_modules.add_argument("--min_p", help="minimum p-value to determine edges, p must have been calculated",
                              type=float)
    make_modules.add_argument("--min_r", help="minimum correlation value to determine edges", type=float)
    make_modules.add_argument("--table", help="biom table usede to make network to be collapsed")
    make_modules.add_argument("-v", "--verbose", help="give verbose messages to STDOUT")
    make_modules.set_defaults(func=module_maker)

    # parser for building a bipartite correlation network between two data types
    between_corr.add_argument("-1", "--table1", help="table to be correlated", required=True)
    between_corr.add_argument("-2", "--table2", help="second table to be correlated", required=True)
    between_corr.add_argument("-o", "--output", help="output file location")
    between_corr.add_argument("-m", "--correl_method", help="correlation method", default="spearman")
    between_corr.add_argument("-a", "--p_adjust", help="p-value adjustment", default="bh")
    between_corr.add_argument("-s", "--min_sample", help="minimum number of samples present in", type=int)
    between_corr.add_argument("--min_p", help="minimum p-value to determine edges", type=float)
    between_corr.add_argument("--min_r", help="minimum R to determine edges", type=float)
    between_corr.add_argument("--sparcc_filter", help="filter using parameters from SparCC publication", default=False,
                              action="store_true")
    between_corr.add_argument("--procs", help="number of processors to use", default=1, type=int)
    between_corr.add_argument("-f", "--force", help="force overwrite output folder if it already exists", default=False,
                              action="store_true")
    between_corr.set_defaults(func=between_correls)

    args = parser.parse_args()
    args.func(args)


if __name__ == "__main__":
    main()

#!/usr/local/bin/python3 Entry to both module_maker and between_correls, only holds main and args are passed to the corresponding program Things # parser for making correlation network with a single biom table # parser for finding modules in a correlation network # parser for building a bipartite correlation network between two data types