precursor.py

#!python
# Copyright (c) 2012, Sven Thiele <sthiele78@gmail.com>
#
# This file is part of precursor.
#
# precursor is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# precursor is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with precursor.  If not, see <http://www.gnu.org/licenses/>.
# -*- coding: utf-8 -*-

#from pyasp.asp import *
from pyasp.term import *;
import argparse
from __precursor__ import query, utils, sbml

if __name__ == '__main__':

    parser = argparse.ArgumentParser()
    parser.add_argument("net",
                        help="metabolic network in SBML format")
    parser.add_argument("inputs",
                        help="targets in XML format")
                        #help="target, seed and ubiquitous metabolites in XML format")

    parser.add_argument('--autoseeds',
                        help="compute possible seed metabolites",
                        action="store_true")

    args        = parser.parse_args()
    netfile     = args.net
    targetsfile = args.inputs

    print('Reading network from ',netfile,'...',end='')
    net = sbml.readSBMLnetwork(netfile)
    print('done.')


    print('Reading inputs from ',targetsfile,'...',end='')
    targets, pseeds, misc  = sbml.readPITUFU(targetsfile)
    print('done.')
    print("   ", len(targets), "target metabolites.")
    print("   ", len(pseeds), "possible seed metabolites.")
    net = TermSet(net.union(misc))
    #print misc

    if args.autoseeds :
      print('\nAutocompute possible seeds ...',end='')
      autoseeds = query.get_automatic_pseeds(net, targets)
      print('done.')
      print('   ', len(autoseeds), 'possible seeds found.')
      pseeds = TermSet(pseeds.union(autoseeds))

    print('\nTesting targets for producebility ...',end='')
    filtered_targets = TermSet()
    for t in targets :
      singlet = String2TermSet(str(t))
      SAT     = query.satcheck(net, pseeds, singlet)
      if not SAT :
          filtered_targets.add(t)
    print('done.')

    if len(filtered_targets) > 0:
      print('   ',len(targets),' targets cannot be produced:')
      for t in filtered_targets : print('   ',t.arg(0))
      print('cannot be produced.')

    targets = TermSet(targets.difference(filtered_targets))

    if len(targets) > 0:
      print('   ',len(targets),' targets can be produced:')
      for t in targets : print('   ',t.arg(0))

      targets = TermSet(targets.difference(filtered_targets))
    else:
      print('    No Target can be produced.')
      utils.clean_up()
      quit()


    print('\nCompute cardinality minimum for a precursor sets ...',end='')
    solution = query.get_card_min_precursor_set(net, pseeds, targets)
    print('done.')

    opt = solution.score[0]
    print('    Minimal size of a precursor set is',str(opt-1)+'.')

    print('\nCompute all cadinality minimal precursor sets...',end='')
    precursors = query.get_card_minimal_precursor_sets(net, pseeds, targets)
    print('done.')

    count=1
    for min_set in precursors :
      print(count,end=': ')
      utils.print_seeds(min_set)
      count+=1

    print('\nCompute subset minimal precursor sets ...',end='')
    precursors = query.get_subset_min_precursor_sets(net, pseeds, targets)
    print('done.')

    print(len(precursors),' subset minimal precursor sets found.')
    count=1
    for min_set in precursors :
      print(count,end=': ')
      utils.print_seeds(min_set)
      count+=1

    utils.clean_up()