"""
CBMPy: MultiCoreFVA module
==========================
PySCeS Constraint Based Modelling (http://cbmpy.sourceforge.net)
Copyright (C) 2009-2017 Brett G. Olivier, VU University Amsterdam, Amsterdam, The Netherlands

This program 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.

This program 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 this program.  If not, see <http://www.gnu.org/licenses/>

Author: Brett G. Olivier
Contact email: bgoli@users.sourceforge.net
Last edit: $Author: bgoli $ ($Id: _multicorefva.py 575 2017-04-13 12:18:44Z bgoli $)

"""

# preparing for Python 3 port
from __future__ import division, print_function
from __future__ import absolute_import
#from __future__ import unicode_literals

import os, time, math, copy, multiprocessing
try:
    import pickle
except ImportError:
    import cPickle as pickle

import cbmpy

def funcFVA(x,r):
    try:
        Args = x.FVAARGS
        del x.FVAARGS
        Args.insert(0, x)
        Args[1] = r
        fva, fvan = cbmpy.CBSolver.FluxVariabilityAnalysis(*Args)
    except Exception as ex:
        print(ex)
        fva = fvan = None
        raise RuntimeError(ex)
    return fva, fvan

def multiCoreFVA(fvamod, procs=2, timeout=None):
    #assert procs >= 2, '\nMinimum 2 processes required'
    rid = fvamod.getReactionIds()
    PRs = [d_[0] for d_ in list(cbmpy.CBMultiCore.grouper(int(math.ceil(len(rid)/float(procs))), range(len(rid))))]
    print(procs, len(PRs), PRs)

    s2time = time.time()
    TP = multiprocessing.Pool(processes=procs)
    results = []
    if procs == 1:
        results.append(TP.apply_async(funcFVA, (fvamod.clone(), rid)))
    else:
        for p_ in range(len(PRs)-1):
            print('{} -> {}'.format(PRs[p_], PRs[p_+1]))
            print('{} -> {}'.format(rid[PRs[p_]], rid[PRs[p_+1]]))
            # investigate using without clone
            #results.append(TP.apply_async(funcFVA, (fvamod, rid[PRs[p_]:PRs[p_+1]])))
            results.append(TP.apply_async(funcFVA, (fvamod.clone(), rid[PRs[p_]:PRs[p_+1]])))
        results.append(TP.apply_async(funcFVA, (fvamod.clone(), rid[PRs[-1]:])))
    fva = []
    fvan = []
    for r_ in results:
        out = r_.get(timeout)
        fva.append(out[0])
        fvan.append(out[1])
    e2time = time.time()
    del results

    print('\nMulticore FVA took: {} min ({} processes)'.format((e2time-s2time)/60., procs))
    return fva, fvan


if __name__ == '__main__':

    print(os.sys.argv)

    cores = int(os.sys.argv[1])
    F = file(os.sys.argv[2],'rb')
    cmod = pickle.load(F)
    F.close()

    cbmpy.CBSolver.analyzeModel(cmod, oldlpgen=False)
    res = multiCoreFVA(cmod, procs=cores)

    F = file(os.sys.argv[2], 'wb')
    pickle.dump(res, F, protocol=-1)
    F.flush()
    F.close()
