#!/usr/bin/env python3
import argparse


NULLDEV='/dev/null'


parser = argparse.ArgumentParser(description='Perform the fast unfolding algorithm over a bivariate distribution.')


parser.add_argument('input_file', metavar='INPUT', type=str,
                    help='the input file that contains the bivariate distribution')
                    
parser.add_argument('vcount', metavar='N', type=int,
                    help='the number of vertices in the graph')
                    
parser.add_argument('output_file', metavar='OUTPUT', type=str,
                    help='the output file to store the detected communities')

parser.add_argument('-t', '--time', metavar='FILE', dest='time_file', type=str, default=NULLDEV,
                    help='record the consumption time to FILE')

parser.add_argument('-s', '--size', metavar='FILE', dest='size_file', type=str, default=NULLDEV,
                    help='record the number of vertices in each round to FILE')

parser.add_argument('-i', '--iter', metavar='FILE', dest='iter_file', type=str, default=NULLDEV,
                    help='record the number of iterations in each round to FILE')
                    
parser.add_argument('-3c', '--three_column', dest='three_column', action='store_true', default=False,
                    help='use three-column format for the bivariate distribution')

args = parser.parse_args()

target_execute_file = './fastunfolding_3c' if args.three_column else './fastunfolding'

cmd = '{} {} {} {} {} {} > {}'.format(target_execute_file, args.input_file, args.vcount, args.time_file, args.size_file, args.iter_file, args.output_file)

import subprocess
# subprocess.Popen(cmd, shell=True)
print(cmd)

824b51fadfb6d3d7b39ac184aa7ba2682fec3789
<mask token>

<mask token>
parser.add_argument('input_file', metavar='INPUT', type=str, help=
    'the input file that contains the bivariate distribution')
parser.add_argument('vcount', metavar='N', type=int, help=
    'the number of vertices in the graph')
parser.add_argument('output_file', metavar='OUTPUT', type=str, help=
    'the output file to store the detected communities')
parser.add_argument('-t', '--time', metavar='FILE', dest='time_file', type=
    str, default=NULLDEV, help='record the consumption time to FILE')
parser.add_argument('-s', '--size', metavar='FILE', dest='size_file', type=
    str, default=NULLDEV, help=
    'record the number of vertices in each round to FILE')
parser.add_argument('-i', '--iter', metavar='FILE', dest='iter_file', type=
    str, default=NULLDEV, help=
    'record the number of iterations in each round to FILE')
parser.add_argument('-3c', '--three_column', dest='three_column', action=
    'store_true', default=False, help=
    'use three-column format for the bivariate distribution')
<mask token>
print(cmd)

<mask token>
NULLDEV = '/dev/null'
parser = argparse.ArgumentParser(description=
    'Perform the fast unfolding algorithm over a bivariate distribution.')
parser.add_argument('input_file', metavar='INPUT', type=str, help=
    'the input file that contains the bivariate distribution')
parser.add_argument('vcount', metavar='N', type=int, help=
    'the number of vertices in the graph')
parser.add_argument('output_file', metavar='OUTPUT', type=str, help=
    'the output file to store the detected communities')
parser.add_argument('-t', '--time', metavar='FILE', dest='time_file', type=
    str, default=NULLDEV, help='record the consumption time to FILE')
parser.add_argument('-s', '--size', metavar='FILE', dest='size_file', type=
    str, default=NULLDEV, help=
    'record the number of vertices in each round to FILE')
parser.add_argument('-i', '--iter', metavar='FILE', dest='iter_file', type=
    str, default=NULLDEV, help=
    'record the number of iterations in each round to FILE')
parser.add_argument('-3c', '--three_column', dest='three_column', action=
    'store_true', default=False, help=
    'use three-column format for the bivariate distribution')
args = parser.parse_args()
target_execute_file = ('./fastunfolding_3c' if args.three_column else
    './fastunfolding')
cmd = '{} {} {} {} {} {} > {}'.format(target_execute_file, args.input_file,
    args.vcount, args.time_file, args.size_file, args.iter_file, args.
    output_file)
<mask token>
print(cmd)

import argparse
NULLDEV = '/dev/null'
parser = argparse.ArgumentParser(description=
    'Perform the fast unfolding algorithm over a bivariate distribution.')
parser.add_argument('input_file', metavar='INPUT', type=str, help=
    'the input file that contains the bivariate distribution')
parser.add_argument('vcount', metavar='N', type=int, help=
    'the number of vertices in the graph')
parser.add_argument('output_file', metavar='OUTPUT', type=str, help=
    'the output file to store the detected communities')
parser.add_argument('-t', '--time', metavar='FILE', dest='time_file', type=
    str, default=NULLDEV, help='record the consumption time to FILE')
parser.add_argument('-s', '--size', metavar='FILE', dest='size_file', type=
    str, default=NULLDEV, help=
    'record the number of vertices in each round to FILE')
parser.add_argument('-i', '--iter', metavar='FILE', dest='iter_file', type=
    str, default=NULLDEV, help=
    'record the number of iterations in each round to FILE')
parser.add_argument('-3c', '--three_column', dest='three_column', action=
    'store_true', default=False, help=
    'use three-column format for the bivariate distribution')
args = parser.parse_args()
target_execute_file = ('./fastunfolding_3c' if args.three_column else
    './fastunfolding')
cmd = '{} {} {} {} {} {} > {}'.format(target_execute_file, args.input_file,
    args.vcount, args.time_file, args.size_file, args.iter_file, args.
    output_file)
import subprocess
print(cmd)

#!/usr/bin/env python3
import argparse


NULLDEV='/dev/null'


parser = argparse.ArgumentParser(description='Perform the fast unfolding algorithm over a bivariate distribution.')


parser.add_argument('input_file', metavar='INPUT', type=str,
                    help='the input file that contains the bivariate distribution')
                    
parser.add_argument('vcount', metavar='N', type=int,
                    help='the number of vertices in the graph')
                    
parser.add_argument('output_file', metavar='OUTPUT', type=str,
                    help='the output file to store the detected communities')

parser.add_argument('-t', '--time', metavar='FILE', dest='time_file', type=str, default=NULLDEV,
                    help='record the consumption time to FILE')

parser.add_argument('-s', '--size', metavar='FILE', dest='size_file', type=str, default=NULLDEV,
                    help='record the number of vertices in each round to FILE')

parser.add_argument('-i', '--iter', metavar='FILE', dest='iter_file', type=str, default=NULLDEV,
                    help='record the number of iterations in each round to FILE')
                    
parser.add_argument('-3c', '--three_column', dest='three_column', action='store_true', default=False,
                    help='use three-column format for the bivariate distribution')

args = parser.parse_args()

target_execute_file = './fastunfolding_3c' if args.three_column else './fastunfolding'

cmd = '{} {} {} {} {} {} > {}'.format(target_execute_file, args.input_file, args.vcount, args.time_file, args.size_file, args.iter_file, args.output_file)

import subprocess
# subprocess.Popen(cmd, shell=True)
print(cmd)
