# Adrian Soto
# 2016-09-13
# Institute for Advanced Computational Science
# Stony Brook University
#
import numpy as np


def loadA(Afile, delim=' '):
# Read adjacency matrix from file

    A = np.loadtxt(Afile)
    return A 


# Load all matrices into a numpy.array
A1=loadA('./data/A1.dat')
A2=loadA('./data/A2.dat')
A3=loadA('./data/A3.dat')
A4=loadA('./data/A4.dat')
A5=loadA('./data/A5.dat')



d9cff4c942e2ab6158e3577bc4fcd547d039b2fa
<mask token>

<mask token>


def loadA(Afile, delim=' '):
    A = np.loadtxt(Afile)
    return A


<mask token>

<mask token>


def loadA(Afile, delim=' '):
    A = np.loadtxt(Afile)
    return A


A1 = loadA('./data/A1.dat')
A2 = loadA('./data/A2.dat')
A3 = loadA('./data/A3.dat')
A4 = loadA('./data/A4.dat')
A5 = loadA('./data/A5.dat')

import numpy as np


def loadA(Afile, delim=' '):
    A = np.loadtxt(Afile)
    return A


A1 = loadA('./data/A1.dat')
A2 = loadA('./data/A2.dat')
A3 = loadA('./data/A3.dat')
A4 = loadA('./data/A4.dat')
A5 = loadA('./data/A5.dat')

# Adrian Soto
# 2016-09-13
# Institute for Advanced Computational Science
# Stony Brook University
#
import numpy as np


def loadA(Afile, delim=' '):
# Read adjacency matrix from file

    A = np.loadtxt(Afile)
    return A 


# Load all matrices into a numpy.array
A1=loadA('./data/A1.dat')
A2=loadA('./data/A2.dat')
A3=loadA('./data/A3.dat')
A4=loadA('./data/A4.dat')
A5=loadA('./data/A5.dat')


