import os, os.path from timeit import default_timer as timer # Third party imports import matplotlib.pyplot as plt from numpy import* # Personal libraries from galib.tools import LoadFromPajek from galib.models import RandomGraph from galib.models_numba import RandomGraph_Numba ################################################################## # 0) READ THE DATA currdir = os.getcwd() currdir = os.path.split(currdir)[0] dataroot = os.path.join(currdir, 'Data/') net, labs = LoadFromPajek(dataroot + 'Cat53_cortex.net', True) netsym = 0.5*(net+net.T) N = len(net) # Define the partition visual = arange(16) audit = arange(16,23) somatomotor = arange(23,39) frontolimbic = arange(39, 53) partition = [visual,audit,somatomotor,frontolimbic] ncoms = len(partition) time1 = timer() N = 5000 # # 1) RING MODELS # latt = Lattice1D(N,5)
# Third party imports
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from numpy import *
# Personal libraries
from galib import RichClub
from galib.models import RewireNetwork
from galib.tools import SymmetriseMatrix, LoadFromPajek
##################################################################
# 0) READ THE DATA
currdir = os.getcwd()
dataroot = os.path.join(currdir, 'Data/')
net = loadtxt(dataroot + 'Zachary.txt', dtype=uint8)
net = LoadFromPajek(dataroot + 'Dolphins.net', getlabels=False)
net, labels = LoadFromPajek(dataroot + 'LesMiserables.net', getlabels=True)
# net = loadtxt(dataroot + 'Cat53_cortex.txt', dtype=uint8)
# net = SymmetriseMatrix(net)
N = len(net)
# 1) COMPUTE THE RICH-CLUB OF THE NETWORKS
# 1.1) Rich-club of the empirical network.
# Notice that 'net' is weighted but function RichClub ignores the weights.
rcdens = RichClub(net, rctype='undirected')
# 1.2) Rich-club in an ensemble of rewired networks for comparison
nrealiz = 100
prewire = 10
kmax = len(rcdens)
rewrcdens = zeros((nrealiz, kmax), float)
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from numpy import *
# Personal libraries
from galib import RichClub
from galib.models import RewireNetwork
from galib.tools import LoadFromPajek, Save2Pajek, LoadLabels, SaveLabels
##################################################################
# 1) READ SOME DATA IN PAJEK FORMAT AND SAVE THE ADJACENCY MATRIX
currdir = os.getcwd()
dataroot = os.path.join(currdir, 'Data/')
# 1.1) Read the data splitting the adjacency matrix and the labels
fname = 'LesMiserables.net'
net, labels = LoadFromPajek(dataroot + fname, getlabels=True)
# 1.2) Save the adjacency matrix as a text file
# Give '%d' formatter for integer data, '%f' for real valued data
outfname1 = 'spam_LesMiserables.txt'
savetxt(dataroot + outfname1, net, fmt='%d')
# 1.3) Save the adjacency matrix in a numpy binary file
outfname2 = 'spam_LesMiserables.npy'
save(dataroot + outfname2, net)
# 1.4) Save the labels in an independent text file
outfname3 = 'spam_LesMiserables_labels.txt'
SaveLabels(dataroot + outfname3, labels)
# 2) READ AN ADJACENCY MATRIX AND SAVE IT AS PAJEK FORMAT