def test_eps_convergence_linbp_Torus():
print "\n-- 'eps_convergence_linbp' for Torus ---"
W, n = load_W(join(data_directory, 'Torus_W.csv'), zeroindexing=False)
print 'W dense:\n', W.todense()
print 'W:\n', W
Hc, k, _ = load_H(join(data_directory, 'Torus_H.csv'), zeroindexing=False)
print "H\n", Hc
print
# Simple spectral = 0.658
start = time.time()
eps = eps_convergence_linbp(Hc, W)
end = time.time()-start
print "Eps:", eps
print "Time needed:", end
# Echo spectral = 0.488
start = time.time()
eps = eps_convergence_linbp(Hc, W, echo=True)
end = time.time()-start
print "Eps:", eps
print "Time needed:", end
def test_eps_convergence_linbp_Torus():
print "\n-- 'eps_convergence_linbp' for Torus ---"
W, n = load_W(join(data_directory, 'Torus_W.csv'), zeroindexing=False)
print 'W dense:\n', W.todense()
print 'W:\n', W
Hc, k, _ = load_H(join(data_directory, 'Torus_H.csv'), zeroindexing=False)
print "H\n", Hc
print
# Simple spectral = 0.658
start = time.time()
eps = eps_convergence_linbp(Hc, W)
end = time.time() - start
print "Eps:", eps
print "Time needed:", end
# Echo spectral = 0.488
start = time.time()
eps = eps_convergence_linbp(Hc, W, echo=True)
end = time.time() - start
print "Eps:", eps
print "Time needed:", end
def test_linBP_undirected_Torus():
print "\n-- 'linBP_undirected', 'eps_convergence_linbp' with Torus --"
# -- Load W, create X and P
W, n = load_W(join(data_directory, 'Torus_W.csv'), zeroindexing=False, delimiter=',')
X = np.array(
[[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0]])
H = np.array(
[[0.1, 0.8, 0.1],
[0.8, 0.1, 0.1],
[0.1, 0.1, 0.8]])
print "W (dense):\n", W.todense()
print "X:\n", X
print "H:\n", H
Hc = to_centering_beliefs(H)
print "Hc:\n", Hc
print
# -- Other parameters
eps = 0.4
numMaxIt = 20
eps_max = eps_convergence_linbp(Hc, W)
print "eps_max: ", eps_max
print "eps: ", eps
Hc2 = Hc*eps
print "P*eps:\n", Hc2
print
# --- linBP
listF = linBP_undirected(X, W, Hc2, numIt=numMaxIt, debug=2)
# --- Display BP results
print "linBP results:"
print "last two F:"
print listF[-2]
print listF[-1]
print "\nValues for node 6 (zero indexing):"
print listF[:, 6, :]
# --- Visualize BP results
filename = join(fig_directory, 'temp.pdf')
print "\nVisualize values for node 3 (zero indexing):"
node = 3
plt.plot(listF[:, node, :], lw=2)
plt.xlabel('# iterations')
plt.ylabel('belief')
plt.xlim(0, numMaxIt)
print filename
plt.savefig(filename, dpi=None, facecolor='w', edgecolor='w',
orientation='portrait', papertype='letter', format='pdf',
transparent=True, bbox_inches='tight', pad_inches=0.1,
frameon=None)
os.system("chmod 744 " + filename) # first change permissions in order to open PDF
os.system("open " + filename) # open PDF