def test_load_and_save_W():
print "\n-- 'load_W', 'save_W'"
print "Example where file does not exist:"
filename1 = 'notExistingFile.csv'
with pytest.raises(IOError):
W, n = load_W(join(data_directory, filename1)) # files still without zero indexing
print "\nTorus, zeroindexing=False"
filename2 = 'Torus_W.csv'
print "File directory:\n ", join(data_directory, filename2)
W, n = load_W(join(data_directory, filename2), zeroindexing=False)
print "W:\n", W
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nTorus, n=9"
W, n = load_W(join(data_directory, filename2), zeroindexing=False, n=9)
print "W:\n", W
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nSave same data with n=9 and load without specifying n=9 during load"
filename3 = 'Torus_W3.gz'
save_W(join(data_directory, filename3), W, saveWeights=True) # gzip is possible
W, n = load_W(join(data_directory, filename3)) # newly written files use zeroindexing=True
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nLoad data with float"
W, n = load_W(join(data_directory, 'Torus_W3.gz'), usefloat=True) # use float for weights other than integers
print "W:\n", W
print "Shape: ", W.shape
print "\nSave data with float works, load without specifying float"
filename4 = 'Torus_W4.csv'
save_W(join(data_directory, filename4), W, saveWeights=True)
W, n = load_W(join(data_directory, filename4), usefloat=True)
print "W:\n", W
print "\n2 columns, directed, space as delimiter"
filename5 = 'test_load_and_save_W.txt'
W, n = load_W(join(data_directory, filename5), delimiter=None, zeroindexing=False)
print "W\n", W
print "\n2 columns, directed, space as delimiter, doubleUndirected"
W, n = load_W(join(data_directory, filename5), delimiter=None, zeroindexing=False, doubleUndirected=True)
print "W\n", W
print "\n3 columns, directed, space as delimiter, doubleUndirected"
W, n = load_W(join(data_directory, 'Torus_W6.csv'), usefloat=True, doubleUndirected=True)
print "W\n", W
print "\nSave the same without weights, and load again"
filename7 = 'Torus_W7.csv'
save_W(join(data_directory, filename7), W, delimiter=' ')
W, n = load_W(join(data_directory, filename7), delimiter=None)
print "W\n", W
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
exponent=exponent,
directed=True,
debug=False)
X0 = from_dictionary_beliefs(Xd)
time_graph = time.time() - start
save_W(join(data_directory, '{}_{}_W.csv'.format(filename, n)),
W,
saveWeights=False)
save_X(join(data_directory, '{}_{}_X.csv'.format(filename, n)), X0)
save_tuple(n, 'graph', time_graph)
else:
W, _ = load_W(join(data_directory,
'{}_{}_W.csv'.format(filename, n)),
skiprows=1,
zeroindexing=True,
n=None,
doubleUndirected=False)
X0, _, _ = load_X(join(data_directory,
'{}_{}_X.csv'.format(filename, n)),
n=None,
k=None,
skiprows=1,
zeroindexing=True)
# -- Repeat loop
for i in range(repeat):
print("\n repeat: {}".format(i))
X2, ind = replace_fraction_of_rows(X0,
1 - f,
def test_load_and_save_W():
print "\n-- 'load_W', 'save_W'"
print "Example where file does not exist:"
filename1 = 'notExistingFile.csv'
with pytest.raises(IOError):
W, n = load_W(join(data_directory,
filename1)) # files still without zero indexing
print "\nTorus, zeroindexing=False"
filename2 = 'Torus_W.csv'
print "File directory:\n ", join(data_directory, filename2)
W, n = load_W(join(data_directory, filename2), zeroindexing=False)
print "W:\n", W
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nTorus, n=9"
W, n = load_W(join(data_directory, filename2), zeroindexing=False, n=9)
print "W:\n", W
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nSave same data with n=9 and load without specifying n=9 during load"
filename3 = 'Torus_W3.gz'
save_W(join(data_directory, filename3), W,
saveWeights=True) # gzip is possible
W, n = load_W(join(data_directory,
filename3)) # newly written files use zeroindexing=True
print "Dense:\n", W.todense()
print "Shape: ", W.shape
print "\nLoad data with float"
W, n = load_W(join(data_directory, 'Torus_W3.gz'),
usefloat=True) # use float for weights other than integers
print "W:\n", W
print "Shape: ", W.shape
print "\nSave data with float works, load without specifying float"
filename4 = 'Torus_W4.csv'
save_W(join(data_directory, filename4), W, saveWeights=True)
W, n = load_W(join(data_directory, filename4), usefloat=True)
print "W:\n", W
print "\n2 columns, directed, space as delimiter"
filename5 = 'test_load_and_save_W.txt'
W, n = load_W(join(data_directory, filename5),
delimiter=None,
zeroindexing=False)
print "W\n", W
print "\n2 columns, directed, space as delimiter, doubleUndirected"
W, n = load_W(join(data_directory, filename5),
delimiter=None,
zeroindexing=False,
doubleUndirected=True)
print "W\n", W
print "\n3 columns, directed, space as delimiter, doubleUndirected"
W, n = load_W(join(data_directory, 'Torus_W6.csv'),
usefloat=True,
doubleUndirected=True)
print "W\n", W
print "\nSave the same without weights, and load again"
filename7 = 'Torus_W7.csv'
save_W(join(data_directory, filename7), W, delimiter=' ')
W, n = load_W(join(data_directory, filename7), delimiter=None)
print "W\n", W
