def test_attribute_with_duplicate_values(self):
# Load the default network
sf = safe.SAFE(verbose=False)
sf.load_network()
f = '/Users/abaryshnikova/Lab/Datasets/safe-data/tests/attribute_file_with_unmatched_duplicated_labels.txt'
sf.load_attributes(attribute_file=f)
def test_euclidean(self):
# Load the default network
sf = safe.SAFE(verbose=False)
sf.load_network()
sf.define_neighborhoods(node_distance_metric='euclidean')
num_neighbors = np.sum(sf.neighborhoods, axis=1)
num_neighbors_avg = np.mean(num_neighbors)
num_neighbors_std = np.std(num_neighbors)
self.assertAlmostEqual(num_neighbors_avg, 148.44, delta=0.5, msg="Should be 148.44.")
self.assertAlmostEqual(num_neighbors_std, 40.99, delta=0.5, msg="Should be 40.99.")
def test_default(self):
# Load the default network
sf = safe.SAFE(verbose=False)
sf.load_network()
sf.define_neighborhoods()
num_neighbors = np.sum(sf.neighborhoods, axis=1)
num_neighbors_avg = np.mean(num_neighbors)
num_neighbors_std = np.std(num_neighbors)
self.assertAlmostEqual(num_neighbors_avg, 37.5, delta=0.5, msg="Should be 37.5.")
self.assertAlmostEqual(num_neighbors_std, 56.74, delta=0.5, msg="Should be 56.74.")
def test_shortpath(self):
# Load the default network
sf = safe.SAFE(verbose=False)
sf.load_network()
sf.define_neighborhoods(node_distance_metric='shortpath',
neighborhood_radius=1)
num_neighbors = np.sum(sf.neighborhoods, axis=1)
num_neighbors_avg = np.mean(num_neighbors)
num_neighbors_std = np.std(num_neighbors)
self.assertAlmostEqual(num_neighbors_avg, 15.20, delta=0.5, msg="Should be 15.20.")
self.assertAlmostEqual(num_neighbors_std, 18.32, delta=0.5, msg="Should be 18.32.")
MZ = mp.Array(ctypes.c_double,FN*(chunk-v*window),lock=False)
S = mp.Array(ctypes.c_float,FN*(chunk-window),lock=False)
SZ1 = mp.Array(ctypes.c_float,FN*(chunk-v*window),lock=False)
ST = mp.Array(ctypes.c_float,FN*(tiles),lock=False)
STZ1 = mp.Array(ctypes.c_float,FN*(tiles-v),lock=False)
STZ2 = mp.Array(ctypes.c_float,FN*(disjoint_tiles),lock=False)
T = mp.Array(ctypes.c_float,FN*FN*(chunk-window-1),lock=False)
TZ = mp.Array(ctypes.c_float, FN*FN*(chunk-v*window-1))
bins = range(0,max_depth,max_depth/FN)+[np.uint32(-1)]
B = mp.Array(ctypes.c_float,bins,lock=False)
s = safe.SAFE()
#testing results here
core.sliding_moments(I,0,chunk,window,window*10,M)
core.sliding_spectrum_bin(I,0,chunk,window,B,S)
core.sliding_transitions_bin(I,0,chunk,window,B,T)
start = time.time()
core.merge_sliding_moments_target(M,MZ,t=v*window)
stop = time.time()
start = time.time()
x = 0
for i in range(tiles):
core.spectrum_bin(I,x,x+window,B,ST,FN,FN*i)
x += window
stop = time.time()
def test_default(self):
# Load the default network
sf = safe.SAFE(verbose=False)
sf.load_network()
sf.load_attributes()