def test_distance():
u = np.array([[np.cos(0.), np.sin(0.)], [np.cos(0.5),
np.sin(0.5)],
[np.cos(10.), np.sin(10.)]])
v = np.array([[np.cos(0.5), np.sin(0.5)], [np.cos(0.5),
np.sin(0.5)],
[np.cos(0.5), np.sin(0.5)]])
expected = np.array([[0.5], [0.], [3.066370614359173]])
circle = Sphere(1)
assert_array_almost_equal(circle.distance(u, v), expected)
def compute_distances_zoo_topology(self):
latencies = {}
max_weight = 0
min_weight = sys.maxint
for n, nbrs in self.graph.adjacency_iter():
for nbr, eattr in nbrs.items():
log.info("edge {0}-{1}: {2}".format(n, nbr, str(eattr)))
n, n_items = self.graph.nodes(data=True)[n]
nbr, nbr_items = self.graph.nodes(data=True)[nbr]
latencies[(n, nbr)] = float(Sphere.distance(n_items['Latitude'], n_items['Longitude'],
nbr_items['Latitude'], nbr_items['Longitude']) * 1000)/200000
log.info("latency: {0}".format(latencies[(n, nbr)]))
return latencies
