def test_nearest_neighbors(self):
a, b, c = self.a, self.b, self.c
ns = list(nearest_neighbors([a, b, c], .25))
self.assertEqual(len(ns), 0)
ns = list(nearest_neighbors([a, b, c], 1.4))
self.assertEqual(len(ns), 2)
ns = list(nearest_neighbors([a,b,c], 2.1))
self.assertEqual(len(ns), 3)
self.assertEqual(ns, [[a, b], [a, c], [c, b]])
def time_everything(n_samples, dim, epsilon, max_dim):
points = [sample_torus(dim) for i in range(n_samples)]
now = time.time()
one_skel = list(nearest_neighbors(points, epsilon))
nn_time = time.time() - now
now = time.time()
# exp_ind = expand_inductive(points, one_skel, max_dim)
exp_ind_time = time.time() - now
now = time.time()
inc_vr = incremental_vr(points, one_skel, max_dim)
inc_vr_time = time.time() - now
def sxs_size(d):
for k in d:
print "{0}: {1}".format(k, len(d[k]))
sxs_size(inc_vr)
return (nn_time, exp_ind_time, inc_vr_time)
def vr(n_samples, dim, epsilon, max_dim):
points = [sample_torus(dim) for i in range(n_samples)]
one_skel = list(nearest_neighbors(points, epsilon))
return incremental_vr(points, one_skel, max_dim)
