def test_graphs():
"""Smoke tests for graph methods."""
n_samples_sizes = [5, 10, 20]
n_features = 3
rng = np.random.RandomState(42)
for n_samples in n_samples_sizes:
X = rng.rand(n_samples, n_features)
lshf = LSHForest(min_hash_match=0)
lshf.fit(X)
kneighbors_graph = lshf.kneighbors_graph(X)
radius_neighbors_graph = lshf.radius_neighbors_graph(X)
assert_equal(kneighbors_graph.shape[0], n_samples)
assert_equal(kneighbors_graph.shape[1], n_samples)
assert_equal(radius_neighbors_graph.shape[0], n_samples)
assert_equal(radius_neighbors_graph.shape[1], n_samples)
def test_graphs():
# Smoke tests for graph methods.
n_samples_sizes = [5, 10, 20]
n_features = 3
rng = np.random.RandomState(42)
for n_samples in n_samples_sizes:
X = rng.rand(n_samples, n_features)
lshf = LSHForest(min_hash_match=0)
ignore_warnings(lshf.fit)(X)
kneighbors_graph = lshf.kneighbors_graph(X)
radius_neighbors_graph = lshf.radius_neighbors_graph(X)
assert_equal(kneighbors_graph.shape[0], n_samples)
assert_equal(kneighbors_graph.shape[1], n_samples)
assert_equal(radius_neighbors_graph.shape[0], n_samples)
assert_equal(radius_neighbors_graph.shape[1], n_samples)
X = np.array(X_tmp)
from sklearn.neighbors import NearestNeighbors
from sklearn.neighbors import LSHForest
for n in range(2, 10):
print "[[[[[" + str(n) + "]]]]]"
start = time.time()
# nbrs = NearestNeighbors(n_neighbors=n, algorithm='ball_tree').fit(X)
# print nbrs.kneighbors_graph(X).toarray()
neigh = NearestNeighbors(n_neighbors=n)
neigh.fit(X)
a = neigh.radius_neighbors_graph(X).toarray()
print a
# a = neigh.kneighbors_graph(X).toarray()
pc.dump(a, open("knn" + str(n) + ".txt", "w"))
end = time.time()
print "NearestNeighbors", end - start
start = time.time()
lshf = LSHForest(n_neighbors=n, random_state=10000)
lshf.fit(X)
# distances, indices = lshf.kneighbors(X, n_neighbors=n)
# print lshf.kneighbors_graph(X).toarray()
a = lshf.radius_neighbors_graph(X).toarray()
print a
pc.dump(a, open("lsh" + str(n) + ".txt", "w"))
end = time.time()
print "LSHForest", end - start
