def test_vq_1d_nested(self):
nested = [[p] for p in random_points]
book_indexes = [231, 31, 250, 104, 233, 289, 236, 259]
book = [nested[i] for i in book_indexes]
vq_file = open(os.path.join(os.path.dirname(__file__), "../../../fixtures/random_points/scipy_vq_output.txt"))
s_code = []
s_dist = []
for l in vq_file.xreadlines():
fields = l.split(",")
if not l.startswith("#") and len(fields) == 2:
s_code.append(int(fields[0].strip()))
s_dist.append(float(fields[1].strip()))
m_code, m_dist = kmeans.compute_clusters(nested, book)
self.assertSequenceEqual(s_code, m_code)
self.assertSequenceAlmostEqual(s_dist, m_dist)
def test_vq(self):
book_indexes = [28, 182, 948, 434, 969, 814, 859, 123]
book = [random_points_3d[i] for i in book_indexes]
vq_file = open(os.path.join(
os.path.dirname(__file__),
'../../../fixtures/random_points_3d/scipy_vq_output.txt'))
s_code = []
s_dist = []
for l in vq_file.xreadlines():
fields = l.split(",")
if not l.startswith("#") and len(fields) == 2:
s_code.append(int(fields[0].strip()))
s_dist.append(float(fields[1].strip()))
m_code, m_dist = kmeans.compute_clusters(random_points_3d, book)
self.assertSequenceEqual(s_code, m_code)
self.assertSequenceAlmostEqual(s_dist, m_dist)
def test_vq(self):
book_indexes = [28, 182, 948, 434, 969, 814, 859, 123]
book = [random_points_3d[i] for i in book_indexes]
vq_file = open(
os.path.join(
os.path.dirname(__file__),
'../../../fixtures/random_points_3d/scipy_vq_output.txt'))
s_code = []
s_dist = []
for l in vq_file.xreadlines():
fields = l.split(",")
if not l.startswith("#") and len(fields) == 2:
s_code.append(int(fields[0].strip()))
s_dist.append(float(fields[1].strip()))
m_code, m_dist = kmeans.compute_clusters(random_points_3d, book)
self.assertSequenceEqual(s_code, m_code)
self.assertSequenceAlmostEqual(s_dist, m_dist)
def test_vq_1d_nested(self):
nested = [[p] for p in random_points]
book_indexes = [231, 31, 250, 104, 233, 289, 236, 259]
book = [nested[i] for i in book_indexes]
vq_file = open(
os.path.join(
os.path.dirname(__file__),
'../../../fixtures/random_points/scipy_vq_output.txt'))
s_code = []
s_dist = []
for l in vq_file.xreadlines():
fields = l.split(",")
if not l.startswith("#") and len(fields) == 2:
s_code.append(int(fields[0].strip()))
s_dist.append(float(fields[1].strip()))
m_code, m_dist = kmeans.compute_clusters(nested, book)
self.assertSequenceEqual(s_code, m_code)
self.assertSequenceAlmostEqual(s_dist, m_dist)
