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)