class TestSCMDS(unittest.TestCase):
def setUp(self):
self.test_matrix = np.loadtxt(get_data_path('full_sym_matrix.txt'))
self.dist_func = lambda x, y: (self.test_matrix[x, y])
self.num_objects = self.test_matrix.shape[0]
self.scmds = Scmds()
def test_scmds(self):
self.scmds.run(self.test_matrix)
def test_scmds_output_dimensions(self):
""" Ensure that an incorrect num_dimensions_out parameter triggers
an exception """
with self.assertRaises(ValueError):
self.scmds.run(self.test_matrix,
num_dimensions_out=self.test_matrix.shape[0])
def test_scmds_cmds_tzeng(self):
"""cmds_tzeng() should return eigenvectors and eigenvalues,
sorted by the eigenvalues
"""
dim = 3
(eigvec, eigval) = self.scmds._cmds_tzeng(self.test_matrix, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (self.test_matrix.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertAlmostEqual(eigval[0], 27336.883436, places=5)
self.assertAlmostEqual(eigval[-1], 536.736247, places=5)
self.assertAlmostEqual(eigvec[0, 0], -14.978621, places=5)
self.assertAlmostEqual(eigvec[-1, -1], 0.673001, places=5)
# full pcoa
dim = self.test_matrix.shape[0]
(eigvec, eigval) = self.scmds._cmds_tzeng(self.test_matrix, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (self.test_matrix.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertAlmostEqual(eigval[0], 27336.883436043929, places=5)
self.assertAlmostEqual(eigval[-1], 0.000000, places=5)
self.assertAlmostEqual(eigvec[0, 0], -14.978621, places=5)
self.assertAlmostEqual(eigvec[-1, -1], 0.000000, places=5)
def test_scmds_rowmeans(self):
"""rowmeans() should return a vector of row-means for a 2d matrix.
"""
rm = self.scmds.combine_mds.rowmeans(self.test_matrix[:10])
self.assertTrue(rm.shape[0] == 10)
self.assertAlmostEqual(float(rm[0]), 25.983320, places=5)
self.assertAlmostEqual(float(rm[-1]), 23.967050, places=5)
def test_scmds_recenter(self):
"""recenter() should recenter an mds solution
"""
mds_coords = matrix([[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
centered_coords = self.scmds.combine_mds.recenter(mds_coords)
self.assertTrue(centered_coords.shape == mds_coords.shape)
center_of_gravity = sum([
centered_coords[:, x].sum()
for x in range(centered_coords.shape[1])
])
self.assertAlmostEqual(center_of_gravity, 0.0, places=5)
def test_scmds_affine_mapping(self):
"""affine_mapping() should return a touple of two matrices of
certain shape
"""
matrix_x = matrix([[
-24.03457111, 10.10355666, -23.17039728, 28.48438894, 22.57322482
], [0.62716392, 20.84502664, 6.42317521, -7.66901011, 14.37923852
], [-2.60793417, 2.83532649, 2.91024821, 1.37414959, -4.22916659]])
matrix_y = matrix([
[-29.81089477, -2.01312927, -30.5925487, 23.05985801, 11.68581751],
[-4.68879117, 23.62633294, 1.07934315, 0.57461989, 20.52800221],
[-0.51503505, 1.18377044, 0.83671471, 1.81751358, -3.28812925]
])
dim = matrix_x.shape[0]
(tu, tb) = self.scmds.combine_mds.affine_mapping(matrix_x, matrix_y)
self.assertTrue(tu.shape[0] == dim and tb.shape[0] == dim)
self.assertTrue(tu.shape[0] == tu.shape[1])
self.assertAlmostEqual(tu[0, 0], 0.966653, places=5)
self.assertAlmostEqual(tu[-1, -1], 0.994816, places=5)
self.assertAlmostEqual(tb[0, 0], -6.480975, places=5)
self.assertAlmostEqual(tb[-1, -1], 0.686521, places=5)
def test_scmds_adjust_mds_to_ref(self):
"""adjust_mds_to_ref() should return an adjusted mds solutions"""
overlap = 5
dim = 3
size = 10
fake_mds_coords_ref = self.test_matrix[:size, :dim]
fake_mds_coords_add = self.test_matrix[overlap:size + overlap, :dim]
mds_adj = self.scmds.combine_mds.adjust_mds_to_ref(
fake_mds_coords_ref, fake_mds_coords_add, overlap)
self.assertTrue(mds_adj.shape == fake_mds_coords_add.shape)
self.assertAlmostEqual(mds_adj[0, 0], 7.526609, places=5)
self.assertAlmostEqual(mds_adj[-1, -1], 18.009350, places=5)
def test_scmds_combine_mds(self):
"""combine_mds() should merge two mds solutions
"""
overlap = 3
dim = 3
mds_coords_1 = matrix([[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
mds_coords_2 = matrix([[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
comb_mds = self.scmds.combine_mds.combine_mds(mds_coords_1,
mds_coords_2, overlap)
self.assertTrue(comb_mds.shape == (mds_coords_1.shape[0] * 2 - overlap,
dim))
self.assertAlmostEqual(comb_mds[0, 0], -3.783335, places=5)
# self.assertAlmostEqual(comb_mds[-1, -1], 0.349951)
def test_scmds_class_combinemds(self):
"""class CombineMds() should be able to join MDS solutions
"""
# tmp note
# tile1 = FULL_SYM_MATRIX[0:5, 0:5]
# tile2 = FULL_SYM_MATRIX[2:7, 2:7]
# mds_coords_1 = cmds_tzeng(tile1, 3)
# mds_coords_2 = cmds_tzeng(tile2, 3)
overlap = 3
mds_coords_1 = matrix([[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
mds_coords_2 = matrix([[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
comb_mds = CombineMds()
comb_mds.add(mds_coords_1, overlap)
comb_mds.add(mds_coords_2, overlap)
final_mds = comb_mds.getFinalMDS()
r, c = mds_coords_1.shape
self.assertTrue(final_mds.shape == (r * 2 - overlap, c))
class TestSCMDS(unittest.TestCase):
def setUp(self):
self.test_matrix = np.loadtxt(get_data_path('full_sym_matrix.txt'))
self.dist_func = lambda x, y: (self.test_matrix[x, y])
self.num_objects = self.test_matrix.shape[0]
self.scmds = Scmds()
def test_scmds(self):
self.scmds.run(self.test_matrix)
def test_scmds_output_dimensions(self):
""" Ensure that an incorrect num_dimensions_out parameter triggers
an exception """
with self.assertRaises(ValueError):
self.scmds.run(self.test_matrix,
num_dimensions_out=self.test_matrix.shape[0])
def test_scmds_cmds_tzeng(self):
"""cmds_tzeng() should return eigenvectors and eigenvalues,
sorted by the eigenvalues
"""
dim = 3
(eigvec, eigval) = self.scmds._cmds_tzeng(self.test_matrix, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (self.test_matrix.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertAlmostEqual(eigval[0], 27336.883436, places=5)
self.assertAlmostEqual(eigval[-1], 536.736247, places=5)
self.assertAlmostEqual(eigvec[0, 0], -14.978621, places=5)
self.assertAlmostEqual(eigvec[-1, -1], 0.673001, places=5)
# full pcoa
dim = self.test_matrix.shape[0]
(eigvec, eigval) = self.scmds._cmds_tzeng(self.test_matrix, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (self.test_matrix.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertAlmostEqual(eigval[0], 27336.883436043929, places=5)
self.assertAlmostEqual(eigval[-1], 0.000000, places=5)
self.assertAlmostEqual(eigvec[0, 0], -14.978621, places=5)
self.assertAlmostEqual(eigvec[-1, -1], 0.000000, places=5)
def test_scmds_rowmeans(self):
"""rowmeans() should return a vector of row-means for a 2d matrix.
"""
rm = self.scmds.combine_mds.rowmeans(self.test_matrix[:10])
self.assertTrue(rm.shape[0] == 10)
self.assertAlmostEqual(float(rm[0]), 25.983320, places=5)
self.assertAlmostEqual(float(rm[-1]), 23.967050, places=5)
def test_scmds_recenter(self):
"""recenter() should recenter an mds solution
"""
mds_coords = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
centered_coords = self.scmds.combine_mds.recenter(mds_coords)
self.assertTrue(centered_coords.shape == mds_coords.shape)
center_of_gravity = sum([centered_coords[:, x].sum()
for x in range(centered_coords.shape[1])])
self.assertAlmostEqual(center_of_gravity, 0.0, places=5)
def test_scmds_affine_mapping(self):
"""affine_mapping() should return a touple of two matrices of
certain shape
"""
matrix_x = matrix([
[-24.03457111, 10.10355666, -23.17039728, 28.48438894,
22.57322482],
[0.62716392, 20.84502664, 6.42317521, -7.66901011,
14.37923852],
[-2.60793417, 2.83532649, 2.91024821, 1.37414959,
-4.22916659]])
matrix_y = matrix([
[-29.81089477, -2.01312927, -30.5925487, 23.05985801,
11.68581751],
[-4.68879117, 23.62633294, 1.07934315, 0.57461989,
20.52800221],
[-0.51503505, 1.18377044, 0.83671471, 1.81751358,
-3.28812925]])
dim = matrix_x.shape[0]
(tu, tb) = self.scmds.combine_mds.affine_mapping(matrix_x, matrix_y)
self.assertTrue(tu.shape[0] == dim and tb.shape[0] == dim)
self.assertTrue(tu.shape[0] == tu.shape[1])
self.assertAlmostEqual(tu[0, 0], 0.966653, places=5)
self.assertAlmostEqual(tu[-1, -1], 0.994816, places=5)
self.assertAlmostEqual(tb[0, 0], -6.480975, places=5)
self.assertAlmostEqual(tb[-1, -1], 0.686521, places=5)
def test_scmds_adjust_mds_to_ref(self):
"""adjust_mds_to_ref() should return an adjusted mds solutions"""
overlap = 5
dim = 3
size = 10
fake_mds_coords_ref = self.test_matrix[:size, :dim]
fake_mds_coords_add = self.test_matrix[overlap:size + overlap, :dim]
mds_adj = self.scmds.combine_mds.adjust_mds_to_ref(fake_mds_coords_ref,
fake_mds_coords_add,
overlap)
self.assertTrue(mds_adj.shape == fake_mds_coords_add.shape)
self.assertAlmostEqual(mds_adj[0, 0], 7.526609, places=5)
self.assertAlmostEqual(mds_adj[-1, -1], 18.009350, places=5)
def test_scmds_combine_mds(self):
"""combine_mds() should merge two mds solutions
"""
overlap = 3
dim = 3
mds_coords_1 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
mds_coords_2 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
comb_mds = self.scmds.combine_mds.combine_mds(mds_coords_1,
mds_coords_2, overlap)
self.assertTrue(comb_mds.shape == (
mds_coords_1.shape[0] * 2 - overlap, dim))
self.assertAlmostEqual(comb_mds[0, 0], -3.783335, places=5)
# self.assertAlmostEqual(comb_mds[-1, -1], 0.349951)
def test_scmds_class_combinemds(self):
"""class CombineMds() should be able to join MDS solutions
"""
# tmp note
# tile1 = FULL_SYM_MATRIX[0:5, 0:5]
# tile2 = FULL_SYM_MATRIX[2:7, 2:7]
# mds_coords_1 = cmds_tzeng(tile1, 3)
# mds_coords_2 = cmds_tzeng(tile2, 3)
overlap = 3
mds_coords_1 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
mds_coords_2 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[5.18887751, -1.2130882, -0.86476508],
[-3.10404298, -0.6620052, -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[4.23608631, 0.7933192, 1.16523198]])
comb_mds = CombineMds()
comb_mds.add(mds_coords_1, overlap)
comb_mds.add(mds_coords_2, overlap)
final_mds = comb_mds.getFinalMDS()
r, c = mds_coords_1.shape
self.assertTrue(final_mds.shape == (r * 2 - overlap, c))
def setUp(self):
self.test_matrix = np.loadtxt(get_data_path('full_sym_matrix.txt'))
self.dist_func = lambda x, y: (self.test_matrix[x, y])
self.num_objects = self.test_matrix.shape[0]
self.scmds = Scmds()
def setUp(self):
self.test_matrix = np.loadtxt(get_data_path('full_sym_matrix.txt'))
self.dist_func = lambda x, y: (self.test_matrix[x, y])
self.num_objects = self.test_matrix.shape[0]
self.scmds = Scmds()