def test_normalize_condensed_matrix(self):
condensed = CondensedDistanceMatrix([ 1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6,2.2, 2.])
expected = CondensedDistanceMatrix([0.0, 0.47, 1.0, 0.83, 0.47, 0.91, 0.76, 0.35, 0.16, 0.13])
minmax = condensed.get_minimum_and_maximum()
condensed.normalize(minmax[0], minmax[1])
for i in range(len(condensed.get_data())):
self.assertAlmostEqual(condensed.get_data()[i],expected.get_data()[i],2)
def test_normalize_condensed_matrix(self):
condensed = CondensedDistanceMatrix(
[1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6, 2.2, 2.])
expected = CondensedDistanceMatrix(
[0.0, 0.47, 1.0, 0.83, 0.47, 0.91, 0.76, 0.35, 0.16, 0.13])
minmax = condensed.get_minimum_and_maximum()
condensed.normalize(minmax[0], minmax[1])
for i in range(len(condensed.get_data())):
self.assertAlmostEqual(condensed.get_data()[i],
expected.get_data()[i], 2)
def test_load_condensed_matrix(self):
matrix_string = """1.0
4.5 8.5
7.2 4.5 7.8
6.7 3.6 2.2 2.0
"""
expected_matrix = CondensedDistanceMatrix([ 1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6,2.2, 2.])
input = cStringIO.StringIO(matrix_string)
loaded_matrix = load_condensed_matrix(input)
for i in range(len(expected_matrix.get_data())):
self.assertAlmostEqual(expected_matrix.get_data()[i],\
loaded_matrix.get_data()[i],3)
def test_load_condensed_matrix(self):
matrix_string = """1.0
4.5 8.5
7.2 4.5 7.8
6.7 3.6 2.2 2.0
"""
expected_matrix = CondensedDistanceMatrix(
[1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6, 2.2, 2.])
input = cStringIO.StringIO(matrix_string)
loaded_matrix = load_condensed_matrix(input)
for i in range(len(expected_matrix.get_data())):
self.assertAlmostEqual(expected_matrix.get_data()[i],\
loaded_matrix.get_data()[i],3)
def test_item_access(self):
condensed_matrix_1 = CondensedDistanceMatrix(
[1.0, 4.5, 7.2, 8.5, 4.5, 7.8])
condensed_matrix_2 = CondensedDistanceMatrix([.0] * 6)
complete_matrix = [[0.0, 1.0, 4.5, 7.2], [1.0, 0.0, 8.5, 4.5],
[4.5, 8.5, 0.0, 7.8], [7.2, 4.5, 7.8, 0.0]]
row_len = condensed_matrix_1.row_length
for i in range(row_len):
for j in range(row_len):
condensed_matrix_2[i, j] = complete_matrix[i][j]
## The access for a complete and a condensed matrix is exactly the same
for i in range(row_len):
for j in range(row_len):
self.assertEquals(condensed_matrix_1[i, j],
complete_matrix[i][j])
## And we can build a condensed matrix as a complete matrix
self.assertItemsEqual(condensed_matrix_1.get_data(),
condensed_matrix_2.get_data())
def test_item_access(self):
condensed_matrix_1 = CondensedDistanceMatrix([1.0, 4.5,7.2,
8.5, 4.5,
7.8])
condensed_matrix_2 = CondensedDistanceMatrix([.0]*6)
complete_matrix = [[0.0, 1.0, 4.5, 7.2],
[1.0, 0.0, 8.5, 4.5],
[4.5, 8.5, 0.0, 7.8],
[7.2, 4.5, 7.8, 0.0]]
row_len = condensed_matrix_1.row_length
for i in range(row_len):
for j in range(row_len):
condensed_matrix_2[i,j] = complete_matrix[i][j]
## The access for a complete and a condensed matrix is exactly the same
for i in range(row_len):
for j in range(row_len):
self.assertEquals(condensed_matrix_1[i,j],complete_matrix[i][j])
## And we can build a condensed matrix as a complete matrix
self.assertItemsEqual(condensed_matrix_1.get_data(), condensed_matrix_2.get_data())
def test_data_sharing(self):
mylist = [1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6, 2.2, 2.]
myarray = np.array([1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6, 2.2, 2.])
mylistaarray = np.array(mylist)
condensed1 = CondensedDistanceMatrix(mylist)
condensed2 = CondensedDistanceMatrix(myarray)
condensed3 = CondensedDistanceMatrix(mylistaarray)
mylist[5] = 0.
self.assertEqual(False, mylist[5] == condensed1.get_data()[5])
myarray[5] = 0.
self.assertEqual(False, myarray[5] == condensed2.get_data()[5])
mylistaarray[5] = 0.
self.assertEqual(False, mylistaarray[5] == condensed3.get_data()[5])
mycontents = condensed3.get_data()
mycontents[5] = 0.
self.assertEqual(True, mycontents[5] == condensed3.get_data()[5] and\
condensed3.get_data()[5] == 0.)
def test_data_sharing(self):
mylist = [ 1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6,2.2, 2.]
myarray = np.array([ 1., 4.5, 8.5, 7.2, 4.5, 7.8, 6.7, 3.6,2.2, 2.])
mylistaarray = np.array(mylist)
condensed1 = CondensedDistanceMatrix(mylist)
condensed2 = CondensedDistanceMatrix(myarray)
condensed3 = CondensedDistanceMatrix(mylistaarray)
mylist[5] = 0.
self.assertEqual(False, mylist[5] == condensed1.get_data()[5])
myarray[5] = 0.
self.assertEqual(False, myarray[5] == condensed2.get_data()[5])
mylistaarray[5] = 0.
self.assertEqual(False, mylistaarray[5] == condensed3.get_data()[5])
mycontents = condensed3.get_data()
mycontents[5] = 0.
self.assertEqual(True, mycontents[5] == condensed3.get_data()[5] and\
condensed3.get_data()[5] == 0.)