def setUp(self):
self.dir_ = data_dir + "/space_test_resources/"
self.init_test_cases = [(DenseMatrix(np.array([[1,2],[3,4]])),
["car", "man"],
["feat1", "feat2"],
{"man":1, "car":0},
{"feat1":0, "feat2":1},
[ScalingOperation(EpmiWeighting())]),
(DenseMatrix(np.array([[1,2],[3,4]])),
["car", "man"],
[],
{"man":1, "car":0},
{},
[ScalingOperation(EpmiWeighting())])]
self.m1 = np.array([[1,2,3]])
self.row1 = ["a"]
self.row2 = ["a", "b", "c"]
self.ft1 = ["f1","f2","f3"]
self.space1 = Space(DenseMatrix(self.m1),self.row1, self.ft1)
self.x = np.mat([[1,2,3],[2,4,6],[4,675,43]])
self.us = np.mat([[ 2.19272110e+00, 3.03174768e+00],
[ 4.38544220e+00, 6.06349536e+00],
[ 6.76369708e+02, -4.91431927e-02]])
self.space2 = Space(DenseMatrix(self.x), self.row2, self.ft1)
def test_apply_weighting_operation(self):
test_cases = [(self.m1, np.array([[0,0,0]])),
(self.m2, np.array([[0]]))]
w = PpmiWeighting()
for in_mat, expected_mat in test_cases:
op = ScalingOperation(w)
tmp_mat = in_mat.copy()
out_mat = op.apply(DenseMatrix(in_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
np.testing.assert_array_equal(in_mat, tmp_mat)
self.assertRaises(IllegalStateError, op.apply, DenseMatrix(in_mat))
def test_project_weighting_operation(self):
test_cases = [(self.m1, self.m3,
np.array([[0.69314718,0,0]])),
(self.m2, self.m4, np.array([[0]]))]
w = PpmiWeighting()
for (core_mat, per_mat, expected_mat) in test_cases:
op = ScalingOperation(w)
tmp_mat = per_mat.copy()
self.assertRaises(IllegalStateError, op.project,
DenseMatrix(per_mat))
op.apply(DenseMatrix(core_mat))
out_mat = op.project(DenseMatrix(per_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
np.testing.assert_array_equal(per_mat, tmp_mat)
out_mat = op.project(DenseMatrix(per_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
def create_operation(self):
return ScalingOperation(self)
