def test_train(self):
a1_mat = DenseMatrix(np.mat([[3,4],[5,6]]))
a2_mat = DenseMatrix(np.mat([[1,2],[3,4]]))
train_data = [("a1", "man", "a1_man"),
("a2", "car", "a2_car"),
("a1", "boy", "a1_boy"),
("a2", "boy", "a2_boy")
]
n_mat = DenseMatrix(np.mat([[13,21],[3,4],[5,6]]))
n_space = Space(n_mat, ["man", "car", "boy"], self.ft)
an1_mat = (a1_mat * n_mat.transpose()).transpose()
an2_mat = (a2_mat * n_mat.transpose()).transpose()
an_mat = an1_mat.vstack(an2_mat)
an_space = Space(an_mat, ["a1_man","a1_car","a1_boy","a2_man","a2_car","a2_boy"], self.ft)
#test train
model = LexicalFunction(learner=LstsqRegressionLearner(intercept=False))
model._MIN_SAMPLES = 1
model.train(train_data, n_space, an_space)
a_space = model.function_space
a1_mat.reshape((1,4))
np.testing.assert_array_almost_equal(a1_mat.mat,
a_space.cooccurrence_matrix.mat[0])
a2_mat.reshape((1,4))
np.testing.assert_array_almost_equal(a2_mat.mat,
a_space.cooccurrence_matrix.mat[1])
self.assertListEqual(a_space.id2row, ["a1", "a2"])
self.assertTupleEqual(a_space.element_shape, (2,2))
#test compose
a1_mat = DenseMatrix(np.mat([[3,4,5,6]]))
a2_mat = DenseMatrix(np.mat([[1,2,3,4]]))
a_mat = a1_mat.vstack(a2_mat)
a_space = Space(a_mat, ["a1", "a2"], [], element_shape=(2,2))
model = LexicalFunction(function_space=a_space)
model._MIN_SAMPLES = 1
comp_space = model.compose(train_data, n_space)
self.assertListEqual(comp_space.id2row, ["a1_man", "a2_car", "a1_boy", "a2_boy"])
self.assertListEqual(comp_space.id2column, [])
self.assertEqual(comp_space.element_shape, (2,))
np.testing.assert_array_almost_equal(comp_space.cooccurrence_matrix.mat,
an_mat[[0,4,2,5]].mat, 8)
def test_train(self):
a1_mat = DenseMatrix(np.mat([[3, 4], [5, 6]]))
a2_mat = DenseMatrix(np.mat([[1, 2], [3, 4]]))
train_data = [("a1", "man", "a1_man"),
("a2", "car", "a2_car"),
("a1", "boy", "a1_boy"),
("a2", "boy", "a2_boy")
]
n_mat = DenseMatrix(np.mat([[13, 21], [3, 4], [5, 6]]))
n_space = Space(n_mat, ["man", "car", "boy"], self.ft)
an1_mat = (a1_mat * n_mat.transpose()).transpose()
an2_mat = (a2_mat * n_mat.transpose()).transpose()
an_mat = an1_mat.vstack(an2_mat)
an_space = Space(an_mat, ["a1_man", "a1_car", "a1_boy", "a2_man", "a2_car", "a2_boy"], self.ft)
#test train
model = LexicalFunction(learner=LstsqRegressionLearner(intercept=False))
model.train(train_data, n_space, an_space)
a_space = model.function_space
a1_mat.reshape((1, 4))
np.testing.assert_array_almost_equal(a1_mat.mat,
a_space.cooccurrence_matrix.mat[0])
a2_mat.reshape((1, 4))
np.testing.assert_array_almost_equal(a2_mat.mat,
a_space.cooccurrence_matrix.mat[1])
self.assertListEqual(a_space.id2row, ["a1", "a2"])
self.assertTupleEqual(a_space.element_shape, (2, 2))
#test compose
a1_mat = DenseMatrix(np.mat([[3, 4, 5, 6]]))
a2_mat = DenseMatrix(np.mat([[1, 2, 3, 4]]))
a_mat = a1_mat.vstack(a2_mat)
a_space = Space(a_mat, ["a1", "a2"], [], element_shape=(2, 2))
model = LexicalFunction(function_space=a_space)
comp_space = model.compose(train_data, n_space)
self.assertListEqual(comp_space.id2row, ["a1_man", "a2_car", "a1_boy", "a2_boy"])
self.assertListEqual(comp_space.id2column, [])
self.assertEqual(comp_space.element_shape, (2,))
np.testing.assert_array_almost_equal(comp_space.cooccurrence_matrix.mat,
an_mat[[0, 4, 2, 5]].mat, 8)
