def test_contrast3(self):
P = np.dot(self.X, np.linalg.pinv(self.X))
resid = np.identity(40) - P
noise = np.dot(resid, numpy.random.standard_normal((40, 5)))
term = np.column_stack((noise, self.X[:, 2]))
c = Contrast(term, self.X)
assert_equal(c.contrast_matrix.shape, (10, ))
def test_estimable(self):
X2 = np.column_stack((self.X, self.X[:, 5]))
c = Contrast(self.X[:, 5], X2)
def test_contrast2(self):
zero = np.zeros((40, ))
term = np.column_stack((zero, self.X[:, 2]))
c = Contrast(term, self.X)
test_contrast = [0] * 2 + [1] + [0] * 7
assert_almost_equal(test_contrast, c.contrast_matrix)
def test_contrast1(self):
term = np.column_stack((self.X[:, 0], self.X[:, 2]))
c = Contrast(term, self.X)
test_contrast = [[1] + [0] * 9, [0] * 2 + [1] + [0] * 7]
assert_almost_equal(test_contrast, c.contrast_matrix)