def test_hstack(self): import numpypy as np a = np.array((1, 2, 3)) b = np.array((2, 3, 4)) c = np.hstack((a, b)) assert np.array_equal(c, [1, 2, 3, 2, 3, 4]) a = np.array([[1], [2], [3]]) b = np.array([[2], [3], [4]]) c = np.hstack((a, b)) assert np.array_equal(c, [[1, 2], [2, 3], [3, 4]]) for shape1, shape2 in [[(1, 2), (1, 3)], [(4, 2), (4, 3)]]: a, b = np.ones(shape1), np.ones(shape2) assert np.all(np.hstack((a, b)) == np.ones((a.shape[0], a.shape[1] + b.shape[1]))) #skip("https://bugs.pypy.org/issue1394") for shape1, shape2 in [[(2, 3, 4), (2, 7, 4)], [(1, 4, 7), (1, 10, 7)], [(1, 4, 7), (1, 0, 7)], [(1, 0, 7), (1, 0, 7)]]: a, b = np.ones(shape1), np.ones(shape2) assert np.all(np.hstack((a, b)) == np.ones((a.shape[0], a.shape[1] + b.shape[1], a.shape[2])))
def add_bias(A): return np.hstack(( np.ones((A.shape[0],1)), A )) # Add 1 as bias.
def add_bias(A): return np.hstack((np.ones((A.shape[0], 1)), A)) # Add 1 as bias.