diff options
Diffstat (limited to 'numpy/linalg/tests')
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index dae4ef61e..3f3bf9f70 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -1930,6 +1930,41 @@ class TestMultiDot: # the result should be a scalar assert_equal(multi_dot([A1d, B, C, D1d]).shape, ()) + def test_three_arguments_and_out(self): + # multi_dot with three arguments uses a fast hand coded algorithm to + # determine the optimal order. Therefore test it separately. + A = np.random.random((6, 2)) + B = np.random.random((2, 6)) + C = np.random.random((6, 2)) + + out = np.zeros((6, 2)) + ret = multi_dot([A, B, C], out=out) + assert out is ret + assert_almost_equal(out, A.dot(B).dot(C)) + assert_almost_equal(out, np.dot(A, np.dot(B, C))) + + def test_two_arguments_and_out(self): + # separate code path with two arguments + A = np.random.random((6, 2)) + B = np.random.random((2, 6)) + out = np.zeros((6, 6)) + ret = multi_dot([A, B], out=out) + assert out is ret + assert_almost_equal(out, A.dot(B)) + assert_almost_equal(out, np.dot(A, B)) + + def test_dynamic_programing_optimization_and_out(self): + # multi_dot with four or more arguments uses the dynamic programing + # optimization and therefore deserve a separate test + A = np.random.random((6, 2)) + B = np.random.random((2, 6)) + C = np.random.random((6, 2)) + D = np.random.random((2, 1)) + out = np.zeros((6, 1)) + ret = multi_dot([A, B, C, D], out=out) + assert out is ret + assert_almost_equal(out, A.dot(B).dot(C).dot(D)) + def test_dynamic_programming_logic(self): # Test for the dynamic programming part # This test is directly taken from Cormen page 376. |
