diff options
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 16 |
1 files changed, 14 insertions, 2 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 61113ae7a..f52eb5fbe 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -466,7 +466,7 @@ class TestGradient(TestCase): '1910-10-12', '1910-12-12', '1912-12-12'], dtype='datetime64[D]') dx = np.array( - [-5, -3, 0, 31, 61, 396, 731], + [-7, -3, 0, 31, 61, 396, 1066], dtype='timedelta64[D]') assert_array_equal(gradient(x), dx) assert_(dx.dtype == np.dtype('timedelta64[D]')) @@ -477,11 +477,23 @@ class TestGradient(TestCase): [-5, -3, 10, 12, 61, 321, 300], dtype='timedelta64[D]') dx = np.array( - [2, 7, 7, 25, 154, 119, -21], + [-3, 7, 7, 25, 154, 119, -161], dtype='timedelta64[D]') assert_array_equal(gradient(x), dx) assert_(dx.dtype == np.dtype('timedelta64[D]')) + def test_second_order_accurate(self): + # Testing that the relative numerical error is less that 3% for + # this example problem. This corresponds to second order + # accurate finite differences for all interior and boundary + # points. + x = np.linspace(0, 1, 10) + dx = x[1] - x[0] + y = 2 * x ** 3 + 4 * x ** 2 + 2 * x + analytical = 6 * x ** 2 + 8 * x + 2 + num_error = np.abs((np.gradient(y, dx) / analytical) - 1) + assert_(np.all(num_error < 0.03) == True) + class TestAngle(TestCase): def test_basic(self): |