diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/function_base.py | 22 | ||||
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 10 |
2 files changed, 16 insertions, 16 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index fabb87adc..9690c305f 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -3070,10 +3070,13 @@ def i0(x): See Also -------- - scipy.special.iv, scipy.special.ive + scipy.special.i0, scipy.special.iv, scipy.special.ive Notes ----- + The scipy implementation is recommended over this function: it is a + proper ufunc written in C, and more than an order of magnitude faster. + We use the algorithm published by Clenshaw [1]_ and referenced by Abramowitz and Stegun [2]_, for which the function domain is partitioned into the two intervals [0,8] and (8,inf), and Chebyshev @@ -3093,21 +3096,14 @@ def i0(x): Examples -------- - >>> np.i0([0.]) - array(1.0) # may vary + >>> np.i0(0.) + array(1.0) # may vary >>> np.i0([0., 1. + 2j]) - array([ 1.00000000+0.j , 0.18785373+0.64616944j]) # may vary + array([ 1.00000000+0.j , 0.18785373+0.64616944j]) # may vary """ - x = atleast_1d(x).copy() - y = empty_like(x) - ind = (x < 0) - x[ind] = -x[ind] - ind = (x <= 8.0) - y[ind] = _i0_1(x[ind]) - ind2 = ~ind - y[ind2] = _i0_2(x[ind2]) - return y.squeeze() + x = np.abs(x) + return piecewise(x, [x <= 8.0], [_i0_1, _i0_2]) ## End of cephes code for i0 diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index a3d4c6efb..93ebabae0 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -1984,9 +1984,9 @@ class Test_I0(object): np.array(1.0634833707413234)) A = np.array([0.49842636, 0.6969809, 0.22011976, 0.0155549]) - assert_almost_equal( - i0(A), - np.array([1.06307822, 1.12518299, 1.01214991, 1.00006049])) + expected = np.array([1.06307822, 1.12518299, 1.01214991, 1.00006049]) + assert_almost_equal(i0(A), expected) + assert_almost_equal(i0(-A), expected) B = np.array([[0.827002, 0.99959078], [0.89694769, 0.39298162], @@ -2000,6 +2000,10 @@ class Test_I0(object): [1.03633899, 1.00067775], [1.03352052, 1.13557954], [1.05884290, 1.06432317]])) + # Regression test for gh-11205 + i0_0 = np.i0([0.]) + assert_equal(i0_0.shape, (1,)) + assert_array_equal(np.i0([0.]), np.array([1.])) class TestKaiser(object): |