diff options
Diffstat (limited to 'numpy/lib')
| -rw-r--r-- | numpy/lib/function_base.py | 12 | ||||
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 51 |
2 files changed, 36 insertions, 27 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 3f49af5f1..b2ec9bb5a 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1846,8 +1846,8 @@ def cov(m, y=None, rowvar=1, bias=0, ddof=None): ddof : int, optional .. versionadded:: 1.5 If not ``None`` normalization is by ``(N - ddof)``, where ``N`` is - the number of observations. When defined, ``ddof`` overrides the - value implied by ``bias``. The default value is ``None``. + the number of observations; this overrides the value implied by + ``bias``. The default value is ``None``. Returns ------- @@ -1893,6 +1893,10 @@ def cov(m, y=None, rowvar=1, bias=0, ddof=None): 11.71 """ + # Check inputs + if ddof is not None and ddof != int(ddof): + raise ValueError("ddof must be integer") + X = array(m, ndmin=2, dtype=float) if X.shape[0] == 1: rowvar = 1 @@ -1961,8 +1965,8 @@ def corrcoef(x, y=None, rowvar=1, bias=0, ddof=None): ddof : {None, int}, optional .. versionadded:: 1.5 If not ``None`` normalization is by ``(N - ddof)``, where ``N`` is - the number of observations. When defined, ``ddof`` overrides the - value implied by ``bias``. The default value is ``None``. + the number of observations; this overrides the value implied by + ``bias``. The default value is ``None``. Returns ------- diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 5d0f8aa45..037e8043a 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -821,30 +821,35 @@ class TestNanFunctsIntTypes(TestCase): class TestCorrCoef(TestCase): + A = array([[ 0.15391142, 0.18045767, 0.14197213], + [ 0.70461506, 0.96474128, 0.27906989], + [ 0.9297531 , 0.32296769, 0.19267156]]) + B = array([[ 0.10377691, 0.5417086 , 0.49807457], + [ 0.82872117, 0.77801674, 0.39226705], + [ 0.9314666 , 0.66800209, 0.03538394]]) + res1 = array([[ 1. , 0.9379533 , -0.04931983], + [ 0.9379533 , 1. , 0.30007991], + [-0.04931983, 0.30007991, 1. ]]) + res2 = array([[ 1. , 0.9379533 , -0.04931983, + 0.30151751, 0.66318558, 0.51532523], + [ 0.9379533 , 1. , 0.30007991, + - 0.04781421, 0.88157256, 0.78052386], + [-0.04931983, 0.30007991, 1. , + - 0.96717111, 0.71483595, 0.83053601], + [ 0.30151751, -0.04781421, -0.96717111, + 1. , -0.51366032, -0.66173113], + [ 0.66318558, 0.88157256, 0.71483595, + - 0.51366032, 1. , 0.98317823], + [ 0.51532523, 0.78052386, 0.83053601, + - 0.66173113, 0.98317823, 1. ]]) + def test_simple(self): - A = array([[ 0.15391142, 0.18045767, 0.14197213], - [ 0.70461506, 0.96474128, 0.27906989], - [ 0.9297531 , 0.32296769, 0.19267156]]) - B = array([[ 0.10377691, 0.5417086 , 0.49807457], - [ 0.82872117, 0.77801674, 0.39226705], - [ 0.9314666 , 0.66800209, 0.03538394]]) - assert_almost_equal(corrcoef(A), - array([[ 1. , 0.9379533 , -0.04931983], - [ 0.9379533 , 1. , 0.30007991], - [-0.04931983, 0.30007991, 1. ]])) - assert_almost_equal(corrcoef(A, B), - array([[ 1. , 0.9379533 , -0.04931983, - 0.30151751, 0.66318558, 0.51532523], - [ 0.9379533 , 1. , 0.30007991, - - 0.04781421, 0.88157256, 0.78052386], - [-0.04931983, 0.30007991, 1. , - - 0.96717111, 0.71483595, 0.83053601], - [ 0.30151751, -0.04781421, -0.96717111, - 1. , -0.51366032, -0.66173113], - [ 0.66318558, 0.88157256, 0.71483595, - - 0.51366032, 1. , 0.98317823], - [ 0.51532523, 0.78052386, 0.83053601, - - 0.66173113, 0.98317823, 1. ]])) + assert_almost_equal(corrcoef(self.A), self.res1) + assert_almost_equal(corrcoef(self.A, self.B), self.res2) + + def test_ddof(self): + assert_almost_equal(corrcoef(self.A, ddof=-1), self.res1) + assert_almost_equal(corrcoef(self.A, self.B, ddof=-1), self.res2) class Test_i0(TestCase): |