diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 58 |
1 files changed, 36 insertions, 22 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 710091de2..984f3086e 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1450,7 +1450,7 @@ def angle(z, deg=False): The counterclockwise angle from the positive real axis on the complex plane in the range ``(-pi, pi]``, with dtype as numpy.float64. - ..versionchanged:: 1.16.0 + .. versionchanged:: 1.16.0 This function works on subclasses of ndarray like `ma.array`. See Also @@ -2268,13 +2268,13 @@ class vectorize: def _cov_dispatcher(m, y=None, rowvar=None, bias=None, ddof=None, - fweights=None, aweights=None): + fweights=None, aweights=None, *, dtype=None): return (m, y, fweights, aweights) @array_function_dispatch(_cov_dispatcher) def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, - aweights=None): + aweights=None, *, dtype=None): """ Estimate a covariance matrix, given data and weights. @@ -2325,6 +2325,11 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, weights can be used to assign probabilities to observation vectors. .. versionadded:: 1.10 + dtype : data-type, optional + Data-type of the result. By default, the return data-type will have + at least `numpy.float64` precision. + + .. versionadded:: 1.20 Returns ------- @@ -2400,13 +2405,16 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, if m.ndim > 2: raise ValueError("m has more than 2 dimensions") - if y is None: - dtype = np.result_type(m, np.float64) - else: + if y is not None: y = np.asarray(y) if y.ndim > 2: raise ValueError("y has more than 2 dimensions") - dtype = np.result_type(m, y, np.float64) + + if dtype is None: + if y is None: + dtype = np.result_type(m, np.float64) + else: + dtype = np.result_type(m, y, np.float64) X = array(m, ndmin=2, dtype=dtype) if not rowvar and X.shape[0] != 1: @@ -2486,12 +2494,14 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, return c.squeeze() -def _corrcoef_dispatcher(x, y=None, rowvar=None, bias=None, ddof=None): +def _corrcoef_dispatcher(x, y=None, rowvar=None, bias=None, ddof=None, *, + dtype=None): return (x, y) @array_function_dispatch(_corrcoef_dispatcher) -def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue): +def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue, *, + dtype=None): """ Return Pearson product-moment correlation coefficients. @@ -2525,6 +2535,11 @@ def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue): Has no effect, do not use. .. deprecated:: 1.10.0 + dtype : data-type, optional + Data-type of the result. By default, the return data-type will have + at least `numpy.float64` precision. + + .. versionadded:: 1.20 Returns ------- @@ -2616,7 +2631,7 @@ def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue): # 2015-03-15, 1.10 warnings.warn('bias and ddof have no effect and are deprecated', DeprecationWarning, stacklevel=3) - c = cov(x, y, rowvar) + c = cov(x, y, rowvar, dtype=dtype) try: d = diag(c) except ValueError: @@ -2733,8 +2748,8 @@ def blackman(M): return array([]) if M == 1: return ones(1, float) - n = arange(0, M) - return 0.42 - 0.5*cos(2.0*pi*n/(M-1)) + 0.08*cos(4.0*pi*n/(M-1)) + n = arange(1-M, M, 2) + return 0.42 + 0.5*cos(pi*n/(M-1)) + 0.08*cos(2.0*pi*n/(M-1)) @set_module('numpy') @@ -2842,8 +2857,8 @@ def bartlett(M): return array([]) if M == 1: return ones(1, float) - n = arange(0, M) - return where(less_equal(n, (M-1)/2.0), 2.0*n/(M-1), 2.0 - 2.0*n/(M-1)) + n = arange(1-M, M, 2) + return where(less_equal(n, 0), 1 + n/(M-1), 1 - n/(M-1)) @set_module('numpy') @@ -2946,8 +2961,8 @@ def hanning(M): return array([]) if M == 1: return ones(1, float) - n = arange(0, M) - return 0.5 - 0.5*cos(2.0*pi*n/(M-1)) + n = arange(1-M, M, 2) + return 0.5 + 0.5*cos(pi*n/(M-1)) @set_module('numpy') @@ -3046,8 +3061,8 @@ def hamming(M): return array([]) if M == 1: return ones(1, float) - n = arange(0, M) - return 0.54 - 0.46*cos(2.0*pi*n/(M-1)) + n = arange(1-M, M, 2) + return 0.54 + 0.46*cos(pi*n/(M-1)) ## Code from cephes for i0 @@ -4229,10 +4244,9 @@ def meshgrid(*xi, copy=True, sparse=False, indexing='xy'): See Also -------- - index_tricks.mgrid : Construct a multi-dimensional "meshgrid" - using indexing notation. - index_tricks.ogrid : Construct an open multi-dimensional "meshgrid" - using indexing notation. + mgrid : Construct a multi-dimensional "meshgrid" using indexing notation. + ogrid : Construct an open multi-dimensional "meshgrid" using indexing + notation. Examples -------- |