xorbits.numpy.nansum#

xorbits.numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=None, combine_size=None)[源代码]#

Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.

In NumPy versions <= 1.9.0 Nan is returned for slices that are all-NaN or empty. In later versions zero is returned.

参数

  • a (array_like) – Array containing numbers whose sum is desired. If a is not an array, a conversion is attempted.

  • axis ({int, tuple of int, None}, optional) – Axis or axes along which the sum is computed. The default is to compute the sum of the flattened array.

  • dtype (data-type, optional) –

    The type of the returned array and of the accumulator in which the elements are summed. By default, the dtype of a is used. An exception is when a has an integer type with less precision than the platform (u)intp. In that case, the default will be either (u)int32 or (u)int64 depending on whether the platform is 32 or 64 bits. For inexact inputs, dtype must be inexact.

    1.8.0(numpy) 新版功能.

  • out (ndarray, optional) –

    Alternate output array in which to place the result. The default is None. If provided, it must have the same shape as the expected output, but the type will be cast if necessary. See ufuncs-output-type for more details. The casting of NaN to integer can yield unexpected results.

    1.8.0(numpy) 新版功能.

  • keepdims – If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original a.

initialscalar, optional (Not supported yet)

Starting value for the sum. See ~numpy.ufunc.reduce for details.

1.22.0(numpy) 新版功能.

wherearray_like of bool, optional (Not supported yet)

Elements to include in the sum. See ~numpy.ufunc.reduce for details.

1.22.0(numpy) 新版功能.

返回

nansum – A new array holding the result is returned unless out is specified, in which it is returned. The result has the same size as a, and the same shape as a if axis is not None or a is a 1-d array.

返回类型

ndarray.

参见

numpy.sum

Sum across array propagating NaNs.

isnan

Show which elements are NaN.

isfinite

Show which elements are not NaN or +/-inf.

提示

If both positive and negative infinity are present, the sum will be Not A Number (NaN).

实际案例

>>> np.nansum(1)  
1
>>> np.nansum([1])  
1
>>> np.nansum([1, np.nan])  
1.0
>>> a = np.array([[1, 1], [1, np.nan]])  
>>> np.nansum(a)  
3.0
>>> np.nansum(a, axis=0)  
array([2.,  1.])
>>> np.nansum([1, np.nan, np.inf])  
inf
>>> np.nansum([1, np.nan, np.NINF])  
-inf
>>> from numpy.testing import suppress_warnings  
>>> with suppress_warnings() as sup:  
...     sup.filter(RuntimeWarning)
...     np.nansum([1, np.nan, np.inf, -np.inf]) # both +/- infinity present
nan
combine_size: int, optional

The number of chunks to combine.

This docstring was copied from numpy.