nums.numpy.nansum

nums.numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=False)[source]

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

This docstring was copied from numpy.nansum.

Some inconsistencies with the NumS version may exist.

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

Parameters

  • a (BlockArray) – 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.

  • out (BlockArray, 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.

  • keepdims (bool, optional) – 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. If the value is anything but the default, then keepdims will be passed through to the mean or sum methods of sub-classes of BlockArray. If the sub-classes methods does not implement keepdims any exceptions will be raised.

Returns

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.

Return type

BlockArray.

See also

numpy.sum

Sum across array propagating NaNs.

isnan

Show which elements are NaN.

isfinite

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

Notes

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

‘out’ is currently not supported.

Examples

The doctests shown below are copied from NumPy. They won’t show the correct result until you operate get().

>>> nps.nansum(nps.array([1])).get()  
array(1)
>>> nps.nansum(nps.array([1, nps.nan])).get()  
array(1.)
>>> a = nps.array([[1, 1], [1, nps.nan]])  
>>> nps.nansum(a).get()  
array(3.)
>>> nps.nansum(a, axis=0).get()  
array([2.,  1.])
>>> nps.nansum(nps.array([1, nps.nan, nps.inf])).get()  
array(inf)
>>> nps.nansum(nps.array([1, nps.nan, nps.NINF])).get()  
array(-inf)

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