nancumsum(a, axis=None, dtype=None)¶
Return the cumulative sum of array elements over a given axis treating Not a Numbers (NaNs) as zero. The cumulative sum does not change when NaNs are encountered and leading NaNs are replaced by zeros.
Zeros are returned for slices that are all-NaN or empty.
bool, the result dtype will be elevated to
a (Tensor) – Input tensor.
axis (int, optional) – Axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array.
mindspore.dtype, optional) – If not specified, stay the same as a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.
- Supported Platforms:
>>> import mindspore.numpy as np >>> a = np.array([[1, 2], [3, np.nan]]) >>> output = np.nancumsum(a) >>> print(output) [1. 3. 6. 6.] >>> output = np.nancumsum(a, axis=0) >>> print(output) [[1. 2.] [4. 2.]] >>> output = np.nancumsum(a, axis=1) >>> print(output) [[1. 3.] [3. 3.]]