mindspore.ops.nanmedian
- mindspore.ops.nanmedian(input, axis=- 1, keepdims=False)[source]
Computes the median and indices of input in specified dimension, ignoring NaN. If all elements in the specified dimensions are NaN, the result will be NaN.
Warning
- indices does not necessarily contain the first occurrence of each median value found in the input,
unless it is unique.
- Parameters
input (Tensor) – The input tensor to calculate the median and indices.
axis (int, optional) – The dimension need to calculate median and indices. Default:
-1
, calculate the last dimension.keepdims (bool, optional) – Whether the output tensor needs to retain dimension or not. Default:
False
, not to retain dimensions.
- Returns
Tensor, the median of input along the specified dimension, has the same dtype as input.
indices (Tensor), median index, dtype is int64.
- Raises
TypeError – If dtype of input is not one of the following: int16, int32, int64, float32, float64.
TypeError – If input input is not a Tensor.
TypeError – If axis is not int.
TypeError – If keepdims is not bool.
ValueError – If axis is not in range of [-r, r) which r means the rank of input.
- Supported Platforms:
CPU
Examples
>>> import mindspore >>> from mindspore import Tensor, ops >>> x = Tensor([[0.57, 0.11, float("nan")], ... [0.38, float("nan"), float("nan")], ... [0.36, 0.16, float("nan")]], mindspore.float32) >>> y, idx = ops.nanmedian(x, axis=0, keepdims=False) >>> print(y) [0.38 0.11 nan] >>> print(idx) [1 0 0]