- paddle. nanmedian ( x, axis=None, keepdim=True, name=None ) [source]
Compute the median along the specified axis, while ignoring NaNs.
If the valid count of elements is a even number, the average value of both elements in the middle is calculated as the median.
x (Tensor) – The input Tensor, it’s data type can be int32, int64, float16, float32, float64.
axis (None|int|list|tuple, optional) – The axis along which to perform median calculations
axisshould be int or list of int.
axisshould be in range [-D, D), where D is the dimensions of
axisis less than 0, it works the same way as \(axis + D\). If
axisis None, median is calculated over all elements of
x. Default is None.
keepdim (bool, optional) – Whether to reserve the reduced dimension(s) in the output Tensor. If
keepdimis True, the dimensions of the output Tensor is the same as
xexcept in the reduced dimensions(it is of size 1 in this case). Otherwise, the shape of the output Tensor is squeezed in
axis. Default is True.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.
Tensor, results of median along
x. The output dtype is the same as x.
import paddle x = paddle.to_tensor([[float('nan'), 2. , 3. ], [0. , 1. , 2. ]]) y1 = x.nanmedian() # y1 is [[2.]] y2 = x.nanmedian(0) # y2 is [[0., 1.5, 2.5]] y3 = x.nanmedian(0, keepdim=False) # y3 is [0., 1.5, 2.5] y4 = x.nanmedian((0, 1)) # y4 is [[2.]]