nanmean

→Tensor

nanmean(x: Tensor, dim: int | Sequence[int] | None = ..., keepdim: bool = ...)

Mean of the tensor, ignoring NaN entries.

A NaN-safe variant of lucid.mean. Both the numerator (sum) and the denominator (element count) are computed only over the non-NaN entries.

xTensor

Input tensor (any floating-point dtype).

dimint | Sequence[int] | None

Axis or axes along which to take the mean. None (default) reduces over the entire tensor.

keepdimbool

If True, retains the reduced dimensions with size 1. Defaults to False.

Tensor

Reduced tensor.

With $\mathcal{S}$ the set of indices being reduced and $\mathbb{1}_i = 1 - \mathbb{1}_{x_i \text{ is NaN}}$ ,

\text{nanmean}(x) = \frac{\sum_{i \in \mathcal{S}} \mathbb{1}_i \cdot x_i} {\sum_{i \in \mathcal{S}} \mathbb{1}_i}.

A slice that is entirely NaN produces 0 / 0 = NaN; this is the standard convention. The gradient at NaN positions is zero.

>>> import lucid
>>> import math
>>> x = lucid.tensor([1.0, math.nan, 3.0])
>>> lucid.nanmean(x)
Tensor(2.)