lucid.histogramdd¶

lucid.histogramdd(a: Tensor, /, bins: int | list[int], range: list[tuple[float, float]], density: bool = False) → tuple[Tensor, Tensor]¶

Function Signature¶

def histogramdd(
    a: Tensor,
    /,
    bins: int | list[int],
    range: list[tuple[float, float]],
    density: bool = False,
) -> tuple[Tensor, Tensor]

Parameters¶

a (Tensor): A 2D tensor of shape (N, D) representing N D-dimensional samples.
bins (int | list[int]): Number of bins for each dimension. If an integer is provided, it will be used for all dimensions.
range (list[tuple[float, float]]): Lower and upper range of each dimension.
density (bool, optional): If True, the result is normalized to form a probability density.

Returns¶

Tensor: An N-dimensional tensor representing the histogram.
Tensor: A 2D tensor of shape (D, B+1) containing the bin edges for each dimension.

Example¶

>>> x = Tensor([[0.5, -0.2], [1.0, 0.3], [-0.8, 0.7]])
>>> hist, edges = histogramdd(x, bins=[4, 4], range=[(-1, 1), (-1, 1)])
>>> hist, edges = histogramdd(x, bins=4, range=[(-1, 1), (-1, 1)])