torch_trapz: Trapz

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Trapz

Description

Trapz

Usage

torch_trapz(y, dx = 1L, x, dim = -1L)

Arguments

y	(Tensor) The values of the function to integrate
dx	(float) The distance between points at which y is sampled.
x	(Tensor) The points at which the function y is sampled. If x is not in ascending order, intervals on which it is decreasing contribute negatively to the estimated integral (i.e., the convention \int_a^b f = -\int_b^a f is followed).
dim	(int) The dimension along which to integrate. By default, use the last dimension.

trapz(y, x, *, dim=-1) -> Tensor

Estimate \int y\,dx along dim, using the trapezoid rule.

trapz(y, *, dx=1, dim=-1) -> Tensor

As above, but the sample points are spaced uniformly at a distance of dx.

Examples

if (torch_is_installed()) {

y = torch_randn(list(2, 3))
y
x = torch_tensor(matrix(c(1, 3, 4, 1, 2, 3), ncol = 3, byrow=TRUE))
torch_trapz(y, x = x)

}

torch documentation built on June 7, 2023, 6:19 p.m.