torch_trapz function

Trapz

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)

}