(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.
dx
(float) The distance between points at which y is sampled.
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.
# NOT RUN {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)
}
# }