Trapz

## 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, *, 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_tensor
#> -0.5979
#> 1.2176
#> [ CPUFloatType{2} ]
```