jax.numpy.trapz¶

jax.numpy.trapz(y, x=None, dx=1.0, axis=- 1)[source]¶

Integrate along the given axis using the composite trapezoidal rule.

LAX-backend implementation of trapz().

Original docstring below.

If x is provided, the integration happens in sequence along its elements - they are not sorted.

Integrate y (x) along each 1d slice on the given axis, compute \(\int y(x) dx\). When x is specified, this integrates along the parametric curve, computing \(\int_t y(t) dt = \int_t y(t) \left.\frac{dx}{dt}\right|_{x=x(t)} dt\).

Parameters

y (array_like) – Input array to integrate.
x (array_like, optional) – The sample points corresponding to the y values. If x is None, the sample points are assumed to be evenly spaced dx apart. The default is None.
dx (scalar, optional) – The spacing between sample points when x is None. The default is 1.
axis (int, optional) – The axis along which to integrate.

Returns

trapz – Definite integral of ‘y’ = n-dimensional array as approximated along a single axis by the trapezoidal rule. If ‘y’ is a 1-dimensional array, then the result is a float. If ‘n’ is greater than 1, then the result is an ‘n-1’ dimensional array.

Return type

float or ndarray

References

1: Wikipedia page: https://en.wikipedia.org/wiki/Trapezoidal_rule
2: Illustration image: https://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png