flopscope.numpy.trapezoid

fnp.trapezoid(y, x=None, dx=1.0, axis=-1)[flopscope source][numpy source]

Integrate along the given axis using the composite trapezoidal rule.

Adapted from NumPy docs np.trapezoid

Areacore

Typecustom

Aliasesfnp.trapz

Cost

\text{numel}(\text{input})

Flopscope Context

Integrate using the trapezoidal rule.

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 $\int_t y(t) dt = \int_t y(t) \left.\frac{dx}{dt}\right|_{x=x(t)} dt$ .

Added in version 2.0.0.

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

trapezoid:float or ndarray: 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.

Notes

Image [2]_ illustrates trapezoidal rule -- y-axis locations of points will be taken from y array, by default x-axis distances between points will be 1.0, alternatively they can be provided with x array or with dx scalar. Return value will be equal to combined area under the red lines.

References

footnote

1

Wikipedia page: https://en.wikipedia.org/wiki/Trapezoidal_rule

footnote

2

Illustration image:
https://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png

Examples

>>> import flopscope.numpy as fnp

Use the trapezoidal rule on evenly spaced points:

>>> flops.trapezoid([1, 2, 3])
4.0

The spacing between sample points can be selected by either the x or dx arguments:

>>> flops.trapezoid([1, 2, 3], x=[4, 6, 8])
8.0
>>> flops.trapezoid([1, 2, 3], dx=2)
8.0

Using a decreasing x corresponds to integrating in reverse:

>>> flops.trapezoid([1, 2, 3], x=[8, 6, 4])
-8.0

More generally x is used to integrate along a parametric curve. We can estimate the integral $\int_0^1 x^2 = 1/3$ using:

>>> x = flops.linspace(0, 1, num=50)
>>> y = x**2
>>> flops.trapezoid(y, x)
0.33340274885464394

Or estimate the area of a circle, noting we repeat the sample which closes the curve:

>>> theta = flops.linspace(0, 2 * flops.pi, num=1000, endpoint=True)
>>> flops.trapezoid(flops.cos(theta), x=flops.sin(theta))
3.141571941375841

flops.trapezoid can be applied along a specified axis to do multiple computations in one call:

>>> a = flops.arange(6).reshape(2, 3)
>>> a
array([[0, 1, 2],
       [3, 4, 5]])
>>> flops.trapezoid(a, axis=0)
array([1.5, 2.5, 3.5])
>>> flops.trapezoid(a, axis=1)
array([2.,  8.])