numpy.trapz
-
numpy.trapz(y, x=None, dx=1.0, axis=-1)
[source] -
Integrate along the given axis using the composite trapezoidal rule.
Integrate
y
(x
) along given axis.- Parameters
-
-
yarray_like
-
Input array to integrate.
-
xarray_like, optional
-
The sample points corresponding to the
y
values. Ifx
is None, the sample points are assumed to be evenly spaceddx
apart. The default is None. -
dxscalar, optional
-
The spacing between sample points when
x
is None. The default is 1. -
axisint, optional
-
The axis along which to integrate.
-
- Returns
-
-
trapzfloat
-
Definite integral as approximated by trapezoidal rule.
-
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 withx
array or withdx
scalar. Return value will be equal to combined area under the red lines.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
Examples
>>> np.trapz([1,2,3]) 4.0 >>> np.trapz([1,2,3], x=[4,6,8]) 8.0 >>> np.trapz([1,2,3], dx=2) 8.0 >>> a = np.arange(6).reshape(2, 3) >>> a array([[0, 1, 2], [3, 4, 5]]) >>> np.trapz(a, axis=0) array([1.5, 2.5, 3.5]) >>> np.trapz(a, axis=1) array([2., 8.])
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.trapz.html