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: |
y : array_like Input array to integrate. x : array_like, optional The sample points corresponding to the dx : scalar, optional The spacing between sample points when axis : int, optional The axis along which to integrate. |
---|---|
Returns: |
trapz : float Definite integral as approximated by trapezoidal rule. |
Image [R292] 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.
[R291] | Wikipedia page: http://en.wikipedia.org/wiki/Trapezoidal_rule |
[R292] | (1, 2) Illustration image: http://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png |
>>> 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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https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.trapz.html