numpy.trapz — NumPy v1.15 Manual (original) (raw)
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 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. |
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| Returns: | trapz : float 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 with x array or with dx scalar. Return value will be equal to combined area under the red lines.
References
| [1] | Wikipedia page: http://en.wikipedia.org/wiki/Trapezoidal_rule |
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| [2] | (1, 2) Illustration image:http://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png |
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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.])