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Module « scipy.integrate »

Fonction cumulative_trapezoid - module scipy.integrate

Signature de la fonction cumulative_trapezoid

def cumulative_trapezoid(y, x=None, dx=1.0, axis=-1, initial=None) 

Description

help(scipy.integrate.cumulative_trapezoid)

Cumulatively integrate y(x) using the composite trapezoidal rule.

Parameters
----------
y : array_like
    Values to integrate.
x : array_like, optional
    The coordinate to integrate along. If None (default), use spacing `dx`
    between consecutive elements in `y`.
dx : float, optional
    Spacing between elements of `y`. Only used if `x` is None.
axis : int, optional
    Specifies the axis to cumulate. Default is -1 (last axis).
initial : scalar, optional
    If given, insert this value at the beginning of the returned result.
    0 or None are the only values accepted. Default is None, which means
    `res` has one element less than `y` along the axis of integration.

Returns
-------
res : ndarray
    The result of cumulative integration of `y` along `axis`.
    If `initial` is None, the shape is such that the axis of integration
    has one less value than `y`. If `initial` is given, the shape is equal
    to that of `y`.

See Also
--------
numpy.cumsum, numpy.cumprod
cumulative_simpson : cumulative integration using Simpson's 1/3 rule
quad : adaptive quadrature using QUADPACK
fixed_quad : fixed-order Gaussian quadrature
dblquad : double integrals
tplquad : triple integrals
romb : integrators for sampled data

Examples
--------
>>> from scipy import integrate
>>> import numpy as np
>>> import matplotlib.pyplot as plt

>>> x = np.linspace(-2, 2, num=20)
>>> y = x
>>> y_int = integrate.cumulative_trapezoid(y, x, initial=0)
>>> plt.plot(x, y_int, 'ro', x, y[0] + 0.5 * x**2, 'b-')
>>> plt.show()

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