# scipy.integrate.romb¶

scipy.integrate.romb(y, dx=1.0, axis=-1, show=False)[source]

Romberg integration using samples of a function.

Parameters: y : array_like A vector of 2**k + 1 equally-spaced samples of a function. dx : float, optional The sample spacing. Default is 1. axis : int, optional The axis along which to integrate. Default is -1 (last axis). show : bool, optional When y is a single 1-D array, then if this argument is True print the table showing Richardson extrapolation from the samples. Default is False. romb : ndarray The integrated result for axis.

quad
romberg
quadrature
fixed_quad
dblquad
double integrals
tplquad
triple integrals
simps
integrators for sampled data
cumtrapz
cumulative integration for sampled data
ode
ODE integrators
odeint
ODE integrators

Examples

>>> from scipy import integrate
>>> x = np.arange(10, 14.25, 0.25)
>>> y = np.arange(3, 12)

>>> integrate.romb(y)
56.0

>>> y = np.sin(np.power(x, 2.5))
>>> integrate.romb(y)
-0.742561336672229

>>> integrate.romb(y, show=True)
Richardson Extrapolation Table for Romberg Integration
====================================================================
-0.81576
4.63862  6.45674
-1.10581 -3.02062 -3.65245
-2.57379 -3.06311 -3.06595 -3.05664
-1.34093 -0.92997 -0.78776 -0.75160 -0.74256
====================================================================
-0.742561336672229


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