romb(y, dx=1.0, axis=-1, show=False)

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.

Returns

romb : ndarray

The integrated result for :None:None:`axis`.

Romberg integration using samples of a function.

See Also

cumulative_trapezoid

cumulative integration for sampled data

dblquad

double integrals

fixed_quad

fixed-order Gaussian quadrature

ode

ODE integrators

odeint

ODE integrators

quad

adaptive quadrature using QUADPACK

quadrature

adaptive Gaussian quadrature

romberg

adaptive Romberg quadrature

simpson

integrators for sampled data

tplquad

triple integrals

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

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.integrate._quadrature.simpson scipy.integrate._quadpack_py.dblquad scipy.integrate._quadrature.quadrature scipy.integrate._quadrature.romb scipy.integrate._quadrature.fixed_quad scipy.integrate._quadrature.cumulative_trapezoid scipy.integrate._quadpack_py.quad scipy.integrate._quadrature.romberg scipy.integrate._quadpack_py.tplquad

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