scipy.integrate.romb#
- scipy.integrate.romb(y, dx=1.0, axis=- 1, show=False)[source]#
Romberg integration using samples of a function.
- Parameters
- yarray_like
A vector of
2**k + 1
equally-spaced samples of a function.- dxfloat, optional
The sample spacing. Default is 1.
- axisint, optional
The axis along which to integrate. Default is -1 (last axis).
- showbool, 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
- rombndarray
The integrated result for axis.
See also
quad
adaptive quadrature using QUADPACK
romberg
adaptive Romberg quadrature
quadrature
adaptive Gaussian quadrature
fixed_quad
fixed-order Gaussian quadrature
dblquad
double integrals
tplquad
triple integrals
simpson
integrators for sampled data
cumulative_trapezoid
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