bundles / scipy latest / scipy / integrate / _quadrature / romb
function
scipy.integrate._quadrature:romb
source: build-install/usr/lib/python3.14/site-packages/scipy/integrate/_quadrature.py:784
Signature
def romb(y, dx = 1.0, axis = -1, show = False)Summary
Romberg integration using samples of a function.
Parameters
y: array_likeA vector of
2**k + 1equally-spaced samples of a function.dx: float, optionalThe sample spacing. Default is 1.
axis: int, optionalThe axis along which to integrate. Default is -1 (last axis).
show: bool, optionalWhen
yis 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: ndarrayThe integrated result for
axis.
Examples
from scipy import integrate import numpy as np x = np.arange(10, 14.25, 0.25) y = np.arange(3, 12)✓
integrate.romb(y)
✗np.float64(56.0)
y = np.sin(np.power(x, 2.5))
✓integrate.romb(y)
✗np.float64(-0.7425613366722694)
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 ====================================================== np.float64(-0.7425613366722694)
integrate.romb([[1, 2, 3], [4, 5, 6]], show=True)
✓*** Printing table only supported for integrals of a single data set. array([ 4., 10.])
See also
- cumulative_trapezoid
cumulative integration for sampled data
- dblquad
double integrals
- fixed_quad
fixed-order Gaussian quadrature
- quad
adaptive quadrature using QUADPACK
- simpson
integrators for sampled data
- tplquad
triple integrals
Aliases
scipy.integrate.romb