simpson(y, x=None, dx=1.0, axis=-1, even='avg')
If there are an even number of samples, N, then there are an odd number of intervals (N-1), but Simpson's rule requires an even number of intervals. The parameter 'even' controls how this is handled.
For an odd number of samples that are equally spaced the result is exact if the function is a polynomial of order 3 or less. If the samples are not equally spaced, then the result is exact only if the function is a polynomial of order 2 or less.
Array to be integrated.
If given, the points at which y
is sampled.
Spacing of integration points along axis of x
. Only used when x
is None. Default is 1.
Axis along which to integrate. Default is the last axis.
'avg'
'avg'
'first'
'first'
'last'
'last'
Integrate y(x) using samples along the given axis and the composite Simpson's rule. If x is None, spacing of dx is assumed.
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
romb
integrators for sampled data
romberg
adaptive Romberg quadrature
tplquad
triple integrals
>>> from scipy import integrate
... x = np.arange(0, 10)
... y = np.arange(0, 10)
>>> integrate.simpson(y, x) 40.5
>>> y = np.power(x, 3)
... integrate.simpson(y, x) 1642.5
>>> integrate.quad(lambda x: x**3, 0, 9)[0] 1640.25
>>> integrate.simpson(y, x, even='first') 1644.5See :
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.simps
scipy.integrate._quadrature.quadrature
scipy.integrate._quadrature.romb
scipy.integrate._quadrature.fixed_quad
scipy.integrate._quadpack_py.quad
scipy.integrate._quadrature.romberg
scipy.integrate._quadpack_py.tplquad
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