scipy.integrate.quadrature¶
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scipy.integrate.quadrature(func, a, b, args=(), tol=1.49e-08, rtol=1.49e-08, maxiter=50, vec_func=True, miniter=1)[source]¶
- Compute a definite integral using fixed-tolerance Gaussian quadrature. - Integrate func from a to b using Gaussian quadrature with absolute tolerance tol. - Parameters
- funcfunction
- A Python function or method to integrate. 
- afloat
- Lower limit of integration. 
- bfloat
- Upper limit of integration. 
- argstuple, optional
- Extra arguments to pass to function. 
- tol, rtolfloat, optional
- Iteration stops when error between last two iterates is less than tol OR the relative change is less than rtol. 
- maxiterint, optional
- Maximum order of Gaussian quadrature. 
- vec_funcbool, optional
- True or False if func handles arrays as arguments (is a “vector” function). Default is True. 
- miniterint, optional
- Minimum order of Gaussian quadrature. 
 
- Returns
- valfloat
- Gaussian quadrature approximation (within tolerance) to integral. 
- errfloat
- Difference between last two estimates of the integral. 
 
 - See also - romberg
- adaptive Romberg quadrature 
- fixed_quad
- fixed-order Gaussian quadrature 
- quad
- adaptive quadrature using QUADPACK 
- dblquad
- double integrals 
- tplquad
- triple integrals 
- romb
- integrator for sampled data 
- simps
- integrator for sampled data 
- cumtrapz
- cumulative integration for sampled data 
- ode
- ODE integrator 
- odeint
- ODE integrator 
 - Examples - >>> from scipy import integrate >>> f = lambda x: x**8 >>> integrate.quadrature(f, 0.0, 1.0) (0.11111111111111106, 4.163336342344337e-17) >>> print(1/9.0) # analytical result 0.1111111111111111 - >>> integrate.quadrature(np.cos, 0.0, np.pi/2) (0.9999999999999536, 3.9611425250996035e-11) >>> np.sin(np.pi/2)-np.sin(0) # analytical result 1.0 
