Guassian Quadrature


This interact illustrates numerical integration using Gaussian quadrature. The user may select how many points will be used to estimate the definite integral and a function to be integrated. The vertical bars are shaded to reflect the relative weights of the points, where a darker bar means a greater weight. The error is printed out and compared on a bar graph.

Sage Cell


import scipy
import numpy
from scipy.special.orthogonal import p_roots, t_roots, u_roots
from scipy.integrate import quad, trapz, simps
from sage.ext.fast_eval import fast_float
from numpy import linspace, asanyarray, diff
#  'Hermite': {'w': e**(-x**2), 'xmin': -numpy.inf, 'xmax': numpy.inf, 'func': h_roots},
#  'Laguerre': {'w': e**(-x), 'xmin': 0, 'xmax': numpy.inf, 'func': l_roots},

methods = {'Legendre': {'w': 1, 'xmin': -1, 'xmax': 1, 'func': p_roots},
     'Chebyshev': {'w': 1/sqrt(1-x**2), 'xmin': -1, 'xmax': 1, 'func': t_roots},
     'Chebyshev2': {'w': sqrt(1-x**2), 'xmin': -1, 'xmax': 1, 'func': u_roots},
     'Trapezoid': {'w': 1, 'xmin': -1, 'xmax': 1, 
        'func': lambda n: (linspace(-1r,1,n), numpy.array([1.0r]+[2.0r]*(n-2)+[1.0r])*1.0r/n)},
     'Simpson': {'w': 1, 'xmin': -1, 'xmax': 1, 
        'func': lambda n: (linspace(-1r,1,n), 
def box(center, height, area,**kwds):
    width2 = 1.0*area/height/2.0
    return polygon([(center-width2,0),

def weights(n=slider(1,30,1,default=10),f=input_box(default=3*x+cos(10*x),type=SR),
    show_method=["Legendre", "Chebyshev", "Chebyshev2", "Trapezoid","Simpson"]):
    ff = fast_float(f,'x')
    method = methods[show_method]
    xcoords,w = (method['func'])(int(n))
    xmin = method['xmin']
    xmax = method['xmax']
    plot_min = max(xmin, -10)
    plot_max = min(xmax, 10)
    scaled_func = f*method['w']
    scaled_ff = fast_float(scaled_func, 'x')

    coords = zip(xcoords,w)
    max_weight = max(w)
    coords_scaled = zip(xcoords,w/max_weight)

    f_graph = plot(scaled_func,plot_min,plot_max)
    boxes = sum(box(x,ff(x),w*ff(x),rgbcolor=(0.5,0.5,0.5),alpha=0.3) for x,w in coords)
    stems = sum(line([(x,0),(x,scaled_ff(x))],rgbcolor=(1-y,1-y,1-y),
        thickness=2,markersize=6,alpha=y) for x,y in coords_scaled)
    points = sum([point([(x,0),
        (x,scaled_ff(x))],rgbcolor='black',pointsize=30) for x,_ in coords])
    graph = stems+points+f_graph+boxes
    if show_weight_graph:
        graph += line([(x,y) for x,y in coords_scaled], rgbcolor='green',alpha=0.4)


    approximation = sum([w*ff(x) for x,w in coords])
    integral,integral_error = scipy.integrate.quad(scaled_ff, xmin, xmax)
    x_val = linspace(min(xcoords), max(xcoords),n)
    y_val = [*map(scaled_ff,x_val)]
    trapezoid = integral-trapz(y_val, x_val)
    simpson = integral-simps(y_val, x_val)
    pretty_print(html(r"$$\sum_{i=1}^{i=%s}w_i\left(%s\right)= %s\approx %s =\int_{-1}^{1}%s \,dx$$"%(n,
        latex(f), approximation, integral, latex(scaled_func))))
    error_data = [trapezoid, simpson, integral-approximation,integral_error]
    print("Trapezoid: %s, Simpson: %s, \nMethod: %s, Real: %s" % tuple(error_data))
    show(bar_chart(error_data,width=1),ymin=min(error_data), ymax=max(error_data))




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Date: 23 Jul 2020 21:12

Submitted by: Zane Corbiere

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