Lecture 28: Comparison of different numerical integrators 1.Adaptive Simpson’s and Trapezoid Rules 2. Romberg Integration 3. Adaptive Gaussian Quadrature

adaptivesimpson.m %test of adaptive Simpson's rule and comparison with composite Trapezoid and Composite Simpson's tol=10^(-10); a=1; b=4; f1=inline('sin(x).^2') disp(['a=',num2str(a),' b=',num2str(b)]) %display limits of integration intexact=quad(f1,a,b,10^(-16)); [fadaptive funccount]=quad(f1,a,b,tol); disp(['Integration using adaptive simpson gives error=',num2str(fadaptive-intexact), ' in ',num2str(funccount), ' function evaluations']); disp(' '); disp(['Now compare with n step of composite simpson rule:']); i=1:10; nvec=2.^(i); ….

>> adaptivesimpson f1 = Inline function: f1(x) = sin(x).^2 a=1 b=4 Integration using adaptive simpson gives error= e-013 in 249 function evaluations Now compare with n step of composite simpson rule: n=2 Error in composite simpson rule = n=4 Error in composite simpson rule = n=8 Error in composite simpson rule = e-005 n=16 Error in composite simpson rule = e-006 n=32 Error in composite simpson rule = e-007 n=64 Error in composite simpson rule = e-009 n=128 Error in composite simpson rule = e-010 n=256 Error in composite simpson rule = e-011 n=512 Error in composite simpson rule = e-012 n=1024 Error in composite simpson rule =-1.299e-013 The same function with composite trapezoid rule: a=1 b=4 n=2 Error in composite trapezod rule = n=4 Error in composite trapezod rule = n=8 Error in composite trapezod rule = n=16 Error in composite trapezod rule = n=32 Error in composite trapezod rule =5.8673e-005 n=64 Error in composite trapezod rule =1.4662e-005 n=128 Error in composite trapezod rule =3.665e-006 n=256 Error in composite trapezod rule =9.1623e-007 n=512 Error in composite trapezod rule =2.2906e-007 n=1024 Error in composite trapezod rule =5.7264e-008 n=2048 Error in composite trapezod rule =1.4316e-008 n=4096 Error in composite trapezod rule =3.579e-009

romberg1.m % Romberg integration with number of function evaluations count funccount % Computes approximation to definite integral % Inputs: Matlab inline function specifying integrand f, % a,b integration interval, n=number of rows % Output: [r(n,n) funccount] function [r1 funccount] =romberg(f,a,b,n) h=(b-a)./(2.^(0:n-1)); r(1,1)=(b-a)*(f(a)+f(b))/2; funccount=2; for j=2:n subtotal = 0; for i=1:2^(j-2) subtotal = subtotal + f(a+(2*i-1)*h(j)); funccount= funccount+1; end r(j,1) = r(j-1,1)/2+h(j)*subtotal; for k=2:j r(j,k) = (4^(k-1)*r(j,k-1)-r(j-1,k-1))/(4^(k-1)-1); end r1=r(n,n);

rombergtest.m %test of romberg integration vs. adaptive Simpson's rule and comparison with composite Trapezoid and Composite Simpson's tol=10^(-10); %desired tolerance a=1; b=4; f1=inline('sin(x).^2') %function f(x) disp(['a=',num2str(a),' b=',num2str(b)]) %display limits of integration intexact=quadl(f1,a,b,10^(-16)); %calculation of "exact" value of integral [fadaptive funccount]=quad(f1,a,b,tol); disp(['Integration using adaptive simpson gives error=',num2str(fadaptive-intexact), ' in ',num2str(funccount), ' function evaluations']); disp(['Now compare with Romberg integration:']); i=1:8; nvec=1.*(i); for i=1:length(nvec) [intromber funccount]=romberg1(f1,a,b,nvec(i)); disp([' Error in Romberg integration =',num2str(intromber-intexact), ' in ',num2str(funccount), ' function evaluations']);% end …

>> rombergtest f1 = Inline function: f1(x) = sin(x).^2 a=1 b=4 Integration using adaptive simpson gives error= e-013 in 249 function evaluations Now compare with Romberg integration: Error in Romberg integration = in 2 function evaluations Error in Romberg integration = in 3 function evaluations Error in Romberg integration = in 5 function evaluations Error in Romberg integration = in 9 function evaluations Error in Romberg integration =3.8208e-007 in 17 function evaluations Error in Romberg integration = e-010 in 33 function evaluations Error in Romberg integration =7.5717e-014 in 65 function evaluations Error in Romberg integration =2.2204e-016 in 129 function evaluations Now compare with n step of composite simpson rule: n=2 Error in composite simpson rule = n=4 Error in composite simpson rule = n=8 Error in composite simpson rule = e-005 n=16 Error in composite simpson rule = e-006 n=32 Error in composite simpson rule = e-007 n=64 Error in composite simpson rule = e-009 n=128 Error in composite simpson rule = e-010 n=256 Error in composite simpson rule = e-011 n=512 Error in composite simpson rule = e-012 n=1024 Error in composite simpson rule = e-013 …

rombergtest2.m %rombergtest2.m: test of romberg integration vs. adaptive Simpson's rule and comparison with composite Trapezoid and Composite Simpson's tol=10^(-10); %desired tolerance a=1; b=15; f1=inline('sin(x).^2') %function f(x) disp(['a=',num2str(a),' b=',num2str(b)]) %display limits of integration intexact=quadl(f1,a,b,10^(-16)); %calculation of "exact" value of integral [fadaptive funccount]=quad(f1,a,b,tol); disp(['Integration using adaptive simpson gives error=',num2str(fadaptive-intexact), ' in ',num2str(funccount), ' function evaluations']); disp(' '); disp(['Now compare with Romberg integration:']); disp(' '); …

>> rombergtest2 f1 = Inline function: f1(x) = sin(x).^2 a=1 b=15 Integration using adaptive simpson gives error= e-013 in 1233 function evaluations Now compare with Romberg integration: Error in Romberg integration = in 2 function evaluations Error in Romberg integration = in 3 function evaluations Error in Romberg integration = in 5 function evaluations Error in Romberg integration = in 9 function evaluations Error in Romberg integration = in 17 function evaluations Error in Romberg integration = in 33 function evaluations Error in Romberg integration =2.3442e-005 in 65 function evaluations Error in Romberg integration = e-008 in 129 function evaluations Error in Romberg integration =8.6331e-012 in 257 function evaluations Error in Romberg integration =0 in 513 function evaluations Error in Romberg integration = e-016 in 1025 function evaluations Error in Romberg integration = e-015 in 2049 function evaluations Now compare with n step of composite simpson rule: n=2 Error in composite simpson rule = n=4 Error in composite simpson rule =4.165 n=8 Error in composite simpson rule = n=16 Error in composite simpson rule = n=32 Error in composite simpson rule = n=64 Error in composite simpson rule =9.8788e-005 n=128 Error in composite simpson rule =6.0685e-006 n=256 Error in composite simpson rule =3.7766e-007 n=512 Error in composite simpson rule =2.3579e-008 n=1024 Error in composite simpson rule =1.4733e-009

gaussianadaptive.m %gaussianadaptive.m: test of gaussian adaptive integration vs. adaptive Simpson's rule and Romberg's integration tol=10^(-8); %desired tolerance a=1; b=4; f1=inline('sin(x).^2') %function f(x) disp(['a=',num2str(a),' b=',num2str(b)]) %display limits of integration intexact=quadl(f1,a,b,10^(-16)); %calculation of "exact" value of integral [fadaptive funccount]=quadl(f1,a,b,tol); disp(['Integration using adaptive Gaussian quadrature gives error=',num2str(fadaptive-intexact), ' in ',num2str(funccount), ' function evaluations']); disp(' '); [fadaptive funccount]=quad(f1,a,b,10^(-10)); disp(['Integration using adaptive simpson gives error=',num2str(fadaptive-intexact), ' in ',num2str(funccount), ' function evaluations']); disp(' '); disp(['Now compare with Romberg integration:']); …

>> gaussianadaptive f1 = Inline function: f1(x) = sin(x).^2 a=1 b=4 Integration using adaptive Gaussian quadrature gives error=2.1849e-013 in 48 function evaluations Integration using adaptive simpson gives error= e-013 in 249 function evaluations Now compare with Romberg integration: Error in Romberg integration = in 2 function evaluations Error in Romberg integration = in 3 function evaluations Error in Romberg integration = in 5 function evaluations Error in Romberg integration = in 9 function evaluations Error in Romberg integration =3.8208e-007 in 17 function evaluations Error in Romberg integration = e-010 in 33 function evaluations Error in Romberg integration =7.5717e-014 in 65 function evaluations Error in Romberg integration =2.2204e-016 in 129 function evaluations Error in Romberg integration = e-016 in 257 function evaluations Error in Romberg integration = e-016 in 513 function evaluations Error in Romberg integration =4.4409e-016 in 1025 function evaluations Error in Romberg integration =0 in 2049 function evaluations

>> adaptivesimpson f1 = Inline function: f1(x) = sin(x).^2 a=1 b=4 Integration using adaptive simpson gives error= e-013 in 249 function evaluations Now compare with n step of composite simpson rule: n=2 Error in composite simpson rule = n=4 Error in composite simpson rule = n=8 Error in composite simpson rule = e-005 n=16 Error in composite simpson rule = e-006 n=32 Error in composite simpson rule = e-007 n=64 Error in composite simpson rule = e-009 n=128 Error in composite simpson rule = e-010 n=256 Error in composite simpson rule = e-011 n=512 Error in composite simpson rule = e-012 n=1024 Error in composite simpson rule =-1.299e-013 The same function with composite trapezoid rule: a=1 b=4 n=2 Error in composite trapezod rule = n=4 Error in composite trapezod rule = n=8 Error in composite trapezod rule = n=16 Error in composite trapezod rule = n=32 Error in composite trapezod rule =5.8673e-005 n=64 Error in composite trapezod rule =1.4662e-005 n=128 Error in composite trapezod rule =3.665e-006 n=256 Error in composite trapezod rule =9.1623e-007 n=512 Error in composite trapezod rule =2.2906e-007 n=1024 Error in composite trapezod rule =5.7264e-008 n=2048 Error in composite trapezod rule =1.4316e-008 n=4096 Error in composite trapezod rule =3.579e-009