Plotting a graphical converge inside a While - Newton Raphson numerical method
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Hi, I'm trying to get a command inside a while so as the Newton Rapshon code shows a graphical converge. If the values of the aproximations are connected between a line, it shows something like a spider web. Can anyone help me out, please?
Here is my code:
clear
clc
syms x
f = input('Introducir la función: '); %function
p0 = input ('Introducir valor semilla: '); %first aproximation
TOL = input ('Introducir la tolerancia de error: '); %error
fplot (f)
grid on
hold on
derivada = diff(f);
derivada = inline (derivada);
f = inline (f);
eabs = 100;
i =0;
while eabs>TOL
p = p0 - (f(p0))/(derivada(p0));
eabs = abs(((p-p0)/p)*100);
p0 = p;
i = i+1;
end
fprintf('\n Valor= %8.3f ',p0)
plot (p)
fplot (0)
hold off
댓글 수: 7
Walter Roberson
2019년 8월 26일
Is it strictly necessary that the lines be drawn during the execution of the while loop, or could it be drawn after the while finishes?
Luis Francisco Sanchez
2019년 8월 26일
Walter Roberson
2019년 8월 26일
allp = p0;
allfp = [];
while eabs>TOL
fp = f(p0);
p = p0 - fp/(derivada(p0));
eabs = abs(((p-p0)/p)*100);
p0 = p;
i = i+1;
allp(end+1) = p;
allfp(end+1) = fp;
end
plot(allp(1:end-1), allfp);
Luis Francisco Sanchez
2019년 8월 27일
Luis Francisco Sanchez
2019년 8월 27일
Walter Roberson
2019년 8월 27일
p = asin(sin(p));
David Wilson
2019년 8월 27일
Another solution assuming you are looking for an iterative numerial stragegy that stays strictly within the given bounds is to use bisection. Sure it is slow, but it will stay within the -pi/2 to +pi/2 bound.
F = @(x) -x +cos(x)+tan(x); % function of interest
eps = 0.0; tol = 1e-6; % assume some stopping tolerance, set eps to 0.1 if nervous
x = [-pi/2+eps, pi/2-eps];
Fx = F(x); % should be vectorised
assert(prod(sign(Fx)) < 0,'x does not bracket root')
while abs(diff(x)) > tol % Now start bisection routine
m = mean(x); % mid point, m = (a + b)/2
fm = F(m); % find f(m)
if Fx(1)*fm > 0
x(1)=m; Fx(1)=fm; % discard left
else
x(2)=m; % discard right
end % if
end % while
Either value of x is a reasonable solution.
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