1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
|
% Let us solve a boundary value problem. The differential equation
% is y''=x*y. We rewrite that in two dimensions and get y1'=y2,
% y2'=x*y1 (y1=y). We want the boundary values y(0)=1, y(1)=1.
%
% We plug this into a function.
>function f(x,y)
$return [y[2],x*y[1]];
$endfunction
% We then use the Heun method to solve this equation.
>help heun
function heun (ffunction,t,y0)
## y=heun("f",x,y0;...) solves the differential equation y'=f(x,y).
## f(x,y;...) must be a function.
## y0 is the starting value.
## ffunction may be an expression in x and y.
% So the method accepts the function f(x,y), the step values x=0..1
% and the intial condition. We choose y(0)=1, y'(0)=1.
%
% Press escape to see the solution.
>t=0:0.05:1; y=heun("f",t,[1,0]); xplot(y[1]); y[1,cols(y)]
1.1723
% An alternative method is the adaptive Runge method. Is is far
% more accurate. We do not need intermediate steps here.
>y=adaptiverunge("f",[0,1],[1,0]); y[1,2]
1.1723
% The next step is to set up a function, which has a zero in the
% solution. We do that by taking y'(0) as a parameter and y(1)-1
% as the function value.
>function g(a)
$t=0:0.001:1;
$y=adaptiverunge("f",[0,1],[1,a]);
$return y[1,2]-1;
$endfunction
% We know already g(0)>0, and we see g(-2)<0.
>g(0), g(-2),
0.1723
-1.99838
% Thus the secant method yields the desired value for y'(0).
>a=secant("g",-2,2)
-0.158752
% A final plot of the answer.
>t=0:0.05:1; y=adaptiverunge("f",t,[1,a]); xplot(t,y[1]);
>
|
