Differential equations: Difference between revisions
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Display solutions of the ordinary differential equation  | Display solutions of the ordinary differential equation  | ||
:<math> y'= f(t,y)</math>  | :<math> y'= f(t,y)</math>  | ||
with initial value <math>(  | with initial value <math>(t_0,y_0)</math>.  | ||
It is easy to incorporate sliders: give the slider a (unique) name and use this name in the equation. In the example below, the slider name is <math>c</math>.  | It is easy to incorporate sliders: give the slider a (unique) name and use this name in the equation. In the example below, the slider name is <math>c</math>.  | ||
<html>  | <html>  | ||
<form>  | <form>  | ||
f(  | f(t,y)=<input type="text" id="odeinput" value="(2-t)*y + c"><input type=button value="ok" onclick="doIt()">  | ||
</form>  | </form>  | ||
</html>  | </html>  | ||
| Line 17: | Line 17: | ||
function doIt() {  | function doIt() {  | ||
   var snip = brd.jc.snippet(document.getElementById("odeinput").value, true, '  |    var snip = brd.jc.snippet(document.getElementById("odeinput").value, true, 't, y');  | ||
   f = function (  |    f = function (t, yy) {  | ||
       return [snip(  |        return [snip(t, yy[0])];  | ||
   }  |    }  | ||
   brd.update();  |    brd.update();  | ||
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<source lang="xml">  | <source lang="xml">  | ||
<form>  | <form>  | ||
f(x,y)=<input type="text" id="odeinput" value="(2-  | f(x,y)=<input type="text" id="odeinput" value="(2-t)*y + c"><input type=button value="ok" onclick="doIt()">  | ||
</form>  | </form>  | ||
</source>  | </source>  | ||
Revision as of 08:41, 18 December 2020
Display solutions of the ordinary differential equation
- [math]\displaystyle{ y'= f(t,y) }[/math]
 
with initial value [math]\displaystyle{ (t_0,y_0) }[/math].
It is easy to incorporate sliders: give the slider a (unique) name and use this name in the equation. In the example below, the slider name is [math]\displaystyle{ c }[/math].
See also
- Systems of differential equations
 - Lotka-Volterra equations
 - Epidemiology: The SIR model
 - Population growth models
 - Autocatalytic process
 - Logistic process
 - Paul Pearson has written a very nice variation: Slope fields and solution curves (using the Runge-Kutta)
 
The underlying JavaScript code
<form>
f(x,y)=<input type="text" id="odeinput" value="(2-t)*y + c"><input type=button value="ok" onclick="doIt()">
</form>
var brd = JXG.JSXGraph.initBoard('jxgbox', {axis:true, boundingbox:[-11,11,11,-11]});
var N = brd.create('slider',[[-7,9.5],[7,9.5],[-15,10,15]], {name:'N'});
var slider = brd.create('slider',[[-7,8],[7,8],[-15,0,15]], {name:'c'});
var P = brd.create('point',[0,1], {name:'(x_0, y_0)'});
var f;
function doIt() {
  var snip = brd.jc.snippet(document.getElementById("odeinput").value, true, 'x, y');
  f = function (x, yy) {
      return [snip(x, yy[0])];
  }
  brd.update();
}
function ode() {
   return JXG.Math.Numerics.rungeKutta('heun', [P.Y()], [P.X(), P.X()+N.Value()], 200, f);
}
var g = brd.create('curve', [[0],[0]], {strokeColor:'red', strokeWidth:2});
g.updateDataArray = function() {
    var data = ode();
    var h = N.Value()/200;
    var i;
    this.dataX = [];
    this.dataY = [];
    for(i=0; i<data.length; i++) {
        this.dataX[i] = P.X()+i*h;
        this.dataY[i] = data[i][0];
    }
};
doIt();