Differential equations: Difference between revisions
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   var snip = brd.jc.snippet(document.getElementById("odeinput").value, true, 'x, y');  |    var snip = brd.jc.snippet(document.getElementById("odeinput").value, true, 'x, y');  | ||
   f = function (x, yy) {  |    f = function (x, yy) {  | ||
       return [snip(yy[0  |        return [snip(x, yy[0])];  | ||
   }  |    }  | ||
   brd.update();  |    brd.update();  | ||
Revision as of 11:25, 19 January 2017
Display solutions of the ordinary differential equation
- [math]\displaystyle{ y'= f(x,y) }[/math]
 
with initial value [math]\displaystyle{ (x_0,y_0) }[/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-x)*y"><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 P = brd.create('point',[0,1], {name:'(x_0,y_0)'});
function doIt() {
  var txt = JXG.GeonextParser.geonext2JS(document.getElementById("odeinput").value);
  f = new Function("x", "yy", "var y = yy[0]; var z = " + txt + "; return [z]");
  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;
    this.dataX = [];
    this.dataY = [];
    for(var i=0; i<data.length; i++) {
        this.dataX[i] = P.X()+i*h;
        this.dataY[i] = data[i][0];
    }
};
doIt();