Fractals/Iterations of real numbers/r iterations

< Fractals < Iterations of real numbers

Diagram types

2D diagrams

3D diagrams

Maps

Logistic map

The logistic map[9][10] is defined by a recurrence relation ( difference equation) :

where :



Bash code [11] Javascript code from Khan Academy [12] MATLAB code:

r_values = (2:0.0002:4)';
iterations_per_value = 10;
y = zeros(length(r_values), iterations_per_value);
y0 = 0.5;
y(:,1) = r_values.*y0*(1-y0);
for i = 1:iterations_per_value-1
    y(:,i+1) = r_values.*y(:,i).*(1-y(:,i));
end
plot(r_values, y, '.', 'MarkerSize', 1);
grid on;

See also Lasin [13]

Maxima CAS code [14]

/* Logistic diagram by Mario Rodriguez Riotorto using Maxima CAS draw packag  */
pts:[];
for r:2.5 while r <= 4.0 step 0.001 do /* min r = 1 */
		(x: 0.25,
		for k:1 thru 1000 do x: r * x * (1-x), /* to remove points from image compute and do not draw it */
		for k:1 thru 500  do (x: r * x * (1-x), /* compute and draw it */
        	 	 pts: cons([r,x], pts))); /* save points to draw it later, re=r, im=x */
load(draw);
draw2d(	terminal   = 'png,
	file_name = "v",
        dimensions = [1900,1300],
	title      = "Bifurcation diagram, x[i+1] = r*x[i]*(1 - x[i])",
	point_type = filled_circle,
	point_size = 0.2,
	color = black,
	points(pts));


Better image

Bifurcation diagram of the logistic map

To show more detaile use tips by User:PAR:

"The horizontal axis is the r parameter, the vertical axis is the x variable. The image was created by forming a 1601 x 1001 array representing increments of 0.001 in r and x. A starting value of x=0.25 was used, and the map was iterated 1000 times in order to stabilize the values of x. 100,000 x -values were then calculated for each value of r and for each x value, the corresponding (x,r) pixel in the image was incremented by one. All values in a column (corresponding to a particular value of r) were then multiplied by the number of non-zero pixels in that column, in order to even out the intensities. Values above 250,000 were set to 250,000, and then the entire image was normalized to 0-255. Finally, pixels for values of r below 3.57 were darkened to increase visibility."

See also :

Lyapunov exponent

Invariant Measure

An invariant measure or probability density in state space [17]

Video on Youtube[18]

Real quadratic map

Lyapunov exponent - image and Maxima CAS code

Great images by Chip Ross[19]

For , the code in MATLAB can be written as:

c = (0:0.001:2)';
iterations_per_value = 100;
y = zeros(length(c), iterations_per_value);
y0 = 0;
y(:,1) = y0.^2 - c;
for i = 1:iterations_per_value-1
    y(:,i+1) = y(:,i).^2 - c;
end
plot(c, y, '.', 'MarkerSize', 1, 'MarkerEdgeColor', 'black');

Maxima CAS code for drawing real quadratic map :  : 

/* based on the code by by Mario Rodriguez Riotorto */
pts:[];
for c:-2.0 while c <= 0.25 step 0.001 do 
                (x: 0.0,
                for k:1 thru 1000 do x: x * x+c, /* to remove points from image compute and do not draw it */
                for k:1 thru 500  do (x:  x * x+c, /* compute and draw it */
                         pts: cons([c,x], pts))); /* save points to draw it later, re=r, im=x */
load(draw);
draw2d( terminal   = 'svg,
        file_name = "b",
        dimensions = [1900,1300],
        title      = "Bifurcation diagram, x[i+1] = x[i]*x[i] +c",
        point_type = filled_circle,
        point_size = 0.2,
        color = black,
        points(pts));

Lyapunov exponent

program lapunow;

  { program draws bifurcation diagram y[n+1]=y[n]*y[n]+x,} { blue}
  {  x: -2 < x < 0.25 }
  {  y: -2 < y < 2    }
  {  and Lyapunov exponet for each x { white}

  uses crt,graph,
        { modul niestandardowy }
       bmpM, {screenCopy}
       Grafm;
  var xe,xemax,xe0,yemax,i1,i2:integer;
      yer,y,x,w,dx,lap:real;

  const xmin=-2;         { wspolczynnik   funkcji fx(y) }
        xmax=0.25;
        ymax=2;
        ymin=-2;
        i1max=100;            { liczba iteracji }
        i2max=20;
        lapmax=10;
        lapmin=-10;


   function wielomian2st(y,x:real) :real;
     begin
       wielomian2st:=y*y+x;
     end;  { wielomian2st }


  procedure wstep;
     begin
       opengraf;
       randomize;            { przygotowanie generatora liczb losowych }
       xemax:=getmaxx;              { liczba pixeli }
       yemax:=getmaxy;
       w:=(yemax+1)/(ymax-ymin);
       dx:=(xmax-xmin)/(xemax+1);
     end;

  begin {cialo}
    wstep;
    for xe:=xemax downTo 0 do
      begin {xe}
        x:=xmin+xe*dx;     { liniowe skalowanie x=a*xe+b }
        i1:=0;
        i2:=0;
        lap:=0;
        y:=random;        { losowy wybor    y0 : 0<y0<1 }

        while (abs(y)<ymax) and (i1<i1max)
        do
          begin {while i1}
            y:=wielomian2st(y,x);
            i1:=i1+1;
            lap:=lap+ln(abs(2*y)+0.1);
            if keypressed then halt;
          end; {while i1}

        while (i2<i2max) and (abs(y)<ymax)
         do
          begin   {while i2}
            y:=wielomian2st(y,x);
            yer:=(y-ymin)*w;         { skalowanie }
            putpixel(xe,yemax-round(yer),blue); { diagram bifurkacyjny }
            i2:=i2+1;
            lap:=lap+ln(abs(2*y)+0.1);
            if keypressed then halt;
          end; {while i2}

          lap:=lap/(i1max+i2max);
          yer:=(lap-lapmin)*(yemax+1)/(lapmax-lapmin);
          putpixel(xe,yemax-round(yer),white);         { wsp Lapunowa }
          putpixel(xe,yemax-round(-ymin*w),red);       { y=0 }
          putpixel(xe,yemax-round((1-ymin)*w),green);  { y=1}

      end; {xe}

    {..... os 0Y .......................................................}
    setcolor(red);
    xe0:=round((0-Xmin)/dx);     {xe0= xe : x=0 }
    line(xe0,0,xe0,yemax);
     SetColor(red);
    OutTextXY(XeMax-50,yemax-round((0-ymin)*w)+10,'y=0 ');
    SetColor(blue);
    OutTextXY(XeMax-50,yemax-round((1-ymin)*w)+10,'y=1');
    {....................................................................}
    screenCopy('screen',640,480);
    {}
    repeat until keypressed;
    closegraph;

 end.

{ Adam Majewski
Turbo Pascal 7.0  Borland
 MS-Dos / Microsoft}

References

  1. ↑ Bifurcation and Orbit Diagrams by Chip Ross
  2. ↑ A revision of the Lyapunov exponent in 1D quadratic maps by Gerardo Pastor, Miguel Romera, Fausto Montoya Vitini. PHYSICA D NONLINEAR PHENOMENA 107(1):17 · AUGUST 1997
  3. ↑ wiki : Cobweb plot
  4. ↑ One-Dimensional Dynamical Systems Part 3: Iteration by Hinke Osinga
  5. ↑ wikipedia : histogram
  6. ↑ CHAOS THEORY: DEPENDENCE ON PARAMETER R
  7. ↑ bat-country by xian
  8. ↑ Power Spectrum of the Logistic Map from wolframmathematica
  9. ↑ The Logistic Map and Chaos by Elmer G. Wiens
  10. ↑ Ausloos, Marcel, Dirickx, Michel (Eds.) : The Logistic Map and the Route to Chaos
  11. ↑ Logistic map by M.R. Titchener
  12. ↑ khanacademy ; logistic-map
  13. ↑ Lasin - Matlab code
  14. ↑ Logistic diagram by Mario Rodriguez Riotorto using Maxima CAS draw package
  15. ↑ earner.org textbook
  16. ↑ calculate lyapunov of the logistic map -LASIN
  17. ↑ Invariant Measure Exercise by James P. Sethna, Christopher R. Myers.
  18. ↑ Invariant measure of logistic map by todo314
  19. ↑ Chip Ross : Bifurcation and Orbit diagrams

See also

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