Image:ExtremeValueTheorem.png
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[edit] Summary
A continuous function on a closed interval, showing the extreme value theorem.
I generated the function with the Python script:
#!/usr/bin/python from random import * k = 0 for i in xrange(1000000): k += gauss(0, 1) print i, k
I redirected the output to a file, then I plotted it with gnuplot with:
set term png size 6000,4500 set out 'out.png' pl [][-600:700] 'randfunc.txt' w p ps 3 pt 7
ps 3 pt 7 gives circular dots of 17 pixels in diameter. The high number of samples caused them to overlap, forming a continuous line. (Actually, in the places where the function happened to change very quickly, there were gaps between them, but in the downscaled version they are not evident.) Then I used GIMP to change the color of the graph, add a blue and a green dot at the bottom and the top, Gaussian blur it at 2 pixels, and downscale it to its current size with cubic interpolation.
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Date/Time | Dimensions | User | Comment | |
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current | 13:50, 22 January 2008 | 1,300×975 (123 KB) | Army1987 (Talk | contribs) | (A continuous function.) |
23:54, 21 January 2008 | 1,300×975 (154 KB) | Army1987 (Talk | contribs) | (A continuous function, showing the extreme value theorem. The maximum is shown in green and the minimum in blue. I generated it with this Python script: <source lang="Python"> #!/usr/bin/python from random import * k = 0 for i in range(100000): k += ) | |
20:18, 21 January 2007 | 300×150 (9 KB) | Army1987 (Talk | contribs) | (A continuous function on a closed interval, showing the extreme value theorem. The function is the integral of a piecewise continuous function which, on each one of 256 very small interval, takes a normally distributed randomly choosen value. I p) |
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