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On Sun, Jul 07, 2002 at 04:56:39AM -0700, Mythran wrote: >> > Why was the dice function written as it is? >> Because it actually simulates the rolling of a number of dice. Your loop >> only chooses a random number between low and high, and thus changes the >> probabilities. >> >> The probability graph of 2-12 is different for "2d12" vs merely "2-12". >> >> And right away, that's a disadvantage. >> > >Take a closer look at my post. You will see that it is not a disadvantage >at all.... Yes it is. It doesn't simulate real dice. >2d12 using the my dice() function has the same probability....it will not >return just 2-12. No, it returns a random number from 2 - 24. But that's not how dice work. Dice have certain probabilities. Unless your PRNG is whacked, it's not gonna give the same results with repetition like dice. >In my dice function, dice(2, 12) will return a min of 2 and a max of >24....this is the same results that the stock dice function would return. No it isn't. At least not in the long run. > >Notice the return statement: > >return (number(num, num * size)); And to show it without the statistical analysis (nicely explained btw) by Mythran, here's a side-by side comparison using both methods (the original dice code and your flat random number generation) using 100000 iterations rolling 2d6. It's pretty obvious that the dice function is giving the same natural bell curve that sitting there rolling (non-loaded) dice will give while your idea gives a very flat dispersal. (2d12, 30d20, etc will still give the same curve, I just used 2d6 to save space, just make sure to do enough loops to get an accurate sample) $ ./dice 100000 Results: dice odds number odds 2: 2744 36.4:1 9148 10.9:1 3: 5630 17.8:1 9192 10.9:1 4: 8263 12.1:1 9142 10.9:1 5: 11047 9.1:1 8913 11.2:1 6: 13836 7.2:1 9029 11.1:1 7: 16696 6.0:1 9202 10.9:1 8: 13647 7.3:1 8929 11.2:1 9: 11269 8.9:1 9058 11.0:1 10: 8558 11.7:1 9112 11.0:1 11: 5511 18.1:1 9168 10.9:1 12: 2799 35.7:1 9107 11.0:1 dice variance: 21531608.000 standard deviation: 4640.216 number variance: 9785.891 standard deviation: 98.924 just in case, that means, on average, you'd roll a 2 once every 36.4 rolls, but you'd roll a 7 once every 6. run them thru gnuplot to see it graphically. something like plot 'plot.dat' using 1:2 smooth csplines title "Dice" replot 'plot.dat' using 1:4 smooth csplines title "Number" (bezier gives a nicer bell curve but distorts the data too much) and you'll see the difference even easier. -me -- +---------------------------------------------------------------+ | FAQ: http://qsilver.queensu.ca/~fletchra/Circle/list-faq.html | | Archives: http://post.queensu.ca/listserv/wwwarch/circle.html | | Newbie List: http://groups.yahoo.com/group/circle-newbies/ | +---------------------------------------------------------------+

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