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Author Topic: How do you calculate probability?  (Read 3051 times)
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July 19, 2010, 03:13:43 AM

.I am trying to correct some PHP code to calculate probability of generating a block for bitbot.  bd_ and llama have provided some debate regarding how to calculate it and I suggest it be moved to forum for further eyes to analyze their findings and to come to a conclusion on best formula to calculate probability.

For now, here's code I've been using:
//var p = target*rate*1000/Math.pow(2,256);
//var txt = "<table border='1'>
// <tr style='font-weight:bold'> <td>Probability</td> <td>Time</td></tr>\n"+"
// <tr> <td>Average</td> <td>"+getHumanTime(1/p)+"</td></tr>\n"+getRow(0.50,p)+getRow(0.95,p)+"</table>";
//document.getElementById('answer').innerHTML = txt;
//function getRow(prob,p) { return "<tr><td>"+100*prob+"%</td><td>"+getHumanTime(-Math.log(1-prob)/p)+"</td></tr>\n";

$a = bcsub(bcpow(2,256),1);
$b = bcmul(bcpow(2,32),$difficulty);
$target = bcdiv($a,$b); // target
$pph = bcdiv($target,bcpow(2,256)); // probability per hash
if (isset($_GET["r"]) && $_GET["r"] != "") {
$rate = $_GET["r"];
if (is_numeric($rate)) {
function humantime($secs) {
if ($secs<0) return false;
$m = (int)($secs / 60); $s = $secs % 60; $s = ($s <= 9) ? "0$s" : $s;
$h = (int)($m / 60); $m = $m % 60; $m = ($m <= 9) ? "0$m" : $m;
$d = (int)($h / 24); $h = $h % 24;
return $d."d $h:$m:$s";
echo "";exit;
// Where does this go?
// <bd_> To compute the number of hashes needed to reach a success probability of P_targ, you'll want n >= log(P_targ)/log(1-P)
// <bd_> So time needed is (log(P_targ)/log(1-P))/rate

// <bd_> To compute the probability per second, you'll want 1-(1-p)^rate, where p is the probability of a single hash being correct
//$pps = bcdiv(bcmul($target,1000),bcpow(2,256)); // probability per second (according to bd_ this is wrong)
bcscale(16); // Next calculation takes too long for higher bits
$pps = bcsub(1,bcpow(bcsub(1,$pph),$rate)); // probability per second
//echo "probabiliy per second == 1-(1-p)^rate == 1-(1-$pph)^$rate == $pps";exit;
// Comment next line for 256-bits of data
$ppr = bcmul($pps,$rate);
//$ppr = $pps;
$etaAvg = humantime(bcdiv(1,$ppr));
$eta25 = humantime(bcdiv(-log(.75),$ppr));
$eta50 = humantime(bcdiv(-log(.5),$ppr));
$eta75 = humantime(bcdiv(-log(.25),$ppr));
$eta95 = humantime(bcdiv(-log(.05),$ppr));
$eta99 = humantime(bcdiv(-log(.01),$ppr));
echo "ProbabilityPerSecond($ppr) Avg($etaAvg) 25%($eta25) 50%($eta50) 75%($eta75) 95%($eta95) 99%($eta99)";
} else echo "This command requires either no argument or a numeric argument representing khash/sec.";
else {
$pph = bcmul($pph,1);
echo "ProbabilityPerHash($pph)";
} where r is your khash/sec
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July 19, 2010, 03:38:52 AM

Actually, it seems that BD_ and I have come to an agreement!

To calculate average (expected value of generation time):


To calculate how long until you have a T chance of producing at least 1 block:



p = probability of a given hash resulting in success (TARGET / 2^256)
r = rate in hashes / sec
T = target probability, such as 0.95
ln = log base e

I got to mine just by plugging variables and rearranging the poisson distribution.  BD_ can give you a different formula for the second equation, which he heroically derived from the binomial distribution, but which yields the same effective results.

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