Random numbers: Difference between revisions

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Revision as of 18:31, 31 May 2007

The goal of this task is to generate a 1000-element array (vector, list, whatever it's called in your language) filled with normally distributed random numbers with a mean of 1.0 and a standard deviation of 0.5

Java

double[] list = new double[1000];
Random rng = new Random();
for(int i = 0;i<list.length;i++) {
  list[i] = 1.0 + 0.5 * rng.nextGaussian()
}

IDL

result = 1.0 + 0.5*randomn(seed,1000)

Tcl

proc nrand {} {return [expr sqrt(-2*log(rand()))*cos(4*acos(0)*rand())]}
for {set i 0} {$i < 1000} {incr i} {lappend result [expr 1+.5*nrand()]}

Python

import random
randList = [random.gauss(1, .5) for i in range(1000)]

@@ Line 5: / Line 5: @@
 ==[[Java]]==
 [[Category:Java]]
- Double[] list = new Double[1000];
+ double[] list = new double[1000];
  Random rng = new Random();
  for(int i = 0;i<list.length;i++) {
-   List[i] = 1.0 + 0.5 * rng.nextGaussian()
+   list[i] = 1.0 + 0.5 * rng.nextGaussian()
  }