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Task/Random-numbers/ERRE/random-numbers.erre

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+PROGRAM DISTRIBUTION
+
+!
+! for rosettacode.org
+!
+
+! formulas taken from TI-59 Master Library manual
+
+CONST NUM_ITEM=1000
+
+!VAR SUMX#,SUMX2#,R1#,R2#,Z#,I%
+
+DIM A#[1000]
+
+BEGIN
+! seeds random number generator with system time
+   RANDOMIZE(TIMER)
+
+   PRINT(CHR$(12);)  !CLS
+   SUMX#=0  SUMX2#=0
+
+   FOR I%=1 TO NUM_ITEM DO
+      R1#=RND(1)  R2#=RND(1)
+      Z#=SQR(-2*LOG(R1#))*COS(2*π*R2#)
+      A#[I%]=Z#/2+1   ! I want a normal distribution with
+                      !      mean=1 and std.dev=0.5
+      SUMX#+=A#[I%]  SUMX2#+=A#[I%]*A#[I%]
+   END FOR
+
+   Z#=SUMX#/NUM_ITEM
+
+   PRINT("Average is";Z#)
+   PRINT("Standard dev. is";SQR(SUMX2#/NUM_ITEM-Z#*Z#))
+
+END PROGRAM

Task/Random-numbers/Free-Pascal/random-numbers.free

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+function randg(mean,stddev: float): float;

Task/Random-numbers/FreeBASIC/random-numbers.freebasic

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+' FB 1.05.0 Win64
+
+Const pi As Double = 3.141592653589793
+Randomize
+
+' Generates normally distributed random numbers with mean 0 and standard deviation 1
+Function randomNormal() As Double
+  Return Cos(2.0 * pi * Rnd) * Sqr(-2.0 * Log(Rnd))
+End Function
+
+Dim r(0 To 999) As Double
+Dim sum As Double = 0.0
+
+' Generate 1000 normally distributed random numbers
+' with mean 1 and standard deviation 0.5
+' and calculate their sum
+For i As Integer = 0 To 999
+   r(i) = 1.0 + randomNormal/2.0
+   sum += r(i)
+Next
+
+Dim mean As Double = sum / 1000.0
+
+Dim sd As Double
+sum = 0.0
+' Now calculate their standard deviation
+For i As Integer = 0 To 999
+  sum += (r(i) - mean) ^ 2.0
+Next
+sd  = Sqr(sum/1000.0)
+
+Print "Mean is              "; mean
+Print "Standard Deviation is"; sd
+Print
+Print "Press any key to quit"
+Sleep

Task/Random-numbers/FutureBasic/random-numbers.futurebasic

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+include "ConsoleWindow"
+
+local fn RandomZeroToOne as double
+dim as double result
+BeginCCode
+  result = (double)( (rand() % 100000 ) * 0.00001 );
+EndC
+end fn = result
+
+local fn RandomGaussian as double
+dim as double r
+
+r = fn RandomZeroToOne
+end fn = 1 + .5 * ( sqr( -2 * log(r) ) * cos( 2 * pi * r ) )
+
+dim as long i
+dim as double mean, std, a(1000)
+
+for i = 1 to 1000
+  a(i) = fn RandomGaussian
+  mean += a(i)
+next
+mean = mean / 1000
+
+for i = 1 to 1000
+  std += ( a(i) - mean )^2
+next
+std = std / 1000
+
+print "           Average:"; mean
+print "Standard Deviation:"; std

Task/Random-numbers/Nim/random-numbers.nim

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+import math, strutils
+
+const  precisn = 5
+var rs: TRunningStat
+
+proc normGauss: float {.inline.} = 1 + 0.76 * cos(2*PI*random(1.0)) * sqrt(-2*log10(random(1.0)))
+
+randomize()
+
+for j in 0..5:
+   for i in 0..1000:
+      rs.push(normGauss())
+   echo("mean: ", $formatFloat(rs.mean,ffDecimal,precisn),
+        " stdDev: ", $formatFloat(rs.standardDeviation(),ffDecimal,precisn))

Task/Random-numbers/Phix/random-numbers.phix

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+function RandomNormal()
+    return sqrt(-2*log(rnd())) * cos(2*PI*rnd())
+end function
+
+sequence s = repeat(0,1000)
+for i=1 to length(s) do
+    s[i] = 1 + 0.5 * RandomNormal()
+end for

Task/Random-numbers/Ring/random-numbers.ring

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+for i = 1 to 10
+    see random(i) + nl
+next i

Task/Random-numbers/Sidef/random-numbers.sidef

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+var arr = 1000.of { 1 + (0.5 * (-2 * 1.rand.log -> sqrt) * (Number.tau * 1.rand -> cos)) }
+arr.each { .say }

Task/Random-numbers/Visual-FoxPro/random-numbers.visual

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+LOCAL i As Integer, m As Double, n As Integer, sd As Double
+py = PI()
+SET TALK OFF
+SET DECIMALS TO 6
+CREATE CURSOR gdev (deviate B(6))
+RAND(-1)
+n = 1000
+m = 1
+sd = 0.5
+CLEAR
+FOR i = 1 TO n
+	INSERT INTO gdev VALUES (GaussDev(m, 1/sd))
+ENDFOR
+CALCULATE AVG(deviate), STD(deviate) TO m, sd
+? "Mean", m, "Std Dev", sd
+SET TALK ON
+SET DECIMALS TO
+
+FUNCTION GaussDev(mean As Double, sdev As Double) As Double
+LOCAL z As Double
+z = SQRT(-2*LOG(RAND()))*COS(py*RAND())
+IF sdev # 0
+	z = mean + z/sdev
+ENDIF
+RETURN z	
+ENDFUNC

Task/Random-numbers/jq/random-numbers-1.jq

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+# 15-bit integers generated using the same formula as rand() from the Microsoft C Runtime.
+# The random numbers are in [0 -- 32767] inclusive.
+# Input: an array of length at least 2 interpreted as [count, state, ...]
+# Output: [count+1, newstate, r] where r is the next pseudo-random number.
+def next_rand_Microsoft:
+  .[0] as $count | .[1] as $state
+  | ( (214013 * $state) + 2531011) % 2147483648 # mod 2^31
+  | [$count+1 , ., (. / 65536 | floor) ] ;

Task/Random-numbers/jq/random-numbers-2.jq

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+# Generate a single number following the normal distribution with mean 0, variance 1,
+# using the Box-Muller method: X = sqrt(-2 ln U) * cos(2 pi V) where U and V are uniform on [0,1].
+# Input: [n, state]
+# Output [n+1, nextstate, r]
+def next_rand_normal:
+  def u: next_rand_Microsoft | .[2] /= 32767;
+  u as $u1
+  | ($u1 | u) as $u2
+  | ((( (8*(1|atan)) * $u1[2]) | cos)
+     * ((-2 * (($u2[2]) | log)) | sqrt)) as $r
+  | [ (.[0]+1), $u2[1], $r] ;
+
+# Generate "count" arrays, each containing a random normal variate with the given mean and standard deviation.
+# Input: [count, state]
+# Output: [updatedcount, updatedstate, rnv]
+# where "state" is a seed and "updatedstate" can be used as a seed.
+def random_normal_variate(mean; sd; count):
+  next_rand_normal
+  | recurse( if .[0] < count then next_rand_normal else empty end)
+  | .[2] = (.[2] * sd) + mean;

Task/Random-numbers/jq/random-numbers-3.jq

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+def summary:
+  length as $l | add as $sum | ($sum/$l) as $a
+  | reduce .[] as $x (0; . + ( ($x - $a) | .*. ))
+  | [ $a, (./$l | sqrt)] ;
+
+[ [0,1] | random_normal_variate(1; 0.5; 1000) | .[2] ] | summary