Random numbers: Difference between revisions
Dialects of BASIC moved to the BASIC section.
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Generate a collection filled with '''1000''' normally distributed random (or pseudo-random) numbers
with a mean of '''1.0''' and a [[wp:Standard_deviation|standard deviation]] of '''0.5'''
Many libraries only generate uniformly distributed random numbers. If so, you may use [[wp:Normal_distribution#Generating_values_from_normal_distribution|one of these algorithms]].
;Related task:
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a(i) = 1 + SQR(-2 * LOG(RND)) * COS(2 * pi * RND)
NEXT i
==={{header|Applesoft BASIC}}===
The [[Random_numbers#Commodore_BASIC|Commodore BASIC]] code works in Applesoft BASIC.
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Standard Deviation is 0.4838570687</pre>
==={{header|BBC BASIC}}===
<syntaxhighlight lang="bbcbasic"> DIM array(999)
FOR number% = 0 TO 999
array(number%) = 1.0 + 0.5 * SQR(-2*LN(RND(1))) * COS(2*PI*RND(1))
NEXT
mean = SUM(array()) / (DIM(array(),1) + 1)
array() -= mean
stdev = MOD(array()) / SQR(DIM(array(),1) + 1)
PRINT "Mean = " ; mean
PRINT "Standard deviation = " ; stdev</syntaxhighlight>
{{out}}
<pre>Mean = 1.01848064
Standard deviation = 0.503551814</pre>
==={{header|Commodore BASIC}}===
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330 END
</syntaxhighlight>
==={{header|FreeBASIC}}===
<syntaxhighlight lang="freebasic">' 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</syntaxhighlight>
Sample result:
{{out}}
<pre>
Mean is 1.000763573902885
Standard Deviation is 0.500653063426955
</pre>
==={{header|FutureBasic}}===
Note: To generate the random number, rather than using FB's native "rnd" function, this code wraps C code into the RandomZeroToOne function.
<syntaxhighlight lang="futurebasic">window 1
local fn RandomZeroToOne as double
double result
cln result = (double)( (rand() % 100000 ) * 0.00001 );
end fn = result
local fn RandomGaussian as double
double r = fn RandomZeroToOne
end fn = 1 + .5 * ( sqr( -2 * log(r) ) * cos( 2 * pi * r ) )
long i
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
HandleEvents</syntaxhighlight>
{{output}}
<pre>
Average: 1.053724951604593
Standard Deviation: 0.2897370762627166
</pre>
==={{header|Liberty BASIC}}===
<syntaxhighlight lang="lb">dim a(1000)
mean =1
sd =0.5
for i = 1 to 1000 ' throw 1000 normal variates
a( i) =mean +sd *( sqr( -2 * log( rnd( 0))) * cos( 2 * pi * rnd( 0)))
next i</syntaxhighlight>
==={{header|PureBasic}}===
<syntaxhighlight lang="purebasic">Procedure.f RandomNormal()
; This procedure can return any real number.
Protected.f x1, x2
; random numbers from the open interval ]0, 1[
x1 = (Random(999998)+1) / 1000000 ; must be > 0 because of Log(x1)
x2 = (Random(999998)+1) / 1000000
ProcedureReturn Sqr(-2*Log(x1)) * Cos(2*#PI*x2)
EndProcedure
Define i, n=1000
Dim a.q(n-1)
For i = 0 To n-1
a(i) = 1 + 0.5 * RandomNormal()
Next</syntaxhighlight>
==={{header|Run BASIC}}===
<syntaxhighlight lang="runbasic">dim a(1000)
pi = 22/7
for i = 1 to 1000
a( i) = 1 + .5 * (sqr(-2 * log(rnd(0))) * cos(2 * pi * rnd(0)))
next i</syntaxhighlight>
==={{header|TI-83 BASIC}}===
Built-in function: randNorm()
randNorm(1,.5)
Or by a program:
Calculator symbol translations:
"STO" arrow: →
Square root sign: √
ClrList L<sub>1</sub>
Radian
For(A,1,1000)
√(-2*ln(rand))*cos(2*π*A)→L<sub>1</sub>(A)
End
==={{header|ZX Spectrum Basic}}===
Here we have converted the QBasic code to suit the ZX Spectrum:
<syntaxhighlight lang="zxbasic">10 RANDOMIZE 0 : REM seeds random number generator based on uptime
20 DIM a(1000)
30 CLS
40 FOR i = 1 TO 1000
50 LET a(i) = 1 + SQR(-2 * LN(RND)) * COS(2 * PI * RND)
60 NEXT i</syntaxhighlight>
=={{header|C}}==
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function randg(mean,stddev: float): float;
</syntaxhighlight>
=={{header|Frink}}==
<syntaxhighlight lang="frink">a = new array[[1000], {|x| randomGaussian[1, 0.5]}]</syntaxhighlight>
=={{header|Go}}==
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{{works with|LabVIEW|8.6}}
[[File:LV_array_of_randoms_with_given_mean_and_stdev.png]]
=={{header|Lingo}}==
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StandardDeviation : 0.489099623426272
</pre>
=={{header|Python}}==
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=={{header|Ruby}}==
<syntaxhighlight lang="ruby">Array.new(1000) { 1 + Math.sqrt(-2 * Math.log(rand)) * Math.cos(2 * Math::PI * rand) }</syntaxhighlight>
=={{header|Rust}}==
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lappend result [expr {$mean + $stddev*nrand()}]
}</syntaxhighlight>
=={{header|TorqueScript}}==
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// calc sd of list of numbers:
(ns.reduce('wrap(p,n){p+(n-mean).pow(2)},0.0)/1000).sqrt() //-->0.494844</syntaxhighlight>
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