Average loop length: Difference between revisions
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Partial translation of C using stl and std.
<syntaxhighlight lang="cpp">#include <random>
#include <random>
#include <vector>
#include <iostream>
Line 414 ⟶ 415:
int randint(int n) {
int r, rmax = RAND_MAX / n * n;
dis=std::uniform_int_distribution<int>(0,rmax) ;
r = dis(gen);
return r / (RAND_MAX / n);
}
unsigned long long factorial(size_t n) {
//Factorial using dynamic programming to memoize the values.
static std::vector<unsigned long long>factorials{1,1,2};
for (;factorials.size() <= n;)
factorials.push_back(((unsigned long long) factorials.back())*factorials.size());
return factorials[n];
}
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{{out}}
<pre>
n
-------------------------------
1 1.0000 1.0000 0.
2 1.
3 1.
4 2.
5 2.
6 2.
7 3.
8 3.2448 3.2450 -0.
9 3.
10 3.
11 3.
12 4.
13 4.
14 4.
15 4.
16 4.
17 4.
18 5.
19 5.
20 5.
</pre>
Line 745 ⟶ 746:
20 5,2960 5,2936 0,046%
</pre>
=={{header|EasyLang}}==
{{trans|Lua}}
<syntaxhighlight>
func average n reps .
for r to reps
f[] = [ ]
for i to n
f[] &= randint n
.
seen[] = [ ]
len seen[] n
x = 1
while seen[x] = 0
seen[x] = 1
x = f[x]
count += 1
.
.
return count / reps
.
func analytical n .
s = 1
t = 1
for i = n - 1 downto 1
t = t * i / n
s += t
.
return s
.
print " N average analytical (error)"
print "=== ======= ========== ======="
for n to 20
avg = average n 1e6
ana = analytical n
err = (avg - ana) / ana * 100
numfmt 0 2
write n
numfmt 4 9
print avg & ana & err & "%"
.
</syntaxhighlight>
=={{header|EchoLisp}}==
<syntaxhighlight lang="scheme">
Line 2,576 ⟶ 2,619:
40 7.6151 7.6091 0.0789
═══ ═════════ ═════════ ═════════
</pre>
=={{header|RPL}}==
This task is an opportunity to showcase several useful instructions - <code>CON, SEQ</code> and <code>∑</code> - which avoid to use a <code>FOR..NEXT</code> loop, to create a constant array, to generate a list of random numbers and to calculate a finite sum.
{{works with|HP|48G}}
« 0 → n times count
« 1 times '''FOR''' j
n { } + 0 CON
« n RAND * CEIL » 'z' 1 n 1 SEQ
1
'''WHILE''' 3 PICK OVER GET NOT '''REPEAT'''
ROT OVER 1 PUT ROT ROT
OVER SWAP GET
'count' 1 STO+
'''END''' 3 DROPN
'''NEXT'''
count times /
» » '<span style="color:blue">XPRMT</span>' STO
« { } DUP
1 20 '''FOR''' n
SWAP n 1000 <span style="color:blue">XPRMT</span> +
SWAP 'j' 1 n 'n!/n^j/(n-j)!' ∑ +
'''NEXT'''
DUP2 SWAP %CH ABS 2 FIX "%" ADD STD
» '<span style="color:blue">TASK</span>' STO
{{out}}
<pre>
3: { 1 1.497 1.882 2.2 2.468 2.823 3 3.258 3.475 3.647 3.854 4.003 4.234 4.46 4.589 4.767 4.852 4.929 5.154 5.251 }
2: { 1 1.5 1.88888888889 2.21875 2.5104 2.77469135802 3.0181387007 3.24501800538 3.45831574488 3.66021568 3.85237205073 4.03607367511 4.21234791298 4.38202942438 4.54580728514 4.70425824709 4.85787082081 5.00706309901 5.15219620097 5.29358458601 }
1:{ "0.00%" "0.20%" "0.36%" "0.85%" "1.69%" "1.74%" "0.60%" "0.40%" "0.48%" "0.36%" "0.04%" "0.82%" "0.51%" "1.78%" "0.95%" "1.33%" "0.12%" "1.56%" "0.04%" "0.80%" }
</pre>
Line 3,188 ⟶ 3,262:
20 5.2992 5.2936 ( 0.11%)
</pre>
=={{header|uBasic/4tH}}==
{{trans|BBC BASIC}}
This is about the limit of what you can do with uBasic/4tH. Since it is an integer BASIC, it uses what has become known in the Forth community as "Brodie math". The last 14 bits of an 64-bit integer are used to represent the fraction, so basically it is a form of "fixed point math". This, of course, leads inevitably to rounding errors. After step 14 the number is too large to fit in a 64-bit integer - so at that point it simply breaks down. Performance is another issue.
<syntaxhighlight lang="uBasic/4tH">M = 14
T = 100000
If Info("wordsize") < 64 Then Print "This program requires a 64-bit uBasic" : End
Print "N\tavg\tcalc\t%diff"
For n = 1 To M
a = FUNC(_Test(n, T))
h = FUNC(_Analytical(n))
d = FUNC(_Fmul(FUNC(_Fdiv(a, h)) - FUNC(_Ntof(1)), FUNC(_Ntof(100))))
Print n; "\t";
Proc _Fprint (a) : Print "\t";
Proc _Fprint (h) : Print "\t";
Proc _Fprint (d) : Print "%"
Next
End
_Analytical
Param (1)
Local (3)
c@ = 0
For b@ = 1 To a@
d@ = FUNC(_Fdiv(FUNC(_Factorial(a@)), a@^b@))
c@ = c@ + FUNC(_Fdiv (d@, FUNC(_Ntof(FUNC(_Factorial(a@-b@))))))
Next
Return (c@)
_Test
Param (2)
Local (4)
e@ = 0
For c@ = 1 To b@
f@ = 1 : d@ = 0
Do While AND(d@, f@) = 0
e@ = e@ + 1
d@ = OR(d@, f@)
f@ = SHL(1, Rnd(a@))
Loop
Next
Return (FUNC(_Fdiv(e@, b@)))
_Factorial
Param(1)
If (a@ = 1) + (a@ = 0) Then Return (1)
Return (a@ * FUNC(_Factorial(a@-1)))
_Fmul Param (2) : Return ((a@*b@)/16384)
_Fdiv Param (2) : Return ((a@*16384)/b@)
_Ftoi Param (1) : Return ((10000*a@)/16384)
_Itof Param (1) : Return ((16384*a@)/10000)
_Ntof Param (1) : Return (16384*a@)
_Fprint Param (1) : a@ = FUNC(_Ftoi(a@)) : Print Using "+?.####";a@; : Return</syntaxhighlight>
{{Out}}
<pre>N avg calc %diff
1 1.0000 1.0000 0.0000%
2 1.4985 1.5000 -0.0976%
3 1.8869 1.8887 -0.1037%
4 2.2192 2.2187 0.0183%
5 2.5130 2.5103 0.1037%
6 2.7761 2.7745 0.0549%
7 3.0264 3.0180 0.2746%
8 3.2504 3.2449 0.1647%
9 3.4528 3.4581 -0.1525%
10 3.6651 3.6599 0.1403%
11 3.8543 3.8521 0.0549%
12 4.0364 4.0357 0.0122%
13 4.2153 4.2119 0.0793%
14 4.3866 4.3815 0.1098%
0 OK, 0:392</pre>
=={{header|Unicon}}==
Line 3,467 ⟶ 3,621:
{{trans|Go}}
{{libheader|Wren-fmt}}
<syntaxhighlight lang="
import "./fmt" for Fmt
var nmax = 20
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var a = avg.call(n)
var b = ana.call(n)
var e = (a - b).abs/ b * 100
}</syntaxhighlight>
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