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Deming's funnel (view source)

Revision as of 19:52, 15 March 2024

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Line 284:
Mean x,y : 3.1341 5.4210
Std.dev x,y : 1.5874 3.9304</pre>
 
=={{header|C#}}==
{{trans|Java}}
<syntaxhighlight lang="C#">
using System;
using System.Linq;
 
public class DemingsFunnel
{
public static void Main(string[] args)
{
double[] dxs = {
-0.533, 0.270, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275,
1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.150, 0.001,
-0.382, 0.161, 0.915, 2.080, -2.337, 0.034, -0.126, 0.014,
0.709, 0.129, -1.093, -0.483, -1.193, 0.020, -0.051, 0.047,
-0.095, 0.695, 0.340, -0.182, 0.287, 0.213, -0.423, -0.021,
-0.134, 1.798, 0.021, -1.099, -0.361, 1.636, -1.134, 1.315,
0.201, 0.034, 0.097, -0.170, 0.054, -0.553, -0.024, -0.181,
-0.700, -0.361, -0.789, 0.279, -0.174, -0.009, -0.323, -0.658,
0.348, -0.528, 0.881, 0.021, -0.853, 0.157, 0.648, 1.774,
-1.043, 0.051, 0.021, 0.247, -0.310, 0.171, 0.000, 0.106,
0.024, -0.386, 0.962, 0.765, -0.125, -0.289, 0.521, 0.017,
0.281, -0.749, -0.149, -2.436, -0.909, 0.394, -0.113, -0.598,
0.443, -0.521, -0.799, 0.087};
 
double[] dys = {
0.136, 0.717, 0.459, -0.225, 1.392, 0.385, 0.121, -0.395,
0.490, -0.682, -0.065, 0.242, -0.288, 0.658, 0.459, 0.000,
0.426, 0.205, -0.765, -2.188, -0.742, -0.010, 0.089, 0.208,
0.585, 0.633, -0.444, -0.351, -1.087, 0.199, 0.701, 0.096,
-0.025, -0.868, 1.051, 0.157, 0.216, 0.162, 0.249, -0.007,
0.009, 0.508, -0.790, 0.723, 0.881, -0.508, 0.393, -0.226,
0.710, 0.038, -0.217, 0.831, 0.480, 0.407, 0.447, -0.295,
1.126, 0.380, 0.549, -0.445, -0.046, 0.428, -0.074, 0.217,
-0.822, 0.491, 1.347, -0.141, 1.230, -0.044, 0.079, 0.219,
0.698, 0.275, 0.056, 0.031, 0.421, 0.064, 0.721, 0.104,
-0.729, 0.650, -1.103, 0.154, -1.720, 0.051, -0.385, 0.477,
1.537, -0.901, 0.939, -0.411, 0.341, -0.411, 0.106, 0.224,
-0.947, -1.424, -0.542, -1.032};
 
Experiment("Rule 1:", dxs, dys, (z, dz) => 0.0);
Experiment("Rule 2:", dxs, dys, (z, dz) => -dz);
Experiment("Rule 3:", dxs, dys, (z, dz) => -(z + dz));
Experiment("Rule 4:", dxs, dys, (z, dz) => z + dz);
}
 
static void Experiment(string label, double[] dxs, double[] dys, Func<double, double, double> rule)
{
double[] resx = Funnel(dxs, rule);
double[] resy = Funnel(dys, rule);
Console.WriteLine(label);
Console.WriteLine($"Mean x, y: {Mean(resx):F4}, {Mean(resy):F4}");
Console.WriteLine($"Std dev x, y: {StdDev(resx):F4}, {StdDev(resy):F4}");
Console.WriteLine();
}
 
static double[] Funnel(double[] input, Func<double, double, double> rule)
{
double x = 0;
double[] result = new double[input.Length];
 
for (int i = 0; i < input.Length; i++)
{
double rx = x + input[i];
x = rule(x, input[i]);
result[i] = rx;
}
return result;
}
 
static double Mean(double[] xs)
{
return xs.Average();
}
 
static double StdDev(double[] xs)
{
double m = Mean(xs);
return Math.Sqrt(xs.Select(x => Math.Pow((x - m), 2)).Sum() / xs.Length);
}
}
</syntaxhighlight>
{{out}}
<pre>
Rule 1:
Mean x, y: 0.0004, 0.0702
Std dev x, y: 0.7153, 0.6462
 
Rule 2:
Mean x, y: 0.0009, -0.0103
Std dev x, y: 1.0371, 0.8999
 
Rule 3:
Mean x, y: 0.0439, -0.0063
Std dev x, y: 7.9871, 4.7784
 
Rule 4:
Mean x, y: 3.1341, 5.4210
Std dev x, y: 1.5874, 3.9304
 
 
</pre>
 
=={{header|C++}}==
<syntaxhighlight lang="c++">
#include <cmath>
#include <functional>
#include <iomanip>
#include <iostream>
#include <string>
#include <vector>
 
double mean(const std::vector<double>& pseudo_random) {
double sum = 0.0;
for ( double item : pseudo_random ) {
sum += item;
}
return sum / pseudo_random.size();
}
 
double standard_deviation(const std::vector<double>& pseudo_random) {
const double average = mean(pseudo_random);
double sum_squares = 0.0;
for ( double item : pseudo_random ) {
sum_squares += item * item;
}
return sqrt(sum_squares / pseudo_random.size() - average * average);
}
 
std::vector<double> funnel(const std::vector<double>& pseudo_random,
const std::function<double(double, double)>& rule) {
double value = 0.0;
std::vector<double> result(pseudo_random.size(), 0);
 
for ( size_t i = 0; i < pseudo_random.size(); i++ ) {
const double result_value = value + pseudo_random[i];
value = rule(value, pseudo_random[i]);
result[i] = result_value;
}
return result;
}
 
void experiment(const std::string& label, const std::vector<double>& pseudo_random_xs,
const std::vector<double>& pseudo_random_ys, const std::function<double(double, double)>& rule) {
 
std::vector<double> result_x = funnel(pseudo_random_xs, rule);
std::vector<double> result_y = funnel(pseudo_random_ys, rule);
 
std::cout << label << std::endl;
std::cout << "-----------------------------------------" << std::endl;
std::cout << "Mean x, y" << std::setw(16) << ": " << std::fixed << std::setprecision(4)
<< mean(result_x) << ", " << mean(result_y) << std::endl;
std::cout << "Standard deviation x, y: " << standard_deviation(result_x) << ", "
<< standard_deviation(result_y) << std::endl;
std::cout << std::endl;
}
 
int main() {
const std::vector<double> pseudo_random_xs = { -0.533, 0.270, 0.859, -0.043, -0.205, -0.127, -0.071,
0.275, 1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.150, 0.001, -0.382, 0.161, 0.915, 2.080, -2.337,
0.034, -0.126, 0.014, 0.709, 0.129, -1.093, -0.483, -1.193, 0.020, -0.051, 0.047, -0.095, 0.695, 0.340,
-0.182, 0.287, 0.213, -0.423, -0.021, -0.134, 1.798, 0.021, -1.099, -0.361, 1.636, -1.134, 1.315,
0.201, 0.034, 0.097, -0.170, 0.054, -0.553, -0.024, -0.181, -0.700, -0.361, -0.789, 0.279, -0.174,
-0.009, -0.323, -0.658, 0.348, -0.528, 0.881, 0.021, -0.853, 0.157, 0.648, 1.774, -1.043, 0.051,
0.021, 0.247, -0.310, 0.171, 0.000, 0.106, 0.024, -0.386, 0.962, 0.765, -0.125, -0.289, 0.521,
0.017, 0.281, -0.749, -0.149, -2.436, -0.909, 0.394, -0.113, -0.598, 0.443, -0.521, -0.799, 0.087 };
 
const std::vector<double> pseudo_random_ys = { 0.136, 0.717, 0.459, -0.225, 1.392, 0.385, 0.121, -0.395,
0.490, -0.682, -0.065, 0.242, -0.288, 0.658, 0.459, 0.000, 0.426, 0.205, -0.765, -2.188, -0.742,
-0.010, 0.089, 0.208, 0.585, 0.633, -0.444, -0.351, -1.087, 0.199, 0.701, 0.096, -0.025, -0.868, 1.051,
0.157, 0.216, 0.162, 0.249, -0.007, 0.009, 0.508, -0.790, 0.723, 0.881, -0.508, 0.393, -0.226, 0.710,
0.038, -0.217, 0.831, 0.480, 0.407, 0.447, -0.295, 1.126, 0.380, 0.549, -0.445, -0.046, 0.428, -0.074,
0.217, -0.822, 0.491, 1.347, -0.141, 1.230, -0.044, 0.079, 0.219, 0.698, 0.275, 0.056, 0.031, 0.421, 0.064,
0.721, 0.104, -0.729, 0.650, -1.103, 0.154, -1.720, 0.051, -0.385, 0.477, 1.537, -0.901, 0.939, -0.411,
0.341, -0.411, 0.106, 0.224, -0.947, -1.424, -0.542, -1.032 };
 
experiment("Rule 1:", pseudo_random_xs, pseudo_random_ys, [](double z, double dz) -> double { return 0.0; });
experiment("Rule 2:", pseudo_random_xs, pseudo_random_ys, [](double z, double dz) -> double { return -dz; });
experiment("Rule 3:", pseudo_random_xs, pseudo_random_ys, [](double z, double dz) -> double { return -(z + dz); });
experiment("Rule 4:", pseudo_random_xs, pseudo_random_ys, [](double z, double dz) -> double { return z + dz; });
}
</syntaxhighlight>
{{ out }}
<pre>
Rule 1:
-----------------------------------------
Mean x, y : 0.0004, 0.0702
Standard deviation x, y: 0.7153, 0.6462
 
Rule 2:
-----------------------------------------
Mean x, y : 0.0009, -0.0103
Standard deviation x, y: 1.0371, 0.8999
 
Rule 3:
-----------------------------------------
Mean x, y : 0.0439, -0.0063
Standard deviation x, y: 7.9871, 4.7784
 
Rule 4:
-----------------------------------------
Mean x, y : 3.1341, 5.4210
Standard deviation x, y: 1.5874, 3.9304
</pre>
 
=={{header|D}}==
Line 380 ⟶ 585:
Mean x, y: 3.1341, 5.4210
Std dev x, y: 1.5874, 3.9304</pre>
 
=={{header|EasyLang}}==
{{trans|Python}}
 
<syntaxhighlight>
dxs[] = [ -0.533 0.27 0.859 -0.043 -0.205 -0.127 -0.071 0.275 1.251 -0.231 -0.401 0.269 0.491 0.951 1.15 0.001 -0.382 0.161 0.915 2.08 -2.337 0.034 -0.126 0.014 0.709 0.129 -1.093 -0.483 -1.193 0.02 -0.051 0.047 -0.095 0.695 0.34 -0.182 0.287 0.213 -0.423 -0.021 -0.134 1.798 0.021 -1.099 -0.361 1.636 -1.134 1.315 0.201 0.034 0.097 -0.17 0.054 -0.553 -0.024 -0.181 -0.7 -0.361 -0.789 0.279 -0.174 -0.009 -0.323 -0.658 0.348 -0.528 0.881 0.021 -0.853 0.157 0.648 1.774 -1.043 0.051 0.021 0.247 -0.31 0.171 0.0 0.106 0.024 -0.386 0.962 0.765 -0.125 -0.289 0.521 0.017 0.281 -0.749 -0.149 -2.436 -0.909 0.394 -0.113 -0.598 0.443 -0.521 -0.799 0.087 ]
#
dys[] = [ 0.136 0.717 0.459 -0.225 1.392 0.385 0.121 -0.395 0.49 -0.682 -0.065 0.242 -0.288 0.658 0.459 0.0 0.426 0.205 -0.765 -2.188 -0.742 -0.01 0.089 0.208 0.585 0.633 -0.444 -0.351 -1.087 0.199 0.701 0.096 -0.025 -0.868 1.051 0.157 0.216 0.162 0.249 -0.007 0.009 0.508 -0.79 0.723 0.881 -0.508 0.393 -0.226 0.71 0.038 -0.217 0.831 0.48 0.407 0.447 -0.295 1.126 0.38 0.549 -0.445 -0.046 0.428 -0.074 0.217 -0.822 0.491 1.347 -0.141 1.23 -0.044 0.079 0.219 0.698 0.275 0.056 0.031 0.421 0.064 0.721 0.104 -0.729 0.65 -1.103 0.154 -1.72 0.051 -0.385 0.477 1.537 -0.901 0.939 -0.411 0.341 -0.411 0.106 0.224 -0.947 -1.424 -0.542 -1.032 ]
#
proc funnel rule . dxs[] rxs[] .
rxs[] = [ ]
for dx in dxs[]
rxs[] &= x + dx
if rule = 1
x = 0
elif rule = 2
x = -dx
elif rule = 3
x = -(x + dx)
else
x = x + dx
.
.
.
proc mean . xs[] r .
r = 0
for x in xs[]
r += x
.
r /= len xs[]
.
proc stddev . xs[] r .
mean xs[] m
for x in xs[]
s += (x - m) * (x - m)
.
r = sqrt (s / len xs[])
.
proc experiment rule . .
funnel rule dxs[] rxs[]
funnel rule dys[] rys[]
print "Rule " & rule
mean rxs[] mx
mean rys[] my
print "Mean x, y : " & mx & " " & my
stddev rxs[] dx
stddev rys[] dy
print "Std dev x, y : " & dx & " " & dy
print ""
.
numfmt 4 0
experiment 1
experiment 2
experiment 3
experiment 4
</syntaxhighlight>
 
=={{header|Elixir}}==
Line 520 ⟶ 781:
Std dev x, y : 1.5874, 3.9304
</pre>
 
=={{header|FreeBASIC}}==
{{trans|Phix}}
<syntaxhighlight lang="vbnet">Dim Shared As Double DXs(100) => {_
-0.533, 0.270, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275, _
1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.150, 0.001, _
-0.382, 0.161, 0.915, 2.080, -2.337, 0.034, -0.126, 0.014, _
0.709, 0.129, -1.093, -0.483, -1.193, 0.020, -0.051, 0.047, _
-0.095, 0.695, 0.340, -0.182, 0.287, 0.213, -0.423, -0.021, _
-0.134, 1.798, 0.021, -1.099, -0.361, 1.636, -1.134, 1.315, _
0.201, 0.034, 0.097, -0.170, 0.054, -0.553, -0.024, -0.181, _
-0.700, -0.361, -0.789, 0.279, -0.174, -0.009, -0.323, -0.658, _
0.348, -0.528, 0.881, 0.021, -0.853, 0.157, 0.648, 1.774, _
-1.043, 0.051, 0.021, 0.247, -0.310, 0.171, 0.000, 0.106, _
0.024, -0.386, 0.962, 0.765, -0.125, -0.289, 0.521, 0.017, _
0.281, -0.749, -0.149, -2.436, -0.909, 0.394, -0.113, -0.598, _
0.443, -0.521, -0.799, 0.087}
 
Dim Shared As Double DYs(100) => { _
0.136, 0.717, 0.459, -0.225, 1.392, 0.385, 0.121, -0.395, _
0.490, -0.682, -0.065, 0.242, -0.288, 0.658, 0.459, 0.000, _
0.426, 0.205, -0.765, -2.188, -0.742, -0.010, 0.089, 0.208, _
0.585, 0.633, -0.444, -0.351, -1.087, 0.199, 0.701, 0.096, _
-0.025, -0.868, 1.051, 0.157, 0.216, 0.162, 0.249, -0.007, _
0.009, 0.508, -0.790, 0.723, 0.881, -0.508, 0.393, -0.226, _
0.710, 0.038, -0.217, 0.831, 0.480, 0.407, 0.447, -0.295, _
1.126, 0.380, 0.549, -0.445, -0.046, 0.428, -0.074, 0.217, _
-0.822, 0.491, 1.347, -0.141, 1.230, -0.044, 0.079, 0.219, _
0.698, 0.275, 0.056, 0.031, 0.421, 0.064, 0.721, 0.104, _
-0.729, 0.650, -1.103, 0.154, -1.720, 0.051, -0.385, 0.477, _
1.537, -0.901, 0.939, -0.411, 0.341, -0.411, 0.106, 0.224, _
-0.947, -1.424, -0.542, -1.032}
 
Function SumArray(arr() As Double) As Double
Dim As Double sum = 0.0
For i As Integer = Lbound(arr) To Ubound(arr)
sum += arr(i)
Next i
Return sum
End Function
 
Sub Funnel(DXs() As Double, rule As Integer, rxs() As Double)
Dim As Double x = 0.0
Dim As Integer i
For i = 1 To Ubound(dxs)
Dim As Double dx = DXs(i)
rxs(i) = x + dx
Select Case rule
Case 2: x = -dx
Case 3: x = -(x+dx)
Case 4: x = x+dx
End Select
Next i
End Sub
 
Function Mean(xs() As Double) As Double
Return SumArray(xs())/Ubound(xs)
End Function
 
Function StdDev(xs() As Double) As Double
Dim As Double m = Mean(xs())
Dim As Double sum = 0.0
For i As Integer = Lbound(xs) To Ubound(xs)
sum += (xs(i) - m) ^ 2
Next i
Return Sqr(sum / Ubound(xs))
End Function
 
Sub experiment(n As Integer, DXs() As Double, DYs() As Double)
Dim As Double rxs(Ubound(dxs)), rys(Ubound(dys))
Funnel(DXs(), n, rxs())
Funnel(DYs(), n, rys())
Print Using "Mean x, y : ###.####, ###.####"; mean(rxs()); mean(rys())
Print Using "Std dev x, y : ###.####, ###.####"; stddev(rxs()); stddev(rys())
End Sub
 
For i As Integer = 1 To 4
experiment(i, DXs(), DYs())
Next i
 
Sleep</syntaxhighlight>
{{out}}
<pre>Mean x, y : 0.0057, 0.0689
Std dev x, y : 0.7133, 0.6462
Mean x, y : -0.0000, 0.0000
Std dev x, y : 1.0330, 0.9068
Mean x, y : -0.0381, 0.0752
Std dev x, y : 7.5940, 4.7279
Mean x, y : 3.6729, 5.3539
Std dev x, y : 1.6174, 3.9340</pre>
 
=={{header|Go}}==
Line 1,223 ⟶ 1,575:
std dev: {1.58739,3.93036}</pre>
 
=== Stretch 1 ===
<syntaxhighlight lang="mathematica">
RadiusDistribution = NormalDistribution[0, 1];
Line 1,260 ⟶ 1,612:
 
 
=== Stretch 2 ===
<syntaxhighlight lang="mathematica">
ListPlot[MarblePositions[#][Transpose[{dxs,dys}]]&/@Range[4],PlotLegends->PointLegend[{1,2,3,4}],AspectRatio->Automatic,ImageSize->600]
Line 1,927 ⟶ 2,279:
Std dev x, y : 1.5874, 3.9304
</pre>
 
=={{header|Scala}}==
{{trans|Java}}
<syntaxhighlight lang="Scala">
object DemingsFunnel {
 
def main(args: Array[String]): Unit = {
val dxs = Array(
-0.533, 0.270, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275,
1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.150, 0.001,
-0.382, 0.161, 0.915, 2.080, -2.337, 0.034, -0.126, 0.014,
0.709, 0.129, -1.093, -0.483, -1.193, 0.020, -0.051, 0.047,
-0.095, 0.695, 0.340, -0.182, 0.287, 0.213, -0.423, -0.021,
-0.134, 1.798, 0.021, -1.099, -0.361, 1.636, -1.134, 1.315,
0.201, 0.034, 0.097, -0.170, 0.054, -0.553, -0.024, -0.181,
-0.700, -0.361, -0.789, 0.279, -0.174, -0.009, -0.323, -0.658,
0.348, -0.528, 0.881, 0.021, -0.853, 0.157, 0.648, 1.774,
-1.043, 0.051, 0.021, 0.247, -0.310, 0.171, 0.000, 0.106,
0.024, -0.386, 0.962, 0.765, -0.125, -0.289, 0.521, 0.017,
0.281, -0.749, -0.149, -2.436, -0.909, 0.394, -0.113, -0.598,
0.443, -0.521, -0.799, 0.087
)
 
val dys = Array(
0.136, 0.717, 0.459, -0.225, 1.392, 0.385, 0.121, -0.395,
0.490, -0.682, -0.065, 0.242, -0.288, 0.658, 0.459, 0.000,
0.426, 0.205, -0.765, -2.188, -0.742, -0.010, 0.089, 0.208,
0.585, 0.633, -0.444, -0.351, -1.087, 0.199, 0.701, 0.096,
-0.025, -0.868, 1.051, 0.157, 0.216, 0.162, 0.249, -0.007,
0.009, 0.508, -0.790, 0.723, 0.881, -0.508, 0.393, -0.226,
0.710, 0.038, -0.217, 0.831, 0.480, 0.407, 0.447, -0.295,
1.126, 0.380, 0.549, -0.445, -0.046, 0.428, -0.074, 0.217,
-0.822, 0.491, 1.347, -0.141, 1.230, -0.044, 0.079, 0.219,
0.698, 0.275, 0.056, 0.031, 0.421, 0.064, 0.721, 0.104,
-0.729, 0.650, -1.103, 0.154, -1.720, 0.051, -0.385, 0.477,
1.537, -0.901, 0.939, -0.411, 0.341, -0.411, 0.106, 0.224,
-0.947, -1.424, -0.542, -1.032
)
 
experiment("Rule 1:", dxs, dys, (z, dz) => 0.0)
experiment("Rule 2:", dxs, dys, (z, dz) => -dz)
experiment("Rule 3:", dxs, dys, (z, dz) => -(z + dz))
experiment("Rule 4:", dxs, dys, (z, dz) => z + dz)
}
 
def experiment(label: String, dxs: Array[Double], dys: Array[Double], rule: (Double, Double) => Double): Unit = {
val resx = funnel(dxs, rule)
val resy = funnel(dys, rule)
println(label)
printf("Mean x, y: %.4f, %.4f%n", mean(resx), mean(resy))
printf("Std dev x, y: %.4f, %.4f%n", stdDev(resx), stdDev(resy))
println()
}
 
def funnel(input: Array[Double], rule: (Double, Double) => Double): Array[Double] = {
var x = 0.0
val result = new Array[Double](input.length)
 
for (i <- input.indices) {
val rx = x + input(i)
x = rule(x, input(i))
result(i) = rx
}
result
}
 
def mean(xs: Array[Double]): Double = xs.sum / xs.length
 
def stdDev(xs: Array[Double]): Double = {
val m = mean(xs)
math.sqrt(xs.map(x => math.pow((x - m), 2)).sum / xs.length)
}
}
</syntaxhighlight>
{{out}}
<pre>
Rule 1:
Mean x, y: 0.0004, 0.0702
Std dev x, y: 0.7153, 0.6462
 
Rule 2:
Mean x, y: 0.0009, -0.0103
Std dev x, y: 1.0371, 0.8999
 
Rule 3:
Mean x, y: 0.0439, -0.0063
Std dev x, y: 7.9871, 4.7784
 
Rule 4:
Mean x, y: 3.1341, 5.4210
Std dev x, y: 1.5874, 3.9304
 
 
</pre>
 
 
 
=={{header|Sidef}}==
Line 2,338 ⟶ 2,786:
{{trans|Go}}{{libheader|Wren-math}}
{{libheader|Wren-fmt}}
<syntaxhighlight lang="ecmascriptwren">import "./math" for Nums
import "./fmt" for Fmt
 
var dxs = [
Line 2,388 ⟶ 2,836:
var rys = funnel.call(dys, r)
System.print("%(label) : x y")
SystemFmt.print("Mean : %(Fmt$7.f(4f, $7.4f", Nums.mean(rxs), 4)), %(Fmt.f(7, Nums.mean(rys), 4))")
SystemFmt.print("Std Dev : %(Fmt$7.f(4f, $7.4f", Nums.popStdDev(rxs), 4)), %(Fmt.f(7, Nums.popStdDev(rys), 4))")
SystemFmt.print()
}
 
Line 2,415 ⟶ 2,863:
Mean : 3.1341, 5.4210
Std Dev : 1.5874, 3.9304
</pre>
 
=={{header|XPL0}}==
Works on RPi. MAlloc works differently in DOS versions and in EXPL.
<syntaxhighlight lang "XPL0">include xpllib; \for Print
 
func real Mean(Array, Size);
real Array; int Size;
real Sum;
int I;
[Sum:= 0.0;
for I:= 0 to Size-1 do
Sum:= Sum + Array(I);
return Sum / float(Size);
];
 
func real StdDev(Array, Size);
real Array; int Size;
real M, Sum;
int I;
[M:= Mean(Array, Size);
Sum:= 0.0;
for I:= 0 to Size-1 do
Sum:= Sum + (Array(I)-M) * (Array(I)-M);
return sqrt(Sum / float(Size));
];
 
func real Funnel(Array, Size, Rule);
real Array; int Size, Rule;
real Posn, Result, Fall;
int AddrResult, I;
def SizeOfReal = 8; \bytes
[AddrResult:= addr Result;
AddrResult(0):= MAlloc(Size*SizeOfReal);
AddrResult(1):= 0; \for safety
Posn:= 0.0;
for I:= 0 to Size-1 do
[Fall:= Array(I);
Result(I):= Posn + Fall;
case Rule of
1: [];
2: Posn:= -Fall;
3: Posn:= -(Posn+Fall);
4: Posn:= Posn+Fall
other [];
];
return Result;
];
 
func Experiment(Rule);
int Rule;
real DXs, DYs, RXs, RYs;
def Size = 100;
[
DXs:= [ -0.533, 0.270, 0.859, -0.043, -0.205, -0.127, -0.071, 0.275,
1.251, -0.231, -0.401, 0.269, 0.491, 0.951, 1.150, 0.001,
-0.382, 0.161, 0.915, 2.080, -2.337, 0.034, -0.126, 0.014,
0.709, 0.129, -1.093, -0.483, -1.193, 0.020, -0.051, 0.047,
-0.095, 0.695, 0.340, -0.182, 0.287, 0.213, -0.423, -0.021,
-0.134, 1.798, 0.021, -1.099, -0.361, 1.636, -1.134, 1.315,
0.201, 0.034, 0.097, -0.170, 0.054, -0.553, -0.024, -0.181,
-0.700, -0.361, -0.789, 0.279, -0.174, -0.009, -0.323, -0.658,
0.348, -0.528, 0.881, 0.021, -0.853, 0.157, 0.648, 1.774,
-1.043, 0.051, 0.021, 0.247, -0.310, 0.171, 0.000, 0.106,
0.024, -0.386, 0.962, 0.765, -0.125, -0.289, 0.521, 0.017,
0.281, -0.749, -0.149, -2.436, -0.909, 0.394, -0.113, -0.598,
0.443, -0.521, -0.799, 0.087 ];
 
DYs:= [ 0.136, 0.717, 0.459, -0.225, 1.392, 0.385, 0.121, -0.395,
0.490, -0.682, -0.065, 0.242, -0.288, 0.658, 0.459, 0.000,
0.426, 0.205, -0.765, -2.188, -0.742, -0.010, 0.089, 0.208,
0.585, 0.633, -0.444, -0.351, -1.087, 0.199, 0.701, 0.096,
-0.025, -0.868, 1.051, 0.157, 0.216, 0.162, 0.249, -0.007,
0.009, 0.508, -0.790, 0.723, 0.881, -0.508, 0.393, -0.226,
0.710, 0.038, -0.217, 0.831, 0.480, 0.407, 0.447, -0.295,
1.126, 0.380, 0.549, -0.445, -0.046, 0.428, -0.074, 0.217,
-0.822, 0.491, 1.347, -0.141, 1.230, -0.044, 0.079, 0.219,
0.698, 0.275, 0.056, 0.031, 0.421, 0.064, 0.721, 0.104,
-0.729, 0.650, -1.103, 0.154, -1.720, 0.051, -0.385, 0.477,
1.537, -0.901, 0.939, -0.411, 0.341, -0.411, 0.106, 0.224,
-0.947, -1.424, -0.542, -1.032 ];
 
RXs:= Funnel(DXs, Size, Rule);
RYs:= Funnel(DYs, Size, Rule);
Print("Rule %d : X Y\n", Rule);
Print("Mean : %3.4f, %3.4f\n", Mean(RXs, Size), Mean(RYs, Size));
Print("Std Dev : %3.4f, %3.4f\n", StdDev(RXs, Size), StdDev(RYs, Size));
CrLf(0);
];
 
int R;
for R:= 1 to 4 do Experiment(R)</syntaxhighlight>
{{out}}
<pre>
Rule 1 : X Y
Mean : 0.0004, 0.0702
Std Dev : 0.7153, 0.6462
 
Rule 2 : X Y
Mean : 0.0009, -0.0103
Std Dev : 1.0371, 0.8999
 
Rule 3 : X Y
Mean : 0.0439, -0.0063
Std Dev : 7.9871, 4.7784
 
Rule 4 : X Y
Mean : 3.1341, 5.4210
Std Dev : 1.5874, 3.9304
 
</pre>
 
Jjuanhdez
2,130

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