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# Copyright 2008, 2009, 2010 Kevin Ryde |
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# This file is part of Chart. |
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# |
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# Chart is free software; you can redistribute it and/or modify it under the |
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# terms of the GNU General Public License as published by the Free Software |
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# Foundation; either version 3, or (at your option) any later version. |
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# |
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# Chart is distributed in the hope that it will be useful, but WITHOUT ANY |
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more |
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# details. |
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# |
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# You should have received a copy of the GNU General Public License along |
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# with Chart. If not, see <http://www.gnu.org/licenses/>. |
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package App::Chart::Series::Calculation; |
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use 5.010; |
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use strict; |
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use warnings; |
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23
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use Carp; |
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50
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22
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1
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5
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use List::Util qw(min max); |
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2
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1
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804
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# use Locale::TextDomain ('App-Chart'); |
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sub identity { |
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0
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0
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0
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0
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return $_[0]; |
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} |
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29
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sub delay { |
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30
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1
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1
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0
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5
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my ($class, $N) = @_; |
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31
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1
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3
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my @array; |
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32
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1
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3
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my $pos = $N - 1; # initial extends |
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return sub { |
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34
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5
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5
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11
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my ($value) = @_; |
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35
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5
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12
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my $ret = $array[$pos]; |
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5
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$array[$pos] = $value; |
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37
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5
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100
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16
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if (++$pos >= $N) { $pos = 0; } |
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2
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4
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38
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5
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11
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return $ret; |
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39
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1
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8
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}; |
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} |
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41
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42
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sub sma_and_stddev { |
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43
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0
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0
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0
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0
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my ($class, $N) = @_; |
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44
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0
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0
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my $delay_proc = $class->delay ($N); |
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45
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0
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0
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my $total = 0; |
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46
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0
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0
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my $total_squares = 0; |
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47
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0
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0
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my $count = 0; |
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48
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return sub { |
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49
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0
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0
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my ($value) = @_; |
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50
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51
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# drop old |
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52
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0
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0
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my $old = $delay_proc->($value); |
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53
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0
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0
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0
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if (defined $old) { |
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54
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0
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0
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$total -= $old; |
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55
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0
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0
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$total_squares -= $old * $old; |
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56
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} else { |
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57
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0
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0
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$count++; |
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58
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} |
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59
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60
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# add new |
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61
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0
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$total += $value; |
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62
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0
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$total_squares += $value * $value; |
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63
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64
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0
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0
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return ($total / $count, |
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65
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sqrt(max (0, $total_squares*$count - $total*$total)) / $count); |
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66
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0
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0
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}; |
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67
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} |
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68
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69
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sub sum { |
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70
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1
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1
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0
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814
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my ($class, $N) = @_; |
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71
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1
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7
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my $delay_proc = $class->delay ($N); |
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72
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1
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4
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my $total = 0; |
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73
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return sub { |
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74
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5
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5
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23
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my ($value) = @_; |
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75
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76
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# drop old |
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77
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5
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my $old = $delay_proc->($value); |
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78
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5
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100
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17
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if (defined $old) { |
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79
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2
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94
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$total -= $old; |
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80
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} |
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81
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# add new |
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82
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5
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$total += $value; |
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83
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84
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5
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32
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return $total; |
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85
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1
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6
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}; |
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86
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} |
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87
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88
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sub ma_proc_by_weights { |
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89
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0
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0
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0
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0
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my @weights = @_; |
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90
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91
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# $a[0] is the newest point, $a[1] the prev, through to $a[$N-1] |
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92
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0
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0
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my @a; |
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93
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my $total_weight; |
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94
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95
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return sub { |
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96
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0
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0
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0
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my ($value) = @_; |
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97
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98
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0
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0
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unshift @a, $value; # add new |
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99
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100
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# keep last $N points |
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101
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0
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0
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0
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if (@a > @weights) { |
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102
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0
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0
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pop @a; # drop old |
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103
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} else { |
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104
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# new total weight for bigger @a |
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105
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0
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0
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$total_weight = List::Util::sum (map {$weights[$_]} 0 .. $#a); |
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0
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0
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106
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} |
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107
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108
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0
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0
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0
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if ($total_weight == 0) { |
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109
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0
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0
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return 0; |
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110
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} |
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111
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0
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0
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return (List::Util::sum (map {$a[$_] * $weights[$_]} 0 .. $#a) |
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0
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0
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112
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/ $total_weight); |
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113
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0
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0
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}; |
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114
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} |
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115
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116
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#------------------------------------------------------------------------------ |
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118
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# http://mathworld.wolfram.com/LeastSquaresFitting.html |
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119
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# Least squares generally, including deriving formula using |
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120
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# derivative==0 as follows: |
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121
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# |
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122
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# The sum of squares is |
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123
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# |
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124
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# R^2(a,b) = Sum (y[i] - (a + b*x[i]))^2 |
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125
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# |
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126
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# Partial derivative with b is |
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127
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# |
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128
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# d R^2(a,b) |
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129
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# ---------- = Sum 2 * (y[i]-b*x[i]) * -x[i] |
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130
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# db |
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131
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# |
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132
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# And want that to be zero at the minimum, so |
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133
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# |
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134
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# Sum -2*x[i]*y[i] + 2*b*Sum x[i]^2 = 0 |
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135
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# |
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136
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# Sum x[i]*y[i] |
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137
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# b = ------------- |
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138
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# Sum x[i]^2 |
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139
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# |
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140
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141
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# Return a procedure which calculates a linear regression line fit over an |
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142
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# accumulated window of $N values. |
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143
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# |
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144
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# Each call $proc->($y) enters a new value into the window, and the return |
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145
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# is two values ($a, $b) where the line is $a+$b*X. The last point entered |
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146
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# is at X=0 and the preceding ones at X=-1, X=-2, etc. A and B are |
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147
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# #f if not enough data yet. |
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148
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# |
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149
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# To prime the window initially, call $proc with $N-1 many points preceding |
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150
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# the first desired. |
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151
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# |
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152
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sub linreg { |
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153
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0
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0
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0
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0
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my ($class, $N) = @_; |
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154
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155
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# The X values used are centred around 0, |
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156
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# $count=4: -1.5, -0.5, 0.5, 1.5 |
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157
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# $count=5: -2, -1, 0, 1, 2 |
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158
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# $count=6: -2.5, -1.5, -0.5, 0.5, 1.5, 2.5 |
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159
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# etc |
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160
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# But the return is then adjusted $a is based on the last point as X=0 |
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161
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# |
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162
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# @array,$pos is a circular list of $count many values. The one at |
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163
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# @array[$pos] is the oldest and is replaced by a new value to cycle that |
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164
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# in. |
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165
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# |
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166
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# $count is how many points are in @array. |
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167
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# |
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168
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# $y_total is the total of the past $count many Y values, ie. the values |
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169
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# in @array. |
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170
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# |
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171
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# $xy2_total is the sum of 2*X*Y for each Y value in @array. |
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172
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# |
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173
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# $xx2_total is 2 * the sum of X*X for each X value used. This is a |
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174
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# constant once $count stops at COUNT. A minimum 1 is enforced for the |
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175
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# degenerate case of $N==0 (there's no slope to in that case but at least |
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176
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# avoid a divide by zero). |
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177
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# |
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178
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0
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0
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my @array; |
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179
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0
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0
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my $pos = $N - 1; # initial extends |
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180
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0
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0
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my $count = 0; |
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181
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182
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0
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0
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my $y_total = 0; |
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183
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0
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0
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my $xy2_total = 0; |
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184
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0
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0
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my $xx2_total = 0; |
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185
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186
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return sub { |
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187
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0
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0
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0
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my ($y) = @_; |
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188
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189
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0
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0
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0
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if ($count >= $N) { |
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190
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# drop oldest point |
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191
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0
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0
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my $prev = $array[$pos]; |
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192
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0
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0
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$y_total -= $prev; |
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193
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0
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0
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$xy2_total += ($count-1) * $prev; |
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194
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} else { |
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195
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# gaining a point |
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196
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0
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0
|
$count++; |
|
197
|
0
|
|
|
|
|
0
|
$xy2_total += $y_total; # adj so below is 1 less x |
|
198
|
0
|
|
|
|
|
0
|
$xx2_total = max (1, linreg_xx2_calc($count)); |
|
199
|
|
|
|
|
|
|
} |
|
200
|
0
|
|
|
|
|
0
|
$array[$pos] = $y; |
|
201
|
0
|
0
|
|
|
|
0
|
if (++$pos >= $N) { $pos = 0; } |
|
|
0
|
|
|
|
|
0
|
|
|
202
|
|
|
|
|
|
|
|
|
203
|
|
|
|
|
|
|
# shift xy products onto 2 less x each |
|
204
|
0
|
|
|
|
|
0
|
$xy2_total -= ($y_total + $y_total); |
|
205
|
|
|
|
|
|
|
|
|
206
|
|
|
|
|
|
|
# add this point |
|
207
|
0
|
|
|
|
|
0
|
$y_total += $y; |
|
208
|
0
|
|
|
|
|
0
|
$xy2_total += ($count-1) * $y; |
|
209
|
|
|
|
|
|
|
|
|
210
|
0
|
|
|
|
|
0
|
my $b = $xy2_total / $xx2_total; |
|
211
|
|
|
|
|
|
|
|
|
212
|
0
|
|
|
|
|
0
|
return ($y_total/$count + $b*0.5*($count-1), |
|
213
|
|
|
|
|
|
|
$b); |
|
214
|
0
|
|
|
|
|
0
|
}; |
|
215
|
|
|
|
|
|
|
} |
|
216
|
|
|
|
|
|
|
|
|
217
|
|
|
|
|
|
|
# `xx2-calc' returns 2*Sum(X^2) for the set of N points centred around |
|
218
|
|
|
|
|
|
|
# zero as described in linreg-slop-calc-proc below. This means for |
|
219
|
|
|
|
|
|
|
# instance, |
|
220
|
|
|
|
|
|
|
# |
|
221
|
|
|
|
|
|
|
# N=4: 2 * [ (-1.5)^2 + (-0.5)^2 + (0.5)^2 + (1.5)^2 ] |
|
222
|
|
|
|
|
|
|
# N=5: 2 * [ (-2)^2 + (-1)^2 + 0^2 + (1)^2 + (2)^2 ] |
|
223
|
|
|
|
|
|
|
# |
|
224
|
|
|
|
|
|
|
# This is (N^3-N)/6, which can be established by taking successive |
|
225
|
|
|
|
|
|
|
# differences or verified by induction (done separately for odds and evens |
|
226
|
|
|
|
|
|
|
# is easiest). |
|
227
|
|
|
|
|
|
|
# |
|
228
|
|
|
|
|
|
|
# N^3-N is always a multiple of 6, since it can be written (N-1)*N*(N+1) |
|
229
|
|
|
|
|
|
|
# which is three consecutive numbers so one is certainly a multiple of 3 |
|
230
|
|
|
|
|
|
|
# and another a multiple of 2. The result is forced to inexact since |
|
231
|
|
|
|
|
|
|
# that's what's wanted for the linreg-slope-calc-proc returns. |
|
232
|
|
|
|
|
|
|
# |
|
233
|
|
|
|
|
|
|
sub linreg_xx2_calc { |
|
234
|
9
|
|
|
9
|
0
|
5836
|
my ($N) = @_; |
|
235
|
9
|
|
|
|
|
33
|
return $N*($N*$N-1) / 6; |
|
236
|
|
|
|
|
|
|
} |
|
237
|
|
|
|
|
|
|
|
|
238
|
|
|
|
|
|
|
1; |