[267] | 1 | <?php
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[2] | 2 | /*=======================================================================
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[267] | 3 | // File: JPGRAPH_REGSTAT.PHP
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| 4 | // Description: Regression and statistical analysis helper classes
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| 5 | // Created: 2002-12-01
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| 6 | // Ver: $Id: jpgraph_regstat.php 781 2006-10-08 08:07:47Z ljp $
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| 7 | //
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| 8 | // Copyright (c) Aditus Consulting. All rights reserved.
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| 9 | //========================================================================
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| 10 | */
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[2] | 11 |
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| 12 | //------------------------------------------------------------------------
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| 13 | // CLASS Spline
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| 14 | // Create a new data array from an existing data array but with more points.
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| 15 | // The new points are interpolated using a cubic spline algorithm
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| 16 | //------------------------------------------------------------------------
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| 17 | class Spline {
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| 18 | // 3:rd degree polynom approximation
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| 19 |
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| 20 | private $xdata,$ydata; // Data vectors
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[267] | 21 | private $y2; // 2:nd derivate of ydata
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[2] | 22 | private $n=0;
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| 23 |
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[267] | 24 | function Spline($xdata,$ydata) {
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| 25 | $this->y2 = array();
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| 26 | $this->xdata = $xdata;
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| 27 | $this->ydata = $ydata;
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[2] | 28 |
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[267] | 29 | $n = count($ydata);
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| 30 | $this->n = $n;
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| 31 | if( $this->n !== count($xdata) ) {
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| 32 | JpGraphError::RaiseL(19001);
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| 33 | //('Spline: Number of X and Y coordinates must be the same');
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| 34 | }
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[2] | 35 |
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[267] | 36 | // Natural spline 2:derivate == 0 at endpoints
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| 37 | $this->y2[0] = 0.0;
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| 38 | $this->y2[$n-1] = 0.0;
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| 39 | $delta[0] = 0.0;
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[2] | 40 |
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[267] | 41 | // Calculate 2:nd derivate
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| 42 | for($i=1; $i < $n-1; ++$i) {
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| 43 | $d = ($xdata[$i+1]-$xdata[$i-1]);
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| 44 | if( $d == 0 ) {
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| 45 | JpGraphError::RaiseL(19002);
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| 46 | //('Invalid input data for spline. Two or more consecutive input X-values are equal. Each input X-value must differ since from a mathematical point of view it must be a one-to-one mapping, i.e. each X-value must correspond to exactly one Y-value.');
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| 47 | }
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| 48 | $s = ($xdata[$i]-$xdata[$i-1])/$d;
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| 49 | $p = $s*$this->y2[$i-1]+2.0;
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| 50 | $this->y2[$i] = ($s-1.0)/$p;
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| 51 | $delta[$i] = ($ydata[$i+1]-$ydata[$i])/($xdata[$i+1]-$xdata[$i]) -
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| 52 | ($ydata[$i]-$ydata[$i-1])/($xdata[$i]-$xdata[$i-1]);
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| 53 | $delta[$i] = (6.0*$delta[$i]/($xdata[$i+1]-$xdata[$i-1])-$s*$delta[$i-1])/$p;
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| 54 | }
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[2] | 55 |
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[267] | 56 | // Backward substitution
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| 57 | for( $j=$n-2; $j >= 0; --$j ) {
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| 58 | $this->y2[$j] = $this->y2[$j]*$this->y2[$j+1] + $delta[$j];
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| 59 | }
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[2] | 60 | }
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| 61 |
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| 62 | // Return the two new data vectors
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| 63 | function Get($num=50) {
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[267] | 64 | $n = $this->n ;
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| 65 | $step = ($this->xdata[$n-1]-$this->xdata[0]) / ($num-1);
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| 66 | $xnew=array();
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| 67 | $ynew=array();
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| 68 | $xnew[0] = $this->xdata[0];
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| 69 | $ynew[0] = $this->ydata[0];
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| 70 | for( $j=1; $j < $num; ++$j ) {
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| 71 | $xnew[$j] = $xnew[0]+$j*$step;
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| 72 | $ynew[$j] = $this->Interpolate($xnew[$j]);
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| 73 | }
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| 74 | return array($xnew,$ynew);
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[2] | 75 | }
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| 76 |
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| 77 | // Return a single interpolated Y-value from an x value
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| 78 | function Interpolate($xpoint) {
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| 79 |
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[267] | 80 | $max = $this->n-1;
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| 81 | $min = 0;
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[2] | 82 |
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[267] | 83 | // Binary search to find interval
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| 84 | while( $max-$min > 1 ) {
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| 85 | $k = ($max+$min) / 2;
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| 86 | if( $this->xdata[$k] > $xpoint )
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| 87 | $max=$k;
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| 88 | else
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| 89 | $min=$k;
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| 90 | }
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[2] | 91 |
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[267] | 92 | // Each interval is interpolated by a 3:degree polynom function
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| 93 | $h = $this->xdata[$max]-$this->xdata[$min];
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[2] | 94 |
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[267] | 95 | if( $h == 0 ) {
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| 96 | JpGraphError::RaiseL(19002);
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| 97 | //('Invalid input data for spline. Two or more consecutive input X-values are equal. Each input X-value must differ since from a mathematical point of view it must be a one-to-one mapping, i.e. each X-value must correspond to exactly one Y-value.');
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| 98 | }
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[2] | 99 |
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| 100 |
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[267] | 101 | $a = ($this->xdata[$max]-$xpoint)/$h;
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| 102 | $b = ($xpoint-$this->xdata[$min])/$h;
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| 103 | return $a*$this->ydata[$min]+$b*$this->ydata[$max]+
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| 104 | (($a*$a*$a-$a)*$this->y2[$min]+($b*$b*$b-$b)*$this->y2[$max])*($h*$h)/6.0;
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[2] | 105 | }
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| 106 | }
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| 107 |
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| 108 | //------------------------------------------------------------------------
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| 109 | // CLASS Bezier
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| 110 | // Create a new data array from a number of control points
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| 111 | //------------------------------------------------------------------------
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| 112 | class Bezier {
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[267] | 113 | /**
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| 114 | * @author Thomas Despoix, openXtrem company
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| 115 | * @license released under QPL
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| 116 | * @abstract Bezier interoplated point generation,
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| 117 | * computed from control points data sets, based on Paul Bourke algorithm :
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| 118 | * http://astronomy.swin.edu.au/~pbourke/curves/bezier/
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| 119 | */
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[2] | 120 | private $datax = array();
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| 121 | private $datay = array();
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| 122 | private $n=0;
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[267] | 123 |
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| 124 | function Bezier($datax, $datay, $attraction_factor = 1) {
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| 125 | // Adding control point multiple time will raise their attraction power over the curve
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| 126 | $this->n = count($datax);
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| 127 | if( $this->n !== count($datay) ) {
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| 128 | JpGraphError::RaiseL(19003);
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| 129 | //('Bezier: Number of X and Y coordinates must be the same');
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| 130 | }
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| 131 | $idx=0;
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| 132 | foreach($datax as $datumx) {
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| 133 | for ($i = 0; $i < $attraction_factor; $i++) {
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| 134 | $this->datax[$idx++] = $datumx;
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| 135 | }
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| 136 | }
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| 137 | $idx=0;
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| 138 | foreach($datay as $datumy) {
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| 139 | for ($i = 0; $i < $attraction_factor; $i++) {
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| 140 | $this->datay[$idx++] = $datumy;
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| 141 | }
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| 142 | }
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| 143 | $this->n *= $attraction_factor;
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[2] | 144 | }
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| 145 |
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| 146 | function Get($steps) {
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[267] | 147 | $datax = array();
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| 148 | $datay = array();
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| 149 | for ($i = 0; $i < $steps; $i++) {
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| 150 | list($datumx, $datumy) = $this->GetPoint((double) $i / (double) $steps);
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| 151 | $datax[] = $datumx;
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| 152 | $datay[] = $datumy;
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| 153 | }
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| 154 |
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| 155 | $datax[] = end($this->datax);
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| 156 | $datay[] = end($this->datay);
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| 157 |
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| 158 | return array($datax, $datay);
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[2] | 159 | }
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[267] | 160 |
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[2] | 161 | function GetPoint($mu) {
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[267] | 162 | $n = $this->n - 1;
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| 163 | $k = 0;
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| 164 | $kn = 0;
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| 165 | $nn = 0;
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| 166 | $nkn = 0;
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| 167 | $blend = 0.0;
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| 168 | $newx = 0.0;
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| 169 | $newy = 0.0;
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[2] | 170 |
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[267] | 171 | $muk = 1.0;
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| 172 | $munk = (double) pow(1-$mu,(double) $n);
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[2] | 173 |
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[267] | 174 | for ($k = 0; $k <= $n; $k++) {
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| 175 | $nn = $n;
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| 176 | $kn = $k;
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| 177 | $nkn = $n - $k;
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| 178 | $blend = $muk * $munk;
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| 179 | $muk *= $mu;
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| 180 | $munk /= (1-$mu);
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| 181 | while ($nn >= 1) {
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| 182 | $blend *= $nn;
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| 183 | $nn--;
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| 184 | if ($kn > 1) {
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| 185 | $blend /= (double) $kn;
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| 186 | $kn--;
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| 187 | }
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| 188 | if ($nkn > 1) {
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| 189 | $blend /= (double) $nkn;
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| 190 | $nkn--;
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| 191 | }
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| 192 | }
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| 193 | $newx += $this->datax[$k] * $blend;
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| 194 | $newy += $this->datay[$k] * $blend;
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| 195 | }
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[2] | 196 |
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[267] | 197 | return array($newx, $newy);
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[2] | 198 | }
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| 199 | }
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| 200 |
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| 201 | // EOF
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| 202 | ?>
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