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587 lines
21 KiB
587 lines
21 KiB
<?php |
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/*======================================================================= |
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// File: JPGRAPH_CONTOUR.PHP |
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// Description: Contour plot |
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// Created: 2009-03-08 |
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// Ver: $Id: jpgraph_contour.php 1870 2009-09-29 04:24:18Z ljp $ |
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// |
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// Copyright (c) Asial Corporation. All rights reserved. |
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//======================================================================== |
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*/ |
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require_once('jpgraph_meshinterpolate.inc.php'); |
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define('HORIZ_EDGE',0); |
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define('VERT_EDGE',1); |
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/** |
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* This class encapsulates the core contour plot algorithm. It will find the path |
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* of the specified isobars in the data matrix specified. It is assumed that the |
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* data matrix models an equspaced X-Y mesh of datavalues corresponding to the Z |
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* values. |
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* |
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*/ |
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class Contour { |
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private $dataPoints = array(); |
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private $nbrCols=0,$nbrRows=0; |
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private $horizEdges = array(), $vertEdges=array(); |
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private $isobarValues = array(); |
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private $stack = null; |
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private $isobarCoord = array(); |
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private $nbrIsobars = 10, $isobarColors = array(); |
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private $invert = true; |
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private $highcontrast = false, $highcontrastbw = false; |
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|
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/** |
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* Create a new contour level "algorithm machine". |
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* @param $aMatrix The values to find the contour from |
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* @param $aIsobars Mixed. If integer it determines the number of isobars to be used. The levels are determined |
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* automatically as equdistance between the min and max value of the matrice. |
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* If $aIsobars is an array then this is interpretated as an array of values to be used as isobars in the |
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* contour plot. |
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* @return an instance of the contour algorithm |
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*/ |
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function __construct($aMatrix,$aIsobars=10, $aColors=null) { |
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$this->nbrRows = count($aMatrix); |
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$this->nbrCols = count($aMatrix[0]); |
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$this->dataPoints = $aMatrix; |
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if( is_array($aIsobars) ) { |
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// use the isobar values supplied |
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$this->nbrIsobars = count($aIsobars); |
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$this->isobarValues = $aIsobars; |
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} |
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else { |
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// Determine the isobar values automatically |
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$this->nbrIsobars = $aIsobars; |
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list($min,$max) = $this->getMinMaxVal(); |
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$stepSize = ($max-$min) / $aIsobars ; |
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$isobar = $min+$stepSize/2; |
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for ($i = 0; $i < $aIsobars; $i++) { |
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$this->isobarValues[$i] = $isobar; |
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$isobar += $stepSize; |
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} |
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} |
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if( $aColors !== null && count($aColors) > 0 ) { |
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if( !is_array($aColors) ) { |
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JpGraphError::RaiseL(28001); |
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//'Third argument to Contour must be an array of colors.' |
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} |
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if( count($aColors) != count($this->isobarValues) ) { |
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JpGraphError::RaiseL(28002); |
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//'Number of colors must equal the number of isobar lines specified'; |
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} |
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$this->isobarColors = $aColors; |
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} |
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} |
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/** |
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* Flip the plot around the Y-coordinate. This has the same affect as flipping the input |
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* data matrice |
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* |
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* @param $aFlg If true the the vertice in input data matrice position (0,0) corresponds to the top left |
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* corner of teh plot otherwise it will correspond to the bottom left corner (a horizontal flip) |
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*/ |
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function SetInvert($aFlg=true) { |
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$this->invert = $aFlg; |
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} |
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/** |
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* Find the min and max values in the data matrice |
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* |
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* @return array(min_value,max_value) |
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*/ |
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function getMinMaxVal() { |
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$min = $this->dataPoints[0][0]; |
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$max = $this->dataPoints[0][0]; |
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for ($i = 0; $i < $this->nbrRows; $i++) { |
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if( ($mi=min($this->dataPoints[$i])) < $min ) $min = $mi; |
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if( ($ma=max($this->dataPoints[$i])) > $max ) $max = $ma; |
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} |
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return array($min,$max); |
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} |
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/** |
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* Reset the two matrices that keeps track on where the isobars crosses the |
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* horizontal and vertical edges |
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*/ |
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function resetEdgeMatrices() { |
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for ($k = 0; $k < 2; $k++) { |
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for ($i = 0; $i <= $this->nbrRows; $i++) { |
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for ($j = 0; $j <= $this->nbrCols; $j++) { |
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$this->edges[$k][$i][$j] = false; |
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} |
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} |
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} |
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} |
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/** |
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* Determine if the specified isobar crosses the horizontal edge specified by its row and column |
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* |
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* @param $aRow Row index of edge to be checked |
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* @param $aCol Col index of edge to be checked |
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* @param $aIsobar Isobar value |
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* @return true if the isobar is crossing this edge |
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*/ |
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function isobarHCrossing($aRow,$aCol,$aIsobar) { |
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if( $aCol >= $this->nbrCols-1 ) { |
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JpGraphError::RaiseL(28003,$aCol); |
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//'ContourPlot Internal Error: isobarHCrossing: Coloumn index too large (%d)' |
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} |
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if( $aRow >= $this->nbrRows ) { |
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JpGraphError::RaiseL(28004,$aRow); |
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//'ContourPlot Internal Error: isobarHCrossing: Row index too large (%d)' |
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} |
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$v1 = $this->dataPoints[$aRow][$aCol]; |
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$v2 = $this->dataPoints[$aRow][$aCol+1]; |
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return ($aIsobar-$v1)*($aIsobar-$v2) < 0 ; |
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} |
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/** |
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* Determine if the specified isobar crosses the vertical edge specified by its row and column |
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* |
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* @param $aRow Row index of edge to be checked |
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* @param $aCol Col index of edge to be checked |
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* @param $aIsobar Isobar value |
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* @return true if the isobar is crossing this edge |
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*/ |
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function isobarVCrossing($aRow,$aCol,$aIsobar) { |
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if( $aRow >= $this->nbrRows-1) { |
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JpGraphError::RaiseL(28005,$aRow); |
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//'isobarVCrossing: Row index too large |
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} |
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if( $aCol >= $this->nbrCols ) { |
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JpGraphError::RaiseL(28006,$aCol); |
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//'isobarVCrossing: Col index too large |
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} |
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$v1 = $this->dataPoints[$aRow][$aCol]; |
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$v2 = $this->dataPoints[$aRow+1][$aCol]; |
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return ($aIsobar-$v1)*($aIsobar-$v2) < 0 ; |
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} |
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/** |
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* Determine all edges, horizontal and vertical that the specified isobar crosses. The crossings |
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* are recorded in the two edge matrices. |
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* |
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* @param $aIsobar The value of the isobar to be checked |
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*/ |
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function determineIsobarEdgeCrossings($aIsobar) { |
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$ib = $this->isobarValues[$aIsobar]; |
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for ($i = 0; $i < $this->nbrRows-1; $i++) { |
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for ($j = 0; $j < $this->nbrCols-1; $j++) { |
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$this->edges[HORIZ_EDGE][$i][$j] = $this->isobarHCrossing($i,$j,$ib); |
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$this->edges[VERT_EDGE][$i][$j] = $this->isobarVCrossing($i,$j,$ib); |
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} |
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} |
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// We now have the bottom and rightmost edges unsearched |
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for ($i = 0; $i < $this->nbrRows-1; $i++) { |
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$this->edges[VERT_EDGE][$i][$j] = $this->isobarVCrossing($i,$this->nbrCols-1,$ib); |
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} |
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for ($j = 0; $j < $this->nbrCols-1; $j++) { |
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$this->edges[HORIZ_EDGE][$i][$j] = $this->isobarHCrossing($this->nbrRows-1,$j,$ib); |
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} |
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} |
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/** |
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* Return the normalized coordinates for the crossing of the specified edge with the specified |
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* isobar- The crossing is simpy detrmined with a linear interpolation between the two vertices |
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* on each side of the edge and the value of the isobar |
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* |
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* @param $aRow Row of edge |
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* @param $aCol Column of edge |
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* @param $aEdgeDir Determine if this is a horizontal or vertical edge |
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* @param $ib The isobar value |
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* @return unknown_type |
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*/ |
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function getCrossingCoord($aRow,$aCol,$aEdgeDir,$aIsobarVal) { |
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// In order to avoid numerical problem when two vertices are very close |
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// we have to check and avoid dividing by close to zero denumerator. |
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if( $aEdgeDir == HORIZ_EDGE ) { |
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$d = abs($this->dataPoints[$aRow][$aCol] - $this->dataPoints[$aRow][$aCol+1]); |
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if( $d > 0.001 ) { |
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$xcoord = $aCol + abs($aIsobarVal - $this->dataPoints[$aRow][$aCol]) / $d; |
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} |
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else { |
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$xcoord = $aCol; |
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} |
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$ycoord = $aRow; |
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} |
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else { |
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$d = abs($this->dataPoints[$aRow][$aCol] - $this->dataPoints[$aRow+1][$aCol]); |
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if( $d > 0.001 ) { |
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$ycoord = $aRow + abs($aIsobarVal - $this->dataPoints[$aRow][$aCol]) / $d; |
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} |
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else { |
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$ycoord = $aRow; |
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} |
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$xcoord = $aCol; |
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} |
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if( $this->invert ) { |
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$ycoord = $this->nbrRows-1 - $ycoord; |
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} |
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return array($xcoord,$ycoord); |
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} |
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/** |
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* In order to avoid all kinds of unpleasent extra checks and complex boundary |
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* controls for the degenerated case where the contour levels exactly crosses |
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* one of the vertices we add a very small delta (0.1%) to the data point value. |
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* This has no visible affect but it makes the code sooooo much cleaner. |
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* |
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*/ |
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function adjustDataPointValues() { |
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$ni = count($this->isobarValues); |
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for ($k = 0; $k < $ni; $k++) { |
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$ib = $this->isobarValues[$k]; |
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for ($row = 0 ; $row < $this->nbrRows-1; ++$row) { |
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for ($col = 0 ; $col < $this->nbrCols-1; ++$col ) { |
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if( abs($this->dataPoints[$row][$col] - $ib) < 0.0001 ) { |
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$this->dataPoints[$row][$col] += $this->dataPoints[$row][$col]*0.001; |
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} |
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} |
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} |
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} |
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} |
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/** |
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* @param $aFlg |
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* @param $aBW |
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* @return unknown_type |
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*/ |
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function UseHighContrastColor($aFlg=true,$aBW=false) { |
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$this->highcontrast = $aFlg; |
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$this->highcontrastbw = $aBW; |
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} |
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/** |
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* Calculate suitable colors for each defined isobar |
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* |
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*/ |
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function CalculateColors() { |
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if ( $this->highcontrast ) { |
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if ( $this->highcontrastbw ) { |
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for ($ib = 0; $ib < $this->nbrIsobars; $ib++) { |
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$this->isobarColors[$ib] = 'black'; |
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} |
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} |
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else { |
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// Use only blue/red scale |
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$step = round(255/($this->nbrIsobars-1)); |
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for ($ib = 0; $ib < $this->nbrIsobars; $ib++) { |
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$this->isobarColors[$ib] = array($ib*$step, 50, 255-$ib*$step); |
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} |
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} |
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} |
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else { |
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$n = $this->nbrIsobars; |
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$v = 0; $step = 1 / ($this->nbrIsobars-1); |
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for ($ib = 0; $ib < $this->nbrIsobars; $ib++) { |
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$this->isobarColors[$ib] = RGB::GetSpectrum($v); |
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$v += $step; |
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} |
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} |
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} |
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/** |
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* This is where the main work is done. For each isobar the crossing of the edges are determined |
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* and then each cell is analyzed to find the 0, 2 or 4 crossings. Then the normalized coordinate |
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* for the crossings are determined and pushed on to the isobar stack. When the method is finished |
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* the $isobarCoord will hold one arrayfor each isobar where all the line segments that makes |
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* up the contour plot are stored. |
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* |
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* @return array( $isobarCoord, $isobarValues, $isobarColors ) |
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*/ |
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function getIsobars() { |
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$this->adjustDataPointValues(); |
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for ($isobar = 0; $isobar < $this->nbrIsobars; $isobar++) { |
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$ib = $this->isobarValues[$isobar]; |
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$this->resetEdgeMatrices(); |
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$this->determineIsobarEdgeCrossings($isobar); |
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$this->isobarCoord[$isobar] = array(); |
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$ncoord = 0; |
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for ($row = 0 ; $row < $this->nbrRows-1; ++$row) { |
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for ($col = 0 ; $col < $this->nbrCols-1; ++$col ) { |
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// Find out how many crossings around the edges |
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$n = 0; |
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if ( $this->edges[HORIZ_EDGE][$row][$col] ) $neigh[$n++] = array($row, $col, HORIZ_EDGE); |
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if ( $this->edges[HORIZ_EDGE][$row+1][$col] ) $neigh[$n++] = array($row+1,$col, HORIZ_EDGE); |
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if ( $this->edges[VERT_EDGE][$row][$col] ) $neigh[$n++] = array($row, $col, VERT_EDGE); |
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if ( $this->edges[VERT_EDGE][$row][$col+1] ) $neigh[$n++] = array($row, $col+1,VERT_EDGE); |
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if ( $n == 2 ) { |
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$n1=0; $n2=1; |
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$this->isobarCoord[$isobar][$ncoord++] = array( |
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$this->getCrossingCoord($neigh[$n1][0],$neigh[$n1][1],$neigh[$n1][2],$ib), |
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$this->getCrossingCoord($neigh[$n2][0],$neigh[$n2][1],$neigh[$n2][2],$ib) ); |
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} |
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elseif ( $n == 4 ) { |
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// We must determine how to connect the edges either northwest->southeast or |
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// northeast->southwest. We do that by calculating the imaginary middle value of |
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// the cell by averaging the for corners. This will compared with the value of the |
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// top left corner will help determine the orientation of the ridge/creek |
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$midval = ($this->dataPoints[$row][$col]+$this->dataPoints[$row][$col+1]+$this->dataPoints[$row+1][$col]+$this->dataPoints[$row+1][$col+1])/4; |
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$v = $this->dataPoints[$row][$col]; |
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if( $midval == $ib ) { |
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// Orientation "+" |
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$n1=0; $n2=1; $n3=2; $n4=3; |
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} elseif ( ($midval > $ib && $v > $ib) || ($midval < $ib && $v < $ib) ) { |
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// Orientation of ridge/valley = "\" |
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$n1=0; $n2=3; $n3=2; $n4=1; |
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} elseif ( ($midval > $ib && $v < $ib) || ($midval < $ib && $v > $ib) ) { |
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// Orientation of ridge/valley = "/" |
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$n1=0; $n2=2; $n3=3; $n4=1; |
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} |
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$this->isobarCoord[$isobar][$ncoord++] = array( |
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$this->getCrossingCoord($neigh[$n1][0],$neigh[$n1][1],$neigh[$n1][2],$ib), |
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$this->getCrossingCoord($neigh[$n2][0],$neigh[$n2][1],$neigh[$n2][2],$ib) ); |
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$this->isobarCoord[$isobar][$ncoord++] = array( |
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$this->getCrossingCoord($neigh[$n3][0],$neigh[$n3][1],$neigh[$n3][2],$ib), |
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$this->getCrossingCoord($neigh[$n4][0],$neigh[$n4][1],$neigh[$n4][2],$ib) ); |
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} |
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} |
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} |
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} |
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if( count($this->isobarColors) == 0 ) { |
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// No manually specified colors. Calculate them automatically. |
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$this->CalculateColors(); |
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} |
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return array( $this->isobarCoord, $this->isobarValues, $this->isobarColors ); |
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} |
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} |
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/** |
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* This class represent a plotting of a contour outline of data given as a X-Y matrice |
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* |
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*/ |
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class ContourPlot extends Plot { |
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private $contour, $contourCoord, $contourVal, $contourColor; |
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private $nbrCountours = 0 ; |
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private $dataMatrix = array(); |
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private $invertLegend = false; |
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private $interpFactor = 1; |
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private $flipData = false; |
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private $isobar = 10; |
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private $showLegend = false; |
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private $highcontrast = false, $highcontrastbw = false; |
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private $manualIsobarColors = array(); |
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/** |
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* Construct a contour plotting algorithm. The end result of the algorithm is a sequence of |
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* line segments for each isobar given as two vertices. |
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* |
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* @param $aDataMatrix The Z-data to be used |
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* @param $aIsobar A mixed variable, if it is an integer then this specified the number of isobars to use. |
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* The values of the isobars are automatically detrmined to be equ-spaced between the min/max value of the |
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* data. If it is an array then it explicetely gives the isobar values |
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* @param $aInvert By default the matrice with row index 0 corresponds to Y-value 0, i.e. in the bottom of |
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* the plot. If this argument is true then the row with the highest index in the matrice corresponds to |
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* Y-value 0. In affect flipping the matrice around an imaginary horizontal axis. |
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* @param $aHighContrast Use high contrast colors (blue/red:ish) |
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* @param $aHighContrastBW Use only black colors for contours |
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* @return an instance of the contour plot algorithm |
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*/ |
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function __construct($aDataMatrix, $aIsobar=10, $aFactor=1, $aInvert=false, $aIsobarColors=array()) { |
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$this->dataMatrix = $aDataMatrix; |
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$this->flipData = $aInvert; |
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$this->isobar = $aIsobar; |
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$this->interpFactor = $aFactor; |
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if ( $this->interpFactor > 1 ) { |
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if( $this->interpFactor > 5 ) { |
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JpGraphError::RaiseL(28007);// ContourPlot interpolation factor is too large (>5) |
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} |
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$ip = new MeshInterpolate(); |
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$this->dataMatrix = $ip->Linear($this->dataMatrix, $this->interpFactor); |
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} |
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$this->contour = new Contour($this->dataMatrix,$this->isobar,$aIsobarColors); |
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if( is_array($aIsobar) ) |
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$this->nbrContours = count($aIsobar); |
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else |
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$this->nbrContours = $aIsobar; |
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} |
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/** |
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* Flipe the data around the center |
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* |
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* @param $aFlg |
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* |
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*/ |
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function SetInvert($aFlg=true) { |
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$this->flipData = $aFlg; |
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} |
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|
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/** |
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* Set the colors for the isobar lines |
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* |
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* @param $aColorArray |
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* |
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*/ |
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function SetIsobarColors($aColorArray) { |
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$this->manualIsobarColors = $aColorArray; |
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} |
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/** |
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* Show the legend |
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* |
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* @param $aFlg true if the legend should be shown |
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* |
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*/ |
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function ShowLegend($aFlg=true) { |
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$this->showLegend = $aFlg; |
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} |
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/** |
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* @param $aFlg true if the legend should start with the lowest isobar on top |
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* @return unknown_type |
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*/ |
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function Invertlegend($aFlg=true) { |
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$this->invertLegend = $aFlg; |
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} |
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|
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/* Internal method. Give the min value to be used for the scaling |
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* |
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*/ |
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function Min() { |
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return array(0,0); |
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} |
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|
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/* Internal method. Give the max value to be used for the scaling |
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* |
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*/ |
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function Max() { |
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return array(count($this->dataMatrix[0])-1,count($this->dataMatrix)-1); |
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} |
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|
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/** |
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* Internal ramewrok method to setup the legend to be used for this plot. |
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* @param $aGraph The parent graph class |
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*/ |
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function Legend($aGraph) { |
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|
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if( ! $this->showLegend ) |
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return; |
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|
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if( $this->invertLegend ) { |
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for ($i = 0; $i < $this->nbrContours; $i++) { |
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$aGraph->legend->Add(sprintf('%.1f',$this->contourVal[$i]), $this->contourColor[$i]); |
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} |
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} |
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else { |
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for ($i = $this->nbrContours-1; $i >= 0 ; $i--) { |
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$aGraph->legend->Add(sprintf('%.1f',$this->contourVal[$i]), $this->contourColor[$i]); |
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} |
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} |
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} |
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/** |
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* Framework function which gets called before the Stroke() method is called |
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* |
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* @see Plot#PreScaleSetup($aGraph) |
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* |
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*/ |
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function PreScaleSetup($aGraph) { |
|
$xn = count($this->dataMatrix[0])-1; |
|
$yn = count($this->dataMatrix)-1; |
|
|
|
$aGraph->xaxis->scale->Update($aGraph->img,0,$xn); |
|
$aGraph->yaxis->scale->Update($aGraph->img,0,$yn); |
|
|
|
$this->contour->SetInvert($this->flipData); |
|
list($this->contourCoord,$this->contourVal,$this->contourColor) = $this->contour->getIsobars(); |
|
} |
|
|
|
/** |
|
* Use high contrast color schema |
|
* |
|
* @param $aFlg True, to use high contrast color |
|
* @param $aBW True, Use only black and white color schema |
|
*/ |
|
function UseHighContrastColor($aFlg=true,$aBW=false) { |
|
$this->highcontrast = $aFlg; |
|
$this->highcontrastbw = $aBW; |
|
$this->contour->UseHighContrastColor($this->highcontrast,$this->highcontrastbw); |
|
} |
|
|
|
/** |
|
* Internal method. Stroke the contour plot to the graph |
|
* |
|
* @param $img Image handler |
|
* @param $xscale Instance of the xscale to use |
|
* @param $yscale Instance of the yscale to use |
|
*/ |
|
function Stroke($img,$xscale,$yscale) { |
|
|
|
if( count($this->manualIsobarColors) > 0 ) { |
|
$this->contourColor = $this->manualIsobarColors; |
|
if( count($this->manualIsobarColors) != $this->nbrContours ) { |
|
JpGraphError::RaiseL(28002); |
|
} |
|
} |
|
|
|
$img->SetLineWeight($this->line_weight); |
|
|
|
for ($c = 0; $c < $this->nbrContours; $c++) { |
|
|
|
$img->SetColor( $this->contourColor[$c] ); |
|
|
|
$n = count($this->contourCoord[$c]); |
|
$i = 0; |
|
while ( $i < $n ) { |
|
list($x1,$y1) = $this->contourCoord[$c][$i][0]; |
|
$x1t = $xscale->Translate($x1); |
|
$y1t = $yscale->Translate($y1); |
|
|
|
list($x2,$y2) = $this->contourCoord[$c][$i++][1]; |
|
$x2t = $xscale->Translate($x2); |
|
$y2t = $yscale->Translate($y2); |
|
|
|
$img->Line($x1t,$y1t,$x2t,$y2t); |
|
} |
|
|
|
} |
|
} |
|
|
|
} |
|
|
|
// EOF |
|
?>
|
|
|