614 lines
21 KiB
PHP
Executable File
614 lines
21 KiB
PHP
Executable File
<?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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{
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private $dataPoints = array();
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private $nbrCols=0;
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private $nbrRows=0;
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private $horizEdges = array();
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private $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;
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private $isobarColors = array();
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private $invert = true;
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private $highcontrast = false;
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private $highcontrastbw = false;
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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 $aIsobars is an array then this is interpretated as an array of values to be used as isobars in the
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* contour plot.
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* @return an instance of the contour algorithm
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*/
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public function __construct($aMatrix, $aIsobars=10, $aColors=null)
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{
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$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 = $aIsobars;
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} else {
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// Determine the isobar values automatically
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$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 $aFlg If true the the vertice in input data matrice position (0,0) corresponds to the top left
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* corner of teh plot otherwise it will correspond to the bottom left corner (a horizontal flip)
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*/
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public function SetInvert($aFlg=true)
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{
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$this->invert = $aFlg;
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}
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/**
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* Find the min and max values in the data matrice
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*
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* @return array(min_value,max_value)
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*/
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public function getMinMaxVal()
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{
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$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])) < $min) {
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$min = $mi;
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}
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if (($ma=max($this->dataPoints[$i])) > $max) {
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$max = $ma;
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}
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}
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return array($min,$max);
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}
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/**
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* Reset the two matrices that keeps track on where the isobars crosses the
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* horizontal and vertical edges
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*/
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public function resetEdgeMatrices()
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{
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for ($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 $aIsobar Isobar value
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* @return true if the isobar is crossing this edge
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*/
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public function isobarHCrossing($aRow, $aCol, $aIsobar)
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{
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if ($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 $aIsobar Isobar value
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* @return true if the isobar is crossing this edge
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*/
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public function isobarVCrossing($aRow, $aCol, $aIsobar)
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{
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if ($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 $aIsobar The value of the isobar to be checked
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*/
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public function determineIsobarEdgeCrossings($aIsobar)
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{
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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 $ib The isobar value
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* @return unknown_type
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*/
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public function getCrossingCoord($aRow, $aCol, $aEdgeDir, $aIsobarVal)
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{
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// In order to avoid numerical problem when two vertices are very close
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// we have to check and avoid dividing by close to zero denumerator.
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if ($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]) / $d;
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} else {
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$xcoord = $aCol;
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}
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$ycoord = $aRow;
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} else {
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$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]) / $d;
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} else {
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$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,$ycoord);
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}
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/**
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* In order to avoid all kinds of unpleasent extra checks and complex boundary
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* controls for the degenerated case where the contour levels exactly crosses
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* one of the vertices we add a very small delta (0.1%) to the data point value.
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* This has no visible affect but it makes the code sooooo much cleaner.
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*
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*/
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public function adjustDataPointValues()
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{
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$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 $aBW
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* @return unknown_type
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*/
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public function UseHighContrastColor($aFlg=true, $aBW=false)
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{
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$this->highcontrast = $aFlg;
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$this->highcontrastbw = $aBW;
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}
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/**
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* Calculate suitable colors for each defined isobar
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*
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*/
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public function CalculateColors()
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{
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if ($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[$ib] = 'black';
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}
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} else {
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// Use only blue/red scale
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$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*$step);
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}
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}
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} else {
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$n = $this->nbrIsobars;
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$v = 0;
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$step = 1 / ($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, $isobarColors )
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*/
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public function getIsobars()
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{
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$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]) {
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$neigh[$n++] = array($row, $col, HORIZ_EDGE);
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}
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if ($this->edges[HORIZ_EDGE][$row+1][$col]) {
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$neigh[$n++] = array($row+1,$col, HORIZ_EDGE);
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}
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if ($this->edges[VERT_EDGE][$row][$col]) {
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$neigh[$n++] = array($row, $col, VERT_EDGE);
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}
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if ($this->edges[VERT_EDGE][$row][$col+1]) {
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$neigh[$n++] = array($row, $col+1,VERT_EDGE);
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}
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if ($n == 2) {
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$n1=0;
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$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], $ib) );
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} elseif ($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;
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$n2=1;
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$n3=2;
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$n4=3;
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} elseif (($midval > $ib && $v > $ib) || ($midval < $ib && $v < $ib)) {
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// Orientation of ridge/valley = "\"
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$n1=0;
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$n2=3;
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$n3=2;
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$n4=1;
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} elseif (($midval > $ib && $v < $ib) || ($midval < $ib && $v > $ib)) {
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// Orientation of ridge/valley = "/"
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$n1=0;
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$n2=2;
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$n3=3;
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$n4=1;
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}
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$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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{
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private $contour;
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private $contourCoord;
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private $contourVal;
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private $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;
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private $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 $aHighContrastBW Use only black colors for contours
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* @return an instance of the contour plot algorithm
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*/
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public function __construct($aDataMatrix, $aIsobar=10, $aFactor=1, $aInvert=false, $aIsobarColors=array())
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{
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$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
|
|
*
|
|
* @param $aFlg
|
|
*
|
|
*/
|
|
public function SetInvert($aFlg=true)
|
|
{
|
|
$this->flipData = $aFlg;
|
|
}
|
|
|
|
/**
|
|
* Set the colors for the isobar lines
|
|
*
|
|
* @param $aColorArray
|
|
*
|
|
*/
|
|
public function SetIsobarColors($aColorArray)
|
|
{
|
|
$this->manualIsobarColors = $aColorArray;
|
|
}
|
|
|
|
/**
|
|
* Show the legend
|
|
*
|
|
* @param $aFlg true if the legend should be shown
|
|
*
|
|
*/
|
|
public function ShowLegend($aFlg=true)
|
|
{
|
|
$this->showLegend = $aFlg;
|
|
}
|
|
|
|
|
|
/**
|
|
* @param $aFlg true if the legend should start with the lowest isobar on top
|
|
* @return unknown_type
|
|
*/
|
|
public function Invertlegend($aFlg=true)
|
|
{
|
|
$this->invertLegend = $aFlg;
|
|
}
|
|
|
|
/* Internal method. Give the min value to be used for the scaling
|
|
*
|
|
*/
|
|
public function Min()
|
|
{
|
|
return array(0,0);
|
|
}
|
|
|
|
/* Internal method. Give the max value to be used for the scaling
|
|
*
|
|
*/
|
|
public function Max()
|
|
{
|
|
return array(count($this->dataMatrix[0])-1,count($this->dataMatrix)-1);
|
|
}
|
|
|
|
/**
|
|
* Internal ramewrok method to setup the legend to be used for this plot.
|
|
* @param $aGraph The parent graph class
|
|
*/
|
|
public function Legend($aGraph)
|
|
{
|
|
if (! $this->showLegend) {
|
|
return;
|
|
}
|
|
|
|
if ($this->invertLegend) {
|
|
for ($i = 0; $i < $this->nbrContours; $i++) {
|
|
$aGraph->legend->Add(sprintf('%.1f', $this->contourVal[$i]), $this->contourColor[$i]);
|
|
}
|
|
} else {
|
|
for ($i = $this->nbrContours-1; $i >= 0 ; $i--) {
|
|
$aGraph->legend->Add(sprintf('%.1f', $this->contourVal[$i]), $this->contourColor[$i]);
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/**
|
|
* Framework function which gets called before the Stroke() method is called
|
|
*
|
|
* @see Plot#PreScaleSetup($aGraph)
|
|
*
|
|
*/
|
|
public function PreScaleSetup($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 $aBW True, Use only black and white color schema
|
|
*/
|
|
public function UseHighContrastColor($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 $yscale Instance of the yscale to use
|
|
*/
|
|
public function Stroke($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
|