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+/**
+* geostats() is a tiny and standalone javascript library for classification
+* Project page - https://github.com/simogeo/geostats
+* Copyright (c) 2011 Simon Georget, http://www.empreinte-urbaine.eu
+* Licensed under the MIT license
+*/
+
+
+(function (definition) {
+ // This file will function properly as a <script> tag, or a module
+ // using CommonJS and NodeJS or RequireJS module formats.
+
+ // CommonJS
+ if (typeof exports === "object") {
+ module.exports = definition();
+
+ // RequireJS
+ } else if (typeof define === "function" && define.amd) {
+ define(definition);
+
+ // <script>
+ } else {
+ geostats = definition();
+ }
+
+})(function () {
+
+var isInt = function(n) {
+ return typeof n === 'number' && parseFloat(n) == parseInt(n, 10) && !isNaN(n);
+} // 6 characters
+
+var _t = function(str) {
+ return str;
+};
+
+//taking from http://stackoverflow.com/questions/18082/validate-decimal-numbers-in-javascript-isnumeric
+var isNumber = function(n) {
+ return !isNaN(parseFloat(n)) && isFinite(n);
+}
+
+
+
+//indexOf polyfill
+// from https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/indexOf
+if (!Array.prototype.indexOf) {
+ Array.prototype.indexOf = function (searchElement, fromIndex) {
+ if ( this === undefined || this === null ) {
+ throw new TypeError( '"this" is null or not defined' );
+ }
+
+ var length = this.length >>> 0; // Hack to convert object.length to a UInt32
+
+ fromIndex = +fromIndex || 0;
+
+ if (Math.abs(fromIndex) === Infinity) {
+ fromIndex = 0;
+ }
+
+ if (fromIndex < 0) {
+ fromIndex += length;
+ if (fromIndex < 0) {
+ fromIndex = 0;
+ }
+ }
+
+ for (;fromIndex < length; fromIndex++) {
+ if (this[fromIndex] === searchElement) {
+ return fromIndex;
+ }
+ }
+
+ return -1;
+ };
+ }
+
+var geostats = function(a) {
+
+ this.objectID = '';
+ this.separator = ' - ';
+ this.legendSeparator = this.separator;
+ this.method = '';
+ this.precision = 0;
+ this.precisionflag = 'auto';
+ this.roundlength = 2; // Number of decimals, round values
+ this.is_uniqueValues = false;
+ this.debug = false;
+ this.silent = false;
+
+ this.bounds = Array();
+ this.ranges = Array();
+ this.inner_ranges = null;
+ this.colors = Array();
+ this.counter = Array();
+
+ // statistics information
+ this.stat_sorted = null;
+ this.stat_mean = null;
+ this.stat_median = null;
+ this.stat_sum = null;
+ this.stat_max = null;
+ this.stat_min = null;
+ this.stat_pop = null;
+ this.stat_variance = null;
+ this.stat_stddev = null;
+ this.stat_cov = null;
+
+
+ /**
+ * logging method
+ */
+ this.log = function(msg, force) {
+
+ if(this.debug == true || force != null)
+ console.log(this.objectID + "(object id) :: " + msg);
+
+ };
+
+ /**
+ * Set bounds
+ */
+ this.setBounds = function(a) {
+
+ this.log('Setting bounds (' + a.length + ') : ' + a.join());
+
+ this.bounds = Array() // init empty array to prevent bug when calling classification after another with less items (sample getQuantile(6) and getQuantile(4))
+
+ this.bounds = a;
+ //this.bounds = this.decimalFormat(a);
+
+ };
+
+ /**
+ * Set a new serie
+ */
+ this.setSerie = function(a) {
+
+ this.log('Setting serie (' + a.length + ') : ' + a.join());
+
+ this.serie = Array() // init empty array to prevent bug when calling classification after another with less items (sample getQuantile(6) and getQuantile(4))
+ this.serie = a;
+ this.setPrecision();
+
+ };
+
+ /**
+ * Set colors
+ */
+ this.setColors = function(colors) {
+
+ this.log('Setting color ramp (' + colors.length + ') : ' + colors.join());
+
+ this.colors = colors;
+
+ };
+
+ /**
+ * Get feature count
+ * With bounds array(0, 0.75, 1.5, 2.25, 3);
+ * should populate this.counter with 5 keys
+ * and increment counters for each key
+ */
+ this.doCount = function() {
+
+ if (this._nodata())
+ return;
+
+
+ var tmp = this.sorted();
+
+ this.counter = new Array();
+
+ // we init counter with 0 value
+ for(i = 0; i < this.bounds.length -1; i++) {
+ this.counter[i]= 0;
+ }
+
+ for(j=0; j < tmp.length; j++) {
+
+ // get current class for value to increment the counter
+ var cclass = this.getClass(tmp[j]);
+ this.counter[cclass]++;
+
+ }
+
+ };
+
+ /**
+ * Set decimal precision according to user input
+ * or automatcally determined according
+ * to the given serie.
+ */
+ this.setPrecision = function(decimals) {
+
+ // only when called from user
+ if(typeof decimals !== "undefined") {
+ this.precisionflag = 'manual';
+ this.precision = decimals;
+ }
+
+ // we calculate the maximal decimal length on given serie
+ if(this.precisionflag == 'auto') {
+
+ for (var i = 0; i < this.serie.length; i++) {
+
+ // check if the given value is a number and a float
+ if (!isNaN((this.serie[i]+"")) && (this.serie[i]+"").toString().indexOf('.') != -1) {
+ var precision = (this.serie[i] + "").split(".")[1].length;
+ } else {
+ var precision = 0;
+ }
+
+ if(precision > this.precision) {
+ this.precision = precision;
+ }
+
+ }
+
+ }
+
+ this.log('Calling setPrecision(). Mode : ' + this.precisionflag + ' - Decimals : '+ this.precision);
+
+ this.serie = this.decimalFormat(this.serie);
+
+ };
+
+ /**
+ * Format array numbers regarding to precision
+ */
+ this.decimalFormat = function(a) {
+
+ var b = new Array();
+
+ for (var i = 0; i < a.length; i++) {
+ // check if the given value is a number
+ if (isNumber(a[i])) {
+ b[i] = parseFloat(a[i].toFixed(this.precision));
+ } else {
+ b[i] = a[i];
+ }
+ }
+
+ return b;
+ }
+
+ /**
+ * Transform a bounds array to a range array the following array : array(0,
+ * 0.75, 1.5, 2.25, 3); becomes : array('0-0.75', '0.75-1.5', '1.5-2.25',
+ * '2.25-3');
+ */
+ this.setRanges = function() {
+
+ this.ranges = Array(); // init empty array to prevent bug when calling classification after another with less items (sample getQuantile(6) and getQuantile(4))
+
+ for (i = 0; i < (this.bounds.length - 1); i++) {
+ this.ranges[i] = this.bounds[i] + this.separator + this.bounds[i + 1];
+ }
+ };
+
+ /** return min value */
+ this.min = function() {
+
+ if (this._nodata())
+ return;
+
+ this.stat_min = Math.min.apply(null, this.serie);
+
+ return this.stat_min;
+ };
+
+ /** return max value */
+ this.max = function() {
+
+ this.stat_max = Math.max.apply(null, this.serie);
+
+ return this.stat_max;
+ };
+
+ /** return sum value */
+ this.sum = function() {
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_sum == null) {
+
+ this.stat_sum = 0;
+ for (i = 0; i < this.pop(); i++) {
+ this.stat_sum += parseFloat(this.serie[i]);
+ }
+
+ }
+
+ return this.stat_sum;
+ };
+
+ /** return population number */
+ this.pop = function() {
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_pop == null) {
+
+ this.stat_pop = this.serie.length;
+
+ }
+
+ return this.stat_pop;
+ };
+
+ /** return mean value */
+ this.mean = function() {
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_mean == null) {
+
+ this.stat_mean = parseFloat(this.sum() / this.pop());
+
+ }
+
+ return this.stat_mean;
+ };
+
+ /** return median value */
+ this.median = function() {
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_median == null) {
+
+ this.stat_median = 0;
+ var tmp = this.sorted();
+
+ // serie pop is odd
+ if (tmp.length % 2) {
+ this.stat_median = parseFloat(tmp[(Math.ceil(tmp.length / 2) - 1)]);
+
+ // serie pop is even
+ } else {
+ this.stat_median = ( parseFloat(tmp[((tmp.length / 2) - 1)]) + parseFloat(tmp[(tmp.length / 2)]) ) / 2;
+ }
+
+ }
+
+ return this.stat_median;
+ };
+
+ /** return variance value */
+ this.variance = function() {
+
+ round = (typeof round === "undefined") ? true : false;
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_variance == null) {
+
+ var tmp = 0;
+ for (var i = 0; i < this.pop(); i++) {
+ tmp += Math.pow( (this.serie[i] - this.mean()), 2 );
+ }
+
+ this.stat_variance = tmp / this.pop();
+
+ if(round == true) {
+ this.stat_variance = Math.round(this.stat_variance * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength);
+ }
+
+ }
+
+ return this.stat_variance;
+ };
+
+ /** return standard deviation value */
+ this.stddev = function(round) {
+
+ round = (typeof round === "undefined") ? true : false;
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_stddev == null) {
+
+ this.stat_stddev = Math.sqrt(this.variance());
+
+ if(round == true) {
+ this.stat_stddev = Math.round(this.stat_stddev * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength);
+ }
+
+ }
+
+ return this.stat_stddev;
+ };
+
+ /** coefficient of variation - measure of dispersion */
+ this.cov = function(round) {
+
+ round = (typeof round === "undefined") ? true : false;
+
+ if (this._nodata())
+ return;
+
+ if (this.stat_cov == null) {
+
+ this.stat_cov = this.stddev() / this.mean();
+
+ if(round == true) {
+ this.stat_cov = Math.round(this.stat_cov * Math.pow(10,this.roundlength) )/ Math.pow(10,this.roundlength);
+ }
+
+ }
+
+ return this.stat_cov;
+ };
+
+ /** data test */
+ this._nodata = function() {
+ if (this.serie.length == 0) {
+
+ if(this.silent) this.log("[silent mode] Error. You should first enter a serie!", true);
+ else alert("Error. You should first enter a serie!");
+ return 1;
+ } else
+ return 0;
+
+ };
+
+ /** check if the serie contains negative value */
+ this._hasNegativeValue = function() {
+
+ for (i = 0; i < this.serie.length; i++) {
+ if(this.serie[i] < 0)
+ return true;
+ }
+
+ return false;
+ };
+
+ /** check if the serie contains zero value */
+ this._hasZeroValue = function() {
+
+ for (i = 0; i < this.serie.length; i++) {
+ if(parseFloat(this.serie[i]) === 0)
+ return true;
+ }
+
+ return false;
+ };
+
+ /** return sorted values (as array) */
+ this.sorted = function() {
+
+ if (this.stat_sorted == null) {
+
+ if(this.is_uniqueValues == false) {
+ this.stat_sorted = this.serie.sort(function(a, b) {
+ return a - b;
+ });
+ } else {
+ this.stat_sorted = this.serie.sort(function(a,b){
+ var nameA=a.toString().toLowerCase(), nameB=b.toString().toLowerCase();
+ if(nameA < nameB) return -1;
+ if(nameA > nameB) return 1;
+ return 0;
+ })
+ }
+ }
+
+ return this.stat_sorted;
+
+ };
+
+ /** return all info */
+ this.info = function() {
+
+ if (this._nodata())
+ return;
+
+ var content = '';
+ content += _t('Population') + ' : ' + this.pop() + ' - [' + _t('Min')
+ + ' : ' + this.min() + ' | ' + _t('Max') + ' : ' + this.max()
+ + ']' + "\n";
+ content += _t('Mean') + ' : ' + this.mean() + ' - ' + _t('Median') + ' : ' + this.median() + "\n";
+ content += _t('Variance') + ' : ' + this.variance() + ' - ' + _t('Standard deviation') + ' : ' + this.stddev()
+ + ' - ' + _t('Coefficient of variation') + ' : ' + this.cov() + "\n";
+
+ return content;
+ };
+
+ /**
+ * Set Manual classification Return an array with bounds : ie array(0,
+ * 0.75, 1.5, 2.25, 3);
+ * Set ranges and prepare data for displaying legend
+ *
+ */
+ this.setClassManually = function(array) {
+
+ if (this._nodata())
+ return;
+
+ if(array[0] !== this.min() || array[array.length-1] !== this.max()) {
+ if(this.silent) this.log("[silent mode] " + t('Given bounds may not be correct! please check your input.\nMin value : ' + this.min() + ' / Max value : ' + this.max()), true);
+ else alert(_t('Given bounds may not be correct! please check your input.\nMin value : ' + this.min() + ' / Max value : ' + this.max()));
+ return;
+ }
+
+ this.setBounds(array);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('manual classification') + ' (' + (array.length -1) + ' ' + _t('classes') + ')';
+
+ return this.bounds;
+ };
+
+ /**
+ * Equal intervals classification Return an array with bounds : ie array(0,
+ * 0.75, 1.5, 2.25, 3);
+ */
+ this.getClassEqInterval = function(nbClass, forceMin, forceMax) {
+
+ if (this._nodata())
+ return;
+
+ var tmpMin = (typeof forceMin === "undefined") ? this.min() : forceMin;
+ var tmpMax = (typeof forceMax === "undefined") ? this.max() : forceMax;
+
+ var a = Array();
+ var val = tmpMin;
+ var interval = (tmpMax - tmpMin) / nbClass;
+
+ for (i = 0; i <= nbClass; i++) {
+ a[i] = val;
+ val += interval;
+ }
+
+ //-> Fix last bound to Max of values
+ a[nbClass] = tmpMax;
+
+ this.setBounds(a);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('eq. intervals') + ' (' + nbClass + ' ' + _t('classes') + ')';
+
+ return this.bounds;
+ };
+
+
+ this.getQuantiles = function(nbClass) {
+ var tmp = this.sorted();
+ var quantiles = [];
+
+ var step = this.pop() / nbClass;
+ for (var i = 1; i < nbClass; i++) {
+ var qidx = Math.round(i*step+0.49);
+ quantiles.push(tmp[qidx-1]); // zero-based
+ }
+
+ return quantiles;
+ };
+
+ /**
+ * Quantile classification Return an array with bounds : ie array(0, 0.75,
+ * 1.5, 2.25, 3);
+ */
+ this.getClassQuantile = function(nbClass) {
+
+ if (this._nodata())
+ return;
+
+ var tmp = this.sorted();
+ var bounds = this.getQuantiles(nbClass);
+ bounds.unshift(tmp[0]);
+
+ if (bounds[tmp.length - 1] !== tmp[tmp.length - 1])
+ bounds.push(tmp[tmp.length - 1]);
+
+ this.setBounds(bounds);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('quantile') + ' (' + nbClass + ' ' + _t('classes') + ')';
+
+ return this.bounds;
+
+ };
+
+ /**
+ * Standard Deviation classification
+ * Return an array with bounds : ie array(0,
+ * 0.75, 1.5, 2.25, 3);
+ */
+ this.getClassStdDeviation = function(nbClass, matchBounds) {
+
+ if (this._nodata())
+ return;
+
+ var tmpMax = this.max();
+ var tmpMin = this.min();
+
+ var a = Array();
+
+ // number of classes is odd
+ if(nbClass % 2 == 1) {
+
+ // Euclidean division to get the inferior bound
+ var infBound = Math.floor(nbClass / 2);
+
+ var supBound = infBound + 1;
+
+ // we set the central bounds
+ a[infBound] = this.mean() - ( this.stddev() / 2);
+ a[supBound] = this.mean() + ( this.stddev() / 2);
+
+ // Values < to infBound, except first one
+ for (i = infBound - 1; i > 0; i--) {
+ var val = a[i+1] - this.stddev();
+ a[i] = val;
+ }
+
+ // Values > to supBound, except last one
+ for (i = supBound + 1; i < nbClass; i++) {
+ var val = a[i-1] + this.stddev();
+ a[i] = val;
+ }
+
+ // number of classes is even
+ } else {
+
+ var meanBound = nbClass / 2;
+
+ // we get the mean value
+ a[meanBound] = this.mean();
+
+ // Values < to the mean, except first one
+ for (i = meanBound - 1; i > 0; i--) {
+ var val = a[i+1] - this.stddev();
+ a[i] = val;
+ }
+
+ // Values > to the mean, except last one
+ for (i = meanBound + 1; i < nbClass; i++) {
+ var val = a[i-1] + this.stddev();
+ a[i] = val;
+ }
+ }
+
+
+ // we finally set the first value
+ // do we excatly match min value or not ?
+ a[0] = (typeof matchBounds === "undefined") ? a[1]-this.stddev() : this.min();
+
+ // we finally set the last value
+ // do we excatly match max value or not ?
+ a[nbClass] = (typeof matchBounds === "undefined") ? a[nbClass-1]+this.stddev() : this.max();
+
+ this.setBounds(a);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('std deviation') + ' (' + nbClass + ' ' + _t('classes')+ ')';
+
+ return this.bounds;
+ };
+
+
+ /**
+ * Geometric Progression classification
+ * http://en.wikipedia.org/wiki/Geometric_progression
+ * Return an array with bounds : ie array(0,
+ * 0.75, 1.5, 2.25, 3);
+ */
+ this.getClassGeometricProgression = function(nbClass) {
+
+ if (this._nodata())
+ return;
+
+ if(this._hasNegativeValue() || this._hasZeroValue()) {
+ if(this.silent) this.log("[silent mode] " + _t('geometric progression can\'t be applied with a serie containing negative or zero values.'), true);
+ else alert(_t('geometric progression can\'t be applied with a serie containing negative or zero values.'));
+ return;
+ }
+
+ var a = Array();
+ var tmpMin = this.min();
+ var tmpMax = this.max();
+
+ var logMax = Math.log(tmpMax) / Math.LN10; // max decimal logarithm (or base 10)
+ var logMin = Math.log(tmpMin) / Math.LN10;; // min decimal logarithm (or base 10)
+
+ var interval = (logMax - logMin) / nbClass;
+
+ // we compute log bounds
+ for (i = 0; i < nbClass; i++) {
+ if(i == 0) {
+ a[i] = logMin;
+ } else {
+ a[i] = a[i-1] + interval;
+ }
+ }
+
+ // we compute antilog
+ a = a.map(function(x) { return Math.pow(10, x); });
+
+ // and we finally add max value
+ a.push(this.max());
+
+ this.setBounds(a);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('geometric progression') + ' (' + nbClass + ' ' + _t('classes') + ')';
+
+ return this.bounds;
+ };
+
+ /**
+ * Arithmetic Progression classification
+ * http://en.wikipedia.org/wiki/Arithmetic_progression
+ * Return an array with bounds : ie array(0,
+ * 0.75, 1.5, 2.25, 3);
+ */
+ this.getClassArithmeticProgression = function(nbClass) {
+
+ if (this._nodata())
+ return;
+
+ var denominator = 0;
+
+ // we compute the (french) "Raison"
+ for (i = 1; i <= nbClass; i++) {
+ denominator += i;
+ }
+
+ var a = Array();
+ var tmpMin = this.min();
+ var tmpMax = this.max();
+
+ var interval = (tmpMax - tmpMin) / denominator;
+
+ for (i = 0; i <= nbClass; i++) {
+ if(i == 0) {
+ a[i] = tmpMin;
+ } else {
+ a[i] = a[i-1] + (i * interval);
+ }
+ }
+
+ this.setBounds(a);
+ this.setRanges();
+
+ // we specify the classification method
+ this.method = _t('arithmetic progression') + ' (' + nbClass + ' ' + _t('classes') + ')';
+
+ return this.bounds;
+ };
+
+ /**
+ * Credits : Doug Curl (javascript) and Daniel J Lewis (python implementation)
+ * http://www.arcgis.com/home/item.html?id=0b633ff2f40d412995b8be377211c47b
+ * http://danieljlewis.org/2010/06/07/jenks-natural-breaks-algorithm-in-python/
+ */
+ this.getClassJenks = function(nbClass) {
+
+ if (this._nodata())
+ return;
+
+ dataList = this.sorted();
+
+ // now iterate through the datalist:
+ // determine mat1 and mat2
+ // really not sure how these 2 different arrays are set - the code for
+ // each seems the same!
+ // but the effect are 2 different arrays: mat1 and mat2
+ var mat1 = []
+ for ( var x = 0, xl = dataList.length + 1; x < xl; x++) {
+ var temp = []
+ for ( var j = 0, jl = nbClass + 1; j < jl; j++) {
+ temp.push(0)
+ }
+ mat1.push(temp)
+ }
+
+ var mat2 = []
+ for ( var i = 0, il = dataList.length + 1; i < il; i++) {
+ var temp2 = []
+ for ( var c = 0, cl = nbClass + 1; c < cl; c++) {
+ temp2.push(0)
+ }
+ mat2.push(temp2)
+ }
+
+ // absolutely no idea what this does - best I can tell, it sets the 1st
+ // group in the
+ // mat1 and mat2 arrays to 1 and 0 respectively
+ for ( var y = 1, yl = nbClass + 1; y < yl; y++) {
+ mat1[0][y] = 1
+ mat2[0][y] = 0
+ for ( var t = 1, tl = dataList.length + 1; t < tl; t++) {
+ mat2[t][y] = Infinity
+ }
+ var v = 0.0
+ }
+
+ // and this part - I'm a little clueless on - but it works
+ // pretty sure it iterates across the entire dataset and compares each
+ // value to
+ // one another to and adjust the indices until you meet the rules:
+ // minimum deviation
+ // within a class and maximum separation between classes
+ for ( var l = 2, ll = dataList.length + 1; l < ll; l++) {
+ var s1 = 0.0
+ var s2 = 0.0
+ var w = 0.0
+ for ( var m = 1, ml = l + 1; m < ml; m++) {
+ var i3 = l - m + 1
+ var val = parseFloat(dataList[i3 - 1])
+ s2 += val * val
+ s1 += val
+ w += 1
+ v = s2 - (s1 * s1) / w
+ var i4 = i3 - 1
+ if (i4 != 0) {
+ for ( var p = 2, pl = nbClass + 1; p < pl; p++) {
+ if (mat2[l][p] >= (v + mat2[i4][p - 1])) {
+ mat1[l][p] = i3
+ mat2[l][p] = v + mat2[i4][p - 1]
+ }
+ }
+ }
+ }
+ mat1[l][1] = 1
+ mat2[l][1] = v
+ }
+
+ var k = dataList.length
+ var kclass = []
+
+ // fill the kclass (classification) array with zeros:
+ for (i = 0; i <= nbClass; i++) {
+ kclass.push(0);
+ }
+
+ // this is the last number in the array:
+ kclass[nbClass] = parseFloat(dataList[dataList.length - 1])
+ // this is the first number - can set to zero, but want to set to lowest
+ // to use for legend:
+ kclass[0] = parseFloat(dataList[0])
+ var countNum = nbClass
+ while (countNum >= 2) {
+ var id = parseInt((mat1[k][countNum]) - 2)
+ kclass[countNum - 1] = dataList[id]
+ k = parseInt((mat1[k][countNum] - 1))
+ // spits out the rank and value of the break values:
+ // console.log("id="+id,"rank = " + String(mat1[k][countNum]),"val =
+ // " + String(dataList[id]))
+ // count down:
+ countNum -= 1
+ }
+ // check to see if the 0 and 1 in the array are the same - if so, set 0
+ // to 0:
+ if (kclass[0] == kclass[1]) {
+ kclass[0] = 0
+ }
+
+ this.setBounds(kclass);
+ this.setRanges();
+
+
+ this.method = _t('Jenks') + ' (' + nbClass + ' ' + _t('classes') + ')';
+
+ return this.bounds; //array of breaks
+ }
+
+
+ /**
+ * Quantile classification Return an array with bounds : ie array(0, 0.75,
+ * 1.5, 2.25, 3);
+ */
+ this.getClassUniqueValues = function() {
+
+ if (this._nodata())
+ return;
+
+ this.is_uniqueValues = true;
+
+ var tmp = this.sorted(); // display in alphabetical order
+
+ var a = Array();
+
+ for (i = 0; i < this.pop(); i++) {
+ if(a.indexOf(tmp[i]) === -1)
+ a.push(tmp[i]);
+ }
+
+ this.bounds = a;
+
+ // we specify the classification method
+ this.method = _t('unique values');
+
+ return a;
+
+ };
+
+
+ /**
+ * Return the class of a given value.
+ * For example value : 6
+ * and bounds array = (0, 4, 8, 12);
+ * Return 2
+ */
+ this.getClass = function(value) {
+
+ for(i = 0; i < this.bounds.length; i++) {
+
+
+ if(this.is_uniqueValues == true) {
+ if(value == this.bounds[i])
+ return i;
+ } else {
+ // parseFloat() is necessary
+ if(parseFloat(value) <= this.bounds[i + 1]) {
+ return i;
+ }
+ }
+ }
+
+ return _t("Unable to get value's class.");
+
+ };
+
+ /**
+ * Return the ranges array : array('0-0.75', '0.75-1.5', '1.5-2.25',
+ * '2.25-3');
+ */
+ this.getRanges = function() {
+
+ return this.ranges;
+
+ };
+
+ /**
+ * Returns the number/index of this.ranges that value falls into
+ */
+ this.getRangeNum = function(value) {
+
+ var bounds, i;
+
+ for (i = 0; i < this.ranges.length; i++) {
+ bounds = this.ranges[i].split(/ - /);
+ if (value <= parseFloat(bounds[1])) {
+ return i;
+ }
+ }
+ }
+
+ /*
+ * Compute inner ranges based on serie.
+ * Produce discontinous ranges used for legend - return an array similar to :
+ * array('0.00-0.74', '0.98-1.52', '1.78-2.25', '2.99-3.14');
+ * If inner ranges already computed, return array values.
+ */
+ this.getInnerRanges = function() {
+
+ // if already computed, we return the result
+ if(this.inner_ranges != null)
+ return this.inner_ranges;
+
+
+ var a = new Array();
+ var tmp = this.sorted();
+
+ var cnt = 1; // bounds array counter
+
+ for (i = 0; i < tmp.length; i++) {
+
+ if(i == 0) var range_firstvalue = tmp[i]; // we init first range value
+
+ if(parseFloat(tmp[i]) > parseFloat(this.bounds[cnt])) {
+
+ a[cnt - 1] = '' + range_firstvalue + this.separator + tmp[i-1];
+
+ var range_firstvalue = tmp[i];
+
+ cnt++;
+
+ }
+
+ // we reach the last range, we finally complete manually
+ // and return the array
+ if(cnt == (this.bounds.length - 1)) {
+ // we set the last value
+ a[cnt - 1] = '' + range_firstvalue + this.separator + tmp[tmp.length-1];
+
+ this.inner_ranges = a;
+ return this.inner_ranges;
+ }
+
+
+ }
+
+ };
+
+ this.getSortedlist = function() {
+
+ return this.sorted().join(', ');
+
+ };
+
+ /**
+ * Return an html legend
+ * colors : specify an array of color (hexadecimal values)
+ * legend : specify a text input for the legend. By default, just displays 'legend'
+ * counter : if not null, display counter value
+ * callback : if not null, callback function applied on legend boundaries
+ * mode : null, 'default', 'distinct', 'discontinuous' :
+ * - if mode is null, will display legend as 'default mode'
+ * - 'default' : displays ranges like in ranges array (continuous values), sample : 29.26 - 378.80 / 378.80 - 2762.25 / 2762.25 - 6884.84
+ * - 'distinct' : Add + 1 according to decimal precision to distinguish classes (discrete values), sample : 29.26 - 378.80 / 378.81 - 2762.25 / 2762.26 - 6884.84
+ * - 'discontinuous' : indicates the range of data actually falling in each class , sample : 29.26 - 225.43 / 852.12 - 2762.20 / 3001.25 - 6884.84 / not implemented yet
+ * order : null, 'ASC', 'DESC'
+ */
+ this.getHtmlLegend = function(colors, legend, counter, callback, mode, order) {
+
+ var cnt= '';
+ var elements = new Array();
+
+ this.doCount(); // we do count, even if not displayed
+
+ if(colors != null) {
+ ccolors = colors;
+ }
+ else {
+ ccolors = this.colors;
+ }
+
+ if(legend != null) {
+ lg = legend;
+ }
+ else {
+ lg = 'Legend';
+ }
+
+ if(counter != null) {
+ getcounter = true;
+ }
+ else {
+ getcounter = false;
+ }
+
+ if(callback != null) {
+ fn = callback;
+ }
+ else {
+ fn = function(o) {return o;};
+ }
+ if(mode == null) {
+ mode = 'default';
+ }
+ if(mode == 'discontinuous') {
+ this.getInnerRanges();
+ // check if some classes are not populated / equivalent of in_array function
+ if(this.counter.indexOf(0) !== -1) {
+ if(this.silent) this.log("[silent mode] " + _t("Geostats cannot apply 'discontinuous' mode to the getHtmlLegend() method because some classes are not populated.\nPlease switch to 'default' or 'distinct' modes. Exit!"), true);
+ else alert(_t("Geostats cannot apply 'discontinuous' mode to the getHtmlLegend() method because some classes are not populated.\nPlease switch to 'default' or 'distinct' modes. Exit!"));
+ return;
+ }
+
+ }
+ if(order !== 'DESC') order = 'ASC';
+
+ if(ccolors.length < this.ranges.length) {
+ if(this.silent) this.log("[silent mode] " + _t('The number of colors should fit the number of ranges. Exit!'), true);
+ else alert(_t('The number of colors should fit the number of ranges. Exit!'));
+ return;
+ }
+
+ if(this.is_uniqueValues == false) {
+
+ for (i = 0; i < (this.ranges.length); i++) {
+ if(getcounter===true) {
+ cnt = ' <span class="geostats-legend-counter">(' + this.counter[i] + ')</span>';
+ }
+ //console.log("Ranges : " + this.ranges[i]);
+
+ // default mode
+ var tmp = this.ranges[i].split(this.separator);
+
+ var start_value = parseFloat(tmp[0]).toFixed(this.precision);
+ var end_value = parseFloat(tmp[1]).toFixed(this.precision);
+
+
+ // if mode == 'distinct' and we are not working on the first value
+ if(mode == 'distinct' && i != 0) {
+
+ if(isInt(start_value)) {
+ start_value = parseInt(start_value) + 1;
+ // format to float if necessary
+ if(this.precisionflag == 'manual' && this.precision != 0) start_value = parseFloat(start_value).toFixed(this.precision);
+ } else {
+
+ start_value = parseFloat(start_value) + (1 / Math.pow(10,this.precision));
+ // strangely the formula above return sometimes long decimal values,
+ // the following instruction fix it
+ start_value = parseFloat(start_value).toFixed(this.precision);
+ }
+ }
+
+ // if mode == 'discontinuous'
+ if(mode == 'discontinuous') {
+
+ var tmp = this.inner_ranges[i].split(this.separator);
+ // console.log("Ranges : " + this.inner_ranges[i]);
+
+ var start_value = parseFloat(tmp[0]).toFixed(this.precision);
+ var end_value = parseFloat(tmp[1]).toFixed(this.precision);
+
+ }
+
+ // we apply callback function
+ var el = fn(start_value) + this.legendSeparator + fn(end_value);
+
+ var block = '<div><div class="geostats-legend-block" style="background-color:' + ccolors[i] + '"></div> ' + el + cnt + '</div>';
+ elements.push(block);
+ }
+
+ } else {
+
+ // only if classification is done on unique values
+ for (i = 0; i < (this.bounds.length); i++) {
+ if(getcounter===true) {
+ cnt = ' <span class="geostats-legend-counter">(' + this.counter[i] + ')</span>';
+ }
+ var el = fn(this.bounds[i]);
+ var block = '<div><div class="geostats-legend-block" style="background-color:' + ccolors[i] + '"></div> ' + el + cnt + '</div>';
+
+ elements.push(block);
+ }
+
+ }
+
+ // do we reverse the return legend ?
+ if(order === 'DESC') elements.reverse();
+
+ // finally we create HTML and return it
+ var content = '<div class="geostats-legend"><div class="geostats-legend-title">' + _t(lg) + '</div>';
+ for (i = 0; i < (elements.length); i++) {
+ content += elements[i];
+ }
+ content += '</div>';
+
+ return content;
+ };
+
+
+
+ // object constructor
+ // At the end of script. If not setPrecision() method is not known
+
+ // we create an object identifier for debugging
+ this.objectID = new Date().getUTCMilliseconds();
+ this.log('Creating new geostats object');
+
+ if(typeof a !== 'undefined' && a.length > 0) {
+ this.serie = a;
+ this.setPrecision();
+ this.log('Setting serie (' + a.length + ') : ' + a.join());
+ } else {
+ this.serie = Array();
+
+ };
+
+ // creating aliases on classification function for backward compatibility
+ this.getJenks = this.getClassJenks;
+ this.getGeometricProgression = this.getClassGeometricProgression;
+ this.getEqInterval = this.getClassEqInterval;
+ this.getQuantile = this.getClassQuantile;
+ this.getStdDeviation = this.getClassStdDeviation;
+ this.getUniqueValues = this.getClassUniqueValues;
+ this.getArithmeticProgression = this.getClassArithmeticProgression;
+
+};
+
+
+return geostats;
+});
generated by cgit v1.2.3 (git 2.25.1) at 2026-10-23 10:07:43 +0000