added geoengine

2 files changed, 1213 insertions, 0 deletions

diff --git a/base_geoengine/static/lib/geostats-1.4.0/geostats.css b/base_geoengine/static/lib/geostats-1.4.0/geostats.css
new file mode 100644
index 0000000..cba5b48
--- /dev/null
+++ b/base_geoengine/static/lib/geostats-1.4.0/geostats.css
@@ -0,0 +1,23 @@
+.geostats-legend div {
+  margin:3px 10px 5px 10px
+}
+
+.geostats-legend-title {
+  font-weight: bold;
+  margin-bottom: 4px;
+}
+
+.geostats-legend-block {
+  border: 1px solid #555555;
+  display: block;
+  float: left;
+  height: 12px;
+  margin: 0 5px 0 20px;
+  width: 20px;
+}
+
+.geostats-legend-counter { 
+  font-size: 0.8em;
+  color:#666;
+  font-style: italic;
+}
diff --git a/base_geoengine/static/lib/geostats-1.4.0/geostats.js b/base_geoengine/static/lib/geostats-1.4.0/geostats.js
new file mode 100755
index 0000000..f099ce5
--- /dev/null
+++ b/base_geoengine/static/lib/geostats-1.4.0/geostats.js
@@ -0,0 +1,1190 @@
+/**
+* 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;
+});