From 9cfd383012726a71d081f0791126d7a747a86076 Mon Sep 17 00:00:00 2001
From: Alban Mouton through Travis-CI <alban.mouton@gmail.com>
Date: Thu, 13 Aug 2015 23:26:02 +0200
Subject: [PATCH 1/6] work in progress for async fitness

---
 lib/genetic.js | 158 ++++++++++++++++++++++++++++++++-----------------
 1 file changed, 104 insertions(+), 54 deletions(-)

diff --git a/lib/genetic.js b/lib/genetic.js
index 7564024..46f6444 100644
--- a/lib/genetic.js
+++ b/lib/genetic.js
@@ -107,6 +107,51 @@ var Genetic = Genetic || (function(){
 		
 		this.usingWebWorker = false;
 		
+		this.mapFitnessAsync = function(entities, callback) {
+			var self = this;
+
+			var scores = entities.map(function() {
+				return null;
+			});
+			var nbScores = 0;
+
+			entities.forEach(function(entity, i) {
+
+				var setScore = function(score) {
+					scores[i] = score;
+					nbScores += 1;
+					if (nbScores === entities.length) {
+						callback(scores);
+					}
+				};
+
+				setTimeout(function() {
+					// Supports fitness function sync or async based on number of expected arguments
+					if (self.fitness.length === 1) {
+						setScore(self.fitness(entity));
+					} else {
+						self.fitness(entity, setScore);
+					}
+				}, 0);
+			});
+		};
+
+		this.seriesAsync = function(nb, func) {
+			var self = this;
+			var results = [];
+
+			var recursion = function(i) {
+				setTimeout(function() {
+					if(i < nb) {
+						func.call(self, function recursionCallback() {
+							recursion(i + 1);
+						});
+					}
+				}, 0);
+			};
+
+			recursion(0);
+		};
 		this.start = function() {
 			
 			var i;
@@ -122,68 +167,73 @@ var Genetic = Genetic || (function(){
 				this.entities.push(Clone(this.seed()));
 			}
 			
-			for (i=0;i<this.configuration.iterations;++i) {
+			this.seriesAsync(this.configuration.iterations, function runGeneration(generationCallback){
 				// reset for each generation
-				this.internalGenState = {};
+				self.internalGenState = {};
 				
-				// score and sort
-				var pop = this.entities
-					.map(function (entity) {
-						return {"fitness": self.fitness(entity), "entity": entity };
-					})
-					.sort(function (a, b) {
-						return self.optimize(a.fitness, b.fitness) ? -1 : 1;
-					});
-				
-				// generation notification
-				var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
-				var stdev = Math.sqrt(pop
-					.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
-					.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+				// Asynchronous score
+				self.mapFitnessAsync(self.entities, function(scores){
+					var pop = self.entities
+						.map(function (entity, i) {
+							return {"fitness": scores[i], "entity": entity };
+						})
+						.sort(function (a, b) {
+							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
+						});
 					
-				var stats = {
-					"maximum": pop[0].fitness
-					, "minimum": pop[pop.length-1].fitness
-					, "mean": mean
-					, "stdev": stdev
-				};
+					// generation notification
+					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
+					var stdev = Math.sqrt(pop
+						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
+						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+						
+					var stats = {
+						"maximum": pop[0].fitness
+						, "minimum": pop[pop.length-1].fitness
+						, "mean": mean
+						, "stdev": stdev
+					};
 
-				var r = this.generation ? this.generation(pop, i, stats) : true;
-				var isFinished = (typeof r != "undefined" && !r) || (i == this.configuration.iterations-1);
-				
-				if (
-					this.notification
-					&& (isFinished || this.configuration["skip"] == 0 || i%this.configuration["skip"] == 0)
-				) {
-					this.sendNotification(pop.slice(0, this.maxResults), i, stats, isFinished);
-				}
+					var r = self.generation ? self.generation(pop, i, stats) : true;
+					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
 					
-				if (isFinished)
-					break;
-				
-				// crossover and mutate
-				var newPop = [];
-				
-				if (this.configuration.fittestAlwaysSurvives) // lets the best solution fall through
-					newPop.push(pop[0].entity);
-				
-				while (newPop.length < self.configuration.size) {
 					if (
-						this.crossover // if there is a crossover function
-						&& Math.random() <= this.configuration.crossover // base crossover on specified probability
-						&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						self.notification
+						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
 					) {
-						var parents = this.select2(pop);
-						var children = this.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
-						newPop.push(children[0], children[1]);
-					} else {
-						newPop.push(mutateOrNot(self.select1(pop)));
+						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
 					}
-				}
-				
-				this.entities = newPop;
-			}
-		}
+						
+					if (isFinished)
+						return;
+					
+					// crossover and mutate
+					var newPop = [];
+					
+					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
+						newPop.push(pop[0].entity);
+					
+					while (newPop.length < self.configuration.size) {
+						if (
+							self.crossover // if there is a crossover function
+							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
+							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						) {
+							var parents = self.select2(pop);
+							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
+							newPop.push(children[0], children[1]);
+						} else {
+							newPop.push(mutateOrNot(self.select1(pop)));
+						}
+					}
+					
+					self.entities = newPop;
+
+					generationCallback();
+				});
+
+			});		
+		};
 		
 		this.sendNotification = function(pop, generation, stats, isFinished) {
 			var response = {

From 77f0e0c6078d920adb12fcadc259e959d98fde7d Mon Sep 17 00:00:00 2001
From: Alban Mouton <mouton-a@mgdis.fr>
Date: Fri, 14 Aug 2015 13:32:37 +0200
Subject: [PATCH 2/6] fix async, do not break compatibility

---
 lib/genetic.js  |  33 ++---
 lib/genetic.js~ | 332 ++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 346 insertions(+), 19 deletions(-)
 create mode 100644 lib/genetic.js~

diff --git a/lib/genetic.js b/lib/genetic.js
index 46f6444..3b08135 100644
--- a/lib/genetic.js
+++ b/lib/genetic.js
@@ -110,9 +110,7 @@ var Genetic = Genetic || (function(){
 		this.mapFitnessAsync = function(entities, callback) {
 			var self = this;
 
-			var scores = entities.map(function() {
-				return null;
-			});
+			var scores = [];
 			var nbScores = 0;
 
 			entities.forEach(function(entity, i) {
@@ -125,14 +123,12 @@ var Genetic = Genetic || (function(){
 					}
 				};
 
-				setTimeout(function() {
-					// Supports fitness function sync or async based on number of expected arguments
-					if (self.fitness.length === 1) {
-						setScore(self.fitness(entity));
-					} else {
-						self.fitness(entity, setScore);
-					}
-				}, 0);
+				// Supports fitness function sync or async based on number of expected arguments
+				if (self.fitness.length === 1) {
+					setScore(self.fitness(entity));
+				} else {
+					self.fitness(entity, setScore);
+				}
 			});
 		};
 
@@ -141,17 +137,16 @@ var Genetic = Genetic || (function(){
 			var results = [];
 
 			var recursion = function(i) {
-				setTimeout(function() {
-					if(i < nb) {
-						func.call(self, function recursionCallback() {
-							recursion(i + 1);
-						});
-					}
-				}, 0);
+				if(i < nb) {
+					func.call(self, i, function recursionCallback() {
+						recursion(i + 1);
+					});
+				}
 			};
 
 			recursion(0);
 		};
+
 		this.start = function() {
 			
 			var i;
@@ -167,7 +162,7 @@ var Genetic = Genetic || (function(){
 				this.entities.push(Clone(this.seed()));
 			}
 			
-			this.seriesAsync(this.configuration.iterations, function runGeneration(generationCallback){
+			this.seriesAsync(this.configuration.iterations, function runGeneration(i, generationCallback){
 				// reset for each generation
 				self.internalGenState = {};
 				
diff --git a/lib/genetic.js~ b/lib/genetic.js~
new file mode 100644
index 0000000..46f6444
--- /dev/null
+++ b/lib/genetic.js~
@@ -0,0 +1,332 @@
+
+var Genetic = Genetic || (function(){
+	
+	'use strict';
+	
+	// facilitates communcation between web workers
+	var Serialization = {
+		"stringify": function (obj) {
+			return JSON.stringify(obj, function (key, value) {
+				if (value instanceof Function || typeof value == "function") return "__func__:" + value.toString();
+				if (value instanceof RegExp) return "__regex__:" + value;
+				return value;
+			});
+		}, "parse": function (str) {
+			return JSON.parse(str, function (key, value) {
+				if (typeof value != "string") return value;
+				if (value.lastIndexOf("__func__:", 0) === 0) return eval('(' + value.slice(9) + ')');
+				if (value.lastIndexOf("__regex__:", 0) === 0) return eval('(' + value.slice(10) + ')');
+				return value;
+			});
+		}
+	};
+	
+	var Clone = function(obj) {
+		if (obj == null || typeof obj != "object")
+			return obj;
+		
+		return JSON.parse(JSON.stringify(obj));
+	};
+	
+	var Optimize = {
+		"Maximize": function (a, b) { return a >= b; }
+		, "Minimize": function (a, b) { return a < b; }
+	};
+	
+	var Select1 = {
+		"Tournament2": function(pop) {
+			var n = pop.length;
+			var a = pop[Math.floor(Math.random()*n)];
+			var b = pop[Math.floor(Math.random()*n)];
+			return this.optimize(a.fitness, b.fitness) ? a.entity : b.entity;
+		}, "Tournament3": function(pop) {
+			var n = pop.length;
+			var a = pop[Math.floor(Math.random()*n)];
+			var b = pop[Math.floor(Math.random()*n)];
+			var c = pop[Math.floor(Math.random()*n)];
+			var best = this.optimize(a.fitness, b.fitness) ? a : b;
+			best = this.optimize(best.fitness, c.fitness) ? best : c;
+			return best.entity;
+		}, "Fittest": function (pop) {
+			return pop[0].entity;
+		}, "Random": function (pop) {
+			return pop[Math.floor(Math.random()*pop.length)].entity;
+		}, "RandomLinearRank": function (pop) {
+			this.internalGenState["rlr"] = this.internalGenState["rlr"]||0;
+			return pop[Math.floor(Math.random()*Math.min(pop.length,(this.internalGenState["rlr"]++)))].entity;
+		}, "Sequential": function (pop) {
+			this.internalGenState["seq"] = this.internalGenState["seq"]||0;
+			return pop[(this.internalGenState["seq"]++)%pop.length].entity;
+		}
+	};
+	
+	var Select2 = {
+		"Tournament2": function(pop) {
+			return [Select1.Tournament2.call(this, pop), Select1.Tournament2.call(this, pop)];
+		}, "Tournament3": function(pop) {
+			return [Select1.Tournament3.call(this, pop), Select1.Tournament3.call(this, pop)];
+		}, "Random": function (pop) {
+			return [Select1.Random.call(this, pop), Select1.Random.call(this, pop)];
+		}, "RandomLinearRank": function (pop) {
+			return [Select1.RandomLinearRank.call(this, pop), Select1.RandomLinearRank.call(this, pop)];
+		}, "Sequential": function (pop) {
+			return [Select1.Sequential.call(this, pop), Select1.Sequential.call(this, pop)];
+		}, "FittestRandom": function (pop) {
+			return [Select1.Fittest.call(this, pop), Select1.Random.call(this, pop)];
+		}
+	};
+	
+	function Genetic() {
+		
+		// population
+		this.fitness = null;
+		this.seed = null;
+		this.mutate = null;
+		this.crossover = null;
+		this.select1 = null;
+		this.select2 = null;
+		this.optimize = null;
+		this.generation = null;
+		this.notification = null;
+		
+		this.configuration = {
+			"size": 250
+			, "crossover": 0.9
+			, "mutation": 0.2
+			, "iterations": 100
+			, "fittestAlwaysSurvives": true
+			, "maxResults": 100
+			, "webWorkers": true
+			, "skip": 0
+		};
+		
+		this.userData = {};
+		this.internalGenState = {};
+		
+		this.entities = [];
+		
+		this.usingWebWorker = false;
+		
+		this.mapFitnessAsync = function(entities, callback) {
+			var self = this;
+
+			var scores = entities.map(function() {
+				return null;
+			});
+			var nbScores = 0;
+
+			entities.forEach(function(entity, i) {
+
+				var setScore = function(score) {
+					scores[i] = score;
+					nbScores += 1;
+					if (nbScores === entities.length) {
+						callback(scores);
+					}
+				};
+
+				setTimeout(function() {
+					// Supports fitness function sync or async based on number of expected arguments
+					if (self.fitness.length === 1) {
+						setScore(self.fitness(entity));
+					} else {
+						self.fitness(entity, setScore);
+					}
+				}, 0);
+			});
+		};
+
+		this.seriesAsync = function(nb, func) {
+			var self = this;
+			var results = [];
+
+			var recursion = function(i) {
+				setTimeout(function() {
+					if(i < nb) {
+						func.call(self, function recursionCallback() {
+							recursion(i + 1);
+						});
+					}
+				}, 0);
+			};
+
+			recursion(0);
+		};
+		this.start = function() {
+			
+			var i;
+			var self = this;
+			
+			function mutateOrNot(entity) {
+				// applies mutation based on mutation probability
+				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
+			}
+			
+			// seed the population
+			for (i=0;i<this.configuration.size;++i)  {
+				this.entities.push(Clone(this.seed()));
+			}
+			
+			this.seriesAsync(this.configuration.iterations, function runGeneration(generationCallback){
+				// reset for each generation
+				self.internalGenState = {};
+				
+				// Asynchronous score
+				self.mapFitnessAsync(self.entities, function(scores){
+					var pop = self.entities
+						.map(function (entity, i) {
+							return {"fitness": scores[i], "entity": entity };
+						})
+						.sort(function (a, b) {
+							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
+						});
+					
+					// generation notification
+					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
+					var stdev = Math.sqrt(pop
+						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
+						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+						
+					var stats = {
+						"maximum": pop[0].fitness
+						, "minimum": pop[pop.length-1].fitness
+						, "mean": mean
+						, "stdev": stdev
+					};
+
+					var r = self.generation ? self.generation(pop, i, stats) : true;
+					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
+					
+					if (
+						self.notification
+						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
+					) {
+						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
+					}
+						
+					if (isFinished)
+						return;
+					
+					// crossover and mutate
+					var newPop = [];
+					
+					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
+						newPop.push(pop[0].entity);
+					
+					while (newPop.length < self.configuration.size) {
+						if (
+							self.crossover // if there is a crossover function
+							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
+							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						) {
+							var parents = self.select2(pop);
+							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
+							newPop.push(children[0], children[1]);
+						} else {
+							newPop.push(mutateOrNot(self.select1(pop)));
+						}
+					}
+					
+					self.entities = newPop;
+
+					generationCallback();
+				});
+
+			});		
+		};
+		
+		this.sendNotification = function(pop, generation, stats, isFinished) {
+			var response = {
+				"pop": pop.map(Serialization.stringify)
+				, "generation": generation
+				, "stats": stats
+				, "isFinished": isFinished
+			};
+			
+			
+			if (this.usingWebWorker) {
+				postMessage(response);
+			} else {
+				// self declared outside of scope
+				self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			}
+			
+		};
+	}
+	
+	Genetic.prototype.evolve = function(config, userData) {
+		
+		var k;
+		for (k in config) {
+			this.configuration[k] = config[k];
+		}
+		
+		for (k in userData) {
+			this.userData[k] = userData[k];
+		}
+		
+		// determine if we can use webworkers
+		this.usingWebWorker = this.configuration.webWorkers
+			&& typeof Blob != "undefined"
+			&& typeof Worker != "undefined"
+			&& typeof window.URL != "undefined"
+			&& typeof window.URL.createObjectURL != "undefined";
+		
+		function addslashes(str) {
+			return str.replace(/[\\"']/g, '\\$&').replace(/\u0000/g, '\\0');
+		}
+			
+		// bootstrap webworker script
+		var blobScript = "'use strict'\n";
+		blobScript += "var Serialization = {'stringify': " + Serialization.stringify.toString() + ", 'parse': " + Serialization.parse.toString() + "};\n";
+		blobScript += "var Clone = " + Clone.toString() + ";\n";
+		
+		// make available in webworker
+		blobScript += "var Optimize = Serialization.parse(\"" + addslashes(Serialization.stringify(Optimize)) + "\");\n";
+		blobScript += "var Select1 = Serialization.parse(\"" + addslashes(Serialization.stringify(Select1)) + "\");\n";
+		blobScript += "var Select2 = Serialization.parse(\"" + addslashes(Serialization.stringify(Select2)) + "\");\n";
+		
+		// materialize our ga instance in the worker
+		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
+		blobScript += "onmessage = function(e) { genetic.start(); }\n";
+		
+		var self = this;
+		
+		if (this.usingWebWorker) {
+			// webworker
+			var blob = new Blob([blobScript]);
+			var worker = new Worker(window.URL.createObjectURL(blob));
+			worker.onmessage = function(e) {
+			  var response = e.data;
+			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			};
+			worker.onerror = function(e) {
+				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
+			};
+			worker.postMessage("");
+		} else {
+			// simulate webworker
+			(function(){
+				var onmessage;
+				eval(blobScript);
+				onmessage(null);
+			})();
+		}
+	}
+	
+	return {
+		"create": function() {
+			return new Genetic();
+		}, "Select1": Select1
+		, "Select2": Select2
+		, "Optimize": Optimize
+		, "Clone": Clone
+	};
+	
+})();
+
+
+// so we don't have to build to run in the browser
+if (typeof module != "undefined") {
+	module.exports = Genetic;
+}

From 5940ca74fda8a009149be79c3090fffcb0c713ae Mon Sep 17 00:00:00 2001
From: Alban Mouton through Travis-CI <alban.mouton@gmail.com>
Date: Sat, 15 Aug 2015 22:33:10 +0200
Subject: [PATCH 3/6] add support for calling functions from caller context in
 async fitness

---
 js/genetic-0.1.14.js     | 224 ++++++++++++++++++++++++++++-----------
 js/genetic-0.1.14.min.js |   2 +-
 lib/genetic.js           |  79 +++++++++++---
 test/async.js            |  92 ++++++++++++++++
 4 files changed, 322 insertions(+), 75 deletions(-)
 create mode 100644 test/async.js

diff --git a/js/genetic-0.1.14.js b/js/genetic-0.1.14.js
index b40a230..3c48e52 100644
--- a/js/genetic-0.1.14.js
+++ b/js/genetic-0.1.14.js
@@ -107,89 +107,173 @@ var Genetic = Genetic || (function(){
 		
 		this.userData = {};
 		this.internalGenState = {};
+		this.callerFunctions = {};
 		
 		this.entities = [];
 		
 		this.usingWebWorker = false;
 		
+		this.mapFitnessAsync = function(entities, callback) {
+			var _this = this;
+
+			var scores = [];
+			var nbScores = 0;
+
+			entities.forEach(function(entity, i) {
+
+				var setScore = function(score) {
+					scores[i] = score;
+					nbScores += 1;
+					if (nbScores === entities.length) {
+						callback(scores);
+					}
+				};
+
+				// Supports fitness function sync or async based on number of expected arguments
+				if (_this.fitness.length === 1) {
+					setScore(_this.fitness(entity));
+				} else {
+					_this.fitness(entity, setScore);
+				}
+			});
+		};
+
+		this.seriesAsync = function(nb, func) {
+			var self = this;
+			var results = [];
+
+			var recursion = function(i) {
+				if(i < nb) {
+					func.call(self, i, function recursionCallback() {
+						recursion(i + 1);
+					});
+				}
+			};
+
+			recursion(0);
+		};
+
 		this.start = function() {
 			
-			var i;
 			var self = this;
 			
+			// prepare wrapping around caller functions
+			for(var k in this.callerFunctions) {
+				this.callerFunctions[k] = this.wrapCallerFunction(k);
+			}
+
 			function mutateOrNot(entity) {
 				// applies mutation based on mutation probability
 				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
 			}
 			
 			// seed the population
-			for (i=0;i<this.configuration.size;++i)  {
+			for (var i=0;i<this.configuration.size;++i)  {
 				this.entities.push(Clone(this.seed()));
 			}
 			
-			for (i=0;i<this.configuration.iterations;++i) {
+			this.seriesAsync(this.configuration.iterations, function runGeneration(i, generationCallback){
 				// reset for each generation
-				this.internalGenState = {};
-				
-				// score and sort
-				var pop = this.entities
-					.map(function (entity) {
-						return {"fitness": self.fitness(entity), "entity": entity };
-					})
-					.sort(function (a, b) {
-						return self.optimize(a.fitness, b.fitness) ? -1 : 1;
-					});
+				self.internalGenState = {};
 				
-				// generation notification
-				var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
-				var stdev = Math.sqrt(pop
-					.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
-					.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+				// Asynchronous score
+				self.mapFitnessAsync(self.entities, function(scores){
+
+					var pop = self.entities
+						.map(function (entity, i) {
+							return {"fitness": scores[i], "entity": entity };
+						})
+						.sort(function (a, b) {
+							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
+						});
 					
-				var stats = {
-					"maximum": pop[0].fitness
-					, "minimum": pop[pop.length-1].fitness
-					, "mean": mean
-					, "stdev": stdev
-				};
+					// generation notification
+					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
+					var stdev = Math.sqrt(pop
+						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
+						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+						
+					var stats = {
+						"maximum": pop[0].fitness
+						, "minimum": pop[pop.length-1].fitness
+						, "mean": mean
+						, "stdev": stdev
+					};
 
-				var r = this.generation ? this.generation(pop, i, stats) : true;
-				var isFinished = (typeof r != "undefined" && !r) || (i == this.configuration.iterations-1);
-				
-				if (
-					this.notification
-					&& (isFinished || this.configuration["skip"] == 0 || i%this.configuration["skip"] == 0)
-				) {
-					this.sendNotification(pop.slice(0, this.maxResults), i, stats, isFinished);
-				}
+					var r = self.generation ? self.generation(pop, i, stats) : true;
+					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
 					
-				if (isFinished)
-					break;
-				
-				// crossover and mutate
-				var newPop = [];
-				
-				if (this.configuration.fittestAlwaysSurvives) // lets the best solution fall through
-					newPop.push(pop[0].entity);
-				
-				while (newPop.length < self.configuration.size) {
 					if (
-						this.crossover // if there is a crossover function
-						&& Math.random() <= this.configuration.crossover // base crossover on specified probability
-						&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						self.notification
+						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
 					) {
-						var parents = this.select2(pop);
-						var children = this.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
-						newPop.push(children[0], children[1]);
-					} else {
-						newPop.push(mutateOrNot(self.select1(pop)));
+						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
 					}
-				}
-				
-				this.entities = newPop;
-			}
-		}
+						
+					if (isFinished)
+						return;
+					
+					// crossover and mutate
+					var newPop = [];
+					
+					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
+						newPop.push(pop[0].entity);
+					
+					while (newPop.length < self.configuration.size) {
+						if (
+							self.crossover // if there is a crossover function
+							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
+							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						) {
+							var parents = self.select2(pop);
+							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
+							newPop.push(children[0], children[1]);
+						} else {
+							newPop.push(mutateOrNot(self.select1(pop)));
+						}
+					}
+					
+					self.entities = newPop;
+
+					generationCallback();
+				});
+
+			});		
+		};
 		
+		this.callerFunctionsCallbacks = {};
+		this.callbackId = 0;
+		// In the context of a web work a callerFunction is wrapped in a postMessage/onmessage exchange
+		this.wrapCallerFunction = function(funcName) {
+			if (this.usingWebWorker) {
+				// do not use 'self' keyword, here. Weird conflict when in non worker mode
+				var _this = this;
+				return function(){
+					var args = Array.prototype.slice.call(arguments);
+					// This id will be used to create request/reply mechanism
+					_this.callerFunctionsCallbacks[_this.callbackId] = args.pop();
+					postMessage({
+						callerFunction: funcName,
+						id: _this.callbackId,
+						arguments: Serialization.stringify(args)
+					});
+					_this.callbackId += 1;
+				};
+			} else {
+				// self declared outside of scope
+				return self.callerFunctions[funcName];
+			}
+		};
+
+		this.onmessage = function(e) {
+			if (e.data && this.callerFunctionsCallbacks[e.data.id]) {
+				this.callerFunctionsCallbacks[e.data.id].apply(this, Serialization.parse(e.data.arguments));
+				delete this.callerFunctionsCallbacks[e.data.id];
+			} else {
+				this.start();
+			}
+		};
+
 		this.sendNotification = function(pop, generation, stats, isFinished) {
 			var response = {
 				"pop": pop.map(Serialization.stringify)
@@ -209,7 +293,7 @@ var Genetic = Genetic || (function(){
 		};
 	}
 	
-	Genetic.prototype.evolve = function(config, userData) {
+	Genetic.prototype.evolve = function(config, userData, callerFunctions) {
 		
 		var k;
 		for (k in config) {
@@ -219,6 +303,10 @@ var Genetic = Genetic || (function(){
 		for (k in userData) {
 			this.userData[k] = userData[k];
 		}
+
+		for (k in callerFunctions) {
+			this.callerFunctions[k] = callerFunctions[k];
+		}
 		
 		// determine if we can use webworkers
 		this.usingWebWorker = this.configuration.webWorkers
@@ -243,7 +331,7 @@ var Genetic = Genetic || (function(){
 		
 		// materialize our ga instance in the worker
 		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
-		blobScript += "onmessage = function(e) { genetic.start(); }\n";
+		blobScript += "onmessage = function(e) { genetic.onmessage(e); }\n";
 		
 		var self = this;
 		
@@ -252,19 +340,31 @@ var Genetic = Genetic || (function(){
 			var blob = new Blob([blobScript]);
 			var worker = new Worker(window.URL.createObjectURL(blob));
 			worker.onmessage = function(e) {
-			  var response = e.data;
-			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			  var data = e.data;
+			  if (data.callerFunction) {
+			  	// receive a request from the work to run a function in caller context, do it then respond by postMessage
+			  	self.callerFunctions[data.callerFunction].apply(self, Serialization.parse(data.arguments).concat(function(){
+			  		var args = Array.prototype.slice.call(arguments);
+			  		worker.postMessage({
+			  			callerFunctionCallback: data.callerFunction,
+			  			id: data.id,
+			  			arguments: Serialization.stringify(args)
+			  		});
+			  	}));
+			  } else {
+			  	self.notification(data.pop.map(Serialization.parse), data.generation, data.stats, data.isFinished);
+			  }
 			};
 			worker.onerror = function(e) {
 				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
 			};
-			worker.postMessage("");
+			worker.postMessage("start");
 		} else {
 			// simulate webworker
 			(function(){
 				var onmessage;
 				eval(blobScript);
-				onmessage(null);
+				onmessage("start");
 			})();
 		}
 	}
diff --git a/js/genetic-0.1.14.min.js b/js/genetic-0.1.14.min.js
index adec35c..221e043 100644
--- a/js/genetic-0.1.14.min.js
+++ b/js/genetic-0.1.14.min.js
@@ -1 +1 @@
-(function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s})({1:[function(require,module,exports){window.Genetic=require("./genetic")},{"./genetic":2}],2:[function(require,module,exports){var Genetic=Genetic||function(){"use strict";var Serialization={stringify:function(obj){return JSON.stringify(obj,function(key,value){if(value instanceof Function||typeof value=="function")return"__func__:"+value.toString();if(value instanceof RegExp)return"__regex__:"+value;return value})},parse:function(str){return JSON.parse(str,function(key,value){if(typeof value!="string")return value;if(value.lastIndexOf("__func__:",0)===0)return eval("("+value.slice(9)+")");if(value.lastIndexOf("__regex__:",0)===0)return eval("("+value.slice(10)+")");return value})}};var Clone=function(obj){if(obj==null||typeof obj!="object")return obj;return JSON.parse(JSON.stringify(obj))};var Optimize={Maximize:function(a,b){return a>=b},Minimize:function(a,b){return a<b}};var Select1={Tournament2:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];return this.optimize(a.fitness,b.fitness)?a.entity:b.entity},Tournament3:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];var c=pop[Math.floor(Math.random()*n)];var best=this.optimize(a.fitness,b.fitness)?a:b;best=this.optimize(best.fitness,c.fitness)?best:c;return best.entity},Fittest:function(pop){return pop[0].entity},Random:function(pop){return pop[Math.floor(Math.random()*pop.length)].entity},RandomLinearRank:function(pop){this.internalGenState["rlr"]=this.internalGenState["rlr"]||0;return pop[Math.floor(Math.random()*Math.min(pop.length,this.internalGenState["rlr"]++))].entity},Sequential:function(pop){this.internalGenState["seq"]=this.internalGenState["seq"]||0;return pop[this.internalGenState["seq"]++%pop.length].entity}};var Select2={Tournament2:function(pop){return[Select1.Tournament2.call(this,pop),Select1.Tournament2.call(this,pop)]},Tournament3:function(pop){return[Select1.Tournament3.call(this,pop),Select1.Tournament3.call(this,pop)]},Random:function(pop){return[Select1.Random.call(this,pop),Select1.Random.call(this,pop)]},RandomLinearRank:function(pop){return[Select1.RandomLinearRank.call(this,pop),Select1.RandomLinearRank.call(this,pop)]},Sequential:function(pop){return[Select1.Sequential.call(this,pop),Select1.Sequential.call(this,pop)]},FittestRandom:function(pop){return[Select1.Fittest.call(this,pop),Select1.Random.call(this,pop)]}};function Genetic(){this.fitness=null;this.seed=null;this.mutate=null;this.crossover=null;this.select1=null;this.select2=null;this.optimize=null;this.generation=null;this.notification=null;this.configuration={size:250,crossover:.9,mutation:.2,iterations:100,fittestAlwaysSurvives:true,maxResults:100,webWorkers:true,skip:0};this.userData={};this.internalGenState={};this.entities=[];this.usingWebWorker=false;this.start=function(){var i;var self=this;function mutateOrNot(entity){return Math.random()<=self.configuration.mutation&&self.mutate?self.mutate(Clone(entity)):entity}for(i=0;i<this.configuration.size;++i){this.entities.push(Clone(this.seed()))}for(i=0;i<this.configuration.iterations;++i){this.internalGenState={};var pop=this.entities.map(function(entity){return{fitness:self.fitness(entity),entity:entity}}).sort(function(a,b){return self.optimize(a.fitness,b.fitness)?-1:1});var mean=pop.reduce(function(a,b){return a+b.fitness},0)/pop.length;var stdev=Math.sqrt(pop.map(function(a){return(a.fitness-mean)*(a.fitness-mean)}).reduce(function(a,b){return a+b},0)/pop.length);var stats={maximum:pop[0].fitness,minimum:pop[pop.length-1].fitness,mean:mean,stdev:stdev};var r=this.generation?this.generation(pop,i,stats):true;var isFinished=typeof r!="undefined"&&!r||i==this.configuration.iterations-1;if(this.notification&&(isFinished||this.configuration["skip"]==0||i%this.configuration["skip"]==0)){this.sendNotification(pop.slice(0,this.maxResults),i,stats,isFinished)}if(isFinished)break;var newPop=[];if(this.configuration.fittestAlwaysSurvives)newPop.push(pop[0].entity);while(newPop.length<self.configuration.size){if(this.crossover&&Math.random()<=this.configuration.crossover&&newPop.length+1<self.configuration.size){var parents=this.select2(pop);var children=this.crossover(Clone(parents[0]),Clone(parents[1])).map(mutateOrNot);newPop.push(children[0],children[1])}else{newPop.push(mutateOrNot(self.select1(pop)))}}this.entities=newPop}};this.sendNotification=function(pop,generation,stats,isFinished){var response={pop:pop.map(Serialization.stringify),generation:generation,stats:stats,isFinished:isFinished};if(this.usingWebWorker){postMessage(response)}else{self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)}}}Genetic.prototype.evolve=function(config,userData){var k;for(k in config){this.configuration[k]=config[k]}for(k in userData){this.userData[k]=userData[k]}this.usingWebWorker=this.configuration.webWorkers&&typeof Blob!="undefined"&&typeof Worker!="undefined"&&typeof window.URL!="undefined"&&typeof window.URL.createObjectURL!="undefined";function addslashes(str){return str.replace(/[\\"']/g,"\\$&").replace(/\u0000/g,"\\0")}var blobScript="'use strict'\n";blobScript+="var Serialization = {'stringify': "+Serialization.stringify.toString()+", 'parse': "+Serialization.parse.toString()+"};\n";blobScript+="var Clone = "+Clone.toString()+";\n";blobScript+='var Optimize = Serialization.parse("'+addslashes(Serialization.stringify(Optimize))+'");\n';blobScript+='var Select1 = Serialization.parse("'+addslashes(Serialization.stringify(Select1))+'");\n';blobScript+='var Select2 = Serialization.parse("'+addslashes(Serialization.stringify(Select2))+'");\n';blobScript+='var genetic = Serialization.parse("'+addslashes(Serialization.stringify(this))+'");\n';blobScript+="onmessage = function(e) { genetic.start(); }\n";var self=this;if(this.usingWebWorker){var blob=new Blob([blobScript]);var worker=new Worker(window.URL.createObjectURL(blob));worker.onmessage=function(e){var response=e.data;self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)};worker.onerror=function(e){alert("ERROR: Line "+e.lineno+" in "+e.filename+": "+e.message)};worker.postMessage("")}else{(function(){var onmessage;eval(blobScript);onmessage(null)})()}};return{create:function(){return new Genetic},Select1:Select1,Select2:Select2,Optimize:Optimize,Clone:Clone}}();if(typeof module!="undefined"){module.exports=Genetic}},{}]},{},[1]);
\ No newline at end of file
+(function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s})({1:[function(require,module,exports){window.Genetic=require("./genetic")},{"./genetic":2}],2:[function(require,module,exports){var Genetic=Genetic||function(){"use strict";var Serialization={stringify:function(obj){return JSON.stringify(obj,function(key,value){if(value instanceof Function||typeof value=="function")return"__func__:"+value.toString();if(value instanceof RegExp)return"__regex__:"+value;return value})},parse:function(str){return JSON.parse(str,function(key,value){if(typeof value!="string")return value;if(value.lastIndexOf("__func__:",0)===0)return eval("("+value.slice(9)+")");if(value.lastIndexOf("__regex__:",0)===0)return eval("("+value.slice(10)+")");return value})}};var Clone=function(obj){if(obj==null||typeof obj!="object")return obj;return JSON.parse(JSON.stringify(obj))};var Optimize={Maximize:function(a,b){return a>=b},Minimize:function(a,b){return a<b}};var Select1={Tournament2:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];return this.optimize(a.fitness,b.fitness)?a.entity:b.entity},Tournament3:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];var c=pop[Math.floor(Math.random()*n)];var best=this.optimize(a.fitness,b.fitness)?a:b;best=this.optimize(best.fitness,c.fitness)?best:c;return best.entity},Fittest:function(pop){return pop[0].entity},Random:function(pop){return pop[Math.floor(Math.random()*pop.length)].entity},RandomLinearRank:function(pop){this.internalGenState["rlr"]=this.internalGenState["rlr"]||0;return pop[Math.floor(Math.random()*Math.min(pop.length,this.internalGenState["rlr"]++))].entity},Sequential:function(pop){this.internalGenState["seq"]=this.internalGenState["seq"]||0;return pop[this.internalGenState["seq"]++%pop.length].entity}};var Select2={Tournament2:function(pop){return[Select1.Tournament2.call(this,pop),Select1.Tournament2.call(this,pop)]},Tournament3:function(pop){return[Select1.Tournament3.call(this,pop),Select1.Tournament3.call(this,pop)]},Random:function(pop){return[Select1.Random.call(this,pop),Select1.Random.call(this,pop)]},RandomLinearRank:function(pop){return[Select1.RandomLinearRank.call(this,pop),Select1.RandomLinearRank.call(this,pop)]},Sequential:function(pop){return[Select1.Sequential.call(this,pop),Select1.Sequential.call(this,pop)]},FittestRandom:function(pop){return[Select1.Fittest.call(this,pop),Select1.Random.call(this,pop)]}};function Genetic(){this.fitness=null;this.seed=null;this.mutate=null;this.crossover=null;this.select1=null;this.select2=null;this.optimize=null;this.generation=null;this.notification=null;this.configuration={size:250,crossover:.9,mutation:.2,iterations:100,fittestAlwaysSurvives:true,maxResults:100,webWorkers:true,skip:0};this.userData={};this.internalGenState={};this.callerFunctions={};this.entities=[];this.usingWebWorker=false;this.mapFitnessAsync=function(entities,callback){var _this=this;var scores=[];var nbScores=0;entities.forEach(function(entity,i){var setScore=function(score){scores[i]=score;nbScores+=1;if(nbScores===entities.length){callback(scores)}};if(_this.fitness.length===1){setScore(_this.fitness(entity))}else{_this.fitness(entity,setScore)}})};this.seriesAsync=function(nb,func){var self=this;var results=[];var recursion=function(i){if(i<nb){func.call(self,i,function recursionCallback(){recursion(i+1)})}};recursion(0)};this.start=function(){var self=this;for(var k in this.callerFunctions){this.callerFunctions[k]=this.wrapCallerFunction(k)}function mutateOrNot(entity){return Math.random()<=self.configuration.mutation&&self.mutate?self.mutate(Clone(entity)):entity}for(var i=0;i<this.configuration.size;++i){this.entities.push(Clone(this.seed()))}this.seriesAsync(this.configuration.iterations,function runGeneration(i,generationCallback){self.internalGenState={};self.mapFitnessAsync(self.entities,function(scores){var pop=self.entities.map(function(entity,i){return{fitness:scores[i],entity:entity}}).sort(function(a,b){return self.optimize(a.fitness,b.fitness)?-1:1});var mean=pop.reduce(function(a,b){return a+b.fitness},0)/pop.length;var stdev=Math.sqrt(pop.map(function(a){return(a.fitness-mean)*(a.fitness-mean)}).reduce(function(a,b){return a+b},0)/pop.length);var stats={maximum:pop[0].fitness,minimum:pop[pop.length-1].fitness,mean:mean,stdev:stdev};var r=self.generation?self.generation(pop,i,stats):true;var isFinished=typeof r!="undefined"&&!r||i==self.configuration.iterations-1;if(self.notification&&(isFinished||self.configuration["skip"]==0||i%self.configuration["skip"]==0)){self.sendNotification(pop.slice(0,self.maxResults),i,stats,isFinished)}if(isFinished)return;var newPop=[];if(self.configuration.fittestAlwaysSurvives)newPop.push(pop[0].entity);while(newPop.length<self.configuration.size){if(self.crossover&&Math.random()<=self.configuration.crossover&&newPop.length+1<self.configuration.size){var parents=self.select2(pop);var children=self.crossover(Clone(parents[0]),Clone(parents[1])).map(mutateOrNot);newPop.push(children[0],children[1])}else{newPop.push(mutateOrNot(self.select1(pop)))}}self.entities=newPop;generationCallback()})})};this.callerFunctionsCallbacks={};this.callbackId=0;this.wrapCallerFunction=function(funcName){if(this.usingWebWorker){var _this=this;return function(){var args=Array.prototype.slice.call(arguments);_this.callerFunctionsCallbacks[_this.callbackId]=args.pop();postMessage({callerFunction:funcName,id:_this.callbackId,arguments:Serialization.stringify(args)});_this.callbackId+=1}}else{return self.callerFunctions[funcName]}};this.onmessage=function(e){if(e.data&&this.callerFunctionsCallbacks[e.data.id]){this.callerFunctionsCallbacks[e.data.id].apply(this,Serialization.parse(e.data.arguments));delete this.callerFunctionsCallbacks[e.data.id]}else{this.start()}};this.sendNotification=function(pop,generation,stats,isFinished){var response={pop:pop.map(Serialization.stringify),generation:generation,stats:stats,isFinished:isFinished};if(this.usingWebWorker){postMessage(response)}else{self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)}}}Genetic.prototype.evolve=function(config,userData,callerFunctions){var k;for(k in config){this.configuration[k]=config[k]}for(k in userData){this.userData[k]=userData[k]}for(k in callerFunctions){this.callerFunctions[k]=callerFunctions[k]}this.usingWebWorker=this.configuration.webWorkers&&typeof Blob!="undefined"&&typeof Worker!="undefined"&&typeof window.URL!="undefined"&&typeof window.URL.createObjectURL!="undefined";function addslashes(str){return str.replace(/[\\"']/g,"\\$&").replace(/\u0000/g,"\\0")}var blobScript="'use strict'\n";blobScript+="var Serialization = {'stringify': "+Serialization.stringify.toString()+", 'parse': "+Serialization.parse.toString()+"};\n";blobScript+="var Clone = "+Clone.toString()+";\n";blobScript+='var Optimize = Serialization.parse("'+addslashes(Serialization.stringify(Optimize))+'");\n';blobScript+='var Select1 = Serialization.parse("'+addslashes(Serialization.stringify(Select1))+'");\n';blobScript+='var Select2 = Serialization.parse("'+addslashes(Serialization.stringify(Select2))+'");\n';blobScript+='var genetic = Serialization.parse("'+addslashes(Serialization.stringify(this))+'");\n';blobScript+="onmessage = function(e) { genetic.onmessage(e); }\n";var self=this;if(this.usingWebWorker){var blob=new Blob([blobScript]);var worker=new Worker(window.URL.createObjectURL(blob));worker.onmessage=function(e){var data=e.data;if(data.callerFunction){self.callerFunctions[data.callerFunction].apply(self,Serialization.parse(data.arguments).concat(function(){var args=Array.prototype.slice.call(arguments);worker.postMessage({callerFunctionCallback:data.callerFunction,id:data.id,arguments:Serialization.stringify(args)})}))}else{self.notification(data.pop.map(Serialization.parse),data.generation,data.stats,data.isFinished)}};worker.onerror=function(e){alert("ERROR: Line "+e.lineno+" in "+e.filename+": "+e.message)};worker.postMessage("start")}else{(function(){var onmessage;eval(blobScript);onmessage("start")})()}};return{create:function(){return new Genetic},Select1:Select1,Select2:Select2,Optimize:Optimize,Clone:Clone}}();if(typeof module!="undefined"){module.exports=Genetic}},{}]},{},[1]);
diff --git a/lib/genetic.js b/lib/genetic.js
index 3b08135..788409a 100644
--- a/lib/genetic.js
+++ b/lib/genetic.js
@@ -102,13 +102,14 @@ var Genetic = Genetic || (function(){
 		
 		this.userData = {};
 		this.internalGenState = {};
+		this.callerFunctions = {};
 		
 		this.entities = [];
 		
 		this.usingWebWorker = false;
 		
 		this.mapFitnessAsync = function(entities, callback) {
-			var self = this;
+			var _this = this;
 
 			var scores = [];
 			var nbScores = 0;
@@ -124,10 +125,10 @@ var Genetic = Genetic || (function(){
 				};
 
 				// Supports fitness function sync or async based on number of expected arguments
-				if (self.fitness.length === 1) {
-					setScore(self.fitness(entity));
+				if (_this.fitness.length === 1) {
+					setScore(_this.fitness(entity));
 				} else {
-					self.fitness(entity, setScore);
+					_this.fitness(entity, setScore);
 				}
 			});
 		};
@@ -149,16 +150,20 @@ var Genetic = Genetic || (function(){
 
 		this.start = function() {
 			
-			var i;
 			var self = this;
 			
+			// prepare wrapping around caller functions
+			for(var k in this.callerFunctions) {
+				this.callerFunctions[k] = this.wrapCallerFunction(k);
+			}
+
 			function mutateOrNot(entity) {
 				// applies mutation based on mutation probability
 				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
 			}
 			
 			// seed the population
-			for (i=0;i<this.configuration.size;++i)  {
+			for (var i=0;i<this.configuration.size;++i)  {
 				this.entities.push(Clone(this.seed()));
 			}
 			
@@ -168,6 +173,7 @@ var Genetic = Genetic || (function(){
 				
 				// Asynchronous score
 				self.mapFitnessAsync(self.entities, function(scores){
+
 					var pop = self.entities
 						.map(function (entity, i) {
 							return {"fitness": scores[i], "entity": entity };
@@ -230,6 +236,39 @@ var Genetic = Genetic || (function(){
 			});		
 		};
 		
+		this.callerFunctionsCallbacks = {};
+		this.callbackId = 0;
+		// In the context of a web work a callerFunction is wrapped in a postMessage/onmessage exchange
+		this.wrapCallerFunction = function(funcName) {
+			if (this.usingWebWorker) {
+				// do not use 'self' keyword, here. Weird conflict when in non worker mode
+				var _this = this;
+				return function(){
+					var args = Array.prototype.slice.call(arguments);
+					// This id will be used to create request/reply mechanism
+					_this.callerFunctionsCallbacks[_this.callbackId] = args.pop();
+					postMessage({
+						callerFunction: funcName,
+						id: _this.callbackId,
+						arguments: Serialization.stringify(args)
+					});
+					_this.callbackId += 1;
+				};
+			} else {
+				// self declared outside of scope
+				return self.callerFunctions[funcName];
+			}
+		};
+
+		this.onmessage = function(e) {
+			if (e.data && this.callerFunctionsCallbacks[e.data.id]) {
+				this.callerFunctionsCallbacks[e.data.id].apply(this, Serialization.parse(e.data.arguments));
+				delete this.callerFunctionsCallbacks[e.data.id];
+			} else {
+				this.start();
+			}
+		};
+
 		this.sendNotification = function(pop, generation, stats, isFinished) {
 			var response = {
 				"pop": pop.map(Serialization.stringify)
@@ -249,7 +288,7 @@ var Genetic = Genetic || (function(){
 		};
 	}
 	
-	Genetic.prototype.evolve = function(config, userData) {
+	Genetic.prototype.evolve = function(config, userData, callerFunctions) {
 		
 		var k;
 		for (k in config) {
@@ -259,6 +298,10 @@ var Genetic = Genetic || (function(){
 		for (k in userData) {
 			this.userData[k] = userData[k];
 		}
+
+		for (k in callerFunctions) {
+			this.callerFunctions[k] = callerFunctions[k];
+		}
 		
 		// determine if we can use webworkers
 		this.usingWebWorker = this.configuration.webWorkers
@@ -283,7 +326,7 @@ var Genetic = Genetic || (function(){
 		
 		// materialize our ga instance in the worker
 		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
-		blobScript += "onmessage = function(e) { genetic.start(); }\n";
+		blobScript += "onmessage = function(e) { genetic.onmessage(e); }\n";
 		
 		var self = this;
 		
@@ -292,19 +335,31 @@ var Genetic = Genetic || (function(){
 			var blob = new Blob([blobScript]);
 			var worker = new Worker(window.URL.createObjectURL(blob));
 			worker.onmessage = function(e) {
-			  var response = e.data;
-			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			  var data = e.data;
+			  if (data.callerFunction) {
+			  	// receive a request from the work to run a function in caller context, do it then respond by postMessage
+			  	self.callerFunctions[data.callerFunction].apply(self, Serialization.parse(data.arguments).concat(function(){
+			  		var args = Array.prototype.slice.call(arguments);
+			  		worker.postMessage({
+			  			callerFunctionCallback: data.callerFunction,
+			  			id: data.id,
+			  			arguments: Serialization.stringify(args)
+			  		});
+			  	}));
+			  } else {
+			  	self.notification(data.pop.map(Serialization.parse), data.generation, data.stats, data.isFinished);
+			  }
 			};
 			worker.onerror = function(e) {
 				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
 			};
-			worker.postMessage("");
+			worker.postMessage("start");
 		} else {
 			// simulate webworker
 			(function(){
 				var onmessage;
 				eval(blobScript);
-				onmessage(null);
+				onmessage("start");
 			})();
 		}
 	}
diff --git a/test/async.js b/test/async.js
new file mode 100644
index 0000000..d881290
--- /dev/null
+++ b/test/async.js
@@ -0,0 +1,92 @@
+
+if (typeof require === 'function') {
+	var Genetic = require("../lib/genetic");
+	var assert = require("assert");
+}
+
+
+var genetic;
+
+beforeEach(function () {
+	genetic = Genetic.create();
+});
+
+
+describe("Async", function() {
+	it("fitness", function (done) {
+		genetic.optimize = Genetic.Optimize.Maximize;
+		genetic.select1 = Genetic.Select1.Tournament2;
+		genetic.seed = function() {
+			return 0;
+		};
+		genetic.mutate = function(entity) {
+			return entity;
+		};
+
+		genetic.fitness = function(entity, callback) {
+			this.internalGenState.val = this.internalGenState.val || 0;
+			this.internalGenState.val += 1;
+			var val = this.internalGenState.val;
+			setTimeout(function(){
+				callback(val);
+			}, 1);
+		};
+		
+		var count = 0;
+		genetic.notification = function(pop, generation, stats, isFinished) {
+			count++;
+			if (isFinished) {
+				assert.equal(count, 2);
+				assert.equal(stats.maximum, 10);
+				assert.equal(stats.mean, 5.5);
+				done();
+			}
+		};
+		var config = {
+			"iterations": 2
+			, "size": 10
+			, "crossover": 0.0
+			, "skip": 10
+		};
+		genetic.evolve(config);
+	});
+
+	it("caller function", function (done) {
+		genetic.optimize = Genetic.Optimize.Maximize;
+		genetic.select1 = Genetic.Select1.Tournament2;
+		genetic.seed = function() {
+			return 0;
+		};
+		genetic.mutate = function(entity) {
+			return entity;
+		};
+
+		genetic.fitness = function(entity, callback) {
+			this.callerFunctions.getCallerVar(callback);
+		};
+		
+		var count = 0;
+		genetic.notification = function(pop, generation, stats, isFinished) {
+			if (isFinished) {
+				assert.equal(stats.maximum, 10);
+				assert.equal(stats.mean, 5.5);
+				done();
+			}
+		};
+		var config = {
+			"iterations": 1
+			, "size": 10
+			, "crossover": 0.0
+			, "skip": 1
+		};
+
+		var callerVar = 0;
+
+		genetic.evolve(config, {}, {
+			getCallerVar: function(callback){
+				callerVar += 1;
+				callback(callerVar);
+			}
+		});
+	});
+});
\ No newline at end of file

From 4d639b3e372b40fe4f0e4e2a795f3f42ba685736 Mon Sep 17 00:00:00 2001
From: Alban Mouton through Travis-CI <alban.mouton@gmail.com>
Date: Sun, 16 Aug 2015 21:09:58 +0200
Subject: [PATCH 4/6] add html launcher for async tests

---
 test/index.html | 25 +++++++++++++++++++++++++
 1 file changed, 25 insertions(+)
 create mode 100644 test/index.html

diff --git a/test/index.html b/test/index.html
new file mode 100644
index 0000000..a8198de
--- /dev/null
+++ b/test/index.html
@@ -0,0 +1,25 @@
+<html>
+<head>
+  <meta charset="utf-8">
+  <title>Mocha Tests</title>
+  <link href="https://cdn.rawgit.com/mochajs/mocha/2.2.5/mocha.css" rel="stylesheet" />
+</head>
+<body>
+  <div id="mocha"></div>
+
+  <script src="../js/genetic-0.1.14.js"></script>
+  <script src="https://rawgit.com/Jxck/assert/master/assert.js"></script>
+  <script src="https://cdn.rawgit.com/mochajs/mocha/2.2.5/mocha.js"></script>
+
+  <script>mocha.setup('bdd')</script>
+  <script src="async.js"></script>
+  <script src="config.js"></script>
+  <script src="misc.js"></script>
+  <script src="parabolic.js"></script>
+  <script src="string.js"></script>
+  <script>
+    mocha.checkLeaks();
+    mocha.run();
+  </script>
+</body>
+</html>
\ No newline at end of file

From a99ca0bb9daf890881dfd017e161097587e39c34 Mon Sep 17 00:00:00 2001
From: Alban Mouton through Travis-CI <alban.mouton@gmail.com>
Date: Tue, 18 Aug 2015 20:57:37 +0200
Subject: [PATCH 5/6] do not use Serialization for caler functions. Not
 necessary and costly for performance

---
 lib/genetic.js | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/lib/genetic.js b/lib/genetic.js
index 788409a..019a85c 100644
--- a/lib/genetic.js
+++ b/lib/genetic.js
@@ -250,7 +250,7 @@ var Genetic = Genetic || (function(){
 					postMessage({
 						callerFunction: funcName,
 						id: _this.callbackId,
-						arguments: Serialization.stringify(args)
+						arguments: args
 					});
 					_this.callbackId += 1;
 				};
@@ -262,7 +262,7 @@ var Genetic = Genetic || (function(){
 
 		this.onmessage = function(e) {
 			if (e.data && this.callerFunctionsCallbacks[e.data.id]) {
-				this.callerFunctionsCallbacks[e.data.id].apply(this, Serialization.parse(e.data.arguments));
+				this.callerFunctionsCallbacks[e.data.id].apply(this, e.data.arguments);
 				delete this.callerFunctionsCallbacks[e.data.id];
 			} else {
 				this.start();
@@ -332,18 +332,19 @@ var Genetic = Genetic || (function(){
 		
 		if (this.usingWebWorker) {
 			// webworker
+
 			var blob = new Blob([blobScript]);
 			var worker = new Worker(window.URL.createObjectURL(blob));
 			worker.onmessage = function(e) {
 			  var data = e.data;
 			  if (data.callerFunction) {
 			  	// receive a request from the work to run a function in caller context, do it then respond by postMessage
-			  	self.callerFunctions[data.callerFunction].apply(self, Serialization.parse(data.arguments).concat(function(){
+			  	self.callerFunctions[data.callerFunction].apply(self, data.arguments.concat(function(){
 			  		var args = Array.prototype.slice.call(arguments);
 			  		worker.postMessage({
 			  			callerFunctionCallback: data.callerFunction,
 			  			id: data.id,
-			  			arguments: Serialization.stringify(args)
+			  			arguments: args
 			  		});
 			  	}));
 			  } else {

From 234678d75fcafa3762bff8b6efec7a57e9cb2a88 Mon Sep 17 00:00:00 2001
From: Alban Mouton through Travis-CI <alban.mouton@gmail.com>
Date: Mon, 31 Aug 2015 22:01:36 +0200
Subject: [PATCH 6/6] remove temp file

---
 lib/genetic.js~ | 332 ------------------------------------------------
 1 file changed, 332 deletions(-)
 delete mode 100644 lib/genetic.js~

diff --git a/lib/genetic.js~ b/lib/genetic.js~
deleted file mode 100644
index 46f6444..0000000
--- a/lib/genetic.js~
+++ /dev/null
@@ -1,332 +0,0 @@
-
-var Genetic = Genetic || (function(){
-	
-	'use strict';
-	
-	// facilitates communcation between web workers
-	var Serialization = {
-		"stringify": function (obj) {
-			return JSON.stringify(obj, function (key, value) {
-				if (value instanceof Function || typeof value == "function") return "__func__:" + value.toString();
-				if (value instanceof RegExp) return "__regex__:" + value;
-				return value;
-			});
-		}, "parse": function (str) {
-			return JSON.parse(str, function (key, value) {
-				if (typeof value != "string") return value;
-				if (value.lastIndexOf("__func__:", 0) === 0) return eval('(' + value.slice(9) + ')');
-				if (value.lastIndexOf("__regex__:", 0) === 0) return eval('(' + value.slice(10) + ')');
-				return value;
-			});
-		}
-	};
-	
-	var Clone = function(obj) {
-		if (obj == null || typeof obj != "object")
-			return obj;
-		
-		return JSON.parse(JSON.stringify(obj));
-	};
-	
-	var Optimize = {
-		"Maximize": function (a, b) { return a >= b; }
-		, "Minimize": function (a, b) { return a < b; }
-	};
-	
-	var Select1 = {
-		"Tournament2": function(pop) {
-			var n = pop.length;
-			var a = pop[Math.floor(Math.random()*n)];
-			var b = pop[Math.floor(Math.random()*n)];
-			return this.optimize(a.fitness, b.fitness) ? a.entity : b.entity;
-		}, "Tournament3": function(pop) {
-			var n = pop.length;
-			var a = pop[Math.floor(Math.random()*n)];
-			var b = pop[Math.floor(Math.random()*n)];
-			var c = pop[Math.floor(Math.random()*n)];
-			var best = this.optimize(a.fitness, b.fitness) ? a : b;
-			best = this.optimize(best.fitness, c.fitness) ? best : c;
-			return best.entity;
-		}, "Fittest": function (pop) {
-			return pop[0].entity;
-		}, "Random": function (pop) {
-			return pop[Math.floor(Math.random()*pop.length)].entity;
-		}, "RandomLinearRank": function (pop) {
-			this.internalGenState["rlr"] = this.internalGenState["rlr"]||0;
-			return pop[Math.floor(Math.random()*Math.min(pop.length,(this.internalGenState["rlr"]++)))].entity;
-		}, "Sequential": function (pop) {
-			this.internalGenState["seq"] = this.internalGenState["seq"]||0;
-			return pop[(this.internalGenState["seq"]++)%pop.length].entity;
-		}
-	};
-	
-	var Select2 = {
-		"Tournament2": function(pop) {
-			return [Select1.Tournament2.call(this, pop), Select1.Tournament2.call(this, pop)];
-		}, "Tournament3": function(pop) {
-			return [Select1.Tournament3.call(this, pop), Select1.Tournament3.call(this, pop)];
-		}, "Random": function (pop) {
-			return [Select1.Random.call(this, pop), Select1.Random.call(this, pop)];
-		}, "RandomLinearRank": function (pop) {
-			return [Select1.RandomLinearRank.call(this, pop), Select1.RandomLinearRank.call(this, pop)];
-		}, "Sequential": function (pop) {
-			return [Select1.Sequential.call(this, pop), Select1.Sequential.call(this, pop)];
-		}, "FittestRandom": function (pop) {
-			return [Select1.Fittest.call(this, pop), Select1.Random.call(this, pop)];
-		}
-	};
-	
-	function Genetic() {
-		
-		// population
-		this.fitness = null;
-		this.seed = null;
-		this.mutate = null;
-		this.crossover = null;
-		this.select1 = null;
-		this.select2 = null;
-		this.optimize = null;
-		this.generation = null;
-		this.notification = null;
-		
-		this.configuration = {
-			"size": 250
-			, "crossover": 0.9
-			, "mutation": 0.2
-			, "iterations": 100
-			, "fittestAlwaysSurvives": true
-			, "maxResults": 100
-			, "webWorkers": true
-			, "skip": 0
-		};
-		
-		this.userData = {};
-		this.internalGenState = {};
-		
-		this.entities = [];
-		
-		this.usingWebWorker = false;
-		
-		this.mapFitnessAsync = function(entities, callback) {
-			var self = this;
-
-			var scores = entities.map(function() {
-				return null;
-			});
-			var nbScores = 0;
-
-			entities.forEach(function(entity, i) {
-
-				var setScore = function(score) {
-					scores[i] = score;
-					nbScores += 1;
-					if (nbScores === entities.length) {
-						callback(scores);
-					}
-				};
-
-				setTimeout(function() {
-					// Supports fitness function sync or async based on number of expected arguments
-					if (self.fitness.length === 1) {
-						setScore(self.fitness(entity));
-					} else {
-						self.fitness(entity, setScore);
-					}
-				}, 0);
-			});
-		};
-
-		this.seriesAsync = function(nb, func) {
-			var self = this;
-			var results = [];
-
-			var recursion = function(i) {
-				setTimeout(function() {
-					if(i < nb) {
-						func.call(self, function recursionCallback() {
-							recursion(i + 1);
-						});
-					}
-				}, 0);
-			};
-
-			recursion(0);
-		};
-		this.start = function() {
-			
-			var i;
-			var self = this;
-			
-			function mutateOrNot(entity) {
-				// applies mutation based on mutation probability
-				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
-			}
-			
-			// seed the population
-			for (i=0;i<this.configuration.size;++i)  {
-				this.entities.push(Clone(this.seed()));
-			}
-			
-			this.seriesAsync(this.configuration.iterations, function runGeneration(generationCallback){
-				// reset for each generation
-				self.internalGenState = {};
-				
-				// Asynchronous score
-				self.mapFitnessAsync(self.entities, function(scores){
-					var pop = self.entities
-						.map(function (entity, i) {
-							return {"fitness": scores[i], "entity": entity };
-						})
-						.sort(function (a, b) {
-							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
-						});
-					
-					// generation notification
-					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
-					var stdev = Math.sqrt(pop
-						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
-						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
-						
-					var stats = {
-						"maximum": pop[0].fitness
-						, "minimum": pop[pop.length-1].fitness
-						, "mean": mean
-						, "stdev": stdev
-					};
-
-					var r = self.generation ? self.generation(pop, i, stats) : true;
-					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
-					
-					if (
-						self.notification
-						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
-					) {
-						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
-					}
-						
-					if (isFinished)
-						return;
-					
-					// crossover and mutate
-					var newPop = [];
-					
-					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
-						newPop.push(pop[0].entity);
-					
-					while (newPop.length < self.configuration.size) {
-						if (
-							self.crossover // if there is a crossover function
-							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
-							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
-						) {
-							var parents = self.select2(pop);
-							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
-							newPop.push(children[0], children[1]);
-						} else {
-							newPop.push(mutateOrNot(self.select1(pop)));
-						}
-					}
-					
-					self.entities = newPop;
-
-					generationCallback();
-				});
-
-			});		
-		};
-		
-		this.sendNotification = function(pop, generation, stats, isFinished) {
-			var response = {
-				"pop": pop.map(Serialization.stringify)
-				, "generation": generation
-				, "stats": stats
-				, "isFinished": isFinished
-			};
-			
-			
-			if (this.usingWebWorker) {
-				postMessage(response);
-			} else {
-				// self declared outside of scope
-				self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
-			}
-			
-		};
-	}
-	
-	Genetic.prototype.evolve = function(config, userData) {
-		
-		var k;
-		for (k in config) {
-			this.configuration[k] = config[k];
-		}
-		
-		for (k in userData) {
-			this.userData[k] = userData[k];
-		}
-		
-		// determine if we can use webworkers
-		this.usingWebWorker = this.configuration.webWorkers
-			&& typeof Blob != "undefined"
-			&& typeof Worker != "undefined"
-			&& typeof window.URL != "undefined"
-			&& typeof window.URL.createObjectURL != "undefined";
-		
-		function addslashes(str) {
-			return str.replace(/[\\"']/g, '\\$&').replace(/\u0000/g, '\\0');
-		}
-			
-		// bootstrap webworker script
-		var blobScript = "'use strict'\n";
-		blobScript += "var Serialization = {'stringify': " + Serialization.stringify.toString() + ", 'parse': " + Serialization.parse.toString() + "};\n";
-		blobScript += "var Clone = " + Clone.toString() + ";\n";
-		
-		// make available in webworker
-		blobScript += "var Optimize = Serialization.parse(\"" + addslashes(Serialization.stringify(Optimize)) + "\");\n";
-		blobScript += "var Select1 = Serialization.parse(\"" + addslashes(Serialization.stringify(Select1)) + "\");\n";
-		blobScript += "var Select2 = Serialization.parse(\"" + addslashes(Serialization.stringify(Select2)) + "\");\n";
-		
-		// materialize our ga instance in the worker
-		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
-		blobScript += "onmessage = function(e) { genetic.start(); }\n";
-		
-		var self = this;
-		
-		if (this.usingWebWorker) {
-			// webworker
-			var blob = new Blob([blobScript]);
-			var worker = new Worker(window.URL.createObjectURL(blob));
-			worker.onmessage = function(e) {
-			  var response = e.data;
-			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
-			};
-			worker.onerror = function(e) {
-				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
-			};
-			worker.postMessage("");
-		} else {
-			// simulate webworker
-			(function(){
-				var onmessage;
-				eval(blobScript);
-				onmessage(null);
-			})();
-		}
-	}
-	
-	return {
-		"create": function() {
-			return new Genetic();
-		}, "Select1": Select1
-		, "Select2": Select2
-		, "Optimize": Optimize
-		, "Clone": Clone
-	};
-	
-})();
-
-
-// so we don't have to build to run in the browser
-if (typeof module != "undefined") {
-	module.exports = Genetic;
-}