// GA constructor
public GA(Initializer init, Fitness fit, Mutate mutater, CrossOver crossOver)
{
computeFitness = fit;
initChromo = init;
crossoverProc = crossOver;
mutateProc = mutater;
}
public GeneticAlgorithm()
{
crossover = CrossOverPMX;
selection = Tornament;
CrossOverRate = ConfigurationGA.rateCrossOver;
MutationRate = ConfigurationGA.rateMutation;
}
private void Init(
int numberOfGenerations,
CompareEvaluate compareTwo,
Evaluate evaluate,
CrossOver crossoverOp,
Generate generator,
List <IIndividual> population)
{
Maximize = false;
EliminatedPercent = 0.2f;
ElitismPercent = 0.1f;
_NumberOfGenerations = numberOfGenerations;
if (population != null)
{
_Population = population
.Select(i => i.ToEI())
.ToList();
_PopSize = population.Count;
}
_Tournament = null;
_GenerationCount = 0;
_Compare = compareTwo;
_Eval = evaluate;
_Generate = generator;
_Crossover = crossoverOp;
_Champions = new List <EvaluatedIndividual>(_NumberOfGenerations);
VariationSettings = new VariationSettings(6, 4, 2);
_Rng = new Random();
_mutationProbability = 0.6f;
_mutationSigma = 1;
Threads = 4;
}
public StraightThrough(StraightConveyorInfo info, ThreeWaySwitch _threeWaySwitch) : base(info)
{
straightConveyorInfo = info;
threeWaySwitch = _threeWaySwitch;
_threeWaySwitch.AllRoutes.Add(this);
WaitingConveyors.Add(ThreeWayRoutes.Left, waitingForLeft);
WaitingConveyors.Add(ThreeWayRoutes.Right, waitingForRight);
WaitingConveyors.Add(ThreeWayRoutes.Center, waitingForCenter);
Length = threeWaySwitch.threeWaySwitchInfo.threeWayLength;
endAP = TransportSection.Route.InsertActionPoint(Length - 0.3f);
startAP = TransportSection.Route.InsertActionPoint(0.3f);
startAP.OnEnter += startAP_OnEnter;
endAP.OnEnter += endAP_OnEnter;
crossOverX = new CrossOver(Core.Environment.Scene.DefaultColor, 1, 0.05f, 0.3f, _threeWaySwitch)
{
straightThrough = this
};
crossOverY = new CrossOver(Core.Environment.Scene.DefaultColor, 1, 0.05f, 0.3f, _threeWaySwitch)
{
straightThrough = this
};
Add(crossOverX);
Add(crossOverY);
RouteAvailable = RouteStatuses.Request;//3 way will control the release of loads onto the transfer
_threeWaySwitch.OnDimensionsChanged += threeWaySwitch_OnDimensionsChanged;
StartFixPoint.OnSnapped += StraightStartFixPoint_OnSnapped;
StartFixPoint.OnUnSnapped += StraightStartFixPoint_OnUnSnapped;
OnNextRouteStatusAvailableChanged += StraightThrough_OnNextRouteStatusAvailableChanged;
}
public override int GetHashCode()
{
int hash = 17;
hash = hash * 23 + CrossOver.GetHashCode();
hash = hash * 23 + Mutate.GetHashCode();
return(hash);
}
public GeneticAlgo(Fitness fitness, Population population, Selection selection, CrossOver crossover, Mutation mutation)
{
Population = population;
_fitness = fitness;
_selection = selection;
_crossover = crossover;
_mutation = mutation;
}
public State <T> Step()
{
State = Killer.Kill(State);
State = CrossOver.CrossOver(State);
//State = Mutator.Mutate(State);
return(State);
}
public void Test_That_Genetic_Algorithm_On_Sphere_Works()
{
GeneticAlgorithm <double[]> garden = new GeneticAlgorithm <double[]>((double[] sol1, double[] sol2) => {
return(CrossOver.CutAndSplice <double>(sol1, sol2)[0].ToArray());
});
Sphere sphere = new Sphere();
garden.create(sphere.getConfiguration());
garden.fullIteration();
}
public void Test_That_Knapsack_Genetic_Algorithm_Works()
{
this.Load(Constants.SAMPLE_MKNAPCB4_DATASET);
Console.WriteLine($"Goal:\t{this.goal}");
GeneticAlgorithm <List <int> > ga = new GeneticAlgorithm <List <int> >((List <int> sol1, List <int> sol2) => {
return(CrossOver.CutAndSplice <int>(sol1.AsEnumerable(), sol2.AsEnumerable())[0].ToList());
});
ga.create(this.getConfiguration());
List <int> finalSolution = ga.fullIteration();
}
public Ages(
int numberOfGenerations,
Evaluate eval,
CrossOver crossOverOp,
Generate generator,
List <IIndividual> individuals)
{
Init(numberOfGenerations,
null,
eval,
crossOverOp,
generator,
individuals);
}
public Ages(
int numberOfGenerations,
CompareEvaluate compareTwo,
CrossOver crossoverOp,
Generate generator,
List <IIndividual> population)
{
Init(numberOfGenerations,
compareTwo,
null,
crossoverOp,
generator,
population);
}
public Ages(
int numberOfGenerations,
CompareEvaluate compareTwo,
CrossOver crossoverOp,
Generate generator,
int popSize)
{
Init(numberOfGenerations,
compareTwo,
null,
crossoverOp,
generator,
null);
_PopSize = popSize;
}
public Ages(
int numberOfGenerations,
Evaluate eval,
CrossOver crossOverOp,
Generate generator,
int popSize)
{
Init(numberOfGenerations,
null,
eval,
crossOverOp,
generator,
null);
_PopSize = popSize;
}
public static void NextGen()
{
Genome c1 = new Genome(false);
Genome c2 = new Genome(false);
RouletteWheelSelection select = new RouletteWheelSelection();
CrossOver cross = new CrossOver();
cross.SinglePointCrossOver(select.RouletteWheelSelect(), select.RouletteWheelSelect(), ref c1, ref c2);
Mutate(ref c1);
Mutate(ref c2);
genome.Add(c1);
genome.Add(c2);
if (genome.Count == DNAattributes.PopulationSize)
{
DNAattributes.pop = genome;
}
}
//sets up the initial GA
public GeneticAlgo CreateGA(string[][] _sampleGenomes)
{
System.Random r = new System.Random(Time.frameCount);
//specify the numbers of genes to the population.
string selectType = "god mode";
string mutateType = "randomChoice";
string crossType = "OnePt";
Encoder encoder = _encode;
Fitness fitness = new Fitness("");
Population population = new Population(_childCount, encoder._symbols, samplePopulation: _sampleGenomes, variableGenomeLength: true);
Selection selection = new Selection(selectType);
CrossOver crossover = new CrossOver(crossType);
Mutation mutation = new Mutation(mutateType, _mutationRate);
return(new GeneticAlgo(encoder, fitness, population, selection, crossover, mutation));
}
public void CreateGA()
{
System.Random r = new System.Random(Time.frameCount);
string selectType = "god mode";
string mutateType = "randomChoice";
string crossType = "OnePt";
Encoder encoder = new Encoder();
string target = encoder.Encode(TextureNoise.CreateNoise(width, height, r));
Fitness fitness = new Fitness(target);
Population population = new Population(20, fitness._targetString)
{
_name = "images"
};
Selection selection = new Selection(selectType);
CrossOver crossover = new CrossOver(crossType);
Mutation mutation = new Mutation(mutateType);
geneticAlgo = new GeneticAlgo(encoder, fitness, population, selection, crossover, mutation);
}
private void btnSearch_Click(object sender, EventArgs e)
{
isInSearch = true;
if (!isValidNumberOfCities())
{
MessageBox.Show("Số thành phố tối thiểu phải bằng 4 !", "Cảnh báo");
return;
}
distanceMatrix = ComputeDistances(points); // tính ma trận khoảng cách từ ma trận điểm đã cho
Initializer khoitaomoi = new Initializer(InitialGA.khoitaoNST);
Mutate dotbien = new Mutate(InitialGA.Compraror_NST);
Fitness phepthichnghi = new Fitness(InitialGA.Thichnghi);
CrossOver pheplaighep = new CrossOver(InitialGA.Laighep);
//tao doi tuong moi
GA GeneticSolver = new GA(khoitaomoi, phepthichnghi, dotbien, pheplaighep);
GeneticSolver.Generations = (long)numGenLimit.Value;
GeneticSolver.PopulationSize = (ushort)numPopSize.Value;
GeneticSolver.Mutation = (double)numMutation.Value;
GeneticSolver.CrossOver = (double)numCrossOver.Value;
// Khoi tao thuat toan
GeneticSolver.Initialize();
// kiem tra dieu kien dung
// chua thoa man thuc hien tao the he moi
while (!GeneticSolver.IsStop())
{
GeneticSolver.CreateNextGeneration();
}
// Lay ra phan tu co do thich nghi tot nhat trong quan the
solutionChromo = GeneticSolver.GetBestChromosome();
// Vẽ phương án lên bản đồ
ptbMap.Refresh();
DrawPath(solutionChromo);
DrawPoints();
}
void Cross()
{
newIndividuals = new Individual[individuals.Length];
if (CrossOver == null || Selection == null)
{
return;
}
int length = Selection.Selected.Length % 2 == 0 ? Selection.Selected.Length : Selection.Selected.Length - 1;
int index = 0;
// Offsprings
for (int i = 0; i < length; i += 2)
{
CrossOver.Cross(
individuals[Selection.Selected[i]],
individuals[Selection.Selected[i + 1]]);
newIndividuals[index++] = CrossOver.Offspring1.Clone();
newIndividuals[index++] = CrossOver.Offspring2.Clone();
}
// Parents
for (int i = 0; i < length && index < newIndividuals.Length; i++)
{
newIndividuals[index++] = individuals[Selection.Selected[i]].Clone();
}
// XXX: for safety
while (index < newIndividuals.Length)
{
int i = random.Next(individuals.Length);
newIndividuals[index++] = individuals[i].Clone();
}
}
public void OnClickAdd()
{
string selectType = dSelect.options [dSelect.value].text;
string mutateType = dMutate.options [dMutate.value].text;
string crossType = dCross.options [dCross.value].text;
if (geneticAlgos.Count < maxPops)
{
Fitness fitness = new Fitness(targetString);
Population population = new Population(popSize, fitness._targetString)
{
_name = (geneticAlgos.Count + 1).ToString()
};
Selection selection = new Selection(selectType);
CrossOver crossover = new CrossOver(crossType);
Mutation mutation = new Mutation(mutateType);
geneticAlgos.Add(new GeneticAlgo(fitness, population, selection, crossover, mutation));
}
else
{
Debug.Log("Population Limit Reached : 5 is the Maximum Number of geneticAlgos");
}
}
static void Main(string[] args)
{
List <Vehicle> vehicles = new List <Vehicle>();
List <Driver> drivers = new List <Driver>();
Driver erez = new Driver(200, "Erez");
Driver ron = new Driver(130, "Ron");
Driver ido = new Driver(220, "Ido");
SportCar mazdaCar = new SportCar(0, "Toyota", "Red", 150);
CrossOver suzukiCrossOver = new CrossOver(1, "suzuki", "black", 100);
Bicycle bmx = new Bicycle(2, "BMX", "white");
mazdaCar.FirstDriver = erez;
mazdaCar.SecondDriver = ron;
bmx.FirstDriver = ido;
drivers.Add(erez);
drivers.Add(ron);
drivers.Add(ido);
vehicles.Add(mazdaCar);
vehicles.Add(suzukiCrossOver);
vehicles.Add(bmx);
string quit;
string assignVehicle;
string assignDriver;
string position;
string id;
string carType;
string input = "-1";
while (input != "8")
{
Console.WriteLine(
"Please input your option -> \n\n" +
"1- Add new vehicle \n" +
"2- Show vehicle list \n" +
"3- Delete a vehicle\n" +
"4- Add new driver \n" +
"5- show driver list \n" +
"6- Delete a driver\n" +
"7- Assign a driver\n" +
"8- Exit\n"
);
input = (Console.ReadLine());
if (!IsNumeric(input))
{
InvalidKey();
}
else
{
switch (input)
{
case "1":
Console.Write(
"Please choose your option-> \n" +
"1- Bicycle \n" +
"2- Sport Car \n" +
"3- CrossOver\n"
);
carType = (Console.ReadLine());
if (!IsNumeric(carType) && carType != "1" && carType != "2" && carType != "3")
{
InvalidKey();
}
else
{
Vehicle temp = AddVehicleHandler(vehicles[vehicles.Count - 1].Id + 1, carType);
if (temp != null)
{
vehicles.Add(temp);
}
}
PressAnyKey();
break;
case "2":
foreach (Vehicle element in vehicles)
{
Console.WriteLine(element.ToString());
}
PressAnyKey();
break;
case "3":
bool flag = true;
foreach (Vehicle element in vehicles)
{
Console.WriteLine(element.ToString());
}
Console.Write("Choose ID to remove ->");
id = Console.ReadLine();
if (!IsNumeric(id))
{
InvalidKey();
PressAnyKey();
break;
}
else
{
flag = false;
foreach (Vehicle element in vehicles)
{
if (element.Id == int.Parse(id))
{
vehicles.Remove(element);
flag = true;
break;
}
}
if (flag)
{
Console.WriteLine("Vehicle removed successfully!");
}
else
{
Console.WriteLine("ID not found. Nothing removed.");
}
}
PressAnyKey();
break;
case "4":
drivers.Add(AddDriverHandler());
PressAnyKey();
break;
case "5":
foreach (Driver element in drivers)
{
Console.WriteLine(element.ToString());
}
PressAnyKey();
break;
case "6":
flag = true;
foreach (Driver element in drivers)
{
Console.WriteLine(element.ToString());
}
Console.Write("Choose ID to remove ->");
id = Console.ReadLine();
if (!IsNumeric(id))
{
InvalidKey();
break;
}
else
{
flag = false;
foreach (Driver element in drivers)
{
if (element.Id == int.Parse(id))
{
drivers.Remove(element);
flag = true;
break;
}
}
if (flag)
{
Console.WriteLine("Driver removed successfully!");
}
else
{
Console.WriteLine("ID not found. Nothing removed.");
}
}
PressAnyKey();
break;
case "7":
foreach (Vehicle element in vehicles)
{
Console.WriteLine(element.ToString());
}
Console.Write("Choose Vehicle ID to assign a driver to ->");
assignVehicle = Console.ReadLine();
flag = false;
foreach (Vehicle element in vehicles)
{
if (element.Id == int.Parse(assignVehicle))
{
flag = true;
Vehicle vehicle = element;
break;
}
}
if (!flag)
{
Console.WriteLine("ID not found, please try again.");
break;
}
else
{
foreach (Driver element in drivers)
{
Console.WriteLine(element.ToString());
}
Console.Write("Choose Driver ID to assign to the selected vehicle ->");
assignDriver = Console.ReadLine();
foreach (Driver element in drivers)
{
if (element.Id == int.Parse(assignDriver))
{
flag = true;
Driver driver = element;
break;
}
}
if (!flag)
{
Console.WriteLine("ID not found, please try again.");
break;
}
else
{
foreach (Vehicle vehicle in vehicles)
{
if (vehicle.Id == int.Parse(assignVehicle))
{
foreach (Driver driver in drivers)
{
if (driver.Id == int.Parse(assignDriver))
{
if (vehicle.AmoutOfDrivers == 1)
{
vehicle.FirstDriver = driver;
}
else
{
Car carVehicle = (Car)vehicle;
Console.Write("Which Driver position do you want to assign to? (1/2) ->");
position = Console.ReadLine();
if (!IsNumeric(position))
{
InvalidKey();
flag = false;
break;
}
else
{
switch (position)
{
case "1":
carVehicle.FirstDriver = driver;
break;
case "2":
carVehicle.SecondDriver = driver;
break;
default: break;
}
}
}
Console.WriteLine("Driver assigned successfully!");
PressAnyKey();
break;
}
}
}
if (!flag)
{
break;
}
}
}
}
PressAnyKey();
break;
case "8":
Console.Write("Are you sure you want to quit? (y/n) ->");
quit = Console.ReadLine();
if (quit == "y")
{
break;
}
else if (quit == "n")
{
input = "-1";
break;
}
InvalidKey();
PressAnyKey();
break;
default: break;
}
}
Console.Clear();
}
}
public void Run()
{
for (int i = 0; i < Generations; i++)
{
if (BeforeRun != null)
{
BeforeRun(this, new GeneticEventArgs(i));
}
foreach (var chromosome in Population.Chromosomes)
{
chromosome.Fitness = Evaluator.ComputeFitness(chromosome.Genes);
}
Population.Chromosomes = Population.Chromosomes.OrderByDescending(x => x.Fitness).ToList();
if (BeforeKill != null)
{
BeforeKill(this, EventArgs.Empty);
}
Killer.Kill(Population);
if (AfterKill != null)
{
AfterKill(this, EventArgs.Empty);
}
var selected = Selector.Select(Population.Chromosomes);
if (BeforeCrossOver != null)
{
BeforeCrossOver(this, EventArgs.Empty);
}
foreach (var pair in selected)
{
var offspring = CrossOver.CrossOver(pair.Item1, pair.Item2);
Population.AddChromosome(offspring);
}
if (AfterCrossOver != null)
{
AfterCrossOver(this, EventArgs.Empty);
}
if (BeforeMutate != null)
{
BeforeMutate(this, EventArgs.Empty);
}
MutateStep(Population);
if (AfterMutate != null)
{
AfterMutate(this, EventArgs.Empty);
}
if (AfterRun != null)
{
AfterRun(this, new GeneticEventArgs(i));
}
if (Solution.IsSolution(Population.Best))
{
if (OnSolution != null)
{
OnSolution(this, EventArgs.Empty);
}
return;
}
}
}
public EvaluationTrain(GettingStarted gettingStarted)
{
_randomSelection = new RandomSelection(gettingStarted.EarlyPopulation);
_rouletteWeelSelection = new RouletteWeel2Selection();
_crossOver = new CrossOver(gettingStarted.Items, gettingStarted.KnapsakCapacity);
}
private void Test_PolynomialGA(Func <double, double> func)
{
//Settings
bool adaptive = false;
int seed = 0;
Utils.SetRandomSeed(seed);
var rng = new Random(seed);
PolynomialOrder = 5;
int populationSize = 100;
//number of samples to use the in the polynomial approx
// to test the differnce
double start = -10, end = 10;
//Step between the samples
double step = 0.02;
//Number of generations to bundle
int genBundleCount = 10;
//Stop at Gen
GenerationStop = 500;
//Get Data for tests
double[] xRange, expectedValues;
GetFofXForRange(func, start, step, end, out xRange, out expectedValues);
double[][] allPowsOfX = GetPowersOfX(xRange, PolynomialOrder);
ExpectedValsX = xRange;
ExpectedValsY = expectedValues;
PowsOfXForAllX = allPowsOfX;
//Create Delegates
Evaluate eval = (i) =>
((CartesianIndividual)i).PolynomialEval(allPowsOfX, expectedValues);
CrossOver crossOver = adaptive
? AdaptiveCartesianIndividual.CrossOver
: (CrossOver)CartesianIndividual.CrossOver;
Generate generate = adaptive
? (Generate)((r) => new AdaptiveCartesianIndividual(PolynomialOrder, 1, r: r, emptySigma: true))
: (r) => new CartesianIndividual(PolynomialOrder, 1, r);
// Generate Population
List <IIndividual> pop;
pop = Enumerable
.Range(0, populationSize)
.Select(i => generate(rng))
.Cast <IIndividual>()
.ToList();
Ages = new Ages(genBundleCount,
eval,
crossOver,
generate,
pop);
Ages.SetRandomSeed(seed);
Ages.NicheStrat = new NicheDensityStrategy(
Ages,
(l, r) => CartesianIndividual.Distance((CartesianIndividual)l, (CartesianIndividual)r));
}
static void Main(string[] args)
{
Console.Write("Enter a Number: ");
string userInput = Console.ReadLine();
Console.WriteLine("Your Number is: {0}", userInput);
var dictionary = new Dictionary <string, string>();
dictionary["apple"] = "A fruit or a computer company";
Console.WriteLine(dictionary["apple"]);
var someList = new List <int>();
someList.Add(1);
someList.Add(2);
someList.Add(3);
someList.Add(5);
someList.Add(8);
someList.Add(11);
someList.RemoveAt(0);
someList.RemoveAt(2);
for (int i = 0; i < someList.Count; i++)
{
Console.WriteLine(someList[i]);
}
foreach (int number in someList)
{
Console.WriteLine(number);
}
someList.ForEach(number => Console.WriteLine(number));
someList.ForEach(Console.WriteLine);
string[] names = { "John", "Daryl", "Mike", "Sarah", "Michele" };
string[] moreNames = new string[5];
moreNames[0] = "John";
moreNames[1] = "Daryl";
Console.WriteLine("Size of names: {0}\nSize of moreNames: {1}", names.Length, moreNames.Length);
// and so on
string student = "John Smith";
char firstCharacter = student[1];
// ---- Exercise for loops ----
var animals = new List <string>();
animals.Add("Lion");
animals.Add("Tiger");
animals.Add("Bird");
animals.Add("Cat");
animals.Add("Dog");
animals.Add("Leopard");
string favoriteAnimal = "Bird";
foreach (string animal in animals)
{
Console.WriteLine(animal);
}
if (animals.Contains(favoriteAnimal))
{
Console.WriteLine("I love {0} and also every other animal, including {1}", favoriteAnimal, animals[2]);
// same as the above line, but without the placeholder
Console.WriteLine("I love " + favoriteAnimal + "and also every other animal, including " + animals[2]);
}
else
{
Console.WriteLine("No, I don't care for those");
}
// dictionary looping
var person = new Dictionary <string, int>();
person.Add("Joan", 22);
person.Add("Daniel", 42);
person.Add("Anna", 34);
// person = {Joan=22, Daniel=42, Anna=34}
// loop through the hash map and return each key/value pair
for (int i = 0; i < person.Count; i++)
{
Console.WriteLine("Key: {0}, Value: {1}",
person.Keys.ElementAt(i),
person[person.Keys.ElementAt(i)]);
}
foreach (var peep in person)
{
// print out the key (their name) and their value
Console.WriteLine("Name: {0}, Age: {1}", peep.Key, peep.Value);
}
var studentData = new Dictionary <string, string>();
studentData["name"] = "Fred";
studentData["age"] = "20";
studentData["hometown"] = "Seattle";
studentData["favorite_food"] = "Pizza";
Console.WriteLine("This is {0}", studentData["name"]);
Console.WriteLine("They are {0} years old", studentData["age"]);
Console.WriteLine("from {0}", studentData["hometown"]);
Console.WriteLine("and their favorite food is {0}", studentData["favorite_food"]);
var students = new Dictionary <string, Dictionary <string, string> >();
students["Fred"] = new Dictionary <string, string>();
students["Fred"].Add("name", "Fred");
students["Fred"].Add("age", "20");
students["Fred"].Add("hometown", "Seattle");
students["Fred"].Add("favorite_food", "Pizza");
Console.WriteLine("This is {0}", students["Fred"]["name"]);
var students2 = new Dictionary <string, Student>();
var someStudent = new Student("Fred", 20, "Seattle", "Pizza");
students2.Add("Fred", someStudent);
var anotherStudent = new Student("Sally", 21, "Columbus", "Pasta");
students2.Add("Sally", anotherStudent);
var studentWithNoData = new Student();
var sedan = new Car("blue", 4);
sedan.Start();
sedan.Stop();
sedan.Drive();
Console.WriteLine("Car color: {0}", sedan.Color);
Console.WriteLine("Number of Doors: {0}", sedan.NumberOfDoors);
var coup = new Car("red", 2);
var compact = new Car("blue");
Car.Compare(sedan, new Car());
int maxDoors = Car.MAX_DOORS;
coup.Type = CarType.SPORTY;
coup.NumberOfDoors = 4;
if (coup == sedan)
{
Console.WriteLine("not sure how, but a coup and sedan are the same?");
}
if (coup.Equals(sedan))
{
Console.WriteLine("");
}
Console.WriteLine(coup.ToString());
var vehicle = new Vehicle();
var genericAnimal = new Animal(0, "amoeba");
genericAnimal.Announce();
var bear = new Bear(1, "Yogi", 9999);
bear.Announce();
var vehicles = new List <Vehicle>();
vehicles.Add(new Truck());
vehicles.Add(sedan);
vehicles.Add(coup);
vehicles.Add(compact);
var vehicles2 = new List <IVehicle>();
var rallyCar = new RallyCar();
vehicles2.Add(new Truck());
vehicles2.Add(new Motorcycle());
vehicles2.Add(sedan);
vehicles2.Add(coup);
vehicles2.Add(compact);
vehicles2.Add(rallyCar);
var crossOver = new CrossOver();
// this won't work, because crossover doesn't implement
// the IVehicle interface
//vehicles2.Add(crossOver);
foreach (var v in vehicles2)
{
v.Accelerate(10);
}
Drive(rallyCar);
Drive(sedan);
Drive(new Truck());
var pupil = new Student("John Smith", 19, "Columbus", "Pizza");
var teacher = new Teacher("Jane Doe", 31);
PrintInfo(pupil);
PrintInfo(teacher);
// Page 21 in interfaces and extension methods example
Console.WriteLine("-----------------------");
}
static void Main(string[] args)
{
Console.Write("Enter a Number: ");
string userInput = Console.ReadLine();
Console.WriteLine("Your Number is: {0}", userInput);
var dictionary = new Dictionary <string, string>();
dictionary["apple"] = "A fruit or a computer company";
Console.WriteLine(dictionary["apple"]);
var someList = new List <int>();
someList.Add(1);
someList.Add(2);
someList.Add(3);
someList.Add(5);
someList.Add(8);
someList.Add(11);
someList.RemoveAt(0);
someList.RemoveAt(2);
for (int i = 0; i < someList.Count; i++)
{
Console.WriteLine(someList[i]);
}
foreach (int number in someList)
{
Console.WriteLine(number);
}
someList.ForEach(number => Console.WriteLine(number));
someList.ForEach(Console.WriteLine);
string[] names = { "John", "Daryl", "Mike", "Sarah", "Michele" };
string[] moreNames = new string[5];
moreNames[0] = "John";
moreNames[1] = "Daryl";
Console.WriteLine("Size of names: {0}\nSize of moreNames: {1}", names.Length, moreNames.Length);
// and so on
string student = "John Smith";
char firstCharacter = student[1];
// ---- Exercise for loops ----
var animals = new List <string>();
animals.Add("Lion");
animals.Add("Tiger");
animals.Add("Bird");
animals.Add("Cat");
animals.Add("Dog");
animals.Add("Leopard");
string favoriteAnimal = "Bird";
foreach (string animal in animals)
{
Console.WriteLine(animal);
}
if (animals.Contains(favoriteAnimal))
{
Console.WriteLine("I love {0} and also every other animal, including {1}", favoriteAnimal, animals[2]);
// same as the above line, but without the placeholder
Console.WriteLine("I love " + favoriteAnimal + "and also every other animal, including " + animals[2]);
}
else
{
Console.WriteLine("No, I don't care for those");
}
// dictionary looping
var person = new Dictionary <string, int>();
person.Add("Joan", 22);
person.Add("Daniel", 42);
person.Add("Anna", 34);
// person = {Joan=22, Daniel=42, Anna=34}
// loop through the hash map and return each key/value pair
for (int i = 0; i < person.Count; i++)
{
Console.WriteLine("Key: {0}, Value: {1}",
person.Keys.ElementAt(i),
person[person.Keys.ElementAt(i)]);
}
foreach (var peep in person)
{
// print out the key (their name) and their value
Console.WriteLine("Name: {0}, Age: {1}", peep.Key, peep.Value);
}
var studentData = new Dictionary <string, string>();
studentData["name"] = "Fred";
studentData["age"] = "20";
studentData["hometown"] = "Seattle";
studentData["favorite_food"] = "Pizza";
Console.WriteLine("This is {0}", studentData["name"]);
Console.WriteLine("They are {0} years old", studentData["age"]);
Console.WriteLine("from {0}", studentData["hometown"]);
Console.WriteLine("and their favorite food is {0}", studentData["favorite_food"]);
var students = new Dictionary <string, Dictionary <string, string> >();
students["Fred"] = new Dictionary <string, string>();
students["Fred"].Add("name", "Fred");
students["Fred"].Add("age", "20");
students["Fred"].Add("hometown", "Seattle");
students["Fred"].Add("favorite_food", "Pizza");
Console.WriteLine("This is {0}", students["Fred"]["name"]);
var students2 = new Dictionary <string, Student>();
var someStudent = new Student("Fred", 20, "Seattle", "Pizza");
students2.Add("Fred", someStudent);
var anotherStudent = new Student("Sally", 21, "Columbus", "Pasta");
students2.Add("Sally", anotherStudent);
var studentWithNoData = new Student();
var sedan = new Car("blue", 4);
sedan.Start();
sedan.Stop();
sedan.Drive();
Console.WriteLine("Car color: {0}", sedan.Color);
Console.WriteLine("Number of Doors: {0}", sedan.NumberOfDoors);
var coup = new Car("red", 2);
var compact = new Car("blue");
Car.Compare(sedan, new Car());
int maxDoors = Car.MAX_DOORS;
coup.Type = CarType.SPORTY;
coup.NumberOfDoors = 4;
if (coup == sedan)
{
Console.WriteLine("not sure how, but a coup and sedan are the same?");
}
if (coup.Equals(sedan))
{
Console.WriteLine("");
}
Console.WriteLine(coup.ToString());
var vehicle = new Vehicle();
var genericAnimal = new Animal(0, "amoeba");
genericAnimal.Announce();
var bear = new Bear(1, "Yogi", 9999);
bear.Announce();
var vehicles = new List <Vehicle>();
vehicles.Add(new Truck());
vehicles.Add(sedan);
vehicles.Add(coup);
vehicles.Add(compact);
var vehicles2 = new List <IVehicle>();
var rallyCar = new RallyCar();
vehicles2.Add(new Truck());
vehicles2.Add(new Motorcycle());
vehicles2.Add(sedan);
vehicles2.Add(coup);
vehicles2.Add(compact);
vehicles2.Add(rallyCar);
var crossOver = new CrossOver();
// this won't work, because crossover doesn't implement
// the IVehicle interface
//vehicles2.Add(crossOver);
foreach (var v in vehicles2)
{
v.Accelerate(10);
}
Drive(rallyCar);
Drive(sedan);
Drive(new Truck());
var pupil = new Student("John Smith", 19, "Columbus", "Pizza");
var teacher = new Teacher("Jane Doe", 31);
PrintInfo(pupil);
PrintInfo(teacher);
// Page 21 in interfaces and extension methods example
Console.WriteLine("-----------------------");
var dbMigrator = new DbMigrator(new ConsoleLogger());
var dbMigrator2 = new DbMigrator(new FileLogger("migrator.log"));
dbMigrator.Migrate();
dbMigrator2.Migrate();
Console.WriteLine("-----------------------");
// event stuff (week 6 day 2)
ProcessBusinessLogic bl = new ProcessBusinessLogic();
bl.ProcessCompleted += bl_ProcessCompleted; // register with an event
bl.ProcessCompleted += bl_ProcessUpdated;
bl.StartProcess();
var myProcess = new PhotoProcessor();
var filters = new PhotoFilters();
Action <Photo> filterHandler = filters.ApplyContrast;
filterHandler += filters.ApplyBrightness;
filterHandler += RemoveRedEyeFilter;
myProcess.Process("pic.jpg", filterHandler);
// lambda function takes in a number and then squares it
Func <int, int> squareFunction = num => num * num;
// in our case, it passes in 3 and returns 9
Console.WriteLine(squareFunction(3));
const int factor = 5;
Func <int, int> multiplier = num => num * factor;
int result = multiplier(10);
Console.WriteLine(multiplier(6));
Console.WriteLine(result);
Func <int, int, int, double> pythagoreanTheorem
= (a, b, c) => Math.Pow(a, 2) + Math.Pow(b, 2) + Math.Pow(c, 2);
double result2 = pythagoreanTheorem(1, 2, 3);
Console.WriteLine(pythagoreanTheorem(2, 3, 4));
Console.WriteLine(result2);
var library = new BookRepository();
List <Book> books = library.Books;
List <Book> cheapBooks = books.FindAll(book => book.Price < 10);
foreach (var book in cheapBooks)
{
Console.WriteLine(book.Title);
}
Console.ReadKey();
}