Rename mutagen package to mutagens

Add docs for genetic package

neuralnetwork/genetic/genetic.go

@@ -35,12 +35,20 @@ import (
 	neuralnetwork "../neuralnetwork"
 )
 
+// Genetic package implements basic proncipals of genetic and natural selection mechanisms for
+// neuralnetwork.NeuralNetwork
+
+// PopulationConfig is structure that is used to specify population parameters
+// PopulationSize - size of population
+// SelectionSize - percentage of best individuals used for next generation
+// CrossbreedPart - percentage of weigts and biases used for crossbreed
 type PopulationConfig struct {
 	PopulationSize int
-	SelectionSize  float64 // 0..1 persentage of success individuals to be used as parents for population
-	CrossbreedPart float64 // 0..1 persentage of weights and biases to be exchanged beetween individuals while Crossbreed
+	SelectionSize  float64 // 0..1 percentage of success individuals to be used as parents for population
+	CrossbreedPart float64 // 0..1 percentage of weights and biases to be exchanged beetween individuals while Crossbreed
 }
 
+// Population is main class for genetic and natural selection of neuralnetwork.NeuralNetwork
 type Population struct {
 	populationConfig *PopulationConfig
 	Networks         []*neuralnetwork.NeuralNetwork
@@ -49,6 +57,8 @@ type Population struct {
 	etalonsCount     int
 }
 
+// NewPopulation is constructor of new Population with specified PopulationVerifier, Mutagen and PopulationConfig.
+// sizes parameter also specified neuralnetwork.NeuralNetwork layers configuration
 func NewPopulation(verifier PopulationVerifier, mutagen Mutagen, populationConfig PopulationConfig, sizes []int) (p *Population) {
 	if populationConfig.PopulationSize%2 != 0 {
 		return nil
@@ -77,6 +87,7 @@ func NewPopulation(verifier PopulationVerifier, mutagen Mutagen, populationConfi
 	return
 }
 
+// NaturalSelection invokes natural selection process for specified number of generation
 func (p *Population) NaturalSelection(generationCount int) {
 	for g := 0; g < generationCount; g++ {
 		p.crossbreedPopulation(p.verifier.Verify(p))

neuralnetwork/genetic/interface.go

@@ -27,15 +27,21 @@ package genetic
 
 import neuralnetwork "../neuralnetwork"
 
+// IndividalFitness used as output fitess of individual
+// Fitness - result of specific network in absolute numbers
+// Index - index of individual in population
 type IndividalFitness struct {
 	Fitness float64
 	Index   int
 }
 
+// PopulationVerifier is interface that used to get fitness results
+// of population
 type PopulationVerifier interface {
 	Verify(*Population) []*IndividalFitness
 }
 
+// Mutagen is interface that applies mutations to provided neuralnetwork.NeuralNetwork
 type Mutagen interface {
 	Mutate(network *neuralnetwork.NeuralNetwork)
 }

neuralnetwork/genetic/mutagen/dummymutagen.go → neuralnetwork/genetic/mutagens/dummymutagen.go

@@ -23,7 +23,7 @@
  * DEALINGS IN THE SOFTWARE.
  */
 
-package mutagen
+package mutagens
 
 import (
 	"math/rand"
@@ -32,11 +32,14 @@ import (
 	neuralnetwork "../../neuralnetwork"
 )
 
+// DummyMutagen is simple randomized mutagen
 type DummyMutagen struct {
 	chance        float64
 	mutationCount int
 }
 
+// NewDummyMutagen constructs DummyMutagen with specified mutation chance and
+// amount of mutations that should be applied per cycle
 func NewDummyMutagen(chance float64, mutationCount int) (dm *DummyMutagen) {
 	dm = &DummyMutagen{
 		chance:        chance,
@@ -45,6 +48,10 @@ func NewDummyMutagen(chance float64, mutationCount int) (dm *DummyMutagen) {
 	return
 }
 
+// Mutate implementaion of Mutagen inteface Mutate method
+// For DummyMutagen it gets pseudo-random number and validates if number in
+// chance bounds. After method applies randomized mutation for random weight
+// and bias in neuralnetwork.NeuralNetwork
 func (dm *DummyMutagen) Mutate(network *neuralnetwork.NeuralNetwork) {
 	rand.Seed(time.Now().UnixNano())
 	for l := 1; l < network.LayerCount; l++ {

snakesimulator/main.go

@@ -27,13 +27,13 @@ package main
 
 import (
 	genetic "../neuralnetwork/genetic"
-	mutagen "../neuralnetwork/genetic/mutagen"
+	mutagens "../neuralnetwork/genetic/mutagens"
 	snakesimulator "./snakesimulator"
 )
 
 func main() {
 	s := snakesimulator.NewSnakeSimulator(400)
 	s.StartServer()
-	p := genetic.NewPopulation(s, mutagen.NewDummyMutagen(1.0, 1), genetic.PopulationConfig{PopulationSize: 2000, SelectionSize: 0.01, CrossbreedPart: 0.5}, []int{24, 18, 18, 4})
+	p := genetic.NewPopulation(s, mutagens.NewDummyMutagen(1.0, 1), genetic.PopulationConfig{PopulationSize: 2000, SelectionSize: 0.01, CrossbreedPart: 0.5}, []int{24, 18, 18, 4})
 	p.NaturalSelection(5000)
 }