ReactivePredictor predicts the case of a reactive user

ReactivePredictor.go

func ReactivePredictor(memoryLength int, moves, wins types.Queue) float64 {
	stateMachine := make(floats.Slice, int(math.Pow(2, 2.*float64(memoryLength)-1.)))
	indMap := make(floats.Slice, 0)
	for i := 2 * memoryLength; i >= 0; i-- {
		indMap = append(indMap, math.Pow(2, float64(i)))
	}
	partOfMoves := moves.Array(moves.Length()-memoryLength, moves.Length()-1)
	partOfWins := wins.Array(wins.Length()-memoryLength-1, wins.Length()-1)
	lastState := append(partOfWins, partOfMoves...)
	lastStateInd := 0.
	for i := 0; i < len(lastState); i++ {
		if lastState[i] == 1 {
			lastStateInd += math.Pow(2., float64(i))
		}
	}
	lastStateResult := moves.Index(moves.Length() - 1)
	//update the state machine
	if stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] == 0 { //no prior info
		stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] = lastStateResult * 0.3
	} else if stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] == lastStateResult*0.3 { //we've been here before so strengthen prediction
		stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] = lastStateResult * 0.8
	} else if stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] == lastStateResult*0.8 { //we've been here before so strengthen prediction
		stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] = lastStateResult * 1
	} else if stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] == lastStateResult*1 { //maximum confidence
		stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] = lastStateResult * 1
	} else { //changed his mind - so go back to 0
		stateMachine[int(math.Mod(lastStateInd, float64(stateMachine.Length())))] = 0
	}
	// what is the current state
	currentPartOfMoves := moves.Array(moves.Length()-memoryLength, moves.Length()-1)

	currentPartOfWins := wins.Array(wins.Length()-memoryLength-1, wins.Length()-1)

	currentState := append(currentPartOfWins, currentPartOfMoves...)

	currentStateInd := 0.
	for i := 0; i < len(currentState); i++ {
		if currentState[i] == 1 {
			currentStateInd += math.Pow(2., float64(i))
		}
	}

	predictionAndScore := stateMachine[int(math.Mod(currentStateInd, float64(stateMachine.Length())))]
	//log.Info('last state %v', lastState, ', last ind ', lastStateInd, '    current state ', currentState, '  current ind ', currentStateInd, '    state machine: ', stateMachine)
	//log.Infof("ReactivePredictor PredictionAndScore: %f", predictionAndScore)
	return predictionAndScore
}