cellular encoding

src/NeuralNetwork/ConstructiveAlgorithms/CellularEncoding/Cell.cpp

@@ -0,0 +1,12 @@
+#include <NeuralNetwork/ConstructiveAlgorithms/CelularEncoding/Cell.h>
+#include <NeuralNetwork/ConstructiveAlgorithms/CelularEncoding/CelularEncoding.h>
+
+void NeuralNetworks::ConstructiveAlgorithms::CelularEncoding::Cell::step(CelularEncoding &c) {
+	if(isAlive()) {
+		reinterpret_cast<Instruction::Instruction *>(codePtr->instruction.lock().get())->run(*this, c, codePtr->parameters);
+	}
+
+	if(codePtr == nullptr) {
+		die();
+	}
+}

src/NeuralNetwork/ConstructiveAlgorithms/CellularEncoding/CellularEncoding.cpp

@@ -0,0 +1,20 @@
+#include <NeuralNetwork/ConstructiveAlgorithms/CelularEncoding/CelularEncoding.h>
+
+std::size_t NeuralNetworks::ConstructiveAlgorithms::CelularEncoding::CelularEncoding::step() {
+	std::size_t activeCellCount = 0;
+	std::vector<std::size_t> processingOrder(_processingOrder);
+	for(std::size_t i = 0; i < processingOrder.size(); i++) {
+		std::size_t cell = processingOrder[i];
+		if(cells[cell]->isAlive()) {
+			currentID = cells[cell]->getID();
+			cells[cell]->step(*this);
+			activeCellCount++;
+		} else {
+			auto iter = std::find(_processingOrder.begin(), _processingOrder.end(), cell);
+			if(iter != _processingOrder.end()) {
+				_processingOrder.erase(iter);
+			}
+		}
+	}
+	return activeCellCount;
+}