reffactored and recurrent implementation

tests/activation.cpp

@@ -0,0 +1,59 @@
+#include <NeuralNetwork/ActivationFunction/Heaviside.h>
+#include <NeuralNetwork/ActivationFunction/Sigmoid.h>
+#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
+
+#include <iostream>
+#include <cassert>
+#include <chrono>
+
+union {
+    __m128 v;    // SSE 4 x float vector
+    float a[4];  // scalar array of 4 floats
+} U;
+
+int main() {
+	{
+		NeuralNetwork::ActivationFunction::Heaviside h(1.0);
+		assert(h(0.2) == 0);
+		assert(h(1.2) == 1);
+	}
+
+	{
+		NeuralNetwork::ActivationFunction::Heaviside h(0.7);
+		assert(h(0.2) == 0);
+		assert(h(0.8) == 1);
+	}
+
+	{
+		NeuralNetwork::ActivationFunction::Sigmoid s(0.7);
+		assert(s(0.1) > 0.517483);
+		assert(s(0.1) < 0.51750);
+
+		assert(s(10) > 0.998989);
+		assert(s(10) < 0.999189);
+	}
+	{
+		NeuralNetwork::ActivationFunction::Sigmoid s(5);
+		assert(s(0.1) > 0.622359);
+		assert(s(0.1) < 0.622559);
+		
+		assert(s(0.7) > 0.970588);
+		assert(s(0.7) < 0.970788);
+	}
+	{
+		NeuralNetwork::ActivationFunction::Sigmoid s(0.7);
+		U.a[0]=0.1;
+		U.a[1]=10;
+		U.v=s(U.v);
+
+		assert(U.a[0] > 0.517483);
+		assert(U.a[0] < 0.51750);
+
+		assert(U.a[1] > 0.998989);
+		assert(U.a[1] < 0.999189);
+	}
+
+	std::cout << "OK" << std::endl;
+
+	return 0;
+}