#include <NeuralNetwork/ActivationFunction/Heaviside.h>
#include <NeuralNetwork/ActivationFunction/Sigmoid.h>
#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
#include <NeuralNetwork/ActivationFunction/Linear.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) > 0.482407);
		assert(s(0.1) < 0.482607);

		assert(s(10) > 0.000901051);
		assert(s(10) < 0.000921051);
	}
	{
		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);
	}
	{
		NeuralNetwork::ActivationFunction::Linear s(1.0);
		assert(s(0.5) > 0.4999);
		assert(s(0.5) < 0.5001);

		assert(s(0.0) == 0.0);
	}
	{
		NeuralNetwork::ActivationFunction::Linear s(0.7);
		assert(s(0.0) == 0.0);

		assert(s(1.0) > 0.6999);
		assert(s(1.0) < 0.7001);
	}

	return 0;
}