#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "randomness.h"
#include "neurons.h"
#include "activations.h"

Weight *init_weight_list(int n_weights)
{
    Weight *first, *last;
    int i;
    for(i=1 ; i<=n_weights ; i++)
    {
        Weight *current = (Weight*)malloc(sizeof(Weight));
        current->value = random_float(0.0 , 1.0);
        current->next = NULL;
        if(i==1)
        {
            first = current;
            last = current;
        }else
        {
            last->next = current;
            last = current;
        }
    }
    return first;
}

Neuron *init_neuron(int n_weights, char *activation_function)
{
    Neuron *neuron = (Neuron*)malloc(sizeof(Neuron));
    if(n_weights == 0)
    {
        neuron->weights = NULL;
    }else
    {
        neuron->weights = init_weight_list(n_weights);
    }
    neuron->output = 0.0;
    if(strcmp(activation_function, "sigmoid") == 0)
    {
        neuron->activation = sigmoid;
        neuron->activation_derivative = sigmoid_derivative;
        neuron->bias = 1.0;
    }
    else if(strcmp(activation_function, "tanh") == 0)
    {
        neuron->activation = tan_hyp;
        neuron->activation_derivative = tan_hyp_derivative;
        neuron->bias = 1.0;
    }else if(strcmp(activation_function, "linear") == 0)
    {
        neuron->activation = linear;
        neuron->activation_derivative = linear_derivative;
        neuron->bias = 1.0;
    }
    else //relu is assumed as default activation function
    {
        neuron->activation = relu;
        neuron->activation_derivative = relu_derivative;
        neuron->bias = 0.1; //as suggested by scientific articles (advice of setting bias to 0.1 when using ReLU and 1.0 with other functions)
    }
    neuron->delta_error = 0.0;
    neuron->same_layer_next_neuron = NULL;

    return neuron;
}

void destroy_neuron(Neuron *neuron)
{
    Weight *temp = NULL;
    while(neuron->weights != NULL)
    {
        temp = neuron->weights;
        neuron->weights = neuron->weights->next;
        free(temp);
    }
    if(neuron != NULL)
    {
        free(neuron);
    }
}