72 lines
2 KiB
C
72 lines
2 KiB
C
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#include <cx.h>
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#include <neural.h>
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Neural_Network *
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neural_new(size_t layer_size, size_t layers) {
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Neural_Network *self = malloc(sizeof(Neural_Network));
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Neuron *n = NULL;
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self->layer_size = layer_size;
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self->layers = layers;
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self->n = calloc(layer_size*layers, sizeof(Neuron));
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for (int j = 0; j < layers; j++) {
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n = &(self->n[j*layer_size]);
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for (int i = 0; i < layers; i++) {
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n->value = 0;
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n->threshold = 0;
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if (j) {
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n->in_values = calloc(layer_size, sizeof(float *));
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n->weights = calloc(layer_size, sizeof(float));
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n->in_values_size = layer_size;
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for (int k = 0; k < layer_size; k++) {
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n->in_values[k] = &(self->n[(j-1)*layer_size + k].value);
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n->weights[k] = 0.5;
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}
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}
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else {
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n->in_values = NULL;
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n->weights = NULL;
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}
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}
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}
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return self;
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}
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void
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neural_randomize(Neural_Network *self) {
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// Does not randomize, just sets 0.5, but it doesn't matter for now.
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for (int i = 0; i < self->layers; i++) {
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Neuron *n = &(self->n[i*self->layer_size]);
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for (int j = 0; j < self->layer_size; j++) {
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n[j].threshold = 0.5;
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}
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}
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}
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float *
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neural_process(Neural_Network *self, float *input) {
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float *retval = NULL;
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for (int i = 0; i < self->layer_size; i++) {
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self->n[i].value = input[i];
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}
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for (int i = 1; i < self->layers; i++) {
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float dot_prod = 0;
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for (int j = 0; j < self->layer_size; j++) {
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// MATH GOES BRRRRRRRR
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dot_prod += *(self->n[i*self->layer_size + j].in_values)[j] *
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self->n[i*self->layer_size + j].weights[j];
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}
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}
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retval = malloc(self->layer_size * sizeof(float));
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for (int i = 0; i < self->layer_size; i++) {
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retval[i] = self->n[self->layer_size*(self->layers-1)].value;
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}
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return retval;
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}
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