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Changed name case, code style.

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This commit is contained in:
Lewis Van Winkle
2016-02-11 14:38:42 -06:00
parent 2bbc1b146c
commit 99e4d6a0e1
8 changed files with 61 additions and 61 deletions
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34
genann.c
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@@ -75,7 +75,7 @@ double genann_act_threshold(double a) {
}
GENANN *genann_init(int inputs, int hidden_layers, int hidden, int outputs) {
genann *genann_init(int inputs, int hidden_layers, int hidden, int outputs) {
if (hidden_layers < 0) return 0;
if (inputs < 1) return 0;
if (outputs < 1) return 0;
@@ -89,8 +89,8 @@ GENANN *genann_init(int inputs, int hidden_layers, int hidden, int outputs) {
const int total_neurons = (inputs + hidden * hidden_layers + outputs);
/* Allocate extra size for weights, outputs, and deltas. */
const int size = sizeof(GENANN) + sizeof(double) * (total_weights + total_neurons + (total_neurons - inputs));
GENANN *ret = malloc(size);
const int size = sizeof(genann) + sizeof(double) * (total_weights + total_neurons + (total_neurons - inputs));
genann *ret = malloc(size);
if (!ret) return 0;
ret->inputs = inputs;
@@ -102,7 +102,7 @@ GENANN *genann_init(int inputs, int hidden_layers, int hidden, int outputs) {
ret->total_neurons = total_neurons;
/* Set pointers. */
ret->weight = (double*)((char*)ret + sizeof(GENANN));
ret->weight = (double*)((char*)ret + sizeof(genann));
ret->output = ret->weight + ret->total_weights;
ret->delta = ret->output + ret->total_neurons;
@@ -115,11 +115,11 @@ GENANN *genann_init(int inputs, int hidden_layers, int hidden, int outputs) {
}
GENANN *genann_read(FILE *in) {
genann *genann_read(FILE *in) {
int inputs, hidden_layers, hidden, outputs;
fscanf(in, "%d %d %d %d", &inputs, &hidden_layers, &hidden, &outputs);
GENANN *ann = genann_init(inputs, hidden_layers, hidden, outputs);
genann *ann = genann_init(inputs, hidden_layers, hidden, outputs);
int i;
for (i = 0; i < ann->total_weights; ++i) {
@@ -130,15 +130,15 @@ GENANN *genann_read(FILE *in) {
}
GENANN *genann_copy(GENANN const *ann) {
const int size = sizeof(GENANN) + sizeof(double) * (ann->total_weights + ann->total_neurons + (ann->total_neurons - ann->inputs));
GENANN *ret = malloc(size);
genann *genann_copy(genann const *ann) {
const int size = sizeof(genann) + sizeof(double) * (ann->total_weights + ann->total_neurons + (ann->total_neurons - ann->inputs));
genann *ret = malloc(size);
if (!ret) return 0;
memcpy(ret, ann, size);
/* Set pointers. */
ret->weight = (double*)((char*)ret + sizeof(GENANN));
ret->weight = (double*)((char*)ret + sizeof(genann));
ret->output = ret->weight + ret->total_weights;
ret->delta = ret->output + ret->total_neurons;
@@ -146,7 +146,7 @@ GENANN *genann_copy(GENANN const *ann) {
}
void genann_randomize(GENANN *ann) {
void genann_randomize(genann *ann) {
int i;
for (i = 0; i < ann->total_weights; ++i) {
double r = GENANN_RANDOM();
@@ -156,13 +156,13 @@ void genann_randomize(GENANN *ann) {
}
void genann_free(GENANN *ann) {
void genann_free(genann *ann) {
/* The weight, output, and delta pointers go to the same buffer. */
free(ann);
}
double const *genann_run(GENANN const *ann, double const *inputs) {
double const *genann_run(genann const *ann, double const *inputs) {
double const *w = ann->weight;
double *o = ann->output + ann->inputs;
double const *i = ann->output;
@@ -173,8 +173,8 @@ double const *genann_run(GENANN const *ann, double const *inputs) {
int h, j, k;
const GENANN_ACTFUN act = ann->activation_hidden;
const GENANN_ACTFUN acto = ann->activation_output;
const genann_actfun act = ann->activation_hidden;
const genann_actfun acto = ann->activation_output;
/* Figure hidden layers, if any. */
for (h = 0; h < ann->hidden_layers; ++h) {
@@ -217,7 +217,7 @@ double const *genann_run(GENANN const *ann, double const *inputs) {
}
void genann_train(GENANN const *ann, double const *inputs, double const *desired_outputs, double learning_rate) {
void genann_train(genann const *ann, double const *inputs, double const *desired_outputs, double learning_rate) {
/* To begin with, we must run the network forward. */
genann_run(ann, inputs);
@@ -334,7 +334,7 @@ void genann_train(GENANN const *ann, double const *inputs, double const *desired
}
void genann_write(GENANN const *ann, FILE *out) {
void genann_write(genann const *ann, FILE *out) {
fprintf(out, "%d %d %d %d", ann->inputs, ann->hidden_layers, ann->hidden, ann->outputs);
int i;