Matching syntax.

This commit is contained in:
Andru Liu
2024-10-08 21:21:43 -07:00
parent d10fcaabc8
commit a23276474f
2 changed files with 20 additions and 20 deletions
+17 -17
View File
@@ -3,10 +3,10 @@
/** /**
* @brief Constructor to initialize the RBF model. * @brief Constructor to initialize the RBF model.
*/ */
RBFModel::RBFModel(int numCenters, int inputDim, double sigma, bool randomCenters) RBFModel::RBFModel(int n_centers, int input_dim, double sigma, bool random_centers)
: numCenters(numCenters), inputDim(inputDim), sigma(sigma) { : n_centers(n_centers), input_dim(input_dim), sigma(sigma) {
centers = new double*[numCenters]; // Allocate memory for centers centers = new double*[n_centers]; // Allocate memory for centers
weights = new double[numCenters]; // Allocate memory for weights weights = new double[n_centers]; // Allocate memory for weights
// Check if memory allocation was successful // Check if memory allocation was successful
if (!centers || !weights) { if (!centers || !weights) {
@@ -15,14 +15,14 @@ RBFModel::RBFModel(int numCenters, int inputDim, double sigma, bool randomCenter
} }
// Initialize centers and weights // Initialize centers and weights
for (int i = 0; i < numCenters; ++i) { for (int i = 0; i < n_centers; ++i) {
centers[i] = new double[inputDim]; // Allocate memory for each center centers[i] = new double[input_dim]; // Allocate memory for each center
if (randomCenters) { if (random_centers) {
for (int j = 0; j < inputDim; ++j) { for (int j = 0; j < input_dim; ++j) {
centers[i][j] = static_cast<double>(rand()) / RAND_MAX; // Random centers centers[i][j] = static_cast<double>(rand()) / RAND_MAX; // Random centers
} }
} else { } else {
for (int j = 0; j < inputDim; ++j) { for (int j = 0; j < input_dim; ++j) {
centers[i][j] = static_cast<double>(i); // Fixed centers centers[i][j] = static_cast<double>(i); // Fixed centers
} }
} }
@@ -34,7 +34,7 @@ RBFModel::RBFModel(int numCenters, int inputDim, double sigma, bool randomCenter
* @brief Destructor to free allocated memory. * @brief Destructor to free allocated memory.
*/ */
RBFModel::~RBFModel() { RBFModel::~RBFModel() {
for (int i = 0; i < numCenters; ++i) { for (int i = 0; i < n_centers; ++i) {
delete[] centers[i]; // Free memory for each center inside centers delete[] centers[i]; // Free memory for each center inside centers
} }
delete[] centers; // Free memory for centers delete[] centers; // Free memory for centers
@@ -46,7 +46,7 @@ RBFModel::~RBFModel() {
*/ */
double RBFModel::gaussian(const double* input, const double* center) { double RBFModel::gaussian(const double* input, const double* center) {
double norm = 0.0; double norm = 0.0;
for (int i = 0; i < inputDim; ++i) { for (int i = 0; i < input_dim; ++i) {
norm += pow(input[i] - center[i], 2); norm += pow(input[i] - center[i], 2);
} }
return exp(-0.5 * norm / (sigma * sigma)); return exp(-0.5 * norm / (sigma * sigma));
@@ -57,7 +57,7 @@ double RBFModel::gaussian(const double* input, const double* center) {
*/ */
double RBFModel::predict(const double* input) { double RBFModel::predict(const double* input) {
double output = 0.0; double output = 0.0;
for (int i = 0; i < numCenters; ++i) { for (int i = 0; i < n_centers; ++i) {
output += weights[i] * gaussian(input, centers[i]); output += weights[i] * gaussian(input, centers[i]);
} }
return output; return output;
@@ -66,10 +66,10 @@ double RBFModel::predict(const double* input) {
/** /**
* @brief Adapt weights based on the error and learning rate. * @brief Adapt weights based on the error and learning rate.
*/ */
void RBFModel::adapt(double error, double learningRate, const double* input) { void RBFModel::adapt(double error, double learning_rate, const double* input) {
for (int i = 0; i < numCenters; ++i) { for (int i = 0; i < n_centers; ++i) {
double influence = gaussian(input, centers[i]); // Calculate influence based on input double influence = gaussian(input, centers[i]); // Calculate influence based on input
weights[i] += learningRate * error * influence; // Update weight based on error and influence weights[i] += learning_rate * error * influence; // Update weight based on error and influence
} }
} }
@@ -77,7 +77,7 @@ void RBFModel::adapt(double error, double learningRate, const double* input) {
* @brief Get the weight at a specific index. * @brief Get the weight at a specific index.
*/ */
double RBFModel::get_weight(int index) const { double RBFModel::get_weight(int index) const {
if (index < 0 || index >= numCenters) return 0.0; if (index < 0 || index >= n_centers) return 0.0;
return weights[index]; return weights[index];
} }
@@ -85,6 +85,6 @@ double RBFModel::get_weight(int index) const {
* @brief Set the weight at a specific index. * @brief Set the weight at a specific index.
*/ */
void RBFModel::set_weight(int index, double value) { void RBFModel::set_weight(int index, double value) {
if (index < 0 || index >= numCenters) return; if (index < 0 || index >= n_centers) return;
weights[index] = value; weights[index] = value;
} }
+3 -3
View File
@@ -21,12 +21,12 @@ public:
* of centers, input dimensions, and the spread (sigma) of the RBFs. * of centers, input dimensions, and the spread (sigma) of the RBFs.
* Random initialization of the centers can be turned off. * Random initialization of the centers can be turned off.
* *
* @param num_centers The number of radial basis function centers. * @param n_centers The number of radial basis function centers.
* @param input_dim The dimensionality of the input data. * @param input_dim The dimensionality of the input data.
* @param sigma The spread of the RBFs (default is 1.0). * @param sigma The spread of the RBFs (default is 1.0).
* @param random_centers Boolean to initialize centers randomly (default is true). * @param random_centers Boolean to initialize centers randomly (default is true).
*/ */
RBFModel(int num_centers, int input_dim, double sigma = 1.0, bool random_centers = true); RBFModel(int n_centers, int input_dim, double sigma = 1.0, bool random_centers = true);
/** /**
* @brief Destructor to free allocated memory. * @brief Destructor to free allocated memory.
@@ -69,7 +69,7 @@ public:
private: private:
double** centers; // 2D array for centers double** centers; // 2D array for centers
double* weights; // Array of weights double* weights; // Array of weights
int num_centers; // Number of RBF centers int n_centers; // Number of RBF centers
int input_dim; // Dimension of the input int input_dim; // Dimension of the input
double sigma; // Spread of the RBF double sigma; // Spread of the RBF