Пример #1
0
// Function that runs the Barnes-Hut implementation of t-SNE
int main() {

    // Define some variables
	int origN, N, D, no_dims, *landmarks;
	double perc_landmarks;
	double perplexity, theta, *data;
    int rand_seed = -1;
    TSNE* tsne = new TSNE();

    // Read the parameters and the dataset
	if(tsne->load_data(&data, &origN, &D, &no_dims, &theta, &perplexity, &rand_seed)) {

		// Make dummy landmarks
        N = origN;
        int* landmarks = (int*) malloc(N * sizeof(int));
        if(landmarks == NULL) { printf("Memory allocation failed!\n"); exit(1); }
        for(int n = 0; n < N; n++) landmarks[n] = n;

		// Now fire up the SNE implementation
		double* Y = (double*) malloc(N * no_dims * sizeof(double));
		double* costs = (double*) calloc(N, sizeof(double));
        if(Y == NULL || costs == NULL) { printf("Memory allocation failed!\n"); exit(1); }
		tsne->run(data, N, D, Y, no_dims, perplexity, theta, rand_seed, false);

		// Save the results
		tsne->save_data(Y, landmarks, costs, N, no_dims);

        // Clean up the memory
		free(data); data = NULL;
		free(Y); Y = NULL;
		free(costs); costs = NULL;
		free(landmarks); landmarks = NULL;
    }
    delete(tsne);
}
Пример #2
0
// Function that runs the Barnes-Hut implementation of t-SNE
int main() {

	// Define some variables
	int origN, N, D, no_dims, iterations, *landmarks;
	double perc_landmarks;
	double perplexity, theta, eta, *data;
	float gpu_mem;
	int verbose;
	int rand_seed = -1;
	int seed = 0;
	TSNE* tsne = new TSNE();

	time_t start = clock();
	// Read the parameters and the dataset
	if (tsne->load_data(&data, &origN, &D, &no_dims, &theta, &perplexity, &eta, &iterations, &seed, &gpu_mem, &verbose, &rand_seed)) {

		// Set random seed
		if (rand_seed >= 0) {
			if (verbose > 0) printf("Using random seed: %d\n", rand_seed);
			srand((unsigned int)rand_seed);
		}
		else {
			if (verbose > 0) printf("Using current time as random seed...\n");
			srand(time(NULL));
		}

		// Make dummy landmarks
		N = origN;
		int* landmarks = (int*)malloc(N * sizeof(int));
		if (landmarks == NULL) { printf("Memory allocation failed!\n"); exit(1); }
		for (int n = 0; n < N; n++) landmarks[n] = n;

		// Now fire up the SNE implementation
		double* Y = (double*)malloc(N * no_dims * sizeof(double));
		double* costs = (double*)calloc(N, sizeof(double));
		if (Y == NULL || costs == NULL) { printf("Memory allocation failed!\n"); exit(1); }

		tsne->zeroMean(data, N, D);
		tsne->normalize(data, N, D);
		if (seed == 0){
			seed = origN;
		}
		tsne->runWithCenterOfMass(data, Y, origN, seed, D, no_dims, perplexity, theta, eta, iterations, gpu_mem, verbose);

		// Save the results
		tsne->save_data(Y, landmarks, costs, N, no_dims, verbose);

		// Clean up the memory
		free(data); data = NULL;
		free(Y); Y = NULL;
		free(costs); costs = NULL;
		free(landmarks); landmarks = NULL;
	}
	delete(tsne);
	time_t end = clock();
	if (verbose > 0) printf("T-sne required %f seconds (%f minutes) to run\n", float(end - start) / CLOCKS_PER_SEC, float(end - start) / (60 * CLOCKS_PER_SEC));

}
Пример #3
0
// Function that runs the Barnes-Hut implementation of t-SNE
int main(int argc, char** argv) {
  int metrics = 0;
  if (argc > 1) {
    if (!strcmp(argv[1], "1")) metrics = 1;
  }

  // Define some variables
  int origN, N, D, no_dims = 2, *landmarks;
  double perc_landmarks;
  double perplexity, theta, *data;
  TSNE* tsne = new TSNE();
  
  // Read the parameters and the dataset
  if(tsne->load_data(&data, &origN, &D, &theta, &perplexity)) {
    
    // Make dummy landmarks
    N = origN;
    int* landmarks = (int*) malloc(N * sizeof(int));
    if(landmarks == NULL) { printf("Memory allocation failed!\n"); exit(1); }
    for(int n = 0; n < N; n++) landmarks[n] = n;
    
    // Now fire up the SNE implementation
    double* Y = (double*) malloc(N * no_dims * sizeof(double));
    double* costs = (double*) calloc(N, sizeof(double));
    if(Y == NULL || costs == NULL) { printf("Memory allocation failed!\n"); exit(1); }
    double (*metric_func) (const DataPoint&, const DataPoint&);
    switch (metrics) {
    case 1: metric_func = log_cosine_distance; printf("Using %s As Distance Metrics.\n", "Log-Cosine-Similarity"); break;
    default: metric_func = euclidean_distance; printf("Using %s As Distance Metrics.\n", "Euclidean-Distance"); break;
    }
    tsne->run(data, N, D, Y, no_dims, perplexity, theta, metric_func);
    
    // Save the results
    tsne->save_data(Y, landmarks, costs, N, no_dims);
    
    // Clean up the memory
    free(data); data = NULL;
    free(Y); Y = NULL;
    free(costs); costs = NULL;
    free(landmarks); landmarks = NULL;
  }
  delete(tsne);
}