static void test_gaussian()
{
int rows = 32;
int cols = 48;
array<float, 2> means;
means[0] = rows / 2.0f;
means[1] = cols / 2.0f;
array<float, 2> std_devs;
std_devs[0] = 3.14f;
std_devs[1] = 2.7f;
internal::GaussianGenerator<float, Eigen::DenseIndex, 2> gaussian_gen(means, std_devs);
Tensor<float, 2> matrix(rows, cols);
Tensor<float, 2> result = matrix.generate(gaussian_gen);
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
float g_rows = powf(rows/2.0f - i, 2) / (3.14f * 3.14f) * 0.5f;
float g_cols = powf(cols/2.0f - j, 2) / (2.7f * 2.7f) * 0.5f;
float gaussian = expf(-g_rows - g_cols);
VERIFY_IS_EQUAL(result(i, j), gaussian);
}
}
}
void gmm_gen(const gsl_rng* rng, const gmm_t* gmm,
gsl_vector* result) {
size_t i = discrete_gen(rng, gmm->weight);
gaussian_gen(rng, gmm->comp[i], result);
}
