9bbe253810
- CMakeLists.txt with libtorch, GoogleTest, GoogleBenchmark, OpenMP, pybind11 - Header files: config, controller, population, fitness, evolution, spectral, oscillation, telemetry, optimizer - Source implementations: controller (full micro-MLP forward pass, mutation, crossover), fitness (Welford's algorithm), oscillation (DFT), spectral (SVD rank), optimizer (sign-SGD stub) - Tests: controller, population, fitness, optimizer (Google Test) - Benchmarks: evolve throughput, optimizer step (Google Benchmark) - Examples: simple optimization, PyTorch/libtorch integration - Python extension: pybind11 bindings with setup.py - README with architecture diagram and build instructions
34 lines
844 B
C++
34 lines
844 B
C++
#include <gtest/gtest.h>
|
|
#include "fces/fitness.hpp"
|
|
|
|
using namespace fces;
|
|
|
|
TEST(RunningStatsTest, BasicUpdate) {
|
|
RunningStats stats;
|
|
stats.update(1.0f);
|
|
stats.update(2.0f);
|
|
stats.update(3.0f);
|
|
EXPECT_NEAR(stats.get_mean(), 2.0f, 1e-5f);
|
|
EXPECT_GT(stats.get_std(), 0.0f);
|
|
}
|
|
|
|
TEST(RunningStatsTest, ZScore) {
|
|
RunningStats stats;
|
|
for (int i = 0; i < 100; ++i) stats.update(static_cast<float>(i));
|
|
float z = stats.z_score(50.0f);
|
|
EXPECT_NEAR(z, 0.0f, 0.1f);
|
|
}
|
|
|
|
TEST(FitnessEngineTest, LossSignal) {
|
|
FitnessEngine engine;
|
|
float sig = engine.calculate_loss_signal(1.0f, 2.0f, "relative");
|
|
EXPECT_LT(sig, 0.0f); // Improving
|
|
}
|
|
|
|
TEST(FitnessEngineTest, KZMDamping) {
|
|
FitnessEngine engine(0.1f);
|
|
float d = engine.compute_kzm_damping(5.0f);
|
|
EXPECT_GT(d, 0.0f);
|
|
EXPECT_LT(d, 1.0f);
|
|
}
|