#include <../src/neurons/lif_discrete.h> #include #include #include #include #define N_TRAIN 500 #define N_TEST 100 #define PI 3.14159265358979323846 int main(void) { /* 1. Configure the reservoir */ double lif_cfg[] = {0.0, 1.0, 0.2, 0.5}; spires_reservoir_config cfg = { .num_neurons = 400, .num_inputs = 1, .num_outputs = 1, .spectral_radius = 0.95, .ei_ratio = 0.8, .input_strength = 0.1, .connectivity = 0.1, .dt = 1.0, .connectivity_type = SPIRES_CONN_RANDOM, .neuron_type = SPIRES_NEURON_LIF_DISCRETE, .neuron_params = lif_cfg, }; /* 2. Create the reservoir */ spires_reservoir *r = NULL; spires_status s = spires_reservoir_create(&cfg, &r); if (s != SPIRES_OK) { fprintf(stderr, "Failed to create reservoir: %d\n", s); return 1; } /* 3. Generate training data — predict sin(t+1) from sin(t) */ double input_train[N_TRAIN]; double target_train[N_TRAIN]; for (int i = 0; i < N_TRAIN; i++) { input_train[i] = sin(2.0 * PI * i / 50.0); target_train[i] = sin(2.0 * PI * (i + 1) / 50.0); } /* 4. Train with ridge regression */ s = spires_train_ridge(r, input_train, target_train, N_TRAIN, 1e-6); if (s != SPIRES_OK) { fprintf(stderr, "Training failed: %d\n", s); spires_reservoir_destroy(r); return 1; } /* 5. Generate test input */ double input_test[N_TEST]; for (int i = 0; i < N_TEST; i++) { input_test[i] = sin(2.0 * PI * (N_TRAIN + i) / 50.0); } /* 6. Run inference */ double *predictions = spires_run(r, input_test, N_TEST); if (!predictions) { fprintf(stderr, "Inference failed\n"); spires_reservoir_destroy(r); return 1; } /* 7. Print a few predictions vs. expected values */ printf("Step | Predicted | Expected\n"); printf("-----+-----------+---------\n"); for (int i = 0; i < 10; i++) { double expected = sin(2.0 * PI * (N_TRAIN + i + 1) / 50.0); printf("%4d | %+.5f | %+.5f\n", i, predictions[i], expected); } /* 8. Clean up */ free(predictions); spires_reservoir_destroy(r); return 0; }