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#include <../src/neurons/lif_discrete.h>
#include <math.h>
#include <spires.h>
#include <stdio.h>
#include <stdlib.h>
#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;
}
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