import joblib
import numpy as np

cache_file = "dataset_cache/training_data_2d.joblib"
data = joblib.load(cache_file)
X = np.array(data['X'])
y = np.array(data['y'])

print("X shape:", X.shape)
print("X mean:", np.mean(X))
print("X std:", np.std(X))
print("X min:", np.min(X))
print("X max:", np.max(X))
print("Any NaN:", np.isnan(X).any())

for i in range(6):
    print(f"Channel {i} mean: {np.mean(X[:, i, :, :]):.4f}, min: {np.min(X[:, i, :, :]):.4f}, max: {np.max(X[:, i, :, :]):.4f}")