"""Smoke test: verify all 11 engines import and run on tiny synthetic data."""
import sys, os
sys.path.insert(0, os.path.dirname(__file__))
import numpy as np

# Generate tiny synthetic data
np.random.seed(42)
d, n = 20, 50
X = np.random.randn(n, d)

errors = []
total = 0
passed = 0

def test_engine(name, data, **kwargs):
    global total, passed
    total += 1
    try:
        import causalscale as cs
        model = cs.CausalDiscovery(data, method=name, **kwargs)
        model.fit(verbose=False)
        net = model.get_network()
        print(f"  [OK] {name}: {net.edge_count} edges, {net.time_s:.1f}s")
        passed += 1
        return True
    except Exception as e:
        print(f"  [FAIL] {name}: {str(e)[:120]}")
        errors.append((name, str(e)))
        return False

print("=== causalscale v3.3.0 Smoke Tests ===\n")

# Core engines
test_engine("dagma", X)
test_engine("cluster_aware", X)
test_engine("transformer", X)
test_engine("lowrank", X)

# Specialized engines
test_engine("multibatch", X, extra_data=[X + 0.1 * np.random.randn(n, d)])
test_engine("llm_prior", X)
test_engine("bayes_lowrank", X, n_bootstrap=5)
test_engine("sc_causal", X)
test_engine("ensemble", X)
test_engine("multimodal", X, extra_data=[X + 0.1 * np.random.randn(n, d)])

# Auto
test_engine("auto", X)

print(f"\n=== Results: {passed}/{total} passed ===")
if errors:
    print("\nFailures:")
    for name, err in errors:
        print(f"  {name}: {err[:200]}")

sys.exit(0 if passed == total else 1)