# example_quantum.py

import numpy as np
from artifact import Artifact, bits, tensor, materialize_artifact, dag_node_count, dag_depth, ArtifactCache
from sid_hashers import SHA256SIDHash
from hashers import SHA256Hash

# ---------------------------------------------------------------------
# Hashers
# ---------------------------------------------------------------------
sid_hasher = SHA256SIDHash()
content_hasher = SHA256Hash()

# ---------------------------------------------------------------------
# Step 1: Create 8 quantum leaves (1 qubit each)
# We'll make simple |0> + |1> superposition for each qubit
# ---------------------------------------------------------------------
quantum_leaves = []
for i in range(8):
    indices = np.array([0, 1], dtype=np.int64)
    values = np.array([1+0j, 1+0j], dtype=np.complex128)
    leaf = Artifact(
        op="leaf.bits",
        params={"_materialized": (indices, values)},  # mandatory for materialization
        children=[],
        sid=f"qubit_{i}_superposition",
        materializer=materialize_artifact,
        content_hasher=content_hasher,
    )
    quantum_leaves.append(leaf)

# ---------------------------------------------------------------------
# Step 2: Tensor all 8 qubits together lazily
# ---------------------------------------------------------------------
# Tensor pairs recursively
def tensor_all(artifacts, sid_hasher):
    if len(artifacts) == 1:
        return artifacts[0]
    mid = len(artifacts) // 2
    left = tensor_all(artifacts[:mid], sid_hasher)
    right = tensor_all(artifacts[mid:], sid_hasher)
    return tensor(left, right, sid_hasher=sid_hasher)

quantum_8q = tensor_all(quantum_leaves, sid_hasher=sid_hasher)

print("8-qubit quantum tensor SID (lazy):")
print(quantum_8q.sid)

print("CID materialized yet?", quantum_8q.is_materialized)

# ---------------------------------------------------------------------
# Step 3: Materialize CID on demand
# ---------------------------------------------------------------------
cid_8q = quantum_8q.cid
print("\nAfter materialization:")
print("8-qubit quantum tensor CID:", cid_8q)

# ---------------------------------------------------------------------
# Step 4: DAG metrics
# ---------------------------------------------------------------------
print("\nDerivation DAG metrics:")
print("Total nodes:", dag_node_count(quantum_8q))
print("DAG depth:", dag_depth(quantum_8q))