def _compute_eigenvalues()

in src/braket/default_simulator/observables.py [0:0]

• 16 lines of code
• 10 McCabe index (conditional complexity)

    def _compute_eigenvalues(factors: List[Observable], qubits: Tuple[int, ...]) -> np.ndarray:
        # Check if there are any non-standard observables, namely Hermitian and Identity
        if any({not observable.is_standard for observable in factors}):
            # Tensor product of observables contains a mixture
            # of standard and nonstandard observables
            factors_sorted = sorted(factors, key=lambda x: x.measured_qubits)
            eigenvalues = np.ones(1)
            for is_standard, group in itertools.groupby(factors_sorted, lambda x: x.is_standard):
                # Group observables by whether or not they are standard
                group_eigenvalues = (
                    # `group` contains only standard observables, so eigenvalues
                    # are simply Pauli eigenvalues
                    pauli_eigenvalues(len(list(group)))
                    if is_standard
                    # `group` contains only nonstandard observables, so eigenvalues
                    # must be calculated
                    else functools.reduce(
                        np.kron, tuple(nonstandard.eigenvalues for nonstandard in group)
                    )
                )
                eigenvalues = np.kron(eigenvalues, group_eigenvalues)
        else:
            eigenvalues = pauli_eigenvalues(len(qubits))

        return eigenvalues