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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _simulate_mixture(self, op: ops.Operation, data: _StateAndBuffer, indices: List[int]) -> None: """Simulate an op that is a mixtures of unitaries."""

        probs, unitaries = zip(*protocols.mixture(op))
        # We work around numpy barfing on choosing from a list of
        # numpy arrays (which is not `one-dimensional`) by selecting
        # the index of the unitary.
        index = np.random.choice(range(len(unitaries)), p=probs)
        shape = (2,) * (2 * len(indices))
        unitary = unitaries[index].astype(self._dtype).reshape(shape)
        result = linalg.targeted_left_multiply(unitary, data.state, indices,
                                               out=data.buffer)
        data.buffer = data.state
        data.state = result