def sample_measurement_ops(
            self,
            measurement_ops: List[ops.GateOperation],
            repetitions: int = 1) -> Dict[str, np.ndarray]:
        """Samples from the system at this point in the computation.

        Note that this does not collapse the wave function.

        In contrast to `sample` which samples qubits, this takes a list of
        `cirq.GateOperation` instances whose gates are `cirq.MeasurementGate`
        instances and then returns a mapping from the key in the measurement
        gate to the resulting bit strings. Different measurement operations must
        not act on the same qubits.

        Args:
            measurement_ops: `GateOperation` instances whose gates are
                `MeasurementGate` instances to be sampled form.
            repetitions: The number of samples to take.

        Returns: A dictionary from measurement gate key to measurement
            results. Measurement results are stored in a 2-dimensional
            numpy array, the first dimension corresponding to the repetition
            and the second to the actual boolean measurement results (ordered
            by the qubits being measured.)

        Raises:
            ValueError: If the operation's gates are not `MeasurementGate`
                instances or a qubit is acted upon multiple times by different
                operations from `measurement_ops`.
        """
        bounds = {}  # type: Dict[str, Tuple]
        all_qubits = []  # type: List[ops.Qid]
        current_index = 0
        for op in measurement_ops:
            gate = op.gate
            if not isinstance(gate, ops.MeasurementGate):
                raise ValueError('{} was not a MeasurementGate'.format(gate))
            key = protocols.measurement_key(gate)
            if key in bounds:
                raise ValueError(
                    'Duplicate MeasurementGate with key {}'.format(key))
            bounds[key] = (current_index, current_index + len(op.qubits))
            all_qubits.extend(op.qubits)
            current_index += len(op.qubits)
        indexed_sample = self.sample(all_qubits, repetitions)
        return {k: np.array([x[s:e] for x in indexed_sample]) for k, (s, e) in
                bounds.items()}