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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 run_and_measure(self, program: Program, trials: int) -> Dict[int, np.ndarray]: """ Run the provided state preparation program and measure all qubits. This will measure all the qubits on this QuantumComputer, not just qubits that are used in the program. The returned data is a dictionary keyed by qubit index because qubits for a given QuantumComputer may be non-contiguous and non-zero-indexed. To turn this dictionary into a 2d numpy array of bitstrings, consider:: bitstring_array = np.vstack(bitstrings[q] for q in qc.qubits()).T bitstring_array.shape # (trials, len(qc.qubits())) .. note:: In contrast to :py:class:`QVMConnection.run_and_measure`, this method simulates noise correctly for noisy QVMs. However, this method is slower for ``trials > 1``. For faster noise-free simulation, consider :py:class:`WavefunctionSimulator.run_and_measure`. :param program: The state preparation program to run and then measure. :param trials: The number of times to run the program. :return: A dictionary keyed by qubit index where the corresponding value is a 1D array of measured bits. """

        program = program.copy()
        validate_supported_quil(program)
        ro = program.declare('ro', 'BIT', len(self.qubits()))
        for i, q in enumerate(self.qubits()):
            program.inst(MEASURE(q, ro[i]))
        program.wrap_in_numshots_loop(trials)
        executable = self.compile(program)
        bitstring_array = self.run(executable=executable)
        bitstring_dict = {}
        for i, q in enumerate(self.qubits()):
            bitstring_dict[q] = bitstring_array[:, i]
        return bitstring_dict