qiskit/tools/qcvv/tomography.py
def tomography_data(results, name, tomoset):
    """
    Return a results dict for a state or process tomography experiment.

    Args:
        results (Result): Results from execution of a process tomography
            circuits on a backend.
        name (string): The name of the circuit being reconstructed.
        tomoset (tomography_set): the dict of tomography configurations.

    Returns:
        list: A list of dicts for the outcome of each process tomography
        measurement circuit.
    """

    labels = tomography_circuit_names(tomoset, name)
    circuits = tomoset['circuits']
    data = []
    prep = None
    for j, _ in enumerate(labels):
        counts = marginal_counts(results.get_counts(labels[j]),
                                 tomoset['qubits'])
        shots = sum(counts.values())
        meas = circuits[j]['meas']
        prep = circuits[j].get('prep', None)
        meas_qubits = sorted(meas.keys())
        if prep:
            prep_qubits = sorted(prep.keys())
        circuit = {}
        for c in counts.keys():
            circuit[c] = {}
            circuit[c]['meas'] = [(meas[meas_qubits[k]], int(c[-1 - k]))
                                  for k in range(len(meas_qubits))]
            if prep:
                circuit[c]['prep'] = [prep[prep_qubits[k]]
                                      for k in range(len(prep_qubits))]
        data.append({'counts': counts, 'shots': shots, 'circuit': circuit})

    ret = {'data': data, 'meas_basis': tomoset['meas_basis']}
    if prep:
        ret['prep_basis'] = tomoset['prep_basis']
    return ret
def tomography_data(results, name, tomoset):
    """
    Return a results dict for a state or process tomography experiment.

    Args:
        results (Result): Results from execution of a process tomography
            circuits on a backend.
        name (string): The name of the circuit being reconstructed.
        tomoset (tomography_set): the dict of tomography configurations.

    Returns:
        list: A list of dicts for the outcome of each process tomography
        measurement circuit.
    """

    labels = tomography_circuit_names(tomoset, name)
    circuits = tomoset['circuits']
    data = []
    prep = None
    for j, _ in enumerate(labels):
        counts = marginal_counts(results.get_counts(labels[j]),
                                 tomoset['qubits'])
        shots = sum(counts.values())
        meas = circuits[j]['meas']
        prep = circuits[j].get('prep', None)
        meas_qubits = sorted(meas.keys())
        if prep:
            prep_qubits = sorted(prep.keys())
        circuit = {}
        for c in counts.keys():
            circuit[c] = {}
            circuit[c]['meas'] = [(meas[meas_qubits[k]], int(c[-1 - k]))
                                  for k in range(len(meas_qubits))]
            if prep:
                circuit[c]['prep'] = [prep[prep_qubits[k]]
                                      for k in range(len(prep_qubits))]
        data.append({'counts': counts, 'shots': shots, 'circuit': circuit})

    ret = {'data': data, 'meas_basis': tomoset['meas_basis']}
    if prep:
        ret['prep_basis'] = tomoset['prep_basis']
    return ret
Return a results dict for a state or process tomography experiment.

    Args:
        results (Result): Results from execution of a process tomography
            circuits on a backend.
        name (string): The name of the circuit being reconstructed.
        tomoset (tomography_set): the dict of tomography configurations.

    Returns:
        list: A list of dicts for the outcome of each process tomography
        measurement circuit.