def tomography_data(results, name, tomoset):
    '\n    Return a results dict for a state or process tomography experiment.\n\n    Args:\n        results (Result): Results from execution of a process tomography\n            circuits on a backend.\n        name (string): The name of the circuit being reconstructed.\n        tomoset (tomography_set): the dict of tomography configurations.\n\n    Returns:\n        list: A list of dicts for the outcome of each process tomography\n        measurement circuit.\n    '
    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.
def tomography_data(results, name, tomoset):
    '\n    Return a results dict for a state or process tomography experiment.\n\n    Args:\n        results (Result): Results from execution of a process tomography\n            circuits on a backend.\n        name (string): The name of the circuit being reconstructed.\n        tomoset (tomography_set): the dict of tomography configurations.\n\n    Returns:\n        list: A list of dicts for the outcome of each process tomography\n        measurement circuit.\n    '
    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