I've already generated a filter for readout error mitigation:
cal_results = cal_job.result() meas_fitter = CompleteMeasFitter(cal_results, state_labels) fig, ax = plt.subplots(figsize=(10, 10)) meas_fitter.plot_calibration(ax) meas_filter = meas_fitter.filter
I have a set of circuits executed using the IBM job manager, the list is called
all_circuits. After transpling the list, I tried:
MExperiments = job_manager.run(all_circuits, backend=backend, shots = nshots) results = MExperiments.results() **mitigated_results = meas_filter.apply(results)**
I'm hoping to use the filter to mitigate the errors for each circuit in the list, but the last line doesn't quite work. It shows me
QiskitError: 'Unrecognized type for raw_data.'
How can I fix this issue? Thanks:)
PS: From the tutorial, there're 4 types of raw data that match the requirement:
Form1: A counts dictionary from results.get_counts,
Form2: A list of counts of length=len(state_labels),
Form3: A list of counts of length=M*len(state_labels) where M is an integer (e.g. for use with the tomography data),
Form4: A qiskit Result.
I'm not pretty sure why the
results in my code doesn't fit any one of them.