qiskit.ignis.mitigation.TensoredMeasFitter
class TensoredMeasFitter(results, mit_pattern, substate_labels_list=None, circlabel='')
Measurement correction fitter for a tensored calibration.
Initialize a measurement calibration matrix from the results of running the circuits returned by measurement_calibration_circuits.
Parameters
- results (
Union[Result,List[Result]]) – the results of running the measurement calibration circuits. If this is None, the user will set calibration matrices later. - mit_pattern (
List[List[int]]) – qubits to perform the measurement correction on, divided to groups according to tensors - substate_labels_list (
Optional[List[List[str]]]) – for each calibration matrix, the labels of its rows and columns. If None, the labels are ordered lexicographically - circlabel (
str) – if the qubits were labeled
Raises
ValueError – if the mit_pattern doesn’t match the substate_labels_list
__init__
__init__(results, mit_pattern, substate_labels_list=None, circlabel='')
Initialize a measurement calibration matrix from the results of running the circuits returned by measurement_calibration_circuits.
Parameters
- results (
Union[Result,List[Result]]) – the results of running the measurement calibration circuits. If this is None, the user will set calibration matrices later. - mit_pattern (
List[List[int]]) – qubits to perform the measurement correction on, divided to groups according to tensors - substate_labels_list (
Optional[List[List[str]]]) – for each calibration matrix, the labels of its rows and columns. If None, the labels are ordered lexicographically - circlabel (
str) – if the qubits were labeled
Raises
ValueError – if the mit_pattern doesn’t match the substate_labels_list
Methods
__init__(results, mit_pattern[, …]) | Initialize a measurement calibration matrix from the results of running the circuits returned by measurement_calibration_circuits. |
add_data(new_results[, rebuild_cal_matrix]) | Add measurement calibration data |
plot_calibration([cal_index, ax, show_plot]) | Plot one of the calibration matrices (2D color grid plot). |
readout_fidelity([cal_index, label_list]) | Based on the results, output the readout fidelity, which is the average of the diagonal entries in the calibration matrices. |
Attributes
cal_matrices | Return cal_matrices. |
filter | Return a measurement filter using the cal matrices. |
nqubits | Return _qubit_list_sizes. |
substate_labels_list | Return _substate_labels_list. |
add_data
add_data(new_results, rebuild_cal_matrix=True)
Add measurement calibration data
Parameters
- new_results (list or qiskit.result.Result) – a single result or list of Result objects.
- rebuild_cal_matrix (bool) – rebuild the calibration matrix
cal_matrices
Return cal_matrices.
filter
Return a measurement filter using the cal matrices.
nqubits
Return _qubit_list_sizes.
plot_calibration
plot_calibration(cal_index=0, ax=None, show_plot=True)
Plot one of the calibration matrices (2D color grid plot).
Parameters
- cal_index (integer) – calibration matrix to plot
- ax (matplotlib.axes) – settings for the graph
- show_plot (bool) – call plt.show()
Raises
- QiskitError – if _cal_matrices was not set.
- ImportError – if matplotlib was not installed.
readout_fidelity
readout_fidelity(cal_index=0, label_list=None)
Based on the results, output the readout fidelity, which is the average of the diagonal entries in the calibration matrices.
Parameters
- cal_index (integer) – readout fidelity for this index in _cal_matrices
- label_list (list) – Returns the average fidelity over of the groups f states. In the form of a list of lists of states. If None, then each state used in the construction of the calibration matrices forms a group of size 1
Returns
The readout fidelity (assignment fidelity)
Return type
numpy.array
Raises
QiskitError – If the calibration matrix has not been set for the object.
Additional Information:
The on-diagonal elements of the calibration matrices are the probabilities of measuring state ‘x’ given preparation of state ‘x’.
substate_labels_list
Return _substate_labels_list.