MeasurementFilter
class MeasurementFilter(cal_matrix, state_labels)
Bases: object
Measurement error mitigation filter.
Produced from a measurement calibration fitter and can be applied to data.
Initialize a measurement error mitigation filter using the cal_matrix from a measurement calibration fitter.
Parameters
- cal_matrix (
matrix) – the calibration matrix for applying the correction - state_labels (
list) – the states for the ordering of the cal matrix
Methods
apply
MeasurementFilter.apply(raw_data, method='least_squares')
Apply the calibration matrix to results.
Parameters
-
raw_data (dict or list) –
The data to be corrected. Can be in a number of forms:
Form 1: a counts dictionary from results.get_counts
Form 2: a list of counts of length==len(state_labels)
Form 3: a list of counts of length==M*len(state_labels) where M is an integer (e.g. for use with the tomography data)
Form 4: a qiskit Result
-
method (str) –
fitting method. If None, then least_squares is used.
pseudo_inverse: direct inversion of the A matrixleast_squares: constrained to have physical probabilities
Returns
The corrected data in the same form as raw_data
Return type
dict or list
Raises
QiskitError – if raw_data is not an integer multiple of the number of calibrated states.
Attributes
cal_matrix
Return cal_matrix.
state_labels
return the state label ordering of the cal matrix