RB experiment #25
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RB experiment #25
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eliarbel
reviewed
Apr 13, 2021
yaelbh
reviewed
Apr 18, 2021
yaelbh
reviewed
Apr 18, 2021
yaelbh
reviewed
Apr 18, 2021
yaelbh
reviewed
Apr 18, 2021
yaelbh
reviewed
Apr 18, 2021
* Add CurveFitAnalysis class * Get outcome label from metadata * Fix import error message if no matplotlib * Add option for fitting means of batched data sets * Reorganize helper functions into separate file * Add curve_fit, multi_curve_fit, and plotting functions for xy data * Refactor example CurveFitAnalysis class to use library functions * Add curve fitting data * Remove CurveFitAnalysis class and leave as library functions * Linting * Clean up curve_fit_data * Remove unneeded check for meas level now that data processor function is an arg * Add optional kwargs for x and series metadata keys for extracting data * Run black * Add filters to curve fit data * Reorganize files * Move curve_fit_data and mutli_curve_fit_data to curve_fitting.py * Move other processing functions to `data_processing.py` * Remove unneeded init import * Initial review edits * Separate x and series data for multi curve fit Rename curve_fit_data to process_curve_data Rename multi_curve_fit_data to process_multi_curve_data * Allow passing p0, and bounds as dict to curve fit * Add sigma to mean_xy_data If sigma is provided the mean and variance is computed using inverse-variance weighting, otherwise it is computed as the sample mean and biased sample variance. * Set default absolute_sigma = True * Fix logical check on np array * Use reduced chi-squared calculation * fixup data processing * Fix error in level2_probabilities multiplying by shots instead of dividing * Add explicit method kwarg for mean_xy_data * Add basic tests for curve fitting * More review edits * Change chisq -> reduced_chisq in result and docs * add dof (degrees of freedom) to returned results * add documentation about sigma by default being absolute sigma. Co-authored-by: Helena Zhang <helena@astbb.com>
yaelbh
approved these changes
Apr 20, 2021
ShellyGarion
approved these changes
Apr 20, 2021
coruscating
approved these changes
Apr 20, 2021
paco-ri
pushed a commit
to paco-ri/qiskit-experiments
that referenced
this pull request
Jul 11, 2022
* RB experiment class based on Chris' draft * Unifying sampling procedures * Some more unification * Style * Style fixes * Analysis now works directly with curve_fit functions * Added plotting (ad-hoc solution for now) * Linting * Adding error bars to plots * fixed link in readme (qiskit-community#15) * Curve fitting analysis helper functions (qiskit-community#19) * Add CurveFitAnalysis class * Get outcome label from metadata * Fix import error message if no matplotlib * Add option for fitting means of batched data sets * Reorganize helper functions into separate file * Add curve_fit, multi_curve_fit, and plotting functions for xy data * Refactor example CurveFitAnalysis class to use library functions * Add curve fitting data * Remove CurveFitAnalysis class and leave as library functions * Linting * Clean up curve_fit_data * Remove unneeded check for meas level now that data processor function is an arg * Add optional kwargs for x and series metadata keys for extracting data * Run black * Add filters to curve fit data * Reorganize files * Move curve_fit_data and mutli_curve_fit_data to curve_fitting.py * Move other processing functions to `data_processing.py` * Remove unneeded init import * Initial review edits * Separate x and series data for multi curve fit Rename curve_fit_data to process_curve_data Rename multi_curve_fit_data to process_multi_curve_data * Allow passing p0, and bounds as dict to curve fit * Add sigma to mean_xy_data If sigma is provided the mean and variance is computed using inverse-variance weighting, otherwise it is computed as the sample mean and biased sample variance. * Set default absolute_sigma = True * Fix logical check on np array * Use reduced chi-squared calculation * fixup data processing * Fix error in level2_probabilities multiplying by shots instead of dividing * Add explicit method kwarg for mean_xy_data * Add basic tests for curve fitting * More review edits * Change chisq -> reduced_chisq in result and docs * add dof (degrees of freedom) to returned results * add documentation about sigma by default being absolute sigma. Co-authored-by: Helena Zhang <helena@astbb.com> * Example notebook * Linting and documentation * Some more linting * Small change * Linting Co-authored-by: Yael Ben-Haim <yaelbh@il.ibm.com> Co-authored-by: Christopher J. Wood <cjwood@us.ibm.com> Co-authored-by: Helena Zhang <helena@astbb.com>
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Summary
This PR build upon Chris' RB proposal, slightly modifying it to enable easy extension to other types of RB (interleaved, purity, CNOT-dihedral).
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