iqm.benchmarks.randomized_benchmarking.multi_lmfit.create_multi_dataset_params

iqm.benchmarks.randomized_benchmarking.multi_lmfit.create_multi_dataset_params#

iqm.benchmarks.randomized_benchmarking.multi_lmfit.create_multi_dataset_params(func: Callable, data: ndarray, initial_guesses: dict[str, float] | None = None, constraints: dict[str, dict[str, float]] | None = None, simultaneously_fit_vars: list[str] | None = None) → Parameters#

Generates lmfit Parameter object with parameters for each line to fit.

Parameters:

  • func (Callable) – The fit function whose parameters will be extracted.

  • data (ndarray) – 2D array where each row represents a dataset to fit.

  • initial_guesses (dict[str, float] | None) – Optional dictionary mapping parameter names to initial values.

  • constraints (dict[str, dict[str, float]] | None) – Optional dictionary mapping parameter names to constraint dicts with ‘min’ and ‘max’ keys.

  • simultaneously_fit_vars (list[str] | None) – Optional list of parameter names that should be fit as a single parameter across all datasets.

Returns:

lmfit Parameters object with parameters for each dataset, with suffixes _1, _2, etc.

Return type:

Parameters

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