qiskit_noise_learning.data.ModelData
class qiskit_noise_learning.data.ModelData(dataset: Dataset)
Bases: LeveledData, Generic[ParameterIndex]
Results from fitting, backed by an xarray Dataset.
The dataset has data variables:
parameter_values: 1D array with dimensionparameter_index.covariance: 2D array with dimensions(parameter_row_index, parameter_col_index).
The parameter_index, parameter_row_index, and parameter_col_index coordinates all share the same parameter labels. Additional fit metadata is stored in dataset attrs.
__init__
__init__(dataset: Dataset)
Methods
Column 1 | Column 2 |
|---|---|
__init__(dataset) | |
filter_time(lb, ub) | Filter to data gathered within the time bounds. |
from_arrays(parameter_indices, ...[, metadata]) | Instantiate from data specified as arrays in standard containers. |
Attributes
Column 1 | Column 2 |
|---|---|
dataset | |
metadata | Metadata describing the model parameter fit. |
from_arrays
classmethod from_arrays(parameter_indices: list[ParameterIndex], parameter_values: ndarray[float64], covariance: ndarray[float64], time_lbs: ndarray[datetime64], time_ubs: ndarray[datetime64], metadata: dict[str, Any] | None = None) → Self
Instantiate from data specified as arrays in standard containers.
Parameters
- parameter_indices – A list of
ParameterIndexinstances. - parameter_values – A 1d array of floats indicating parameter values.
- covariance – A 2d array of floats indicating the covariances of the parameter values.
- time_lbs – A 1d array of data acquisition time lower bounds for each parameter estimate.
- time_ubs – A 1d array of data acquisition time upper bounds for each parameter estimate.
- metadata – Any metadata to attach to the dataset.
metadata
filter_time
filter_time(lb: datetime64, ub: datetime64) → Self
Filter to data gathered within the time bounds.
Parameters
- lb – The time lower bound (inclusive).
- ub – The time upper bound (inclusive).
Returns
The time filtered version of self.