pybop.pybamm.synthetic_utils#

Utilities for synthetic data generation.

Attributes#

`DEFAULT_COLUMN_DEFINITIONS`
`EIS_COLUMN_DEFINITIONS`
`PARAMETERS_TO_SWAP`

Functions#

`_build_eis_sweep_dataframe`(→ polars.LazyFrame)	Create a PyProBE-compatible dataframe for one EIS sweep.
`_build_frequency_grid`(→ numpy.ndarray)	Build the frequency grid for an EIS experiment.
`_canonical_cell_format`(→ str)	Normalize cell type string to archive format.
`_flatten_sequence`(→ list[str])	Flatten a list of experiment tuples into a list of per-event descriptions.
`_get_experiment_sequences`(→ tuple[list[tuple[int, ...)	Expand a spec experiment into PyBaMM experiment step tuples.
`_get_experiment_type`(→ str)	Return the synthetic experiment type.
`_load_spec`(→ dict[str, Any])	Load a JSON spec file.
`_remap_cycle_info`(→ polars.LazyFrame)	Map PyBaMM step and cycle numbers back to match the cycle information.
`_safe_name`(→ str)	Create a safe filename from a string.
`_solution_to_dataframe`(→ polars.LazyFrame)	Convert a PyBaMM solution into the PyProBE-required dataframe layout.
`_solve_eis_experiment`(→ tuple[polars.LazyFrame, ...)	Solve an EIS experiment and return a PyProBE-compatible dataframe.
`_solve_time_domain_experiment`(→ pybamm.Solution)	Solve a standard time-domain experiment.
`_validate_experiment`(→ None)
`_validate_frequency_spec`(→ None)
`_validate_spec`(→ tuple[dict[str, Any], dict[str, Any]])
`_validate_steps`(→ None)
`archive_data`(cell, archive_root)	Archive the data fron the cell object.
`convert_to_half_cell_parameters`(→ pybamm.ParameterValues)	Function to adapt a full cell parameter set to a half cell.
`simulate_procedure`(→ None)

Module Contents#

pybop.pybamm.synthetic_utils._build_eis_sweep_dataframe(step_number: int, event_number: int, frequencies: numpy.ndarray, impedance: numpy.ndarray, initial_voltage: float | None) → polars.LazyFrame[source]#: Create a PyProBE-compatible dataframe for one EIS sweep.

pybop.pybamm.synthetic_utils._build_frequency_grid(frequency_spec: list[float] | dict[str, Any]) → numpy.ndarray[source]#: Build the frequency grid for an EIS experiment.

pybop.pybamm.synthetic_utils._canonical_cell_format(cell_type: str) → str[source]#: Normalize cell type string to archive format.

pybop.pybamm.synthetic_utils._flatten_sequence(sequences: list[tuple[str, Ellipsis]]) → list[str][source]#: Flatten a list of experiment tuples into a list of per-event descriptions.

pybop.pybamm.synthetic_utils._get_experiment_sequences(experiment_info: dict[str, Any]) → tuple[list[tuple[int, Ellipsis]], list[tuple[str, Ellipsis]]][source]#: Expand a spec experiment into PyBaMM experiment step tuples.

pybop.pybamm.synthetic_utils._get_experiment_type(experiment_info: dict[str, Any]) → str[source]#: Return the synthetic experiment type.

pybop.pybamm.synthetic_utils._load_spec(path: pathlib.Path) → dict[str, Any][source]#: Load a JSON spec file.

pybop.pybamm.synthetic_utils._remap_cycle_info(dataframe: polars.LazyFrame, step_sequence: list[tuple[int, Ellipsis]], event_offset: int) → polars.LazyFrame[source]#: Map PyBaMM step and cycle numbers back to match the cycle information.

pybop.pybamm.synthetic_utils._safe_name(value: str) → str[source]#: Create a safe filename from a string.

pybop.pybamm.synthetic_utils._solution_to_dataframe(solution: pybamm.Solution, step_sequence: list[tuple[int, Ellipsis]], start_time: float, event_offset: int) → polars.LazyFrame[source]#: Convert a PyBaMM solution into the PyProBE-required dataframe layout.

pybop.pybamm.synthetic_utils._solve_eis_experiment(experiment_info: dict[str, Any], model: pybamm.BaseModel, parameter_values: pybamm.ParameterValues, previous_solution: pybamm.Solution | None, step_offset: int, solve_kwargs: dict[str, float] | None) → tuple[polars.LazyFrame, dict[str, Any], pybamm.Solution | None, int, int][source]#: Solve an EIS experiment and return a PyProBE-compatible dataframe.

pybop.pybamm.synthetic_utils._solve_time_domain_experiment(experiment: pybamm.Experiment, model: pybamm.BaseModel, parameter_values: pybamm.ParameterValues, previous_solution: pybamm.Solution | None, solve_kwargs: dict[str, float] | None) → pybamm.Solution[source]#: Solve a standard time-domain experiment.

pybop.pybamm.synthetic_utils._validate_experiment(experiment_name: str, experiment_info: Any) → None[source]#

pybop.pybamm.synthetic_utils._validate_frequency_spec(experiment_name: str, frequency_spec: Any) → None[source]#

pybop.pybamm.synthetic_utils._validate_spec(spec_path: pathlib.Path) → tuple[dict[str, Any], dict[str, Any]][source]#

pybop.pybamm.synthetic_utils._validate_steps(experiment_name: str, experiment_info: dict[str, Any]) → None[source]#

pybop.pybamm.synthetic_utils.archive_data(cell, archive_root: pathlib.Path)[source]#: Archive the data fron the cell object.

pybop.pybamm.synthetic_utils.convert_to_half_cell_parameters(parameter_values: pybamm.ParameterValues, electrode_type: str) → pybamm.ParameterValues[source]#

Function to adapt a full cell parameter set to a half cell.

Positive electrode parameters are set from the working electrode, negative electrode parameters are set for a lithium counter, from Xu2019.

pybop.pybamm.synthetic_utils.simulate_procedure(info: dict, model: pybamm.BaseModel, parameter_values: pybamm.ParameterValues, spec_path: pathlib.Path, solve_kwargs: dict[str, float] | None = None) → None[source]#

pybop.pybamm.synthetic_utils.DEFAULT_COLUMN_DEFINITIONS: dict[str, str]#

pybop.pybamm.synthetic_utils.EIS_COLUMN_DEFINITIONS: dict[str, str]#

pybop.pybamm.synthetic_utils.PARAMETERS_TO_SWAP: list[str] = ['Positive electrode conductivity [S.m-1]', 'Maximum concentration in positive electrode...#