LECA.analyze.create_input

LECA.analyze.create_input(feature_dict: Dict[str, List[float]], steps: int = 10, temp: int | float = -1) → Tuple[DataFrame, array]

Create a dataframe grid of input electrolyte compositions from sparse feature vectors, or [min, max] + step values.

Parameters:

• feature_dict (Dict[str, list[float]]) – Dictionary with input feature names as keys, and either [min, max] as values, or a list of explicit values [val0, val1, val2, …] to be generated.

• steps – Number of values to generate for each feature axis provided as [min, max] values.

temp: Union[int, float]

Temperature to be converted to inverse temperature (1000/(273.15+temp)) and added as a feature in the grid. If -1, no temperature is added.

Default value -1

Returns:

The DataFrame is the meshgrid spanning all of the feature dimensions given in the feature_dict (+ optionally the inverse temperature).

The array is the set of feature names returned.

Return type:

Tuple[pd.DataFrame, np.array]