core.eval:delta()

Resolve transport data acquired using the delta method.

Usage

Source

core.eval:delta(data: np.ndarray) -> tuple[np.ndarray, np.ndarray]
core.eval:delta(
    data: pl.DataFrame,
    column: str | None = None,
) -> pl.LazyFrame

Dispatches on the type of data: numpy arrays are evaluated eagerly with delta_numpy, polars DataFrames with delta_polars, whose result is not collected, so polars can optimize it together with later stages of a query. Numpy input raises a FutureWarning, as it will be removed in a future release.

Parameters

data: np.ndarray or pl.DataFrame

Array of data with dimension ‘m’ containing e.g. voltage, or a frame holding such a column. Format must be [value for +I, value for -I, value for +I, …].

column: str = None

Only used for polars DataFrames. Name of the column containing the data, e.g. voltage. If not given, the frame must contain exactly one column, which is used.

Returns

pos: np.ndarray or pl.LazyFrame

For numpy input: array with dimension ‘m//2’ containing the contribution symmetric in current. For polars input: lazy frame with dimension ‘m//2’ and the columns pos and neg.

neg: np.ndarray

Array with dimension ‘m//2’ containing the contribution antisymmetric in current. Only returned for numpy input.

See Also

delta_numpy

delta_polars