operating_characteristics#

causalpy.checks.operating_characteristics(pit_result, *, effect_sizes=None, rope_half_width=None, threshold=None, n_points=201, mde_target=0.8)[source]#

Compute exact ROPE operating curves from a completed check result.

Parameters:

  • pit_result (CheckResult) – Completed PlaceboInTime result with an identified learned null.

  • effect_sizes (list[float] | ndarray | None) – Finite one-dimensional effect grid. The default is a nonnegative regular grid based on the learned-null spread and ROPE.

  • rope_half_width (float | None) – Nonnegative ROPE half-width, overriding result metadata.

  • threshold (float | None) – Decision probability in (0, 1), overriding result metadata.

  • n_points (int) – Positive number of grid points when effect_sizes is omitted.

  • mde_target (float) – Detection probability in (0, 1) at which to report MDE.

Returns:

Exact curve, MDE, false-positive-rate, assurance, and plotting API.

Return type:

OperatingCharacteristics