skills/pkpd-modeling/scripts/nca.py

• Profile · class · L56-L63 — class Profile
• _parse_conc · function · L66-L86 — def _parse_conc(raw: str, lloq: float | None, rule: str) -> tuple[float | None, bool]
• load_profiles · function · L89-L140 — def load_profiles(args: argparse.Namespace) -> list[Profile]
• _segment · function · L146-L163 — def _segment(t0: float, t1: float, c0: float, c1: float, method: str) -> tuple[float, float]
• cumulative_auc · function · L166-L173 — def cumulative_auc(time: np.ndarray, conc: np.ndarray, method: str) -> tuple[np.ndarray, np.ndarray]
• interpolate · function · L176-L188 — def interpolate(time: np.ndarray, conc: np.ndarray, target: float, method: str) -> float
• partial_auc · function · L191-L198 — def partial_auc(time: np.ndarray, conc: np.ndarray, start: float, end: float, method: str) -> float
• LambdaZ · class · L205-L219 — class LambdaZ
• half_life · method · L218-L219 — def half_life(self) -> float | None
• _loglinear_fit · function · L222-L233 — def _loglinear_fit(t: np.ndarray, c: np.ndarray) -> tuple[float, float, float]
• estimate_lambda_z · function · L236-L307 — def estimate_lambda_z( time: np.ndarray, conc: np.ndarray, is_blq: np.ndarray, tmax: float, min_points: int = 3, manual: tuple[float, float] | None = None, ) -> LambdaZ
• analyse · function · L313-L424 — def analyse(profile: Profile, args: argparse.Namespace) -> tuple[dict, LambdaZ, list[str]]
• summarise · function · L430-L454 — def summarise(rows: Sequence[dict], keys: Sequence[str]) -> list[dict]
• _partial_spec · function · L460-L468 — def _partial_spec(text: str) -> tuple[float, float]
• _window_spec · function · L471-L472 — def _window_spec(text: str) -> tuple[float, float]
• build_parser · function · L475-L516 — def build_parser() -> argparse.ArgumentParser
• run · function · L519-L583 — def run(argv: Sequence[str] | None = None) -> int