"""Versioned ascending-zero DFG measurement; original data and gates unchanged."""

import numpy as np

from periodic import GATES, REFERENCE_GATES, compare

VERSION = "dfg-ascending-zero-v2"


def ascending_crossings(t, y):
    t = np.asarray(t, dtype=float); y = np.asarray(y, dtype=float)
    if t.ndim != 1 or y.shape != t.shape or not np.isfinite(t).all() or not np.isfinite(y).all():
        raise ValueError("Finite one-dimensional time/signal arrays required")
    if np.any(np.diff(t) <= 0):
        raise ValueError("Strictly increasing times required")
    i = np.flatnonzero((y[:-1] < 0) & (y[1:] >= 0))
    return (t[i] - y[i] * (t[i+1] - t[i]) / (y[i+1] - y[i])).tolist()


def validate_rows(rows):
    keys = ("tstar", "tstar_force", "cd", "cl", "dp", "mass", "flux_in", "flux_out")
    values = np.asarray([[row[k] for k in keys] for row in rows], dtype=float)
    if not np.isfinite(values).all():
        raise ValueError("Nonfinite observation")
    if len(rows) and (np.any(np.diff(values[:, 0]) <= 0) or np.any(np.diff(values[:, 1]) <= 0)):
        raise ValueError("Strictly increasing observation times required")


def extract(rows, min_time=250.0):
    validate_rows(rows)
    if len(rows) < 3:
        return []
    t = np.array([r["tstar_force"] for r in rows])
    cl = np.array([r["cl"] for r in rows])
    ends = ascending_crossings(t, cl)
    cycles = []
    for a, b in zip(ends, ends[1:]):
        if a < min_time or not GATES["min_period"] < b - a < GATES["max_period"]:
            continue
        grid = np.linspace(a, b, 257)
        c = dict(start=a, end=b, period=b - a, st=1 / (b - a))
        for key in ("cd", "cl", "dp", "mass", "flux_in", "flux_out"):
            times = np.array(
                [r["tstar" if key not in ("cd", "cl") else "tstar_force"] for r in rows]
            )
            # No endpoint extrapolation: pressure/mass must cover the whole cycle.
            if a < times[0] or b > times[-1]:
                break
            v = np.interp(grid, times, [r[key] for r in rows])
            c[key + "_min"] = float(v.min())
            c[key + "_max"] = float(v.max())
            c[key + "_midrange"] = float((v.min() + v.max()) / 2)
            c[key + "_amplitude"] = float(v.max() - v.min())
            c[key + "_time_mean"] = float(
                np.sum((v[1:] + v[:-1]) * np.diff(grid) / 2) / (b - a)
            )
            if key in ("cd", "cl", "dp"):
                c[key + "_waveform"] = v.tolist()
        else:
            c["flux_relative"] = abs(
                c["flux_in_time_mean"] - c["flux_out_time_mean"]
            ) / max(abs(c["flux_in_time_mean"]), 1e-30)
            cycles.append(c)
    return cycles


def assess(rows):
    cycles = extract(rows, min_time=GATES["min_tstar"])
    tail = cycles[-GATES["cycles"] :]
    checks = {}
    checks["enough_cycles"] = len(tail) == GATES["cycles"]
    if checks["enough_cycles"]:
        checks["consecutive"] = all(
            abs(a["end"] - b["start"]) < 1e-8 for a, b in zip(tail, tail[1:])
        )
        checks["recent"] = (
            0 <= rows[-1]["tstar_force"] - tail[-1]["end"] <= GATES["max_period"]
        )
        checks["shedding"] = (
            min(c["cl_amplitude"] for c in tail) >= GATES["min_lift_amplitude"]
        )
        periods = [c["period"] for c in tail]
        checks["period"] = (
            np.ptp(periods) / np.mean(periods) <= GATES["period_relative_range"]
        )
        checks["extrema"] = all(
            np.ptp([c[k + "_" + e] for c in tail]) <= GATES["extrema_absolute_range"]
            for k in ("cd", "cl", "dp")
            for e in ("min", "max")
        )
        mass = [c["mass_time_mean"] for c in tail]
        checks["mass"] = (
            np.ptp(mass) / abs(np.mean(mass)) <= GATES["mass_relative_range"]
        )
        checks["flux"] = (
            max(c["flux_relative"] for c in tail) <= GATES["cycle_mean_flux_relative"]
        )
    return dict(
        periodic=bool(checks["enough_cycles"] and all(checks.values())),
        checks={k: bool(v) for k, v in checks.items()},
        cycles=cycles,
    )