"""Consequence check for diag_analogy_sequence.py: the flag rises in the phases of the
period-4 cycle whose configuration does NOT recur (the undershoot whose relative step
shrinks every cycle, the crossing), while the recurring phases are the ones with the flag
down.  The entry demands both AT THE SAME STATE, so it waits until a flag state happens
to recur.

Candidate (not in the method): the analogy is a property of the RUN, the flag of the
MOMENT - once any state has been analogous to its past with m >= 2, enter at the next
flag.  Per problem, on traces of the proposed rule with NO regime (so both rules see the
same states): the state of entry under 'same state' and under 'analogy remembered', and
how many problems would enter at all, per group.  Nothing in the method changes.

    python -u diag_analogy_decoupled.py
"""
from __future__ import annotations

from collections import defaultdict

from simroot.pure import _analogous_and_steep, _config3, pure_root
from sweep_full import MAXFEV, XTOL, load_problems

FLAT = ("fun3", "fun4", "fun5", "fun6")


def entries(trace):
    past, seen = [], False
    same = remembered = None
    for k, s in enumerate(trace):
        cur = _config3(s["x"], s["fx"], s["xp"], s["fp"], s["xp2"], s["fp2"])
        flag = s["fp"] != 0.0 and s["fx"] / s["fp"] >= 0.25
        ana = _analogous_and_steep(cur, past)
        if flag and ana and same is None:
            same = k
        if flag and (seen or ana) and remembered is None:
            remembered = k
        seen = seen or ana
        if cur is not None:
            past.append(cur)
    return same, remembered


def main():
    per = defaultdict(lambda: [0, 0, 0, 0, 0])  # problems, same, remembered, sum same, sum rem
    for s, pid, f, a, b, _root in load_problems():
        st = {"trace": []}
        pure_root(f, a, b, XTOL, MAXFEV, similarity="ratio", scale="derived3",
                  guard="project", stats=st)
        fam = pid.split(".")[0]
        g = "APS" if s == "APS" else ("CHA-flat" if fam in FLAT else f"CHA-{fam}")
        same, rem = entries(st["trace"])
        p = per[g]
        p[0] += 1
        p[1] += same is not None
        p[2] += rem is not None
        if g == "CHA-flat" and same is not None and rem is not None:
            p[3] += same
            p[4] += rem
    print(f"{'group':<10} {'problems':>8} {'enter: same state':>18} {'analogy remembered':>19}")
    for g in sorted(per):
        n, a_, b_, s1, s2 = per[g]
        print(f"{g:<10} {n:8d} {a_:18d} {b_:19d}")
    fl = per["CHA-flat"]
    print(f"\nflat: mean entry state {fl[3] / fl[1]:.1f} (same state) -> "
          f"{fl[4] / fl[1]:.1f} (analogy remembered)")
    print("diag done")


if __name__ == "__main__":
    main()