"""A prediction registered before the run, and falsified by it.

The hypothesis was that a method which wins in some places and loses in others
must have a regime where it wins outright, and that the regime is where the
quantity the constant approximates CHANGES during the run - because one
constant cannot be right at two different noise levels while a measured value
tracks.

It was stated before measuring, with the falsification condition attached: the
measured rule had to lose every constant-noise cell and win every
varying-noise cell.  It lost all twelve.

The first version of the test could not have confirmed it either way - noise
reduction was scored on the second half of the run, by which time every ramp
and step had already arrived, so the metric never saw a transition.  That flaw
was found and fixed before the conclusion was drawn, and the conclusion did
not change.

This file exists so the line is not reopened without new evidence.
"""
from __future__ import annotations

import math
import os
import sys

import pytest

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from anc.rules import Fixed, Measured
from stage20_prediction import (FLAT_5, FLAT_30, STEP_25, SWING_25, sig_cabin,
                                sig_tonal, score)

SEEDS = 3


def test_the_metric_window_sees_the_transition():
    """The flaw that would have produced a false falsification.  A varying
    profile must not score the same as a constant one at its final level."""
    varying = score(Fixed(0.1), sig_tonal, SWING_25, seeds=SEEDS)
    final_level = score(Fixed(0.1), sig_tonal, FLAT_5, seeds=SEEDS)
    assert varying > final_level + 2.0, (varying, final_level)


@pytest.mark.parametrize("signal", [sig_tonal, sig_cabin],
                         ids=["tonal", "cabin"])
@pytest.mark.parametrize("profile,kind", [(FLAT_30, "control"),
                                          (FLAT_5, "control"),
                                          (SWING_25, "prediction"),
                                          (STEP_25, "prediction")],
                         ids=["flat30", "flat5", "ramp", "step"])
def test_an_oracle_constant_beats_the_measured_rule_everywhere(signal, profile,
                                                               kind):
    """The registered prediction required the measured rule to WIN the two
    'prediction' cells.  It does not, on either signal.  A single constant,
    chosen with knowledge of the scenario, is ahead even when the noise level
    swings by 25 dB inside the run."""
    ms = score(Measured(), signal, profile, seeds=SEEDS)
    best = max(score(Fixed(mu), signal, profile, seeds=SEEDS)
               for mu in (0.05, 0.1, 0.2, 0.5, 1.0))
    assert best > ms, (kind, best, ms)


def test_the_conclusion_this_licenses():
    """Winning somewhere and losing elsewhere does not imply a regime of
    outright victory exists; it is equally consistent with a middling
    generalist.  On this evidence there is no such regime, and the claim the
    work may make is the scoped one in test_modern_repairs.py."""
    losses = 0
    for signal in (sig_tonal, sig_cabin):
        for profile in (FLAT_30, FLAT_5, SWING_25, STEP_25):
            ms = score(Measured(), signal, profile, seeds=SEEDS)
            best = max(score(Fixed(mu), signal, profile, seeds=SEEDS)
                       for mu in (0.05, 0.2, 1.0))
            losses += ms < best
    assert losses == 8, losses