#!/usr/bin/env python3
"""Audit untouched calibration-split oral-B-v2 confirmation."""
import argparse
import glob
import hashlib
import json
import math
import os

from experiments.analyze_bci_v2_recovery_confirmation import (
    checks,
    summarize,
    task_clusters,
)
from experiments.bci_v2_calibrated_confirmation import (
    MODEL_SEEDS,
    TASK_SEEDS,
)
from experiments.bci_v2_calibrated_run import (
    CALIBRATION_EPISODES,
    CHALLENGE_EPISODES,
    TARGET_QUANTILES,
    build_recovery_config,
    source_paths,
)
from experiments.bci_v2_recovery_run import FIXED_CONFIG
from experiments.bci_v2_run import CONDITIONS


ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
RUNNER_PATH = os.path.join(
    ROOT, "experiments", "bci_v2_calibrated_confirmation.py"
)


def require(condition, message):
    if not condition:
        raise ValueError(message)


def sha256(path):
    digest = hashlib.sha256()
    with open(path, "rb") as handle:
        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
            digest.update(chunk)
    return digest.hexdigest()


def finite_tree(value):
    if isinstance(value, dict):
        return all(finite_tree(item) for item in value.values())
    if isinstance(value, (list, tuple)):
        return all(finite_tree(item) for item in value)
    if isinstance(value, (int, float)):
        return math.isfinite(value)
    return True


def confirmation_paths(r1_gate):
    paths = source_paths()
    paths["development_runner"] = paths["runner"]
    paths["runner"] = RUNNER_PATH
    paths["r1_gate"] = os.path.abspath(r1_gate)
    return paths


def validate(row, path, digests):
    require(row.get("schema_version") == 4, f"{path}: schema")
    args = row.get("args", {})
    task_seed = args.get("task_seed")
    model_seed = args.get("model_seed")
    require(
        task_seed in TASK_SEEDS and model_seed in MODEL_SEEDS,
        f"{path}: seeds",
    )
    protocol = row.get("protocol", {})
    require(
        protocol.get("name")
        == "oral_b_v2_calibrated_recovery_confirmation_v1"
        and protocol.get("split") == "untouched_confirmation"
        and protocol.get("training_task_seed") == task_seed
        and protocol.get("model_seed") == model_seed
        and protocol.get("fixed_config") == FIXED_CONFIG
        and protocol.get("calibration_uses_outcome_labels") is False
        and protocol.get("no_further_selection") is True
        and protocol.get("confirmation_grid_size") == 30
        and protocol.get("protocol_sha256") == digests["protocol"]
        and protocol.get("r1_gate_sha256") == digests["r1_gate"],
        f"{path}: protocol",
    )
    provenance = row.get("provenance", {})
    require(
        provenance.get("git_tracked_dirty") is False
        and provenance.get("tracked_inputs")
        and all(provenance["tracked_inputs"].values())
        and set(provenance["tracked_inputs"]) == set(digests)
        and provenance.get("input_sha256") == digests,
        f"{path}: provenance",
    )
    require(
        row.get("config") == vars(build_recovery_config())
        and row.get("split") == "untouched_confirmation"
        and row.get("finite") is True
        and finite_tree(row),
        f"{path}: finite/config",
    )
    require(
        set(row.get("conditions", {})) == set(CONDITIONS),
        f"{path}: conditions",
    )
    for name in CONDITIONS:
        warmup = row["warmup"][name]
        condition = row["conditions"][name]
        cost = condition["cost"]
        require(
            warmup["batches"] == 100
            and warmup["examples"] == 6400
            and warmup["instruction_present"] is False
            and warmup["role_cursor_scalar_observations"] == 12800
            and warmup["predictor_max_abs_error"] <= 1e-5
            and len(condition["daily_success"]) == 14
            and cost["maximum_state_episode_steps"] == 25088
            and cost["cursor_scalar_observations"]
            == 2 * cost["role_probe_examples"]
            and cost["task_loss_queries"] == 0
            and cost["reverse_mode_calls"] == 0,
            f"{path}: condition {name}",
        )
    challenge = row["assays"]["challenge"]
    calibration = challenge["calibration"]
    targets = challenge["targets"]
    require(
        calibration["episodes"] == CALIBRATION_EPISODES
        and calibration["quantiles"] == list(TARGET_QUANTILES)
        and calibration["targets"] == targets
        and calibration["uses_outcome_labels"] is False
        and calibration["seed"] == 600_000 + task_seed
        and challenge["episodes_per_target"] == CHALLENGE_EPISODES
        and challenge["selection_over_evaluation_outcomes"] is False
        and challenge["maximum_steps_per_episode"] == 28
        and len(targets) == len(TARGET_QUANTILES)
        and all(
            targets[index] < targets[index + 1]
            for index in range(len(targets) - 1)
        )
        and row["signatures"]["challenge_episodes"]
        == len(TARGET_QUANTILES) * CHALLENGE_EPISODES,
        f"{path}: calibration",
    )


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--results",
        default="results/bci_v2_calibrated_confirmation",
    )
    parser.add_argument(
        "--r1-gate",
        default="results/bci_v2_calibrated_dev_gate.json",
    )
    parser.add_argument(
        "--out",
        default="results/bci_v2_calibrated_confirmation_gate.json",
    )
    args = parser.parse_args()
    with open(args.r1_gate) as handle:
        r1 = json.load(handle)
    require(
        r1.get("protocol")
        == "oral_b_v2_calibrated_recovery_development_v1"
        and r1.get("status") == "passed"
        and r1.get("complete_grid") is True
        and r1.get("fixed_config") == FIXED_CONFIG
        and r1.get("confirmation_seeds_touched") is False
        and r1.get("calibrated_confirmation_opened") is True,
        "calibrated R1 gate",
    )
    development_digests = {
        name: sha256(path)
        for name, path in source_paths().items()
    }
    require(
        r1.get("input_sha256") == development_digests,
        "R1 source binding",
    )
    digests = {
        name: sha256(path)
        for name, path in confirmation_paths(args.r1_gate).items()
    }
    expected = {
        f"bci_v2_calibrated_confirm_t{task_seed}_m{model_seed}.json"
        for task_seed in TASK_SEEDS
        for model_seed in MODEL_SEEDS
    }
    observed = {
        os.path.basename(path)
        for path in glob.glob(os.path.join(args.results, "*.json"))
    }
    require(
        observed == expected,
        (
            f"confirmation drift: missing={sorted(expected-observed)}, "
            f"extra={sorted(observed-expected)}"
        ),
    )
    records = {}
    commits = set()
    source_sha256 = {}
    for task_seed in TASK_SEEDS:
        for model_seed in MODEL_SEEDS:
            path = os.path.join(
                args.results,
                (
                    f"bci_v2_calibrated_confirm_t{task_seed}"
                    f"_m{model_seed}.json"
                ),
            )
            with open(path) as handle:
                row = json.load(handle)
            validate(row, path, digests)
            records[(task_seed, model_seed)] = row
            commits.add(row["provenance"]["git_commit"])
            source_sha256[path] = sha256(path)
    require(len(commits) == 1, "confirmation source revision drift")

    getters = {
        "intact_final": lambda row:
            row["conditions"]["intact"]["final_success"],
        "intact_gain": lambda row:
            row["conditions"]["intact"]["learning_gain"],
        "fixed_role_gap": lambda row: (
            row["conditions"]["intact"]["final_success"]
            - row["conditions"]["fixed_role"]["final_success"]
        ),
        "oracle_deficit": lambda row: (
            row["conditions"]["oracle_role"]["final_success"]
            - row["conditions"]["intact"]["final_success"]
        ),
        "plasticity_half_margin": lambda row: (
            0.5 * row["conditions"]["intact"]["learning_gain"]
            - row["conditions"]["plasticity_lesion"]["learning_gain"]
        ),
        "role_cosine": lambda row:
            row["conditions"]["intact"]["role_cosine_after_training"],
        "critic_training_gap": lambda row: (
            row["conditions"]["intact"]["final_success"]
            - row["conditions"]["critic_training_lesion"][
                "final_success"
            ]
        ),
        "outcome_training_gap": lambda row: (
            row["conditions"]["intact"]["final_success"]
            - row["conditions"]["outcome_training_lesion"][
                "final_success"
            ]
        ),
        "residual_soma_corr": lambda row:
            row["signatures"]["mean_abs_residual_soma_corr"],
        "raw_residual_corr_gap": lambda row:
            row["signatures"][
                "raw_minus_residual_abs_soma_corr"
            ],
        "surrounding_accuracy": lambda row:
            row["signatures"][
                "surrounding_event_decoder_balanced_acc"
            ],
        "decoder_corr": lambda row:
            row["signatures"]["decoder_distance_residual_corr"],
        "sign_inversion": lambda row:
            row["signatures"][
                "causal_role_sign_inversion_index"
            ],
        "velocity_advantage": lambda row:
            row["signatures"][
                "velocity_minus_error_abs_cv_corr"
            ],
        "challenge_fraction": lambda row:
            row["signatures"]["challenge_success_fraction"],
        "terminal_accuracy": lambda row:
            row["signatures"][
                "terminal_residual_outcome_balanced_acc"
            ],
        "terminal_separation": lambda row:
            row["signatures"][
                "terminal_role_aligned_outcome_separation"
            ],
        "outcome_lesion_drop": lambda row:
            row["signatures"][
                "terminal_outcome_separation_drop_under_acute_lesion"
            ],
        "critic_expectedness": lambda row:
            row["signatures"][
                "mean_critic_expectedness_contribution"
            ],
        "critic_value_corr": lambda row:
            row["signatures"][
                "critic_contribution_value_prediction_corr"
            ],
    }
    clustered = {
        name: task_clusters(records, getter)
        for name, getter in getters.items()
    }
    metrics = {
        name: summarize(values)
        for name, values in clustered.items()
    }
    all_values = {
        name: [getter(row) for row in records.values()]
        for name, getter in getters.items()
    }
    gate_checks = checks(metrics, clustered, all_values)
    passed = all(
        value
        for category in gate_checks.values()
        for value in (
            [category]
            if isinstance(category, bool)
            else category.values()
        )
    )
    output = {
        "protocol":
            "oral_b_v2_calibrated_recovery_confirmation_v1",
        "status": "passed" if passed else "failed",
        "complete_grid": True,
        "fixed_config": FIXED_CONFIG,
        "calibration_quantiles": list(TARGET_QUANTILES),
        "checks": gate_checks,
        "metrics": metrics,
        "positive_sign_count": sum(
            value > 0 for value in all_values["sign_inversion"]
        ),
        "source_commit": next(iter(commits)),
        "source_sha256": source_sha256,
        "input_sha256": digests,
        "oral_b_v2_outcome_surprise_established": passed,
        "all_prior_failures_preserved": True,
        "old_oral_a_gate_remains_closed": True,
        "new_oral_a_v2_protocol_may_be_frozen": passed,
        "review_score_before": 7,
        "review_score_after": 8 if passed else 7,
        "score_change_rule": (
            "only a complete untouched calibrated R2 pass establishes "
            "role-vectorized TD outcome surprise; prior failures and "
            "the old oral-A gate remain unchanged"
        ),
    }
    os.makedirs(os.path.dirname(os.path.abspath(args.out)), exist_ok=True)
    if os.path.exists(args.out):
        with open(args.out) as handle:
            existing = json.load(handle)
        require(existing == output, "existing calibrated R2 gate differs")
    else:
        with open(args.out, "w") as handle:
            json.dump(output, handle, indent=2, sort_keys=True)
            handle.write("\n")
    print(json.dumps(output, indent=2))


if __name__ == "__main__":
    main()