"""Expose frozen historical network alarms without implying a live validated feed."""
import datetime as dt
import json
import math
from pathlib import Path
from zoneinfo import ZoneInfo
from .network_review import aware_time

DATA=Path(__file__).with_name('data')/'network_monitor_research.json'


def load_bundle():
    if not DATA.exists():return {'state':'research_monitor_not_installed'}
    return json.loads(DATA.read_text(encoding='utf-8'))


def watch_signal(bundle,date,cutoff):
    instant=aware_time(cutoff)
    if instant is None:raise ValueError('cutoff requires a timezone-aware timestamp')
    requested=dt.date.fromisoformat(date)
    if bundle.get('state')!='research_evaluation_available':return {'state':'research_monitor_not_installed'}
    local_day=instant.astimezone(ZoneInfo('Asia/Seoul')).date()
    if (local_day-requested).days>1:
        return {'state':'stale_research_date_for_cutoff','date':date,'cutoff_utc':instant.isoformat()}
    if requested<=dt.date.fromisoformat(bundle['training_end']):
        return {'state':'calibration_not_available_before_signal','date':date,'training_end':bundle['training_end']}
    available=aware_time(date+'T23:59:59+09:00')
    if available>instant:return {'state':'unclosed_or_unavailable_session','date':date}
    observations=bundle['observations']
    if date not in observations:
        return {'state':'research_date_unavailable','date':date,'available_start':min(observations,default=None),
                'available_end':max(observations,default=None)}
    row=observations[date]
    score=row.get('score');cut=bundle.get('model',{}).get('cut')
    if (bundle.get('model',{}).get('state')!='fitted' or not isinstance(row.get('original_alert'),bool)
            or score is None or cut is None or not math.isfinite(float(score)) or not math.isfinite(float(cut))):
        return {'state':'insufficient_network_data','date':date,'score':None,'research_only':True}
    return dict(state='research_alert' if row['original_alert'] else 'no_research_alert',date=date,
        cutoff_utc=instant.isoformat(),available_by_assumption=available.isoformat(),
        primary_rule=bundle['primary_rule'],training_end=bundle['training_end'],
        market_scope=bundle.get('market_scope','Original fixed Korean-equity research sample'),
        available_snapshot_dates=bundle.get('available_snapshot_dates',[]),
        score=float(score),frozen_cut=float(cut),above_frozen_cut=float(score)>=float(cut),
        original_alert=row['original_alert'],equal_token_capacity_alert=row.get('equal_token_capacity_alert'),
        baseline_alerts=row.get('baseline_alerts',{}),research_only=True,live_monitor=False,
        validated_detection_or_forecast_superiority=False,
        comparison_findings=bundle.get('comparison_findings',{}),
        historical_membership_and_release_vintages_verified=False,
        interpretation='Fixed original-research historical rule; an alert is a model threshold event, not proof of an abnormal regime, future loss or causation.')