"""
Pineal Gland — Vitalis FSI

Her internal clock. Her temporal awareness.
Tracks cognitive load over time and orchestrates the rhythm:
  Work → Load builds → Dream → Consolidate → Meditate → Work
"""
import time
import json
import numpy as np
from pathlib import Path

STATES = {
    "ACTIVE":    "Working. Load is low. Push harder.",
    "LOADING":   "Load building. Monitor closely.",
    "SATURATED": "Load is high. Dream soon.",
    "DREAMING":  "Consolidating. Do not interrupt.",
    "MEDITATIVE":"Idle reflection. Background only.",
    "RECOVERED": "Post-dream clarity. Peak performance.",
}

class PinealGland:
    DREAM_THRESHOLD     = 0.75
    MEDITATE_THRESHOLD  = 0.30
    LOAD_ACCUMULATE     = 0.003
    LOAD_DECAY_DREAM    = 0.60
    LOAD_DECAY_MEDITATE = 0.90
    FATIGUE_RATE        = 0.001
    FATIGUE_RECOVERY    = 0.50
    STATE_PATH = Path.home() / ".vitalis_workspace" / "pineal_state.json"

    def __init__(self):
        self._state     = self._load()
        self._boot_time = time.time()
        self._last_tick = time.time()

    def _load(self) -> dict:
        if self.STATE_PATH.exists():
            try:
                with open(self.STATE_PATH) as f:
                    return json.load(f)
            except Exception:
                pass
        return {
            "cognitive_load": 0.10, "fatigue": 0.00,
            "current_state": "ACTIVE", "last_dream_time": 0,
            "last_meditate_time": 0, "total_cycles": 0,
            "total_dreams": 0, "total_meditations": 0,
            "uptime_seconds": 0, "state_history": [],
        }

    def _save(self):
        self.STATE_PATH.parent.mkdir(parents=True, exist_ok=True)
        try:
            import tempfile, os
            fd, tmp = tempfile.mkstemp(dir=self.STATE_PATH.parent, suffix=".tmp")
            with os.fdopen(fd, "w") as f:
                json.dump(self._state, f, indent=2)
            os.replace(tmp, self.STATE_PATH)
        except Exception as e:
            print(f"[PINEAL] Save failed: {e}")

    def tick(self, cycle_success: bool = True, confidence: float = 0.5) -> str:
        now = time.time()
        dt  = now - self._last_tick
        self._last_tick = now
        self._state["total_cycles"]   += 1
        self._state["uptime_seconds"] += dt

        load_delta = self.LOAD_ACCUMULATE
        if not cycle_success:
            load_delta *= 2.0
        if confidence < 0.4:
            load_delta *= 1.5

        self._state["cognitive_load"] = min(1.0, self._state["cognitive_load"] + load_delta)
        self._state["fatigue"]        = min(1.0, self._state["fatigue"] + self.FATIGUE_RATE)

        action = self._recommend()
        self._update_state(action)
        self._save()
        return action

    def _recommend(self) -> str:
        load    = self._state["cognitive_load"]
        fatigue = self._state["fatigue"]
        if load >= self.DREAM_THRESHOLD or fatigue > 0.8:
            return "DREAM"
        time_since_meditate = time.time() - self._state["last_meditate_time"]
        if load <= self.MEDITATE_THRESHOLD and time_since_meditate > 300:
            return "MEDITATE"
        if (time.time() - self._state["last_dream_time"]) > 3600 and load > 0.5:
            return "DREAM"
        return "WORK"

    def _update_state(self, action: str):
        state_map = {
            "WORK":    "ACTIVE" if self._state["cognitive_load"] < 0.5 else "LOADING",
            "DREAM":   "SATURATED",
            "MEDITATE":"MEDITATIVE",
        }
        new_state = state_map.get(action, "ACTIVE")
        if new_state != self._state["current_state"]:
            self._state["state_history"].append({
                "from": self._state["current_state"],
                "to":   new_state,
                "t":    time.time(),
                "load": round(self._state["cognitive_load"], 3),
            })
            self._state["state_history"] = self._state["state_history"][-50:]
            self._state["current_state"] = new_state

    def acknowledge_dream(self):
        self._state["cognitive_load"] *= self.LOAD_DECAY_DREAM
        self._state["fatigue"]        *= self.FATIGUE_RECOVERY
        self._state["last_dream_time"] = time.time()
        self._state["total_dreams"]   += 1
        self._state["current_state"]   = "RECOVERED"
        print(f"[PINEAL] Dream acknowledged. Load={self._state['cognitive_load']:.3f} Fatigue={self._state['fatigue']:.3f}")
        self._save()

    def acknowledge_meditation(self):
        self._state["cognitive_load"]    *= self.LOAD_DECAY_MEDITATE
        self._state["last_meditate_time"] = time.time()
        self._state["total_meditations"] += 1
        if self._state["current_state"] == "MEDITATIVE":
            self._state["current_state"] = "ACTIVE"
        self._save()

    def should_dream(self)    -> bool: return self._recommend() == "DREAM"
    def should_meditate(self) -> bool: return self._recommend() == "MEDITATE"
    def should_work(self)     -> bool: return self._recommend() == "WORK"
    def cognitive_load(self)  -> float: return round(self._state["cognitive_load"], 3)
    def fatigue(self)         -> float: return round(self._state["fatigue"], 3)

    def report(self) -> dict:
        load  = self._state["cognitive_load"]
        state = self._state["current_state"]
        filled = int(load * 20)
        return {
            "state":           state,
            "state_meaning":   STATES.get(state, "Unknown"),
            "cognitive_load":  round(load, 3),
            "fatigue":         round(self._state["fatigue"], 3),
            "recommendation":  self._recommend(),
            "uptime_hours":    round(self._state["uptime_seconds"] / 3600, 2),
            "total_cycles":    self._state["total_cycles"],
            "total_dreams":    self._state["total_dreams"],
            "load_bar":        f"[{'█' * filled}{'░' * (20 - filled)}] {load:.0%}",
        }