"""Signal Router visualization tab — live on slider change."""

import numpy as np
import streamlit as st

from src.primitives.signal_router import (
    AdaptiveParams,
    SignalRouterConfig,
    simulate_signal_routing,
)
from dashboard.charts import fig_signal_routing


def render():
    st.header("Signal Router")
    st.caption("Parameters update live — no button needed (sub-ms computation).")

    config = st.session_state.get("myco_config")

    col1, col2 = st.columns(2)
    with col1:
        trajectory = st.selectbox(
            "Price trajectory",
            ["stable", "bull", "crash", "volatile"],
            index=3,
        )
        steps = st.slider("Steps", 50, 500, 200)
    with col2:
        k_vol_flow = st.slider("k_vol_flow", 0.0, 5.0, 1.0, 0.1)
        k_dev_alpha = st.slider("k_dev_alpha", 0.0, 5.0, 2.0, 0.1)
        k_vol_fee = st.slider("k_vol_fee", 0.0, 5.0, 1.5, 0.1)
        k_oracle_vel = st.slider("k_oracle_vel", 0.0, 0.1, 0.01, 0.001, format="%.3f")

    # Generate trajectory
    t = np.linspace(0, 1, steps)
    traj_map = {
        "stable": lambda: [1.0] * steps,
        "bull": lambda: (1.0 + t * 0.5).tolist(),
        "crash": lambda: (1.0 - 0.4 * t + 0.1 * np.sin(t * 20)).tolist(),
        "volatile": lambda: (1.0 + 0.3 * np.sin(t * 30) + 0.1 * np.cos(t * 7)).tolist(),
    }
    prices = traj_map[trajectory]()

    # Use config's fee/flow params as base adaptive params
    base_flow = config.flow_threshold if config else 0.1
    base_alpha = config.pamm_params.alpha_bar if config else 10.0
    base_surge = config.surge_fee_rate if config else 0.05

    base = AdaptiveParams(
        flow_threshold=base_flow,
        pamm_alpha_bar=base_alpha,
        surge_fee_rate=base_surge,
        oracle_multiplier_velocity=0.0,
    )
    router_config = SignalRouterConfig(
        k_vol_flow=k_vol_flow,
        k_dev_alpha=k_dev_alpha,
        k_vol_fee=k_vol_fee,
        k_oracle_vel=k_oracle_vel,
    )

    result = simulate_signal_routing(base, router_config, prices)
    result["prices"] = prices  # Add for chart

    st.plotly_chart(fig_signal_routing(result), use_container_width=True)

    # Summary metrics
    m1, m2, m3, m4 = st.columns(4)
    m1.metric("Final Flow Threshold", f"{result['flow_threshold'][-1]:.6f}")
    m2.metric("Final Alpha Bar", f"{result['pamm_alpha_bar'][-1]:.2f}")
    m3.metric("Final Surge Fee", f"{result['surge_fee_rate'][-1]:.6f}")
    m4.metric("Final Volatility", f"{result['volatility'][-1]:.6f}")