"""Parameter visualization components"""

import streamlit as st
import plotly.graph_objects as go
import plotly.express as px
import pandas as pd
import numpy as np
from typing import Dict, List, Optional

def plot_parameters(parameters: Dict[str, float], title: str = "Seven Parameters"):
    """Create parameter bar chart"""
    
    params = list(parameters.keys())
    values = list(parameters.values())
    
    # Define colors based on thresholds
    colors = []
    for param, value in parameters.items():
        if param.lower() == 'wcc':
            colors.append('red' if value > 1.58 else 'orange' if value > 1.35 else 'green')
        elif param.lower() == 'kpr':
            colors.append('red' if value > 2.0 else 'orange' if value > 1.6 else 'green')
        elif param.lower() == 'hfsi':
            colors.append('red' if value < 0.4 else 'orange' if value < 0.6 else 'green')
        elif param.lower() == 'becf':
            colors.append('red' if value > 6.0 else 'orange' if value > 4.0 else 'green')
        else:
            colors.append('blue')
    
    fig = go.Figure(data=[
        go.Bar(name='Parameters', x=params, y=values, marker_color=colors)
    ])
    
    fig.update_layout(
        title=title,
        xaxis_title="Parameter",
        yaxis_title="Value",
        height=400
    )
    
    st.plotly_chart(fig, use_container_width=True)

def plot_parameter_timeseries(parameter: str, history: pd.DataFrame):
    """Plot parameter time series"""
    
    fig = px.line(
        history, 
        x='timestamp', 
        y='value',
        title=f"{parameter} Time Series"
    )
    
    # Add threshold lines
    thresholds = {
        'wcc': {'safe': 1.35, 'critical': 1.58},
        'kpr': {'safe': 1.6, 'critical': 2.0},
        'hfsi': {'safe': 0.6, 'critical': 0.4},
        'becf': {'safe': 4.0, 'critical': 6.0},
        'sdb': {'safe': 2.5, 'critical': 1.0},
        'sbsp': {'safe': 0.7, 'critical': 1.2},
        'smvi': {'safe': 0.4, 'critical': 0.6}
    }
    
    if parameter.lower() in thresholds:
        t = thresholds[parameter.lower()]
        fig.add_hline(y=t['safe'], line_dash="dash", line_color="orange")
        fig.add_hline(y=t['critical'], line_dash="dash", line_color="red")
    
    st.plotly_chart(fig, use_container_width=True)

def plot_parameter_comparison(param_data: Dict[str, List[float]], 
                              zones: List[str],
                              parameter: str):
    """Compare parameter across zones"""
    
    df = pd.DataFrame(param_data, index=zones)
    
    fig = px.bar(
        df.T,
        title=f"{parameter} Comparison Across Zones",
        barmode='group'
    )
    
    st.plotly_chart(fig, use_container_width=True)

def plot_correlation_matrix(parameters_df: pd.DataFrame):
    """Plot correlation matrix of parameters"""
    
    corr = parameters_df.corr()
    
    fig = px.imshow(
        corr,
        text_auto=True,
        aspect="auto",
        title="Parameter Correlation Matrix",
        color_continuous_scale='RdBu_r'
    )
    
    st.plotly_chart(fig, use_container_width=True)

def plot_radar_chart(parameters: Dict[str, float], 
                     normalized: bool = True,
                     title: str = "Parameter Radar Chart"):
    """Create radar chart of parameters"""
    
    # Normalize if requested
    if normalized:
        norm_params = {}
        for param, value in parameters.items():
            if param.lower() == 'wcc':
                norm_params[param] = min(value / 1.58, 1.0)
            elif param.lower() == 'kpr':
                norm_params[param] = min(value / 2.0, 1.0)
            elif param.lower() == 'hfsi':
                norm_params[param] = 1 - min(value / 1.0, 1.0)  # Invert
            elif param.lower() == 'becf':
                norm_params[param] = min(value / 6.0, 1.0)
            else:
                norm_params[param] = min(value / 1.0, 1.0)
    else:
        norm_params = parameters
    
    fig = go.Figure(data=go.Scatterpolar(
        r=list(norm_params.values()),
        theta=list(norm_params.keys()),
        fill='toself'
    ))
    
    fig.update_layout(
        polar=dict(
            radialaxis=dict(
                visible=True,
                range=[0, 1]
            )),
        showlegend=False,
        title=title
    )
    
    st.plotly_chart(fig, use_container_width=True)