src/viz_engine.py

import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
from src.config_manager import get_config

def get_sdg_colors():
    """
    Get SDG colors from configuration or use defaults.
    """
    config = get_config()
    sdg_colors_config = config.get('visualization.sdg_colors', {})
    
    # Default colors if not in config
    default_colors = {
        "1": '#E5243B',   # No Poverty
        "2": '#DDA63A',   # Zero Hunger
        "3": '#4C9F38',   # Good Health and Well-being
        "4": '#C5192D',   # Quality Education
        "5": '#FF3A21',   # Gender Equality
        "6": '#26BDE2',   # Clean Water and Sanitation
        "7": '#FCC30B',   # Affordable and Clean Energy
        "8": '#A21942',   # Decent Work and Economic Growth
        "9": '#FD6925',   # Industry, Innovation and Infrastructure
        "10": '#DD1367',  # Reduced Inequalities
        "11": '#FD9D24',  # Sustainable Cities and Communities
        "12": '#BF8B2E',  # Responsible Consumption and Production
        "13": '#3F7E44',  # Climate Action
        "14": '#0A97D9',  # Life Below Water
        "15": '#56C02B',  # Life on Land
        "16": '#00689D',  # Peace, Justice and Strong Institutions
        "17": '#19486A'   # Partnerships for the Goals
    }
    
    # Use config colors or fallback to defaults
    colors = sdg_colors_config or default_colors
    
    # Convert string keys to integers
    return {int(k): v for k, v in colors.items()}


# Get colors from configuration
SDG_COLORS = get_sdg_colors()

SDG_NAMES = {
    1: 'No Poverty',
    2: 'Zero Hunger',
    3: 'Good Health',
    4: 'Quality Education',
    5: 'Gender Equality',
    6: 'Clean Water',
    7: 'Clean Energy',
    8: 'Decent Work',
    9: 'Industry & Innovation',
    10: 'Reduced Inequalities',
    11: 'Sustainable Cities',
    12: 'Responsible Consumption',
    13: 'Climate Action',
    14: 'Life Below Water',
    15: 'Life on Land',
    16: 'Peace & Justice',
    17: 'Partnerships'
}

def create_world_map(df):
    """
    Create a Choropleth map for the overall SDG index score.
    """
    fig = px.choropleth(
        df,
        locations="country",
        locationmode="country names",
        color="sdg_index_score",
        hover_name="country",
        hover_data={'sdg_index_score': ':.1f'},
        color_continuous_scale=[
            [0, '#FF6B6B'],
            [0.25, '#FFE66D'],
            [0.5, '#4ECDC4'],
            [0.75, '#45B7D1'],
            [1.0, '#2ECC71']
        ],
        title="🌐 Global SDG Index Progress (Latest Year)",
        labels={'sdg_index_score': 'SDG Index Score'}
    )
    fig.update_layout(
        geo=dict(
            showframe=False,
            showcoastlines=True,
            coastlinecolor='#ddd',
            projection_type='equirectangular',
            bgcolor='rgba(0,0,0,0)',
            landcolor='#f5f5f5',
            countrycolor='#fff'
        ),
        margin=dict(l=0, r=0, b=0, t=50),
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(0,0,0,0)',
        coloraxis_colorbar=dict(
            title=dict(text="Score", font=dict(size=14)),
            tickfont=dict(size=12),
            len=0.6,
            thickness=15
        ),
        title=dict(font=dict(size=18, color='#0d4f6c'))
    )
    return fig

def create_radar_chart(df, country, year):
    """
    Create a radar chart for the 17 SDG goals with official colors and labels.
    """
    target_row = df[(df['country'] == country) & (df['year'] == year)]
    if target_row.empty:
        return None
    
    # Use goal names as labels for better clarity
    categories = [f"SDG {i}: {SDG_NAMES[i]}" for i in range(1, 18)]
    
    # Robustly extract values as scalars
    values = []
    for i in range(1, 18):
        col_name = f"goal_{i}_score"
        if col_name not in target_row.columns:
            values.append(0.0)
            continue
            
        val = target_row[col_name]
        if isinstance(val, pd.DataFrame):
            val = val.iloc[0, 0]
        elif isinstance(val, pd.Series):
            val = val.iloc[0]
            
        try:
            val = float(val)
            if pd.isna(val): val = 0.0
        except:
            val = 0.0
        values.append(val)
        
    # Close the radar loop
    values_closed = values + [values[0]]
    categories_closed = categories + [categories[0]]
    
    fig = go.Figure()
    
    # Add the radar area
    fig.add_trace(go.Scatterpolar(
        r=values_closed,
        theta=categories_closed,
        fill='toself',
        fillcolor='rgba(59, 130, 246, 0.2)',
        line=dict(color='#3b82f6', width=2),
        name=f'{country} ({year})',
        hoverinfo='skip'  # Disable hover for area to avoid interference with markers
    ))
    
    # Add individual markers for each goal with their official colors
    for i, (r, cat) in enumerate(zip(values, categories)):
        goal_id = i + 1
        fig.add_trace(go.Scatterpolar(
            r=[r],
            theta=[cat],
            mode='markers',
            marker=dict(
                color=SDG_COLORS.get(goal_id, '#888'),
                size=12,
                line=dict(color='white', width=1)
            ),
            name=f"SDG {goal_id}",
            hovertemplate=f"<b>{SDG_NAMES[goal_id]}</b><br>Score: {r:.1f}<extra></extra>"
        ))
    
    fig.update_layout(
        polar=dict(
            radialaxis=dict(
                visible=True,
                range=[0, 100],
                tickfont=dict(size=9),
                gridcolor='#e2e8f0',
                angle=0,
                tickangle=0
            ),
            angularaxis=dict(
                tickfont=dict(size=10, color='#64748b'),
                gridcolor='#e2e8f0',
                rotation=90,
                direction='clockwise'
            ),
            bgcolor='rgba(255, 255, 255, 0)'
        ),
        showlegend=False,
        title=dict(
            text=f"🎯 {country} SDG Performance ({year})",
            font=dict(size=18, color='#1e293b'),
            x=0.5,
            y=0.95
        ),
        margin=dict(t=80, b=40, l=80, r=80),
        height=450,
        paper_bgcolor='rgba(0,0,0,0)'
    )
    return fig

def create_trend_chart(df_filtered):
    """
    Create a multi-line chart for SDG trends with 2025 styling.
    """
    fig = px.line(
        df_filtered,
        x="year",
        y="sdg_index_score",
        title="📈 Overall SDG Index Score Trend (2000-2025)",
        markers=True,
        line_shape="spline"
    )
    
    fig.update_traces(
        line=dict(color='#3b82f6', width=4),
        marker=dict(size=10, symbol='circle', line=dict(width=2, color='white')),
        hovertemplate='<b>Year: %{x}</b><br>SDG Index: %{y:.2f}<extra></extra>'
    )
    
    fig.update_layout(
        xaxis=dict(
            title=dict(text="Year", font=dict(size=14)),
            gridcolor='#f1f5f9',
            dtick=2
        ),
        yaxis=dict(
            title=dict(text="Overall Score", font=dict(size=14)),
            gridcolor='#f1f5f9',
            range=[
                df_filtered['sdg_index_score'].min() * 0.95 if not df_filtered['sdg_index_score'].dropna().empty else 0,
                df_filtered['sdg_index_score'].max() * 1.05 if not df_filtered['sdg_index_score'].dropna().empty else 100
            ]
        ),
        annotations=[
            dict(
                text="Data: SDSN 2025 | Unit: Score (0-100)",
                showarrow=False,
                xref="paper", yref="paper",
                x=1, y=-0.2,
                font=dict(size=10, color="gray")
            )
        ],
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(255, 255, 255, 0.5)',
        hovermode='x unified',
        height=450
    )
    
    return fig

def create_detailed_trend_chart(df_filtered):
    """
    Create a detailed multi-line chart for individual goals.
    """
    cols = [f"goal_{i}_score" for i in range(1, 18)]
    
    # Melt the dataframe for plotting
    df_melted = df_filtered.melt(
        id_vars=['year'],
        value_vars=cols,
        var_name='Goal',
        value_name='Score'
    )
    
    # Map goal numbers to SDG names and colors
    df_melted['Goal_Num'] = df_melted['Goal'].str.extract(r'goal_(\d+)_score').astype(int)
    df_melted['Goal_Name'] = df_melted['Goal_Num'].map(lambda x: f"SDG {x}: {SDG_NAMES[x]}")
    df_melted['Color'] = df_melted['Goal_Num'].map(SDG_COLORS)
    
    fig = go.Figure()
    
    for goal_num in range(1, 18):
        goal_data = df_melted[df_melted['Goal_Num'] == goal_num]
        fig.add_trace(go.Scatter(
            x=goal_data['year'],
            y=goal_data['Score'],
            mode='lines+markers',
            name=f"SDG {goal_num}",
            line=dict(color=SDG_COLORS[goal_num], width=2),
            marker=dict(size=6),
            hovertemplate=f'{SDG_NAMES[goal_num]}<br>Year: %{{x}}<br>Score: %{{y:.1f}}<extra></extra>'
        ))
    
    fig.update_layout(
        title=dict(
            text="📊 Individual SDG Goals Trends",
            font=dict(size=16, color='#0d4f6c')
        ),
        xaxis=dict(
            title=dict(text="Year", font=dict(size=13)),
            gridcolor='#eee'
        ),
        yaxis=dict(
            title=dict(text="Score", font=dict(size=13)),
            range=[0, 100],
            gridcolor='#eee'
        ),
        legend=dict(
            orientation='h',
            yanchor='bottom',
            y=-0.4,
            xanchor='center',
            x=0.5,
            font=dict(size=10)
        ),
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(248, 250, 252, 0.5)',
        height=500,
        margin=dict(b=120)
    )
    
    return fig