import argparse
from pathlib import Path
import pandas as pd
import plotly.graph_objects as go
from utils.extractor import load_data

def _format_can_id(x):
    if pd.isna(x):
        return "UNKNOWN"
    s = str(x).strip()
    if not s:
        return "UNKNOWN"
    if s.lower().startswith('0x'):
        s = s[2:]
    return s.upper()

def prepare_data(df, target_id):
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    df['Formatted_ID'] = df[can_id_col].apply(_format_can_id)
    target_id_clean = _format_can_id(target_id)
    filtered = df[df['Formatted_ID'] == target_id_clean].copy()

    byte_cols = [f"b{i}" for i in range(8)]
    for col in byte_cols:
        filtered[col] = pd.to_numeric(
            filtered[col].apply(lambda x: int(x, 16) if pd.notna(x) else None),
            errors='coerce'
        )

    filtered = filtered.sort_values('Timestamp')
    mask = (filtered[byte_cols] != filtered[byte_cols].shift()).any(axis=1)
    filtered = filtered[mask]

    return filtered, byte_cols

def plot_bits(df, byte_cols, can_id, title):
    fig = go.Figure()

    colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf']

    for i, col in enumerate(byte_cols):
        fig.add_trace(go.Scatter(
            x=df['Timestamp'],
            y=df[col],
            mode='lines',
            line=dict(shape='hv', width=2, color=colors[i]),
            name=col.upper(),
            hovertemplate=f"<b>{col.upper()}</b><br>Time: %{{x}}<br>Value: %{{y}}<extra></extra>"
        ))

    fig.update_layout(
        height=600,
        autosize=True,
        template='plotly_white',
        title=dict(
            text=f"{title} - ID: {can_id}",
            font=dict(size=20, color='#1a1a1a'),
            x=0.5, xanchor='center',
            pad=dict(b=20)
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color='#2a2a2a'),
        hoverlabel=dict(
            bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor='#cccccc'
        ),
        margin=dict(l=60, r=40, t=120, b=60),
        legend=dict(
            title=dict(text="Bytes"),
            bgcolor="rgba(255,255,255,0.8)",
            bordercolor="#cccccc",
            borderwidth=1,
            font=dict(size=12, color="#2a2a2a")
        ),
        xaxis=dict(
            title=dict(text="Timestamp", font=dict(size=13, color="#1a1a1a")),
            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
            zeroline=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside", ticklen=4, tickcolor="#cccccc",
            minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5)
        ),
        yaxis=dict(
            title=dict(text="Byte Value", font=dict(size=13, color="#1a1a1a")),
            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
            zeroline=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside", ticklen=4, tickcolor="#cccccc"
        )
    )

    return fig

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Visualize CAN bus byte changes over time")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("can_id", type=str, help="CAN ID to visualize")
    parser.add_argument("output", type=Path, nargs="?", default=Path("bits_report.html"), help="Path to the output HTML report")
    parser.add_argument("title", nargs="?", default="Byte Visualization", help="Title for the HTML report")
    args = parser.parse_args()

    df = load_data(args.input)
    filtered_df, byte_cols = prepare_data(df, args.can_id)
    fig = plot_bits(filtered_df, byte_cols, args.can_id, title=args.title)

    config = {
        'responsive': True,
        'displaylogo': False,
        'scrollZoom': True,
        'modeBarButtonsToAdd': ['toggleSpikelines'],
        'toImageButtonOptions': {'format': 'png', 'scale': 2}
    }
    fig.write_html(str(args.output), include_plotlyjs='cdn', config=config)