# File: frequency.py
# Copyright (C) 2026 Erick Ahmed
# SPDX-License-Identifier: AGPL-3.0-or-later

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

def _format_can_id_vec(s: pd.Series) -> pd.Series:
    s = s.astype('string').str.strip()
    s = s.str.replace(r'^0x', '', case=False, regex=True)
    s = s.str.upper()
    return s.fillna('UNKNOWN').replace('', 'UNKNOWN')

def calculate_frequency(df: pd.DataFrame) -> pd.DataFrame:
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    formatted = _format_can_id_vec(df[can_id_col])

    counts = formatted.value_counts()
    freq_df = pd.DataFrame({
        'Identifier': counts.index,
        'Count': counts.to_numpy(),
    })
    total = counts.sum()
    freq_df['Percentage'] = np.round(freq_df['Count'] / total * 100, 2) if total else 0.0
    return freq_df.sort_values('Count', ascending=True).reset_index(drop=True)

def plot_frequency(stats_df: pd.DataFrame, title: str) -> go.Figure:
    n = len(stats_df)
    fig = go.Figure(go.Bar(
        y=stats_df['Identifier'],
        x=stats_df['Count'],
        orientation='h',
        marker=dict(
            color=stats_df['Count'],
            colorscale='Turbo',
            cmin=int(stats_df['Count'].min()) if n else 0,
            cmax=int(stats_df['Count'].max()) if n else 1,
            line_width=0,
        ),
        customdata=stats_df[['Percentage']].to_numpy(),
        hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>",
        texttemplate='%{x:,}',
        textposition='outside',
        cliponaxis=False,
    ))

    fig.update_layout(
        height=max(600, n * 18),
        autosize=True,
        template='plotly_white',
        xaxis=dict(
            type='log',
            title=dict(text="Message count [log scale]", font=dict(size=13, color="#1a1a1a")),
            side="top",
            dtick=1,
            showgrid=False,
            linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside",
            ticklen=4,
            tickcolor="#cccccc",
        ),
        yaxis=dict(
            title=dict(text="PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
            showgrid=False,
            linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside",
            ticklen=4,
            tickcolor="#cccccc",
            automargin=True,
            type='category',
        ),
        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=200, r=40, t=120, b=60),
        bargap=0.35,
        coloraxis_colorbar=dict(
            title=dict(text='Message Count', side='top'),
            orientation='h',
            thickness=15,
            len=0.35,
            x=1.0,
            xanchor='right',
            y=1.02,
            yanchor='bottom',
            tickformat=',',
            outlinecolor='#cccccc',
            outlinewidth=0.5,
        ),
        title=dict(text=title, font=dict(size=20, color='#1a1a1a'), x=0.5, xanchor='center', pad=dict(b=20)),
    )
    fig.update_xaxes(
        showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
        zeroline=False, linecolor='#bdbdbd', mirror=False,
        tickformat=',',
        minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5),
    )
    fig.update_yaxes(
        showgrid=False, zeroline=False, linecolor='#bdbdbd',
        ticks='outside', ticklen=4, tickcolor='#cccccc', automargin=True,
    )
    return fig

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Analyze CAN bus message frequency")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("output", type=Path, nargs="?", default=Path("freq_report.html"))
    parser.add_argument("title", nargs="?", default="Frequency")
    args = parser.parse_args()

    df = load_data(args.input)
    stats = calculate_frequency(df)
    fig = plot_frequency(stats, 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)