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

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

def calc_freq(df: pd.DataFrame) -> pd.DataFrame:
    """Calculates frequency counts and percentages for identifiers."""
    freq_df = df['Identifier'].value_counts().reset_index()
    freq_df.columns = ['Identifier', 'Count']
    total = freq_df['Count'].sum()
    freq_df['Percentage'] = (freq_df['Count'] / total * 100).round(2)
    return freq_df.sort_values('Count', ascending=True)

def plot_freq(stats_df: pd.DataFrame, title: str) -> go.Figure:
    """Generates interactive horizontal bar chart with log x-axis."""
    fig = px.bar(
        stats_df, y='Identifier', x='Count', orientation='h', title=title, log_x=True,
        labels={'Identifier': 'PGN / CAN ID', 'Count': 'Message Count'},
        color='Count', color_continuous_scale='Turbo',
        range_color=(stats_df['Count'].min(), stats_df['Count'].max()),
        hover_data={'Percentage': ':.2f', 'Count': ':,', 'Identifier': True}
    )
    fig.update_layout(
        height=max(600, len(stats_df) * 18),
        autosize=True,
        template='plotly_white',
        xaxis=dict(
            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")),
            #autorange="",
            showgrid=False,
            linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside",
            ticklen=4,
            tickcolor="#cccccc",
            automargin=True,
        ),
        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(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
    )
    fig.update_traces(
        hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>",
        marker_line_width=0,
        texttemplate='%{x:,}',
        textposition='outside',
        textfont=dict(size=10, color='#666666'),
        cliponaxis=False,
        selected=dict(marker=dict(opacity=0.6)),
        unselected=dict(marker=dict(opacity=0.2))
    )
    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"), help="Path to the output HTML report")
    parser.add_argument("title", nargs="?", default="CAN Bus Message Frequency", help="Title for the HTML report")
    args = parser.parse_args()

    df = load_data(args.input)
    stats = calc_freq(df)
    fig = plot_freq(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)