import io

import numpy as np
import pandas as pd
from fastapi import HTTPException
from scipy import signal

from .config import MAX_CSV_BYTES, MAX_PLOT_POINTS


def downsample_for_plot(index, original, filtered):
    total = len(index)
    if total <= MAX_PLOT_POINTS:
        return index, original, filtered, 1
    step = int(np.ceil(total / MAX_PLOT_POINTS))
    return index[::step], original[::step], filtered[::step], step


async def read_csv_upload(file):
    filename = (file.filename or "").lower()
    if filename and not filename.endswith(".csv"):
        raise HTTPException(status_code=400, detail="請上傳 CSV 檔案")
    contents = await file.read(MAX_CSV_BYTES + 1)
    if len(contents) > MAX_CSV_BYTES:
        raise HTTPException(status_code=413, detail=f"CSV 檔案不可超過 {MAX_CSV_BYTES // (1024 * 1024)}MB")
    if not contents.strip():
        raise HTTPException(status_code=400, detail="CSV 不可為空")
    try:
        df = pd.read_csv(io.BytesIO(contents))
    except Exception as e:
        raise HTTPException(status_code=400, detail=f"CSV 讀取失敗: {str(e)}")
    if df.empty:
        raise HTTPException(status_code=400, detail="CSV 不可為空")
    return df


def filtered_csv_data(df, b_vals, a_vals, col_idx):
    if col_idx < 0 or len(df.columns) <= col_idx:
        raise HTTPException(status_code=400, detail="欄位索引超出範圍")
    col_to_filter = df.columns[col_idx]
    x_signal = pd.to_numeric(df[col_to_filter], errors="coerce")
    if x_signal.isna().any():
        raise HTTPException(status_code=400, detail=f"欄位 {col_to_filter} 含有非數值資料")
    x_values = x_signal.to_numpy(dtype=float)
    if not np.isfinite(x_values).all():
        raise HTTPException(status_code=400, detail=f"欄位 {col_to_filter} 含有非有限數值")
    y_signal = signal.lfilter(b_vals, a_vals, x_values)
    return col_to_filter, x_values, y_signal


def filter_preview_response(df, b_vals, a_vals, col_idx):
    col_to_filter, x_signal, y_signal = filtered_csv_data(df, b_vals, a_vals, col_idx)
    index, original, filtered, step = downsample_for_plot(df.index.to_numpy(), x_signal, y_signal)

    return {
        "index": index.tolist(),
        "original": original.tolist(),
        "filtered": filtered.tolist(),
        "col_name": col_to_filter,
        "total_points": int(len(df.index)),
        "plot_points": int(len(index)),
        "downsample_step": int(step),
    }


def filtered_csv_text(df, b_vals, a_vals, col_idx):
    col_to_filter, _, y_signal = filtered_csv_data(df, b_vals, a_vals, col_idx)
    df[f"{col_to_filter}_filtered"] = y_signal
    csv_buffer = io.StringIO()
    df.to_csv(csv_buffer, index=False)
    return csv_buffer.getvalue()