"""
Smoke test for Step 10 散点 CSV 模式 (WaterIndexCsvProcessor)

模拟 Step 4 输出格式 (sampling_spectra.csv):
    x_coord, y_coord, pixel_x, pixel_y, "400.000000", "401.000000", ...

验证 WaterIndexCsvProcessor.compute_indices_from_csv:
  1. 正确读取 x_coord/y_coord → 重命名为 longitude/latitude
  2. 正确识别数字列名 = 光谱列
  3. 复用 WaterQualityIndexCalculator 逐行计算
  4. 输出每个公式一个 CSV,三列严格为 longitude, latitude, <formula_name>
  5. 公式值数量级合理 (非 NaN,非 inf)
"""
import os
import sys
import tempfile
import shutil
from pathlib import Path

# 让脚本能找到项目根
PROJECT_ROOT = Path(__file__).parent
sys.path.insert(0, str(PROJECT_ROOT))


def create_synthetic_sampling_csv(path: str, n_points: int = 5):
    """模拟 Step 4 输出: x_coord, y_coord, pixel_x, pixel_y, 数字列名光谱"""
    import csv
    # 选一组关键波段（确保 waterindex.csv 中的 BGA_Am09KBBI 等公式都能找到）
    wavelengths = [400.0, 443.0, 458.0, 486.0, 500.0, 510.0, 531.0, 547.0, 555.0,
                   615.0, 622.0, 629.0, 644.0, 658.0, 665.0, 672.0, 681.0, 686.0,
                   700.0, 709.0, 714.0, 715.0, 753.0, 857.0, 900.0]
    fieldnames = ['x_coord', 'y_coord', 'pixel_x', 'pixel_y'] + [f'{w:.6f}' for w in wavelengths]

    with open(path, 'w', newline='', encoding='utf-8-sig') as f:
        writer = csv.DictWriter(f, fieldnames=fieldnames)
        writer.writeheader()
        for i in range(n_points):
            # 模拟水体光谱（典型内陆湖泊反射率 0.005-0.05）
            row = {
                'x_coord': 100.0 + i * 10,
                'y_coord': 30.0 + i * 5,
                'pixel_x': 100 + i,
                'pixel_y': 30 + i,
            }
            for w in wavelengths:
                # 简单合成光谱: 蓝光 < 红光 + 一点叶绿素峰
                base = 0.01 + 0.0001 * (w - 400)
                chl_peak = 0.005 * (1 - abs(w - 560) / 200) if abs(w - 560) < 200 else 0
                row[f'{w:.6f}'] = round(base + chl_peak, 6)
            writer.writerow(row)


def run_smoke():
    print("=" * 70)
    print("Step 10 散点 CSV 模式 Smoke Test")
    print("=" * 70)

    tmpdir = tempfile.mkdtemp(prefix="step10_smoke_")
    print(f"Tempdir: {tmpdir}")

    sampling_csv = os.path.join(tmpdir, "sampling_spectra.csv")
    output_dir = os.path.join(tmpdir, "10_WaterIndex_CSV")
    os.makedirs(output_dir, exist_ok=True)

    # 1) 创建合成 sampling CSV
    create_synthetic_sampling_csv(sampling_csv, n_points=5)
    print(f"Created sampling CSV: {sampling_csv}")
    with open(sampling_csv, encoding='utf-8-sig') as f:
        header_line = f.readline().strip()
    print(f"  header: {header_line[:120]}...")

    # 2) 找到项目自带的 waterindex.csv
    waterindex_csv = PROJECT_ROOT / "src" / "gui" / "model" / "waterindex.csv"
    print(f"Using waterindex.csv: {waterindex_csv}")
    assert waterindex_csv.is_file(), "waterindex.csv not found!"

    # 3) 调 WaterIndexCsvProcessor
    # 注意：父包 __init__.py 顶部有 `from osgeo import gdal, osr`，
    #       在没装 gdal 的 venv 里任何 from ...waterindex_inversion import ... 都会炸。
    #       这里用 importlib 按文件路径直接加载 csv_processor.py 子模块，
    #       完全绕开 __init__.py 的 osgeo 加载。
    import importlib.util as _ilu
    _csv_proc_path = (
        PROJECT_ROOT / "src" / "core" / "algorithms" / "waterindex_inversion"
        / "csv_processor.py"
    )
    _spec = _ilu.spec_from_file_location("waterindex_csv_processor", _csv_proc_path)
    _mod = _ilu.module_from_spec(_spec)
    sys.modules["waterindex_csv_processor"] = _mod
    _spec.loader.exec_module(_mod)
    WaterIndexCsvProcessor = _mod.WaterIndexCsvProcessor

    progress_log = []
    def progress_cb(msg, pct):
        progress_log.append((msg, pct))

    proc = WaterIndexCsvProcessor(str(waterindex_csv))
    print(f"\n[Step] compute_indices_from_csv...")
    out_files = proc.compute_indices_from_csv(
        sampling_csv_path=sampling_csv,
        output_dir=output_dir,
        selected_formulas=["BGA_Am09KBBI", "BGA_Da052BDA", "BGA_Be16NDPhyI"],
        progress_callback=progress_cb,
    )

    print(f"\n[Result] Generated {len(out_files)} CSV files:")
    for name, path in out_files.items():
        size = os.path.getsize(path)
        print(f"  {name:30s} -> {os.path.basename(path)}  ({size} bytes)")

    # 4) 验证每个输出 CSV 的列结构
    print(f"\n[Verify] Column structure check:")
    all_pass = True
    import pandas as pd
    for name, path in out_files.items():
        df = pd.read_csv(path, encoding='utf-8-sig')
        cols = list(df.columns)
        expected = ['longitude', 'latitude', name]
        ok = (cols == expected) and (len(df) == 5)
        flag = "✓" if ok else "✗"
        if not ok:
            all_pass = False
        print(f"  {flag} {name:30s}  cols={cols}  rows={len(df)}")

    # 5) 验证坐标重命名
    print(f"\n[Verify] Coordinate rename (x_coord→longitude, y_coord→latitude):")
    sample = pd.read_csv(out_files[list(out_files.keys())[0]], encoding='utf-8-sig')
    print(f"  longitude values: {sample['longitude'].tolist()}")
    print(f"  latitude  values: {sample['latitude'].tolist()}")
    coord_ok = (sample['longitude'].iloc[0] == 100.0 and
                sample['latitude'].iloc[0] == 30.0)
    if not coord_ok:
        all_pass = False
    print(f"  {'✓' if coord_ok else '✗'} coordinate rename correct")

    # 6) 验证公式值非 NaN
    print(f"\n[Verify] Formula values (no NaN):")
    for name, path in out_files.items():
        df = pd.read_csv(path, encoding='utf-8-sig')
        col = df[name]
        n_nan = col.isna().sum()
        n_inf = ((col == float('inf')) | (col == float('-inf'))).sum()
        all_nan = col.dropna().empty
        if n_nan > 0 or n_inf > 0 or all_nan:
            print(f"  ✗ {name:30s}: NaN={n_nan} Inf={n_inf} empty={all_nan}")
            print(f"     values: {col.tolist()}")
            all_pass = False
        else:
            mn, mx = col.min(), col.max()
            print(f"  ✓ {name:30s}: range=[{mn:.4f}, {mx:.4f}]")

    # 7) 进度回调检查
    print(f"\n[Verify] Progress callback:")
    print(f"  Total progress events: {len(progress_log)}")
    if progress_log:
        first_msg, first_pct = progress_log[0]
        last_msg, last_pct = progress_log[-1]
        print(f"  First: ({first_pct:.1f}%) {first_msg}")
        print(f"  Last : ({last_pct:.1f}%) {last_msg}")
        progress_ok = (last_pct == 100.0)
        if not progress_ok:
            all_pass = False
        print(f"  {'✓' if progress_ok else '✗'} last progress = 100%")

    # 8) 总结
    print(f"\n{'=' * 70}")
    if all_pass:
        print(f"✓ ALL CHECKS PASSED")
    else:
        print(f"✗ SOME CHECKS FAILED — inspect output above")
    print(f"{'=' * 70}")

    # 清理
    shutil.rmtree(tmpdir, ignore_errors=True)
    return all_pass


if __name__ == "__main__":
    success = run_smoke()
    sys.exit(0 if success else 1)