232 lines
8.7 KiB
Python
232 lines
8.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Step10 后端计算服务（水色指数反演 · 散点 CSV 模式）
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====================================================
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纯计算函数——绝对不引用 PyQt、绝对不引用 main_view、绝对不读写全局变量。它只：
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1. 从 ``config`` 字典读取参数；
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2. 调用 ``WaterIndexCsvProcessor.compute_indices_from_csv``
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读取 Step 4 输出的 ``sampling_spectra.csv`` 散点，对每行采样点
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套用 ``waterindex.csv`` 中勾选的公式，输出每公式一个 CSV；
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3. 返回结果字典 ``{status, output_path, message, mode, ...}``。
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调用入口（由 main_view 在后台 QThread 中调用）：
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execute_step10({
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"sampling_csv_path": "D:/4_sampling/sampling_spectra.csv", # 必填
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"selected_formulas": ["NDCI", "BGA_Am09KBBI"], # 勾选公式；空 → 全部
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"formula_csv_path": "D:/waterindex.csv", # waterindex.csv 路径
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"output_dir": "D:/10_WaterIndex_CSV", # 输出目录；可省
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"enabled": True,
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"work_dir": "D:/workspace", # 主窗口注入
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})
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返回字典字段：
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* ``status`` : "completed" | "skipped" | "error"
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* ``output_path`` : 输出目录路径（失败时为 None）
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* ``output_files`` : {公式名: 公式 CSV 路径}（失败时为空 dict）
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* ``message`` : 人类可读说明
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* ``mode`` : "watercolor_inversion_csv"（便于 UI 提示）
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设计要点
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========
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- 与 Step 9 (ML 预测) 完全对称的"散点处理模式"：输入 CSV、输出 CSV，
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坐标列重命名为 longitude/latitude，公式值以列形式追加。
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- 旧"读 BSQ 全图 → 输出 GeoTIFF"模式已废弃（科学上误差大且与 GIS 栅格计算器重复）。
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- 兼容调用方可能仍传旧键（bsq_path / hdr_path / deglint_img_path），检测到时
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静默忽略并回退到 sampling_spectra.csv 路径解析（避免破坏已有 pipeline 配置）。
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"""
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from __future__ import annotations
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from src.new.services._output_resolver import get_user_output_path
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def _resolve_sampling_csv_path(
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sampling_csv_path: Optional[str],
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work_dir: str,
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) -> str:
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"""解析采样点 CSV 路径
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解析顺序：
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1. 显式传入的 ``sampling_csv_path``
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2. ``{work_dir}/4_sampling/sampling_spectra.csv``
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3. ``{work_dir}/4_sampling/`` 下任意 ``.csv`` (取最新)
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"""
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if sampling_csv_path and Path(sampling_csv_path).is_file():
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return sampling_csv_path
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if not work_dir:
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return sampling_csv_path or ""
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primary = Path(work_dir) / "4_sampling" / "sampling_spectra.csv"
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if primary.is_file():
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return str(primary).replace("\\", "/")
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sample_dir = Path(work_dir) / "4_sampling"
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if sample_dir.is_dir():
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cands = sorted(sample_dir.glob("*.csv"), key=lambda p: p.stat().st_mtime, reverse=True)
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if cands:
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return str(cands[0]).replace("\\", "/")
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return sampling_csv_path or ""
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def _resolve_waterindex_csv(formula_csv_path: Optional[str], work_dir: str) -> str:
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"""解析 waterindex.csv 路径（与 WaterIndexCsvProcessor.__init__ 默认逻辑保持一致）"""
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if formula_csv_path and Path(formula_csv_path).is_file():
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return formula_csv_path
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candidates = [
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Path(work_dir) / "waterindex.csv",
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Path(work_dir) / "model" / "waterindex.csv",
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Path("src/gui/model/waterindex.csv"),
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]
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for c in candidates:
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if c.is_file():
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return str(c).replace("\\", "/")
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return formula_csv_path or ""
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def _resolve_output_dir(config: Dict[str, Any], work_dir: str) -> tuple[Path, str]:
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"""根据 output_dir / work_dir 计算水色指数反演结果输出目录
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使用共享解析器强制执行"用户优先"规则——用户指定 output_dir 时直接用其值
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（step10 的 output_dir 本身就是一个目录），否则用
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``work_dir/10_WaterIndex_CSV`` 默认。
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"""
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user_path = get_user_output_path(config, "output_dir", "output_path")
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if user_path:
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return Path(user_path), "user"
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return Path(work_dir) / "10_WaterIndex_CSV", "default"
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def execute_step10(config: Dict[str, Any]) -> Dict[str, Any]:
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"""Step 10 后端计算入口——纯函数（散点 CSV 模式）
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Args:
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config: 由前端 view.get_config() 序列化、再经 main_view 注入 work_dir 的字典
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Returns:
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标准结果字典 ``{status, output_path, output_files, message, mode}``
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"""
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# ---------- 入参规整 ----------
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sampling_csv_path: str = (
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config.get("sampling_csv_path")
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or config.get("spectrum_csv_path") # 兼容旧字段
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or ""
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)
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selected_formulas: List[str] = config.get("selected_formulas") or []
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formula_csv_path: str = config.get("formula_csv_path") or ""
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output_dir: str = config.get("output_dir") or ""
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enabled: bool = bool(config.get("enabled", True))
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work_dir: str = config.get("work_dir") or "."
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output_path, _source = _resolve_output_dir(config, work_dir)
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mode = "watercolor_inversion_csv"
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# ---------- 提前失败检查 ----------
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if not enabled:
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return {
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"status": "skipped",
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"output_path": None,
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"output_files": {},
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"message": "用户禁用此步骤（enabled=False）",
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"mode": mode,
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}
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# 解析采样点 CSV 路径
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resolved_sampling_csv = _resolve_sampling_csv_path(sampling_csv_path, work_dir)
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if not resolved_sampling_csv:
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": "未提供 sampling_csv_path 且默认位置均找不到 sampling_spectra.csv",
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"mode": mode,
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}
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if not Path(resolved_sampling_csv).is_file():
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": f"采样点 CSV 不存在: {resolved_sampling_csv}",
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"mode": mode,
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}
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# 解析 waterindex.csv
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resolved_formula_csv = _resolve_waterindex_csv(formula_csv_path, work_dir)
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if not resolved_formula_csv:
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": "未提供 formula_csv_path 且默认位置均找不到 waterindex.csv",
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"mode": mode,
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}
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if not Path(resolved_formula_csv).is_file():
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": f"waterindex.csv 不存在: {resolved_formula_csv}",
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"mode": mode,
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}
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# ---------- 执行（包一层 try/except 把异常转 dict，避免炸线程） ----------
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try:
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from src.core.algorithms.waterindex_inversion import (
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WaterIndexCsvProcessor,
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)
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print(f"[Step10 Service] 水色指数反演(散点模式): sampling_csv={resolved_sampling_csv}")
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print(f"[Step10 Service] formula_csv={resolved_formula_csv}")
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print(f"[Step10 Service] selected_formulas={selected_formulas or '全部'}")
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print(f"[Step10 Service] output_dir={output_path}")
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processor = WaterIndexCsvProcessor(resolved_formula_csv)
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out_files = processor.compute_indices_from_csv(
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sampling_csv_path=resolved_sampling_csv,
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output_dir=str(output_path).replace("\\", "/"),
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selected_formulas=selected_formulas or None,
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progress_callback=None, # 日志由 main_view 统一接管
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)
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except FileNotFoundError as e:
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": f"文件不存在: {e}",
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"mode": mode,
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}
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except ValueError as e:
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": f"参数错误: {e}",
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"mode": mode,
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}
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except Exception as e: # noqa: BLE001 —— service 层兜底捕获所有
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return {
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"status": "error",
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"output_path": None,
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"output_files": {},
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"message": f"{type(e).__name__}: {e}",
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"mode": mode,
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}
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# ---------- 成功路径 ----------
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p = Path(output_path)
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n_results = len(out_files) if isinstance(out_files, dict) else 0
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return {
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"status": "completed",
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"output_path": str(p).replace("\\", "/"),
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"output_files": out_files,
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"message": f"水色指数反演完成，共生成 {n_results} 个指数 CSV",
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"mode": mode,
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}
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