refactor(step10_new_arch): 同步新架构 view + service 到散点 CSV 模式
This commit is contained in:
@ -1,36 +1,42 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step10 后端计算服务（水色指数反演）
|
||||
====================================
|
||||
Step10 后端计算服务（水色指数反演 · 散点 CSV 模式）
|
||||
====================================================
|
||||
|
||||
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：
|
||||
|
||||
1. 从 ``config`` 字典读取参数；
|
||||
2. 调用 ``WaterIndexProcessor.run_inversion`` 用 ``waterindex.csv`` 中的
|
||||
公式直接处理去耀斑 BSQ 影像，输出各水质参数指数的 GeoTIFF；
|
||||
3. 返回结果字典 ``{status, output_path, message, mode}``。
|
||||
2. 调用 ``WaterIndexCsvProcessor.compute_indices_from_csv``
|
||||
读取 Step 4 输出的 ``sampling_spectra.csv`` 散点，对每行采样点
|
||||
套用 ``waterindex.csv`` 中勾选的公式，输出每公式一个 CSV；
|
||||
3. 返回结果字典 ``{status, output_path, message, mode, ...}``。
|
||||
|
||||
调用入口（由 main_view 在后台 QThread 中调用）：
|
||||
|
||||
execute_step10({
|
||||
"bsq_path": "D:/deglint_output.bsq", # 去耀斑 BSQ 影像（必填）
|
||||
"deglint_img_path": "D:/deglint_output.bsq", # 同上（兼容旧 panel 字段）
|
||||
"hdr_path": "D:/deglint_output.hdr", # ENVI 头文件（可省，自动 .bsq→.hdr 推断）
|
||||
"selected_formulas": ["NDCI", "BGA_Am09KBBI"], # 要处理的公式名列表（空 → 全部）
|
||||
"formula_csv_path": "D:/waterindex.csv", # waterindex.csv 路径（可省，自动探测）
|
||||
"water_mask_path": "D:/water_mask.dat", # 水域掩膜路径（可省）
|
||||
"nodata_value": -9999.0, # NoData 标记值
|
||||
"output_dir": "D:/10_WaterIndex_Images", # 输出目录（可省 → work_dir/10_WaterIndex_Images）
|
||||
"enabled": True,
|
||||
"work_dir": "D:/workspace", # 工作目录（main_view 注入）
|
||||
"sampling_csv_path": "D:/4_sampling/sampling_spectra.csv", # 必填
|
||||
"selected_formulas": ["NDCI", "BGA_Am09KBBI"], # 勾选公式；空 → 全部
|
||||
"formula_csv_path": "D:/waterindex.csv", # waterindex.csv 路径
|
||||
"output_dir": "D:/10_WaterIndex_CSV", # 输出目录；可省
|
||||
"enabled": True,
|
||||
"work_dir": "D:/workspace", # 主窗口注入
|
||||
})
|
||||
|
||||
返回字典字段：
|
||||
|
||||
* ``status`` : "completed" | "skipped" | "error"
|
||||
* ``output_path`` : 输出目录路径（失败时为 None）
|
||||
* ``output_files`` : {公式名: 公式 CSV 路径}（失败时为空 dict）
|
||||
* ``message`` : 人类可读说明
|
||||
* ``mode`` : "watercolor_inversion"（便于 UI 提示）
|
||||
* ``mode`` : "watercolor_inversion_csv"（便于 UI 提示）
|
||||
|
||||
设计要点
|
||||
========
|
||||
- 与 Step 9 (ML 预测) 完全对称的"散点处理模式"：输入 CSV、输出 CSV，
|
||||
坐标列重命名为 longitude/latitude，公式值以列形式追加。
|
||||
- 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）。
|
||||
- 兼容调用方可能仍传旧键（bsq_path / hdr_path / deglint_img_path），检测到时
|
||||
静默忽略并回退到 sampling_spectra.csv 路径解析（避免破坏已有 pipeline 配置）。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
@ -38,11 +44,40 @@ from __future__ import annotations
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from src.new.services._output_resolver import get_user_output_path, is_user_specified, resolve_output_dir
|
||||
from src.new.services._output_resolver import get_user_output_path
|
||||
|
||||
|
||||
def _resolve_sampling_csv_path(
|
||||
sampling_csv_path: Optional[str],
|
||||
work_dir: str,
|
||||
) -> str:
|
||||
"""解析采样点 CSV 路径
|
||||
|
||||
解析顺序：
|
||||
1. 显式传入的 ``sampling_csv_path``
|
||||
2. ``{work_dir}/4_sampling/sampling_spectra.csv``
|
||||
3. ``{work_dir}/4_sampling/`` 下任意 ``.csv`` (取最新)
|
||||
"""
|
||||
if sampling_csv_path and Path(sampling_csv_path).is_file():
|
||||
return sampling_csv_path
|
||||
if not work_dir:
|
||||
return sampling_csv_path or ""
|
||||
|
||||
primary = Path(work_dir) / "4_sampling" / "sampling_spectra.csv"
|
||||
if primary.is_file():
|
||||
return str(primary).replace("\\", "/")
|
||||
|
||||
sample_dir = Path(work_dir) / "4_sampling"
|
||||
if sample_dir.is_dir():
|
||||
cands = sorted(sample_dir.glob("*.csv"), key=lambda p: p.stat().st_mtime, reverse=True)
|
||||
if cands:
|
||||
return str(cands[0]).replace("\\", "/")
|
||||
|
||||
return sampling_csv_path or ""
|
||||
|
||||
|
||||
def _resolve_waterindex_csv(formula_csv_path: Optional[str], work_dir: str) -> str:
|
||||
"""解析 waterindex.csv 路径（与 WaterIndexProcessor.__init__ 默认逻辑保持一致）"""
|
||||
"""解析 waterindex.csv 路径（与 WaterIndexCsvProcessor.__init__ 默认逻辑保持一致）"""
|
||||
if formula_csv_path and Path(formula_csv_path).is_file():
|
||||
return formula_csv_path
|
||||
candidates = [
|
||||
@ -52,142 +87,118 @@ def _resolve_waterindex_csv(formula_csv_path: Optional[str], work_dir: str) -> s
|
||||
]
|
||||
for c in candidates:
|
||||
if c.is_file():
|
||||
return str(c)
|
||||
return str(c).replace("\\", "/")
|
||||
return formula_csv_path or ""
|
||||
|
||||
|
||||
def _resolve_water_mask_path(water_mask_path: Optional[str], work_dir: str) -> Optional[str]:
|
||||
"""解析水域掩膜路径（缺省时尝试从 work_dir/1_water_mask 自动扫盘）"""
|
||||
if water_mask_path and Path(water_mask_path).is_file():
|
||||
return water_mask_path
|
||||
if not work_dir:
|
||||
return None
|
||||
mask_dir = Path(work_dir) / "1_water_mask"
|
||||
if not mask_dir.is_dir():
|
||||
return None
|
||||
for pat in ("*.tif", "*.TIF", "*.dat", "*.DT"):
|
||||
cands = sorted(mask_dir.glob(pat))
|
||||
if cands:
|
||||
return str(cands[0])
|
||||
return None
|
||||
|
||||
|
||||
def _resolve_output_dir(config: Dict[str, Any], work_dir: str) -> tuple[Path, str]:
|
||||
"""根据 output_dir / work_dir 计算水色指数反演结果输出目录
|
||||
|
||||
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
|
||||
（step10 的 output_dir 本身就是一个目录），否则用 work_dir/10_WaterIndex_Images 默认。
|
||||
|
||||
注意：step10 与其他步骤不同——output_dir 直接表示目录而非文件路径，
|
||||
所以使用 Path(user_path) 而非 .parent。
|
||||
（step10 的 output_dir 本身就是一个目录），否则用
|
||||
``work_dir/10_WaterIndex_CSV`` 默认。
|
||||
"""
|
||||
user_path = get_user_output_path(config, "output_dir", "output_path")
|
||||
if user_path:
|
||||
return Path(user_path), "user"
|
||||
return Path(work_dir) / "10_WaterIndex_Images", "default"
|
||||
return Path(work_dir) / "10_WaterIndex_CSV", "default"
|
||||
|
||||
|
||||
def execute_step10(config: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Step 10 后端计算入口——纯函数
|
||||
"""Step 10 后端计算入口——纯函数（散点 CSV 模式）
|
||||
|
||||
Args:
|
||||
config: 由前端 view.get_config() 序列化、再经 main_view 注入 work_dir 的字典
|
||||
|
||||
Returns:
|
||||
标准结果字典 ``{status, output_path, message, mode}``
|
||||
标准结果字典 ``{status, output_path, output_files, message, mode}``
|
||||
"""
|
||||
# ---------- 入参规整 ----------
|
||||
bsq_path: str = config.get("bsq_path") or config.get("deglint_img_path") or ""
|
||||
hdr_path: str = config.get("hdr_path") or ""
|
||||
sampling_csv_path: str = (
|
||||
config.get("sampling_csv_path")
|
||||
or config.get("spectrum_csv_path") # 兼容旧字段
|
||||
or ""
|
||||
)
|
||||
selected_formulas: List[str] = config.get("selected_formulas") or []
|
||||
formula_csv_path: str = config.get("formula_csv_path") or ""
|
||||
water_mask_path: Optional[str] = config.get("water_mask_path")
|
||||
nodata_value: float = float(config.get("nodata_value", -9999.0))
|
||||
output_dir: str = config.get("output_dir") or ""
|
||||
enabled: bool = bool(config.get("enabled", True))
|
||||
work_dir: str = config.get("work_dir") or "."
|
||||
|
||||
output_path, _source = _resolve_output_dir(config, work_dir)
|
||||
mode = "watercolor_inversion"
|
||||
mode = "watercolor_inversion_csv"
|
||||
|
||||
# ---------- 提前失败检查 ----------
|
||||
if not enabled:
|
||||
return {
|
||||
"status": "skipped",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": "用户禁用此步骤（enabled=False）",
|
||||
"mode": mode,
|
||||
}
|
||||
if not bsq_path:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"message": "未提供 BSQ 影像路径（bsq_path / deglint_img_path）",
|
||||
"mode": mode,
|
||||
}
|
||||
if not Path(bsq_path).is_file():
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"message": f"BSQ 影像不存在: {bsq_path}",
|
||||
"mode": mode,
|
||||
}
|
||||
if not hdr_path:
|
||||
# 自动探测 .hdr
|
||||
hdr_path = str(Path(bsq_path).with_suffix(".hdr"))
|
||||
if not Path(hdr_path).is_file():
|
||||
hdr_alt = str(Path(bsq_path).with_suffix(".HDR"))
|
||||
if Path(hdr_alt).is_file():
|
||||
hdr_path = hdr_alt
|
||||
else:
|
||||
hdr_path = ""
|
||||
|
||||
if not hdr_path or not Path(hdr_path).is_file():
|
||||
# 解析采样点 CSV 路径
|
||||
resolved_sampling_csv = _resolve_sampling_csv_path(sampling_csv_path, work_dir)
|
||||
if not resolved_sampling_csv:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"message": f"未找到 ENVI 头文件（与 BSQ 同名 .hdr）: {bsq_path}",
|
||||
"output_files": {},
|
||||
"message": "未提供 sampling_csv_path 且默认位置均找不到 sampling_spectra.csv",
|
||||
"mode": mode,
|
||||
}
|
||||
if not Path(resolved_sampling_csv).is_file():
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": f"采样点 CSV 不存在: {resolved_sampling_csv}",
|
||||
"mode": mode,
|
||||
}
|
||||
|
||||
# ---------- 解析 waterindex.csv ----------
|
||||
# 解析 waterindex.csv
|
||||
resolved_formula_csv = _resolve_waterindex_csv(formula_csv_path, work_dir)
|
||||
if not resolved_formula_csv:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": "未提供 formula_csv_path 且默认位置均找不到 waterindex.csv",
|
||||
"mode": mode,
|
||||
}
|
||||
|
||||
# ---------- 解析水域掩膜（可选） ----------
|
||||
resolved_water_mask = _resolve_water_mask_path(water_mask_path, work_dir)
|
||||
if not Path(resolved_formula_csv).is_file():
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": f"waterindex.csv 不存在: {resolved_formula_csv}",
|
||||
"mode": mode,
|
||||
}
|
||||
|
||||
# ---------- 执行（包一层 try/except 把异常转 dict，避免炸线程） ----------
|
||||
try:
|
||||
from src.core.algorithms.waterindex_inversion import WaterIndexProcessor
|
||||
from src.core.algorithms.waterindex_inversion import (
|
||||
WaterIndexCsvProcessor,
|
||||
)
|
||||
|
||||
print(f"[Step10 Service] 水色指数反演: bsq={bsq_path}")
|
||||
print(f"[Step10 Service] hdr={hdr_path}")
|
||||
print(f"[Step10 Service] 水色指数反演(散点模式): sampling_csv={resolved_sampling_csv}")
|
||||
print(f"[Step10 Service] formula_csv={resolved_formula_csv}")
|
||||
print(f"[Step10 Service] selected_formulas={selected_formulas or '全部'}")
|
||||
if resolved_water_mask:
|
||||
print(f"[Step10 Service] water_mask={resolved_water_mask}")
|
||||
print(f"[Step10 Service] output_dir={output_path}")
|
||||
|
||||
processor = WaterIndexProcessor(resolved_formula_csv)
|
||||
results = processor.run_inversion(
|
||||
deglint_img_path=bsq_path,
|
||||
work_dir=work_dir,
|
||||
formula_csv_path=resolved_formula_csv,
|
||||
processor = WaterIndexCsvProcessor(resolved_formula_csv)
|
||||
out_files = processor.compute_indices_from_csv(
|
||||
sampling_csv_path=resolved_sampling_csv,
|
||||
output_dir=str(output_path).replace("\\", "/"),
|
||||
selected_formulas=selected_formulas or None,
|
||||
water_mask_path=resolved_water_mask,
|
||||
nodata_value=nodata_value,
|
||||
callback=None, # 日志由 main_view 统一接管
|
||||
progress_callback=None, # 日志由 main_view 统一接管
|
||||
)
|
||||
except FileNotFoundError as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": f"文件不存在: {e}",
|
||||
"mode": mode,
|
||||
}
|
||||
@ -195,6 +206,7 @@ def execute_step10(config: Dict[str, Any]) -> Dict[str, Any]:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": f"参数错误: {e}",
|
||||
"mode": mode,
|
||||
}
|
||||
@ -202,16 +214,18 @@ def execute_step10(config: Dict[str, Any]) -> Dict[str, Any]:
|
||||
return {
|
||||
"status": "error",
|
||||
"output_path": None,
|
||||
"output_files": {},
|
||||
"message": f"{type(e).__name__}: {e}",
|
||||
"mode": mode,
|
||||
}
|
||||
|
||||
# ---------- 成功路径 ----------
|
||||
p = Path(output_path)
|
||||
n_results = len(results) if isinstance(results, dict) else 0
|
||||
n_results = len(out_files) if isinstance(out_files, dict) else 0
|
||||
return {
|
||||
"status": "completed",
|
||||
"output_path": str(p).replace("\\", "/"),
|
||||
"message": f"水色指数反演完成，共生成 {n_results} 个指数 GeoTIFF",
|
||||
"output_files": out_files,
|
||||
"message": f"水色指数反演完成，共生成 {n_results} 个指数 CSV",
|
||||
"mode": mode,
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user