测试修改

This commit is contained in:
DXC
2026-06-23 14:39:54 +08:00
parent c4aa246c95
commit b8d263e494
21 changed files with 595 additions and 2706 deletions

View File

@ -1,14 +1,24 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
依赖订阅混入模块
依赖订阅混入模块(架构解耦版)
新规则dependencies 字典的键名 = 下游目标控件的真实属性名,
第三元素source_attr= 上游源控件的真实属性名。
提供 subscribe_panel_to_dependencies() 函数,让步骤面板根据
PANEL_REGISTRY 中声明的 dependencies 自动向 global_event_bus
订阅 OutputUpdated 事件。当上游步骤产出落地时,面板自动将路径
填入对应的 FileSelectWidget无需主窗口手工传导。
内含:
- 自动识别下游 widget按 dict 键名查找)
- 非空保护:仅在目标框为空时填充,避免覆盖用户已选路径
- 智能目录转换:目标控件名含 'dir' 且事件携带的是文件路径时,自动取父目录
"""
import os
from src.gui.core.event_bus import global_event_bus
@ -19,18 +29,21 @@ def subscribe_panel_to_dependencies(panel, step_id, dependencies):
匹配时,自动将路径填入面板对应的 FileSelectWidget。
Args:
panel: 步骤面板实例QWidget 子类)
panel: 步骤面板实例QWidget 子类),即下游目标面板
step_id: 当前面板的 step_id仅用于日志非匹配键
dependencies: dict, {input_field: (dep_step, output_type, panel_attr)}
dependencies: dict, {target_field: (dep_step, output_type, source_attr)}
target_field 必须等于 panel 上某个控件的属性名
source_attr 仅作回放端使用(本函数不直接依赖)
"""
if not dependencies:
return
for _input_field, (dep_step, output_type, panel_attr) in dependencies.items():
_make_subscription(panel, dep_step, output_type, panel_attr)
# 注意:我们使用字典的键名 (_input_field) 作为唯一的下游目标框名查找依据
for _input_field, (dep_step, output_type, source_panel_attr) in dependencies.items():
_make_subscription(panel, dep_step, output_type, _input_field)
def _make_subscription(panel, dep_step, output_type, panel_attr):
def _make_subscription(panel, dep_step, output_type, target_widget_name):
"""为单个依赖项创建事件订阅。使用工厂函数避免闭包变量延迟绑定。"""
def callback(data):
@ -39,7 +52,7 @@ def _make_subscription(panel, dep_step, output_type, panel_attr):
if data.get('output_type') != output_type:
return
widget = getattr(panel, panel_attr, None)
widget = getattr(panel, target_widget_name, None)
if widget is None:
return
@ -56,6 +69,10 @@ def _make_subscription(panel, dep_step, output_type, panel_attr):
if not path:
return
# 智能转换:如果要的是目录,但来的是文件,自动截取父目录
if 'dir' in target_widget_name.lower() and os.path.isfile(path):
path = os.path.dirname(path)
if hasattr(widget, 'set_path'):
widget.set_path(path)
elif hasattr(widget, 'setText'):

View File

@ -169,11 +169,12 @@ class PanelFactory:
if placeholder is not None and self._tab_widget is not None:
tab_title = self._tab_widget.tabText(tab_index)
tab_icon = self._tab_widget.tabIcon(tab_index)
current_active = self._tab_widget.currentIndex() # 记住当前正在看的 Tab
self._tab_widget.blockSignals(True)
try:
self._tab_widget.removeTab(tab_index)
self._tab_widget.insertTab(tab_index, scroll, tab_icon, tab_title)
self._tab_widget.setCurrentIndex(tab_index)
self._tab_widget.setCurrentIndex(current_active) # 恢复原来的 Tab严禁后台预加载引发跳页
finally:
self._tab_widget.blockSignals(False)
@ -226,33 +227,40 @@ class PanelFactory:
self._replay_live_panel_inputs()
def _replay_live_panel_inputs(self):
"""遍历 PANEL_REGISTRY 依赖声明,从已加载面板实时读取属性值。
"""遍历 PANEL_REGISTRY 依赖声明,从已加载面板实时读取属性值并强制广播
若源面板已实例化,读取其 widget 的当前值并发布为 OutputUpdated
确保懒加载面板能收到全局输入(如 Step1.img_file → reference_img
架构解耦2026-06-22第三个元素 source_attr 现在明确代表上游控件的真实名字
不再混用语义。回放端仅依赖 source_attr 在 SOURCE 面板上能命中 widget
"""
from src.gui.core.event_bus import global_event_bus
for entry in self._registry:
deps = entry.get('dependencies')
if not deps:
continue
for _input_field, (dep_step, output_type, panel_attr) in deps.items():
if not deps: continue
# 第三个元素 source_attr 现在明确代表上游控件的真实名字
for target_field, (dep_step, output_type, source_attr) in deps.items():
src_panel = self._panels.get(dep_step)
if src_panel is None:
continue
widget = getattr(src_panel, panel_attr, None)
if widget is None:
continue
path = ''
if src_panel is None: continue
widget = getattr(src_panel, source_attr, None)
if widget is None: continue
path = ""
if hasattr(widget, 'get_path'):
path = widget.get_path().strip()
elif hasattr(widget, 'text'):
path = widget.text().strip()
if not path:
continue
if not path: continue
# 核心修复:强制转为绝对路径,防止跨目录传递时路径丢失
import os
absolute_path = os.path.abspath(path).replace('\\', '/')
global_event_bus.publish('OutputUpdated', {
'step_id': dep_step,
'output_type': output_type,
'path': path,
'path': absolute_path,
})
def _get_current_work_dir(self):

View File

@ -48,14 +48,13 @@ PANEL_REGISTRY = [
'icon': '2.png',
'stage': '阶段一:影像预处理',
'display_name': '2. 耀斑区域识别',
# 对账修复2026-06-18
# - img_path: 来源 step1.img_file、目标 step2.img_file ✓ 两端均存在
# - water_mask_path: 原 panel_attr='water_mask_file' 在 step1 panel 不存在(断链)
# → 改为 step1 真实控件名 'mask_file'step1 默认现有掩膜输入模式)
# → NDWI 模式由 step2.update_from_config 自补足,不依赖 EventBus 链路
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名;
# 第三元素 source_attr = 上游源控件真实属性名panel_factory 回放端使用)
'dependencies': {
'img_path': ('step1', 'reference_img', 'img_file'),
'water_mask_path': ('step1', 'water_mask', 'mask_file'),
# 目标框: self.img_file ← 上游 step1.img_file
'img_file': ('step1', 'reference_img', 'img_file'),
# 目标框: self.water_mask_file ← 上游 step1.mask_file
'water_mask_file': ('step1', 'water_mask', 'mask_file'),
},
'constructor_kwargs': None,
},
@ -66,14 +65,12 @@ PANEL_REGISTRY = [
'icon': '3.png',
'stage': '阶段一:影像预处理',
'display_name': '3. 耀斑去除与修复',
# 对账修复2026-06-18
# - img_path: 来源 step1.img_file、目标 step3.img_file ✓ 两端均存在
# - water_mask: 原 panel_attr='water_mask_file' 在 step1 panel 不存在(断链)
# → 改为 step1 真实控件名 'mask_file'
# → NDWI 模式由 step3.update_from_config 自补足
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名
'dependencies': {
'img_path': ('step1', 'reference_img', 'img_file'),
'water_mask': ('step1', 'water_mask', 'mask_file'),
# 目标框: self.img_file ← 上游 step1.img_file
'img_file': ('step1', 'reference_img', 'img_file'),
# 目标框: self.water_mask_file ← 上游 step1.mask_file
'water_mask_file': ('step1', 'water_mask', 'mask_file'),
},
'constructor_kwargs': None,
},
@ -88,14 +85,13 @@ PANEL_REGISTRY = [
'icon': '4.png',
'stage': '阶段二:样本数据准备',
'display_name': '4. 采样点布设',
# 对账修复2026-06-18
# - deglint_img_path: 原 panel_attr='deglint_img_file' 在 step3 panel 不存在(断链
# → step3 输出 widget 真实名为 'output_file'deglint_image.bsq
# - water_mask_path: 原 'water_mask_file' 在 step1 panel 不存在
# → 改为 step1 真实控件名 'mask_file'
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名;
# 第三元素 source_attr = 上游源控件真实属性名panel_factory 回放端使用
'dependencies': {
'deglint_img_path': ('step3', 'deglint_image', 'output_file'),
'water_mask_path': ('step1', 'water_mask', 'mask_file'),
# 目标框: self.deglint_img_file ← 上游 step3.output_file
'deglint_img_file': ('step3', 'deglint_image', 'output_file'),
# 目标框: self.water_mask_file ← 上游 step1.mask_file
'water_mask_file': ('step1', 'water_mask', 'mask_file'),
},
'constructor_kwargs': None,
},
@ -117,18 +113,16 @@ PANEL_REGISTRY = [
'icon': '6.png',
'stage': '阶段二:样本数据准备',
'display_name': '6. 光谱特征提取',
# 对账修复2026-06-18
# - deglint_img_path: 原 'deglint_img_file' 在 step3 panel 不存在(断链)
# → 改为 step3 输出 widget 'output_file'
# - csv_path: 原 'csv_file' ✓ step5 panel 有 self.csv_file无修改
# - boundary_mask_path: 原 'water_mask_file' 在 step1 panel 不存在
# → 改为 step1 真实控件名 'mask_file'
# - glint_mask_path: 原 'glint_mask_file' ✓ step2 panel 有,无修改
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名
'dependencies': {
'deglint_img_path': ('step3', 'deglint_image', 'output_file'),
'csv_path': ('step5_clean', 'processed_data', 'csv_file'),
'boundary_mask_path': ('step1', 'water_mask', 'mask_file'),
'glint_mask_path': ('step2', 'glint_mask', 'glint_mask_file'),
# 目标框: self.deglint_img_file ← 上游 step3.output_file
'deglint_img_file': ('step3', 'deglint_image', 'output_file'),
# 目标框: self.csv_file ← 上游 step5_clean.csv_file
'csv_file': ('step5_clean', 'processed_data', 'csv_file'),
# 目标框: self.water_mask_file ← 上游 step1.mask_file
'water_mask_file': ('step1', 'water_mask', 'mask_file'),
# 目标框: self.glint_mask_file ← 上游 step2.output_file
'glint_mask_file': ('step2', 'glint_mask', 'output_file'),
},
'constructor_kwargs': None,
},
@ -139,18 +133,11 @@ PANEL_REGISTRY = [
'icon': '7.png',
'stage': '阶段二:样本数据准备',
'display_name': '7. 水质指数计算',
# 对账修复2026-06-18
# - training_csv_path:
# 原 ('step6_feature', 'training_spectra', 'training_data_widget')
# output_type='training_spectra' 仅作为 EventBus 事件标签,不匹配 step6 输出
# panel_attr='training_data_widget' 已是 step7 view 真实控件 ✓
# 改 output_type='output_file'step6 输出 file widget 名为 output_file
# ⚠️ 用户原文要求 panel_attr='csv_file',但 step7 无 csv_file widget
# (只有 training_data_widget 与 formula_csv_widget
# 实际改用 step7 真实控件 'training_data_widget'
# source panel_attr 取 step6 的 'output_file'(双源对账一致)
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名;
# 第三元素 source_attr = 上游源控件真实属性名
'dependencies': {
'training_csv_path': ('step6_feature', 'output_file', 'training_data_widget'),
# 目标框: self.training_data_widget ← 上游 step6_feature.output_file
'training_data_widget': ('step6_feature', 'output_file', 'output_file'),
},
'constructor_kwargs': None,
},
@ -165,13 +152,9 @@ PANEL_REGISTRY = [
'icon': '8.png',
'stage': '阶段三:模型构建与训练',
'display_name': '8. 机器学习建模',
# 对账修复2026-06-18
# - training_csv_file:
# 原 ('step7_index', 'training_spectra_indices', 'training_csv_file')
# source panel_attr='training_csv_file' 在 step7 view 不存在(断链)
# → step7 view 输出(指数计算后 CSV真实控件为 'training_data_widget'
# target panel_attr='training_csv_file' ✓ step8 panel 有 self.training_csv_file
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名
'dependencies': {
# 目标框: self.training_csv_file ← 上游 step7_index.training_data_widget
'training_csv_file': ('step7_index', 'training_spectra_indices', 'training_data_widget'),
},
'constructor_kwargs': None,
@ -187,14 +170,11 @@ PANEL_REGISTRY = [
'icon': '10.png',
'stage': '阶段四:预测与成果输出',
'display_name': '9. 机器学习预测',
# 对账修复2026-06-18
# - models_dir:
# 原 ('step8_ml_train', 'Supervised_Model_Training', 'models_dir_file')
# source panel_attr='models_dir_file' 在 step8 panel 不存在(断链)
# → step8 模型输出真实控件为 'output_path'
# target panel_attr='models_dir_file' ✓ step9 panel 有 self.models_dir_file
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名;
# 第三元素 source_attr = 上游源控件真实属性名
'dependencies': {
'models_dir': ('step8_ml_train', 'Supervised_Model_Training', 'output_path'),
# 目标框: self.models_dir_file ← 上游 step8_ml_train.output_path
'models_dir_file': ('step8_ml_train', 'Supervised_Model_Training', 'output_path'),
},
'constructor_kwargs': None,
},
@ -205,13 +185,12 @@ PANEL_REGISTRY = [
'icon': '10.png',
'stage': '阶段四:预测与成果输出',
'display_name': '10. 水色指数反演',
# 对账修复2026-06-18
# - bsq_file:
# 原 ('step3', 'deglint_image', 'bsq_file')
# source panel_attr='bsq_file' 在 step3 panel 不存在(断链)
# → step3 输出deglint_image.bsq真实控件为 'output_file'
# target panel_attr='bsq_file' ✓ step10 panel 有 self.bsq_file
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名;
# 第三元素 source_attr = 上游源控件真实属性名
# step10 panel 仅有 bsq_file / hdr_file / output_dir没有 water_mask widget
# 故删除 water_mask 依赖,避免悬挂回调
'dependencies': {
# 目标框: self.bsq_file ← 上游 step3.output_file
'bsq_file': ('step3', 'deglint_image', 'output_file'),
},
'constructor_kwargs': None,
@ -223,21 +202,14 @@ PANEL_REGISTRY = [
'icon': '10.png',
'stage': '阶段四:预测与成果输出',
'display_name': '11. 专题图生成',
# 对账修复2026-06-18
# - prediction_csv_dir_edit:
# 原 ('step9_ml_predict', '9_ML_Prediction', 'prediction_csv_dir_edit')
# source panel_attr='prediction_csv_dir_edit' 在 step9 panel 不存在(断链)
# → step9 输出prediction.csv真实控件为 'output_file'
# target panel_attr='prediction_csv_dir_edit' ✓ step11 panel 有该 widget
# ⚠️ 语义注记target 是「目录」QLineEdit但 source 是「单文件」,下游需手动指定目录
# - geotiff_dir_edit:
# 原 ('step10_watercolor', 'WaterIndex_Images', 'geotiff_dir_edit')
# source panel_attr='geotiff_dir_edit' 在 step10 panel 不存在(断链)
# → step10 输出GeoTIFF 目录)真实控件为 'output_dir'
# target panel_attr='geotiff_dir_edit' ✓ step11 panel 有该 widget
# 架构解耦2026-06-22dict 键名 = 下游目标控件真实属性名
'dependencies': {
# 目标框: self.prediction_csv_dir_edit ← 上游 step9_ml_predict.output_file
'prediction_csv_dir_edit': ('step9_ml_predict', '9_ML_Prediction', 'output_file'),
# 目标框: self.geotiff_dir_edit ← 上游 step10_watercolor.output_dir
'geotiff_dir_edit': ('step10_watercolor', 'WaterIndex_Images', 'output_dir'),
# 目标框: self.boundary_file ← 上游 step1.mask_file
'boundary_file': ('step1', 'water_mask', 'mask_file'),
},
'constructor_kwargs': None,
},

View File

@ -30,7 +30,7 @@ import traceback
from pathlib import Path
from typing import Dict, List, Optional
from PyQt5.QtCore import QObject, Qt
from PyQt5.QtCore import QObject, Qt, QTimer
from PyQt5.QtWidgets import QMessageBox, QDialog
from src.gui.core.event_bus import global_event_bus
@ -58,6 +58,11 @@ class PipelineExecutor(QObject):
self._workspace_initializer = workspace_initializer
self._worker: Optional[WorkerThread] = None
# ★ 防卡死看门狗:监控 WorkerThread 是否在合理时间内推进进度
self._watchdog_timer = QTimer()
self._watchdog_timer.timeout.connect(self._check_worker_health)
self._last_progress_time = 0.0
# 订阅面板发出的单步执行请求(解耦面板与执行器)
global_event_bus.subscribe('RequestRunSingleStep', self._on_request_run_single_step)
@ -303,6 +308,11 @@ class PipelineExecutor(QObject):
global_event_bus.publish('LogMessage', {'message': '开始执行完整流程...', 'level': 'info'})
global_event_bus.publish('LogMessage', {'message': '=' * 50, 'level': 'info'})
# ★ 启动看门狗worker.start() 之后立刻开始监控180s 超时)
import time
self._last_progress_time = time.time()
self._watchdog_timer.start(5000) # 每 5 秒巡检一次
self._worker.start()
def run_single_step(self, step_name: str, config: dict = None):
@ -375,6 +385,11 @@ class PipelineExecutor(QObject):
})
global_event_bus.publish('LogMessage', {'message': '=' * 50, 'level': 'info'})
# ★ 启动看门狗worker.start() 之后立刻开始监控180s 超时)
import time
self._last_progress_time = time.time()
self._watchdog_timer.start(5000) # 每 5 秒巡检一次
self._worker.start()
def stop_pipeline(self):
@ -460,7 +475,12 @@ class PipelineExecutor(QObject):
})
def _on_progress_update(self, percentage: int, message: str):
"""WorkerThread 进度 → EventBus ProgressUpdate 事件。"""
"""WorkerThread 进度 → EventBus ProgressUpdate 事件。
同步重置看门狗计时器:每次收到进度更新就视为 Worker 还活着。
"""
import time
self._last_progress_time = time.time()
global_event_bus.publish('ProgressUpdate', {
'percentage': percentage,
'message': message,
@ -482,11 +502,40 @@ class PipelineExecutor(QObject):
主窗口订阅此事件,恢复按钮状态并弹窗。
"""
# ★ 停止看门狗Worker 已正常收口,看门狗可以下班
self._watchdog_timer.stop()
global_event_bus.publish('PipelineFinished', {
'success': success,
'message': message,
})
def _check_worker_health(self):
"""看门狗巡检:每 5 秒触发一次。
判定逻辑:
- Worker 已不在运行(自然结束/被强杀) → 停掉看门狗
- Worker 仍在运行 + 上次进度距今 > 180 秒 → 判定为假死/死锁,
强制 terminate() 并通过 _on_finished(False, ...) 汇流解 UI
让被卡死的「独立运行此步骤」按钮恢复可用。
"""
import time
if self._worker and self._worker.isRunning():
if time.time() - self._last_progress_time > 180:
self._log_message("[错误] 后台任务响应超时超过3分钟无响应强制终止...", "error")
self._worker.terminate()
self._on_finished(False, "后台任务响应超时或发生底层段错误,已强制终止。")
else:
# Worker 已退出(自然结束 / 已 terminate关闭看门狗
self._watchdog_timer.stop()
def _log_message(self, message: str, level: str = "info"):
"""看门狗专用的轻量日志通道(直接走 EventBus不绕过转发槽"""
global_event_bus.publish('LogMessage', {
'message': message,
'level': level,
})
# ═══════════════════════════════════════════════════════════
# 内部辅助
# ═══════════════════════════════════════════════════════════

View File

@ -14,8 +14,8 @@ import numpy as np
def _viz_training_spectra_csv_path(work_path: Path) -> Path:
"""可视化光谱/统计及模型散点图使用的训练光谱表路径(与步骤5输出一致)。"""
return work_path / "5_training_spectra" / "training_spectra.csv"
"""可视化光谱/统计及模型散点图使用的训练光谱表路径(与步骤6输出一致)。"""
return work_path / "6_Spectral_Feature_Extraction" / "training_spectra.csv"
def _viz_infer_wavelength_start_column(df) -> Union[str, int]:
@ -194,7 +194,7 @@ class VisualizationWorkerThread(QThread):
training_csv_path = (self.extra.get("training_csv_path") or "").strip()
models_dir = (self.extra.get("models_dir") or "").strip()
if not training_csv_path or not Path(training_csv_path).is_file():
self.failed.emit("训练光谱 CSV 无效或不存在,请确认已选择步骤5输出的文件。")
self.failed.emit("训练光谱 CSV 无效或不存在,请确认已选择步骤6输出的文件。")
return
if not models_dir or not Path(models_dir).is_dir():
self.failed.emit("模型目录无效或不存在请确认步骤6已生成 7_Supervised_Model_Training 下的参数子文件夹。")
@ -213,7 +213,7 @@ class VisualizationWorkerThread(QThread):
if training_csv_path:
training_csv = Path(training_csv_path)
else:
training_csv = wp / "5_training_spectra" / "training_spectra.csv"
training_csv = wp / "6_Spectral_Feature_Extraction" / "training_spectra.csv"
if self.extra.get("gen_scatter"):
if training_csv.is_file():

View File

@ -241,13 +241,11 @@ class WorkspaceInitializer(QObject):
# ═══════════════════════════════════════════════════════════
def _auto_fill_output_paths(self):
"""根据工作目录自动填充 step1 的输出路径。
"""【已禁用】禁止在工作目录刚选定后瞎拼凑假路径。
注意Step1 的输出路径由 update_work_directory() 根据模式自动控制
历史行为:曾经在此处调用 step1_panel.update_work_directory(self._work_dir) 自动回填输出路径
现已清空为 no-op原因刚选定目录时任何"自动推断"的子目录都是幽灵路径,
会污染后续面板的 input field让用户误以为已经填好了实际却指向不存在的目录。
真实填充时机交由面板自身的 update_from_config + 用户手动指定。
"""
if not self._work_dir:
return
step1_panel = self._panel_factory.get_panel('step1')
if step1_panel:
step1_panel.update_work_directory(self._work_dir)
pass

View File

@ -22,39 +22,29 @@ from pathlib import Path
from typing import Optional, Union
# 用户口语编号 / 业务别名 → main_window 上真实属性名的映射
# 这是"张冠李戴"修复的核心——之前代码写的 step11_panel 实际不存在
# 真实存在的属性见 water_quality_gui.py:1891-1928
# 用户口语编号 / 业务别名 → PANEL_REGISTRY 中真实 step_id 的映射
# 这是"张冠李戴"修复的核心——main_window 上已不再直接挂载 panel 属性
# 所有面板都通过 _panel_factory.get_panel(step_id) 懒加载访问。
STEP_DATA_SOURCE = {
# 数据流 step 编号(用户口语) → main_window 真实属性
'step5_clean_output': 'step5_clean_panel',
'step7_index_output': 'step7_index_panel',
'step8_ml_train_output': 'step8_ml_train_panel',
'step8_5_non_empirical': 'step8_non_empirical_panel', # 之前写错成 step11_panel
'step9_ml_predict_output': 'step9_ml_predict_panel',
'step10_watercolor_output': 'step10_watercolor_panel',
'step11_ml_prediction': 'step9_ml_predict_panel', # 主流程 step11 = ML 预测
'step12_regression_prediction': 'step8_non_empirical_panel', # 主流程 step12 = 非经验预测
'step13_custom_regression': 'step13_report_panel', # 占位(自定义回归本身没有专属 panel
'sampling_csv': 'step4_sampling_panel',
'training_spectra_csv': 'step5_clean_panel',
'indices_csv': 'step7_index_panel',
'models_dir': 'step8_ml_train_panel',
'watercolor_dir': 'step10_watercolor_panel',
'prediction_csv_dir': 'step9_ml_predict_panel', # 默认从 ML 预测读
# 数据流 step 编号(用户口语) → PANEL_REGISTRY 中的 step_id
'step5_clean_output': 'step5_clean',
'step7_index_output': 'step7_index',
'step8_ml_train_output': 'step8_ml_train',
'step8_5_non_empirical': 'step8_ml_train',
'step9_ml_predict_output': 'step9_ml_predict',
'step10_watercolor_output': 'step10_watercolor',
'step11_ml_prediction': 'step9_ml_predict', # 主流程 step11 = ML 预测
'step12_regression_prediction': 'step8_ml_train', # 主流程 step12 = 非经验预测
'step13_custom_regression': 'step13_report', # 自定义回归借用 step13 报告面板
'sampling_csv': 'step4_sampling',
'training_spectra_csv': 'step5_clean',
'indices_csv': 'step7_index',
'models_dir': 'step8_ml_train',
'watercolor_dir': 'step10_watercolor',
'prediction_csv_dir': 'step9_ml_predict', # 默认从 ML 预测读
}
def _get_widget(main_window, attr_name: str, widget_attr: str = 'output_file'):
"""从 main_window.<attr_name> 取出指定子组件,失败时返回 None。"""
if main_window is None:
return None
panel = getattr(main_window, attr_name, None)
if panel is None:
return None
return getattr(panel, widget_attr, None)
def _read_widget_path(widget) -> str:
"""统一从 widget 读 path兼容 FileSelectWidget / QLineEdit / 字符串)。"""
if widget is None:
@ -75,15 +65,30 @@ def _read_widget_path(widget) -> str:
def resolve_step_widget(main_window, step_key: str, widget_attr: str = 'output_file'):
"""根据业务 step_key 解析出正确的 widget消除张冠李戴
"""通过 panel_factory 访问对应面板,并获取其实际的输入/输出控件
解析顺序:
1. STEP_DATA_SOURCE[step_key] 找到真实 step_id
2. main_window._panel_factory.get_panel(step_id) 懒加载拿到面板
3. getattr(panel, widget_attr) 取出真实控件
Returns:
widget 对象 or None找不到时返回 None调用方需自行兜底
"""
attr_name = STEP_DATA_SOURCE.get(step_key)
if attr_name is None:
step_id = STEP_DATA_SOURCE.get(step_key)
if not step_id:
return None
return _get_widget(main_window, attr_name, widget_attr)
# 从主窗口获取工厂,再由工厂通过 step_id 拿出真实面板
factory = getattr(main_window, '_panel_factory', None)
if not factory:
return None
panel = factory.get_panel(step_id)
if not panel:
return None
return getattr(panel, widget_attr, None)
_FALLBACK_DIR_TABLE = {

View File

@ -489,146 +489,43 @@ class Step11MapPanel(QWidget):
self.output_dir.set_path(str(p.parent))
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充预测结果目录
if work_dir:
self.work_dir = work_dir
main_window = self.window()
factory = getattr(main_window, '_panel_factory', None) if main_window else None
if not factory: return
优先使用 Step8机器学习预测的输出目录作为待预测 CSV 目录
其次回退到 Step8.5(回归预测)或 Step8.75(自定义回归预测)的输出目录。
# 1. 安全抓取 Step 9 的预测 CSV 目录
step9_panel = factory.get_panel('step9_ml_predict')
if step9_panel and hasattr(step9_panel, 'output_file'):
path = step9_panel.output_file.get_path()
if path:
self.prediction_csv_dir_edit.setText(path)
self.mode_folder_rb.setChecked(True)
Args:
work_dir: 工作目录路径
pipeline: Pipeline 实例(未使用,保留接口兼容性)
"""
try:
import traceback
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
# 2. 安全抓取 Step 1 的真实掩膜文件(彻底拒绝瞎猜 roi.shp
step1_panel = factory.get_panel('step1')
if step1_panel:
use_ndwi = step1_panel.use_ndwi_radio.isChecked()
# 根据用户在第1步的选择拿真实的输出掩膜或导入的掩膜
if use_ndwi and hasattr(step1_panel, 'output_file'):
path = step1_panel.output_file.get_path()
elif not use_ndwi and hasattr(step1_panel, 'mask_file'):
path = step1_panel.mask_file.get_path()
else:
self.work_dir = None
path = ""
existing = self.boundary_file.get_path()
if path and not existing:
self.boundary_file.set_path(path)
main_window = self.window()
if not main_window:
return
# 1. 优先:从 Step9机器学习预测读输出目录9_ML_Prediction 子目录
# 修复张冠李戴:原 main_window.step11_prediction_panel 不存在,真实属性是 step9_ml_predict_panel
pred_dir = None
step10_output = get_step_output_path(
main_window, 'step11_ml_prediction', work_dir=self.work_dir,
widget_attr='output_file', fallback_key='step9_ml_predict',
)
if step10_output:
# 提取父目录后追加 9_ML_Prediction最底层真实子目录
base_pred_dir = str(Path(step10_output).parent)
ml_pred_dir = Path(base_pred_dir) / "9_ML_Prediction"
pred_dir = str(ml_pred_dir) if ml_pred_dir.exists() else base_pred_dir
# 2. 备选:从 Step8非经验预测读输出目录
# 修复张冠李戴:原 main_window.step11_panel 不存在,真实属性是 step8_non_empirical_panel
if not pred_dir:
step8_5_output = get_step_output_path(
main_window, 'step12_regression_prediction', work_dir=self.work_dir,
widget_attr='output_file', fallback_key='step8_ml_train',
)
if step8_5_output:
pred_dir = str(Path(step8_5_output).parent)
# 3. 备选:从 Step13 panel自定义回归读输出目录
# 修复张冠李戴:原 main_window.step12_panel 不存在;自定义回归 panel 是 step13_panel 类main_window 上无此名)
if not pred_dir:
step8_75_output = get_step_output_path(
main_window, 'step13_custom_regression', work_dir=self.work_dir,
widget_attr='output_dir_widget', fallback_key='custom_regression',
)
if step8_75_output:
pred_dir = step8_75_output
# 自动填入"预测CSV目录"(文件夹批量模式)
if pred_dir:
existing_dir = (self.prediction_csv_dir_edit.text() or "").strip()
if not existing_dir:
self.prediction_csv_dir_edit.setText(pred_dir)
# 切换到文件夹批量模式
self.mode_folder_rb.setChecked(True)
# 4. 自动填充输出目录14_visualization
if self.work_dir:
output_dir = resolve_subdir(self.work_dir, 'visualization')
os.makedirs(output_dir, exist_ok=True)
existing_out = self.output_dir.get_path()
if not existing_out or not existing_out.strip():
self.output_dir.set_path(output_dir)
# 4.5. 自动探测 Step1 水体掩膜(修复张冠李戴:原仅找 roi.shp找不到时未尝试 1_water_mask
# 优先调用 main_window.pipeline.get_step_output_dir('step1')(数据真实来源)
# 兜底走 resolve_subdir('water_mask') → <work_dir>/1_water_mask
# Step1 典型产物water_mask_from_ndwi.dat、water_mask_from_shp.dat、xxx.shp
if self.work_dir:
water_mask_dir = None
pipeline = None
try:
_win = self.window()
if _win is not None:
pipeline = getattr(_win, 'pipeline', None)
except Exception:
pipeline = None
if pipeline is not None and hasattr(pipeline, 'get_step_output_dir'):
try:
water_mask_dir = pipeline.get_step_output_dir('step1')
except Exception as e:
print(f"⚠️ [step11_map_panel] pipeline.get_step_output_dir('step1') 失败: {e}")
water_mask_dir = None
if not water_mask_dir:
water_mask_dir = resolve_subdir(self.work_dir, 'water_mask')
existing_boundary = (self.boundary_file.get_path() or "").strip()
if not existing_boundary and water_mask_dir and os.path.isdir(water_mask_dir):
# 优先 .shpgeopandas 读矢量最稳),其次 .dat
mask_candidates = (
sorted(Path(water_mask_dir).glob("*.shp"))
+ sorted(Path(water_mask_dir).glob("*.dat"))
)
if mask_candidates:
self.boundary_file.set_path(str(mask_candidates[0]))
print(f"✅ [step11_map_panel] 自动从 Step1 掩膜目录填入: {mask_candidates[0]}")
# 5. 自动探测原始矢量边界文件(.shp作为专题图底图
# 优先回溯 input-test/roi.shpgeopandas.read_file 仅支持矢量格式
if self.work_dir:
possible_shp = None
candidates = [
Path(self.work_dir).parent / "input-test" / "roi.shp",
Path(self.work_dir) / "roi.shp",
Path(self.work_dir).parent / "roi.shp",
]
for candidate in candidates:
if candidate.exists() and candidate.suffix.lower() == ".shp":
possible_shp = candidate
break
existing_boundary = (self.boundary_file.get_path() or "").strip()
if not existing_boundary and possible_shp:
self.boundary_file.set_path(str(possible_shp))
elif not existing_boundary:
self.boundary_file.set_path("")
print("⚠️ 提示:专题图生成模块需传入标准矢量边界文件 (.shp),请手动选择。")
# 6. 自动探测 Step 8 输出的水色指数 GeoTIFFGeoTIFF 渲染模式)
step10_out_dir = Path(self.work_dir) / "10_WaterIndex_Images" if self.work_dir else None
if step10_out_dir and step10_out_dir.is_dir():
# GeoTIFF 批量模式:填充目录供批量渲染
if not (self.geotiff_dir_edit.text() or "").strip():
self.geotiff_dir_edit.setText(str(step10_out_dir))
# GeoTIFF 单文件模式:默认选中第一个
tif_files = sorted(step10_out_dir.glob("*.tif"))
if tif_files and not (self.geotiff_file.get_path() or "").strip():
self.geotiff_file.set_path(str(tif_files[0]))
except Exception as e:
import traceback
print(f"{self.__class__.__name__}】自动填充失败,跳过: {e}")
traceback.print_exc()
# 3. 生成第 11 步的绝对输出目录 (杜绝保存到相对路径)
if hasattr(self, 'work_dir') and self.work_dir:
import os
out_dir = os.path.join(self.work_dir, "14_visualization").replace('\\', '/')
os.makedirs(out_dir, exist_ok=True)
self.output_dir.set_path(out_dir)
def browse_output_dir(self):
"""浏览输出目录"""
@ -683,13 +580,10 @@ class Step11MapPanel(QWidget):
QMessageBox.warning(self, "输入验证失败", "边界文件不存在")
return
parent = self.parent()
while parent and not hasattr(parent, 'run_single_step'):
parent = parent.parent()
if not parent or not hasattr(parent, 'run_single_step'):
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
return
# 获取顶层主窗口(用于弹窗或直接调用)
main_win = self.window()
# 修正:将后面代码中所有的 parent 替换为 main_win
parent = main_win
if self.mode_folder_rb.isChecked():
# -------- CSV 插值批量 --------
@ -827,22 +721,23 @@ class Step11MapPanel(QWidget):
return
config = self.get_config()
parent.run_single_step('step11_map', {'step11_map': config})
# V2 架构:通过事件总线发送执行请求,彻底解耦
from src.gui.core.event_bus import global_event_bus
global_event_bus.publish('RequestRunSingleStep', {
'step_name': 'step11_map',
'config': {'step11_map': config},
})
def _on_step10_batch_ok(self, n: int):
self.progress_bar.setVisible(False)
QMessageBox.information(self, "完成", f"已批量生成 {n} 个分布图。")
parent = self.parent()
while parent and not hasattr(parent, "log_message"):
parent = parent.parent()
if parent and hasattr(parent, "log_message"):
parent.log_message(f"专题图批量完成,共 {n} 个文件。", "info")
main_win = self.window()
if main_win and hasattr(main_win, "log_message"):
main_win.log_message(f"专题图批量完成,共 {n} 个文件。", "info")
def _on_step10_batch_fail(self, err: str):
self.progress_bar.setVisible(False)
QMessageBox.critical(self, "失败", f"批量生成中断:\n{err[:900]}")
parent = self.parent()
while parent and not hasattr(parent, "log_message"):
parent = parent.parent()
if parent and hasattr(parent, "log_message"):
parent.log_message(err, "error")
main_win = self.window()
if main_win and hasattr(main_win, "log_message"):
main_win.log_message(err, "error")

View File

@ -36,12 +36,12 @@ PIPELINE_AVAILABLE = True
def _viz_training_spectra_csv_path(work_path: Path) -> Path:
"""可视化光谱/统计及模型散点图使用的训练光谱表路径(与步骤5输出一致)。
"""可视化光谱/统计及模型散点图使用的训练光谱表路径(与步骤6输出一致)。
注意步骤5.5水质指数计算执行后会覆盖此文件为94维增强版本
因此下游步骤无需任何修改,直接读取此路径即可。
"""
return work_path / "5_training_spectra" / "training_spectra.csv"
return work_path / "6_Spectral_Feature_Extraction" / "training_spectra.csv"
def _viz_infer_wavelength_start_column(df: pd.DataFrame) -> Union[str, int]:
@ -242,7 +242,7 @@ class VisualizationWorkerThread(QThread):
if training_csv_path:
training_csv = Path(training_csv_path)
else:
training_csv = wp / "5_training_spectra" / "training_spectra.csv"
training_csv = wp / "6_Spectral_Feature_Extraction" / "training_spectra.csv"
if self.extra.get("gen_scatter"):
if training_csv.is_file():
@ -1697,9 +1697,9 @@ class Step12VizPanel(QWidget):
}
main_window = self.window()
factory = getattr(main_window, '_panel_factory', None) if main_window else None
step5_panel = factory.get_panel('step5_clean') if factory else None
if step5_panel and getattr(step5_panel, 'output_file', None):
_resolved_csv = step5_panel.output_file.get_path()
step6_panel = factory.get_panel('step6_feature') if factory else None
if step6_panel and getattr(step6_panel, 'output_file', None):
_resolved_csv = step6_panel.output_file.get_path()
if _resolved_csv:
extra["training_csv_path"] = _resolved_csv
step8_panel = factory.get_panel('step8_ml_train') if factory else None
@ -1721,17 +1721,17 @@ class Step12VizPanel(QWidget):
try:
main_window = self.window()
factory = getattr(main_window, '_panel_factory', None) if main_window else None
step5_panel = factory.get_panel('step5_clean') if factory else None
if step5_panel and getattr(step5_panel, 'output_file', None) and step5_panel.output_file.get_path():
training_spectra_csv = Path(step5_panel.output_file.get_path())
step6_panel = factory.get_panel('step6_feature') if factory else None
if step6_panel and getattr(step6_panel, 'output_file', None) and step6_panel.output_file.get_path():
training_spectra_csv = Path(step6_panel.output_file.get_path())
else:
training_spectra_csv = _viz_training_spectra_csv_path(work_path)
if chart_type == 'scatter':
if not training_spectra_csv.is_file():
QMessageBox.warning(
self, "警告",
"未找到 5_training_spectra\\training_spectra.csv。\n"
"请先执行步骤5(光谱特征提取)生成该文件。",
"未找到 6_Spectral_Feature_Extraction\\training_spectra.csv。\n"
"请先执行步骤6(光谱特征提取)生成该文件。",
)
return
training_csv = training_spectra_csv
@ -1751,8 +1751,8 @@ class Step12VizPanel(QWidget):
if not training_spectra_csv.is_file():
QMessageBox.warning(
self, "警告",
"未找到 5_training_spectra\\training_spectra.csv。\n"
"光谱分析固定使用该文件,请先执行步骤5(光谱特征提取)。",
"未找到 6_Spectral_Feature_Extraction\\training_spectra.csv。\n"
"光谱分析固定使用该文件,请先执行步骤6(光谱特征提取)。",
)
return
csv_file = training_spectra_csv
@ -1775,8 +1775,8 @@ class Step12VizPanel(QWidget):
if not training_spectra_csv.is_file():
QMessageBox.warning(
self, "警告",
"未找到 5_training_spectra\\training_spectra.csv。\n"
"统计分析固定使用该文件,请先执行步骤5(光谱特征提取)。",
"未找到 6_Spectral_Feature_Extraction\\training_spectra.csv。\n"
"统计分析固定使用该文件,请先执行步骤6(光谱特征提取)。",
)
return
csv_file = training_spectra_csv

View File

@ -1,225 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step12 面板 - 自定义回归预测
"""
import os
import sys
from pathlib import Path
# 路径归一化 helper与 pipeline.get_step_output_dir 互为表里)
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
sys.path.insert(0, _HERE)
from _step_path_resolver import get_step_output_path, resolve_step_widget, resolve_subdir
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox,
QPushButton, QCheckBox, QMessageBox, QFileDialog,
)
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
class Step12Panel(QWidget):
"""步骤12自定义回归预测"""
def __init__(self, parent=None):
super().__init__(parent)
self.init_ui()
def init_ui(self):
layout = QVBoxLayout()
# 采样光谱CSV文件选择
self.sampling_csv_file = FileSelectWidget(
"采样光谱CSV:",
"CSV Files (*.csv);;All Files (*.*)"
)
layout.addWidget(self.sampling_csv_file)
# 自定义回归模型目录选择13_Custom_Regression
self.regression_models_dir = FileSelectWidget(
"回归模型目录:",
"Directories;;All Files (*.*)"
)
self.regression_models_dir.label.setText("回归模型目录:")
self.regression_models_dir.browse_btn.clicked.disconnect()
self.regression_models_dir.browse_btn.clicked.connect(self.browse_regression_models_dir)
self.regression_models_dir.set_path("") # 路径由 update_from_config 根据 work_dir 自动填充
layout.addWidget(self.regression_models_dir)
# 公式CSV文件选择用于查找index_formula
self.formula_csv_file = FileSelectWidget(
"公式CSV文件:",
"CSV Files (*.csv);;All Files (*.*)"
)
self.formula_csv_file.label.setText("公式CSV文件:")
layout.addWidget(self.formula_csv_file)
# 输出目录选择
self.output_dir_widget = FileSelectWidget(
"输出目录:",
"Directories;;All Files (*.*)"
)
self.output_dir_widget.label.setText("输出目录:")
self.output_dir_widget.browse_btn.clicked.disconnect()
self.output_dir_widget.browse_btn.clicked.connect(self.browse_output_dir)
self.output_dir_widget.line_edit.setPlaceholderText("留空使用默认prediction目录")
layout.addWidget(self.output_dir_widget)
# 启用步骤
self.enable_checkbox = QCheckBox("启用此步骤")
self.enable_checkbox.setChecked(True)
layout.addWidget(self.enable_checkbox)
# 独立运行按钮
self.run_button = QPushButton("独立运行此步骤")
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_button.clicked.connect(self.run_step)
layout.addWidget(self.run_button)
layout.addStretch()
self.setLayout(layout)
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充采样光谱和自定义回归模型目录
Args:
work_dir: 工作目录路径
pipeline: Pipeline 实例(未使用,保留接口兼容性)
"""
try:
import traceback
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
else:
self.work_dir = None
main_window = self.window()
# 1. 尝试从 Step7水质光谱指数界面读取全湖采样点 CSV 路径
# 修复张冠李戴:原 main_window.step7_panel 不存在,真实属性是 step7_index_panel
step7_output_path = get_step_output_path(
main_window, 'sampling_csv', work_dir=self.work_dir,
widget_attr='output_file', fallback_key='step7_index',
)
if step7_output_path:
existing = self.sampling_csv_file.get_path()
if not existing or not existing.strip():
self.sampling_csv_file.set_path(step7_output_path)
# 2. 尝试从 Step8非经验回归/自定义回归源)读取模型目录
# 修复张冠李戴:原 main_window.step12_panel 不存在;按代码原意是 step9 的 output_dir
step9_models_dir = get_step_output_path(
main_window, 'models_dir', work_dir=self.work_dir,
widget_attr='output_dir', fallback_key='step8_ml_train',
)
if step9_models_dir:
existing_models = self.regression_models_dir.get_path()
if not existing_models or not existing_models.strip():
self.regression_models_dir.set_path(step9_models_dir)
# 3. 自动填充回归模型目录(如果 step9 未提供)
if self.work_dir:
models_dir = self.regression_models_dir.get_path().strip()
if not models_dir:
default_models_dir = resolve_subdir(self.work_dir, 'custom_regression')
self.regression_models_dir.set_path(default_models_dir)
# 4. 自动填充输出目录(自定义回归预测目录)
if self.work_dir:
output_dir = os.path.join(resolve_subdir(self.work_dir, 'custom_regression'), "Custom_Regression_Prediction")
os.makedirs(output_dir, exist_ok=True)
existing_out = self.output_dir_widget.get_path()
if not existing_out or not existing_out.strip():
self.output_dir_widget.set_path(output_dir)
except Exception as e:
import traceback
print(f"{self.__class__.__name__}】自动填充失败,跳过: {e}")
traceback.print_exc()
def _get_default_work_dir(self):
"""获取 work_dir优先用 panel 自身缓存的,否则尝试从主窗口取"""
if hasattr(self, 'work_dir') and self.work_dir:
return str(self.work_dir)
mw = self.window()
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
return str(mw.work_dir)
return ""
def browse_regression_models_dir(self):
"""浏览回归模型目录"""
default = self._get_default_work_dir()
if default:
default = resolve_subdir(default, 'custom_regression')
dir_path = QFileDialog.getExistingDirectory(self, "选择回归模型目录", default)
if dir_path:
self.regression_models_dir.set_path(dir_path)
def browse_output_dir(self):
"""浏览输出目录"""
default = self._get_default_work_dir()
if default:
default = os.path.join(default, "13_Custom_Regression/Custom_Regression_Prediction")
dir_path = QFileDialog.getExistingDirectory(self, "选择输出目录", default)
if dir_path:
self.output_dir_widget.set_path(dir_path)
def get_config(self):
"""获取配置"""
config = {
'enabled': self.enable_checkbox.isChecked()
}
sampling_csv_path = self.sampling_csv_file.get_path()
if sampling_csv_path:
config['sampling_csv_path'] = sampling_csv_path
regression_models_dir = self.regression_models_dir.get_path()
if regression_models_dir:
config['custom_regression_dir'] = regression_models_dir
formula_csv_path = self.formula_csv_file.get_path()
if formula_csv_path:
config['formula_csv_path'] = formula_csv_path
output_dir = self.output_dir_widget.get_path()
if output_dir:
config['output_dir'] = output_dir
return config
def set_config(self, config):
"""设置配置"""
if 'sampling_csv_path' in config:
self.sampling_csv_file.set_path(config['sampling_csv_path'])
if 'custom_regression_dir' in config:
self.regression_models_dir.set_path(config['custom_regression_dir'])
if 'formula_csv_path' in config:
self.formula_csv_file.set_path(config['formula_csv_path'])
if 'output_dir' in config:
self.output_dir_widget.set_path(config['output_dir'])
if 'enabled' in config:
self.enable_checkbox.setChecked(config['enabled'])
def run_step(self):
"""独立运行步骤12"""
sampling_csv_path = self.sampling_csv_file.get_path()
if not sampling_csv_path:
QMessageBox.warning(self, "输入错误", "请选择采样光谱CSV文件")
return
regression_models_dir = self.regression_models_dir.get_path()
if not regression_models_dir:
QMessageBox.warning(self, "输入错误", "请选择回归模型目录!")
return
config = self.get_config()
parent = self.parent()
while parent and not hasattr(parent, 'run_single_step'):
parent = parent.parent()
if parent and hasattr(parent, 'run_single_step'):
parent.run_single_step('step13_report', {'step13_report': config})
else:
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")

View File

@ -20,18 +20,23 @@ from PyQt5.QtCore import Qt, QThread, pyqtSignal, QSettings
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QFormLayout,
QLabel, QCheckBox, QPushButton, QLineEdit,
QMessageBox, QFileDialog,
QMessageBox, QFileDialog, QProgressBar,
)
from src.gui.styles import ModernStylesheet
from src.gui.dialogs import AISettingsDialog, AI_SETTINGS_ORG, AI_SETTINGS_APP
class ReportGenerateThread(QThread):
"""后台生成 Word 报告(避免阻塞 UI"""
finished_ok = pyqtSignal(str)
failed = pyqtSignal(str)
log_message = pyqtSignal(str, str)
class ReportWorkerThread(QThread):
"""后台生成 Word 报告(避免阻塞 UI
三信号协议:
- progress(int, str):报告进度百分比 + 当前文案
- finished(str):生成的报告绝对路径
- error(str):异常信息(含 traceback
"""
progress = pyqtSignal(int, str)
finished = pyqtSignal(str)
error = pyqtSignal(str)
def __init__(self, work_dir: str, output_dir: Optional[str], report_title: str, enable_ai: bool):
super().__init__()
@ -44,7 +49,6 @@ class ReportGenerateThread(QThread):
try:
from src.postprocessing.report_word import WaterQualityReportGenerator, ReportGenerationConfig
# 唯一数据源:直接从 QSettings 读取 AI 配置
s = QSettings(AI_SETTINGS_ORG, AI_SETTINGS_APP)
provider = s.value("ai_provider", "minimax", type=str)
timeout = int(s.value("timeout_s", 120, type=int))
@ -68,10 +72,6 @@ class ReportGenerateThread(QThread):
enable_ai_analysis=self.enable_ai,
)
self.log_message.emit(
f"报告生成:工作目录={self.work_dir}AI={'' if self.enable_ai else ''}Provider={provider}",
"info",
)
gen = WaterQualityReportGenerator(
work_dir=self.work_dir,
output_dir=self.output_dir,
@ -80,10 +80,11 @@ class ReportGenerateThread(QThread):
out_path = gen.generate_report(
work_dir=self.work_dir,
report_title=self.report_title or "水质参数反演分析报告",
on_progress=lambda pct, text: self.progress.emit(int(pct), str(text)),
)
self.finished_ok.emit(str(out_path))
self.finished.emit(str(out_path))
except Exception as e:
self.failed.emit(f"{e}\n{traceback.format_exc()}")
self.error.emit(f"{e}\n{traceback.format_exc()}")
class Step13ReportPanel(QWidget):
@ -117,11 +118,14 @@ class Step13ReportPanel(QWidget):
wd_row = QHBoxLayout()
self.work_dir_edit = QLineEdit()
self.work_dir_edit.setPlaceholderText("选择流程工作目录(含 14_visualization")
self.work_dir_edit.setPlaceholderText("流程工作目录(含 14_visualization")
self.work_dir_edit.setReadOnly(True)
wd_browse = QPushButton("浏览…")
wd_browse.clicked.connect(self.browse_work_dir)
wd_browse.setVisible(False)
sync_btn = QPushButton("同步主窗口工作目录")
sync_btn.clicked.connect(self.sync_work_dir_from_main)
sync_btn.setVisible(False)
wd_row.addWidget(self.work_dir_edit, 1)
wd_row.addWidget(wd_browse)
wd_row.addWidget(sync_btn)
@ -179,12 +183,27 @@ class Step13ReportPanel(QWidget):
btn_row.addStretch()
layout.addLayout(btn_row)
# ── 进度条 + 状态文案 ────────────────────────────────────────────────
progress_row = QHBoxLayout()
self.progress_label = QLabel("就绪")
self.progress_label.setMinimumWidth(220)
progress_row.addWidget(self.progress_label)
self.progress_bar = QProgressBar()
self.progress_bar.setRange(0, 100)
self.progress_bar.setValue(0)
self.progress_bar.setTextVisible(True)
progress_row.addWidget(self.progress_bar, 1)
layout.addLayout(progress_row)
layout.addStretch()
self.setLayout(layout)
# 刷新引擎提示文字
self._refresh_ai_label()
# 初次构建时尝试同步主窗口工作目录
self._auto_pull_work_dir()
def _refresh_ai_label(self):
"""从 QSettings 读取当前 Provider 并更新只读标签。"""
s = QSettings(AI_SETTINGS_ORG, AI_SETTINGS_APP)
@ -229,6 +248,28 @@ class Step13ReportPanel(QWidget):
if work_dir:
self.work_dir_edit.setText(str(work_dir))
def _auto_pull_work_dir(self):
"""从主窗口自动同步工作目录到 work_dir_edit无需用户操作"""
mw = self.main_window
if mw is not None and getattr(mw, "work_dir", None):
wd = str(mw.work_dir)
cur = self.work_dir_edit.text().strip()
if wd and wd != cur:
self.work_dir_edit.setText(wd)
def update_from_config(self, work_dir=None, pipeline=None):
"""切入面板时由主窗口统一调用,把当前 work_dir 同步到本面板。
解耦手动 browsework_dir_edit 已 ReadOnly外部只能通过此入口更新。
"""
if work_dir:
self.work_dir_edit.setText(str(work_dir))
self._auto_pull_work_dir()
def showEvent(self, event):
"""Tab 切换到本面板时再次兜底同步一次(应对 init_ui 时尚未绑定 main_window 的场景)。"""
super().showEvent(event)
self._auto_pull_work_dir()
def get_config(self):
"""返回路径和标题配置AI 配置不由本面板持有)。"""
return {
@ -271,14 +312,15 @@ class Step13ReportPanel(QWidget):
title = self.report_title_edit.text().strip() or "水质参数反演分析报告"
enable_ai = self.enable_ai_cb.isChecked()
# 重置进度条并禁用按钮
self.generate_btn.setEnabled(False)
self._report_thread = ReportGenerateThread(wd, out, title, enable_ai)
self._report_thread.log_message.connect(self._forward_log, Qt.QueuedConnection)
self._report_thread.finished_ok.connect(self._on_report_ok, Qt.QueuedConnection)
self._report_thread.failed.connect(self._on_report_fail, Qt.QueuedConnection)
self._report_thread.finished.connect(
lambda: self.generate_btn.setEnabled(True), Qt.QueuedConnection
)
self.progress_bar.setValue(0)
self.progress_label.setText("正在准备生成…")
self._report_thread = ReportWorkerThread(wd, out, title, enable_ai)
self._report_thread.progress.connect(self._on_progress, Qt.QueuedConnection)
self._report_thread.finished.connect(self._on_finished, Qt.QueuedConnection)
self._report_thread.error.connect(self._on_error, Qt.QueuedConnection)
self._report_thread.start()
self._forward_log("已开始生成 Word 报告…", "info")
@ -289,10 +331,22 @@ class Step13ReportPanel(QWidget):
else:
print(f"[{level}] {msg}")
def _on_report_ok(self, path: str):
def _on_progress(self, pct: int, text: str):
"""接收 ReportWorkerThread.progress(int, str) —— 主线程槽。"""
self.progress_bar.setValue(int(pct))
self.progress_label.setText(text or f"{pct}%")
def _on_finished(self, path: str):
"""报告生成成功 —— 主线程槽。"""
self.progress_bar.setValue(100)
self.progress_label.setText("完成")
self.generate_btn.setEnabled(True)
QMessageBox.information(self, "完成", f"报告已生成:\n{path}")
self._forward_log(f"Word 报告已保存: {path}", "info")
def _on_report_fail(self, err: str):
def _on_error(self, err: str):
"""报告生成异常 —— 主线程槽。"""
self.progress_label.setText("失败")
self.generate_btn.setEnabled(True)
QMessageBox.critical(self, "失败", f"报告生成失败:\n{err[:800]}")
self._forward_log(err, "error")

View File

@ -1,814 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step14 面板 - 分布图生成
"""
import os
import sys
import traceback
from pathlib import Path
from typing import List, Optional
# 路径归一化 helper与 pipeline.get_step_output_dir 互为表里)
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
sys.path.insert(0, _HERE)
from _step_path_resolver import get_step_output_path, resolve_step_widget
from PyQt5.QtCore import Qt, QThread, pyqtSignal
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QHBoxLayout,
QLabel, QCheckBox, QPushButton, QLineEdit, QDoubleSpinBox,
QRadioButton, QButtonGroup, QMessageBox, QFileDialog, QComboBox,
QProgressBar,
)
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
PIPELINE_AVAILABLE = True
class Step14BatchThread(QThread):
"""专题图:按文件夹内多个预测 CSV 批量生成分布图。"""
finished_ok = pyqtSignal(int)
failed = pyqtSignal(str)
log_message = pyqtSignal(str, str)
progress = pyqtSignal(int, int) # (current, total)
def __init__(self, work_dir: str, csv_paths: List[str], step14_kwargs: dict, output_dir_optional: Optional[str]):
super().__init__()
self.work_dir = work_dir
self.csv_paths = csv_paths
self.step14_kwargs = step14_kwargs
self.output_dir_optional = (output_dir_optional or "").strip() or None
def run(self):
mpl_prev = None
try:
import matplotlib
mpl_prev = matplotlib.get_backend()
except Exception:
pass
try:
import matplotlib.pyplot as plt
plt.switch_backend("Agg")
except Exception:
mpl_prev = None
try:
from src.core.steps.mapping_step import MappingStep
n = len(self.csv_paths)
for i, csv_p in enumerate(self.csv_paths):
self.progress.emit(i + 1, n)
self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
kw = {**self.step14_kwargs, "prediction_csv_path": csv_p}
kw.pop("skip_dependency_check", None)
if self.output_dir_optional:
stem = Path(csv_p).stem
kw["output_image_path"] = str(Path(self.output_dir_optional) / f"{stem}_distribution.png")
else:
kw["output_image_path"] = None
MappingStep.generate_distribution_map(**kw)
self.finished_ok.emit(n)
except Exception as e:
self.failed.emit(f"{e}\n{traceback.format_exc()}")
finally:
if mpl_prev:
try:
import matplotlib.pyplot as plt
plt.switch_backend(mpl_prev)
except Exception:
pass
class Step14GeoTIFFBatchThread(QThread):
"""GeoTIFF 批量渲染:遍历文件夹下所有 .tif/.bsq 逐一渲染成分布图 PNG。"""
finished_ok = pyqtSignal(int)
failed = pyqtSignal(str)
log_message = pyqtSignal(str, str)
progress = pyqtSignal(int, int) # (current, total)
def __init__(
self,
tif_paths: List[str],
output_dir: str,
boundary_shp_path: Optional[str],
input_crs: str,
output_crs: str,
):
super().__init__()
self.tif_paths = tif_paths
self.output_dir = output_dir
self.boundary_shp_path = boundary_shp_path
self.input_crs = input_crs
self.output_crs = output_crs
def run(self):
mpl_prev = None
try:
import matplotlib
mpl_prev = matplotlib.get_backend()
except Exception:
pass
try:
import matplotlib.pyplot as plt
plt.switch_backend("Agg")
except Exception:
mpl_prev = None
try:
from src.postprocessing.map import ContentMapper
mapper = ContentMapper()
n = len(self.tif_paths)
for i, tif_path in enumerate(self.tif_paths):
self.progress.emit(i + 1, n)
tif_stem = Path(tif_path).stem
chinese_name = mapper._get_chinese_title(tif_stem)
output_png = str(Path(self.output_dir) / f"{chinese_name}_专题图.png")
self.log_message.emit(f"GeoTIFF 渲染 [{i + 1}/{n}] {tif_stem}", "info")
try:
mapper.visualize_raster(
raster_tif_path=tif_path,
output_file=output_png,
boundary_shp_path=self.boundary_shp_path,
nodata_value=-9999.0,
figsize=(14, 10),
alpha=0.9,
)
except Exception as vis_err:
self.log_message.emit(f" ⚠️ 渲染失败,跳过: {vis_err}", "warning")
continue
self.finished_ok.emit(n)
except Exception as e:
self.failed.emit(f"{e}\n{traceback.format_exc()}")
finally:
if mpl_prev:
try:
import matplotlib.pyplot as plt
plt.switch_backend(mpl_prev)
except Exception:
pass
class Step14Panel(QWidget):
"""步骤14分布图生成"""
def __init__(self, parent=None):
super().__init__(parent)
self._batch_thread = None
self.init_ui()
def init_ui(self):
layout = QVBoxLayout()
hint = QLabel(
"独立运行:可选「单个 CSV」或「文件夹批量」扫描目录下所有 .csv"
"GeoTIFF 栅格模式下亦支持批量渲染步骤8输出的所有水色指数 GeoTIFF 文件。"
)
hint.setWordWrap(True)
hint.setStyleSheet(
f"color: {ModernStylesheet.COLORS.get('text_secondary', '#666')};"
)
layout.addWidget(hint)
mode_row = QHBoxLayout()
self.mode_single_rb = QRadioButton("单个 CSV 文件")
self.mode_folder_rb = QRadioButton("文件夹批量")
self._mode_group = QButtonGroup(self)
self._mode_group.addButton(self.mode_single_rb, 0)
self._mode_group.addButton(self.mode_folder_rb, 1)
mode_row.addWidget(self.mode_single_rb)
mode_row.addWidget(self.mode_folder_rb)
mode_row.addStretch()
layout.addLayout(mode_row)
# ---------- 渲染模式选择器CSV vs GeoTIFF ----------
render_row = QHBoxLayout()
render_row.addWidget(QLabel("渲染模式:"))
self.render_mode_combo = QComboBox()
self.render_mode_combo.addItems(["CSV 插值模式", "GeoTIFF 栅格模式"])
self.render_mode_combo.setMinimumWidth(180)
self.render_mode_combo.currentTextChanged.connect(self._toggle_input_mode)
render_row.addWidget(self.render_mode_combo)
render_row.addStretch()
layout.addLayout(render_row)
# ---------- RadioButton 美化样式(选中状态为方形实心块,贴合主界面风格) ----------
radio_style = """
QRadioButton {
font-size: 14px;
spacing: 8px;
color: #333333;
}
QRadioButton::indicator {
width: 16px;
height: 16px;
border: 2px solid #999999;
border-radius: 3px;
background-color: white;
}
QRadioButton::indicator:checked {
border: 2px solid #0078d4;
background-color: #0078d4;
image: none;
}
QRadioButton::indicator:hover {
border: 2px solid #005a9e;
}
"""
self.mode_single_rb.setStyleSheet(radio_style)
self.mode_folder_rb.setStyleSheet(radio_style)
self.prediction_csv_file = FileSelectWidget(
"预测结果CSV:",
"CSV Files (*.csv);;All Files (*.*)"
)
layout.addWidget(self.prediction_csv_file)
folder_row = QHBoxLayout()
self.prediction_csv_dir_label = QLabel("预测CSV目录:")
self.prediction_csv_dir_label.setMinimumWidth(120)
self.prediction_csv_dir_edit = QLineEdit()
self.prediction_csv_dir_edit.setPlaceholderText("选择含多个预测结果 CSV 的文件夹…")
pred_dir_btn = QPushButton("浏览…")
pred_dir_btn.setMaximumWidth(80)
pred_dir_btn.clicked.connect(self.browse_prediction_csv_dir)
folder_row.addWidget(self.prediction_csv_dir_label)
folder_row.addWidget(self.prediction_csv_dir_edit, 1)
folder_row.addWidget(pred_dir_btn)
self._folder_row_widget = QWidget()
self._folder_row_widget.setLayout(folder_row)
layout.addWidget(self._folder_row_widget)
# ---------- GeoTIFF 栅格文件选择器 ----------
self.geotiff_file = FileSelectWidget(
"水色指数 GeoTIFF:",
"GeoTIFF Files (*.tif);;All Files (*.*)"
)
self.geotiff_file.line_edit.setPlaceholderText("选择步骤8输出的水色指数 GeoTIFF 文件…")
self.geotiff_file.setVisible(False)
layout.addWidget(self.geotiff_file)
# ---------- GeoTIFF 文件夹批量选择器GeoTIFF + 文件夹模式时显示) ----------
geotiff_dir_row = QHBoxLayout()
self.geotiff_dir_label = QLabel("水色指数目录:")
self.geotiff_dir_label.setMinimumWidth(120)
self.geotiff_dir_edit = QLineEdit()
self.geotiff_dir_edit.setPlaceholderText("选择 10_WaterIndex_Images 文件夹(批量渲染)…")
geotiff_dir_btn = QPushButton("浏览…")
geotiff_dir_btn.setMaximumWidth(80)
geotiff_dir_btn.clicked.connect(self.browse_geotiff_dir)
geotiff_dir_row.addWidget(self.geotiff_dir_label)
geotiff_dir_row.addWidget(self.geotiff_dir_edit, 1)
geotiff_dir_row.addWidget(geotiff_dir_btn)
self._geotiff_dir_widget = QWidget()
self._geotiff_dir_widget.setLayout(geotiff_dir_row)
self._geotiff_dir_widget.setVisible(False)
layout.addWidget(self._geotiff_dir_widget)
self.recursive_csv_cb = QCheckBox("包含子文件夹(递归扫描 *.csv")
layout.addWidget(self.recursive_csv_cb)
self.boundary_file = FileSelectWidget(
"边界文件:",
"Shapefiles (*.shp);;All Files (*.*)"
)
layout.addWidget(self.boundary_file)
# 参数设置
params_group = QGroupBox("生成参数")
params_layout = QFormLayout()
self.resolution = QDoubleSpinBox()
self.resolution.setRange(1, 1000)
self.resolution.setValue(30)
params_layout.addRow("分辨率(米):", self.resolution)
self.input_crs = QLineEdit()
self.input_crs.setText("EPSG:32651")
params_layout.addRow("输入坐标系:", self.input_crs)
self.output_crs = QLineEdit()
self.output_crs.setText("EPSG:4326")
params_layout.addRow("输出坐标系:", self.output_crs)
self.show_points = QCheckBox("显示采样点")
params_layout.addRow("", self.show_points)
self.use_diffusion = QCheckBox("启用距离扩散")
self.use_diffusion.setChecked(True)
params_layout.addRow("", self.use_diffusion)
params_group.setLayout(params_layout)
layout.addWidget(params_group)
# 输出目录
self.output_dir = FileSelectWidget(
"输出分布图目录:",
"Directories;;All Files (*.*)"
)
self.output_dir.line_edit.setPlaceholderText("留空→工作目录/14_visualization")
self.output_dir.browse_btn.clicked.disconnect()
self.output_dir.browse_btn.clicked.connect(self.browse_output_dir)
layout.addWidget(self.output_dir)
# 启用步骤
self.enable_checkbox = QCheckBox("启用此步骤")
self.enable_checkbox.setChecked(True)
layout.addWidget(self.enable_checkbox)
# 独立运行按钮
self.run_button = QPushButton("独立运行此步骤")
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_button.clicked.connect(self.run_step)
layout.addWidget(self.run_button)
# 批量渲染进度条
self.progress_bar = QProgressBar()
self.progress_bar.setVisible(False)
self.progress_bar.setMinimum(0)
self.progress_bar.setMaximum(100)
self.progress_bar.setValue(0)
layout.addWidget(self.progress_bar)
layout.addStretch()
self.setLayout(layout)
# 信号绑定与初始状态
self.mode_single_rb.toggled.connect(self._toggle_input_mode)
self.mode_folder_rb.toggled.connect(self._toggle_input_mode)
self.mode_single_rb.setChecked(True) # 默认选中"单个 CSV"
self._toggle_input_mode() # 根据默认值设置初始显示状态
def _toggle_input_mode(self):
"""槽函数:根据渲染模式和输入模式动态显示/隐藏对应的输入组件。"""
geotiff_mode = self.render_mode_combo.currentText() == "GeoTIFF 栅格模式"
folder_mode = self.mode_folder_rb.isChecked()
# CSV 插值模式
if not geotiff_mode:
self.prediction_csv_file.setVisible(not folder_mode)
self._folder_row_widget.setVisible(folder_mode)
self.recursive_csv_cb.setVisible(folder_mode)
self.geotiff_file.setVisible(False)
self._geotiff_dir_widget.setVisible(False)
# GeoTIFF 栅格模式
else:
self.prediction_csv_file.setVisible(False)
self._folder_row_widget.setVisible(False)
self.recursive_csv_cb.setVisible(False)
# GeoTIFF + 文件夹批量 → 显示文件夹选择器;否则 → 显示单文件选择器
self.geotiff_file.setVisible(not folder_mode)
self._geotiff_dir_widget.setVisible(folder_mode)
def _get_default_work_dir(self):
"""获取 work_dir优先用 panel 自身缓存的,否则尝试从主窗口取"""
if hasattr(self, 'work_dir') and self.work_dir:
return str(self.work_dir)
mw = self.window()
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
return str(mw.work_dir)
return ""
def browse_prediction_csv_dir(self):
default = self._get_default_work_dir()
if default:
default = resolve_subdir(default, 'prediction_dir')
d = QFileDialog.getExistingDirectory(self, "选择预测结果 CSV 所在文件夹", default)
if d:
self.prediction_csv_dir_edit.setText(d)
def _collect_csv_paths_from_folder(self) -> List[str]:
folder = (self.prediction_csv_dir_edit.text() or "").strip()
if not folder or not os.path.isdir(folder):
return []
root = Path(folder)
if self.recursive_csv_cb.isChecked():
files = sorted(root.rglob("*.csv"))
else:
files = sorted(root.glob("*.csv"))
return [str(p) for p in files if p.is_file()]
def browse_geotiff_dir(self):
"""浏览 GeoTIFF 文件夹(批量模式)"""
default = self._get_default_work_dir()
if default:
default = resolve_subdir(default, 'watercolor')
d = QFileDialog.getExistingDirectory(
self, "选择水色指数 GeoTIFF 文件夹", default
)
if d:
self.geotiff_dir_edit.setText(d)
def _collect_tif_paths_from_folder(self) -> List[str]:
"""扫描所选文件夹,收集所有 .tif 和 .bsq 文件路径"""
folder = (self.geotiff_dir_edit.text() or "").strip()
if not folder or not os.path.isdir(folder):
return []
root = Path(folder)
tif_files = sorted(root.glob("*.tif"))
bsq_files = sorted(root.glob("*.bsq"))
return [str(p) for p in tif_files + bsq_files if p.is_file()]
def _step14_base_pipeline_kwargs(self) -> dict:
return {
'boundary_shp_path': self.boundary_file.get_path(),
'resolution': self.resolution.value(),
'input_crs': self.input_crs.text(),
'output_crs': self.output_crs.text(),
'show_sample_points': self.show_points.isChecked(),
'use_distance_diffusion': self.use_diffusion.isChecked(),
}
def get_config(self):
pred_csv = (self.prediction_csv_file.get_path() or "").strip()
folder_mode = self.mode_folder_rb.isChecked()
pred_dir = (self.prediction_csv_dir_edit.text() or "").strip()
geotiff_path = (self.geotiff_file.get_path() or "").strip()
config = {
'step14_batch_mode': 'folder' if folder_mode else 'single',
'render_mode': self.render_mode_combo.currentText(),
'prediction_csv_dir': pred_dir if pred_dir else None,
'recursive_csv_scan': self.recursive_csv_cb.isChecked(),
'prediction_csv_path': None if folder_mode else (pred_csv if pred_csv else None),
'geotiff_path': geotiff_path if geotiff_path else None,
'geotiff_dir': (self.geotiff_dir_edit.text() or "").strip() or None,
'boundary_shp_path': self.boundary_file.get_path(),
'resolution': self.resolution.value(),
'input_crs': self.input_crs.text(),
'output_crs': self.output_crs.text(),
'show_sample_points': self.show_points.isChecked(),
'use_distance_diffusion': self.use_diffusion.isChecked(),
}
out_dir = (self.output_dir.get_path() or "").strip()
if not folder_mode and pred_csv and out_dir:
stem = Path(pred_csv).stem
config['output_image_path'] = str(Path(out_dir) / f"{stem}_distribution.png")
else:
config['output_image_path'] = None
return config
def set_config(self, config):
mode = config.get('step14_batch_mode', 'single')
if mode == 'folder':
self.mode_folder_rb.setChecked(True)
else:
self.mode_single_rb.setChecked(True)
render_mode = config.get('render_mode', 'CSV 插值模式')
idx = self.render_mode_combo.findText(render_mode)
if idx >= 0:
self.render_mode_combo.setCurrentIndex(idx)
if config.get('prediction_csv_dir'):
self.prediction_csv_dir_edit.setText(str(config['prediction_csv_dir']))
if 'recursive_csv_scan' in config:
self.recursive_csv_cb.setChecked(bool(config['recursive_csv_scan']))
if 'prediction_csv_path' in config and config['prediction_csv_path']:
self.prediction_csv_file.set_path(str(config['prediction_csv_path']))
if 'geotiff_path' in config and config['geotiff_path']:
self.geotiff_file.set_path(str(config['geotiff_path']))
if 'geotiff_dir' in config and config['geotiff_dir']:
self.geotiff_dir_edit.setText(str(config['geotiff_dir']))
if 'boundary_shp_path' in config:
self.boundary_file.set_path(config['boundary_shp_path'])
if 'resolution' in config:
self.resolution.setValue(config['resolution'])
if 'input_crs' in config:
self.input_crs.setText(config['input_crs'])
if 'output_crs' in config:
self.output_crs.setText(config['output_crs'])
if 'show_sample_points' in config:
self.show_points.setChecked(config['show_sample_points'])
if 'use_distance_diffusion' in config:
self.use_diffusion.setChecked(config['use_distance_diffusion'])
if 'output_dir' in config and config['output_dir']:
self.output_dir.set_path(str(config['output_dir']))
elif config.get('output_image_path'):
p = Path(str(config['output_image_path']))
if p.parent and str(p.parent) != '.':
self.output_dir.set_path(str(p.parent))
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充预测结果目录
优先使用 Step8机器学习预测的输出目录作为待预测 CSV 目录;
其次回退到 Step8.5(回归预测)或 Step8.75(自定义回归预测)的输出目录。
Args:
work_dir: 工作目录路径
pipeline: Pipeline 实例(未使用,保留接口兼容性)
"""
try:
import traceback
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
else:
self.work_dir = None
main_window = self.window()
if not main_window:
return
# 1. 优先:从 Step9机器学习预测读输出目录9_ML_Prediction 子目录
# 修复张冠李戴:原 main_window.step11_prediction_panel 不存在
pred_dir = None
step10_output = get_step_output_path(
main_window, 'step11_ml_prediction', work_dir=self.work_dir,
widget_attr='output_file', fallback_key='step9_ml_predict',
)
if step10_output:
base_pred_dir = str(Path(step10_output).parent)
ml_pred_dir = Path(base_pred_dir) / "9_ML_Prediction"
pred_dir = str(ml_pred_dir) if ml_pred_dir.exists() else base_pred_dir
# 2. 备选:从 Step8非经验预测读输出目录
# 修复张冠李戴:原 main_window.step11_panel 不存在
if not pred_dir:
step8_5_output = get_step_output_path(
main_window, 'step12_regression_prediction', work_dir=self.work_dir,
widget_attr='output_file', fallback_key='step8_ml_train',
)
if step8_5_output:
pred_dir = str(Path(step8_5_output).parent)
# 3. 备选:从 Step13 panel自定义回归读输出目录
# 修复张冠李戴:原 main_window.step12_panel 不存在
if not pred_dir:
step8_75_output = get_step_output_path(
main_window, 'step13_custom_regression', work_dir=self.work_dir,
widget_attr='output_dir_widget', fallback_key='custom_regression',
)
if step8_75_output:
pred_dir = step8_75_output
# 自动填入"预测CSV目录"(文件夹批量模式)
if pred_dir:
existing_dir = (self.prediction_csv_dir_edit.text() or "").strip()
if not existing_dir:
self.prediction_csv_dir_edit.setText(pred_dir)
# 切换到文件夹批量模式
self.mode_folder_rb.setChecked(True)
# 4. 自动填充输出目录14_visualization
if self.work_dir:
output_dir = resolve_subdir(self.work_dir, 'visualization')
os.makedirs(output_dir, exist_ok=True)
existing_out = self.output_dir.get_path()
if not existing_out or not existing_out.strip():
self.output_dir.set_path(output_dir)
# 5. 自动探测原始矢量边界文件(.shp作为专题图底图
# 优先回溯 input-test/roi.shpgeopandas.read_file 仅支持矢量格式
if self.work_dir:
possible_shp = None
candidates = [
Path(self.work_dir).parent / "input-test" / "roi.shp",
Path(self.work_dir) / "roi.shp",
Path(self.work_dir).parent / "roi.shp",
]
for candidate in candidates:
if candidate.exists() and candidate.suffix.lower() == ".shp":
possible_shp = candidate
break
existing_boundary = (self.boundary_file.get_path() or "").strip()
if not existing_boundary and possible_shp:
self.boundary_file.set_path(str(possible_shp))
elif not existing_boundary:
self.boundary_file.set_path("")
print("⚠️ 提示:专题图生成模块需传入标准矢量边界文件 (.shp),请手动选择。")
# 6. 自动探测 Step 8 输出的水色指数 GeoTIFFGeoTIFF 渲染模式)
step10_out_dir = Path(self.work_dir) / "10_WaterIndex_Images" if self.work_dir else None
if step10_out_dir and step10_out_dir.is_dir():
# GeoTIFF 批量模式:填充目录供批量渲染
if not (self.geotiff_dir_edit.text() or "").strip():
self.geotiff_dir_edit.setText(str(step10_out_dir))
# GeoTIFF 单文件模式:默认选中第一个
tif_files = sorted(step10_out_dir.glob("*.tif"))
if tif_files and not (self.geotiff_file.get_path() or "").strip():
self.geotiff_file.set_path(str(tif_files[0]))
except Exception as e:
import traceback
print(f"{self.__class__.__name__}】自动填充失败,跳过: {e}")
traceback.print_exc()
def browse_output_dir(self):
"""浏览输出目录"""
default = self._get_default_work_dir()
if default:
default = resolve_subdir(default, 'visualization')
dir_path = QFileDialog.getExistingDirectory(self, "选择输出分布图目录", default)
if dir_path:
self.output_dir.set_path(dir_path)
def _start_batch_run(self, csv_list, work_dir, base_kw, out_dir_opt, parent):
"""封装 CSV 批量启动逻辑,统一处理信号连接和进度条"""
self.run_button.setEnabled(False)
self.progress_bar.setVisible(True)
self.progress_bar.setValue(0)
self._batch_thread = Step14BatchThread(work_dir, csv_list, base_kw, out_dir_opt)
main_win = parent
def _batch_log(msg, lvl):
if hasattr(main_win, "log_message"):
main_win.log_message(msg, lvl)
def _on_progress(cur, total):
if total > 0:
self.progress_bar.setMaximum(total)
self.progress_bar.setValue(cur)
self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)")
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection)
self._batch_thread.finished_ok.connect(self._on_step14_batch_ok, Qt.QueuedConnection)
self._batch_thread.failed.connect(self._on_step14_batch_fail, Qt.QueuedConnection)
self._batch_thread.finished.connect(
lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)),
Qt.QueuedConnection,
)
self._batch_thread.start()
if hasattr(parent, "log_message"):
parent.log_message(f"专题图批量:共 {len(csv_list)} 个 CSV工作目录 {work_dir}", "info")
def run_step(self):
"""独立运行步骤14"""
if self._batch_thread and self._batch_thread.isRunning():
QMessageBox.information(self, "提示", "批量任务正在运行,请稍候。")
return
boundary_shp_path = self.boundary_file.get_path()
if not boundary_shp_path:
QMessageBox.warning(self, "输入验证失败", "请选择边界文件")
return
if not os.path.exists(boundary_shp_path):
QMessageBox.warning(self, "输入验证失败", "边界文件不存在")
return
parent = self.parent()
while parent and not hasattr(parent, 'run_single_step'):
parent = parent.parent()
if not parent or not hasattr(parent, 'run_single_step'):
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
return
if self.mode_folder_rb.isChecked():
# -------- CSV 插值批量 --------
if self.render_mode_combo.currentText() != "GeoTIFF 栅格模式":
csv_list = self._collect_csv_paths_from_folder()
if not csv_list:
QMessageBox.warning(
self,
"输入验证失败",
"所选文件夹中未找到 .csv 文件,或目录无效。\n"
"可勾选「包含子文件夹」以递归扫描。",
)
return
if not PIPELINE_AVAILABLE:
QMessageBox.critical(self, "错误", "Pipeline 模块不可用,无法批量生成专题图。")
return
work_dir = getattr(parent, "work_dir", None) or "./work_dir"
work_dir = str(work_dir)
base_kw = self._step14_base_pipeline_kwargs()
out_dir_opt = (self.output_dir.get_path() or "").strip() or None
self._start_batch_run(csv_list, work_dir, base_kw, out_dir_opt, parent)
return
# -------- GeoTIFF 栅格批量 --------
tif_list = self._collect_tif_paths_from_folder()
if not tif_list:
QMessageBox.warning(
self,
"输入验证失败",
"所选文件夹中未找到 .tif / .bsq 文件,\n"
"请确认目录包含步骤8输出的水色指数 GeoTIFF 文件。",
)
return
out_dir = (self.output_dir.get_path() or "").strip()
if not out_dir:
out_dir = resolve_subdir(self._get_default_work_dir(), 'visualization')
os.makedirs(out_dir, exist_ok=True)
self.run_button.setEnabled(False)
self.progress_bar.setVisible(True)
self.progress_bar.setValue(0)
self._batch_thread = Step14GeoTIFFBatchThread(
tif_paths=tif_list,
output_dir=out_dir,
boundary_shp_path=boundary_shp_path,
input_crs=self.input_crs.text(),
output_crs=self.output_crs.text(),
)
main_win = parent
def _batch_log(msg, lvl):
if hasattr(main_win, "log_message"):
main_win.log_message(msg, lvl)
def _on_progress(cur, total):
if total > 0:
pct = int(cur / total * 100)
self.progress_bar.setMaximum(total)
self.progress_bar.setValue(cur)
self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)")
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection)
self._batch_thread.finished_ok.connect(self._on_step14_batch_ok, Qt.QueuedConnection)
self._batch_thread.failed.connect(self._on_step14_batch_fail, Qt.QueuedConnection)
self._batch_thread.finished.connect(
lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)),
Qt.QueuedConnection,
)
self._batch_thread.start()
if hasattr(parent, "log_message"):
parent.log_message(f"GeoTIFF 批量渲染:共 {len(tif_list)} 个文件 → {out_dir}", "info")
return
# -------- GeoTIFF 栅格单文件模式 --------
if self.render_mode_combo.currentText() == "GeoTIFF 栅格模式":
geotiff_path = (self.geotiff_file.get_path() or "").strip()
if not geotiff_path:
QMessageBox.warning(self, "输入验证失败", "请选择水色指数 GeoTIFF 文件")
return
if not os.path.isfile(geotiff_path):
QMessageBox.warning(self, "输入验证失败", f"GeoTIFF 文件不存在:\n{geotiff_path}")
return
boundary_shp_path = self.boundary_file.get_path()
input_crs = self.input_crs.text()
output_crs = self.output_crs.text()
# 构造输出路径
out_dir = (self.output_dir.get_path() or "").strip()
if not out_dir:
out_dir = resolve_subdir(self._get_default_work_dir(), 'visualization')
os.makedirs(out_dir, exist_ok=True)
tif_stem = Path(geotiff_path).stem
chinese_name = mapper._get_chinese_title(tif_stem)
output_png = os.path.join(out_dir, f"{chinese_name}_专题图.png")
self.run_button.setEnabled(False)
try:
from src.postprocessing.map import ContentMapper
mapper = ContentMapper()
result_path = mapper.visualize_raster(
raster_tif_path=geotiff_path,
output_file=output_png,
boundary_shp_path=boundary_shp_path if boundary_shp_path else None,
nodata_value=-9999.0,
figsize=(14, 10),
alpha=0.9,
)
self.run_button.setEnabled(True)
QMessageBox.information(
self, "完成",
f"GeoTIFF 栅格渲染完成!\n{result_path}"
)
if hasattr(parent, "log_message"):
parent.log_message(f"Step14 GeoTIFF 渲染完成 → {result_path}", "info")
except Exception as e:
self.run_button.setEnabled(True)
QMessageBox.critical(self, "渲染失败", f"{e}\n{traceback.format_exc()[:500]}")
if hasattr(parent, "log_message"):
parent.log_message(str(e), "error")
return
prediction_csv_path = (self.prediction_csv_file.get_path() or "").strip()
if not prediction_csv_path:
QMessageBox.warning(
self,
"输入验证失败",
"请选择「预测结果 CSV」文件或切换到「文件夹批量」。",
)
return
if not os.path.isfile(prediction_csv_path):
QMessageBox.warning(self, "输入验证失败", "预测结果 CSV 不存在或不是文件")
return
config = self.get_config()
parent.run_single_step('step14', {'step14': config})
def _on_step14_batch_ok(self, n: int):
self.progress_bar.setVisible(False)
QMessageBox.information(self, "完成", f"已批量生成 {n} 个分布图。")
parent = self.parent()
while parent and not hasattr(parent, "log_message"):
parent = parent.parent()
if parent and hasattr(parent, "log_message"):
parent.log_message(f"专题图批量完成,共 {n} 个文件。", "info")
def _on_step14_batch_fail(self, err: str):
self.progress_bar.setVisible(False)
QMessageBox.critical(self, "失败", f"批量生成中断:\n{err[:900]}")
parent = self.parent()
while parent and not hasattr(parent, "log_message"):
parent = parent.parent()
if parent and hasattr(parent, "log_message"):
parent.log_message(err, "error")

View File

@ -1,326 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step7 面板 - 水质指数计算
"""
import os
import sys
import pandas as pd
from pathlib import Path
from typing import Dict, List, Optional
# 路径归一化 helper与 pipeline.get_step_output_dir 互为表里)
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
sys.path.insert(0, _HERE)
from _step_path_resolver import resolve_subdir
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
QRadioButton, QButtonGroup
)
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QColor, QBrush, QFont
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
def get_resource_path(relative_path: str) -> str:
"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
if hasattr(sys, '_MEIPASS'):
internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
if os.path.exists(internal):
return internal
return os.path.join(sys._MEIPASS, relative_path)
exe_dir = os.path.dirname(sys.executable)
internal = os.path.join(exe_dir, '_internal', relative_path)
if os.path.exists(internal):
return internal
base_dir = Path(__file__).resolve().parent.parent / "model"
return str(base_dir / os.path.basename(relative_path))
class Step7IndexPanel(QWidget):
COLOR_RATIO = QColor(255, 255, 255)
COLOR_CONCENTRATION = QColor(220, 240, 255)
COLOR_HEADER = QColor(245, 245, 245)
def __init__(self, parent=None):
super().__init__(parent)
self.index_checkboxes: Dict[str, QListWidgetItem] = {}
self.work_dir: Optional[str] = None
self.builtin_formula_path = get_resource_path("waterindex.csv")
self._formula_type_map: Dict[str, str] = {}
self._formula_color_map: Dict[str, QColor] = {}
self._formula_coef_map: Dict[str, List[float]] = {}
self.init_ui()
self._auto_load_formulas()
def init_ui(self):
main_layout = QVBoxLayout()
main_layout.setContentsMargins(20, 20, 20, 20)
main_layout.setSpacing(10)
# 1. 公式配置源 (只读)
path_group = QGroupBox("公式配置源 (内置)")
path_layout = QVBoxLayout()
self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
self.formula_csv_widget.set_path(self.builtin_formula_path)
self.formula_csv_widget.set_read_only(True)
self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
path_layout.addWidget(self.formula_csv_widget)
path_group.setLayout(path_layout)
main_layout.addWidget(path_group)
# 2. 训练数据输入
input_group = QGroupBox("输入样本数据")
input_layout = QVBoxLayout()
self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
input_layout.addWidget(self.training_data_widget)
input_group.setLayout(input_layout)
main_layout.addWidget(input_group)
# 3. 公式选择区 (分组 ListWidget)
self.formula_group = QGroupBox("待计算水质指数勾选")
formula_outer_layout = QVBoxLayout()
btn_layout = QHBoxLayout()
self.select_all_btn = QPushButton("全选")
self.deselect_all_btn = QPushButton("清空")
self.select_ratio_btn = QPushButton("仅选比值型")
self.select_conc_btn = QPushButton("仅选浓度型")
self.select_all_btn.clicked.connect(self.select_all_formulas)
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
self.select_ratio_btn.clicked.connect(self._select_ratio_only)
self.select_conc_btn.clicked.connect(self._select_conc_only)
btn_layout.addWidget(self.select_all_btn)
btn_layout.addWidget(self.deselect_all_btn)
btn_layout.addWidget(self.select_ratio_btn)
btn_layout.addWidget(self.select_conc_btn)
btn_layout.addStretch()
self.refresh_button = QPushButton("重新加载")
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
btn_layout.addWidget(self.refresh_button)
formula_outer_layout.addLayout(btn_layout)
scroll = QScrollArea()
scroll.setWidgetResizable(True)
scroll.setMinimumHeight(280)
self.scroll_content = QWidget()
self.formula_layout = QVBoxLayout(self.scroll_content)
self.formula_layout.setContentsMargins(4, 4, 4, 4)
self.formula_layout.setSpacing(2)
self.formula_layout.setAlignment(Qt.AlignTop)
self.formula_list = QListWidget()
self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
self.formula_list.setMinimumHeight(300)
self.formula_list.itemChanged.connect(self._on_item_changed)
self.formula_layout.addWidget(self.formula_list)
scroll.setWidget(self.scroll_content)
formula_outer_layout.addWidget(scroll)
self.formula_group.setLayout(formula_outer_layout)
main_layout.addWidget(self.formula_group)
# 4. 执行设置
output_group = QGroupBox("执行设置")
output_layout = QVBoxLayout()
self.enable_checkbox = QCheckBox("启用计算流程")
self.enable_checkbox.setChecked(True)
output_layout.addWidget(self.enable_checkbox)
output_group.setLayout(output_layout)
main_layout.addWidget(output_group)
# 5. 运行按钮
self.run_button = QPushButton("立即执行计算")
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_button.setMinimumHeight(40)
self.run_button.clicked.connect(self.run_step)
main_layout.addWidget(self.run_button)
self.setLayout(main_layout)
def _on_item_changed(self, item: QListWidgetItem):
if item.checkState() == Qt.Checked:
bg_color = self.COLOR_RATIO
for name, ref_item in self.index_checkboxes.items():
if ref_item is item:
bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
break
item.setBackground(QBrush(bg_color))
else:
item.setBackground(QBrush(self.COLOR_RATIO))
def _auto_load_formulas(self):
if os.path.exists(self.builtin_formula_path):
self.refresh_formulas(silent=True)
else:
print(f"DEBUG: 自动加载失败,路径不存在: {self.builtin_formula_path}")
def refresh_formulas(self, silent=False):
path = self.builtin_formula_path
if not os.path.exists(path):
if not silent:
QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
return
try:
df = None
for enc in ('utf-8', 'gbk', 'utf-8-sig'):
try:
df = pd.read_csv(path, encoding=enc)
if 'Formula_Name' in df.columns:
break
except Exception:
continue
if df is None or 'Formula_Name' not in df.columns:
if not silent:
QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name'")
return
self._formula_type_map.clear()
self._formula_coef_map.clear()
for _, row in df.iterrows():
name = str(row['Formula_Name']).strip()
if not name:
continue
ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
self._formula_type_map[name] = ftype
# Parse Coefficient for concentration formulas
coef_str = str(row.get('Coefficient', '')).strip()
if coef_str:
try:
coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
self._formula_coef_map[name] = coeffs
except Exception:
self._formula_coef_map[name] = []
else:
self._formula_coef_map[name] = []
self.formula_list.clear()
self.index_checkboxes.clear()
self._formula_color_map.clear()
for name, ftype in self._formula_type_map.items():
item = QListWidgetItem(name, self.formula_list)
item.setCheckState(Qt.Checked)
if ftype == 'concentration':
bg_color = QColor(220, 240, 255)
else:
bg_color = self.COLOR_RATIO
self._formula_color_map[name] = bg_color
item.setBackground(QBrush(bg_color))
self.index_checkboxes[name] = item
self.formula_list.adjustSize()
print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
except Exception as e:
if not silent:
QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
def _select_ratio_only(self):
for name, item in self.index_checkboxes.items():
ftype = self._formula_type_map.get(name, 'ratio')
item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
def _select_conc_only(self):
for name, item in self.index_checkboxes.items():
ftype = self._formula_type_map.get(name, 'ratio')
item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
def select_all_formulas(self):
for item in self.index_checkboxes.values():
item.setCheckState(Qt.Checked)
def deselect_all_formulas(self):
for item in self.index_checkboxes.values():
item.setCheckState(Qt.Unchecked)
def get_config(self) -> dict:
"""获取配置"""
selected = [
name for name, item in self.index_checkboxes.items()
if item.checkState() == Qt.Checked
]
config = {
'training_csv_path': self.training_data_widget.get_path(),
'formula_csv_file': self.builtin_formula_path,
'formula_names': selected,
'enabled': self.enable_checkbox.isChecked(),
'output_mode': 0,
}
work_dir = self._get_work_dir()
if work_dir:
track_a_dir = resolve_subdir(work_dir, 'indices')
os.makedirs(track_a_dir, exist_ok=True)
config['output_file'] = os.path.join(track_a_dir, "training_spectra_indices.csv").replace('\\', '/')
return config
def set_config(self, config: Dict):
if 'training_csv_path' in config:
self.training_data_widget.set_path(config['training_csv_path'])
if 'formula_names' in config:
sel = set(config['formula_names'])
for name, item in self.index_checkboxes.items():
item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked)
self.enable_checkbox.setChecked(config.get('enabled', True))
def update_from_config(self, work_dir=None, pipeline=None):
if work_dir:
self.work_dir = work_dir
main = self.window()
if hasattr(main, 'step6_panel'):
p5 = main.step6_panel.output_file.get_path()
if p5:
if not os.path.isabs(p5):
p5 = os.path.join(self.work_dir or '', p5)
p5 = p5.replace('\\', '/')
self.training_data_widget.set_path(p5)
def _get_work_dir(self) -> Optional[str]:
if self.work_dir:
return self.work_dir
main = self.window()
if hasattr(main, 'work_dir') and main.work_dir:
return main.work_dir
return None
def run_step(self):
"""独立运行步骤7 (通过标准的 Worker 路由下发)"""
config = self.get_config()
if not config['enabled']:
QMessageBox.information(self, "提示", "已禁用计算流程(启用计算流程未勾选)")
return
training_path = config.get('training_csv_path')
if not training_path or not os.path.exists(training_path):
QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件")
return
if not config.get('formula_names'):
QMessageBox.warning(self, "提示", "请至少勾选一个公式")
return
main_window = self.window()
if hasattr(main_window, 'run_single_step'):
pipeline_config = {'step7_index': config}
main_window.run_single_step('step7_index', pipeline_config)

View File

@ -100,13 +100,11 @@ class Step8MlTrainPanel(QWidget):
self.create_ml_page()
layout.addWidget(self.ml_page)
# 输出文件路径
# 输出文件路径 (改为文件夹模式)
self.output_path = FileSelectWidget(
"输出文件:",
"CSV Files (*.csv);;All Files (*.*)",
mode="save"
"模型输出目录:",
"Directories"
)
self.output_path.line_edit.setPlaceholderText("自动生成,或手动指定输出文件路径...")
self.output_path.browse_btn.clicked.disconnect()
self.output_path.browse_btn.clicked.connect(self.browse_output_path)
layout.addWidget(self.output_path)
@ -276,28 +274,12 @@ class Step8MlTrainPanel(QWidget):
return ""
def browse_output_path(self):
"""浏览输出文件路径(保存对话框)"""
current = self.output_path.get_path().strip()
if current:
initial_dir = os.path.dirname(current)
initial_file = os.path.basename(current)
else:
initial_dir = ""
initial_file = ""
if not initial_dir or not os.path.isdir(initial_dir):
# 默认定位到 indices 目录
work_dir = self._get_default_work_dir()
initial_dir = resolve_subdir(work_dir, 'indices') if work_dir else ""
if initial_dir and not os.path.isdir(initial_dir):
os.makedirs(initial_dir, exist_ok=True)
file_path, _ = QFileDialog.getSaveFileName(
self, "保存输出文件", os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
"CSV Files (*.csv);;All Files (*.*)"
)
if file_path:
self.output_path.set_path(file_path)
"""浏览输出模型目录"""
work_dir = getattr(self, 'work_dir', "")
initial_dir = os.path.join(work_dir, '8_Machine_Learning_Models') if work_dir else ""
dir_path = QFileDialog.getExistingDirectory(self, "选择模型输出目录", initial_dir)
if dir_path:
self.output_path.set_path(dir_path)
def get_config(self):
"""获取配置"""
@ -381,20 +363,12 @@ class Step8MlTrainPanel(QWidget):
if step6_training_csv:
self.training_csv_file.set_path(step6_training_csv)
# 2. 自动填充输出文件路径(基于工作目录和输入文件名)
# 输入是 training_spectra.csv → 输出 {work_dir}/7_Water_Quality_Indices/training_spectra_indices.csv
# 输入是 sampling_spectra.csv → 输出 {work_dir}/7_Water_Quality_Indices/sampling_spectra_indices.csv
# 2. 自动填充输出目录为 8_Machine_Learning_Models
if self.work_dir:
indices_dir = resolve_subdir(self.work_dir, 'indices')
os.makedirs(indices_dir, exist_ok=True)
training_csv = self.training_csv_file.get_path()
if training_csv:
basename = os.path.splitext(os.path.basename(training_csv))[0]
output_file = f"{basename}_indices.csv"
else:
output_file = "training_spectra_indices.csv"
output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
self.output_path.set_path(output_path)
import os
models_dir = os.path.join(self.work_dir, "8_Machine_Learning_Models").replace('\\', '/')
os.makedirs(models_dir, exist_ok=True)
self.output_path.set_path(models_dir)
else:
self.output_path.set_path("")

View File

@ -1,312 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step8 面板 - 非经验统计回归建模
"""
import os
import sys
from pathlib import Path
# 路径归一化 helper与 pipeline.get_step_output_dir 互为表里)
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
sys.path.insert(0, _HERE)
from _step_path_resolver import get_step_output_path, resolve_step_widget, resolve_subdir
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
QHBoxLayout, QLabel, QCheckBox, QSpinBox, QPushButton,
QFileDialog, QMessageBox,
)
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
class Step8NonEmpiricalPanel(QWidget):
"""步骤8非经验统计回归建模"""
def __init__(self, parent=None):
super().__init__(parent)
self.init_ui()
def init_ui(self):
layout = QVBoxLayout()
# 标题
# 训练数据文件(用于独立运行)
self.training_csv_file = FileSelectWidget(
"训练数据CSV:",
"CSV Files (*.csv);;All Files (*.*)"
)
layout.addWidget(self.training_csv_file)
# 参数设置
params_group = QGroupBox("模型参数")
params_layout = QFormLayout()
# 预处理方法
self.preproc_checkboxes = {}
preproc_group = QGroupBox("预处理方法 (可多选)")
preproc_layout = QVBoxLayout()
preproc_grid = QGridLayout()
preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
for i, method in enumerate(preproc_methods):
checkbox = QCheckBox(method)
checkbox.setChecked(True)
self.preproc_checkboxes[method] = checkbox
preproc_grid.addWidget(checkbox, i // 4, i % 4)
button_layout = QHBoxLayout()
select_all_btn = QPushButton("全选")
deselect_all_btn = QPushButton("全不选")
select_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, True))
deselect_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, False))
button_layout.addWidget(select_all_btn)
button_layout.addWidget(deselect_all_btn)
button_layout.addStretch()
preproc_layout.addLayout(preproc_grid)
preproc_layout.addLayout(button_layout)
preproc_group.setLayout(preproc_layout)
params_layout.addRow(preproc_group)
# 算法选择(可多选)
self.algorithm_inputs = {}
algorithms_widget = QWidget()
algorithms_layout = QVBoxLayout()
algorithms_layout.setContentsMargins(0, 0, 0, 0)
algorithms_layout.setSpacing(4)
algorithm_list = ['chl_a', 'nh3', 'mno4', 'tn', 'tp', 'tss']
for algorithm in algorithm_list:
row_widget = QWidget()
row_layout = QHBoxLayout()
row_layout.setContentsMargins(0, 0, 0, 0)
checkbox = QCheckBox(algorithm)
checkbox.setChecked(True)
spinbox = QSpinBox()
spinbox.setRange(0, 500)
spinbox.setValue(0)
spinbox.setMaximumWidth(90)
row_layout.addWidget(checkbox)
row_layout.addWidget(QLabel("对应值列索引:"))
row_layout.addWidget(spinbox)
row_layout.addStretch()
row_widget.setLayout(row_layout)
algorithms_layout.addWidget(row_widget)
self.algorithm_inputs[algorithm] = (checkbox, spinbox)
algorithms_widget.setLayout(algorithms_layout)
params_layout.addRow("非经验算法选择:", algorithms_widget)
# 光谱起始列
self.spectral_start_col = QSpinBox()
self.spectral_start_col.setRange(0, 100)
self.spectral_start_col.setValue(1)
params_layout.addRow("光谱起始列索引:", self.spectral_start_col)
# 窗口大小 (变量名已修正,避免覆盖 QWidget.window)
self.window_size_spinbox = QSpinBox()
self.window_size_spinbox.setRange(1, 20)
self.window_size_spinbox.setValue(5)
params_layout.addRow("窗口大小:", self.window_size_spinbox)
params_group.setLayout(params_layout)
layout.addWidget(params_group)
# 输出文件路径
self.output_dir = FileSelectWidget(
"输出模型目录:",
"Directories;;All Files (*.*)"
)
self.output_dir.line_edit.setPlaceholderText("8_Regression_Modeling")
self.output_dir.browse_btn.clicked.disconnect()
self.output_dir.browse_btn.clicked.connect(self.browse_output_dir)
layout.addWidget(self.output_dir)
# 启用步骤
self.enable_checkbox = QCheckBox("启用此步骤")
self.enable_checkbox.setChecked(True)
layout.addWidget(self.enable_checkbox)
# 独立运行按钮
self.run_button = QPushButton("独立运行此步骤")
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_button.clicked.connect(self.run_step)
layout.addWidget(self.run_button)
layout.addStretch()
self.setLayout(layout)
def get_config(self):
"""获取配置"""
selected_algorithms = [
name for name, (checkbox, _) in self.algorithm_inputs.items()
if checkbox.isChecked()
]
if not selected_algorithms:
selected_algorithms = list(self.algorithm_inputs.keys())
value_cols = {
name: spinbox.value()
for name, (_, spinbox) in self.algorithm_inputs.items()
if name in selected_algorithms
}
preprocessing_methods = [
method for method, checkbox in self.preproc_checkboxes.items()
if checkbox.isChecked()
] or ['None']
config = {
'preprocessing_methods': preprocessing_methods,
'algorithms': selected_algorithms,
'value_cols': value_cols,
'spectral_start_col': self.spectral_start_col.value(),
'window': self.window_size_spinbox.value(),
'enabled': self.enable_checkbox.isChecked()
}
output_dir = self.output_dir.get_path()
if not output_dir:
main_window = self.parent().window()
if hasattr(main_window, 'work_dir') and main_window.work_dir:
output_dir = str(Path(main_window.work_dir) / "8_Regression_Modeling")
else:
output_dir = str(Path.cwd() / "8_Regression_Modeling")
config['output_dir'] = output_dir
training_csv_path = self.training_csv_file.get_path()
if training_csv_path:
config['csv_path'] = training_csv_path
return config
def set_config(self, config):
"""设置配置"""
if 'preprocessing_methods' in config:
methods = config['preprocessing_methods']
for method, checkbox in self.preproc_checkboxes.items():
checkbox.setChecked(method in methods)
if 'algorithms' in config:
algorithm_values = config['algorithms']
for algorithm, (checkbox, spinbox) in self.algorithm_inputs.items():
checkbox.setChecked(algorithm in algorithm_values)
if 'value_cols' in config:
value_cols = config['value_cols']
if isinstance(value_cols, dict):
for algorithm, (_, spinbox) in self.algorithm_inputs.items():
if algorithm in value_cols:
spinbox.setValue(value_cols[algorithm])
else:
for _, spinbox in self.algorithm_inputs.values():
spinbox.setValue(value_cols)
if 'spectral_start_col' in config:
self.spectral_start_col.setValue(config['spectral_start_col'])
if 'window' in config:
self.window_size_spinbox.setValue(config['window'])
if 'output_dir' in config:
self.output_dir.set_path(config['output_dir'])
if 'csv_path' in config:
self.training_csv_file.set_path(config['csv_path'])
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充训练数据和输出路径
Args:
work_dir: 工作目录路径
pipeline: Pipeline 实例(未使用,保留接口兼容性)
"""
try:
import traceback
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
else:
self.work_dir = None
# 借用父组件的 window() 方法,安全绕过当前类的命名冲突
parent_widget = self.parentWidget()
main_window = parent_widget.window() if parent_widget else None
# 1. 强制读 Step 6 的 training_spectra.csv光谱特征提取结果
# 修复张冠李戴:原链路 STEP_DATA_SOURCE['training_spectra_csv'] → step5_clean_panel
# 错误地指向 Step 5 的 processed_data.csv纯清洗数据不含光谱特征
# 实际非经验建模需要的特征数据来自 Step 6 的 6_Spectral_Feature_Extraction/training_spectra.csv
existing_csv = self.training_csv_file.get_path()
if not existing_csv or not existing_csv.strip():
if self.work_dir:
step6_dir = resolve_subdir(self.work_dir, 'spectral_feature')
step6_training_csv = os.path.join(
step6_dir, 'training_spectra.csv'
).replace('\\', '/')
if step6_training_csv:
self.training_csv_file.set_path(step6_training_csv)
# 2. 自动填充输出目录8_Regression_Modeling
if self.work_dir:
output_dir = resolve_subdir(self.work_dir, 'regression_modeling')
os.makedirs(output_dir, exist_ok=True)
existing_out = self.output_dir.get_path()
if not existing_out or not existing_out.strip():
self.output_dir.set_path(output_dir)
except Exception as e:
import traceback
print(f"{self.__class__.__name__}】自动填充失败,跳过: {e}")
traceback.print_exc()
def _get_default_work_dir(self):
"""获取 work_dir优先用 panel 自身缓存的,否则尝试从主窗口取"""
if hasattr(self, 'work_dir') and self.work_dir:
return str(self.work_dir)
# 借用父组件的 window() 方法,安全绕过当前类的命名冲突
parent_widget = self.parentWidget()
mw = parent_widget.window() if parent_widget else None
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
return str(mw.work_dir)
return ""
def browse_output_dir(self):
"""浏览输出目录"""
default = self._get_default_work_dir()
if default:
default = resolve_subdir(default, 'regression_modeling')
dir_path = QFileDialog.getExistingDirectory(self, "选择输出模型目录", default)
if dir_path:
self.output_dir.set_path(dir_path)
def run_step(self):
"""独立运行步骤8"""
training_csv_path = self.training_csv_file.get_path()
if not training_csv_path:
QMessageBox.warning(self, "输入错误", "请选择训练数据CSV文件")
return
if not os.path.exists(training_csv_path):
QMessageBox.warning(self, "输入错误", "训练数据CSV文件不存在")
return
config = self.get_config()
parent = self.parent()
while parent and not hasattr(parent, 'run_single_step'):
parent = parent.parent()
if parent and hasattr(parent, 'run_single_step'):
parent.run_single_step('step8_non_empirical_modeling', {'step8_non_empirical_modeling': config})
else:
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
def _toggle_checkboxes(self, checkboxes_dict, checked):
"""统一设置预处理checkbox状态"""
for checkbox in checkboxes_dict.values():
checkbox.setChecked(checked)

View File

@ -1,337 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step8 面板 - QAA 物理反演(非经验模型)
"""
import os
import sys
# 路径归一化 helper与 pipeline.get_step_output_dir 互为表里)
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
sys.path.insert(0, _HERE)
from _step_path_resolver import resolve_subdir
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
QHBoxLayout, QLabel, QLineEdit, QComboBox, QCheckBox,
QPushButton, QFileDialog, QMessageBox,
)
from PyQt5.QtGui import QFont
from PyQt5.QtCore import Qt
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
from src.utils.water_owt_config import (
get_all_lake_names,
get_lake_config,
get_lambda_0,
get_default_lake,
)
from src.core.algorithms.qaa import QAABaselineSolver
class Step8QAAPanel(QWidget):
"""步骤8QAA 物理反演(非经验模型)"""
def __init__(self, parent=None):
super().__init__(parent)
self.init_ui()
def init_ui(self):
layout = QVBoxLayout()
title = QLabel("步骤8QAA 物理反演(非经验模型)")
title.setFont(QFont("Arial", 12, QFont.Bold))
layout.addWidget(title)
# 光谱 CSV 文件输入
self.spectrum_csv_file = FileSelectWidget(
"光谱 CSV 文件:",
"CSV Files (*.csv);;All Files (*.*)"
)
self.spectrum_csv_file.line_edit.setPlaceholderText(
"选择实测光谱或采样点光谱 CSV含波长列"
)
layout.addWidget(self.spectrum_csv_file)
# 水域类型选择
lake_group = QGroupBox("水域类型配置")
lake_layout = QFormLayout()
self.lake_combo = QComboBox()
lake_names = get_all_lake_names()
self.lake_combo.addItems(lake_names)
default_lake = get_default_lake()
if default_lake in lake_names:
self.lake_combo.setCurrentText(default_lake)
self.lake_combo.currentTextChanged.connect(self._on_lake_changed)
lake_layout.addRow("水域选择:", self.lake_combo)
# 参考波长显示
self.lambda_0_label = QLabel()
self.lambda_0_label.setStyleSheet(
f"color: {ModernStylesheet.COLORS['accent']}; "
f"font-weight: bold;"
)
lake_layout.addRow("参考波长 λ₀:", self.lambda_0_label)
# 算法提示
self.hint_label = QLabel()
self.hint_label.setWordWrap(True)
self.hint_label.setStyleSheet(
f"color: {ModernStylesheet.COLORS['text_secondary']}; "
"font-size: 12px;"
)
lake_layout.addRow("算法提示:", self.hint_label)
lake_group.setLayout(lake_layout)
layout.addWidget(lake_group)
# 输出路径
self.output_path = FileSelectWidget(
"输出文件:",
"CSV Files (*.csv);;All Files (*.*)",
mode="save"
)
self.output_path.line_edit.setPlaceholderText(
"自动生成到 8_QAA_Inversion或手动指定..."
)
self.output_path.browse_btn.clicked.disconnect()
self.output_path.browse_btn.clicked.connect(self.browse_output_path)
layout.addWidget(self.output_path)
# 启用步骤
self.enable_checkbox = QCheckBox("启用此步骤")
self.enable_checkbox.setChecked(False)
layout.addWidget(self.enable_checkbox)
# 独立运行按钮
self.run_btn = QPushButton("执行 QAA 反演")
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_btn.clicked.connect(self._on_run_single_clicked)
layout.addWidget(self.run_btn)
layout.addStretch()
self.setLayout(layout)
self._on_lake_changed(self.lake_combo.currentText())
def _on_lake_changed(self, lake_name: str):
"""当用户切换水域时更新显示"""
cfg = get_lake_config(lake_name)
if cfg:
self.lambda_0_label.setText(
f"{cfg['lambda_0']} nm{cfg['qaa_version']}"
)
self.hint_label.setText(cfg.get('notes', ''))
else:
self.lambda_0_label.setText("")
self.hint_label.setText("")
def _get_default_work_dir(self) -> str:
"""获取 work_dir优先用 panel 自身缓存的,否则尝试从主窗口取"""
if hasattr(self, 'work_dir') and self.work_dir:
return str(self.work_dir)
mw = self.window()
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
return str(mw.work_dir)
return ""
def browse_output_path(self):
"""浏览输出文件路径"""
current = self.output_path.get_path().strip()
if current:
initial_dir = os.path.dirname(current)
initial_file = os.path.basename(current)
else:
initial_dir = ""
initial_file = ""
if not initial_dir or not os.path.isdir(initial_dir):
work_dir = self._get_default_work_dir()
initial_dir = resolve_subdir(work_dir, 'qaa_inversion') if work_dir else ""
if initial_dir and not os.path.isdir(initial_dir):
os.makedirs(initial_dir, exist_ok=True)
file_path, _ = QFileDialog.getSaveFileName(
self, "保存输出文件",
os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
"CSV Files (*.csv);;All Files (*.*)"
)
if file_path:
self.output_path.set_path(file_path)
def get_config(self) -> dict:
"""获取面板配置"""
config = {
'lake_name': self.lake_combo.currentText(),
'lambda_0': get_lambda_0(self.lake_combo.currentText()),
'spectrum_csv_path': self.spectrum_csv_file.get_path(),
}
output_path = self.output_path.get_path()
if output_path:
config['output_path'] = output_path
return config
def set_config(self, config: dict):
"""设置面板配置"""
if 'lake_name' in config:
lake_name = config['lake_name']
idx = self.lake_combo.findText(lake_name)
if idx >= 0:
self.lake_combo.setCurrentIndex(idx)
if 'spectrum_csv_path' in config:
self.spectrum_csv_file.set_path(config['spectrum_csv_path'])
if 'output_path' in config:
self.output_path.set_path(config['output_path'])
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充训练数据和输出路径"""
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
else:
self.work_dir = None
main_window = self.window()
if main_window and hasattr(main_window, 'step5_panel'):
step5_output = main_window.step5_panel.output_file.get_path()
if step5_output:
if not os.path.isabs(step5_output):
step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
self.spectrum_csv_file.set_path(step5_output)
if self.work_dir:
qaa_dir = resolve_subdir(self.work_dir, 'qaa_inversion')
os.makedirs(qaa_dir, exist_ok=True)
output_path = os.path.join(qaa_dir, "a_lambda_results.csv").replace('\\', '/')
self.output_path.set_path(output_path)
else:
self.output_path.set_path("")
def _on_run_single_clicked(self):
"""通过 EventBus 发布单步执行请求(解耦面板与 PipelineExecutor"""
from src.gui.core.event_bus import global_event_bus
spectrum_path = self.spectrum_csv_file.get_path()
if not spectrum_path:
QMessageBox.warning(self, "输入错误", "请选择光谱 CSV 文件!")
return
config = {'step8_qaa': self.get_config()}
global_event_bus.publish('RequestRunSingleStep', {
'step_name': 'step8_qaa',
'config': config,
})
def run_step(self):
"""独立运行 QAA 反演(旧版 parent 链上溯方式,保留兼容)。"""
spectrum_path = self.spectrum_csv_file.get_path()
if not spectrum_path:
QMessageBox.warning(self, "输入错误", "请选择光谱 CSV 文件!")
return
main_window = self.window()
if hasattr(main_window, 'run_single_step'):
config = {'step8_qaa': self.get_config()}
main_window.run_single_step('step8_qaa', config)
else:
self._run_qaa_direct()
def _run_qaa_direct(self):
"""直接执行 QAA 反演(不依赖主窗口流水线)"""
spectrum_path = self.spectrum_csv_file.get_path()
output_path = self.output_path.get_path()
lake_name = self.lake_combo.currentText()
lambda_0 = get_lambda_0(lake_name)
if not output_path:
work_dir = self._get_default_work_dir()
qaa_dir = resolve_subdir(work_dir, 'qaa_inversion') if work_dir else ""
if qaa_dir and not os.path.isdir(qaa_dir):
os.makedirs(qaa_dir, exist_ok=True)
output_path = os.path.join(qaa_dir, "a_lambda_results.csv").replace('\\', '/')
try:
import numpy as np
import pandas as pd
df = pd.read_csv(spectrum_path, encoding="utf-8-sig")
col_names = df.columns.tolist()
wavelength_col_idx = None
for i, col in enumerate(col_names):
try:
float(col)
wavelength_col_idx = i
break
except (ValueError, TypeError):
pass
if wavelength_col_idx is None:
QMessageBox.warning(
self, "解析错误",
"无法从 CSV 列名中识别波长信息请确保列名包含数值型波长nm"
)
return
wavelengths = np.array(
[float(c) for c in col_names[wavelength_col_idx:]], dtype=np.float64
)
data_matrix = df.iloc[:, wavelength_col_idx:].values.astype(np.float64)
if data_matrix.ndim == 1:
data_matrix = data_matrix[np.newaxis, :]
solver = QAABaselineSolver()
raw_result = solver.run_inversion(wavelengths, data_matrix, lambda_0)
# run_inversion 返回:单样本 → dict多样本 → list[dict]
if isinstance(raw_result, list):
sample_results = raw_result
aw_0 = raw_result[0].get('aw_0', 0)
bbw_0 = raw_result[0].get('bbw_0', 0)
else:
sample_results = [raw_result]
aw_0 = raw_result.get('aw_0', 0)
bbw_0 = raw_result.get('bbw_0', 0)
rows_out = []
for i, sample_result in enumerate(sample_results):
wl_arr = wavelengths
a_arr = sample_result['a_lambda']
bb_arr = sample_result['bb_lambda']
for j, wl in enumerate(wl_arr):
rows_out.append({
'sample_id': f"sample_{i}",
'Wavelength': wl,
'a_lambda': a_arr[j],
'bb_lambda': bb_arr[j],
})
result_df = pd.DataFrame(rows_out)
os.makedirs(os.path.dirname(output_path) or '.', exist_ok=True)
result_df.to_csv(output_path, index=False, float_format='%.8f')
QMessageBox.information(
self, "执行成功",
f"QAA 反演完成!\n"
f"水域: {lake_name}\n"
f"参考波长 λ₀: {lambda_0} nm\n"
f"λ₀ 处 aw: {aw_0:.6f} m⁻¹\n"
f"λ₀ 处 bbw: {bbw_0:.6f} m⁻¹\n"
f"结果已保存到:\n{output_path}"
)
except Exception as e:
QMessageBox.critical(self, "执行错误", f"QAA 反演失败:\n{str(e)}")
def get_training_params(self) -> dict:
"""获取反演参数"""
return {
'pipeline_type': 'qaa_non_empirical',
'lake_name': self.lake_combo.currentText(),
'lambda_0': get_lambda_0(self.lake_combo.currentText()),
}

View File

@ -307,62 +307,30 @@ class Step9MlPredictPanel(QWidget):
return result
def update_from_config(self, work_dir=None, pipeline=None):
"""从全局配置自动填充采样光谱和模型目录
if work_dir: self.work_dir = work_dir
Args:
work_dir: 工作目录路径
pipeline: Pipeline 实例(未使用,保留接口兼容性)
"""
try:
import traceback
main_window = self.window()
factory = getattr(main_window, '_panel_factory', None) if main_window else None
if not factory: return
if work_dir:
self.work_dir = work_dir
elif hasattr(self, 'work_dir') and self.work_dir:
pass
else:
self.work_dir = None
# 1. 拿第 4 步的采样光谱
step4_panel = factory.get_panel('step4_sampling')
if step4_panel and hasattr(step4_panel, 'output_file'):
path = step4_panel.output_file.get_path()
if path: self.sampling_csv_file.set_path(path)
main_window = self.window()
# 2. 拿第 8 步的模型目录
step8_panel = factory.get_panel('step8_ml_train')
if step8_panel and hasattr(step8_panel, 'output_path'):
path = step8_panel.output_path.get_path()
if path: self.models_dir_file.set_path(path)
# 1. 尝试从 Step4采样点布设读取全湖采样点 CSV 路径
if main_window and hasattr(main_window, 'step4_sampling_panel'):
step4_widget = getattr(main_window.step4_sampling_panel, 'output_file', None)
step4_output_path = ""
if hasattr(step4_widget, 'get_path'):
step4_output_path = step4_widget.get_path() or ""
elif hasattr(step4_widget, 'text'):
step4_output_path = step4_widget.text() or ""
if step4_output_path:
if not os.path.isabs(step4_output_path):
step4_output_path = os.path.join(self.work_dir or '', step4_output_path).replace('\\', '/')
existing = self.sampling_csv_file.get_path()
if not existing or not existing.strip():
self.sampling_csv_file.set_path(step4_output_path)
# 2. 尝试从 Step8监督建模读取模型目录修复张冠李戴原代码 main_window.step9_panel 不存在)
step8_models_dir = get_step_output_path(
main_window, 'models_dir', work_dir=self.work_dir,
widget_attr='output_dir', fallback_key='step8_ml_train',
)
if step8_models_dir:
existing_models = self.models_dir_file.get_path()
if not existing_models or not existing_models.strip():
self.models_dir_file.set_path(step8_models_dir)
# 3. 自动填充输出路径(机器学习预测目录,归属 step9 → 9_ML_Prediction
# 注9_ML_Prediction 是 prediction_dir 的子目录,用本地约定
if self.work_dir:
output_dir = resolve_subdir(self.work_dir, 'ml_prediction')
os.makedirs(output_dir, exist_ok=True)
existing_out = self.output_file.get_path()
if not existing_out or not existing_out.strip():
self.output_file.set_path(output_dir)
except Exception as e:
import traceback
print(f"{self.__class__.__name__}】自动填充失败,跳过: {e}")
traceback.print_exc()
# 3. 生成第 9 步的输出目录
if hasattr(self, 'work_dir') and self.work_dir:
import os
out_dir = os.path.join(self.work_dir, "9_ML_Prediction").replace('\\', '/')
os.makedirs(out_dir, exist_ok=True)
self.output_file.set_path(out_dir)
def _get_default_work_dir(self):
"""获取 work_dir优先用 panel 自身缓存的,否则尝试从主窗口取"""

View File

@ -458,52 +458,65 @@ class WaterQualityGUI(QMainWindow):
# ================================================================
def _on_step_list_changed(self, index):
"""左侧导航 → 右侧 Tab 单向路由Tab 头部已隐藏,无反向同步)。"""
if index < 0:
return
from PyQt5.QtCore import Qt
if index < 0: return
item = self._step_list.item(index)
if not item:
return
if not item: return
item_data = item.data(Qt.UserRole)
if item_data == "stage_header" or item_data is None:
return
from src.gui.core.panel_registry import get_tab_index
if item_data in (None, "stage_header"): return # 跳过阶段标题
from src.gui.core.panel_registry import get_tab_index, PANEL_REGISTRY
tab_index = get_tab_index(item_data)
if tab_index < 0:
return
if tab_index < 0: return
try:
# 触发懒加载再切 Tab避免 removeTab/insertTab 与导航事件重叠
# 1. 触发懒加载生成面板
self._panel_factory.get_panel(item_data)
self._tab_widget.setCurrentIndex(tab_index)
except Exception as e:
import traceback
traceback.print_exc()
from PyQt5.QtWidgets import QMessageBox
QMessageBox.critical(self, "面板加载失败",
f"加载页面时发生严重错误:\n{e}\n\n详见终端日志。")
# 🚨 核心防卡死补丁:如果目标 Tab 被后台任务异常永久锁定,强制撬开!
if not self._tab_widget.isTabEnabled(tab_index):
self._log_manager.info(f"检测到 {item_data} 处于异常锁定状态,已执行强制解锁。")
self._tab_widget.setTabEnabled(tab_index, True)
# ====== 终极状态回滚机制 ======
self._step_list.blockSignals(True)
# 【新增修复】:在跳之前,再核实一遍要去的 tab_index 和 item_data 的 step_id 是否吻合!
# 如果因为删除了死文件导致索引错位,这里强行用真实 step_id 再找一遍!
try:
current_tab_idx = self._tab_widget.currentIndex()
from src.gui.core.panel_registry import PANEL_REGISTRY
if 0 <= current_tab_idx < len(PANEL_REGISTRY):
correct_step_id = PANEL_REGISTRY[current_tab_idx]['step_id']
for i in range(self._step_list.count()):
item_node = self._step_list.item(i)
if item_node and item_node.data(Qt.UserRole) == correct_step_id:
self._step_list.setCurrentRow(i)
self._panel_factory.get_panel(item_data)
# 遍历右侧所有已加载的 Tab找到属于当前 step_id 的那个正确的 Tab 索引
for i in range(self._tab_widget.count()):
scroll_area = self._tab_widget.widget(i)
if scroll_area and hasattr(scroll_area, 'widget'):
real_panel = scroll_area.widget()
# 如果这个 panel 就是我们要找的 panel强制更新 tab_index
if real_panel == self._panel_factory.get_panel(item_data):
tab_index = i
break
except Exception:
pass
finally:
except Exception as e:
self._log_manager.error(f"页面实例化失败: {str(e)}")
return
# 2. 强制使用注册表的固定索引进行跳转
self._tab_widget.setCurrentIndex(tab_index)
# 【新增修复】:每次切页时,强制重播所有面板的输入值!
# 原理:打破 preload_window 造成的时序差,确保目标页面能拿到源页面最新填写的值
if hasattr(self, '_panel_factory'):
self._panel_factory._replay_live_panel_inputs()
# 3. 防撕裂回弹机制:如果由于某种原因没跳过去,把左边的蓝条强行拽回当前真实页面
if self._tab_widget.currentIndex() != tab_index:
self._step_list.blockSignals(True)
current_step_id = PANEL_REGISTRY[self._tab_widget.currentIndex()]['step_id']
for i in range(self._step_list.count()):
list_item = self._step_list.item(i)
if list_item and list_item.data(Qt.UserRole) == current_step_id:
self._step_list.setCurrentRow(i)
break
self._step_list.blockSignals(False)
return
# 动态更新上一步/下一步按钮可用状态
self._prev_btn.setEnabled(self._find_prev_step_row(index) is not None)
self._next_btn.setEnabled(self._find_next_step_row(index) is not None)
except Exception as e:
self._log_manager.error(f"页面跳转失败: {str(e)}")
def _find_prev_step_row(self, current_row):
"""从 current_row 向上遍历,跳过 stage_header 和空分隔符,返回上一个有效 step 的行号。"""