测试修改
This commit is contained in:
@ -32,13 +32,22 @@ class Step9MlPredictHandler(BaseStepHandler):
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models_dir = config.get('models_dir') or str(context.models_dir)
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# 【硬编码路径清除】优先读取前端 config 中的 output_path / output_dir，
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# 绝不允许私自拼接 11_12_13_predictions 覆盖用户在前端填写的路径。
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# 前端 step9_ml_predict_panel.get_config() 用的是 'output_path' 这个 key。
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output_dir = (
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config.get('output_path')
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or config.get('output_dir')
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or str(context.prediction_dir / "9_ML_Prediction")
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)
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try:
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result = PredictionStep.predict_water_quality(
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sampling_csv_path=sampling_csv_path,
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models_dir=models_dir,
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metric=config.get('metric', 'test_r2'),
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prediction_column=config.get('prediction_column', 'prediction'),
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output_dir=str(context.prediction_dir / "9_ML_Prediction"),
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output_dir=output_dir,
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_report_generator=context.report_generator,
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_external_model=config.get('_external_model'),
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_external_model_path=config.get('_external_model_path'),
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@ -1,14 +1,24 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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依赖订阅混入模块
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依赖订阅混入模块（架构解耦版）
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新规则：dependencies 字典的键名 = 下游目标控件的真实属性名，
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第三元素（source_attr）= 上游源控件的真实属性名。
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提供 subscribe_panel_to_dependencies() 函数，让步骤面板根据
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PANEL_REGISTRY 中声明的 dependencies 自动向 global_event_bus
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订阅 OutputUpdated 事件。当上游步骤产出落地时，面板自动将路径
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填入对应的 FileSelectWidget，无需主窗口手工传导。
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内含：
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- 自动识别下游 widget（按 dict 键名查找）
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- 非空保护：仅在目标框为空时填充，避免覆盖用户已选路径
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- 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
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"""
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import os
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from src.gui.core.event_bus import global_event_bus
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@ -19,18 +29,21 @@ def subscribe_panel_to_dependencies(panel, step_id, dependencies):
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匹配时，自动将路径填入面板对应的 FileSelectWidget。
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Args:
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panel: 步骤面板实例（QWidget 子类）
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panel: 步骤面板实例（QWidget 子类），即下游目标面板
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step_id: 当前面板的 step_id（仅用于日志，非匹配键）
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dependencies: dict, {input_field: (dep_step, output_type, panel_attr)}
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dependencies: dict, {target_field: (dep_step, output_type, source_attr)}
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target_field 必须等于 panel 上某个控件的属性名
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source_attr 仅作回放端使用（本函数不直接依赖）
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"""
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if not dependencies:
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return
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for _input_field, (dep_step, output_type, panel_attr) in dependencies.items():
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_make_subscription(panel, dep_step, output_type, panel_attr)
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# 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
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for _input_field, (dep_step, output_type, source_panel_attr) in dependencies.items():
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_make_subscription(panel, dep_step, output_type, _input_field)
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def _make_subscription(panel, dep_step, output_type, panel_attr):
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def _make_subscription(panel, dep_step, output_type, target_widget_name):
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"""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。"""
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def callback(data):
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@ -39,7 +52,7 @@ def _make_subscription(panel, dep_step, output_type, panel_attr):
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if data.get('output_type') != output_type:
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return
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widget = getattr(panel, panel_attr, None)
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widget = getattr(panel, target_widget_name, None)
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if widget is None:
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return
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@ -56,6 +69,10 @@ def _make_subscription(panel, dep_step, output_type, panel_attr):
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if not path:
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return
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# 智能转换：如果要的是目录，但来的是文件，自动截取父目录
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if 'dir' in target_widget_name.lower() and os.path.isfile(path):
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path = os.path.dirname(path)
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if hasattr(widget, 'set_path'):
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widget.set_path(path)
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elif hasattr(widget, 'setText'):
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@ -169,11 +169,12 @@ class PanelFactory:
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if placeholder is not None and self._tab_widget is not None:
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tab_title = self._tab_widget.tabText(tab_index)
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tab_icon = self._tab_widget.tabIcon(tab_index)
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current_active = self._tab_widget.currentIndex() # 记住当前正在看的 Tab
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self._tab_widget.blockSignals(True)
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try:
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self._tab_widget.removeTab(tab_index)
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self._tab_widget.insertTab(tab_index, scroll, tab_icon, tab_title)
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self._tab_widget.setCurrentIndex(tab_index)
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self._tab_widget.setCurrentIndex(current_active) # 恢复原来的 Tab，严禁后台预加载引发跳页！
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finally:
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self._tab_widget.blockSignals(False)
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@ -226,33 +227,40 @@ class PanelFactory:
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self._replay_live_panel_inputs()
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def _replay_live_panel_inputs(self):
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"""遍历 PANEL_REGISTRY 依赖声明，从已加载面板实时读取属性值。
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"""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。
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若源面板已实例化，读取其 widget 的当前值并发布为 OutputUpdated，
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确保懒加载面板能收到全局输入（如 Step1.img_file → reference_img）。
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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，
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不再混用语义。回放端仅依赖 source_attr 在 SOURCE 面板上能命中 widget。
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"""
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from src.gui.core.event_bus import global_event_bus
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for entry in self._registry:
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deps = entry.get('dependencies')
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if not deps:
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continue
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for _input_field, (dep_step, output_type, panel_attr) in deps.items():
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if not deps: continue
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# 第三个元素 source_attr 现在明确代表上游控件的真实名字
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for target_field, (dep_step, output_type, source_attr) in deps.items():
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src_panel = self._panels.get(dep_step)
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if src_panel is None:
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continue
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widget = getattr(src_panel, panel_attr, None)
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if widget is None:
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continue
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path = ''
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if src_panel is None: continue
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widget = getattr(src_panel, source_attr, None)
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if widget is None: continue
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path = ""
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if hasattr(widget, 'get_path'):
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path = widget.get_path().strip()
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elif hasattr(widget, 'text'):
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path = widget.text().strip()
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if not path:
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continue
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if not path: continue
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# 核心修复：强制转为绝对路径，防止跨目录传递时路径丢失
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import os
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absolute_path = os.path.abspath(path).replace('\\', '/')
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global_event_bus.publish('OutputUpdated', {
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'step_id': dep_step,
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'output_type': output_type,
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'path': path,
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'path': absolute_path,
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})
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def _get_current_work_dir(self):
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@ -48,14 +48,13 @@ PANEL_REGISTRY = [
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'icon': '2.png',
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'stage': '阶段一：影像预处理',
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'display_name': '2. 耀斑区域识别',
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# 对账修复（2026-06-18）：
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# - img_path: 来源 step1.img_file、目标 step2.img_file ✓ 两端均存在
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# - water_mask_path: 原 panel_attr='water_mask_file' 在 step1 panel 不存在（断链）
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# → 改为 step1 真实控件名 'mask_file'（step1 默认现有掩膜输入模式）
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# → NDWI 模式由 step2.update_from_config 自补足，不依赖 EventBus 链路
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名；
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# 第三元素 source_attr = 上游源控件真实属性名（panel_factory 回放端使用）
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'dependencies': {
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'img_path': ('step1', 'reference_img', 'img_file'),
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'water_mask_path': ('step1', 'water_mask', 'mask_file'),
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# 目标框: self.img_file ← 上游 step1.img_file
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'img_file': ('step1', 'reference_img', 'img_file'),
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# 目标框: self.water_mask_file ← 上游 step1.mask_file
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'water_mask_file': ('step1', 'water_mask', 'mask_file'),
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},
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'constructor_kwargs': None,
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},
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@ -66,14 +65,12 @@ PANEL_REGISTRY = [
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'icon': '3.png',
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'stage': '阶段一：影像预处理',
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'display_name': '3. 耀斑去除与修复',
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# 对账修复（2026-06-18）：
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# - img_path: 来源 step1.img_file、目标 step3.img_file ✓ 两端均存在
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# - water_mask: 原 panel_attr='water_mask_file' 在 step1 panel 不存在（断链）
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# → 改为 step1 真实控件名 'mask_file'
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# → NDWI 模式由 step3.update_from_config 自补足
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名
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'dependencies': {
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'img_path': ('step1', 'reference_img', 'img_file'),
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'water_mask': ('step1', 'water_mask', 'mask_file'),
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# 目标框: self.img_file ← 上游 step1.img_file
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'img_file': ('step1', 'reference_img', 'img_file'),
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# 目标框: self.water_mask_file ← 上游 step1.mask_file
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'water_mask_file': ('step1', 'water_mask', 'mask_file'),
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},
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'constructor_kwargs': None,
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},
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@ -88,14 +85,13 @@ PANEL_REGISTRY = [
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'icon': '4.png',
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'stage': '阶段二：样本数据准备',
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'display_name': '4. 采样点布设',
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# 对账修复（2026-06-18）：
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# - deglint_img_path: 原 panel_attr='deglint_img_file' 在 step3 panel 不存在（断链）
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# → step3 输出 widget 真实名为 'output_file'（deglint_image.bsq）
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# - water_mask_path: 原 'water_mask_file' 在 step1 panel 不存在
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# → 改为 step1 真实控件名 'mask_file'
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名；
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# 第三元素 source_attr = 上游源控件真实属性名（panel_factory 回放端使用）
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'dependencies': {
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'deglint_img_path': ('step3', 'deglint_image', 'output_file'),
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'water_mask_path': ('step1', 'water_mask', 'mask_file'),
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# 目标框: self.deglint_img_file ← 上游 step3.output_file
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'deglint_img_file': ('step3', 'deglint_image', 'output_file'),
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# 目标框: self.water_mask_file ← 上游 step1.mask_file
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'water_mask_file': ('step1', 'water_mask', 'mask_file'),
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},
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'constructor_kwargs': None,
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},
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@ -117,18 +113,16 @@ PANEL_REGISTRY = [
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'icon': '6.png',
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'stage': '阶段二：样本数据准备',
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'display_name': '6. 光谱特征提取',
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# 对账修复（2026-06-18）：
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# - deglint_img_path: 原 'deglint_img_file' 在 step3 panel 不存在（断链）
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# → 改为 step3 输出 widget 'output_file'
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# - csv_path: 原 'csv_file' ✓ step5 panel 有 self.csv_file，无修改
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# - boundary_mask_path: 原 'water_mask_file' 在 step1 panel 不存在
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# → 改为 step1 真实控件名 'mask_file'
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# - glint_mask_path: 原 'glint_mask_file' ✓ step2 panel 有，无修改
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名
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'dependencies': {
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'deglint_img_path': ('step3', 'deglint_image', 'output_file'),
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'csv_path': ('step5_clean', 'processed_data', 'csv_file'),
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'boundary_mask_path': ('step1', 'water_mask', 'mask_file'),
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'glint_mask_path': ('step2', 'glint_mask', 'glint_mask_file'),
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# 目标框: self.deglint_img_file ← 上游 step3.output_file
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'deglint_img_file': ('step3', 'deglint_image', 'output_file'),
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# 目标框: self.csv_file ← 上游 step5_clean.csv_file
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'csv_file': ('step5_clean', 'processed_data', 'csv_file'),
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# 目标框: self.water_mask_file ← 上游 step1.mask_file
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'water_mask_file': ('step1', 'water_mask', 'mask_file'),
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# 目标框: self.glint_mask_file ← 上游 step2.output_file
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'glint_mask_file': ('step2', 'glint_mask', 'output_file'),
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},
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'constructor_kwargs': None,
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},
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@ -139,18 +133,11 @@ PANEL_REGISTRY = [
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'icon': '7.png',
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'stage': '阶段二：样本数据准备',
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'display_name': '7. 水质指数计算',
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# 对账修复（2026-06-18）：
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# - training_csv_path:
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# 原 ('step6_feature', 'training_spectra', 'training_data_widget')
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# output_type='training_spectra' 仅作为 EventBus 事件标签，不匹配 step6 输出
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# panel_attr='training_data_widget' 已是 step7 view 真实控件 ✓
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# 改 output_type='output_file'（step6 输出 file widget 名为 output_file）
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# ⚠️ 用户原文要求 panel_attr='csv_file'，但 step7 无 csv_file widget
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# （只有 training_data_widget 与 formula_csv_widget），
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# 实际改用 step7 真实控件 'training_data_widget'，
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# source panel_attr 取 step6 的 'output_file'（双源对账一致）
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名；
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# 第三元素 source_attr = 上游源控件真实属性名
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'dependencies': {
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'training_csv_path': ('step6_feature', 'output_file', 'training_data_widget'),
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# 目标框: self.training_data_widget ← 上游 step6_feature.output_file
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'training_data_widget': ('step6_feature', 'output_file', 'output_file'),
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},
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'constructor_kwargs': None,
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},
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@ -165,13 +152,9 @@ PANEL_REGISTRY = [
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'icon': '8.png',
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'stage': '阶段三：模型构建与训练',
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'display_name': '8. 机器学习建模',
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# 对账修复（2026-06-18）：
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# - training_csv_file:
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# 原 ('step7_index', 'training_spectra_indices', 'training_csv_file')
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# source panel_attr='training_csv_file' 在 step7 view 不存在（断链）
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# → step7 view 输出（指数计算后 CSV）真实控件为 'training_data_widget'
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# target panel_attr='training_csv_file' ✓ step8 panel 有 self.training_csv_file
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名
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'dependencies': {
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# 目标框: self.training_csv_file ← 上游 step7_index.training_data_widget
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'training_csv_file': ('step7_index', 'training_spectra_indices', 'training_data_widget'),
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},
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'constructor_kwargs': None,
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@ -187,14 +170,11 @@ PANEL_REGISTRY = [
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'icon': '10.png',
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'stage': '阶段四：预测与成果输出',
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'display_name': '9. 机器学习预测',
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# 对账修复（2026-06-18）：
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# - models_dir:
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# 原 ('step8_ml_train', 'Supervised_Model_Training', 'models_dir_file')
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# source panel_attr='models_dir_file' 在 step8 panel 不存在（断链）
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# → step8 模型输出真实控件为 'output_path'
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# target panel_attr='models_dir_file' ✓ step9 panel 有 self.models_dir_file
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# 架构解耦（2026-06-22）：dict 键名 = 下游目标控件真实属性名；
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# 第三元素 source_attr = 上游源控件真实属性名
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'dependencies': {
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'models_dir': ('step8_ml_train', 'Supervised_Model_Training', 'output_path'),
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# 目标框: self.models_dir_file ← 上游 step8_ml_train.output_path
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'models_dir_file': ('step8_ml_train', 'Supervised_Model_Training', 'output_path'),
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},
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'constructor_kwargs': None,
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},
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@ -205,13 +185,12 @@ PANEL_REGISTRY = [
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'icon': '10.png',
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'stage': '阶段四：预测与成果输出',
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'display_name': '10. 水色指数反演',
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# 对账修复（2026-06-18）：
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# - bsq_file:
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||||
# 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（2026-06-22）：dict 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（2026-06-22）：dict 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,
|
||||
},
|
||||
|
||||
@ -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
|
||||
# ═══════════════════════════════════════════════════════════
|
||||
|
||||
@ -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():
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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 = {
|
||||
|
||||
@ -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 .shp（geopandas 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.shp，geopandas.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 GeoTIFF（GeoTIFF 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")
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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")
|
||||
@ -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={'开' if self.enable_ai else '关'}，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 browse：work_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")
|
||||
@ -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.shp，geopandas.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 GeoTIFF（GeoTIFF 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")
|
||||
@ -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' 列")
|
||||
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)
|
||||
@ -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("")
|
||||
|
||||
|
||||
@ -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)
|
||||
@ -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8：QAA 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8：QAA 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()),
|
||||
}
|
||||
@ -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"""
|
||||
|
||||
@ -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:
|
||||
# 先触发懒加载再切 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。"""
|
||||
|
||||
@ -35,11 +35,12 @@ import pandas as pd
|
||||
|
||||
|
||||
class _SimpleProgress:
|
||||
"""无依赖进度条（控制台单行刷新）。"""
|
||||
"""无依赖进度条（控制台单行刷新，支持 Qt 回调上递）。"""
|
||||
|
||||
def __init__(self, total: int, desc: str = ""):
|
||||
def __init__(self, total: int, desc: str = "", on_step=None):
|
||||
self.total = max(1, int(total))
|
||||
self.desc = desc
|
||||
self.on_step = on_step
|
||||
self.n = 0
|
||||
self._render()
|
||||
|
||||
@ -47,6 +48,10 @@ class _SimpleProgress:
|
||||
self.n = min(self.total, self.n + int(step))
|
||||
self._render()
|
||||
|
||||
def set_description(self, text: str):
|
||||
"""动态更新进度描述文案（用于按段切换分析对象）。"""
|
||||
self.desc = text
|
||||
|
||||
def close(self):
|
||||
# 换行，避免覆盖后续输出
|
||||
print()
|
||||
@ -58,6 +63,11 @@ class _SimpleProgress:
|
||||
bar = "█" * filled + "·" * (bar_len - filled)
|
||||
prefix = f"{self.desc} " if self.desc else ""
|
||||
print(f"\r{prefix}[{bar}] {self.n}/{self.total} ({pct}%)", end="", flush=True)
|
||||
if self.on_step:
|
||||
try:
|
||||
self.on_step(pct, self.desc)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
@dataclass
|
||||
@ -210,98 +220,17 @@ class WaterQualityReportGenerator:
|
||||
}
|
||||
|
||||
# 每个参数对应的图片顺序（统一5张图模式）
|
||||
params_list = ["Chlorophyll", "COD", "DO", "PH", "Temperature",
|
||||
"spCond", "Turbidity", "TDS", "Cl-", "NO3-N",
|
||||
"NH3-N", "BGA", "TT"]
|
||||
self.parameter_images = {
|
||||
"Chlorophyll": [
|
||||
"Chlorophyll_histogram.png",
|
||||
"Chlorophyll_spectrum_comparison.png",
|
||||
"Chlorophyll_scatter_with_confidence.png",
|
||||
"Chlorophyll_boxplot.png",
|
||||
"Chlorophyll_distribution.png"
|
||||
],
|
||||
"COD": [
|
||||
"COD_histogram.png",
|
||||
"COD_spectrum_comparison.png",
|
||||
"COD_scatter_with_confidence.png",
|
||||
"COD_boxplot.png",
|
||||
"COD_distribution.png"
|
||||
],
|
||||
"DO": [
|
||||
"DO_histogram.png",
|
||||
"DO_spectrum_comparison.png",
|
||||
"DO_scatter_with_confidence.png",
|
||||
"DO_boxplot.png",
|
||||
"DO_distribution.png"
|
||||
],
|
||||
"PH": [
|
||||
"PH_histogram.png",
|
||||
"PH_spectrum_comparison.png",
|
||||
"PH_scatter_with_confidence.png",
|
||||
"PH_boxplot.png",
|
||||
"PH_distribution.png"
|
||||
],
|
||||
"Temperature": [
|
||||
"Temperature_histogram.png",
|
||||
"Temperature_spectrum_comparison.png",
|
||||
"Temperature_scatter_with_confidence.png",
|
||||
"Temperature_boxplot.png",
|
||||
"Temperature_distribution.png"
|
||||
],
|
||||
"spCond": [
|
||||
"spCond_histogram.png",
|
||||
"spCond_spectrum_comparison.png",
|
||||
"spCond_scatter_with_confidence.png",
|
||||
"spCond_boxplot.png",
|
||||
"spCond_distribution.png"
|
||||
],
|
||||
"Turbidity": [
|
||||
"Turbidity_histogram.png",
|
||||
"Turbidity_spectrum_comparison.png",
|
||||
"Turbidity_scatter_with_confidence.png",
|
||||
"Turbidity_boxplot.png",
|
||||
"Turbidity_distribution.png"
|
||||
],
|
||||
"TDS": [
|
||||
"TDS_histogram.png",
|
||||
"TDS_spectrum_comparison.png",
|
||||
"TDS_scatter_with_confidence.png",
|
||||
"TDS_boxplot.png",
|
||||
"TDS_distribution.png"
|
||||
],
|
||||
"Cl-": [
|
||||
"Cl-histogram.png",
|
||||
"Cl-spectrum_comparison.png",
|
||||
"Cl-scatter_with_confidence.png",
|
||||
"Cl-boxplot.png",
|
||||
"Cl-distribution.png"
|
||||
],
|
||||
"NO3-N": [
|
||||
"NO3-N_histogram.png",
|
||||
"NO3-N_spectrum_comparison.png",
|
||||
"NO3-N_scatter_with_confidence.png",
|
||||
"NO3-N_boxplot.png",
|
||||
"NO3-N_distribution.png"
|
||||
],
|
||||
"NH3-N": [
|
||||
"NH3-N_histogram.png",
|
||||
"NH3-N_spectrum_comparison.png",
|
||||
"NH3-N_scatter_with_confidence.png",
|
||||
"NH3-N_boxplot.png",
|
||||
"NH3-N_distribution.png"
|
||||
],
|
||||
"BGA": [
|
||||
"BGA_histogram.png",
|
||||
"BGA_spectrum_comparison.png",
|
||||
"BGA_scatter_with_confidence.png",
|
||||
"BGA_boxplot.png",
|
||||
"BGA_distribution.png"
|
||||
],
|
||||
"TT": [
|
||||
"TT_histogram.png",
|
||||
"TT_spectrum_comparison.png",
|
||||
"TT_scatter_with_confidence.png",
|
||||
"TT_boxplot.png",
|
||||
"TT_distribution.png"
|
||||
]
|
||||
param: [
|
||||
f"{param}_histogram.png",
|
||||
f"{param}_spectrum_comparison.png",
|
||||
f"{param}_scatter_true_vs_pred.png",
|
||||
f"{param}_boxplot.png",
|
||||
f"{param}_distribution_enhanced.png"
|
||||
] for param in params_list
|
||||
}
|
||||
|
||||
def apply_ai_config(self, ai_config: ReportGenerationConfig) -> None:
|
||||
@ -397,6 +326,7 @@ class WaterQualityReportGenerator:
|
||||
|
||||
payload: Dict[str, Any] = {
|
||||
"model": self.minimax_text_model,
|
||||
"max_tokens": 4096,
|
||||
"messages": [
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": user_prompt},
|
||||
@ -447,6 +377,7 @@ class WaterQualityReportGenerator:
|
||||
|
||||
payload: Dict[str, Any] = {
|
||||
"model": self.minimax_vision_model,
|
||||
"max_tokens": 4096,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
@ -518,123 +449,90 @@ class WaterQualityReportGenerator:
|
||||
return self._ollama_chat(model, system_prompt, user_prompt, image_path)
|
||||
|
||||
def _get_prompt_for_image(self, image_type: str, param: str, figure_num: int) -> Dict[str, str]:
|
||||
"""按图片类型返回 system/user 提示词，带防幻觉约束。"""
|
||||
"""按图片类型返回 system/user 提示词，注入水质遥感专家级约束。"""
|
||||
system = (
|
||||
"你是一位水质遥感与机器学习建模专家。\n"
|
||||
"研究背景：我们利用高光谱影像数据，结合机器学习算法对研究区的水质参数进行了空间反演，并生成了以下图表。"
|
||||
"现需要撰写自动化分析报告，请严格按照“图表类型→分析重点”的对应关系进行描述。\n\n"
|
||||
"分析要求：\n"
|
||||
"1. 请严格基于图片中可见信息进行分析，禁止编造不存在的数值、区域名称、采样时间或结论。\n"
|
||||
"2. 如果图片无法支撑某项判断，必须明确写“根据本图无法判断”。\n"
|
||||
"3. 不允许引用图片之外的背景知识来补全细节。"
|
||||
"你是一位资深的水环境遥感与水生态学专家。现需为一份高光谱水质参数反演报告撰写专业分析。\n"
|
||||
"【绝对禁忌】：严禁写“看图说话”式的废话（如“曲线先升后降”、“柱子集中在中间”）。\n"
|
||||
"【核心规范】：\n"
|
||||
"1. 必须结合【水色光学机理】和【水环境地学意义】进行解释。\n"
|
||||
"2. 提及波长时，必须解释其对应的物理/生化意义（如叶绿素红光吸收谷、悬浮物散射峰、水体吸收特性等）。\n"
|
||||
"3. 分析浓度数值时，必须结合自然水体的常规背景值或富营养化状态进行定性评价（如“处于清洁水平”或“存在水华风险”）。\n"
|
||||
"4. 严格基于图中可见的规律，不编造图中没有的具体坐标或日期。"
|
||||
)
|
||||
|
||||
# 为每种图表类型单独定义：分析要点 + 结论聚焦
|
||||
type_specs = {
|
||||
"histogram": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 分布形态：是左偏、右偏还是对称？是否存在多峰？\n"
|
||||
"- 集中范围：数据主要集中在哪个区间？（参照横轴和纵轴柱高）\n"
|
||||
"- 离群值：是否有明显孤立于主体分布的小柱，位于何处？\n"
|
||||
"- 若图中包含拟合曲线，描述其形状（正态、指数等）。"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：该参数的分布形态（如左偏/右偏/对称）、主要集中区间、是否存在极端离群值。"
|
||||
"用一句话概括数据分布的核心特征，不推测成因。"
|
||||
f"- 结合自然水体中 {param} 的常规阈值，评估该水域当前的整体水平（清洁、轻度污染或富营养化）。\n"
|
||||
"- 从生态学角度解释这种数值分布形态（如多峰分布可能暗示存在多个不同性质的污染源或水团交汇）。\n"
|
||||
"- 关注极端离群值，指出其可能代表的局部异常环境事件。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：该水质参数的整体健康水平评估及主要生态风险提示。",
|
||||
},
|
||||
"spectrum_comparison": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 多条曲线的整体趋势是否一致？\n"
|
||||
"- 在哪些波段（参照横轴波长位置）出现明显分离？\n"
|
||||
"- 是否存在系统性的整体偏移（一条曲线全程高于另一条）？\n"
|
||||
"- 图中是否有阴影或误差带表示置信区间？若有，描述其范围。"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：各光谱曲线的整体一致性、关键差异波段、是否存在系统性偏移。"
|
||||
"用一句话概括光谱对比的主要特征，不推测物理原因。"
|
||||
f"- 结合 {param} 的固有光学特性，重点分析400-900nm区间内的特征波段响应（如吸收谷、反射峰、双峰效应等）。\n"
|
||||
"- 对比不同浓度组别的光谱差异，说明浓度变化是如何改变水体对光吸收和后向散射规律的。\n"
|
||||
"- 指出对该参数反演最具区分度的关键波段区间，验证模型的物理可解释性。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：浓度梯度引起的光谱响应规律及其对应的光学机制验证。",
|
||||
},
|
||||
"scatter_with_confidence": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 点云整体是否沿1:1线（对角线）分布？\n"
|
||||
"- 点云在低值区/高值区是否存在系统性偏离（如整体偏上/偏下）？\n"
|
||||
"- 置信带（若存在）覆盖了多少点？是否所有点都在置信带内？\n"
|
||||
"- 是否有明显离群点（远离主体点云）？"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：模型预测精度（点云与1:1线贴合程度）、偏差方向、置信带覆盖情况。"
|
||||
"用一句话评价模型性能，不推测误差来源。"
|
||||
"- 评估机器学习反演模型在该参数上的鲁棒性。点云对1:1线的贴合度反映了反演精度。\n"
|
||||
"- 重点分析在极低值区或极高值区是否存在系统性高估/低估（这是水色遥感的常见难点，如高浓度下的光谱饱和效应）。\n"
|
||||
"- 结合置信带宽度，说明模型在不同浓度区间的预测不确定性。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：反演模型的整体精度表现、局限性及可靠的浓度预测区间。",
|
||||
},
|
||||
"boxplot": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 中位数（箱体中间线）的位置。\n"
|
||||
"- 四分位间距（箱体高度）反映的离散程度。\n"
|
||||
"- 须（whisker）的长度，是否超出1.5倍IQR的离群点（用圆点/星号标示）。\n"
|
||||
"- 若多个箱线图并排，比较各组的中心趋势和离散度。"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：各组的中心趋势（中位数）、离散程度（四分位距）、是否存在离群点。"
|
||||
"用一句话概括数据分布的统计特征，若有多组则简述对比。"
|
||||
"- 结合中位数和四分位距，分析不同类别（或区域）间水质差异的显著性。\n"
|
||||
"- 解释离散程度大（箱体长）可能代表的强烈时空异质性。\n"
|
||||
"- 指出箱线图上下的离群点，探讨其作为局部水质突变信号的价值。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：核心对比趋势及数据整体的时空变异特征。",
|
||||
},
|
||||
"distribution": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 高值区域：位于图中的哪个方位（如东北部、中部偏西、东南沿岸等）？呈现何种形状（斑块状、条带状、片状）？\n"
|
||||
"- 低值区域：位置及形态。\n"
|
||||
"- 梯度变化：是否存在明显的从某方位向另一方位递减或递增的趋势？\n"
|
||||
"- 聚集特征：高值区是否成片聚集，还是零星散布？\n"
|
||||
"注意：仅使用方位描述位置（如上、下、左、右、中心、边缘、沿岸等），禁止使用具体经纬度坐标或地名。"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：高值区与低值区的空间方位、聚集形态、主要梯度方向。"
|
||||
"用一句话概括空间分布格局，不推测污染源或成因。"
|
||||
f"- 分析 {param} 高值区与低值区的空间异质性特征。\n"
|
||||
"- 推断污染/物质来源类型：高值区呈斑块状/点状（通常提示点源排放或局部水华），还是呈沿岸带状/梯度扩散（通常提示面源径流或水动力扩散）。\n"
|
||||
"- 结合常见水动力学特征，简述物质可能的输移趋势。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：水质参数的空间格局特征及其指示的宏观环境动力学过程。",
|
||||
},
|
||||
"correlation_heatmap": {
|
||||
"analysis": (
|
||||
"分析要点：\n"
|
||||
"- 各变量对之间的相关性强度：颜色深浅对应的相关系数大小（参照图例）。\n"
|
||||
"- 正相关与负相关：红色/蓝色分别代表正负（根据图例），描述主要的高正相关对和高负相关对。\n"
|
||||
"- 若图中包含数值标注，可提及范围（如“大多数相关系数介于0.6~0.8”），但不得编造具体数字。\n"
|
||||
"- 若单元格颜色过于接近难以区分，则写“根据本图无法判断具体相关性强弱”。"
|
||||
),
|
||||
"conclusion": (
|
||||
"结论应聚焦于：变量间相关性的整体强弱水平、最主要的正负相关对。"
|
||||
"用一句话概括相关性矩阵的核心特征，不推测因果关系。"
|
||||
"- 挖掘关键水质参数间的生物地球化学联系。如叶绿素与总氮/总磷的正相关提示营养盐驱动，与浊度的正相关提示藻类为主导的悬浮物等。\n"
|
||||
"- 识别拮抗作用（强负相关），并解释其潜在的生化机制（如高浊度遮蔽光照导致叶绿素降低）。\n"
|
||||
"- 基于相关性聚类，推断水体中的核心主导污染因子群。"
|
||||
),
|
||||
"conclusion": "结论应聚焦：水质指标间的核心协同/拮抗机制及水环境的主要驱动力。",
|
||||
},
|
||||
}
|
||||
|
||||
# 默认规格（如果类型未定义）
|
||||
default_spec = {
|
||||
"analysis": "重点：概括图中主要信息，列出可见的轴标签、图例、数据特征。",
|
||||
"conclusion": "结论应基于可见信息，概括图中主要趋势或数据特征，不添加外部知识。",
|
||||
"analysis": "结合水环境遥感原理，深入解读图中展现的数据分布或空间格局特征。",
|
||||
"conclusion": "结论应聚焦：该图表传递的核心水质遥感科学结论。",
|
||||
}
|
||||
|
||||
spec = type_specs.get(image_type, default_spec)
|
||||
analysis_part = spec["analysis"]
|
||||
conclusion_part = spec["conclusion"]
|
||||
|
||||
common_output = (
|
||||
"输出格式：\n"
|
||||
"请结合坐标轴、图例、曲线、点云、颜色条等可见元素，描述数据特征（如分布形态、对比关系、空间位置等），引用图中具体元素但不编造数值。"
|
||||
"随后用一句话总结该图揭示的主要趋势或数据质量。总结必须严格基于前文描述的可见信息，不得引入图中未呈现的外部知识、推测原因或隐含假设。"
|
||||
"若信息不足以得出明确结论，则写“根据本图无法得出明确结论”。"
|
||||
"要求：直接输出分析内容，不要使用“第一段”“第二段”等标记，两段之间不要留空行。")
|
||||
|
||||
|
||||
user = (
|
||||
f"图号：图{figure_num}\n"
|
||||
f"参数：{param}\n"
|
||||
f"图类型：{image_type}\n\n"
|
||||
f"{analysis_part}\n\n"
|
||||
f"{common_output}"
|
||||
f"当前分析参数：{param}\n"
|
||||
f"图表类型：{image_type}\n\n"
|
||||
"【专业要求】：\n"
|
||||
f"{spec['analysis']}\n\n"
|
||||
"【输出格式】：\n"
|
||||
"直接输出一段（不要分段）150~300字的专业分析。前半部分描述关键数据现象并深挖其光学或生态机制，最后用一句“总之，…”作为全文的科学性总结。\n"
|
||||
f"【最终落脚点要求】：{spec['conclusion']}\n"
|
||||
)
|
||||
return {"system": system, "user": user}
|
||||
|
||||
@ -735,13 +633,20 @@ class WaterQualityReportGenerator:
|
||||
self._save_ai_cache(cache)
|
||||
return text
|
||||
|
||||
def _create_progress(self, total: int, desc: str = "进度"):
|
||||
"""创建进度条：优先 tqdm，否则使用简单进度条。"""
|
||||
def _create_progress(self, total: int, desc: str = "进度", on_step=None):
|
||||
"""创建进度条：优先 tqdm，否则使用简单进度条。
|
||||
|
||||
Args:
|
||||
on_step: 可选回调，签名 on_step(percent: int, text: str)。用于驱动 Qt QProgressBar / QThread 进度信号。
|
||||
"""
|
||||
# 如果有 UI 回调需求，强制使用自带的 _SimpleProgress，防止 tqdm 吞掉信号
|
||||
if on_step is not None:
|
||||
return _SimpleProgress(total=total, desc=desc, on_step=on_step)
|
||||
try:
|
||||
from tqdm import tqdm # type: ignore
|
||||
return tqdm(total=total, desc=desc, unit="步", ncols=90)
|
||||
except Exception:
|
||||
return _SimpleProgress(total=total, desc=desc)
|
||||
return _SimpleProgress(total=total, desc=desc, on_step=on_step)
|
||||
|
||||
def _analyze_statistics(self, stats_data: List[Dict[str, Any]], param_names: List[str]) -> str:
|
||||
"""对水质参数统计数据进行 AI 分析"""
|
||||
@ -768,14 +673,19 @@ class WaterQualityReportGenerator:
|
||||
return self._ai_chat(self.ollama_text_model, system, user, image_path=None)
|
||||
|
||||
|
||||
def generate_report(self,
|
||||
def generate_report(self,
|
||||
work_dir: str = None,
|
||||
parameters: List[str] = None,
|
||||
report_title: str = "水质参数反演分析报告",
|
||||
output_path: Optional[str] = None) -> str:
|
||||
output_path: Optional[str] = None,
|
||||
on_progress=None) -> str:
|
||||
"""
|
||||
生成 Word 报告 - 所有数据均来自工作目录（work_dir）
|
||||
可视化图片、统计数据等均从 work_dir/14_visualization 和 work_dir/4_processed_data 中读取
|
||||
|
||||
Args:
|
||||
on_progress: 可选回调，签名 on_progress(percent: int, text: str)。
|
||||
会在进度更新时被调用，用于驱动 Qt QProgressBar/QThread 信号。
|
||||
"""
|
||||
# 设置工作目录（整个流程的核心）
|
||||
if work_dir is not None:
|
||||
@ -805,7 +715,7 @@ class WaterQualityReportGenerator:
|
||||
# 进度条（按“图片处理 + 汇总”计步）
|
||||
total_images = sum(len(self.parameter_images.get(p, [])) for p in parameters)
|
||||
total_steps = total_images + 1 + 1 # +1 相关性热力图（尝试一次），+1 综合总结
|
||||
progress = self._create_progress(total=total_steps, desc="生成Word报告")
|
||||
progress = self._create_progress(total=total_steps, desc="生成Word报告", on_step=on_progress)
|
||||
|
||||
# 创建文档
|
||||
doc = Document()
|
||||
@ -847,6 +757,7 @@ class WaterQualityReportGenerator:
|
||||
base_section_num = 5
|
||||
last_param_section_num = base_section_num + len(parameters) - 1
|
||||
for section_num, param in enumerate(parameters, base_section_num):
|
||||
progress.set_description(f"正在分析 {param} 数据 ({section_num - base_section_num + 1}/{len(parameters)})")
|
||||
figure_counter = self._add_parameter_section(
|
||||
doc,
|
||||
param,
|
||||
@ -873,15 +784,19 @@ class WaterQualityReportGenerator:
|
||||
]
|
||||
)
|
||||
system = (
|
||||
"你是一位水质遥感与报告撰写专家。"
|
||||
"只能基于提供的“逐图分析文本”做总结，禁止引入任何外部事实或猜测。"
|
||||
"若信息不足，必须明确说明“根据现有分析无法判断”。"
|
||||
"你是一位水环境管理决策专家与遥感首席科学家。现需根据前面生成的各参数逐图分析文本，提炼出一份执行摘要级别的综合结论。\n"
|
||||
"必须具备宏观视角，能够将离散的参数分析整合成对该水域整体健康状况的系统性诊断。"
|
||||
)
|
||||
user = (
|
||||
"以下是逐图分析文本，请给出报告级别的综合总结，要求：\n"
|
||||
"- 150~300字中文\n"
|
||||
"- 结构：总体概况 / 主要异常或热点 / 参数间关系（如有）/ 建议关注点\n"
|
||||
"- 不要编造具体数值、地名、日期\n\n"
|
||||
"以下是各个水质参数的详尽逐图分析文本，请基于此撰写一份最终的综合分析总结。\n"
|
||||
"【内容结构需包含】：\n"
|
||||
"1. 整体水质评估（如营养状态、主要污染程度）。\n"
|
||||
"2. 关键时空热点与驱动因子（最需关注的高值区域及核心主导参数）。\n"
|
||||
"3. 遥感反演模型可靠性综合评价。\n"
|
||||
"4. 宏观水环境管理与保护建议。\n"
|
||||
"【⚠️强制要求】：\n"
|
||||
"- 总结的字数必须严格控制在 300 到 450 字之间！\n"
|
||||
"- 必须输出完整的结尾标点符号，绝不允许出现话说一半突然截断的情况！高度精炼，切勿啰嗦。\n\n"
|
||||
f"{analyses_text}"
|
||||
)
|
||||
summary_text = self._ai_chat(self.ollama_text_model, system, user, image_path=None)
|
||||
@ -959,30 +874,47 @@ class WaterQualityReportGenerator:
|
||||
for i, img_name in enumerate(image_list):
|
||||
figure_num = start_figure_num + i
|
||||
|
||||
# 选择子文件夹
|
||||
|
||||
# 选择子文件夹与动态寻址
|
||||
if "boxplot" in img_name.lower():
|
||||
sub_dir = vis_dir / "boxplots"
|
||||
title_key = "boxplot"
|
||||
elif "scatter" in img_name.lower() or "confidence" in img_name.lower():
|
||||
sub_dir = vis_dir / "scatter_plots"
|
||||
title_key = "scatter_with_confidence"
|
||||
elif "histogram" in img_name.lower():
|
||||
sub_dir = vis_dir
|
||||
title_key = "histogram"
|
||||
elif "spectrum" in img_name.lower():
|
||||
sub_dir = vis_dir
|
||||
title_key = "spectrum_comparison"
|
||||
elif "distribution" in img_name.lower():
|
||||
sub_dir = vis_dir
|
||||
title_key = "distribution"
|
||||
else:
|
||||
sub_dir = vis_dir
|
||||
title_key = "histogram"
|
||||
|
||||
img_path = sub_dir / img_name
|
||||
if not img_path.exists():
|
||||
img_path = vis_dir / img_name
|
||||
|
||||
elif "scatter" in img_name.lower() or "pred" in img_name.lower() or "confidence" in img_name.lower():
|
||||
title_key = "scatter_with_confidence"
|
||||
img_path = vis_dir / "scatter_plots" / img_name
|
||||
if not img_path.exists():
|
||||
img_path = vis_dir / img_name
|
||||
elif "histogram" in img_name.lower():
|
||||
title_key = "histogram"
|
||||
img_path = vis_dir / img_name
|
||||
elif "spectrum" in img_name.lower():
|
||||
title_key = "spectrum_comparison"
|
||||
img_path = vis_dir / img_name
|
||||
elif "distribution" in img_name.lower():
|
||||
title_key = "distribution"
|
||||
# 颜色地图由预测步骤生成，开启全盘指索
|
||||
search_dirs = [
|
||||
vis_dir.parent / "9_water_quality_prediction",
|
||||
vis_dir.parent / "11_12_13_predictions",
|
||||
vis_dir.parent / "9_Concentration" / "charts",
|
||||
vis_dir.parent / "9_Concentration",
|
||||
vis_dir
|
||||
]
|
||||
found_map = False
|
||||
for s_dir in search_dirs:
|
||||
if s_dir.exists():
|
||||
candidates = list(s_dir.glob(f"*{param}*.png")) + list(s_dir.glob(f"*{param}*.jpg"))
|
||||
# 剔除掉属于其他类型的图
|
||||
candidates = [c for c in candidates if not any(x in c.name.lower() for x in ("scatter", "histogram", "spectrum", "boxplot", "preview"))]
|
||||
if candidates:
|
||||
img_path = candidates[0]
|
||||
found_map = True
|
||||
break
|
||||
if not found_map:
|
||||
img_path = vis_dir / img_name
|
||||
else:
|
||||
title_key = "histogram"
|
||||
img_path = vis_dir / img_name
|
||||
if img_path.exists():
|
||||
param_cn = param.replace("Chlorophyll", "叶绿素").replace("NO3-N", "硝酸盐氮").replace("NH3-N", "氨氮")
|
||||
cn_title = title_map.get(title_key, "分析图")
|
||||
@ -1245,7 +1177,7 @@ class WaterQualityReportGenerator:
|
||||
vis_dir = self.visualization_dir
|
||||
|
||||
# 0. 航线规划图
|
||||
flight_path_img_path = work_dir_path / "14_visualization" / "flight_maps"
|
||||
flight_path_img_path = work_dir_path / "14_visualization" / "flight_paths"
|
||||
h3 = doc.add_heading("航线规划：", level=3)
|
||||
self._style_heading(h3, level=3)
|
||||
|
||||
@ -1636,7 +1568,7 @@ class WaterQualityReportGenerator:
|
||||
|
||||
# 从工作目录的4_processed_data文件夹查找CSV文件
|
||||
work_dir_path = vis_dir.parent
|
||||
processed_data_dir = work_dir_path / "4_processed_data"
|
||||
processed_data_dir = work_dir_path / "5_Data_Cleaning"
|
||||
|
||||
if not processed_data_dir.exists():
|
||||
doc.add_paragraph(f"未找到数据处理目录: {processed_data_dir}")
|
||||
|
||||
@ -328,31 +328,40 @@ class WaterQualityVisualization:
|
||||
plt.close()
|
||||
output_paths['boxplot'] = str(boxplot_path)
|
||||
|
||||
# 2. 直方图 (每个水质参数列)
|
||||
|
||||
# 2. 直方图与单参数箱线图 (每个水质参数列)
|
||||
for col in numeric_cols:
|
||||
fig, ax = plt.subplots(figsize=(10, 6))
|
||||
data = df[col].dropna()
|
||||
if len(data) > 1:
|
||||
ax.hist(data, bins=30, edgecolor='black', alpha=0.7, color='skyblue')
|
||||
ax.set_xlabel(f'{col} 数值', fontsize=12, fontweight='bold')
|
||||
ax.set_ylabel('频数', fontsize=12, fontweight='bold')
|
||||
ax.set_title(f'{col} 分布直方图', fontsize=14, fontweight='bold')
|
||||
ax.grid(True, alpha=0.3, axis='y')
|
||||
|
||||
# 添加统计信息
|
||||
mean_val = data.mean()
|
||||
std_val = data.std() if len(data) > 1 else 0
|
||||
ax.axvline(mean_val, color='red', linestyle='--', linewidth=2, label=f'均值: {mean_val:.4f}')
|
||||
ax.legend()
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
safe_name = "".join(c for c in col if c.isalnum() or c in ('-', '_', '.'))
|
||||
hist_path = output_dir / f"{safe_name}_histogram.png"
|
||||
plt.savefig(hist_path, dpi=300, bbox_inches='tight')
|
||||
plt.close()
|
||||
if len(data) > 0:
|
||||
# === 直方图生成 ===
|
||||
fig, ax = plt.subplots(figsize=(10, 6))
|
||||
if len(data) > 1:
|
||||
ax.hist(data, bins=30, edgecolor='black', alpha=0.7, color='skyblue')
|
||||
ax.set_xlabel(f'{col} 数值', fontsize=12, fontweight='bold')
|
||||
ax.set_ylabel('频数', fontsize=12, fontweight='bold')
|
||||
ax.set_title(f'{col} 分布直方图', fontsize=14, fontweight='bold')
|
||||
ax.grid(True, alpha=0.3, axis='y')
|
||||
mean_val = data.mean()
|
||||
ax.axvline(mean_val, color='red', linestyle='--', linewidth=2, label=f'均值: {mean_val:.4f}')
|
||||
ax.legend()
|
||||
plt.tight_layout()
|
||||
safe_name = "".join(c for c in col if c.isalnum() or c in ('-', '_', '.'))
|
||||
hist_path = output_dir / f"{safe_name}_histogram.png"
|
||||
plt.savefig(hist_path, dpi=300, bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
output_paths[f'histogram_{col}'] = str(hist_path)
|
||||
|
||||
|
||||
# === 新增：单参数箱线图生成 ===
|
||||
fig_box, ax_box = plt.subplots(figsize=(6, 8))
|
||||
ax_box.boxplot([data], labels=[col])
|
||||
ax_box.set_ylabel('数值', fontsize=12, fontweight='bold')
|
||||
ax_box.set_title(f'{col} 箱线图', fontsize=14, fontweight='bold')
|
||||
ax_box.grid(True, alpha=0.3, axis='y')
|
||||
plt.tight_layout()
|
||||
box_path = output_dir / f"{safe_name}_boxplot.png"
|
||||
plt.savefig(box_path, dpi=300, bbox_inches='tight')
|
||||
plt.close(fig_box)
|
||||
output_paths[f'boxplot_{col}'] = str(box_path)
|
||||
# 3. 相关性热力图
|
||||
if len(numeric_cols) >= 2:
|
||||
corr_matrix = df[numeric_cols].corr()
|
||||
|
||||
Reference in New Issue
Block a user