feat(gui): 全流程面板合并 + 一键式运行 GUI 入口集成
This commit is contained in:
@ -8,7 +8,17 @@ Pipeline 调度核心：基于 Context 的内存级依赖注入。
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- 不绑定具体 Pipeline 实现（duck-typed），WorkerThread / Web API / 单测可共用
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"""
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from .context import PipelineContext
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from .runner import StepSpec, PIPELINE_STEPS, PipelineRunner
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from .context import (
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PipelineContext,
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STEP_MAP_OLD_TO_NEW, STEP_MAP_NEW_TO_OLD,
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resolve_step_id, ALL_STEP_IDS,
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)
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from .runner import (
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StepSpec, PIPELINE_STEPS, PipelineRunner, PipelineHalt,
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)
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__all__ = ["PipelineContext", "StepSpec", "PIPELINE_STEPS", "PipelineRunner"]
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__all__ = [
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"PipelineContext", "StepSpec", "PIPELINE_STEPS", "PipelineRunner", "PipelineHalt",
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"STEP_MAP_OLD_TO_NEW", "STEP_MAP_NEW_TO_OLD",
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"resolve_step_id", "ALL_STEP_IDS",
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]
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@ -12,7 +12,34 @@ PipelineContext：内存级数据载体，跨 14 个 step 传递路径与元信
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional
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from typing import Any, Dict, List, Optional, Set
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# ============================================================
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# 步骤命名映射（定义在叶子节点，打破循环依赖）
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# ============================================================
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STEP_MAP_OLD_TO_NEW: Dict[str, str] = {
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"step5_5": "step8",
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"step6_5": "step8_non_empirical_modeling",
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"step6_75": "step9",
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"step8_5": "step11",
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"step8_75": "step12",
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"step7": "step10",
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"step8": "step11_ml",
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"step9": "step14",
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}
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STEP_MAP_NEW_TO_OLD: Dict[str, str] = {v: k for k, v in STEP_MAP_OLD_TO_NEW.items()}
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ALL_STEP_IDS: Set[str] = set(STEP_MAP_OLD_TO_NEW.keys()) | set(STEP_MAP_OLD_TO_NEW.values())
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def resolve_step_id(step_id: str) -> str:
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"""将任意 step_id 转换为标准新格式。"""
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if step_id in STEP_MAP_OLD_TO_NEW:
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return STEP_MAP_OLD_TO_NEW[step_id]
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return step_id
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@dataclass
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@ -63,10 +90,29 @@ class PipelineContext:
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pipeline_end_time: Optional[float] = None
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last_error: Optional[str] = None
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# ── 错误汇总（全流程结束后可用） ──
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error_summary: List[tuple[str, str]] = field(default_factory=list)
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# ── 出错时立即停止全流程（默认 False：继续后续步骤） ──
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breakpoint_on_error: bool = False
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# ── ★ 智能补全锁定步骤列表（由 _auto_fill_missing_steps 自动开启的步骤） ──
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# GUI 层读取此字段，在运行期间禁用对应面板的启用复选框
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locked_steps: List[str] = field(default_factory=list)
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# ============================================================
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# 读写辅助
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# ============================================================
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def step_id(self, step_id: str) -> str:
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"""将任意 step_id（可能是旧名）转换为标准新格式。
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用法示例：
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ctx.status[ctx.step_id('step6_5')] # 'step8_non_empirical_modeling'
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ctx.user_config[ctx.step_id('step8_5')] # 'step11'
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"""
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if step_id in STEP_MAP_OLD_TO_NEW:
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return STEP_MAP_OLD_TO_NEW[step_id]
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return step_id
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def set(self, key: str, value: Any) -> None:
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"""原地写入任意属性。
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@ -660,7 +660,7 @@ class WaterQualityInversionPipeline:
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self._notify("completed", f"训练光谱数据已保存: {result}")
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return result
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def step5_5_calculate_water_quality_indices(self,
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def step8_water_quality_indices(self,
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training_csv_path: Optional[str] = None,
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formula_csv_file: Optional[str] = None,
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formula_names: Optional[List[str]] = None,
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@ -704,7 +704,7 @@ class WaterQualityInversionPipeline:
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self._notify("completed", f"水质指数已保存: {result}")
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return result
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def step6_train_models(self, feature_start_column: str = "374.285004",
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def step7_ml_modeling(self, feature_start_column: str = "374.285004",
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preprocessing_methods: List[str] = None,
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model_names: List[str] = None,
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split_methods: List[str] = None,
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@ -747,7 +747,7 @@ class WaterQualityInversionPipeline:
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self._notify("completed", f"模型训练完成，结果保存在: {result}")
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return result
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def step7_generate_sampling_points(self, deglint_img_path: Optional[str] = None,
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def step10_sampling(self, deglint_img_path: Optional[str] = None,
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interval: int = 50,
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sample_radius: int = 5,
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chunk_size: int = 1000,
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@ -756,7 +756,7 @@ class WaterQualityInversionPipeline:
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use_adaptive_sampling: bool = True,
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skip_dependency_check: bool = False, **kwargs) -> str:
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"""
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步骤7: 生成根据水域掩膜内且耀斑掩膜外的采样点，统计采样点的平均光谱
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步骤10: 生成根据水域掩膜内且耀斑掩膜外的采样点，统计采样点的平均光谱
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Args:
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deglint_img_path: 去除耀斑后的影像文件路径（如果为None，使用步骤3的结果）
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@ -779,7 +779,7 @@ class WaterQualityInversionPipeline:
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if water_mask_path is None and self.water_mask_path is not None:
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water_mask_path = self.water_mask_path
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self._notify("started", "步骤7: 生成预测采样点")
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self._notify("started", "步骤10: 生成预测采样点")
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result = PredictionStep.generate_sampling_points(
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deglint_img_path=img_path,
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interval=interval,
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@ -790,21 +790,21 @@ class WaterQualityInversionPipeline:
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output_dir=str(self.sampling_dir),
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use_adaptive_sampling=use_adaptive_sampling,
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)
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self._record_step_time("步骤7: 生成预测采样点", 0, 0)
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self._record_step_time("步骤10: 生成预测采样点", 0, 0)
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self._notify("completed", f"采样点光谱数据已保存: {result}")
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return result
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def step8_predict_water_quality(self, sampling_csv_path: str,
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def step11_ml_prediction(self, sampling_csv_path: str,
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models_dir: Optional[str] = None,
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metric: str = 'test_r2',
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prediction_column: str = 'prediction',
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skip_dependency_check: bool = False, **kwargs) -> Dict[str, str]:
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"""
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步骤8: 将训练好的最佳机器学习模型应用到采样点的平均光谱上，预测水质参数
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步骤11: 将训练好的最佳机器学习模型应用到采样点的平均光谱上，预测水质参数
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Args:
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sampling_csv_path: 采样点光谱数据CSV路径
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models_dir: 模型保存目录（如果为None，使用步骤6的结果）
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models_dir: 模型保存目录（如果为None，使用步骤7的结果）
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metric: 选择最佳模型的指标
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prediction_column: 预测结果列名
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@ -818,7 +818,7 @@ class WaterQualityInversionPipeline:
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print(f"[Pipeline] 收到字典: {'Yes' if _external_models_dict else 'No'}"
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f", 收到单模型: {'Yes' if _external_model else 'No'}")
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self._notify("started", "步骤8: 预测水质参数")
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self._notify("started", "步骤11: 预测水质参数")
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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 if models_dir else str(self.models_dir),
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@ -831,11 +831,11 @@ class WaterQualityInversionPipeline:
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_external_models_dict=_external_models_dict,
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_external_model_dir=_external_model_dir,
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)
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self._record_step_time("步骤8: 预测水质参数", 0, 0)
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self._record_step_time("步骤11: 预测水质参数", 0, 0)
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self._notify("completed", f"预测完成，结果保存在: {self.prediction_dir}")
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return result
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def step9_generate_distribution_map(self, prediction_csv_path: str,
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def step14_distribution_map(self, prediction_csv_path: str,
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boundary_shp_path: str,
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output_image_path: Optional[str] = None,
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resolution: float = 30,
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@ -1524,99 +1524,99 @@ class WaterQualityInversionPipeline:
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else:
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self._notify("步骤5: 光谱提取", "skipped", "未配置")
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# 步骤5.5: 计算水质指数
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if 'step5_5' in config:
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self._notify("步骤5.5: 水质指数计算", "start")
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self.step5_5_calculate_water_quality_indices(**config['step5_5'])
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self._notify("步骤5.5: 水质指数计算", "completed", f"(输出: {self.indices_path})")
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# 步骤8: 计算水质指数
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if 'step8' in config:
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self._notify("步骤8: 水质指数计算", "start")
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self.step8_water_quality_indices(**config['step8'])
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self._notify("步骤8: 水质指数计算", "completed", f"(输出: {self.indices_path})")
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else:
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self._notify("步骤5.5: 水质指数计算", "skipped", "未配置")
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self._notify("步骤8: 水质指数计算", "skipped", "未配置")
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# 步骤6: 训练模型
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if 'step6' in config:
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self._notify("步骤6: 模型训练", "start")
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self.step6_train_models(**config['step6'])
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self._notify("步骤6: 模型训练", "completed", f"(输出: {self.models_dir})")
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else:
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self._notify("步骤6: 模型训练", "skipped", "未配置")
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# 步骤6.5: 非经验统计回归模型训练
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if 'step6_5' in config:
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self._notify("步骤6.5: 非经验模型训练", "start")
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self.step6_5_non_empirical_modeling(**config['step6_5'])
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self._notify("步骤6.5: 非经验模型训练", "completed", f"(输出: {self.models_dir})")
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else:
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self._notify("步骤6.5: 非经验模型训练", "skipped", "未配置")
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# 步骤6.75: 自定义回归分析
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if 'step6_75' in config:
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self._notify("步骤6.75: 自定义回归", "start")
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self.step6_75_custom_regression(**config['step6_75'])
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self._notify("步骤6.75: 自定义回归", "completed", f"(输出: {self.custom_regression_path})")
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else:
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self._notify("步骤6.75: 自定义回归", "skipped", "未配置")
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# 步骤7: 生成预测采样点
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# 步骤7: 训练模型
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if 'step7' in config:
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self._notify("步骤7: 采样点生成", "start")
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sampling_csv_path = self.step7_generate_sampling_points(**config['step7'])
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self._notify("步骤7: 采样点生成", "completed", f"(输出: {sampling_csv_path})")
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self._notify("步骤7: 模型训练", "start")
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self.step7_ml_modeling(**config['step7'])
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self._notify("步骤7: 模型训练", "completed", f"(输出: {self.models_dir})")
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else:
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self._notify("步骤7: 模型训练", "skipped", "未配置")
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# 步骤8_non_empirical_modeling: 非经验统计回归模型训练
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if 'step8_non_empirical_modeling' in config:
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self._notify("步骤8: 非经验模型训练", "start")
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self.step8_non_empirical_modeling(**config['step8_non_empirical_modeling'])
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self._notify("步骤8: 非经验模型训练", "completed", f"(输出: {self.models_dir})")
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else:
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self._notify("步骤8: 非经验模型训练", "skipped", "未配置")
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# 步骤9: 自定义回归分析
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if 'step9' in config:
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self._notify("步骤9: 自定义回归", "start")
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self.step9_custom_regression(**config['step9'])
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self._notify("步骤9: 自定义回归", "completed", f"(输出: {self.custom_regression_path})")
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else:
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self._notify("步骤9: 自定义回归", "skipped", "未配置")
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# 步骤10: 生成预测采样点
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if 'step10' in config:
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self._notify("步骤10: 采样点生成", "start")
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sampling_csv_path = self.step10_sampling(**config['step10'])
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self._notify("步骤10: 采样点生成", "completed", f"(输出: {sampling_csv_path})")
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else:
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sampling_csv_path = None
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self._notify("步骤7: 采样点生成", "skipped", "未配置")
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self._notify("步骤10: 采样点生成", "skipped", "未配置")
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# 步骤8: 预测水质参数
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if 'step8' in config and sampling_csv_path:
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self._notify("步骤8: 参数预测", "start")
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step8_config = config['step8'].copy()
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step8_config['sampling_csv_path'] = sampling_csv_path
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prediction_files = self.step8_predict_water_quality(**step8_config)
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self._notify("步骤8: 参数预测", "completed", f"(生成{len(prediction_files)}个预测文件)")
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# 步骤11_ml: 预测水质参数
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if 'step11_ml' in config and sampling_csv_path:
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self._notify("步骤11: 参数预测", "start")
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step11_ml_config = config['step11_ml'].copy()
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step11_ml_config['sampling_csv_path'] = sampling_csv_path
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prediction_files = self.step11_ml_prediction(**step11_ml_config)
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self._notify("步骤11: 参数预测", "completed", f"(生成{len(prediction_files)}个预测文件)")
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else:
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prediction_files = {}
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self._notify("步骤8: 参数预测", "skipped", "未配置或缺少采样点")
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self._notify("步骤11: 参数预测", "skipped", "未配置或缺少采样点")
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# 步骤8.5: 使用非经验模型进行参数预测
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# 步骤11: 使用非经验模型进行参数预测
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non_empirical_prediction_files = {}
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if 'step8_5' in config and sampling_csv_path:
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self._notify("步骤8.5: 非经验模型预测", "start")
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step8_5_config = config['step8_5'].copy()
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step8_5_config['sampling_csv_path'] = sampling_csv_path
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non_empirical_prediction_files = self.step8_5_predict_with_non_empirical_models(**step8_5_config)
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self._notify("步骤8.5: 非经验模型预测", "completed", f"(生成{len(non_empirical_prediction_files)}个预测文件)")
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if 'step11' in config and sampling_csv_path:
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self._notify("步骤11: 非经验模型预测", "start")
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step11_config = config['step11'].copy()
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step11_config['sampling_csv_path'] = sampling_csv_path
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non_empirical_prediction_files = self.step11_non_empirical_prediction(**step11_config)
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self._notify("步骤11: 非经验模型预测", "completed", f"(生成{len(non_empirical_prediction_files)}个预测文件)")
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else:
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self._notify("步骤8.5: 非经验模型预测", "skipped", "未配置或缺少采样点")
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self._notify("步骤11: 非经验模型预测", "skipped", "未配置或缺少采样点")
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# 步骤8.75: 使用自定义回归模型进行参数预测
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# 步骤12: 使用自定义回归模型进行参数预测
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custom_regression_prediction_files = {}
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if 'step8_75' in config and sampling_csv_path:
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self._notify("步骤8.75: 自定义回归预测", "start")
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step8_75_config = config['step8_75'].copy()
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step8_75_config['sampling_csv_path'] = sampling_csv_path
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custom_regression_prediction_files = self.step8_75_predict_with_custom_regression(**step8_75_config)
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self._notify("步骤8.75: 自定义回归预测", "completed", f"(生成{len(custom_regression_prediction_files)}个预测文件)")
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if 'step12' in config and sampling_csv_path:
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self._notify("步骤12: 自定义回归预测", "start")
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step12_config = config['step12'].copy()
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step12_config['sampling_csv_path'] = sampling_csv_path
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custom_regression_prediction_files = self.step12_custom_regression_prediction(**step12_config)
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self._notify("步骤12: 自定义回归预测", "completed", f"(生成{len(custom_regression_prediction_files)}个预测文件)")
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else:
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self._notify("步骤8.75: 自定义回归预测", "skipped", "未配置或缺少采样点")
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self._notify("步骤12: 自定义回归预测", "skipped", "未配置或缺少采样点")
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|
||||
# 合并机器学习预测、非经验模型预测和自定义回归预测结果
|
||||
all_prediction_files = {**prediction_files, **non_empirical_prediction_files, **custom_regression_prediction_files}
|
||||
|
||||
# 步骤9: 生成分布图
|
||||
# 步骤14: 生成分布图
|
||||
distribution_maps = {}
|
||||
if 'step9' in config and all_prediction_files:
|
||||
self._notify("步骤9: 分布图生成", "start")
|
||||
if 'step14' in config and all_prediction_files:
|
||||
self._notify("步骤14: 分布图生成", "start")
|
||||
for target_name, pred_file in all_prediction_files.items():
|
||||
step9_config = config['step9'].copy()
|
||||
step14_config = config['step14'].copy()
|
||||
for _k in ('step9_batch_mode', 'prediction_csv_dir', 'recursive_csv_scan'):
|
||||
step9_config.pop(_k, None)
|
||||
step9_config['prediction_csv_path'] = pred_file
|
||||
if 'output_image_path' not in step9_config:
|
||||
step9_config['output_image_path'] = None
|
||||
dist_map_path = self.step9_generate_distribution_map(**step9_config)
|
||||
step14_config.pop(_k, None)
|
||||
step14_config['prediction_csv_path'] = pred_file
|
||||
if 'output_image_path' not in step14_config:
|
||||
step14_config['output_image_path'] = None
|
||||
dist_map_path = self.step14_distribution_map(**step14_config)
|
||||
distribution_maps[target_name] = dist_map_path
|
||||
self._notify("步骤9: 分布图生成", "completed", f"(生成{len(distribution_maps)}个分布图)")
|
||||
self._notify("步骤14: 分布图生成", "completed", f"(生成{len(distribution_maps)}个分布图)")
|
||||
else:
|
||||
self._notify("步骤9: 分布图生成", "skipped", "未配置或缺少预测结果")
|
||||
self._notify("步骤14: 分布图生成", "skipped", "未配置或缺少预测结果")
|
||||
|
||||
# 生成可视化图表
|
||||
output_files = {}
|
||||
@ -1716,10 +1716,10 @@ class WaterQualityInversionPipeline:
|
||||
pipeline_info['step3'] = {'status': 'completed', 'output_file': str(self.deglint_img_path) if self.deglint_img_path else 'N/A'}
|
||||
pipeline_info['step4'] = {'status': 'completed', 'output_file': str(self.processed_csv_path) if self.processed_csv_path else 'N/A'}
|
||||
pipeline_info['step5'] = {'status': 'completed', 'output_file': str(self.training_csv_path) if self.training_csv_path else 'N/A'}
|
||||
pipeline_info['step5_5'] = {'status': 'completed', 'output_file': str(self.indices_path) if self.indices_path else 'N/A'}
|
||||
pipeline_info['step6'] = {'status': 'completed', 'output_file': str(self.models_dir)}
|
||||
pipeline_info['step6_75'] = {'status': 'completed', 'output_file': str(self.custom_regression_path) if self.custom_regression_path else 'N/A'}
|
||||
pipeline_info['training_params'] = config.get('step6', {})
|
||||
pipeline_info['step8'] = {'status': 'completed', 'output_file': str(self.indices_path) if self.indices_path else 'N/A'}
|
||||
pipeline_info['step7'] = {'status': 'completed', 'output_file': str(self.models_dir)}
|
||||
pipeline_info['step9'] = {'status': 'completed', 'output_file': str(self.custom_regression_path) if self.custom_regression_path else 'N/A'}
|
||||
pipeline_info['training_params'] = config.get('step7', {})
|
||||
|
||||
summary_path = self.report_generator.generate_batch_inference_summary(pipeline_info)
|
||||
print(f"批量处理摘要已生成: {summary_path}")
|
||||
@ -1769,7 +1769,7 @@ class WaterQualityInversionPipeline:
|
||||
traceback.print_exc()
|
||||
raise
|
||||
|
||||
def step6_5_non_empirical_modeling(self, csv_path: Optional[str] = None,
|
||||
def step8_non_empirical_modeling(self, csv_path: Optional[str] = None,
|
||||
preprocessing_methods: List[str] = None,
|
||||
algorithms: List[str] = None,
|
||||
value_cols: Union[int, Dict[str, int]] = 0,
|
||||
@ -1819,7 +1819,7 @@ class WaterQualityInversionPipeline:
|
||||
self._notify("completed", f"非经验模型训练完成")
|
||||
return result
|
||||
|
||||
def step6_75_custom_regression(self,
|
||||
def step9_custom_regression(self,
|
||||
csv_path: Optional[str] = None,
|
||||
x_columns: Optional[Union[str, List[str]]] = None,
|
||||
y_columns: Optional[Union[str, List[str]]] = None,
|
||||
@ -1999,7 +1999,7 @@ class WaterQualityInversionPipeline:
|
||||
|
||||
return summary_path
|
||||
|
||||
def step8_5_predict_with_non_empirical_models(self, sampling_csv_path: str,
|
||||
def step11_non_empirical_prediction(self, sampling_csv_path: str,
|
||||
non_empirical_models_dir: Optional[str] = None,
|
||||
output_path: Optional[str] = None,
|
||||
metric: str = 'Average Accuracy(%)',
|
||||
@ -2007,13 +2007,13 @@ class WaterQualityInversionPipeline:
|
||||
enabled: bool = True,
|
||||
skip_dependency_check: bool = False, **kwargs) -> Dict[str, str]:
|
||||
"""
|
||||
步骤8.5: 使用非经验统计回归模型进行参数预测
|
||||
步骤11: 使用非经验统计回归模型进行参数预测
|
||||
|
||||
根据非经验模型训练结果汇总CSV筛选给定方法的准确率最高的模型，使用该模型进行预测
|
||||
|
||||
Args:
|
||||
sampling_csv_path: 采样点光谱数据CSV路径
|
||||
non_empirical_models_dir: 非经验模型保存目录（如果为None，使用步骤6.5的结果）
|
||||
non_empirical_models_dir: 非经验模型保存目录（如果为None，使用步骤8的结果）
|
||||
output_path: 输出目录路径（如果为None，使用默认目录）
|
||||
metric: 选择最佳模型的指标（默认使用平均准确率）
|
||||
prediction_column: 预测结果列名
|
||||
@ -2021,7 +2021,7 @@ class WaterQualityInversionPipeline:
|
||||
Returns:
|
||||
预测结果文件路径字典（键为算法名）
|
||||
"""
|
||||
self._notify("started", "步骤8.5: 使用非经验模型进行参数预测")
|
||||
self._notify("started", "步骤11: 使用非经验模型进行参数预测")
|
||||
result = PredictionStep.predict_with_non_empirical_models(
|
||||
sampling_csv_path=sampling_csv_path,
|
||||
non_empirical_models_dir=non_empirical_models_dir,
|
||||
@ -2031,11 +2031,11 @@ class WaterQualityInversionPipeline:
|
||||
enabled=enabled,
|
||||
work_dir=str(self.work_dir),
|
||||
)
|
||||
self._record_step_time("步骤8.5: 非经验模型预测", 0, 0)
|
||||
self._record_step_time("步骤11: 非经验模型预测", 0, 0)
|
||||
self._notify("completed", f"非经验模型预测完成，结果保存在: {self.prediction_dir}")
|
||||
return result
|
||||
|
||||
def step8_75_predict_with_custom_regression(self, sampling_csv_path: str,
|
||||
def step12_custom_regression_prediction(self, sampling_csv_path: str,
|
||||
custom_regression_dir: Optional[str] = None,
|
||||
formula_csv_path: Optional[str] = None,
|
||||
coordinate_columns: Optional[List[str]] = None,
|
||||
@ -2044,13 +2044,13 @@ class WaterQualityInversionPipeline:
|
||||
enabled: bool = True,
|
||||
skip_dependency_check: bool = False, **kwargs) -> Dict[str, str]:
|
||||
"""
|
||||
步骤8.75: 使用自定义回归模型进行参数预测
|
||||
|
||||
步骤12: 使用自定义回归模型进行参数预测
|
||||
|
||||
使用新的CustomRegressionPredictor模块，基于9_Custom_Regression_Modeling文件夹中的CSV，
|
||||
根据r_squared选择最佳模型，批量预测水质参数
|
||||
|
||||
|
||||
Args:
|
||||
sampling_csv_path: 采样点光谱数据CSV路径（来自步骤7）
|
||||
sampling_csv_path: 采样点光谱数据CSV路径（来自步骤10）
|
||||
custom_regression_dir: 自定义回归模型目录（9_Custom_Regression_Modeling）
|
||||
formula_csv_path: 公式CSV文件路径，用于查找index_formula
|
||||
coordinate_columns: 坐标列名列表，默认为['longitude', 'latitude']或自动识别
|
||||
@ -2058,11 +2058,11 @@ class WaterQualityInversionPipeline:
|
||||
filename_prefix: 输出文件名前缀
|
||||
enabled: 是否启用
|
||||
skip_dependency_check: 是否跳过依赖检查
|
||||
|
||||
|
||||
Returns:
|
||||
预测结果文件路径字典（键为参数名）
|
||||
"""
|
||||
self._notify("started", "步骤8.75: 使用自定义回归模型进行参数预测")
|
||||
self._notify("started", "步骤12: 使用自定义回归模型进行参数预测")
|
||||
result = PredictionStep.predict_with_custom_regression(
|
||||
sampling_csv_path=sampling_csv_path,
|
||||
custom_regression_dir=custom_regression_dir,
|
||||
@ -2073,7 +2073,7 @@ class WaterQualityInversionPipeline:
|
||||
enabled=enabled,
|
||||
work_dir=str(self.work_dir),
|
||||
)
|
||||
self._record_step_time("步骤8.75: 自定义回归模型预测", 0, 0)
|
||||
self._record_step_time("步骤12: 自定义回归模型预测", 0, 0)
|
||||
self._notify("completed", f"自定义回归预测完成")
|
||||
return result
|
||||
|
||||
@ -2161,20 +2161,20 @@ def main():
|
||||
# 单步运行时建议显式指定；完整流程中可省略，将使用步骤2输出的耀斑掩膜
|
||||
# 'glint_mask_path': r"path/to/severe_glint_area.dat",
|
||||
},
|
||||
'step5_5': {
|
||||
'step8': {
|
||||
'formula_csv_file': 'path/to/water_quality_formulas.csv', # 公式CSV文件路径
|
||||
'formula_names': ['Al10SABI', 'TurbBe16RedOverViolet'], # 要计算的公式名称列表
|
||||
'output_filename': 'water_quality_indices.csv',
|
||||
'enabled': True # 是否启用水质指数计算
|
||||
},
|
||||
'step6': {
|
||||
'step7': {
|
||||
'feature_start_column': '374.285004',
|
||||
'preprocessing_methods': ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT'],
|
||||
'model_names': ['SVR', 'RF', 'Ridge', 'Lasso'],
|
||||
'split_methods': ['spxy', 'ks', 'random'],
|
||||
'cv_folds': 3
|
||||
},
|
||||
'step6_5': {
|
||||
'step8_non_empirical_modeling': {
|
||||
'preprocessing_methods': ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT'],
|
||||
'algorithms': ['chl_a', 'nh3', 'mno4', 'tn', 'tp', 'tss'],
|
||||
'value_cols': 0, # 可以是单个整数或字典，如 {'chl_a': 0, 'nh3': 1, 'mno4': 2, 'tn': 3, 'tp': 4, 'tss': 5}
|
||||
@ -2182,14 +2182,14 @@ def main():
|
||||
'window': 5,
|
||||
'enabled': True # 是否启用非经验模型训练
|
||||
},
|
||||
'step6_75': {
|
||||
'step9': {
|
||||
'x_columns': ['NDWI', 'NDVI'], # 自变量列名列表
|
||||
'y_columns': ['chl_a', 'tn', 'tp'], # 因变量列名列表
|
||||
'methods': 'all', # 回归方法
|
||||
'output_dir': 'custom_regression_results', # 输出目录
|
||||
'enabled': True # 是否启用自定义回归分析
|
||||
},
|
||||
'step7': {
|
||||
'step10': {
|
||||
'interval': 50,
|
||||
'sample_radius': 5,
|
||||
'chunk_size': 1000,
|
||||
@ -2197,16 +2197,16 @@ def main():
|
||||
# 可选：耀斑掩膜文件（dat），若不提供将使用步骤2结果；需要外部指定时取消注释
|
||||
# 'glint_mask_path': r"D:\path\to\severe_glint_area.dat",
|
||||
},
|
||||
'step8': {
|
||||
'step11_ml': {
|
||||
'metric': 'test_r2',
|
||||
'prediction_column': 'prediction'
|
||||
},
|
||||
'step8_5': {
|
||||
'step11': {
|
||||
'metric': 'Average Accuracy(%)', # 选择最佳模型的指标
|
||||
'prediction_column': 'prediction',
|
||||
'enabled': True # 是否启用非经验模型预测
|
||||
},
|
||||
'step8_75': {
|
||||
'step12': {
|
||||
'custom_regression_dir': None, # 自定义回归模型目录（None表示使用9_Custom_Regression_Modeling）
|
||||
'formula_csv_path': None, # 公式CSV文件路径，用于查找index_formula（如water_quality_formulas.csv）
|
||||
'coordinate_columns': None, # 坐标列名（None表示自动识别）
|
||||
@ -2214,7 +2214,7 @@ def main():
|
||||
'filename_prefix': 'custom_regression_prediction', # 输出文件名前缀
|
||||
'enabled': True # 是否启用自定义回归预测
|
||||
},
|
||||
'step9': {
|
||||
'step14': {
|
||||
'boundary_shp_path': r"D:\BaiduNetdiskDownload\yaobao\roi\roi.shp" ,
|
||||
'resolution': 30,
|
||||
'input_crs': 'EPSG:32651',
|
||||
@ -2345,41 +2345,41 @@ def example_independent_steps():
|
||||
except Exception as e:
|
||||
print(f"步骤6失败: {e}")
|
||||
|
||||
# 示例6: 独立运行步骤7 - 采样点生成
|
||||
print("\n示例6: 独立运行步骤7 - 采样点生成")
|
||||
# 示例6: 独立运行步骤10 - 采样点生成
|
||||
print("\n示例6: 独立运行步骤10 - 采样点生成")
|
||||
try:
|
||||
sampling_csv = pipeline.step7_generate_sampling_points(
|
||||
sampling_csv = pipeline.step10_sampling(
|
||||
deglint_img_path="path/to/deglint_image.bsq",
|
||||
water_mask_path="path/to/water_mask.dat",
|
||||
skip_dependency_check=True
|
||||
)
|
||||
print(f"采样点数据: {sampling_csv}")
|
||||
except Exception as e:
|
||||
print(f"步骤7失败: {e}")
|
||||
print(f"步骤10失败: {e}")
|
||||
|
||||
# 示例7: 独立运行步骤8 - 水质预测
|
||||
print("\n示例7: 独立运行步骤8 - 水质预测")
|
||||
# 示例7: 独立运行步骤11 - 水质预测
|
||||
print("\n示例7: 独立运行步骤11 - 水质预测")
|
||||
try:
|
||||
predictions = pipeline.step8_predict_water_quality(
|
||||
predictions = pipeline.step11_ml_prediction(
|
||||
sampling_csv_path="path/to/sampling_spectra.csv",
|
||||
models_dir="path/to/models_directory",
|
||||
skip_dependency_check=True
|
||||
)
|
||||
print(f"预测结果: {predictions}")
|
||||
except Exception as e:
|
||||
print(f"步骤8失败: {e}")
|
||||
print(f"步骤11失败: {e}")
|
||||
|
||||
# 示例8: 独立运行步骤9 - 分布图生成
|
||||
print("\n示例8: 独立运行步骤9 - 分布图生成")
|
||||
# 示例8: 独立运行步骤14 - 分布图生成
|
||||
print("\n示例8: 独立运行步骤14 - 分布图生成")
|
||||
try:
|
||||
distribution_map = pipeline.step9_generate_distribution_map(
|
||||
distribution_map = pipeline.step14_distribution_map(
|
||||
prediction_csv_path="path/to/prediction_results.csv",
|
||||
boundary_shp_path="path/to/boundary.shp",
|
||||
skip_dependency_check=True
|
||||
)
|
||||
print(f"分布图: {distribution_map}")
|
||||
except Exception as e:
|
||||
print(f"步骤9失败: {e}")
|
||||
print(f"步骤14失败: {e}")
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("独立步骤运行示例完成")
|
||||
|
||||
237
src/gui/core/pipeline_mode_dialog.py
Normal file
237
src/gui/core/pipeline_mode_dialog.py
Normal file
@ -0,0 +1,237 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
PipelineModeDialog：全流程运行前的模式选择弹窗。
|
||||
|
||||
用户点击"运行完整流程"后，首先弹出此弹窗选择执行模式：
|
||||
- 选项 A（训练新模型并预测）：执行完整建模与预测流程，需要实测水质 CSV
|
||||
- 选项 B（使用已有模型直接预测）：跳过训练步骤，直接使用外部模型目录进行预测
|
||||
|
||||
弹窗结果：
|
||||
- QDialog.Accepted + self.selected_mode = "training" 或 "prediction_only"
|
||||
- QDialog.Rejected → 调用方中止 run_full_pipeline
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import Optional
|
||||
|
||||
from PyQt5.QtCore import Qt
|
||||
from PyQt5.QtGui import QFont
|
||||
from PyQt5.QtWidgets import (
|
||||
QDialog, QVBoxLayout, QHBoxLayout, QLabel, QPushButton,
|
||||
QRadioButton, QGroupBox, QButtonGroup, QMessageBox, QSizePolicy,
|
||||
)
|
||||
|
||||
|
||||
def _is_valid_model_dir(path: str) -> bool:
|
||||
"""深层递归检测模型目录：只要任意层级存在文件即返回 True。"""
|
||||
if not path or not os.path.isdir(path):
|
||||
return False
|
||||
for _root, _dirs, files in os.walk(path):
|
||||
if files:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
class PipelineModeDialog(QDialog):
|
||||
"""全流程模式选择对话框。
|
||||
|
||||
两个单选按钮覆盖两种业务场景：
|
||||
- A：训练新模型（完整流程，需要 step4 CSV）
|
||||
- B：仅预测（跳过 step4/5/7/8，直接用外部模型目录）
|
||||
|
||||
属性：
|
||||
selected_mode: "training" | "prediction_only"
|
||||
"""
|
||||
|
||||
def __init__(self, main_window=None, parent=None):
|
||||
super().__init__(parent)
|
||||
self.main_window = main_window
|
||||
self.selected_mode: Optional[str] = None
|
||||
self.setWindowTitle("选择运行模式")
|
||||
self.setMinimumSize(560, 340)
|
||||
self.setModal(True)
|
||||
self._setup_ui()
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# UI 构建
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def _setup_ui(self):
|
||||
layout = QVBoxLayout(self)
|
||||
layout.setContentsMargins(28, 24, 28, 20)
|
||||
layout.setSpacing(14)
|
||||
|
||||
# ── 标题 ──
|
||||
title = QLabel("请选择全流程运行模式")
|
||||
title_font = QFont()
|
||||
title_font.setPointSize(13)
|
||||
title_font.setBold(True)
|
||||
title.setFont(title_font)
|
||||
title.setAlignment(Qt.AlignCenter)
|
||||
layout.addWidget(title)
|
||||
|
||||
layout.addSpacing(4)
|
||||
|
||||
# ── 选项 A：训练新模型 ──
|
||||
group_a = QGroupBox()
|
||||
group_a.setObjectName("groupA")
|
||||
group_a.setMinimumHeight(100)
|
||||
layout.addWidget(group_a)
|
||||
|
||||
self.radio_a = QRadioButton("【训练新模型并预测】")
|
||||
self.radio_a.setChecked(True) # 默认选项 A
|
||||
self.radio_a.setObjectName("radioTraining")
|
||||
|
||||
desc_a = QLabel(
|
||||
"需要提供实测水质数据 (CSV)，将执行完整建模与预测流程。\n"
|
||||
"包括：水域掩膜 → 耀斑去除 → 光谱特征提取 → 模型训练 → 密集采样 → 预测 → 专题图"
|
||||
)
|
||||
desc_a.setWordWrap(True)
|
||||
desc_a.setStyleSheet("color: #555555; background: transparent;")
|
||||
desc_a.setObjectName("descA")
|
||||
|
||||
vbox_a = QVBoxLayout(group_a)
|
||||
vbox_a.setContentsMargins(16, 20, 16, 14)
|
||||
vbox_a.setSpacing(8)
|
||||
vbox_a.addWidget(self.radio_a)
|
||||
vbox_a.addWidget(desc_a)
|
||||
|
||||
# ── 选项 B：仅预测 ──
|
||||
group_b = QGroupBox()
|
||||
group_b.setObjectName("groupB")
|
||||
group_b.setMinimumHeight(100)
|
||||
layout.addWidget(group_b)
|
||||
|
||||
self.radio_b = QRadioButton("【使用已有模型直接预测】")
|
||||
self.radio_b.setObjectName("radioPrediction")
|
||||
|
||||
desc_b = QLabel(
|
||||
"跳过模型训练步骤，直接使用导入的外部模型目录进行预测。\n"
|
||||
"前提条件：请在「监督预测」或「回归预测」面板中指定模型目录。\n"
|
||||
"适用范围：已有预训练模型、或其他来源模型目录。"
|
||||
)
|
||||
desc_b.setWordWrap(True)
|
||||
desc_b.setStyleSheet("color: #555555; background: transparent;")
|
||||
desc_b.setObjectName("descB")
|
||||
|
||||
vbox_b = QVBoxLayout(group_b)
|
||||
vbox_b.setContentsMargins(16, 20, 16, 14)
|
||||
vbox_b.setSpacing(8)
|
||||
vbox_b.addWidget(self.radio_b)
|
||||
vbox_b.addWidget(desc_b)
|
||||
|
||||
# ── 强制互斥：QButtonGroup ──
|
||||
self.mode_group = QButtonGroup(self)
|
||||
self.mode_group.addButton(self.radio_a)
|
||||
self.mode_group.addButton(self.radio_b)
|
||||
|
||||
# ── 提示栏（动态显示 models_dir 状态） ──
|
||||
self.models_hint = QLabel()
|
||||
self.models_hint.setObjectName("modelsHint")
|
||||
self.models_hint.setWordWrap(True)
|
||||
self.models_hint.setStyleSheet("color: #888888; font-size: 11px; padding: 4px 0;")
|
||||
layout.addWidget(self.models_hint)
|
||||
|
||||
# ── 强制 QRadioButton 指示器为实心圆点 ──
|
||||
self.setStyleSheet("""
|
||||
QRadioButton::indicator {
|
||||
width: 14px;
|
||||
height: 14px;
|
||||
}
|
||||
QRadioButton::indicator:checked {
|
||||
background-color: #0078D7;
|
||||
border: 2px solid #0078D7;
|
||||
border-radius: 7px;
|
||||
}
|
||||
QRadioButton::indicator:unchecked {
|
||||
background-color: white;
|
||||
border: 2px solid #A0A0A0;
|
||||
border-radius: 7px;
|
||||
}
|
||||
""")
|
||||
|
||||
# ── 按钮 ──
|
||||
btn_layout = QHBoxLayout()
|
||||
btn_layout.addStretch()
|
||||
|
||||
cancel_btn = QPushButton("取消")
|
||||
cancel_btn.setObjectName("cancelBtn")
|
||||
cancel_btn.setMinimumWidth(90)
|
||||
cancel_btn.clicked.connect(self.reject)
|
||||
|
||||
self.btn_confirm = QPushButton("确认")
|
||||
self.btn_confirm.setObjectName("confirmBtn")
|
||||
self.btn_confirm.setMinimumWidth(90)
|
||||
self.btn_confirm.setDefault(True)
|
||||
self.btn_confirm.clicked.connect(self._on_confirm)
|
||||
|
||||
btn_layout.addWidget(self.btn_confirm)
|
||||
btn_layout.addWidget(cancel_btn)
|
||||
layout.addLayout(btn_layout)
|
||||
|
||||
# 信号连接：任一 radio 切换时重新渲染提示 + 按钮状态
|
||||
self.radio_a.toggled.connect(self._update_models_hint)
|
||||
self.radio_b.toggled.connect(self._update_models_hint)
|
||||
|
||||
# 初始状态渲染
|
||||
self._update_models_hint()
|
||||
|
||||
def _update_models_hint(self, checked=False, *args) -> None:
|
||||
"""根据当前选中模式和 models_dir 状态更新提示文字及确认按钮可用性。"""
|
||||
training_checked = self.radio_a.isChecked()
|
||||
|
||||
# 从主窗口 config 读取 models_dir（优先 ml，其次 reg）
|
||||
models_dir = ""
|
||||
if self.main_window:
|
||||
config = self.main_window.get_current_config()
|
||||
models_dir = config.get("step11_ml", {}).get("models_dir", "")
|
||||
if not models_dir:
|
||||
models_dir = config.get("step11", {}).get("models_dir", "")
|
||||
|
||||
has_files = bool(models_dir and _is_valid_model_dir(models_dir))
|
||||
dir_exists = bool(models_dir and os.path.isdir(models_dir))
|
||||
|
||||
if training_checked:
|
||||
if hasattr(self, 'btn_confirm') and self.btn_confirm is not None:
|
||||
self.btn_confirm.setEnabled(True)
|
||||
if has_files:
|
||||
self.models_hint.setText(
|
||||
f"⚠ 注意：当前模型目录已包含文件，继续训练将会【覆盖】原有模型！\n路径：{models_dir}"
|
||||
)
|
||||
self.models_hint.setStyleSheet("color: #e65100; font-size: 11px; padding: 4px 0;")
|
||||
else:
|
||||
label = f"✓ 模型将保存至该目录（当前为空，安全）。\n路径：{models_dir}" if dir_exists else "✓ 尚未指定模型目录，将使用默认路径创建新模型。"
|
||||
self.models_hint.setText(label)
|
||||
self.models_hint.setStyleSheet("color: #2e7d32; font-size: 11px; padding: 4px 0;")
|
||||
else:
|
||||
if has_files:
|
||||
self.models_hint.setText(
|
||||
f"✓ 已检测到有效模型目录，可以直接预测。\n路径：{models_dir}"
|
||||
)
|
||||
self.models_hint.setStyleSheet("color: #2e7d32; font-size: 11px; padding: 4px 0;")
|
||||
if hasattr(self, 'btn_confirm') and self.btn_confirm is not None:
|
||||
self.btn_confirm.setEnabled(True)
|
||||
else:
|
||||
if dir_exists:
|
||||
self.models_hint.setText(
|
||||
f"❌ 错误：模型目录为空（未找到任何文件），无法进行预测！\n路径：{models_dir}"
|
||||
)
|
||||
else:
|
||||
self.models_hint.setText(
|
||||
"❌ 错误：模型目录为空或不存在！请先返回对应面板配置有效路径。"
|
||||
)
|
||||
self.models_hint.setStyleSheet("color: #c62828; font-size: 11px; padding: 4px 0;")
|
||||
if hasattr(self, 'btn_confirm') and self.btn_confirm is not None:
|
||||
self.btn_confirm.setEnabled(False)
|
||||
|
||||
def _on_confirm(self) -> None:
|
||||
"""确认按钮回调：直接存储模式并关闭。
|
||||
|
||||
注意：按钮禁用状态已在 _update_models_hint 中处理，
|
||||
此处仅负责结果存储，不再做二次弹窗拦截。
|
||||
"""
|
||||
if self.radio_a.isChecked():
|
||||
self.selected_mode = "training"
|
||||
else:
|
||||
self.selected_mode = "prediction_only"
|
||||
self.accept()
|
||||
@ -349,6 +349,12 @@ class AISettingsDialog(QDialog):
|
||||
# 交互式采样点与光谱查看器
|
||||
# ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
import matplotlib.pyplot as _plt
|
||||
|
||||
# 全局字体设置（防中文乱码 + 负号显示异常）
|
||||
_plt.rcParams['font.sans-serif'] = ['Microsoft YaHei', 'SimHei', 'Arial Unicode MS']
|
||||
_plt.rcParams['axes.unicode_minus'] = False
|
||||
|
||||
|
||||
class SamplingViewerDialog(QDialog):
|
||||
"""交互式采样点与光谱查看器
|
||||
@ -381,8 +387,8 @@ class SamplingViewerDialog(QDialog):
|
||||
self._fig = Figure(figsize=(6, 5))
|
||||
self._canvas = FigureCanvasQTAgg(self._fig)
|
||||
self._ax_scatter = self._fig.add_subplot(111)
|
||||
self._ax_scatter.set_xlabel("pixel_x")
|
||||
self._ax_scatter.set_ylabel("pixel_y")
|
||||
self._ax_scatter.set_xlabel("像素 X")
|
||||
self._ax_scatter.set_ylabel("像素 Y")
|
||||
self._ax_scatter.set_title("采样点分布（点击查看详情）")
|
||||
self._ax_scatter.invert_yaxis()
|
||||
self._fig.tight_layout()
|
||||
@ -392,18 +398,20 @@ class SamplingViewerDialog(QDialog):
|
||||
# --- 右侧：信息面板 + 光谱子图 ---
|
||||
right_widget = QWidget()
|
||||
right_layout = QVBoxLayout(right_widget)
|
||||
right_layout.setContentsMargins(0, 0, 0, 0)
|
||||
|
||||
# 坐标信息面板（多行中文清晰显示）
|
||||
self._info_label = QLabel("点击左侧散点图选择采样点")
|
||||
self._info_label.setStyleSheet(
|
||||
"QLabel { background-color: #f0f0f0; padding: 6px; "
|
||||
"border: 1px solid #ccc; font-size: 13px; }"
|
||||
"QLabel { background-color: #f0f0f0; padding: 8px; "
|
||||
"border: 1px solid #ccc; border-radius: 4px; font-size: 13px; }"
|
||||
)
|
||||
right_layout.addWidget(self._info_label)
|
||||
|
||||
# 采样点列表迷你表格
|
||||
self._point_table = QTableWidget()
|
||||
self._point_table.setColumnCount(3)
|
||||
self._point_table.setHorizontalHeaderLabels(["pixel_x", "pixel_y", "index"])
|
||||
self._point_table.setHorizontalHeaderLabels(["像素 X", "像素 Y", "序号"])
|
||||
self._point_table.setMaximumHeight(120)
|
||||
self._point_table.setEditTriggers(QTableWidget.NoEditTriggers)
|
||||
self._point_table.setSelectionBehavior(QTableWidget.SelectRows)
|
||||
@ -413,8 +421,8 @@ class SamplingViewerDialog(QDialog):
|
||||
# 光谱曲线子图
|
||||
self._fig_right = Figure(figsize=(5, 3))
|
||||
self._ax_spectrum = self._fig_right.add_subplot(111)
|
||||
self._ax_spectrum.set_xlabel("Band Index")
|
||||
self._ax_spectrum.set_ylabel("Reflectance")
|
||||
self._ax_spectrum.set_xlabel("波段序号")
|
||||
self._ax_spectrum.set_ylabel("反射率")
|
||||
self._ax_spectrum.set_title("光谱曲线")
|
||||
self._fig_right.tight_layout()
|
||||
|
||||
@ -440,8 +448,8 @@ class SamplingViewerDialog(QDialog):
|
||||
def _draw_scatter(self):
|
||||
"""绘制散点图"""
|
||||
self._ax_scatter.clear()
|
||||
self._ax_scatter.set_xlabel("pixel_x")
|
||||
self._ax_scatter.set_ylabel("pixel_y")
|
||||
self._ax_scatter.set_xlabel("像素 X")
|
||||
self._ax_scatter.set_ylabel("像素 Y")
|
||||
self._ax_scatter.set_title("采样点分布（点击查看详情）")
|
||||
self._ax_scatter.invert_yaxis()
|
||||
|
||||
@ -497,14 +505,14 @@ class SamplingViewerDialog(QDialog):
|
||||
|
||||
self._info_label.setText(
|
||||
f"<b>选中的采样点 #{nearest_idx}</b><br>"
|
||||
f"pixel_x = {pixel_x} pixel_y = {pixel_y}<br>"
|
||||
f"x_coord = {x_coord} y_coord = {y_coord}"
|
||||
f"图像像素坐标: X = {pixel_x}, Y = {pixel_y}<br>"
|
||||
f"地理真实坐标: 经度(X) = {x_coord}, 纬度(Y) = {y_coord}"
|
||||
)
|
||||
|
||||
# 高亮散点图
|
||||
self._ax_scatter.clear()
|
||||
self._ax_scatter.set_xlabel("pixel_x")
|
||||
self._ax_scatter.set_ylabel("pixel_y")
|
||||
self._ax_scatter.set_xlabel("像素 X")
|
||||
self._ax_scatter.set_ylabel("像素 Y")
|
||||
self._ax_scatter.set_title(f"采样点分布（共 {len(self.df)} 个）")
|
||||
self._ax_scatter.invert_yaxis()
|
||||
self._ax_scatter.scatter(
|
||||
@ -523,8 +531,8 @@ class SamplingViewerDialog(QDialog):
|
||||
def _draw_spectrum(self, row: pd.Series):
|
||||
"""从一行数据中提取纯波段数值并绘图"""
|
||||
self._ax_spectrum.clear()
|
||||
self._ax_spectrum.set_xlabel("Band Index")
|
||||
self._ax_spectrum.set_ylabel("Reflectance")
|
||||
self._ax_spectrum.set_xlabel("波段序号")
|
||||
self._ax_spectrum.set_ylabel("反射率")
|
||||
self._ax_spectrum.set_title("光谱曲线")
|
||||
|
||||
exclude_patterns = (
|
||||
|
||||
252
src/gui/panels/step10_panel.py
Normal file
252
src/gui/panels/step10_panel.py
Normal file
@ -0,0 +1,252 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step10 面板 - 采样点生成
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout,
|
||||
QPushButton, QCheckBox, QSpinBox, QMessageBox,
|
||||
)
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.dialogs import SamplingViewerDialog
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step10Panel(QWidget):
|
||||
"""步骤10：采样点生成"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 去耀斑影像文件（用于独立运行）
|
||||
self.deglint_img_file = FileSelectWidget(
|
||||
"去耀斑影像:",
|
||||
"Image Files (*.bsq *.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.deglint_img_file)
|
||||
|
||||
# 水域掩膜文件（可选，用于独立运行）
|
||||
self.water_mask_file = FileSelectWidget(
|
||||
"水域掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
self.water_mask_file.label.setText("水域掩膜:")
|
||||
layout.addWidget(self.water_mask_file)
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("采样参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.interval = QSpinBox()
|
||||
self.interval.setRange(10, 500)
|
||||
self.interval.setValue(50)
|
||||
params_layout.addRow("采样点间隔(像素):", self.interval)
|
||||
|
||||
self.sample_radius = QSpinBox()
|
||||
self.sample_radius.setRange(1, 50)
|
||||
self.sample_radius.setValue(5)
|
||||
params_layout.addRow("采样半径(像素):", self.sample_radius)
|
||||
|
||||
self.chunk_size = QSpinBox()
|
||||
self.chunk_size.setRange(100, 10000)
|
||||
self.chunk_size.setValue(1000)
|
||||
params_layout.addRow("处理块大小:", self.chunk_size)
|
||||
|
||||
self.use_adaptive_sampling = QCheckBox("启用自适应采样")
|
||||
self.use_adaptive_sampling.setChecked(True)
|
||||
params_layout.addRow("采样模式:", self.use_adaptive_sampling)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 输出文件路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出采样点:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.output_file.line_edit.setPlaceholderText("sampling_points.csv")
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 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_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
# 交互式预览按钮
|
||||
self.preview_btn = QPushButton("📊 交互式预览采样点与光谱")
|
||||
self.preview_btn.setEnabled(False)
|
||||
self.preview_btn.clicked.connect(self._open_sampling_viewer)
|
||||
layout.addWidget(self.preview_btn)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
|
||||
# 监听输出路径变化，实时更新预览按钮状态
|
||||
self.output_file.line_edit.textChanged.connect(self._on_output_changed)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
config = {
|
||||
'interval': self.interval.value(),
|
||||
'sample_radius': self.sample_radius.value(),
|
||||
'chunk_size': self.chunk_size.value(),
|
||||
'use_adaptive_sampling': self.use_adaptive_sampling.isChecked(),
|
||||
}
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if deglint_img_path:
|
||||
config['deglint_img_path'] = deglint_img_path
|
||||
water_mask_path = self.water_mask_file.get_path()
|
||||
if water_mask_path:
|
||||
config['water_mask_path'] = water_mask_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'interval' in config:
|
||||
self.interval.setValue(config['interval'])
|
||||
if 'sample_radius' in config:
|
||||
self.sample_radius.setValue(config['sample_radius'])
|
||||
if 'chunk_size' in config:
|
||||
self.chunk_size.setValue(config['chunk_size'])
|
||||
if 'use_adaptive_sampling' in config:
|
||||
self.use_adaptive_sampling.setChecked(config['use_adaptive_sampling'])
|
||||
if 'deglint_img_path' in config:
|
||||
self.deglint_img_file.set_path(config['deglint_img_path'])
|
||||
if 'water_mask_path' in config:
|
||||
self.water_mask_file.set_path(config['water_mask_path'])
|
||||
if 'glint_mask_path' in config:
|
||||
self.glint_mask_file.set_path(config['glint_mask_path'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充去耀斑影像和掩膜路径
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（用于从 step_outputs 获取绝对路径）
|
||||
"""
|
||||
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()
|
||||
|
||||
# 1. 填充去耀斑影像路径（优先从 pipeline.step_outputs 获取绝对路径）
|
||||
deglint_path = None
|
||||
if pipeline and hasattr(pipeline, 'step_outputs'):
|
||||
step3_outputs = getattr(pipeline, 'step_outputs', {}).get('step3', {})
|
||||
deglint_path = (
|
||||
step3_outputs.get('deglint_image')
|
||||
or step3_outputs.get('output_path')
|
||||
or step3_outputs.get('output_file')
|
||||
or step3_outputs.get('deglint_img_path')
|
||||
)
|
||||
# 回退：从 step3 面板 widget 直接读取（可能是相对路径）
|
||||
if not deglint_path and hasattr(main_window, 'step3_panel'):
|
||||
deglint_path = main_window.step3_panel.output_file.get_path()
|
||||
|
||||
if deglint_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(deglint_path):
|
||||
deglint_path = os.path.join(self.work_dir or '', deglint_path).replace('\\', '/')
|
||||
self.deglint_img_file.set_path(deglint_path)
|
||||
|
||||
# 2. 填充水域掩膜路径（优先级：pipeline.step_outputs > step1_panel > 1_water_mask > input-test）
|
||||
water_mask_path = None
|
||||
if pipeline and hasattr(pipeline, 'step_outputs'):
|
||||
step1_outputs = getattr(pipeline, 'step_outputs', {}).get('step1', {})
|
||||
water_mask_path = (
|
||||
step1_outputs.get('water_mask')
|
||||
or step1_outputs.get('output_path')
|
||||
or step1_outputs.get('output_file')
|
||||
)
|
||||
# 回退：从 step1 面板 widget 直接读取
|
||||
if not water_mask_path and hasattr(main_window, 'step1_panel'):
|
||||
water_mask_path = main_window.step1_panel.output_file.get_path()
|
||||
# 备选：扫描 1_water_mask 目录下的 .dat 文件
|
||||
if not water_mask_path and self.work_dir:
|
||||
mask_dir = os.path.join(self.work_dir, "1_water_mask")
|
||||
if os.path.isdir(mask_dir):
|
||||
dat_files = [f for f in os.listdir(mask_dir) if f.lower().endswith('.dat')]
|
||||
if dat_files:
|
||||
water_mask_path = os.path.join(mask_dir, dat_files[0]).replace('\\', '/')
|
||||
# 备选：扫描 input-test 目录（优先匹配 water_mask_from_shp.dat）
|
||||
if not water_mask_path and self.work_dir:
|
||||
input_test_dir = os.path.join(self.work_dir, "input-test")
|
||||
if os.path.isdir(input_test_dir):
|
||||
dat_files = [f for f in os.listdir(input_test_dir) if f.lower().endswith('.dat')]
|
||||
# 优先匹配 water_mask_from_shp.dat
|
||||
for f in dat_files:
|
||||
if 'water_mask_from_shp' in f.lower():
|
||||
water_mask_path = os.path.join(input_test_dir, f).replace('\\', '/')
|
||||
break
|
||||
# 否则取第一个 .dat 文件
|
||||
if not water_mask_path and dat_files:
|
||||
water_mask_path = os.path.join(input_test_dir, dat_files[0]).replace('\\', '/')
|
||||
|
||||
if water_mask_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(water_mask_path):
|
||||
water_mask_path = os.path.join(self.work_dir or '', water_mask_path).replace('\\', '/')
|
||||
self.water_mask_file.set_path(water_mask_path)
|
||||
|
||||
# 3. 自动填充输出路径（绝对路径）
|
||||
if self.work_dir:
|
||||
output_path = os.path.join(self.work_dir, "10_sampling", "sampling_spectra.csv")
|
||||
os.makedirs(os.path.dirname(output_path), exist_ok=True)
|
||||
self.output_file.set_path(output_path.replace('\\', '/'))
|
||||
|
||||
# 4. 同步更新预览按钮状态（路径可能已自动填充）
|
||||
self._check_csv_exists()
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤10"""
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if not deglint_img_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择去耀斑影像文件！")
|
||||
return
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step10': self.get_config()}
|
||||
main_window.run_single_step('step10', config)
|
||||
|
||||
def _check_csv_exists(self):
|
||||
"""检查 output csv 是否存在，驱动预览按钮启停"""
|
||||
csv_path = self.output_file.get_path()
|
||||
enabled = bool(csv_path and os.path.isabs(csv_path) and os.path.exists(csv_path))
|
||||
self.preview_btn.setEnabled(enabled)
|
||||
return enabled
|
||||
|
||||
def _on_output_changed(self, _text=None):
|
||||
"""输出路径输入框内容变化时调用（_text 为 line_edit.textChanged 信号参数）"""
|
||||
self._check_csv_exists()
|
||||
|
||||
def _open_sampling_viewer(self):
|
||||
"""打开交互式采样点查看器弹窗"""
|
||||
csv_path = self.output_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
QMessageBox.warning(
|
||||
self, "文件不存在",
|
||||
f"采样点 CSV 文件不存在：{csv_path}\n请先运行步骤10生成数据。"
|
||||
)
|
||||
return
|
||||
dialog = SamplingViewerDialog(csv_path, self)
|
||||
dialog.exec_()
|
||||
# 弹窗关闭后再次检查状态（可能文件被覆盖等）
|
||||
self._check_csv_exists()
|
||||
462
src/gui/panels/step11_ml_panel.py
Normal file
462
src/gui/panels/step11_ml_panel.py
Normal file
@ -0,0 +1,462 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step8 面板 - 机器学习预测
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout,
|
||||
QPushButton, QCheckBox, QComboBox, QLineEdit, QMessageBox,
|
||||
QFileDialog, QRadioButton, QListWidget, QAbstractItemView, QHBoxLayout,
|
||||
QListWidgetItem,
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step11MlPanel(QWidget):
|
||||
"""步骤11：机器学习预测"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.external_models_dict = {} # {subdir_name: model_obj, ...}
|
||||
self.external_model_dir = "" # 母文件夹路径（隐藏）
|
||||
self.init_ui()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# -------- 模型来源选择（单选按钮组） --------
|
||||
source_group = QGroupBox("模型来源")
|
||||
source_layout = QVBoxLayout()
|
||||
|
||||
self.use_trained_model = QRadioButton("使用当前训练流程的模型")
|
||||
self.use_external_model = QRadioButton("导入本地预训练模型 (.joblib)")
|
||||
self.use_trained_model.setChecked(True)
|
||||
source_layout.addWidget(self.use_trained_model)
|
||||
source_layout.addWidget(self.use_external_model)
|
||||
|
||||
self.use_trained_model.toggled.connect(self._on_model_source_changed)
|
||||
self.use_external_model.toggled.connect(self._on_model_source_changed)
|
||||
|
||||
source_group.setStyleSheet("""
|
||||
QRadioButton {
|
||||
font-size: 13px;
|
||||
spacing: 8px;
|
||||
}
|
||||
QRadioButton::indicator {
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
border-radius: 9px;
|
||||
border: 2px solid #A0A0A0;
|
||||
background-color: #FFFFFF;
|
||||
}
|
||||
QRadioButton::indicator:hover {
|
||||
border: 2px solid #0078D7;
|
||||
}
|
||||
QRadioButton::indicator:checked {
|
||||
background-color: #0078D7;
|
||||
border: 2px solid #0078D7;
|
||||
}
|
||||
""")
|
||||
|
||||
source_group.setLayout(source_layout)
|
||||
layout.addWidget(source_group)
|
||||
|
||||
# -------- 外部模型文件选择（条件显示） --------
|
||||
self.external_model_widget = FileSelectWidget(
|
||||
"模型母文件夹:",
|
||||
"Directories"
|
||||
)
|
||||
self.external_model_widget.browse_btn.clicked.disconnect()
|
||||
self.external_model_widget.browse_btn.clicked.connect(self._scan_external_model_dir)
|
||||
self.external_model_widget.setVisible(False)
|
||||
layout.addWidget(self.external_model_widget)
|
||||
|
||||
# -------- 已扫描模型列表（条件显示） --------
|
||||
self.model_list_group = QGroupBox("选择参与预测的模型")
|
||||
self.model_list_group.setVisible(False)
|
||||
model_list_layout = QVBoxLayout()
|
||||
|
||||
self.model_list = QListWidget()
|
||||
self.model_list.setMaximumHeight(130)
|
||||
self.model_list.setSelectionMode(QAbstractItemView.NoSelection)
|
||||
self.model_list.setStyleSheet("""
|
||||
QListWidget {
|
||||
border: 1px solid #C0C0C0;
|
||||
border-radius: 4px;
|
||||
background-color: #FFFFFF;
|
||||
font-size: 12px;
|
||||
}
|
||||
QListWidget::item {
|
||||
padding: 4px 6px;
|
||||
border-bottom: 1px solid #F0F0F0;
|
||||
}
|
||||
QListWidget::item:selected {
|
||||
background-color: transparent;
|
||||
}
|
||||
""")
|
||||
model_list_layout.addWidget(self.model_list)
|
||||
|
||||
btn_row = QHBoxLayout()
|
||||
self.btn_select_all = QPushButton("全选")
|
||||
self.btn_select_all.setMaximumWidth(80)
|
||||
self.btn_select_all.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
|
||||
self.btn_select_all.clicked.connect(self._select_all_models)
|
||||
|
||||
self.btn_select_none = QPushButton("全不选")
|
||||
self.btn_select_none.setMaximumWidth(80)
|
||||
self.btn_select_none.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
|
||||
self.btn_select_none.clicked.connect(self._select_none_models)
|
||||
|
||||
btn_row.addWidget(self.btn_select_all)
|
||||
btn_row.addWidget(self.btn_select_none)
|
||||
btn_row.addStretch()
|
||||
model_list_layout.addLayout(btn_row)
|
||||
|
||||
self.model_list_group.setLayout(model_list_layout)
|
||||
layout.addWidget(self.model_list_group)
|
||||
|
||||
# -------- 采样光谱CSV文件（用于独立运行）--------
|
||||
self.sampling_csv_file = FileSelectWidget(
|
||||
"采样光谱CSV:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.sampling_csv_file)
|
||||
|
||||
# 模型目录（用于独立运行）
|
||||
self.models_dir_file = FileSelectWidget(
|
||||
"模型目录:",
|
||||
"Directories;;All Files (*.*)"
|
||||
)
|
||||
self.models_dir_file.label.setText("模型目录:")
|
||||
self.models_dir_file.browse_btn.clicked.disconnect()
|
||||
self.models_dir_file.browse_btn.clicked.connect(self.browse_models_dir)
|
||||
layout.addWidget(self.models_dir_file)
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("预测参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.metric = QComboBox()
|
||||
self.metric.addItems(['test_r2', 'test_rmse', 'test_mae'])
|
||||
params_layout.addRow("模型选择指标:", self.metric)
|
||||
|
||||
self.prediction_column = QLineEdit()
|
||||
self.prediction_column.setText("prediction")
|
||||
params_layout.addRow("预测列名:", self.prediction_column)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 输出路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出路径:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 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_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
|
||||
def _on_model_source_changed(self, checked: bool):
|
||||
"""单选按钮切换：控制外部模型文件选择控件的显示/隐藏"""
|
||||
if not checked:
|
||||
return
|
||||
is_external = self.use_external_model.isChecked()
|
||||
self.external_model_widget.setVisible(is_external)
|
||||
self.model_list_group.setVisible(is_external)
|
||||
if not is_external:
|
||||
self.external_models_dict = {}
|
||||
self.external_model_dir = ""
|
||||
self._clear_model_list()
|
||||
|
||||
def _scan_external_model_dir(self):
|
||||
"""浏览模型母文件夹，自动扫描子目录中的 .joblib 文件"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "7_Supervised_Model_Training")
|
||||
dir_path = QFileDialog.getExistingDirectory(
|
||||
self,
|
||||
"选择模型母文件夹",
|
||||
default,
|
||||
)
|
||||
if not dir_path:
|
||||
return
|
||||
|
||||
self.external_model_dir = dir_path
|
||||
models_found = {}
|
||||
errors = []
|
||||
|
||||
try:
|
||||
import joblib
|
||||
|
||||
for subentry in os.scandir(dir_path):
|
||||
if not subentry.is_dir():
|
||||
continue
|
||||
subdir_name = subentry.name
|
||||
joblib_files = [
|
||||
f for f in os.scandir(subentry.path)
|
||||
if f.is_file() and f.name.lower().endswith(".joblib")
|
||||
]
|
||||
if not joblib_files:
|
||||
continue
|
||||
# 每个子目录只取第一个 .joblib 文件（与 batch 逻辑一致）
|
||||
joblib_path = joblib_files[0].path
|
||||
try:
|
||||
loaded = joblib.load(joblib_path)
|
||||
if isinstance(loaded, dict) and "model" in loaded:
|
||||
model_obj = loaded["model"]
|
||||
elif hasattr(loaded, "predict"):
|
||||
model_obj = loaded
|
||||
else:
|
||||
errors.append(f"{subdir_name}: 无法识别的格式 {type(loaded).__name__}")
|
||||
continue
|
||||
models_found[subdir_name] = model_obj
|
||||
except Exception as e:
|
||||
errors.append(f"{subdir_name}: {type(e).__name__}: {e}")
|
||||
|
||||
except Exception as e:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"扫描失败",
|
||||
f"遍历模型目录时发生错误：\n{type(e).__name__}: {e}",
|
||||
)
|
||||
return
|
||||
|
||||
if not models_found:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"未找到模型",
|
||||
f"在「{dir_path}」的子目录中未发现任何 .joblib 文件。\n"
|
||||
"请确认每个水质参数对应一个子文件夹，内含 .joblib 模型文件。",
|
||||
)
|
||||
self.external_model_widget.set_path("")
|
||||
self.external_models_dict = {}
|
||||
self._clear_model_list()
|
||||
return
|
||||
|
||||
self.external_models_dict = models_found
|
||||
self._populate_model_list(models_found)
|
||||
names = sorted(models_found.keys())
|
||||
display = f"已识别到 {len(names)} 个模型: {', '.join(names)}"
|
||||
self.external_model_widget.set_path(display)
|
||||
self.external_model_widget.line_edit.setStyleSheet("color: #0078D7; font-weight: bold;")
|
||||
|
||||
err_lines = "\n".join(errors) if errors else "无"
|
||||
QMessageBox.information(
|
||||
self,
|
||||
"模型扫描完成",
|
||||
f"成功加载 {len(models_found)} 个模型：\n{display}\n\n"
|
||||
f"加载失败 {len(errors)} 个：\n{err_lines}",
|
||||
)
|
||||
|
||||
def _populate_model_list(self, models_dict):
|
||||
"""将扫描到的模型填充到 QListWidget，每个条目可勾选，默认全选"""
|
||||
self.model_list.clear()
|
||||
for name in sorted(models_dict.keys()):
|
||||
item = QListWidgetItem(name)
|
||||
item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
|
||||
item.setCheckState(Qt.Checked)
|
||||
self.model_list.addItem(item)
|
||||
|
||||
def _clear_model_list(self):
|
||||
"""清空模型列表"""
|
||||
self.model_list.clear()
|
||||
|
||||
def _select_all_models(self):
|
||||
"""全选：设置所有条目为 Checked"""
|
||||
for i in range(self.model_list.count()):
|
||||
self.model_list.item(i).setCheckState(Qt.Checked)
|
||||
|
||||
def _select_none_models(self):
|
||||
"""全不选：设置所有条目为 Unchecked"""
|
||||
for i in range(self.model_list.count()):
|
||||
self.model_list.item(i).setCheckState(Qt.Unchecked)
|
||||
|
||||
def _get_checked_models_dict(self):
|
||||
"""从列表中提取用户勾选的模型，组装成字典返回"""
|
||||
result = {}
|
||||
for i in range(self.model_list.count()):
|
||||
item = self.model_list.item(i)
|
||||
if item.checkState() == Qt.Checked:
|
||||
name = item.text()
|
||||
if name in self.external_models_dict:
|
||||
result[name] = self.external_models_dict[name]
|
||||
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
|
||||
|
||||
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 界面读取全湖采样点 CSV 路径
|
||||
if main_window and hasattr(main_window, 'step10_panel'):
|
||||
step7_widget = getattr(main_window.step10_panel, 'output_file', None)
|
||||
step7_output_path = ""
|
||||
if hasattr(step7_widget, 'get_path'):
|
||||
step7_output_path = step7_widget.get_path() or ""
|
||||
elif hasattr(step7_widget, 'text'):
|
||||
step7_output_path = step7_widget.text() or ""
|
||||
|
||||
if step7_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step7_output_path):
|
||||
step7_output_path = os.path.join(self.work_dir or '', step7_output_path).replace('\\', '/')
|
||||
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 Step6 界面读取监督模型目录
|
||||
if main_window and hasattr(main_window, 'step7_panel'):
|
||||
step6_widget = getattr(main_window.step7_panel, 'output_dir', None)
|
||||
step6_models_dir = ""
|
||||
if hasattr(step6_widget, 'get_path'):
|
||||
step6_models_dir = step6_widget.get_path() or ""
|
||||
elif hasattr(step6_widget, 'text'):
|
||||
step6_models_dir = step6_widget.text() or ""
|
||||
|
||||
if step6_models_dir:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step6_models_dir):
|
||||
step6_models_dir = os.path.join(self.work_dir or '', step6_models_dir).replace('\\', '/')
|
||||
existing_models = self.models_dir_file.get_path()
|
||||
if not existing_models or not existing_models.strip():
|
||||
self.models_dir_file.set_path(step6_models_dir)
|
||||
|
||||
# 3. 自动填充输出路径（机器学习预测目录）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Machine_Learning_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()
|
||||
|
||||
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_models_dir(self):
|
||||
"""浏览模型目录"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "7_Supervised_Model_Training")
|
||||
dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", default)
|
||||
if dir_path:
|
||||
self.models_dir_file.set_path(dir_path)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
config = {
|
||||
'metric': self.metric.currentText(),
|
||||
'prediction_column': self.prediction_column.text(),
|
||||
}
|
||||
sampling_csv_path = self.sampling_csv_file.get_path()
|
||||
if sampling_csv_path:
|
||||
config['sampling_csv_path'] = sampling_csv_path
|
||||
models_dir = self.models_dir_file.get_path()
|
||||
if models_dir:
|
||||
config['models_dir'] = models_dir
|
||||
output_path = self.output_file.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'metric' in config:
|
||||
idx = self.metric.findText(config['metric'])
|
||||
if idx >= 0:
|
||||
self.metric.setCurrentIndex(idx)
|
||||
if 'prediction_column' in config:
|
||||
self.prediction_column.setText(config['prediction_column'])
|
||||
if 'sampling_csv_path' in config:
|
||||
self.sampling_csv_file.set_path(config['sampling_csv_path'])
|
||||
if 'models_dir' in config:
|
||||
self.models_dir_file.set_path(config['models_dir'])
|
||||
if 'output_path' in config:
|
||||
self.output_file.set_path(config['output_path'])
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤8"""
|
||||
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
|
||||
|
||||
# 外部模型优先：用户选择了"导入本地预训练模型"
|
||||
if self.use_external_model.isChecked():
|
||||
if not self.external_models_dict:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"模型未加载",
|
||||
"请先点击「浏览...」按钮选择模型母文件夹！",
|
||||
)
|
||||
return
|
||||
# 只传递用户勾选的模型
|
||||
checked_dict = self._get_checked_models_dict()
|
||||
if not checked_dict:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"未选择模型",
|
||||
"请至少勾选一个模型参与预测！",
|
||||
)
|
||||
return
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {
|
||||
'step11_ml': self.get_config(),
|
||||
'_external_models_dict': checked_dict,
|
||||
'_external_model_dir': self.external_model_dir,
|
||||
}
|
||||
main_window.run_single_step('step11_ml', config)
|
||||
return
|
||||
|
||||
# 默认流程：使用模型目录
|
||||
models_dir = self.models_dir_file.get_path()
|
||||
if not models_dir:
|
||||
QMessageBox.warning(self, "输入错误", "请选择模型目录！")
|
||||
return
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step11_ml': self.get_config()}
|
||||
main_window.run_single_step('step11_ml', config)
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step8_5 面板 - 非经验模型预测
|
||||
Step11 面板 - 非经验模型预测
|
||||
"""
|
||||
|
||||
import os
|
||||
@ -17,8 +17,8 @@ from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step8_5Panel(QWidget):
|
||||
"""步骤8.5：非经验模型预测"""
|
||||
class Step11Panel(QWidget):
|
||||
"""步骤11：非经验模型预测"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -118,22 +118,22 @@ class Step8_5Panel(QWidget):
|
||||
if not existing or not existing.strip():
|
||||
self.sampling_csv_file.set_path(step7_output_path)
|
||||
|
||||
# 2. 尝试从 Step6.5 界面读取回归模型目录
|
||||
if main_window and hasattr(main_window, 'step6_5_panel'):
|
||||
step6_5_widget = getattr(main_window.step6_5_panel, 'output_dir', None)
|
||||
step6_5_models_dir = ""
|
||||
if hasattr(step6_5_widget, 'get_path'):
|
||||
step6_5_models_dir = step6_5_widget.get_path() or ""
|
||||
elif hasattr(step6_5_widget, 'text'):
|
||||
step6_5_models_dir = step6_5_widget.text() or ""
|
||||
# 2. 尝试从 Step8_Non_Empirical 界面读取回归模型目录
|
||||
if main_window and hasattr(main_window, 'step8_non_empirical_panel'):
|
||||
step8_non_empirical_widget = getattr(main_window.step8_non_empirical_panel, 'output_dir', None)
|
||||
step8_non_empirical_models_dir = ""
|
||||
if hasattr(step8_non_empirical_widget, 'get_path'):
|
||||
step8_non_empirical_models_dir = step8_non_empirical_widget.get_path() or ""
|
||||
elif hasattr(step8_non_empirical_widget, 'text'):
|
||||
step8_non_empirical_models_dir = step8_non_empirical_widget.text() or ""
|
||||
|
||||
if step6_5_models_dir:
|
||||
if step8_non_empirical_models_dir:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step6_5_models_dir):
|
||||
step6_5_models_dir = os.path.join(self.work_dir or '', step6_5_models_dir).replace('\\', '/')
|
||||
if not os.path.isabs(step8_non_empirical_models_dir):
|
||||
step8_non_empirical_models_dir = os.path.join(self.work_dir or '', step8_non_empirical_models_dir).replace('\\', '/')
|
||||
existing_models = self.models_dir_file.get_path()
|
||||
if not existing_models or not existing_models.strip():
|
||||
self.models_dir_file.set_path(step6_5_models_dir)
|
||||
self.models_dir_file.set_path(step8_non_empirical_models_dir)
|
||||
|
||||
# 3. 自动填充输出路径（非经验模型预测目录）
|
||||
if self.work_dir:
|
||||
@ -208,7 +208,7 @@ class Step8_5Panel(QWidget):
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤8.5"""
|
||||
"""独立运行步骤11"""
|
||||
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！")
|
||||
@ -221,6 +221,6 @@ class Step8_5Panel(QWidget):
|
||||
parent = parent.parent()
|
||||
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step8_5', {'step8_5': config})
|
||||
parent.run_single_step('step11', {'step11': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step8_75 面板 - 自定义回归预测
|
||||
Step12 面板 - 自定义回归预测
|
||||
"""
|
||||
|
||||
import os
|
||||
@ -15,8 +15,8 @@ from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step8_75Panel(QWidget):
|
||||
"""步骤8.75：自定义回归预测"""
|
||||
class Step12Panel(QWidget):
|
||||
"""步骤12：自定义回归预测"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -111,25 +111,25 @@ class Step8_75Panel(QWidget):
|
||||
if not existing or not existing.strip():
|
||||
self.sampling_csv_file.set_path(step7_output_path)
|
||||
|
||||
# 2. 尝试从 Step6.75 界面读取自定义回归模型目录
|
||||
if main_window and hasattr(main_window, 'step6_75_panel'):
|
||||
step6_75_widget = getattr(main_window.step6_75_panel, 'output_dir', None)
|
||||
step6_75_models_dir = ""
|
||||
if hasattr(step6_75_widget, 'get_path'):
|
||||
step6_75_models_dir = step6_75_widget.get_path() or ""
|
||||
elif hasattr(step6_75_widget, 'text'):
|
||||
step6_75_models_dir = step6_75_widget.text() or ""
|
||||
step6_75_models_dir = step6_75_models_dir.strip()
|
||||
# 2. 尝试从 Step9 界面读取自定义回归模型目录
|
||||
if main_window and hasattr(main_window, 'step12_panel'):
|
||||
step9_widget = getattr(main_window.step9_panel, 'output_dir', None)
|
||||
step9_models_dir = ""
|
||||
if hasattr(step9_widget, 'get_path'):
|
||||
step9_models_dir = step9_widget.get_path() or ""
|
||||
elif hasattr(step9_widget, 'text'):
|
||||
step9_models_dir = step9_widget.text() or ""
|
||||
step9_models_dir = step9_models_dir.strip()
|
||||
|
||||
if step6_75_models_dir:
|
||||
if step9_models_dir:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step6_75_models_dir):
|
||||
step6_75_models_dir = os.path.join(self.work_dir or '', step6_75_models_dir).replace('\\', '/')
|
||||
if not os.path.isabs(step9_models_dir):
|
||||
step9_models_dir = os.path.join(self.work_dir or '', step9_models_dir).replace('\\', '/')
|
||||
existing_models = self.regression_models_dir.get_path()
|
||||
if not existing_models or not existing_models.strip():
|
||||
self.regression_models_dir.set_path(step6_75_models_dir)
|
||||
self.regression_models_dir.set_path(step9_models_dir)
|
||||
|
||||
# 3. 自动填充回归模型目录（如果 step6_75 未提供）
|
||||
# 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:
|
||||
@ -208,7 +208,7 @@ class Step8_75Panel(QWidget):
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤8.75"""
|
||||
"""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！")
|
||||
@ -225,6 +225,6 @@ class Step8_75Panel(QWidget):
|
||||
parent = parent.parent()
|
||||
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step8_75', {'step8_75': config})
|
||||
parent.run_single_step('step12', {'step12': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
533
src/gui/panels/step14_panel.py
Normal file
533
src/gui/panels/step14_panel.py
Normal file
@ -0,0 +1,533 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step14 面板 - 分布图生成
|
||||
"""
|
||||
|
||||
import os
|
||||
import traceback
|
||||
from pathlib import Path
|
||||
from typing import List, Optional
|
||||
|
||||
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,
|
||||
)
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
# Pipeline 可用性（与 core/worker_thread.py 保持一致）
|
||||
try:
|
||||
from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
|
||||
PIPELINE_AVAILABLE = True
|
||||
except ImportError:
|
||||
PIPELINE_AVAILABLE = False
|
||||
|
||||
|
||||
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)
|
||||
|
||||
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.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
|
||||
pipeline = WaterQualityInversionPipeline(work_dir=self.work_dir)
|
||||
n = len(self.csv_paths)
|
||||
for i, csv_p in enumerate(self.csv_paths):
|
||||
self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
|
||||
kw = {**self.step14_kwargs, "prediction_csv_path": csv_p, "skip_dependency_check": True}
|
||||
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
|
||||
pipeline.step9_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 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）。"
|
||||
"完整流程中预测 CSV 由步骤11、12、13 自动传入，无需在此选择。"
|
||||
)
|
||||
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)
|
||||
|
||||
# ---------- 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)
|
||||
|
||||
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)
|
||||
|
||||
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：根据单选框状态动态显示/隐藏对应的输入组件。"""
|
||||
folder_mode = self.mode_folder_rb.isChecked()
|
||||
# 单个 CSV 模式：显示单文件选择，隐藏文件夹选择
|
||||
self.prediction_csv_file.setVisible(not folder_mode)
|
||||
# 文件夹批量模式：显示文件夹选择 + 递归选项，隐藏单文件选择
|
||||
self._folder_row_widget.setVisible(folder_mode)
|
||||
self.recursive_csv_cb.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 = os.path.join(default, "11_12_13_predictions")
|
||||
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 _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()
|
||||
config = {
|
||||
'step14_batch_mode': 'folder' if folder_mode else 'single',
|
||||
'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),
|
||||
'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)
|
||||
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 '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. 尝试从 Step8 界面读取机器学习预测输出目录（最优先）
|
||||
pred_dir = None
|
||||
if hasattr(main_window, 'step11_prediction_panel'):
|
||||
step8_widget = getattr(main_window.step11_prediction_panel, 'output_file', None)
|
||||
step8_output = ""
|
||||
if hasattr(step8_widget, 'get_path'):
|
||||
step8_output = step8_widget.get_path() or ""
|
||||
elif hasattr(step8_widget, 'text'):
|
||||
step8_output = step8_widget.text() or ""
|
||||
|
||||
if step8_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_output):
|
||||
step8_output = os.path.join(self.work_dir or '', step8_output).replace('\\', '/')
|
||||
# 提取父目录后追加 Machine_Learning_Prediction（最底层真实子目录）
|
||||
base_pred_dir = str(Path(step8_output).parent)
|
||||
ml_pred_dir = Path(base_pred_dir) / "Machine_Learning_Prediction"
|
||||
pred_dir = str(ml_pred_dir) if ml_pred_dir.exists() else base_pred_dir
|
||||
|
||||
# 2. 备选：从 Step11 界面读取非经验预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step11_panel'):
|
||||
step8_5_widget = getattr(main_window.step11_panel, 'output_file', None)
|
||||
step8_5_output = ""
|
||||
if hasattr(step8_5_widget, 'get_path'):
|
||||
step8_5_output = step8_5_widget.get_path() or ""
|
||||
elif hasattr(step8_5_widget, 'text'):
|
||||
step8_5_output = step8_5_widget.text() or ""
|
||||
|
||||
if step8_5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_5_output):
|
||||
step8_5_output = os.path.join(self.work_dir or '', step8_5_output).replace('\\', '/')
|
||||
pred_dir = str(Path(step8_5_output).parent)
|
||||
|
||||
# 3. 备选：从 Step12 界面读取自定义回归预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step12_panel'):
|
||||
step8_75_widget = getattr(main_window.step12_panel, 'output_dir_widget', None)
|
||||
step8_75_output = ""
|
||||
if hasattr(step8_75_widget, 'get_path'):
|
||||
step8_75_output = step8_75_widget.get_path() or ""
|
||||
elif hasattr(step8_75_widget, 'text'):
|
||||
step8_75_output = step8_75_widget.text() or ""
|
||||
|
||||
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 = os.path.join(self.work_dir, "14_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:
|
||||
# 未找到 .shp 时清空并提示用户手动选择矢量文件
|
||||
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。")
|
||||
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 = os.path.join(default, "14_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 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_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.run_button.setEnabled(False)
|
||||
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)
|
||||
|
||||
self._batch_thread.log_message.connect(_batch_log, 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), 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")
|
||||
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):
|
||||
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):
|
||||
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")
|
||||
@ -1,225 +0,0 @@
|
||||
import os
|
||||
import sys
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Union
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox, QScrollArea
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
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。
|
||||
支持两种打包模式：
|
||||
1. --onedir 模式：文件在 exe_root/_internal/ 下 → 检查 _internal 目录
|
||||
2. --onefile 模式：文件在 sys._MEIPASS 平铺目录
|
||||
"""
|
||||
# 优先检查 PyInstaller onefile 模式（文件平铺在 _MEIPASS 下）
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal_path = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal_path):
|
||||
return internal_path
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
|
||||
# 兼容 PyInstaller onedir 模式的 _internal 目录（exe 同级目录下）
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal_path = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal_path):
|
||||
return internal_path
|
||||
|
||||
# 开发环境下：基于当前文件 (step5_5_panel.py) 的绝对路径进行回溯
|
||||
# 当前在 src/gui/panels/，目标在 src/gui/model/
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
target_path = base_dir / os.path.basename(relative_path)
|
||||
return str(target_path)
|
||||
|
||||
class Step5_5Panel(QWidget):
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.index_checkboxes: Dict[str, QCheckBox] = {}
|
||||
# 标识为 waterindex.csv，目录跳转逻辑在 get_resource_path 中
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
|
||||
self.init_ui()
|
||||
# 延迟一小会儿加载，确保UI框架已就绪
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
|
||||
# 1. 路径展示区 (半透明只读)
|
||||
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)
|
||||
# 视觉微调：提示用户这是内置的
|
||||
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
|
||||
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_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addStretch()
|
||||
|
||||
self.refresh_button = QPushButton("手动重新加载公式")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
|
||||
# 核心滚动区
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(300) # 强制最小高度，防止塌陷
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QGridLayout(self.scroll_content)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop) # 靠顶对齐
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
|
||||
# 4. 输出与运行
|
||||
output_group = QGroupBox("结果输出")
|
||||
output_layout = QVBoxLayout()
|
||||
self.output_file_widget = FileSelectWidget("保存路径:", "CSV Files (*.csv)", mode="save")
|
||||
output_layout.addWidget(self.output_file_widget)
|
||||
output_group.setLayout(output_layout)
|
||||
main_layout.addWidget(output_group)
|
||||
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
main_layout.addWidget(self.enable_checkbox)
|
||||
|
||||
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 _auto_load_formulas(self):
|
||||
"""启动时自动加载逻辑"""
|
||||
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:
|
||||
# 清理旧列表
|
||||
for i in reversed(range(self.formula_layout.count())):
|
||||
widget = self.formula_layout.itemAt(i).widget()
|
||||
if widget: widget.deleteLater()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
# 鲁棒性读取：尝试不同编码
|
||||
for encoding in ['utf-8', 'gbk', 'utf-8-sig']:
|
||||
try:
|
||||
df = pd.read_csv(path, encoding=encoding)
|
||||
if 'Formula_Name' in df.columns: break
|
||||
except: continue
|
||||
|
||||
if 'Formula_Name' not in df.columns:
|
||||
if not silent: QMessageBox.critical(self, "错误", "CSV文件缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
names = df['Formula_Name'].dropna().unique().tolist()
|
||||
|
||||
row, col = 0, 0
|
||||
for name in names:
|
||||
name = str(name).strip()
|
||||
if not name: continue
|
||||
cb = QCheckBox(name)
|
||||
cb.setChecked(True)
|
||||
self.index_checkboxes[name] = cb
|
||||
self.formula_layout.addWidget(cb, row, col)
|
||||
col += 1
|
||||
if col >= 3:
|
||||
col = 0
|
||||
row += 1
|
||||
|
||||
# 强制UI更新
|
||||
self.scroll_content.adjustSize()
|
||||
print(f"✅ 成功加载 {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_all_formulas(self):
|
||||
for cb in self.index_checkboxes.values(): cb.setChecked(True)
|
||||
|
||||
def deselect_all_formulas(self):
|
||||
for cb in self.index_checkboxes.values(): cb.setChecked(False)
|
||||
|
||||
def get_config(self):
|
||||
selected = [n for n, cb in self.index_checkboxes.items() if cb.isChecked()]
|
||||
return {
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'output_file': self.output_file_widget.get_path(),
|
||||
'enabled': self.enable_checkbox.isChecked()
|
||||
}
|
||||
|
||||
def set_config(self, config):
|
||||
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 n, cb in self.index_checkboxes.items(): cb.setChecked(n in sel)
|
||||
if 'output_file' in config: self.output_file_widget.set_path(config['output_file'])
|
||||
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, 'step5_panel'):
|
||||
p5 = main.step5_panel.output_file.get_path() # 修正：变量名对齐
|
||||
if p5:
|
||||
if not os.path.isabs(p5): p5 = os.path.join(self.work_dir or '', p5).replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
|
||||
if self.work_dir:
|
||||
out = os.path.join(self.work_dir, "6_water_quality_indices", "training_spectra_indices.csv").replace('\\', '/')
|
||||
self.output_file_widget.set_path(out)
|
||||
|
||||
def run_step(self):
|
||||
config = self.get_config()
|
||||
if not config['training_csv_path']:
|
||||
QMessageBox.warning(self, "提示", "请先选择输入数据")
|
||||
return
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, 'run_single_step'): parent = parent.parent()
|
||||
if parent: parent.run_single_step('step5_5', {'step5_5': config})
|
||||
@ -1,374 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step6_75 面板 - 自定义回归分析
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import Dict
|
||||
|
||||
import pandas as pd
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QCheckBox, QPushButton,
|
||||
QScrollArea, QMessageBox,
|
||||
)
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step6_75Panel(QWidget):
|
||||
"""步骤6.75：自定义回归分析"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.x_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.y_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.method_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.csv_columns = []
|
||||
self.init_ui()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
hint = QLabel("指定自变量与因变量列，批量尝试不同回归方法")
|
||||
hint.setStyleSheet("color: #666; font-size: 11px;")
|
||||
layout.addWidget(hint)
|
||||
|
||||
# CSV文件选择
|
||||
csv_group = QGroupBox("数据文件")
|
||||
csv_layout = QVBoxLayout()
|
||||
|
||||
self.csv_file = FileSelectWidget(
|
||||
"输入CSV文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.csv_file.line_edit.textChanged.connect(self.on_csv_file_changed)
|
||||
csv_layout.addWidget(self.csv_file)
|
||||
|
||||
self.refresh_btn = QPushButton("刷新列信息")
|
||||
self.refresh_btn.clicked.connect(self.refresh_csv_columns)
|
||||
csv_layout.addWidget(self.refresh_btn)
|
||||
|
||||
csv_group.setLayout(csv_layout)
|
||||
layout.addWidget(csv_group)
|
||||
|
||||
# 自变量选择
|
||||
x_group = QGroupBox("自变量列选择 (可多选)")
|
||||
x_layout = QVBoxLayout()
|
||||
|
||||
x_scroll = QScrollArea()
|
||||
x_scroll.setWidgetResizable(True)
|
||||
x_scroll.setMinimumHeight(250)
|
||||
x_scroll.setMaximumHeight(350)
|
||||
|
||||
x_widget = QWidget()
|
||||
self.x_columns_layout = QGridLayout()
|
||||
x_widget.setLayout(self.x_columns_layout)
|
||||
|
||||
x_scroll.setWidget(x_widget)
|
||||
x_layout.addWidget(x_scroll)
|
||||
|
||||
x_btn_layout = QHBoxLayout()
|
||||
self.x_select_all = QPushButton("全选")
|
||||
self.x_deselect_all = QPushButton("全不选")
|
||||
self.x_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, True))
|
||||
self.x_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, False))
|
||||
x_btn_layout.addWidget(self.x_select_all)
|
||||
x_btn_layout.addWidget(self.x_deselect_all)
|
||||
x_btn_layout.addStretch()
|
||||
x_layout.addLayout(x_btn_layout)
|
||||
|
||||
x_group.setLayout(x_layout)
|
||||
layout.addWidget(x_group)
|
||||
|
||||
# 因变量选择
|
||||
y_group = QGroupBox("因变量列选择 (可多选)")
|
||||
y_layout = QVBoxLayout()
|
||||
|
||||
y_scroll = QScrollArea()
|
||||
y_scroll.setWidgetResizable(True)
|
||||
y_scroll.setMinimumHeight(200)
|
||||
y_scroll.setMaximumHeight(300)
|
||||
|
||||
y_widget = QWidget()
|
||||
self.y_columns_layout = QGridLayout()
|
||||
y_widget.setLayout(self.y_columns_layout)
|
||||
|
||||
y_scroll.setWidget(y_widget)
|
||||
y_layout.addWidget(y_scroll)
|
||||
|
||||
y_btn_layout = QHBoxLayout()
|
||||
self.y_select_all = QPushButton("全选")
|
||||
self.y_deselect_all = QPushButton("全不选")
|
||||
self.y_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, True))
|
||||
self.y_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, False))
|
||||
y_btn_layout.addWidget(self.y_select_all)
|
||||
y_btn_layout.addWidget(self.y_deselect_all)
|
||||
y_btn_layout.addStretch()
|
||||
y_layout.addLayout(y_btn_layout)
|
||||
|
||||
y_group.setLayout(y_layout)
|
||||
layout.addWidget(y_group)
|
||||
|
||||
# 回归方法选择
|
||||
method_group = QGroupBox("回归方法选择 (可多选)")
|
||||
method_layout = QVBoxLayout()
|
||||
|
||||
method_grid = QGridLayout()
|
||||
regression_methods = [
|
||||
'linear', 'exponential', 'power', 'logarithmic',
|
||||
'polynomial', 'hyperbolic', 'sigmoidal'
|
||||
]
|
||||
|
||||
for i, method in enumerate(regression_methods):
|
||||
checkbox = QCheckBox(method)
|
||||
if method in ['linear', 'exponential', 'power', 'logarithmic']:
|
||||
checkbox.setChecked(True)
|
||||
self.method_checkboxes[method] = checkbox
|
||||
method_grid.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
method_layout.addLayout(method_grid)
|
||||
|
||||
method_btn_layout = QHBoxLayout()
|
||||
self.method_select_all = QPushButton("全选")
|
||||
self.method_deselect_all = QPushButton("全不选")
|
||||
self.method_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, True))
|
||||
self.method_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, False))
|
||||
method_btn_layout.addWidget(self.method_select_all)
|
||||
method_btn_layout.addWidget(self.method_deselect_all)
|
||||
method_btn_layout.addStretch()
|
||||
method_layout.addLayout(method_btn_layout)
|
||||
|
||||
method_group.setLayout(method_layout)
|
||||
layout.addWidget(method_group)
|
||||
|
||||
# 输出目录
|
||||
output_group = QGroupBox("输出设置")
|
||||
output_layout = QFormLayout()
|
||||
|
||||
self.output_dir = QLineEdit()
|
||||
self.output_dir.setText("") # 路径由 update_from_config 根据 work_dir 自动填充
|
||||
output_layout.addRow("输出目录名:", self.output_dir)
|
||||
|
||||
output_group.setLayout(output_layout)
|
||||
layout.addWidget(output_group)
|
||||
|
||||
# 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 toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
def on_csv_file_changed(self):
|
||||
"""CSV文件改变时自动刷新列信息"""
|
||||
self.refresh_csv_columns()
|
||||
|
||||
def refresh_csv_columns(self):
|
||||
"""刷新CSV文件的列信息"""
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
return
|
||||
|
||||
try:
|
||||
df = pd.read_csv(csv_path, nrows=0)
|
||||
self.csv_columns = list(df.columns)
|
||||
self.update_column_widgets()
|
||||
except Exception as e:
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
print(f"读取CSV列信息失败: {e}")
|
||||
|
||||
def update_column_widgets(self):
|
||||
"""更新列选择组件"""
|
||||
for checkbox in self.x_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.x_column_checkboxes.clear()
|
||||
|
||||
for checkbox in self.y_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.y_column_checkboxes.clear()
|
||||
|
||||
if not self.csv_columns:
|
||||
return
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd', 'b']):
|
||||
checkbox.setChecked(True)
|
||||
self.x_column_checkboxes[col] = checkbox
|
||||
self.x_columns_layout.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['chl', 'tn', 'tp', 'turbidity', 'do', 'ph', 'conductivity']):
|
||||
checkbox.setChecked(True)
|
||||
self.y_column_checkboxes[col] = checkbox
|
||||
self.y_columns_layout.addWidget(checkbox, i // 2, i % 2)
|
||||
|
||||
self.x_columns_layout.update()
|
||||
self.y_columns_layout.update()
|
||||
|
||||
def get_config(self):
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
selected_methods = 'all'
|
||||
|
||||
return {
|
||||
'csv_path': self.csv_file.get_path() or None,
|
||||
'x_columns': selected_x_columns,
|
||||
'y_columns': selected_y_columns,
|
||||
'methods': selected_methods,
|
||||
'output_dir': self.output_dir.text().strip() or None,
|
||||
'enabled': self.enable_checkbox.isChecked()
|
||||
}
|
||||
|
||||
def set_config(self, config):
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
self.refresh_csv_columns()
|
||||
|
||||
if 'x_columns' in config:
|
||||
selected_x = set(config['x_columns']) if isinstance(config['x_columns'], list) else set()
|
||||
for col, checkbox in self.x_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_x)
|
||||
|
||||
if 'y_columns' in config:
|
||||
selected_y = set(config['y_columns']) if isinstance(config['y_columns'], list) else set()
|
||||
for col, checkbox in self.y_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_y)
|
||||
|
||||
if 'methods' in config:
|
||||
methods = config['methods']
|
||||
if isinstance(methods, list):
|
||||
selected_methods = set(methods)
|
||||
elif methods == 'all':
|
||||
selected_methods = set(self.method_checkboxes.keys())
|
||||
else:
|
||||
selected_methods = set()
|
||||
for method, checkbox in self.method_checkboxes.items():
|
||||
checkbox.setChecked(method in selected_methods)
|
||||
|
||||
if 'output_dir' in config:
|
||||
self.output_dir.setText(config['output_dir'] or "9_Custom_Regression_Modeling")
|
||||
if 'enabled' in config:
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
|
||||
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
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练光谱 CSV 路径
|
||||
main_window = self.window()
|
||||
if main_window and hasattr(main_window, 'step5_panel'):
|
||||
step5_widget = getattr(main_window.step5_panel, 'output_file', None)
|
||||
step5_output_path = ""
|
||||
if hasattr(step5_widget, 'get_path'):
|
||||
step5_output_path = step5_widget.get_path() or ""
|
||||
elif hasattr(step5_widget, 'text'):
|
||||
step5_output_path = step5_widget.text() or ""
|
||||
|
||||
if step5_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_output_path):
|
||||
step5_output_path = os.path.join(self.work_dir or '', step5_output_path).replace('\\', '/')
|
||||
existing = self.csv_file.get_path()
|
||||
if not existing or not existing.strip():
|
||||
self.csv_file.set_path(step5_output_path)
|
||||
|
||||
# 2. 自动填充输出目录（9_Custom_Regression_Modeling）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "9_Custom_Regression_Modeling")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
existing_out = self.output_dir.text().strip()
|
||||
if not existing_out:
|
||||
self.output_dir.setText(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 run_step(self):
|
||||
"""独立运行步骤6.75"""
|
||||
csv_path = self.csv_file.get_path()
|
||||
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入验证失败", "请选择输入CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "输入CSV文件不存在")
|
||||
return
|
||||
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_x_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个自变量列")
|
||||
return
|
||||
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_y_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个因变量列")
|
||||
return
|
||||
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一种回归方法")
|
||||
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('step6_75', {'step6_75': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
@ -1,415 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step6 面板 - 机器学习建模
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox,
|
||||
QPushButton, QFileDialog, QMessageBox,
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 中文映射表（内部键名 -> 显示文本）
|
||||
# ============================================================
|
||||
|
||||
# 预处理方法：内部键 -> 显示文本
|
||||
PREPROC_CHINESE = {
|
||||
'None': '无 (None)',
|
||||
'MMS': '最小-最大归一化 (MMS)',
|
||||
'SS': '标度化 (SS)',
|
||||
'SNV': '标准正态变换 (SNV)',
|
||||
'MA': '移动平均 (MA)',
|
||||
'SG': 'Savitzky-Golay (SG)',
|
||||
'MSC': '多元散射校正 (MSC)',
|
||||
'D1': '一阶导数 (D1)',
|
||||
'D2': '二阶导数 (D2)',
|
||||
'DT': '去趋势 (DT)',
|
||||
'CT': '中心化 (CT)',
|
||||
}
|
||||
|
||||
# 模型类型：内部键 -> 显示文本
|
||||
MODEL_CHINESE = {
|
||||
# 线性模型
|
||||
'LinearRegression': '多元线性回归 (MLR)',
|
||||
'Ridge': '岭回归 (Ridge)',
|
||||
'Lasso': '套索回归 (Lasso)',
|
||||
'ElasticNet': '弹性网络 (ElasticNet)',
|
||||
'PLS': '偏最小二乘 (PLSR)',
|
||||
# 树模型
|
||||
'DecisionTree': '决策树 (CART)',
|
||||
'RF': '随机森林 (RF)',
|
||||
'ExtraTrees': '极端随机树 (ET)',
|
||||
'XGBoost': '极值梯度提升 (XGBoost)',
|
||||
'LightGBM': '轻量梯度提升 (LightGBM)',
|
||||
'CatBoost': '类别梯度提升 (CatBoost)',
|
||||
# 集成学习
|
||||
'GradientBoosting': '梯度提升树 (GBDT)',
|
||||
'AdaBoost': '自适应提升 (AdaBoost)',
|
||||
# 其他模型
|
||||
'SVR': '支持向量回归 (SVR)',
|
||||
'KNN': 'K近邻回归 (KNN)',
|
||||
'MLP': '多层感知机 (BP神经网络)',
|
||||
}
|
||||
|
||||
# 数据划分方法：内部键 -> 显示文本
|
||||
SPLIT_CHINESE = {
|
||||
'spxy': 'SPXY 算法 (考量X-Y空间)',
|
||||
'ks': 'KS 算法 (考量X空间)',
|
||||
'random': '随机划分 (Random)',
|
||||
}
|
||||
|
||||
|
||||
class Step6Panel(QWidget):
|
||||
"""步骤6：机器学习建模"""
|
||||
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 Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.training_csv_file)
|
||||
|
||||
# 机器学习模型页面
|
||||
self.ml_page = QWidget()
|
||||
self.create_ml_page()
|
||||
layout.addWidget(self.ml_page)
|
||||
|
||||
# 输出文件路径
|
||||
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，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)
|
||||
|
||||
# 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("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
|
||||
def create_ml_page(self):
|
||||
"""创建机器学习模型页面"""
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("训练参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.feature_start = QLineEdit()
|
||||
self.feature_start.setText("374.285004")
|
||||
params_layout.addRow("特征起始列:", self.feature_start)
|
||||
|
||||
self.cv_folds = QSpinBox()
|
||||
self.cv_folds.setRange(2, 10)
|
||||
self.cv_folds.setValue(3)
|
||||
params_layout.addRow("交叉验证折数:", self.cv_folds)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 预处理方法 - 多选
|
||||
preproc_group = QGroupBox("预处理方法 (可多选)")
|
||||
preproc_layout = QVBoxLayout()
|
||||
|
||||
preproc_grid = QGridLayout()
|
||||
self.preproc_checkboxes = {}
|
||||
preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
|
||||
|
||||
for i, method in enumerate(preproc_methods):
|
||||
checkbox = QCheckBox(PREPROC_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
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)
|
||||
layout.addWidget(preproc_group)
|
||||
|
||||
# 模型选择 - 多选
|
||||
model_group = QGroupBox("模型类型 (可多选)")
|
||||
model_layout = QVBoxLayout()
|
||||
|
||||
model_grid = QGridLayout()
|
||||
self.model_checkboxes = {}
|
||||
|
||||
model_groups = [
|
||||
("【线性模型】", ['LinearRegression', 'Ridge', 'Lasso', 'ElasticNet', 'PLS']),
|
||||
("【树模型】", ['DecisionTree', 'RF', 'ExtraTrees', 'XGBoost', 'LightGBM', 'CatBoost']),
|
||||
("【集成学习】", ['GradientBoosting', 'AdaBoost']),
|
||||
("【其他模型】", ['SVR', 'KNN', 'MLP'])
|
||||
]
|
||||
|
||||
row = 0
|
||||
for group_name, models in model_groups:
|
||||
group_label = QLabel(f"<b>{group_name}</b>")
|
||||
group_label.setStyleSheet(
|
||||
f"background-color: {ModernStylesheet.COLORS['hover']}; "
|
||||
f"padding: 5px; border: 1px solid {ModernStylesheet.COLORS['border_light']}; "
|
||||
f"border-radius: 3px;"
|
||||
)
|
||||
model_grid.addWidget(group_label, row, 0, 1, 4)
|
||||
row += 1
|
||||
|
||||
for i, model in enumerate(models):
|
||||
checkbox = QCheckBox(MODEL_CHINESE.get(model, model))
|
||||
checkbox.setChecked(False)
|
||||
self.model_checkboxes[model] = checkbox
|
||||
model_grid.addWidget(checkbox, row, i % 4)
|
||||
if (i + 1) % 4 == 0:
|
||||
row += 1
|
||||
|
||||
row += 1
|
||||
|
||||
model_button_layout = QHBoxLayout()
|
||||
model_select_all = QPushButton("全选")
|
||||
model_deselect_all = QPushButton("全不选")
|
||||
model_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, True))
|
||||
model_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, False))
|
||||
model_button_layout.addWidget(model_select_all)
|
||||
model_button_layout.addWidget(model_deselect_all)
|
||||
model_button_layout.addStretch()
|
||||
|
||||
model_layout.addLayout(model_grid)
|
||||
model_layout.addLayout(model_button_layout)
|
||||
model_group.setLayout(model_layout)
|
||||
layout.addWidget(model_group)
|
||||
|
||||
# 数据划分方法 - 多选
|
||||
split_group = QGroupBox("数据划分方法 (可多选)")
|
||||
split_layout = QVBoxLayout()
|
||||
|
||||
split_grid = QGridLayout()
|
||||
self.split_checkboxes = {}
|
||||
split_methods = ['spxy', 'ks', 'random']
|
||||
|
||||
for i, method in enumerate(split_methods):
|
||||
checkbox = QCheckBox(SPLIT_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.split_checkboxes[method] = checkbox
|
||||
split_grid.addWidget(checkbox, 0, i)
|
||||
|
||||
split_button_layout = QHBoxLayout()
|
||||
split_select_all = QPushButton("全选")
|
||||
split_deselect_all = QPushButton("全不选")
|
||||
split_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, True))
|
||||
split_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, False))
|
||||
split_button_layout.addWidget(split_select_all)
|
||||
split_button_layout.addWidget(split_deselect_all)
|
||||
split_button_layout.addStretch()
|
||||
|
||||
split_layout.addLayout(split_grid)
|
||||
split_layout.addLayout(split_button_layout)
|
||||
split_group.setLayout(split_layout)
|
||||
layout.addWidget(split_group)
|
||||
|
||||
self.ml_page.setLayout(layout)
|
||||
|
||||
def _toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
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_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 = os.path.join(work_dir, "6_water_quality_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)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
preprocessing_methods = [
|
||||
method for method, checkbox in self.preproc_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
model_names = [
|
||||
model for model, checkbox in self.model_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
split_methods = [
|
||||
method for method, checkbox in self.split_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
|
||||
config = {
|
||||
'feature_start_column': self.feature_start.text(),
|
||||
'preprocessing_methods': preprocessing_methods if preprocessing_methods else ['None'],
|
||||
'model_names': model_names if model_names else ['SVR'],
|
||||
'split_methods': split_methods if split_methods else ['random'],
|
||||
'cv_folds': self.cv_folds.value()
|
||||
}
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if training_csv_path:
|
||||
config['training_csv_path'] = training_csv_path
|
||||
output_path = self.output_path.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'feature_start_column' in config:
|
||||
self.feature_start.setText(str(config['feature_start_column']))
|
||||
if 'cv_folds' in config:
|
||||
self.cv_folds.setValue(config['cv_folds'])
|
||||
if 'preprocessing_methods' in config:
|
||||
methods = config['preprocessing_methods']
|
||||
for method, checkbox in self.preproc_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'model_names' in config:
|
||||
models = config['model_names']
|
||||
for model, checkbox in self.model_checkboxes.items():
|
||||
checkbox.setChecked(model in models)
|
||||
if 'split_methods' in config:
|
||||
methods = config['split_methods']
|
||||
for method, checkbox in self.split_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'training_csv_path' in config:
|
||||
self.training_csv_file.set_path(config['training_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
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练数据路径，并确保为绝对路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step5_panel'):
|
||||
# 优先直接从 Step5 的输出 widget 读取
|
||||
step5_output = main_window.step5_panel.output_file.get_path()
|
||||
if step5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_output):
|
||||
step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_output)
|
||||
elif hasattr(main_window, 'step5_panel') and hasattr(main_window.step5_panel, 'get_config'):
|
||||
# 回退：从 Step5 的 config 字典中查找可能的键名
|
||||
step5_cfg = main_window.step5_panel.get_config()
|
||||
step5_csv = (
|
||||
step5_cfg.get('training_csv_path')
|
||||
or step5_cfg.get('output_file')
|
||||
or step5_cfg.get('csv_path')
|
||||
or step5_cfg.get('output_csv')
|
||||
)
|
||||
if step5_csv:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_csv):
|
||||
step5_csv = os.path.join(self.work_dir or '', step5_csv).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_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}/6_water_quality_indices/training_spectra_indices.csv
|
||||
# 输入是 sampling_spectra.csv → 输出 {work_dir}/6_water_quality_indices/sampling_spectra_indices.csv
|
||||
if self.work_dir:
|
||||
indices_dir = os.path.join(self.work_dir, "6_water_quality_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 = "water_quality_indices.csv"
|
||||
output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
|
||||
self.output_path.set_path(output_path)
|
||||
else:
|
||||
self.output_path.set_path("")
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤6"""
|
||||
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
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step6': self.get_config()}
|
||||
main_window.run_single_step('step6', config)
|
||||
|
||||
def get_training_params(self):
|
||||
"""获取模型训练参数"""
|
||||
return {
|
||||
'pipeline_type': 'machine_learning',
|
||||
'feature_start': float(self.feature_start.text()),
|
||||
'cv_folds': self.cv_folds.value(),
|
||||
'preprocess_methods': [method for method, cb in self.preproc_checkboxes.items() if cb.isChecked()],
|
||||
'model_types': [model for model, cb in self.model_checkboxes.items() if cb.isChecked()],
|
||||
'split_methods': [method for method, cb in self.split_checkboxes.items() if cb.isChecked()]
|
||||
}
|
||||
@ -1,23 +1,75 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step7 面板 - 采样点生成
|
||||
Step7 面板 - 机器学习建模
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout,
|
||||
QPushButton, QCheckBox, QSpinBox, QMessageBox,
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox,
|
||||
QPushButton, QFileDialog, QMessageBox,
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.dialogs import SamplingViewerDialog
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 中文映射表（内部键名 -> 显示文本）
|
||||
# ============================================================
|
||||
|
||||
# 预处理方法：内部键 -> 显示文本
|
||||
PREPROC_CHINESE = {
|
||||
'None': '无 (None)',
|
||||
'MMS': '最小-最大归一化 (MMS)',
|
||||
'SS': '标度化 (SS)',
|
||||
'SNV': '标准正态变换 (SNV)',
|
||||
'MA': '移动平均 (MA)',
|
||||
'SG': 'Savitzky-Golay (SG)',
|
||||
'MSC': '多元散射校正 (MSC)',
|
||||
'D1': '一阶导数 (D1)',
|
||||
'D2': '二阶导数 (D2)',
|
||||
'DT': '去趋势 (DT)',
|
||||
'CT': '中心化 (CT)',
|
||||
}
|
||||
|
||||
# 模型类型：内部键 -> 显示文本
|
||||
MODEL_CHINESE = {
|
||||
# 线性模型
|
||||
'LinearRegression': '多元线性回归 (MLR)',
|
||||
'Ridge': '岭回归 (Ridge)',
|
||||
'Lasso': '套索回归 (Lasso)',
|
||||
'ElasticNet': '弹性网络 (ElasticNet)',
|
||||
'PLS': '偏最小二乘 (PLSR)',
|
||||
# 树模型
|
||||
'DecisionTree': '决策树 (CART)',
|
||||
'RF': '随机森林 (RF)',
|
||||
'ExtraTrees': '极端随机树 (ET)',
|
||||
'XGBoost': '极值梯度提升 (XGBoost)',
|
||||
'LightGBM': '轻量梯度提升 (LightGBM)',
|
||||
'CatBoost': '类别梯度提升 (CatBoost)',
|
||||
# 集成学习
|
||||
'GradientBoosting': '梯度提升树 (GBDT)',
|
||||
'AdaBoost': '自适应提升 (AdaBoost)',
|
||||
# 其他模型
|
||||
'SVR': '支持向量回归 (SVR)',
|
||||
'KNN': 'K近邻回归 (KNN)',
|
||||
'MLP': '多层感知机 (BP神经网络)',
|
||||
}
|
||||
|
||||
# 数据划分方法：内部键 -> 显示文本
|
||||
SPLIT_CHINESE = {
|
||||
'spxy': 'SPXY 算法 (考量X-Y空间)',
|
||||
'ks': 'KS 算法 (考量X空间)',
|
||||
'random': '随机划分 (Random)',
|
||||
}
|
||||
|
||||
|
||||
class Step7Panel(QWidget):
|
||||
"""步骤7：采样点生成"""
|
||||
"""步骤7：机器学习建模"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -25,58 +77,35 @@ class Step7Panel(QWidget):
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 去耀斑影像文件（用于独立运行）
|
||||
self.deglint_img_file = FileSelectWidget(
|
||||
"去耀斑影像:",
|
||||
"Image Files (*.bsq *.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.deglint_img_file)
|
||||
# 标题
|
||||
|
||||
# 水域掩膜文件（可选，用于独立运行）
|
||||
self.water_mask_file = FileSelectWidget(
|
||||
"水域掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
self.water_mask_file.label.setText("水域掩膜:")
|
||||
layout.addWidget(self.water_mask_file)
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("采样参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.interval = QSpinBox()
|
||||
self.interval.setRange(10, 500)
|
||||
self.interval.setValue(50)
|
||||
params_layout.addRow("采样点间隔(像素):", self.interval)
|
||||
|
||||
self.sample_radius = QSpinBox()
|
||||
self.sample_radius.setRange(1, 50)
|
||||
self.sample_radius.setValue(5)
|
||||
params_layout.addRow("采样半径(像素):", self.sample_radius)
|
||||
|
||||
self.chunk_size = QSpinBox()
|
||||
self.chunk_size.setRange(100, 10000)
|
||||
self.chunk_size.setValue(1000)
|
||||
params_layout.addRow("处理块大小:", self.chunk_size)
|
||||
|
||||
self.use_adaptive_sampling = QCheckBox("启用自适应采样")
|
||||
self.use_adaptive_sampling.setChecked(True)
|
||||
params_layout.addRow("采样模式:", self.use_adaptive_sampling)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 输出文件路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出采样点:",
|
||||
# 训练数据文件（用于独立运行）
|
||||
self.training_csv_file = FileSelectWidget(
|
||||
"训练数据:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.output_file.line_edit.setPlaceholderText("sampling_points.csv")
|
||||
layout.addWidget(self.output_file)
|
||||
layout.addWidget(self.training_csv_file)
|
||||
|
||||
# 机器学习模型页面
|
||||
self.ml_page = QWidget()
|
||||
self.create_ml_page()
|
||||
layout.addWidget(self.ml_page)
|
||||
|
||||
# 输出文件路径
|
||||
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，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)
|
||||
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
self.enable_checkbox.setChecked(False)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
|
||||
# 独立运行按钮
|
||||
@ -85,57 +114,233 @@ class Step7Panel(QWidget):
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
# 交互式预览按钮
|
||||
self.preview_btn = QPushButton("📊 交互式预览采样点与光谱")
|
||||
self.preview_btn.setEnabled(False)
|
||||
self.preview_btn.clicked.connect(self._open_sampling_viewer)
|
||||
layout.addWidget(self.preview_btn)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
|
||||
# 监听输出路径变化，实时更新预览按钮状态
|
||||
self.output_file.line_edit.textChanged.connect(self._on_output_changed)
|
||||
def create_ml_page(self):
|
||||
"""创建机器学习模型页面"""
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("训练参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.feature_start = QLineEdit()
|
||||
self.feature_start.setText("374.285004")
|
||||
params_layout.addRow("特征起始列:", self.feature_start)
|
||||
|
||||
self.cv_folds = QSpinBox()
|
||||
self.cv_folds.setRange(2, 10)
|
||||
self.cv_folds.setValue(3)
|
||||
params_layout.addRow("交叉验证折数:", self.cv_folds)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 预处理方法 - 多选
|
||||
preproc_group = QGroupBox("预处理方法 (可多选)")
|
||||
preproc_layout = QVBoxLayout()
|
||||
|
||||
preproc_grid = QGridLayout()
|
||||
self.preproc_checkboxes = {}
|
||||
preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
|
||||
|
||||
for i, method in enumerate(preproc_methods):
|
||||
checkbox = QCheckBox(PREPROC_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
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)
|
||||
layout.addWidget(preproc_group)
|
||||
|
||||
# 模型选择 - 多选
|
||||
model_group = QGroupBox("模型类型 (可多选)")
|
||||
model_layout = QVBoxLayout()
|
||||
|
||||
model_grid = QGridLayout()
|
||||
self.model_checkboxes = {}
|
||||
|
||||
model_groups = [
|
||||
("【线性模型】", ['LinearRegression', 'Ridge', 'Lasso', 'ElasticNet', 'PLS']),
|
||||
("【树模型】", ['DecisionTree', 'RF', 'ExtraTrees', 'XGBoost', 'LightGBM', 'CatBoost']),
|
||||
("【集成学习】", ['GradientBoosting', 'AdaBoost']),
|
||||
("【其他模型】", ['SVR', 'KNN', 'MLP'])
|
||||
]
|
||||
|
||||
row = 0
|
||||
for group_name, models in model_groups:
|
||||
group_label = QLabel(f"<b>{group_name}</b>")
|
||||
group_label.setStyleSheet(
|
||||
f"background-color: {ModernStylesheet.COLORS['hover']}; "
|
||||
f"padding: 5px; border: 1px solid {ModernStylesheet.COLORS['border_light']}; "
|
||||
f"border-radius: 3px;"
|
||||
)
|
||||
model_grid.addWidget(group_label, row, 0, 1, 4)
|
||||
row += 1
|
||||
|
||||
for i, model in enumerate(models):
|
||||
checkbox = QCheckBox(MODEL_CHINESE.get(model, model))
|
||||
checkbox.setChecked(False)
|
||||
self.model_checkboxes[model] = checkbox
|
||||
model_grid.addWidget(checkbox, row, i % 4)
|
||||
if (i + 1) % 4 == 0:
|
||||
row += 1
|
||||
|
||||
row += 1
|
||||
|
||||
model_button_layout = QHBoxLayout()
|
||||
model_select_all = QPushButton("全选")
|
||||
model_deselect_all = QPushButton("全不选")
|
||||
model_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, True))
|
||||
model_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, False))
|
||||
model_button_layout.addWidget(model_select_all)
|
||||
model_button_layout.addWidget(model_deselect_all)
|
||||
model_button_layout.addStretch()
|
||||
|
||||
model_layout.addLayout(model_grid)
|
||||
model_layout.addLayout(model_button_layout)
|
||||
model_group.setLayout(model_layout)
|
||||
layout.addWidget(model_group)
|
||||
|
||||
# 数据划分方法 - 多选
|
||||
split_group = QGroupBox("数据划分方法 (可多选)")
|
||||
split_layout = QVBoxLayout()
|
||||
|
||||
split_grid = QGridLayout()
|
||||
self.split_checkboxes = {}
|
||||
split_methods = ['spxy', 'ks', 'random']
|
||||
|
||||
for i, method in enumerate(split_methods):
|
||||
checkbox = QCheckBox(SPLIT_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.split_checkboxes[method] = checkbox
|
||||
split_grid.addWidget(checkbox, 0, i)
|
||||
|
||||
split_button_layout = QHBoxLayout()
|
||||
split_select_all = QPushButton("全选")
|
||||
split_deselect_all = QPushButton("全不选")
|
||||
split_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, True))
|
||||
split_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, False))
|
||||
split_button_layout.addWidget(split_select_all)
|
||||
split_button_layout.addWidget(split_deselect_all)
|
||||
split_button_layout.addStretch()
|
||||
|
||||
split_layout.addLayout(split_grid)
|
||||
split_layout.addLayout(split_button_layout)
|
||||
split_group.setLayout(split_layout)
|
||||
layout.addWidget(split_group)
|
||||
|
||||
self.ml_page.setLayout(layout)
|
||||
|
||||
def _toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
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_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 = os.path.join(work_dir, "6_water_quality_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)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
preprocessing_methods = [
|
||||
method for method, checkbox in self.preproc_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
model_names = [
|
||||
model for model, checkbox in self.model_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
split_methods = [
|
||||
method for method, checkbox in self.split_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
|
||||
config = {
|
||||
'interval': self.interval.value(),
|
||||
'sample_radius': self.sample_radius.value(),
|
||||
'chunk_size': self.chunk_size.value(),
|
||||
'use_adaptive_sampling': self.use_adaptive_sampling.isChecked(),
|
||||
'feature_start_column': self.feature_start.text(),
|
||||
'preprocessing_methods': preprocessing_methods if preprocessing_methods else ['None'],
|
||||
'model_names': model_names if model_names else ['SVR'],
|
||||
'split_methods': split_methods if split_methods else ['random'],
|
||||
'cv_folds': self.cv_folds.value()
|
||||
}
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if deglint_img_path:
|
||||
config['deglint_img_path'] = deglint_img_path
|
||||
water_mask_path = self.water_mask_file.get_path()
|
||||
if water_mask_path:
|
||||
config['water_mask_path'] = water_mask_path
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if training_csv_path:
|
||||
config['training_csv_path'] = training_csv_path
|
||||
output_path = self.output_path.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'interval' in config:
|
||||
self.interval.setValue(config['interval'])
|
||||
if 'sample_radius' in config:
|
||||
self.sample_radius.setValue(config['sample_radius'])
|
||||
if 'chunk_size' in config:
|
||||
self.chunk_size.setValue(config['chunk_size'])
|
||||
if 'use_adaptive_sampling' in config:
|
||||
self.use_adaptive_sampling.setChecked(config['use_adaptive_sampling'])
|
||||
if 'deglint_img_path' in config:
|
||||
self.deglint_img_file.set_path(config['deglint_img_path'])
|
||||
if 'water_mask_path' in config:
|
||||
self.water_mask_file.set_path(config['water_mask_path'])
|
||||
if 'glint_mask_path' in config:
|
||||
self.glint_mask_file.set_path(config['glint_mask_path'])
|
||||
if 'feature_start_column' in config:
|
||||
self.feature_start.setText(str(config['feature_start_column']))
|
||||
if 'cv_folds' in config:
|
||||
self.cv_folds.setValue(config['cv_folds'])
|
||||
if 'preprocessing_methods' in config:
|
||||
methods = config['preprocessing_methods']
|
||||
for method, checkbox in self.preproc_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'model_names' in config:
|
||||
models = config['model_names']
|
||||
for model, checkbox in self.model_checkboxes.items():
|
||||
checkbox.setChecked(model in models)
|
||||
if 'split_methods' in config:
|
||||
methods = config['split_methods']
|
||||
for method, checkbox in self.split_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'training_csv_path' in config:
|
||||
self.training_csv_file.set_path(config['training_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去耀斑影像和掩膜路径
|
||||
"""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（用于从 step_outputs 获取绝对路径）
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
@ -144,81 +349,53 @@ class Step7Panel(QWidget):
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练数据路径，并确保为绝对路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step5_panel'):
|
||||
# 优先直接从 Step5 的输出 widget 读取
|
||||
step5_output = main_window.step5_panel.output_file.get_path()
|
||||
if step5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_output):
|
||||
step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_output)
|
||||
elif hasattr(main_window, 'step5_panel') and hasattr(main_window.step5_panel, 'get_config'):
|
||||
# 回退：从 Step5 的 config 字典中查找可能的键名
|
||||
step5_cfg = main_window.step5_panel.get_config()
|
||||
step5_csv = (
|
||||
step5_cfg.get('training_csv_path')
|
||||
or step5_cfg.get('output_file')
|
||||
or step5_cfg.get('csv_path')
|
||||
or step5_cfg.get('output_csv')
|
||||
)
|
||||
if step5_csv:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_csv):
|
||||
step5_csv = os.path.join(self.work_dir or '', step5_csv).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_csv)
|
||||
|
||||
# 1. 填充去耀斑影像路径（优先从 pipeline.step_outputs 获取绝对路径）
|
||||
deglint_path = None
|
||||
if pipeline and hasattr(pipeline, 'step_outputs'):
|
||||
step3_outputs = getattr(pipeline, 'step_outputs', {}).get('step3', {})
|
||||
deglint_path = (
|
||||
step3_outputs.get('deglint_image')
|
||||
or step3_outputs.get('output_path')
|
||||
or step3_outputs.get('output_file')
|
||||
or step3_outputs.get('deglint_img_path')
|
||||
)
|
||||
# 回退：从 step3 面板 widget 直接读取（可能是相对路径）
|
||||
if not deglint_path and hasattr(main_window, 'step3_panel'):
|
||||
deglint_path = main_window.step3_panel.output_file.get_path()
|
||||
|
||||
if deglint_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(deglint_path):
|
||||
deglint_path = os.path.join(self.work_dir or '', deglint_path).replace('\\', '/')
|
||||
self.deglint_img_file.set_path(deglint_path)
|
||||
|
||||
# 2. 填充水域掩膜路径（优先级：pipeline.step_outputs > step1_panel > 1_water_mask > input-test）
|
||||
water_mask_path = None
|
||||
if pipeline and hasattr(pipeline, 'step_outputs'):
|
||||
step1_outputs = getattr(pipeline, 'step_outputs', {}).get('step1', {})
|
||||
water_mask_path = (
|
||||
step1_outputs.get('water_mask')
|
||||
or step1_outputs.get('output_path')
|
||||
or step1_outputs.get('output_file')
|
||||
)
|
||||
# 回退：从 step1 面板 widget 直接读取
|
||||
if not water_mask_path and hasattr(main_window, 'step1_panel'):
|
||||
water_mask_path = main_window.step1_panel.output_file.get_path()
|
||||
# 备选：扫描 1_water_mask 目录下的 .dat 文件
|
||||
if not water_mask_path and self.work_dir:
|
||||
mask_dir = os.path.join(self.work_dir, "1_water_mask")
|
||||
if os.path.isdir(mask_dir):
|
||||
dat_files = [f for f in os.listdir(mask_dir) if f.lower().endswith('.dat')]
|
||||
if dat_files:
|
||||
water_mask_path = os.path.join(mask_dir, dat_files[0]).replace('\\', '/')
|
||||
# 备选：扫描 input-test 目录（优先匹配 water_mask_from_shp.dat）
|
||||
if not water_mask_path and self.work_dir:
|
||||
input_test_dir = os.path.join(self.work_dir, "input-test")
|
||||
if os.path.isdir(input_test_dir):
|
||||
dat_files = [f for f in os.listdir(input_test_dir) if f.lower().endswith('.dat')]
|
||||
# 优先匹配 water_mask_from_shp.dat
|
||||
for f in dat_files:
|
||||
if 'water_mask_from_shp' in f.lower():
|
||||
water_mask_path = os.path.join(input_test_dir, f).replace('\\', '/')
|
||||
break
|
||||
# 否则取第一个 .dat 文件
|
||||
if not water_mask_path and dat_files:
|
||||
water_mask_path = os.path.join(input_test_dir, dat_files[0]).replace('\\', '/')
|
||||
|
||||
if water_mask_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(water_mask_path):
|
||||
water_mask_path = os.path.join(self.work_dir or '', water_mask_path).replace('\\', '/')
|
||||
self.water_mask_file.set_path(water_mask_path)
|
||||
|
||||
# 3. 自动填充输出路径（绝对路径）
|
||||
# 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}/6_water_quality_indices/training_spectra_indices.csv
|
||||
# 输入是 sampling_spectra.csv → 输出 {work_dir}/6_water_quality_indices/sampling_spectra_indices.csv
|
||||
if self.work_dir:
|
||||
output_path = os.path.join(self.work_dir, "10_sampling", "sampling_spectra.csv")
|
||||
os.makedirs(os.path.dirname(output_path), exist_ok=True)
|
||||
self.output_file.set_path(output_path.replace('\\', '/'))
|
||||
|
||||
# 4. 同步更新预览按钮状态（路径可能已自动填充）
|
||||
self._check_csv_exists()
|
||||
indices_dir = os.path.join(self.work_dir, "6_water_quality_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 = "water_quality_indices.csv"
|
||||
output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
|
||||
self.output_path.set_path(output_path)
|
||||
else:
|
||||
self.output_path.set_path("")
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤7"""
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if not deglint_img_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择去耀斑影像文件！")
|
||||
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
|
||||
|
||||
main_window = self.window()
|
||||
@ -226,27 +403,13 @@ class Step7Panel(QWidget):
|
||||
config = {'step7': self.get_config()}
|
||||
main_window.run_single_step('step7', config)
|
||||
|
||||
def _check_csv_exists(self):
|
||||
"""检查 output csv 是否存在，驱动预览按钮启停"""
|
||||
csv_path = self.output_file.get_path()
|
||||
enabled = bool(csv_path and os.path.isabs(csv_path) and os.path.exists(csv_path))
|
||||
self.preview_btn.setEnabled(enabled)
|
||||
return enabled
|
||||
|
||||
def _on_output_changed(self, _text=None):
|
||||
"""输出路径输入框内容变化时调用（_text 为 line_edit.textChanged 信号参数）"""
|
||||
self._check_csv_exists()
|
||||
|
||||
def _open_sampling_viewer(self):
|
||||
"""打开交互式采样点查看器弹窗"""
|
||||
csv_path = self.output_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
QMessageBox.warning(
|
||||
self, "文件不存在",
|
||||
f"采样点 CSV 文件不存在：{csv_path}\n请先运行步骤7生成数据。"
|
||||
)
|
||||
return
|
||||
dialog = SamplingViewerDialog(csv_path, self)
|
||||
dialog.exec_()
|
||||
# 弹窗关闭后再次检查状态（可能文件被覆盖等）
|
||||
self._check_csv_exists()
|
||||
def get_training_params(self):
|
||||
"""获取模型训练参数"""
|
||||
return {
|
||||
'pipeline_type': 'machine_learning',
|
||||
'feature_start': float(self.feature_start.text()),
|
||||
'cv_folds': self.cv_folds.value(),
|
||||
'preprocess_methods': [method for method, cb in self.preproc_checkboxes.items() if cb.isChecked()],
|
||||
'model_types': [model for model, cb in self.model_checkboxes.items() if cb.isChecked()],
|
||||
'split_methods': [method for method, cb in self.split_checkboxes.items() if cb.isChecked()]
|
||||
}
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step6_5 面板 - 非经验统计回归建模
|
||||
Step8 面板 - 非经验统计回归建模
|
||||
"""
|
||||
|
||||
import os
|
||||
@ -17,8 +17,8 @@ from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step6_5Panel(QWidget):
|
||||
"""步骤6.5：非经验统计回归建模"""
|
||||
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()
|
||||
@ -280,7 +280,7 @@ class Step6_5Panel(QWidget):
|
||||
self.output_dir.set_path(dir_path)
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤6.5"""
|
||||
"""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！")
|
||||
@ -297,7 +297,7 @@ class Step6_5Panel(QWidget):
|
||||
parent = parent.parent()
|
||||
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step6_5', {'step6_5': config})
|
||||
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")
|
||||
|
||||
@ -1,462 +1,225 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step8 面板 - 机器学习预测
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Union
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout,
|
||||
QPushButton, QCheckBox, QComboBox, QLineEdit, QMessageBox,
|
||||
QFileDialog, QRadioButton, QListWidget, QAbstractItemView, QHBoxLayout,
|
||||
QListWidgetItem,
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox, QScrollArea
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
|
||||
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。
|
||||
支持两种打包模式：
|
||||
1. --onedir 模式：文件在 exe_root/_internal/ 下 → 检查 _internal 目录
|
||||
2. --onefile 模式：文件在 sys._MEIPASS 平铺目录
|
||||
"""
|
||||
# 优先检查 PyInstaller onefile 模式（文件平铺在 _MEIPASS 下）
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal_path = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal_path):
|
||||
return internal_path
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
|
||||
# 兼容 PyInstaller onedir 模式的 _internal 目录（exe 同级目录下）
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal_path = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal_path):
|
||||
return internal_path
|
||||
|
||||
# 开发环境下：基于当前文件 (step8_panel.py) 的绝对路径进行回溯
|
||||
# 当前在 src/gui/panels/，目标在 src/gui/model/
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
target_path = base_dir / os.path.basename(relative_path)
|
||||
return str(target_path)
|
||||
|
||||
class Step8Panel(QWidget):
|
||||
"""步骤8：机器学习预测"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.external_models_dict = {} # {subdir_name: model_obj, ...}
|
||||
self.external_model_dir = "" # 母文件夹路径（隐藏）
|
||||
self.index_checkboxes: Dict[str, QCheckBox] = {}
|
||||
# 标识为 waterindex.csv，目录跳转逻辑在 get_resource_path 中
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
|
||||
self.init_ui()
|
||||
# 延迟一小会儿加载，确保UI框架已就绪
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
|
||||
# -------- 模型来源选择（单选按钮组） --------
|
||||
source_group = QGroupBox("模型来源")
|
||||
source_layout = QVBoxLayout()
|
||||
# 1. 路径展示区 (半透明只读)
|
||||
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)
|
||||
# 视觉微调：提示用户这是内置的
|
||||
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)
|
||||
|
||||
self.use_trained_model = QRadioButton("使用当前训练流程的模型")
|
||||
self.use_external_model = QRadioButton("导入本地预训练模型 (.joblib)")
|
||||
self.use_trained_model.setChecked(True)
|
||||
source_layout.addWidget(self.use_trained_model)
|
||||
source_layout.addWidget(self.use_external_model)
|
||||
# 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)
|
||||
|
||||
self.use_trained_model.toggled.connect(self._on_model_source_changed)
|
||||
self.use_external_model.toggled.connect(self._on_model_source_changed)
|
||||
# 3. 公式选择区
|
||||
self.formula_group = QGroupBox("待计算水质指数勾选")
|
||||
formula_outer_layout = QVBoxLayout()
|
||||
|
||||
source_group.setStyleSheet("""
|
||||
QRadioButton {
|
||||
font-size: 13px;
|
||||
spacing: 8px;
|
||||
}
|
||||
QRadioButton::indicator {
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
border-radius: 9px;
|
||||
border: 2px solid #A0A0A0;
|
||||
background-color: #FFFFFF;
|
||||
}
|
||||
QRadioButton::indicator:hover {
|
||||
border: 2px solid #0078D7;
|
||||
}
|
||||
QRadioButton::indicator:checked {
|
||||
background-color: #0078D7;
|
||||
border: 2px solid #0078D7;
|
||||
}
|
||||
""")
|
||||
btn_layout = QHBoxLayout()
|
||||
self.select_all_btn = QPushButton("全选")
|
||||
self.deselect_all_btn = QPushButton("清空")
|
||||
self.select_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addStretch()
|
||||
|
||||
source_group.setLayout(source_layout)
|
||||
layout.addWidget(source_group)
|
||||
self.refresh_button = QPushButton("手动重新加载公式")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
|
||||
# -------- 外部模型文件选择（条件显示） --------
|
||||
self.external_model_widget = FileSelectWidget(
|
||||
"模型母文件夹:",
|
||||
"Directories"
|
||||
)
|
||||
self.external_model_widget.browse_btn.clicked.disconnect()
|
||||
self.external_model_widget.browse_btn.clicked.connect(self._scan_external_model_dir)
|
||||
self.external_model_widget.setVisible(False)
|
||||
layout.addWidget(self.external_model_widget)
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
|
||||
# -------- 已扫描模型列表（条件显示） --------
|
||||
self.model_list_group = QGroupBox("选择参与预测的模型")
|
||||
self.model_list_group.setVisible(False)
|
||||
model_list_layout = QVBoxLayout()
|
||||
# 核心滚动区
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(300) # 强制最小高度，防止塌陷
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QGridLayout(self.scroll_content)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop) # 靠顶对齐
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
|
||||
self.model_list = QListWidget()
|
||||
self.model_list.setMaximumHeight(130)
|
||||
self.model_list.setSelectionMode(QAbstractItemView.NoSelection)
|
||||
self.model_list.setStyleSheet("""
|
||||
QListWidget {
|
||||
border: 1px solid #C0C0C0;
|
||||
border-radius: 4px;
|
||||
background-color: #FFFFFF;
|
||||
font-size: 12px;
|
||||
}
|
||||
QListWidget::item {
|
||||
padding: 4px 6px;
|
||||
border-bottom: 1px solid #F0F0F0;
|
||||
}
|
||||
QListWidget::item:selected {
|
||||
background-color: transparent;
|
||||
}
|
||||
""")
|
||||
model_list_layout.addWidget(self.model_list)
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
|
||||
btn_row = QHBoxLayout()
|
||||
self.btn_select_all = QPushButton("全选")
|
||||
self.btn_select_all.setMaximumWidth(80)
|
||||
self.btn_select_all.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
|
||||
self.btn_select_all.clicked.connect(self._select_all_models)
|
||||
# 4. 输出与运行
|
||||
output_group = QGroupBox("结果输出")
|
||||
output_layout = QVBoxLayout()
|
||||
self.output_file_widget = FileSelectWidget("保存路径:", "CSV Files (*.csv)", mode="save")
|
||||
output_layout.addWidget(self.output_file_widget)
|
||||
output_group.setLayout(output_layout)
|
||||
main_layout.addWidget(output_group)
|
||||
|
||||
self.btn_select_none = QPushButton("全不选")
|
||||
self.btn_select_none.setMaximumWidth(80)
|
||||
self.btn_select_none.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
|
||||
self.btn_select_none.clicked.connect(self._select_none_models)
|
||||
|
||||
btn_row.addWidget(self.btn_select_all)
|
||||
btn_row.addWidget(self.btn_select_none)
|
||||
btn_row.addStretch()
|
||||
model_list_layout.addLayout(btn_row)
|
||||
|
||||
self.model_list_group.setLayout(model_list_layout)
|
||||
layout.addWidget(self.model_list_group)
|
||||
|
||||
# -------- 采样光谱CSV文件（用于独立运行）--------
|
||||
self.sampling_csv_file = FileSelectWidget(
|
||||
"采样光谱CSV:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.sampling_csv_file)
|
||||
|
||||
# 模型目录（用于独立运行）
|
||||
self.models_dir_file = FileSelectWidget(
|
||||
"模型目录:",
|
||||
"Directories;;All Files (*.*)"
|
||||
)
|
||||
self.models_dir_file.label.setText("模型目录:")
|
||||
self.models_dir_file.browse_btn.clicked.disconnect()
|
||||
self.models_dir_file.browse_btn.clicked.connect(self.browse_models_dir)
|
||||
layout.addWidget(self.models_dir_file)
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("预测参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
self.metric = QComboBox()
|
||||
self.metric.addItems(['test_r2', 'test_rmse', 'test_mae'])
|
||||
params_layout.addRow("模型选择指标:", self.metric)
|
||||
|
||||
self.prediction_column = QLineEdit()
|
||||
self.prediction_column.setText("prediction")
|
||||
params_layout.addRow("预测列名:", self.prediction_column)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
# 输出路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出路径:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
main_layout.addWidget(self.enable_checkbox)
|
||||
|
||||
# 独立运行按钮
|
||||
self.run_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
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)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
self.setLayout(main_layout)
|
||||
|
||||
def _on_model_source_changed(self, checked: bool):
|
||||
"""单选按钮切换：控制外部模型文件选择控件的显示/隐藏"""
|
||||
if not checked:
|
||||
def _auto_load_formulas(self):
|
||||
"""启动时自动加载逻辑"""
|
||||
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
|
||||
is_external = self.use_external_model.isChecked()
|
||||
self.external_model_widget.setVisible(is_external)
|
||||
self.model_list_group.setVisible(is_external)
|
||||
if not is_external:
|
||||
self.external_models_dict = {}
|
||||
self.external_model_dir = ""
|
||||
self._clear_model_list()
|
||||
|
||||
def _scan_external_model_dir(self):
|
||||
"""浏览模型母文件夹，自动扫描子目录中的 .joblib 文件"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "7_Supervised_Model_Training")
|
||||
dir_path = QFileDialog.getExistingDirectory(
|
||||
self,
|
||||
"选择模型母文件夹",
|
||||
default,
|
||||
)
|
||||
if not dir_path:
|
||||
return
|
||||
|
||||
self.external_model_dir = dir_path
|
||||
models_found = {}
|
||||
errors = []
|
||||
|
||||
try:
|
||||
import joblib
|
||||
# 清理旧列表
|
||||
for i in reversed(range(self.formula_layout.count())):
|
||||
widget = self.formula_layout.itemAt(i).widget()
|
||||
if widget: widget.deleteLater()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
for subentry in os.scandir(dir_path):
|
||||
if not subentry.is_dir():
|
||||
continue
|
||||
subdir_name = subentry.name
|
||||
joblib_files = [
|
||||
f for f in os.scandir(subentry.path)
|
||||
if f.is_file() and f.name.lower().endswith(".joblib")
|
||||
]
|
||||
if not joblib_files:
|
||||
continue
|
||||
# 每个子目录只取第一个 .joblib 文件（与 batch 逻辑一致）
|
||||
joblib_path = joblib_files[0].path
|
||||
# 鲁棒性读取：尝试不同编码
|
||||
for encoding in ['utf-8', 'gbk', 'utf-8-sig']:
|
||||
try:
|
||||
loaded = joblib.load(joblib_path)
|
||||
if isinstance(loaded, dict) and "model" in loaded:
|
||||
model_obj = loaded["model"]
|
||||
elif hasattr(loaded, "predict"):
|
||||
model_obj = loaded
|
||||
else:
|
||||
errors.append(f"{subdir_name}: 无法识别的格式 {type(loaded).__name__}")
|
||||
continue
|
||||
models_found[subdir_name] = model_obj
|
||||
except Exception as e:
|
||||
errors.append(f"{subdir_name}: {type(e).__name__}: {e}")
|
||||
df = pd.read_csv(path, encoding=encoding)
|
||||
if 'Formula_Name' in df.columns: break
|
||||
except: continue
|
||||
|
||||
if 'Formula_Name' not in df.columns:
|
||||
if not silent: QMessageBox.critical(self, "错误", "CSV文件缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
names = df['Formula_Name'].dropna().unique().tolist()
|
||||
|
||||
row, col = 0, 0
|
||||
for name in names:
|
||||
name = str(name).strip()
|
||||
if not name: continue
|
||||
cb = QCheckBox(name)
|
||||
cb.setChecked(True)
|
||||
self.index_checkboxes[name] = cb
|
||||
self.formula_layout.addWidget(cb, row, col)
|
||||
col += 1
|
||||
if col >= 3:
|
||||
col = 0
|
||||
row += 1
|
||||
|
||||
# 强制UI更新
|
||||
self.scroll_content.adjustSize()
|
||||
print(f"✅ 成功加载 {len(self.index_checkboxes)} 个公式")
|
||||
|
||||
except Exception as e:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"扫描失败",
|
||||
f"遍历模型目录时发生错误：\n{type(e).__name__}: {e}",
|
||||
)
|
||||
return
|
||||
if not silent: QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
|
||||
|
||||
if not models_found:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"未找到模型",
|
||||
f"在「{dir_path}」的子目录中未发现任何 .joblib 文件。\n"
|
||||
"请确认每个水质参数对应一个子文件夹，内含 .joblib 模型文件。",
|
||||
)
|
||||
self.external_model_widget.set_path("")
|
||||
self.external_models_dict = {}
|
||||
self._clear_model_list()
|
||||
return
|
||||
def select_all_formulas(self):
|
||||
for cb in self.index_checkboxes.values(): cb.setChecked(True)
|
||||
|
||||
self.external_models_dict = models_found
|
||||
self._populate_model_list(models_found)
|
||||
names = sorted(models_found.keys())
|
||||
display = f"已识别到 {len(names)} 个模型: {', '.join(names)}"
|
||||
self.external_model_widget.set_path(display)
|
||||
self.external_model_widget.line_edit.setStyleSheet("color: #0078D7; font-weight: bold;")
|
||||
|
||||
err_lines = "\n".join(errors) if errors else "无"
|
||||
QMessageBox.information(
|
||||
self,
|
||||
"模型扫描完成",
|
||||
f"成功加载 {len(models_found)} 个模型：\n{display}\n\n"
|
||||
f"加载失败 {len(errors)} 个：\n{err_lines}",
|
||||
)
|
||||
|
||||
def _populate_model_list(self, models_dict):
|
||||
"""将扫描到的模型填充到 QListWidget，每个条目可勾选，默认全选"""
|
||||
self.model_list.clear()
|
||||
for name in sorted(models_dict.keys()):
|
||||
item = QListWidgetItem(name)
|
||||
item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
|
||||
item.setCheckState(Qt.Checked)
|
||||
self.model_list.addItem(item)
|
||||
|
||||
def _clear_model_list(self):
|
||||
"""清空模型列表"""
|
||||
self.model_list.clear()
|
||||
|
||||
def _select_all_models(self):
|
||||
"""全选：设置所有条目为 Checked"""
|
||||
for i in range(self.model_list.count()):
|
||||
self.model_list.item(i).setCheckState(Qt.Checked)
|
||||
|
||||
def _select_none_models(self):
|
||||
"""全不选：设置所有条目为 Unchecked"""
|
||||
for i in range(self.model_list.count()):
|
||||
self.model_list.item(i).setCheckState(Qt.Unchecked)
|
||||
|
||||
def _get_checked_models_dict(self):
|
||||
"""从列表中提取用户勾选的模型，组装成字典返回"""
|
||||
result = {}
|
||||
for i in range(self.model_list.count()):
|
||||
item = self.model_list.item(i)
|
||||
if item.checkState() == Qt.Checked:
|
||||
name = item.text()
|
||||
if name in self.external_models_dict:
|
||||
result[name] = self.external_models_dict[name]
|
||||
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
|
||||
|
||||
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 界面读取全湖采样点 CSV 路径
|
||||
if main_window and hasattr(main_window, 'step7_panel'):
|
||||
step7_widget = getattr(main_window.step7_panel, 'output_file', None)
|
||||
step7_output_path = ""
|
||||
if hasattr(step7_widget, 'get_path'):
|
||||
step7_output_path = step7_widget.get_path() or ""
|
||||
elif hasattr(step7_widget, 'text'):
|
||||
step7_output_path = step7_widget.text() or ""
|
||||
|
||||
if step7_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step7_output_path):
|
||||
step7_output_path = os.path.join(self.work_dir or '', step7_output_path).replace('\\', '/')
|
||||
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 Step6 界面读取监督模型目录
|
||||
if main_window and hasattr(main_window, 'step6_panel'):
|
||||
step6_widget = getattr(main_window.step6_panel, 'output_dir', None)
|
||||
step6_models_dir = ""
|
||||
if hasattr(step6_widget, 'get_path'):
|
||||
step6_models_dir = step6_widget.get_path() or ""
|
||||
elif hasattr(step6_widget, 'text'):
|
||||
step6_models_dir = step6_widget.text() or ""
|
||||
|
||||
if step6_models_dir:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step6_models_dir):
|
||||
step6_models_dir = os.path.join(self.work_dir or '', step6_models_dir).replace('\\', '/')
|
||||
existing_models = self.models_dir_file.get_path()
|
||||
if not existing_models or not existing_models.strip():
|
||||
self.models_dir_file.set_path(step6_models_dir)
|
||||
|
||||
# 3. 自动填充输出路径（机器学习预测目录）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Machine_Learning_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()
|
||||
|
||||
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_models_dir(self):
|
||||
"""浏览模型目录"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "7_Supervised_Model_Training")
|
||||
dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", default)
|
||||
if dir_path:
|
||||
self.models_dir_file.set_path(dir_path)
|
||||
def deselect_all_formulas(self):
|
||||
for cb in self.index_checkboxes.values(): cb.setChecked(False)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
config = {
|
||||
'metric': self.metric.currentText(),
|
||||
'prediction_column': self.prediction_column.text(),
|
||||
selected = [n for n, cb in self.index_checkboxes.items() if cb.isChecked()]
|
||||
return {
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'output_file': self.output_file_widget.get_path(),
|
||||
'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
|
||||
models_dir = self.models_dir_file.get_path()
|
||||
if models_dir:
|
||||
config['models_dir'] = models_dir
|
||||
output_path = self.output_file.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'metric' in config:
|
||||
idx = self.metric.findText(config['metric'])
|
||||
if idx >= 0:
|
||||
self.metric.setCurrentIndex(idx)
|
||||
if 'prediction_column' in config:
|
||||
self.prediction_column.setText(config['prediction_column'])
|
||||
if 'sampling_csv_path' in config:
|
||||
self.sampling_csv_file.set_path(config['sampling_csv_path'])
|
||||
if 'models_dir' in config:
|
||||
self.models_dir_file.set_path(config['models_dir'])
|
||||
if 'output_path' in config:
|
||||
self.output_file.set_path(config['output_path'])
|
||||
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 n, cb in self.index_checkboxes.items(): cb.setChecked(n in sel)
|
||||
if 'output_file' in config: self.output_file_widget.set_path(config['output_file'])
|
||||
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, 'step5_panel'):
|
||||
p5 = main.step5_panel.output_file.get_path() # 修正：变量名对齐
|
||||
if p5:
|
||||
if not os.path.isabs(p5): p5 = os.path.join(self.work_dir or '', p5).replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
|
||||
if self.work_dir:
|
||||
out = os.path.join(self.work_dir, "6_water_quality_indices", "training_spectra_indices.csv").replace('\\', '/')
|
||||
self.output_file_widget.set_path(out)
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤8"""
|
||||
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！")
|
||||
config = self.get_config()
|
||||
if not config['training_csv_path']:
|
||||
QMessageBox.warning(self, "提示", "请先选择输入数据")
|
||||
return
|
||||
|
||||
# 外部模型优先：用户选择了"导入本地预训练模型"
|
||||
if self.use_external_model.isChecked():
|
||||
if not self.external_models_dict:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"模型未加载",
|
||||
"请先点击「浏览...」按钮选择模型母文件夹！",
|
||||
)
|
||||
return
|
||||
# 只传递用户勾选的模型
|
||||
checked_dict = self._get_checked_models_dict()
|
||||
if not checked_dict:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"未选择模型",
|
||||
"请至少勾选一个模型参与预测！",
|
||||
)
|
||||
return
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {
|
||||
'step8': self.get_config(),
|
||||
'_external_models_dict': checked_dict,
|
||||
'_external_model_dir': self.external_model_dir,
|
||||
}
|
||||
main_window.run_single_step('step8', config)
|
||||
return
|
||||
|
||||
# 默认流程：使用模型目录
|
||||
models_dir = self.models_dir_file.get_path()
|
||||
if not models_dir:
|
||||
QMessageBox.warning(self, "输入错误", "请选择模型目录！")
|
||||
return
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step8': self.get_config()}
|
||||
main_window.run_single_step('step8', config)
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, 'run_single_step'): parent = parent.parent()
|
||||
if parent: parent.run_single_step('step8', {'step8': config})
|
||||
@ -1,206 +1,158 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step9 面板 - 分布图生成
|
||||
Step9 面板 - 自定义回归分析
|
||||
"""
|
||||
|
||||
import os
|
||||
import traceback
|
||||
from pathlib import Path
|
||||
from typing import List, Optional
|
||||
from typing import Dict
|
||||
|
||||
from PyQt5.QtCore import Qt, QThread, pyqtSignal
|
||||
import pandas as pd
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QHBoxLayout,
|
||||
QLabel, QCheckBox, QPushButton, QLineEdit, QDoubleSpinBox,
|
||||
QRadioButton, QButtonGroup, QMessageBox, QFileDialog,
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QCheckBox, QPushButton,
|
||||
QScrollArea, QMessageBox,
|
||||
)
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
# Pipeline 可用性（与 core/worker_thread.py 保持一致）
|
||||
try:
|
||||
from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
|
||||
PIPELINE_AVAILABLE = True
|
||||
except ImportError:
|
||||
PIPELINE_AVAILABLE = False
|
||||
|
||||
|
||||
class Step9BatchThread(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)
|
||||
|
||||
def __init__(self, work_dir: str, csv_paths: List[str], step9_kwargs: dict, output_dir_optional: Optional[str]):
|
||||
super().__init__()
|
||||
self.work_dir = work_dir
|
||||
self.csv_paths = csv_paths
|
||||
self.step9_kwargs = step9_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.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
|
||||
pipeline = WaterQualityInversionPipeline(work_dir=self.work_dir)
|
||||
n = len(self.csv_paths)
|
||||
for i, csv_p in enumerate(self.csv_paths):
|
||||
self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
|
||||
kw = {**self.step9_kwargs, "prediction_csv_path": csv_p, "skip_dependency_check": True}
|
||||
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
|
||||
pipeline.step9_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 Step9Panel(QWidget):
|
||||
"""步骤9：分布图生成"""
|
||||
"""步骤9：自定义回归分析"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self._batch_thread = None
|
||||
self.x_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.y_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.method_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.csv_columns = []
|
||||
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）。"
|
||||
"完整流程中预测 CSV 由步骤11、12、13 自动传入，无需在此选择。"
|
||||
)
|
||||
hint.setWordWrap(True)
|
||||
hint.setStyleSheet(
|
||||
f"color: {ModernStylesheet.COLORS.get('text_secondary', '#666')};"
|
||||
)
|
||||
hint = QLabel("指定自变量与因变量列，批量尝试不同回归方法")
|
||||
hint.setStyleSheet("color: #666; font-size: 11px;")
|
||||
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)
|
||||
# CSV文件选择
|
||||
csv_group = QGroupBox("数据文件")
|
||||
csv_layout = QVBoxLayout()
|
||||
|
||||
# ---------- 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:",
|
||||
self.csv_file = FileSelectWidget(
|
||||
"输入CSV文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.prediction_csv_file)
|
||||
self.csv_file.line_edit.textChanged.connect(self.on_csv_file_changed)
|
||||
csv_layout.addWidget(self.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)
|
||||
self.refresh_btn = QPushButton("刷新列信息")
|
||||
self.refresh_btn.clicked.connect(self.refresh_csv_columns)
|
||||
csv_layout.addWidget(self.refresh_btn)
|
||||
|
||||
self.recursive_csv_cb = QCheckBox("包含子文件夹（递归扫描 *.csv）")
|
||||
layout.addWidget(self.recursive_csv_cb)
|
||||
csv_group.setLayout(csv_layout)
|
||||
layout.addWidget(csv_group)
|
||||
|
||||
self.boundary_file = FileSelectWidget(
|
||||
"边界文件:",
|
||||
"Shapefiles (*.shp);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.boundary_file)
|
||||
# 自变量选择
|
||||
x_group = QGroupBox("自变量列选择 (可多选)")
|
||||
x_layout = QVBoxLayout()
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("生成参数")
|
||||
params_layout = QFormLayout()
|
||||
x_scroll = QScrollArea()
|
||||
x_scroll.setWidgetResizable(True)
|
||||
x_scroll.setMinimumHeight(250)
|
||||
x_scroll.setMaximumHeight(350)
|
||||
|
||||
self.resolution = QDoubleSpinBox()
|
||||
self.resolution.setRange(1, 1000)
|
||||
self.resolution.setValue(30)
|
||||
params_layout.addRow("分辨率(米):", self.resolution)
|
||||
x_widget = QWidget()
|
||||
self.x_columns_layout = QGridLayout()
|
||||
x_widget.setLayout(self.x_columns_layout)
|
||||
|
||||
self.input_crs = QLineEdit()
|
||||
self.input_crs.setText("EPSG:32651")
|
||||
params_layout.addRow("输入坐标系:", self.input_crs)
|
||||
x_scroll.setWidget(x_widget)
|
||||
x_layout.addWidget(x_scroll)
|
||||
|
||||
self.output_crs = QLineEdit()
|
||||
self.output_crs.setText("EPSG:4326")
|
||||
params_layout.addRow("输出坐标系:", self.output_crs)
|
||||
x_btn_layout = QHBoxLayout()
|
||||
self.x_select_all = QPushButton("全选")
|
||||
self.x_deselect_all = QPushButton("全不选")
|
||||
self.x_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, True))
|
||||
self.x_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, False))
|
||||
x_btn_layout.addWidget(self.x_select_all)
|
||||
x_btn_layout.addWidget(self.x_deselect_all)
|
||||
x_btn_layout.addStretch()
|
||||
x_layout.addLayout(x_btn_layout)
|
||||
|
||||
self.show_points = QCheckBox("显示采样点")
|
||||
params_layout.addRow("", self.show_points)
|
||||
x_group.setLayout(x_layout)
|
||||
layout.addWidget(x_group)
|
||||
|
||||
self.use_diffusion = QCheckBox("启用距离扩散")
|
||||
self.use_diffusion.setChecked(True)
|
||||
params_layout.addRow("", self.use_diffusion)
|
||||
# 因变量选择
|
||||
y_group = QGroupBox("因变量列选择 (可多选)")
|
||||
y_layout = QVBoxLayout()
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
y_scroll = QScrollArea()
|
||||
y_scroll.setWidgetResizable(True)
|
||||
y_scroll.setMinimumHeight(200)
|
||||
y_scroll.setMaximumHeight(300)
|
||||
|
||||
y_widget = QWidget()
|
||||
self.y_columns_layout = QGridLayout()
|
||||
y_widget.setLayout(self.y_columns_layout)
|
||||
|
||||
y_scroll.setWidget(y_widget)
|
||||
y_layout.addWidget(y_scroll)
|
||||
|
||||
y_btn_layout = QHBoxLayout()
|
||||
self.y_select_all = QPushButton("全选")
|
||||
self.y_deselect_all = QPushButton("全不选")
|
||||
self.y_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, True))
|
||||
self.y_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, False))
|
||||
y_btn_layout.addWidget(self.y_select_all)
|
||||
y_btn_layout.addWidget(self.y_deselect_all)
|
||||
y_btn_layout.addStretch()
|
||||
y_layout.addLayout(y_btn_layout)
|
||||
|
||||
y_group.setLayout(y_layout)
|
||||
layout.addWidget(y_group)
|
||||
|
||||
# 回归方法选择
|
||||
method_group = QGroupBox("回归方法选择 (可多选)")
|
||||
method_layout = QVBoxLayout()
|
||||
|
||||
method_grid = QGridLayout()
|
||||
regression_methods = [
|
||||
'linear', 'exponential', 'power', 'logarithmic',
|
||||
'polynomial', 'hyperbolic', 'sigmoidal'
|
||||
]
|
||||
|
||||
for i, method in enumerate(regression_methods):
|
||||
checkbox = QCheckBox(method)
|
||||
if method in ['linear', 'exponential', 'power', 'logarithmic']:
|
||||
checkbox.setChecked(True)
|
||||
self.method_checkboxes[method] = checkbox
|
||||
method_grid.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
method_layout.addLayout(method_grid)
|
||||
|
||||
method_btn_layout = QHBoxLayout()
|
||||
self.method_select_all = QPushButton("全选")
|
||||
self.method_deselect_all = QPushButton("全不选")
|
||||
self.method_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, True))
|
||||
self.method_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, False))
|
||||
method_btn_layout.addWidget(self.method_select_all)
|
||||
method_btn_layout.addWidget(self.method_deselect_all)
|
||||
method_btn_layout.addStretch()
|
||||
method_layout.addLayout(method_btn_layout)
|
||||
|
||||
method_group.setLayout(method_layout)
|
||||
layout.addWidget(method_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)
|
||||
output_group = QGroupBox("输出设置")
|
||||
output_layout = QFormLayout()
|
||||
|
||||
self.output_dir = QLineEdit()
|
||||
self.output_dir.setText("") # 路径由 update_from_config 根据 work_dir 自动填充
|
||||
output_layout.addRow("输出目录名:", self.output_dir)
|
||||
|
||||
output_group.setLayout(output_layout)
|
||||
layout.addWidget(output_group)
|
||||
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
@ -216,119 +168,120 @@ class Step9Panel(QWidget):
|
||||
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_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
def _toggle_input_mode(self):
|
||||
"""槽函数：根据单选框状态动态显示/隐藏对应的输入组件。"""
|
||||
folder_mode = self.mode_folder_rb.isChecked()
|
||||
# 单个 CSV 模式：显示单文件选择，隐藏文件夹选择
|
||||
self.prediction_csv_file.setVisible(not folder_mode)
|
||||
# 文件夹批量模式：显示文件夹选择 + 递归选项，隐藏单文件选择
|
||||
self._folder_row_widget.setVisible(folder_mode)
|
||||
self.recursive_csv_cb.setVisible(folder_mode)
|
||||
def on_csv_file_changed(self):
|
||||
"""CSV文件改变时自动刷新列信息"""
|
||||
self.refresh_csv_columns()
|
||||
|
||||
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 refresh_csv_columns(self):
|
||||
"""刷新CSV文件的列信息"""
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
return
|
||||
|
||||
def browse_prediction_csv_dir(self):
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "11_12_13_predictions")
|
||||
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)
|
||||
try:
|
||||
df = pd.read_csv(csv_path, nrows=0)
|
||||
self.csv_columns = list(df.columns)
|
||||
self.update_column_widgets()
|
||||
except Exception as e:
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
print(f"读取CSV列信息失败: {e}")
|
||||
|
||||
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 update_column_widgets(self):
|
||||
"""更新列选择组件"""
|
||||
for checkbox in self.x_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.x_column_checkboxes.clear()
|
||||
|
||||
def _step9_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(),
|
||||
}
|
||||
for checkbox in self.y_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.y_column_checkboxes.clear()
|
||||
|
||||
if not self.csv_columns:
|
||||
return
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd', 'b']):
|
||||
checkbox.setChecked(True)
|
||||
self.x_column_checkboxes[col] = checkbox
|
||||
self.x_columns_layout.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['chl', 'tn', 'tp', 'turbidity', 'do', 'ph', 'conductivity']):
|
||||
checkbox.setChecked(True)
|
||||
self.y_column_checkboxes[col] = checkbox
|
||||
self.y_columns_layout.addWidget(checkbox, i // 2, i % 2)
|
||||
|
||||
self.x_columns_layout.update()
|
||||
self.y_columns_layout.update()
|
||||
|
||||
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()
|
||||
config = {
|
||||
'step9_batch_mode': 'folder' if folder_mode else 'single',
|
||||
'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),
|
||||
'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(),
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
selected_methods = 'all'
|
||||
|
||||
return {
|
||||
'csv_path': self.csv_file.get_path() or None,
|
||||
'x_columns': selected_x_columns,
|
||||
'y_columns': selected_y_columns,
|
||||
'methods': selected_methods,
|
||||
'output_dir': self.output_dir.text().strip() or None,
|
||||
'enabled': self.enable_checkbox.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('step9_batch_mode', 'single')
|
||||
if mode == 'folder':
|
||||
self.mode_folder_rb.setChecked(True)
|
||||
else:
|
||||
self.mode_single_rb.setChecked(True)
|
||||
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 '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))
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
self.refresh_csv_columns()
|
||||
|
||||
if 'x_columns' in config:
|
||||
selected_x = set(config['x_columns']) if isinstance(config['x_columns'], list) else set()
|
||||
for col, checkbox in self.x_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_x)
|
||||
|
||||
if 'y_columns' in config:
|
||||
selected_y = set(config['y_columns']) if isinstance(config['y_columns'], list) else set()
|
||||
for col, checkbox in self.y_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_y)
|
||||
|
||||
if 'methods' in config:
|
||||
methods = config['methods']
|
||||
if isinstance(methods, list):
|
||||
selected_methods = set(methods)
|
||||
elif methods == 'all':
|
||||
selected_methods = set(self.method_checkboxes.keys())
|
||||
else:
|
||||
selected_methods = set()
|
||||
for method, checkbox in self.method_checkboxes.items():
|
||||
checkbox.setChecked(method in selected_methods)
|
||||
|
||||
if 'output_dir' in config:
|
||||
self.output_dir.setText(config['output_dir'] or "9_Custom_Regression_Modeling")
|
||||
if 'enabled' in config:
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
|
||||
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。
|
||||
"""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
|
||||
@ -344,190 +297,78 @@ class Step9Panel(QWidget):
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练光谱 CSV 路径
|
||||
main_window = self.window()
|
||||
if not main_window:
|
||||
return
|
||||
if main_window and hasattr(main_window, 'step5_panel'):
|
||||
step5_widget = getattr(main_window.step5_panel, 'output_file', None)
|
||||
step5_output_path = ""
|
||||
if hasattr(step5_widget, 'get_path'):
|
||||
step5_output_path = step5_widget.get_path() or ""
|
||||
elif hasattr(step5_widget, 'text'):
|
||||
step5_output_path = step5_widget.text() or ""
|
||||
|
||||
# 1. 尝试从 Step8 界面读取机器学习预测输出目录（最优先）
|
||||
pred_dir = None
|
||||
if hasattr(main_window, 'step8_panel'):
|
||||
step8_widget = getattr(main_window.step8_panel, 'output_file', None)
|
||||
step8_output = ""
|
||||
if hasattr(step8_widget, 'get_path'):
|
||||
step8_output = step8_widget.get_path() or ""
|
||||
elif hasattr(step8_widget, 'text'):
|
||||
step8_output = step8_widget.text() or ""
|
||||
|
||||
if step8_output:
|
||||
if step5_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_output):
|
||||
step8_output = os.path.join(self.work_dir or '', step8_output).replace('\\', '/')
|
||||
# 提取父目录后追加 Machine_Learning_Prediction（最底层真实子目录）
|
||||
base_pred_dir = str(Path(step8_output).parent)
|
||||
ml_pred_dir = Path(base_pred_dir) / "Machine_Learning_Prediction"
|
||||
pred_dir = str(ml_pred_dir) if ml_pred_dir.exists() else base_pred_dir
|
||||
if not os.path.isabs(step5_output_path):
|
||||
step5_output_path = os.path.join(self.work_dir or '', step5_output_path).replace('\\', '/')
|
||||
existing = self.csv_file.get_path()
|
||||
if not existing or not existing.strip():
|
||||
self.csv_file.set_path(step5_output_path)
|
||||
|
||||
# 2. 备选：从 Step8.5 界面读取非经验预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step8_5_panel'):
|
||||
step8_5_widget = getattr(main_window.step8_5_panel, 'output_file', None)
|
||||
step8_5_output = ""
|
||||
if hasattr(step8_5_widget, 'get_path'):
|
||||
step8_5_output = step8_5_widget.get_path() or ""
|
||||
elif hasattr(step8_5_widget, 'text'):
|
||||
step8_5_output = step8_5_widget.text() or ""
|
||||
|
||||
if step8_5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_5_output):
|
||||
step8_5_output = os.path.join(self.work_dir or '', step8_5_output).replace('\\', '/')
|
||||
pred_dir = str(Path(step8_5_output).parent)
|
||||
|
||||
# 3. 备选：从 Step8.75 界面读取自定义回归预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step8_75_panel'):
|
||||
step8_75_widget = getattr(main_window.step8_75_panel, 'output_dir_widget', None)
|
||||
step8_75_output = ""
|
||||
if hasattr(step8_75_widget, 'get_path'):
|
||||
step8_75_output = step8_75_widget.get_path() or ""
|
||||
elif hasattr(step8_75_widget, 'text'):
|
||||
step8_75_output = step8_75_widget.text() or ""
|
||||
|
||||
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）
|
||||
# 2. 自动填充输出目录（9_Custom_Regression_Modeling）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "14_visualization")
|
||||
output_dir = os.path.join(self.work_dir, "9_Custom_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)
|
||||
|
||||
# 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:
|
||||
# 未找到 .shp 时清空并提示用户手动选择矢量文件
|
||||
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。")
|
||||
existing_out = self.output_dir.text().strip()
|
||||
if not existing_out:
|
||||
self.output_dir.setText(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 browse_output_dir(self):
|
||||
"""浏览输出目录"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "14_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 run_step(self):
|
||||
"""独立运行步骤9"""
|
||||
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。")
|
||||
csv_path = self.csv_file.get_path()
|
||||
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入验证失败", "请选择输入CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "输入CSV文件不存在")
|
||||
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")
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_x_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个自变量列")
|
||||
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")
|
||||
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_y_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个因变量列")
|
||||
return
|
||||
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一种回归方法")
|
||||
return
|
||||
|
||||
config = self.get_config()
|
||||
|
||||
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'):
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step9', {'step9': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
return
|
||||
|
||||
if self.mode_folder_rb.isChecked():
|
||||
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._step9_base_pipeline_kwargs()
|
||||
out_dir_opt = (self.output_dir.get_path() or "").strip() or None
|
||||
self.run_button.setEnabled(False)
|
||||
self._batch_thread = Step9BatchThread(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)
|
||||
|
||||
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
|
||||
self._batch_thread.finished_ok.connect(self._on_step9_batch_ok, Qt.QueuedConnection)
|
||||
self._batch_thread.failed.connect(self._on_step9_batch_fail, Qt.QueuedConnection)
|
||||
self._batch_thread.finished.connect(lambda: self.run_button.setEnabled(True), 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")
|
||||
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('step9', {'step9': config})
|
||||
|
||||
def _on_step9_batch_ok(self, n: int):
|
||||
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_step9_batch_fail(self, err: str):
|
||||
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")
|
||||
|
||||
@ -1567,12 +1567,12 @@ class VisualizationPanel(QWidget):
|
||||
ml_dir.mkdir(parents=True, exist_ok=True)
|
||||
reg_dir.mkdir(parents=True, exist_ok=True)
|
||||
custom_dir.mkdir(parents=True, exist_ok=True)
|
||||
if hasattr(self, 'step8_panel') and hasattr(self.step8_panel, 'output_file'):
|
||||
self.step8_panel.output_file.set_path(str(ml_dir))
|
||||
if hasattr(self, 'step8_5_panel') and hasattr(self.step8_5_panel, 'output_file'):
|
||||
self.step8_5_panel.output_file.set_path(str(reg_dir))
|
||||
if hasattr(self, 'step8_75_panel') and hasattr(self.step8_75_panel, 'output_dir_widget'):
|
||||
self.step8_75_panel.output_dir_widget.set_path(str(custom_dir))
|
||||
if hasattr(self, 'step11_ml_panel') and hasattr(self.step11_ml_panel, 'output_file'):
|
||||
self.step11_ml_panel.output_file.set_path(str(ml_dir))
|
||||
if hasattr(self, 'step11_panel') and hasattr(self.step11_panel, 'output_file'):
|
||||
self.step11_panel.output_file.set_path(str(reg_dir))
|
||||
if hasattr(self, 'step12_panel') and hasattr(self.step12_panel, 'output_dir_widget'):
|
||||
self.step12_panel.output_dir_widget.set_path(str(custom_dir))
|
||||
print(f"预测输出目录已设置:\n ML: {ml_dir}\n Reg: {reg_dir}\n Custom: {custom_dir}")
|
||||
except Exception as e:
|
||||
print(f"设置预测输出目录失败: {e}")
|
||||
|
||||
@ -119,19 +119,22 @@ from src.gui.panels.step2_panel import Step2Panel
|
||||
from src.gui.panels.step3_panel import Step3Panel
|
||||
from src.gui.panels.step4_panel import Step4Panel
|
||||
from src.gui.panels.step5_panel import Step5Panel
|
||||
from src.gui.panels.step5_5_panel import Step5_5Panel
|
||||
from src.gui.panels.step6_panel import Step6Panel
|
||||
from src.gui.panels.step6_5_panel import Step6_5Panel
|
||||
from src.gui.panels.step6_75_panel import Step6_75Panel
|
||||
from src.gui.panels.step7_panel import Step7Panel
|
||||
from src.gui.panels.step8_panel import Step8Panel
|
||||
from src.gui.panels.step8_5_panel import Step8_5Panel
|
||||
from src.gui.panels.step8_75_panel import Step8_75Panel
|
||||
from src.gui.panels.step9_panel import Step9Panel
|
||||
from src.gui.panels.step8_panel import Step8Panel # was step5_5_panel
|
||||
from src.gui.panels.step7_panel import Step7Panel # was step6_panel
|
||||
from src.gui.panels.step8_non_empirical_panel import Step8NonEmpiricalPanel # was step6_5_panel
|
||||
from src.gui.panels.step9_panel import Step9Panel # was step6_75_panel
|
||||
from src.gui.panels.step10_panel import Step10Panel # was step7_panel
|
||||
from src.gui.panels.step11_ml_panel import Step11MlPanel # ML prediction (step11_ml)
|
||||
from src.gui.panels.step11_panel import Step11Panel # was step8_5_panel
|
||||
from src.gui.panels.step12_panel import Step12Panel # was step8_75_panel
|
||||
from src.gui.panels.step14_panel import Step14Panel # was step9_panel
|
||||
from src.gui.dialogs import BandConfirmDialog, AISettingsDialog
|
||||
from src.gui.panels.visualization_panel import VisualizationPanel
|
||||
from src.gui.panels.report_generation_panel import ReportGenerationPanel
|
||||
|
||||
# Pipeline 核心异常（用于预检弹窗）
|
||||
from src.core.pipeline.runner import PipelineHalt
|
||||
|
||||
# Matplotlib相关导入 (推迟并加入底层防爆保护)
|
||||
import matplotlib
|
||||
try:
|
||||
@ -152,6 +155,9 @@ from src.gui.core.worker_thread import (
|
||||
check_pipeline_dependencies,
|
||||
diagnose_pipeline_import_error,
|
||||
)
|
||||
# 预检交互对话框
|
||||
from src.gui.core.preflight_dialog import PreflightDialog
|
||||
from src.gui.core.pipeline_mode_dialog import PipelineModeDialog
|
||||
|
||||
|
||||
def _viz_training_spectra_csv_path(work_path: Path) -> Path:
|
||||
@ -1384,31 +1390,31 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step5': {
|
||||
'training_spectra': '5_training_spectra/training_spectra.csv'
|
||||
},
|
||||
'step5_5': {
|
||||
'step8': {
|
||||
'water_indices': '6_water_quality_indices/water_quality_indices.csv'
|
||||
},
|
||||
'step6': {
|
||||
'step7': {
|
||||
'models': '7_Supervised_Model_Training/' # 目录，包含各参数子目录
|
||||
},
|
||||
'step6_5': {
|
||||
'step8_non_empirical_modeling': {
|
||||
'regression_models': '8_Regression_Modeling/' # 目录，包含各参数子目录
|
||||
},
|
||||
'step6_75': {
|
||||
'step9': {
|
||||
'custom_regression_models': '9_Custom_Regression_Modeling/' # 目录
|
||||
},
|
||||
'step7': {
|
||||
'step10': {
|
||||
'sampling_points': '10_sampling/sampling_spectra.csv'
|
||||
},
|
||||
'step8': {
|
||||
'step11_ml': {
|
||||
'predictions': '11_12_13_predictions/Machine_Learning_Prediction/' # 目录，包含机器学习预测结果
|
||||
},
|
||||
'step8_5': {
|
||||
'step11': {
|
||||
'regression_predictions': '11_12_13_predictions/Non_Empirical_Prediction/' # 目录，包含非经验模型预测结果
|
||||
},
|
||||
'step8_75': {
|
||||
'step12': {
|
||||
'custom_predictions': '11_12_13_predictions/Custom_Regression_Prediction/' # 目录，包含自定义回归预测结果
|
||||
},
|
||||
'step9': {
|
||||
'step14': {
|
||||
'distribution_maps': '14_visualization/' # 目录，包含专题图
|
||||
}
|
||||
}
|
||||
@ -1432,37 +1438,37 @@ class WaterQualityGUI(QMainWindow):
|
||||
'boundary_mask_path': ('step1', 'water_mask', 'boundary_mask_file'), # 步骤5可选水体掩膜
|
||||
'glint_mask_path': ('step2', 'glint_mask', 'glint_mask_file') # 步骤5可选耀斑掩膜
|
||||
},
|
||||
'step5_5': {
|
||||
'training_csv_path': ('step5', 'training_spectra', 'output_file') # 步骤5.5需要步骤5输出的训练光谱
|
||||
},
|
||||
'step6': {
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤6需要训练光谱数据
|
||||
},
|
||||
'step6_5': {
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤6.5需要训练光谱数据
|
||||
},
|
||||
'step6_75': {
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤6.75需要训练光谱数据
|
||||
'step8': {
|
||||
'training_csv_path': ('step5', 'training_spectra', 'output_file') # 步骤8需要步骤5输出的训练光谱
|
||||
},
|
||||
'step7': {
|
||||
'deglint_img_path': ('step3', 'deglint_image', 'deglint_img_file'), # 步骤7需要去耀斑影像
|
||||
'water_mask_path': ('step1', 'water_mask', 'water_mask_file'), # 步骤7需要水域掩膜
|
||||
'glint_mask_path': ('step2', 'glint_mask', 'glint_mask_file') # 步骤7可选耀斑掩膜
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤7需要训练光谱数据
|
||||
},
|
||||
'step8': {
|
||||
'sampling_csv_path': ('step7', 'sampling_points', 'sampling_csv_file'), # 步骤8需要采样点
|
||||
'models_dir': ('step6', 'models', 'models_dir_file') # 步骤8需要训练好的模型
|
||||
},
|
||||
'step8_5': {
|
||||
'sampling_csv_path': ('step7', 'sampling_points', 'sampling_csv_file'), # 步骤8.5需要采样点
|
||||
'models_dir': ('step6_5', 'regression_models', 'models_dir') # 步骤8.5需要回归模型
|
||||
},
|
||||
'step8_75': {
|
||||
'sampling_csv_path': ('step7', 'sampling_points', 'sampling_csv_file'), # 步骤8.75需要采样点
|
||||
'models_dir': ('step6_75', 'custom_regression_models', 'models_dir') # 步骤8.75需要自定义回归模型
|
||||
'step8_non_empirical_modeling': {
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤8非经验建模需要训练光谱数据
|
||||
},
|
||||
'step9': {
|
||||
'prediction_csv_path': ('step8', 'predictions', 'prediction_csv_file') # 步骤9需要预测结果CSV
|
||||
'csv_path': ('step5', 'training_spectra', 'csv_file') # 步骤9需要训练光谱数据
|
||||
},
|
||||
'step10': {
|
||||
'deglint_img_path': ('step3', 'deglint_image', 'deglint_img_file'), # 步骤10需要去耀斑影像
|
||||
'water_mask_path': ('step1', 'water_mask', 'water_mask_file'), # 步骤10需要水域掩膜
|
||||
'glint_mask_path': ('step2', 'glint_mask', 'glint_mask_file') # 步骤10可选耀斑掩膜
|
||||
},
|
||||
'step11_ml': {
|
||||
'sampling_csv_path': ('step10', 'sampling_points', 'sampling_csv_file'), # 步骤11ML需要采样点
|
||||
'models_dir': ('step7', 'models', 'models_dir_file') # 步骤11ML需要训练好的模型
|
||||
},
|
||||
'step11': {
|
||||
'sampling_csv_path': ('step10', 'sampling_points', 'sampling_csv_file'), # 步骤11需要采样点
|
||||
'models_dir': ('step8_non_empirical_modeling', 'regression_models', 'models_dir') # 步骤11需要回归模型
|
||||
},
|
||||
'step12': {
|
||||
'sampling_csv_path': ('step10', 'sampling_points', 'sampling_csv_file'), # 步骤12需要采样点
|
||||
'models_dir': ('step9', 'custom_regression_models', 'models_dir') # 步骤12需要自定义回归模型
|
||||
},
|
||||
'step14': {
|
||||
'prediction_csv_path': ('step11_ml', 'predictions', 'prediction_csv_file') # 步骤14需要预测结果CSV
|
||||
}
|
||||
}
|
||||
|
||||
@ -1545,7 +1551,7 @@ class WaterQualityGUI(QMainWindow):
|
||||
|
||||
def init_ui(self):
|
||||
"""初始化UI"""
|
||||
self.setWindowTitle("MegaCube-Water Quality V1.1")
|
||||
self.setWindowTitle("MegaCube-Water Quality V1.2")
|
||||
|
||||
# 获取屏幕可用区域（排除任务栏）
|
||||
screen_geometry = QApplication.primaryScreen().availableGeometry()
|
||||
@ -1730,7 +1736,7 @@ class WaterQualityGUI(QMainWindow):
|
||||
def create_banner_widget(self):
|
||||
"""创建横幅区域 - 支持自适应等比缩放"""
|
||||
# 横幅标题文字（方便后续直接修改版本号）
|
||||
self._APP_TITLE = "MegaCube-Water Quality V1.1"
|
||||
self._APP_TITLE = "MegaCube-Water Quality V1.2"
|
||||
|
||||
# 创建横幅容器
|
||||
banner_widget = QWidget()
|
||||
@ -1844,19 +1850,19 @@ class WaterQualityGUI(QMainWindow):
|
||||
"阶段二：样本数据准备 ": [
|
||||
("step4", "4. 数据标准化处理"),
|
||||
("step5", "5. 光谱特征提取"),
|
||||
("step5_5", "6. 水质参数指数计算"),
|
||||
("step8", "6. 水质参数指数计算"),
|
||||
],
|
||||
"阶段三：模型构建与训练": [
|
||||
("step6", "7. 机器学习模型训练"),
|
||||
("step6_5", "8. 回归模型训练"),
|
||||
("step6_75", "9. 自定义回归模型训练"),
|
||||
("step7", "7. 机器学习模型训练"),
|
||||
("step8_non_empirical_modeling", "8. 回归模型训练"),
|
||||
("step9", "9. 自定义回归模型训练"),
|
||||
],
|
||||
"阶段四：预测与成果输出 ": [
|
||||
("step7", "10. 采样点布设"),
|
||||
("step8", "11. 机器学习预测"),
|
||||
("step8_5", "12. 回归预测"),
|
||||
("step8_75", "13. 自定义回归预测"),
|
||||
("step9", "14. 专题图生成"),
|
||||
("step10", "10. 采样点布设"),
|
||||
("step11_ml", "11. 机器学习预测"),
|
||||
("step11", "12. 回归预测"),
|
||||
("step12", "13. 自定义回归预测"),
|
||||
("step14", "14. 专题图生成"),
|
||||
("step9_viz", "15. 可视化分析"),
|
||||
("step_report", "16. 分析报告生成"),
|
||||
]
|
||||
@ -1878,7 +1884,7 @@ class WaterQualityGUI(QMainWindow):
|
||||
self.step_list.addItem(stage_item)
|
||||
|
||||
# 添加该阶段的所有步骤
|
||||
HIDDEN_STEP_IDS = {"step6_5", "step6_75", "step8_5", "step8_75"}
|
||||
HIDDEN_STEP_IDS = {"step8_non_empirical_modeling", "step9", "step11", "step12"}
|
||||
for step_id, step_display in steps:
|
||||
if step_id in HIDDEN_STEP_IDS:
|
||||
continue
|
||||
@ -1958,36 +1964,36 @@ class WaterQualityGUI(QMainWindow):
|
||||
self.step5_panel = Step5Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step5_panel), QIcon(self.get_icon_path("5.png")), "特征构建")
|
||||
|
||||
self.step5_5_panel = Step5_5Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step5_5_panel), QIcon(self.get_icon_path("5.png")), "水质指数")
|
||||
|
||||
self.step6_panel = Step6Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step6_panel), QIcon(self.get_icon_path("6.png")), "监督建模")
|
||||
|
||||
self.step6_5_panel = Step6_5Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step6_5_panel), QIcon(self.get_icon_path("6.png")), "回归建模")
|
||||
self.step_stack.tabBar().setTabVisible(7, False) # 隐藏回归建模 Tab
|
||||
|
||||
self.step6_75_panel = Step6_75Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step6_75_panel), QIcon(self.get_icon_path("6.png")), "自定义回归建模")
|
||||
self.step_stack.tabBar().setTabVisible(8, False) # 隐藏自定义回归建模 Tab
|
||||
self.step8_panel = Step8Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_panel), QIcon(self.get_icon_path("5.png")), "水质指数")
|
||||
|
||||
self.step7_panel = Step7Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step7_panel), QIcon(self.get_icon_path("7.png")), "采样点布设")
|
||||
|
||||
self.step8_panel = Step8Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_panel), QIcon(self.get_icon_path("8.png")), "监督预测")
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step7_panel), QIcon(self.get_icon_path("6.png")), "监督建模")
|
||||
|
||||
self.step8_5_panel = Step8_5Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_5_panel), QIcon(self.get_icon_path("8.png")), "回归预测")
|
||||
self.step_stack.tabBar().setTabVisible(11, False) # 隐藏回归预测 Tab
|
||||
|
||||
self.step8_75_panel = Step8_75Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_75_panel), QIcon(self.get_icon_path("8.png")), "自定义回归预测")
|
||||
self.step_stack.tabBar().setTabVisible(12, False) # 隐藏自定义回归预测 Tab
|
||||
self.step8_non_empirical_panel = Step8NonEmpiricalPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_non_empirical_panel), QIcon(self.get_icon_path("6.png")), "回归建模")
|
||||
self.step_stack.tabBar().setTabVisible(7, False) # 隐藏回归建模 Tab
|
||||
|
||||
self.step9_panel = Step9Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step9_panel), QIcon(self.get_icon_path("10.png")), "专题图生成")
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step9_panel), QIcon(self.get_icon_path("6.png")), "自定义回归建模")
|
||||
self.step_stack.tabBar().setTabVisible(8, False) # 隐藏自定义回归建模 Tab
|
||||
|
||||
self.step10_panel = Step10Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step10_panel), QIcon(self.get_icon_path("7.png")), "采样点布设")
|
||||
|
||||
self.step11_ml_panel = Step11MlPanel() # ML prediction panel (step11_ml)
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step11_ml_panel), QIcon(self.get_icon_path("8.png")), "监督预测")
|
||||
|
||||
self.step11_panel = Step11Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step11_panel), QIcon(self.get_icon_path("8.png")), "回归预测")
|
||||
self.step_stack.tabBar().setTabVisible(11, False) # 隐藏回归预测 Tab
|
||||
|
||||
self.step12_panel = Step12Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step12_panel), QIcon(self.get_icon_path("8.png")), "自定义回归预测")
|
||||
self.step_stack.tabBar().setTabVisible(12, False) # 隐藏自定义回归预测 Tab
|
||||
|
||||
self.step14_panel = Step14Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step14_panel), QIcon(self.get_icon_path("10.png")), "专题图生成")
|
||||
|
||||
self.viz_panel = VisualizationPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.viz_panel), QIcon(self.get_icon_path("9.png")), "可视化")
|
||||
@ -2137,15 +2143,15 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step3': 2,
|
||||
'step4': 3,
|
||||
'step5': 4,
|
||||
'step5_5': 5,
|
||||
'step6': 6,
|
||||
'step6_5': 7,
|
||||
'step6_75': 8,
|
||||
'step7': 9,
|
||||
'step8': 10,
|
||||
'step8_5': 11,
|
||||
'step8_75': 12,
|
||||
'step9': 13,
|
||||
'step8': 5,
|
||||
'step7': 6,
|
||||
'step8_non_empirical_modeling': 7,
|
||||
'step9': 8,
|
||||
'step10': 9,
|
||||
'step11_ml': 10,
|
||||
'step11': 11,
|
||||
'step12': 12,
|
||||
'step14': 13,
|
||||
'step9_viz': 14,
|
||||
'step_report': 15,
|
||||
}
|
||||
@ -2168,15 +2174,15 @@ class WaterQualityGUI(QMainWindow):
|
||||
2: 'step3',
|
||||
3: 'step4',
|
||||
4: 'step5',
|
||||
5: 'step5_5',
|
||||
6: 'step6',
|
||||
7: 'step6_5',
|
||||
8: 'step6_75',
|
||||
9: 'step7',
|
||||
10: 'step8',
|
||||
11: 'step8_5',
|
||||
12: 'step8_75',
|
||||
13: 'step9',
|
||||
5: 'step8',
|
||||
6: 'step7',
|
||||
7: 'step8_non_empirical_modeling',
|
||||
8: 'step9',
|
||||
9: 'step10',
|
||||
10: 'step11_ml',
|
||||
11: 'step11',
|
||||
12: 'step12',
|
||||
13: 'step14',
|
||||
14: 'step9_viz',
|
||||
15: 'step_report',
|
||||
}
|
||||
@ -2213,41 +2219,41 @@ class WaterQualityGUI(QMainWindow):
|
||||
elif index == 4:
|
||||
self.step5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step5_5 切换时自动填充输出路径
|
||||
# Step8（水质指数）切换时自动填充输出路径
|
||||
elif index == 5:
|
||||
self.step5_5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
self.step8_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step6 切换时自动填充训练数据和输出路径
|
||||
# Step7（监督建模）切换时自动填充训练数据和输出路径
|
||||
elif index == 6:
|
||||
self.step6_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step6.5（非经验回归建模）切换时自动填充训练数据和模型目录
|
||||
elif index == 7:
|
||||
self.step6_5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step6.75（自定义回归建模）切换时自动填充训练数据和模型目录
|
||||
elif index == 8:
|
||||
self.step6_75_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step7（采样点布设）切换时自动填充掩膜和输出路径
|
||||
elif index == 9:
|
||||
self.step7_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8非经验建模切换时自动填充训练数据和模型目录
|
||||
elif index == 7:
|
||||
self.step8_non_empirical_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step9（自定义回归建模）切换时自动填充训练数据和模型目录
|
||||
elif index == 8:
|
||||
self.step9_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step10（采样点布设）切换时自动填充掩膜和输出路径
|
||||
elif index == 9:
|
||||
self.step10_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8（机器学习预测）切换时自动填充采样光谱和模型目录
|
||||
elif index == 10:
|
||||
self.step8_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
self.step11_ml_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8.5（非经验模型预测）切换时自动填充采样光谱和回归模型目录
|
||||
# Step11（回归预测）切换时自动填充采样光谱和回归模型目录
|
||||
elif index == 11:
|
||||
self.step8_5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
self.step11_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8.75（自定义回归预测）切换时自动填充采样光谱和自定义回归模型目录
|
||||
# Step12（自定义回归预测）切换时自动填充采样光谱和自定义回归模型目录
|
||||
elif index == 12:
|
||||
self.step8_75_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
self.step12_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step9（专题图生成）切换时自动填充预测结果目录
|
||||
# Step14（专题图生成）切换时自动填充预测结果目录
|
||||
elif index == 13:
|
||||
self.step9_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
self.step14_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# 可视化分析面板切换时自动推断图像目录并加载目录树
|
||||
elif index == 14:
|
||||
@ -2294,22 +2300,22 @@ class WaterQualityGUI(QMainWindow):
|
||||
self.step4_panel.set_config(config['step4'])
|
||||
if 'step5' in config:
|
||||
self.step5_panel.set_config(config['step5'])
|
||||
if 'step5_5' in config:
|
||||
self.step5_5_panel.set_config(config['step5_5'])
|
||||
if 'step6' in config:
|
||||
self.step6_panel.set_config(config['step6'])
|
||||
if 'step6_5' in config:
|
||||
self.step6_5_panel.set_config(config['step6_5'])
|
||||
if 'step6_75' in config:
|
||||
self.step6_75_panel.set_config(config['step6_75'])
|
||||
if 'step7' in config:
|
||||
self.step7_panel.set_config(config['step7'])
|
||||
if 'step8' in config:
|
||||
self.step8_panel.set_config(config['step8'])
|
||||
if 'step8_5' in config:
|
||||
self.step8_5_panel.set_config(config['step8_5'])
|
||||
if 'step7' in config:
|
||||
self.step7_panel.set_config(config['step7'])
|
||||
if 'step8_non_empirical_modeling' in config:
|
||||
self.step8_non_empirical_panel.set_config(config['step8_non_empirical_modeling'])
|
||||
if 'step9' in config:
|
||||
self.step9_panel.set_config(config['step9'])
|
||||
if 'step10' in config:
|
||||
self.step10_panel.set_config(config['step10'])
|
||||
if 'step11_ml' in config:
|
||||
self.step11_ml_panel.set_config(config['step11_ml'])
|
||||
if 'step11' in config:
|
||||
self.step11_panel.set_config(config['step11'])
|
||||
if 'step14' in config:
|
||||
self.step14_panel.set_config(config['step14'])
|
||||
if 'visualization' in config:
|
||||
self.viz_panel.set_config(config['visualization'])
|
||||
if 'report_generation' in config:
|
||||
@ -2352,14 +2358,14 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step3': self.step3_panel.get_config(),
|
||||
'step4': self.step4_panel.get_config(),
|
||||
'step5': self.step5_panel.get_config(),
|
||||
'step5_5': self.step5_5_panel.get_config(),
|
||||
'step6': self.step6_panel.get_config(),
|
||||
'step6_5': self.step6_5_panel.get_config(),
|
||||
'step6_75': self.step6_75_panel.get_config(),
|
||||
'step7': self.step7_panel.get_config(),
|
||||
'step8': self.step8_panel.get_config(),
|
||||
'step8_5': self.step8_5_panel.get_config(),
|
||||
'step7': self.step7_panel.get_config(),
|
||||
'step8_non_empirical_modeling': self.step8_non_empirical_panel.get_config(),
|
||||
'step9': self.step9_panel.get_config(),
|
||||
'step10': self.step10_panel.get_config(),
|
||||
'step11_ml': self.step11_ml_panel.get_config(),
|
||||
'step11': self.step11_panel.get_config(),
|
||||
'step14': self.step14_panel.get_config(),
|
||||
'visualization': self.viz_panel.get_config(),
|
||||
'report_generation': self.report_panel.get_config(),
|
||||
}
|
||||
@ -2410,15 +2416,15 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step3': self.step3_panel,
|
||||
'step4': self.step4_panel,
|
||||
'step5': self.step5_panel,
|
||||
'step5_5': self.step5_5_panel,
|
||||
'step6': self.step6_panel,
|
||||
'step6_5': self.step6_5_panel,
|
||||
'step6_75': self.step6_75_panel,
|
||||
'step7': self.step7_panel,
|
||||
'step8': self.step8_panel,
|
||||
'step8_5': self.step8_5_panel,
|
||||
'step8_75': self.step8_75_panel,
|
||||
'step7': self.step7_panel,
|
||||
'step8_non_empirical_modeling': self.step8_non_empirical_panel,
|
||||
'step9': self.step9_panel,
|
||||
'step10': self.step10_panel,
|
||||
'step11_ml': self.step11_ml_panel,
|
||||
'step11': self.step11_panel,
|
||||
'step12': self.step12_panel,
|
||||
'step14': self.step14_panel,
|
||||
}
|
||||
return panel_map.get(step_id)
|
||||
|
||||
@ -2426,15 +2432,38 @@ class WaterQualityGUI(QMainWindow):
|
||||
"""查找指定步骤的输出文件"""
|
||||
if step_id not in self.step_default_outputs:
|
||||
return None
|
||||
|
||||
|
||||
step_outputs = self.step_default_outputs[step_id]
|
||||
|
||||
|
||||
# ★ 掩膜类型列表：这些类型只接受科学数据格式
|
||||
mask_types = {'water_mask', 'glint_mask', 'boundary_mask'}
|
||||
# ★ 白名单机制：只允许 .dat .tif .tiff .shp，拒绝其他一切格式
|
||||
scientific_extensions = {'.dat', '.tif', '.tiff', '.shp'}
|
||||
# ★ 临时文件关键词黑名单
|
||||
tmp_keywords = ('__tmp', '_tmp')
|
||||
|
||||
def _is_scientific_mask(path_str):
|
||||
"""白名单判断：只有 .dat .tif .tiff .shp 才算科学数据格式"""
|
||||
p = Path(path_str)
|
||||
name_lower = str(path_str).lower()
|
||||
# 拒绝临时文件
|
||||
if any(kw in name_lower for kw in tmp_keywords):
|
||||
return False
|
||||
# 白名单校验
|
||||
return p.suffix.lower() in scientific_extensions
|
||||
|
||||
# 特殊处理：从step_outputs记录中查找实际输出路径
|
||||
if step_id in self.step_outputs:
|
||||
actual_outputs = self.step_outputs[step_id]
|
||||
if output_type in actual_outputs:
|
||||
return actual_outputs[output_type]
|
||||
|
||||
candidate = actual_outputs[output_type]
|
||||
# ★ 掩膜类型白名单二次校验：不在白名单内的一律拒绝
|
||||
if output_type in mask_types and not _is_scientific_mask(candidate):
|
||||
# 非科学格式被拒绝，不使用 step_outputs 中的值
|
||||
pass
|
||||
else:
|
||||
return candidate
|
||||
|
||||
# 根据输出类型查找对应的文件
|
||||
if output_type == 'water_mask':
|
||||
# 水域掩膜：优先查找NDWI生成的，其次是shp生成的
|
||||
@ -2485,19 +2514,19 @@ class WaterQualityGUI(QMainWindow):
|
||||
# 扫描各个子目录
|
||||
subdirs = {
|
||||
'1_water_mask': 'step1',
|
||||
'2_glint': 'step2',
|
||||
'2_glint': 'step2',
|
||||
'3_deglint': 'step3',
|
||||
'4_processed_data': 'step4',
|
||||
'5_training_spectra': 'step5',
|
||||
'6_water_quality_indices': 'step5_5',
|
||||
'7_Supervised_Model_Training': 'step6',
|
||||
'8_Regression_Modeling': 'step6_5',
|
||||
'9_Custom_Regression_Modeling': 'step6_75',
|
||||
'10_sampling': 'step7',
|
||||
'11_12_13_predictions/Machine_Learning_Prediction': 'step8',
|
||||
'11_12_13_predictions/Non_Empirical_Prediction': 'step8_5',
|
||||
'11_12_13_predictions/Custom_Regression_Prediction': 'step8_75',
|
||||
'14_visualization': 'step9'
|
||||
'6_water_quality_indices': 'step8',
|
||||
'7_Supervised_Model_Training': 'step7',
|
||||
'8_Regression_Modeling': 'step8_non_empirical_modeling',
|
||||
'9_Custom_Regression_Modeling': 'step9',
|
||||
'10_sampling': 'step10',
|
||||
'11_12_13_predictions/Machine_Learning_Prediction': 'step11_ml',
|
||||
'11_12_13_predictions/Non_Empirical_Prediction': 'step11',
|
||||
'11_12_13_predictions/Custom_Regression_Prediction': 'step12',
|
||||
'14_visualization': 'step14'
|
||||
}
|
||||
|
||||
for subdir, step_ids in subdirs.items():
|
||||
@ -2517,23 +2546,37 @@ class WaterQualityGUI(QMainWindow):
|
||||
for step_id in step_ids:
|
||||
if step_id not in discovered_outputs:
|
||||
discovered_outputs[step_id] = {}
|
||||
|
||||
|
||||
# ★ 掩膜文件白名单过滤：只有 .dat .tif .tiff .shp 才通过，拒绝 .hdr .xml .png 等
|
||||
scientific_extensions = {'.dat', '.tif', '.tiff', '.shp'}
|
||||
tmp_keywords = ('__tmp', '_tmp')
|
||||
|
||||
def _is_scientific_mask(path_str):
|
||||
"""白名单判断：拒绝 .hdr .xml 临时文件等，只接受科学数据格式"""
|
||||
p = Path(path_str)
|
||||
name_lower = str(path_str).lower()
|
||||
if any(kw in name_lower for kw in tmp_keywords):
|
||||
return False
|
||||
return p.suffix.lower() in scientific_extensions
|
||||
|
||||
# 匹配不同的文件类型
|
||||
if 'water_mask' in file_name and step_id == 'step1':
|
||||
discovered_outputs[step_id]['water_mask'] = str(file_path)
|
||||
if _is_scientific_mask(file_path):
|
||||
discovered_outputs[step_id]['water_mask'] = str(file_path)
|
||||
elif 'glint' in file_name and 'mask' in file_name and step_id == 'step2':
|
||||
discovered_outputs[step_id]['glint_mask'] = str(file_path)
|
||||
if _is_scientific_mask(file_path):
|
||||
discovered_outputs[step_id]['glint_mask'] = str(file_path)
|
||||
elif 'deglint' in file_name and step_id == 'step3':
|
||||
discovered_outputs[step_id]['deglint_image'] = str(file_path)
|
||||
elif 'processed_data' in file_name and step_id == 'step4':
|
||||
discovered_outputs[step_id]['processed_data'] = str(file_path)
|
||||
elif 'training_spectra' in file_name and step_id == 'step5':
|
||||
discovered_outputs[step_id]['training_spectra'] = str(file_path)
|
||||
elif 'water_quality_indices' in file_name and step_id == 'step5_5':
|
||||
elif 'water_quality_indices' in file_name and step_id == 'step8':
|
||||
discovered_outputs[step_id]['water_indices'] = str(file_path)
|
||||
elif 'sampling_spectra' in file_name and step_id == 'step7':
|
||||
elif 'sampling_spectra' in file_name and step_id == 'step10':
|
||||
discovered_outputs[step_id]['sampling_points'] = str(file_path)
|
||||
elif file_name.endswith('.csv') and step_id in ['step8', 'step8_5', 'step8_75']:
|
||||
elif file_name.endswith('.csv') and step_id in ['step11_ml', 'step11', 'step12']:
|
||||
discovered_outputs[step_id]['predictions'] = str(file_path)
|
||||
|
||||
# 更新内部记录
|
||||
@ -2556,8 +2599,8 @@ class WaterQualityGUI(QMainWindow):
|
||||
# 首先扫描工作目录发现已有的输出文件
|
||||
self.scan_work_directory_for_files(work_path)
|
||||
|
||||
step_order = ['step2', 'step3', 'step4', 'step5', 'step5_5', 'step6', 'step6_5', 'step6_75',
|
||||
'step7', 'step8', 'step8_5', 'step8_75', 'step9']
|
||||
step_order = ['step2', 'step3', 'step4', 'step5', 'step8', 'step7', 'step8_non_empirical_modeling', 'step9',
|
||||
'step10', 'step11_ml', 'step11', 'step12', 'step14']
|
||||
|
||||
filled_count = 0
|
||||
for step_id in step_order:
|
||||
@ -2579,15 +2622,15 @@ class WaterQualityGUI(QMainWindow):
|
||||
('step2', self.step2_panel),
|
||||
('step3', self.step3_panel),
|
||||
('step5', self.step5_panel),
|
||||
('step5_5', self.step5_5_panel),
|
||||
('step6', self.step6_panel),
|
||||
('step6_5', self.step6_5_panel),
|
||||
('step6_75', self.step6_75_panel),
|
||||
('step7', self.step7_panel),
|
||||
('step8', self.step8_panel),
|
||||
('step8_5', self.step8_5_panel),
|
||||
('step8_75', self.step8_75_panel),
|
||||
('step9', self.step9_panel)
|
||||
('step7', self.step7_panel),
|
||||
('step8_non_empirical_modeling', self.step8_non_empirical_panel),
|
||||
('step9', self.step9_panel),
|
||||
('step10', self.step10_panel),
|
||||
('step11_ml', self.step11_ml_panel),
|
||||
('step11', self.step11_panel),
|
||||
('step12', self.step12_panel),
|
||||
('step14', self.step14_panel)
|
||||
]
|
||||
|
||||
for step_id, panel in panels_with_dependencies:
|
||||
@ -2735,7 +2778,7 @@ class WaterQualityGUI(QMainWindow):
|
||||
"""显示关于对话框"""
|
||||
QMessageBox.about(
|
||||
self, "关于",
|
||||
"MegaCube-Water Quality V1.1\n\n"
|
||||
"MegaCube-Water Quality V1.2\n\n"
|
||||
"一个完整的水质参数反演工作流程工具\n\n"
|
||||
"功能包括：\n"
|
||||
"- 水域掩膜生成\n"
|
||||
@ -2858,6 +2901,41 @@ class WaterQualityGUI(QMainWindow):
|
||||
|
||||
return True
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# ★ 全流程模式动态裁剪
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def _prune_config_for_prediction_mode(self, config: dict) -> dict:
|
||||
"""Prediction-only 模式：禁用训练相关步骤，保留预测和成图步骤。
|
||||
|
||||
被禁用的 step dict 中统一写入 'enabled': False，
|
||||
这些配置最终传给 PipelineRunner，Runner 会跳过它们。
|
||||
同时，被跳过的步骤的 required_input_files 在 build_missing_items
|
||||
中不会被检查，从而自然规避了"CSV 缺失"等训练模式下的误报。
|
||||
|
||||
Args:
|
||||
config: 完整配置字典（来自 get_current_config）
|
||||
|
||||
Returns:
|
||||
裁剪后的 config（深拷贝，原 config 不被修改）
|
||||
"""
|
||||
cfg = copy.deepcopy(config)
|
||||
|
||||
# 在每个训练相关步骤的 dict 中写入 enabled=False
|
||||
training_steps = [
|
||||
"step4", # CSV 实测数据清洗
|
||||
"step5", # 实测点光谱提取（→ training_csv_path）
|
||||
"step7", # ML 监督建模
|
||||
"step8", # 水质指数计算（辅助训练）
|
||||
"step8_non_empirical_modeling", # 非经验回归建模
|
||||
"step9", # 自定义回归建模
|
||||
]
|
||||
for step_id in training_steps:
|
||||
step_cfg = cfg.setdefault(step_id, {})
|
||||
step_cfg["enabled"] = False
|
||||
|
||||
return cfg
|
||||
|
||||
def run_full_pipeline(self):
|
||||
"""运行完整流程"""
|
||||
if not PIPELINE_AVAILABLE:
|
||||
@ -2867,8 +2945,14 @@ class WaterQualityGUI(QMainWindow):
|
||||
)
|
||||
return
|
||||
|
||||
# ── 0) 强制获取 work_dir（禁止依赖外部或全局变量） ──
|
||||
work_dir = getattr(self, 'work_dir', None)
|
||||
if not work_dir:
|
||||
QMessageBox.warning(self, "警告", "未选择工作目录，请先设置工作目录。")
|
||||
return
|
||||
|
||||
# ── 1) 运行前智能预检与自动回填（硬盘已有产物自动跳过） ──
|
||||
work_path = Path(getattr(self, 'work_dir', './work_dir'))
|
||||
work_path = Path(work_dir)
|
||||
self.log_message("正在进行运行前环境预检与自动扫描...", "info")
|
||||
self.scan_work_directory_for_files(work_path)
|
||||
self.auto_populate_all_steps()
|
||||
@ -2878,31 +2962,52 @@ class WaterQualityGUI(QMainWindow):
|
||||
if not self._precheck_step3_bands():
|
||||
return # 用户点"取消运行"
|
||||
|
||||
# ── 1.6) ★ 全流程模式选择弹窗 ──
|
||||
mode_dlg = PipelineModeDialog(main_window=self, parent=self)
|
||||
if mode_dlg.exec() != QDialog.Accepted:
|
||||
return # 用户点"取消"
|
||||
selected_mode = mode_dlg.selected_mode
|
||||
self.log_message(f"[模式选择] 选定模式: {'训练新模型' if selected_mode == 'training' else '使用已有模型直接预测'}", "info")
|
||||
|
||||
# ── 2) 刷新配置（拿到自动填充后的"满血版" config） ──
|
||||
config = self.get_current_config()
|
||||
|
||||
# ── 3) 根基数据校验：step1.img_path（参考影像） ──
|
||||
if not config['step1'].get('img_path'):
|
||||
QMessageBox.warning(self, "警告", "缺失核心数据：请先在步骤 1 中上传【参考影像】！")
|
||||
for i in range(self.step_list.count()):
|
||||
item = self.step_list.item(i)
|
||||
if item.data(Qt.UserRole) == 'step1':
|
||||
self.step_list.setCurrentRow(i)
|
||||
break
|
||||
return
|
||||
# ── 2.1) ★ 根据模式动态裁剪配置 ──
|
||||
if selected_mode == "prediction_only":
|
||||
config = self._prune_config_for_prediction_mode(config)
|
||||
self.log_message("[模式选择] 已裁剪训练相关步骤（step4/5/7/8），进入仅预测模式", "info")
|
||||
|
||||
# ── 4) 软提示：csv_path 缺失 → 模型训练步骤会被静默跳过（不阻断） ──
|
||||
csv_path = config.get('step4', {}).get('csv_path') or config.get('step5', {}).get('csv_path')
|
||||
if not csv_path:
|
||||
QMessageBox.information(
|
||||
self,
|
||||
"提示：模型训练将被跳过",
|
||||
"未检测到实测水质数据 (CSV)。\n"
|
||||
"流程将自动跳过模型训练（步骤 4-6），仅执行预测与制图。\n"
|
||||
"如果需要训练新模型，请先在步骤 4 中上传水质数据。",
|
||||
)
|
||||
# ── 3) ★ 一次性全预检 + 用户交互式决策 ──
|
||||
missing_items = PreflightDialog.build_missing_items(config)
|
||||
if missing_items:
|
||||
critical_items = [it for it in missing_items if it.is_critical]
|
||||
if critical_items:
|
||||
lines = "\n".join(f" - [{it.step_name}] {it.reason}" for it in critical_items)
|
||||
QMessageBox.critical(
|
||||
self, "预检失败（阻断性错误）",
|
||||
f"以下为阻断性缺失，流程无法启动：\n\n{lines}\n\n"
|
||||
"请填写后重新运行。"
|
||||
)
|
||||
return
|
||||
dialog = PreflightDialog(missing_items, parent=self)
|
||||
if dialog.exec() != QDialog.Accepted:
|
||||
return
|
||||
result = dialog.get_result()
|
||||
if result is None:
|
||||
return
|
||||
action, *payload = result
|
||||
if action == "fill":
|
||||
_, step_id, tab_index = result
|
||||
self.step_stack.setCurrentIndex(tab_index)
|
||||
self.log_message(f"[预检] 用户选择填写 {step_id}，已切换到对应面板。", "info")
|
||||
return
|
||||
skip_list: List[str] = payload[0] if payload else []
|
||||
if skip_list:
|
||||
self.log_message(f"[预检] 用户强制跳过 {len(skip_list)} 个步骤: {skip_list}", "info")
|
||||
else:
|
||||
skip_list = []
|
||||
|
||||
# 确认执行
|
||||
# ── 4) 确认执行
|
||||
reply = QMessageBox.question(
|
||||
self, "确认",
|
||||
"是否开始执行完整流程？\n\n这可能需要较长时间，请确保配置正确。",
|
||||
@ -2913,19 +3018,18 @@ class WaterQualityGUI(QMainWindow):
|
||||
return
|
||||
|
||||
# 创建pipeline实例
|
||||
work_dir = getattr(self, 'work_dir', './work_dir')
|
||||
self.log_message(f"初始化pipeline，工作目录: {work_dir}", "info")
|
||||
|
||||
# 准备实际运行配置（排除未启用的步骤）
|
||||
worker_config = copy.deepcopy(config)
|
||||
step5_5_cfg = worker_config.get('step5_5')
|
||||
if step5_5_cfg:
|
||||
enabled = step5_5_cfg.pop('enabled', True)
|
||||
step8_cfg = worker_config.get('step8')
|
||||
if step8_cfg:
|
||||
enabled = step8_cfg.pop('enabled', True)
|
||||
if not enabled:
|
||||
worker_config.pop('step5_5', None)
|
||||
worker_config.pop('step8', None)
|
||||
|
||||
# 工作线程内创建 Pipeline，避免主线程阻塞及 Qt5Agg 子线程绘图卡死
|
||||
self.worker = WorkerThread(work_dir, worker_config, mode='full')
|
||||
self.worker = WorkerThread(work_dir, worker_config, mode='full', skip_list=skip_list)
|
||||
self.worker.log_message.connect(self.log_message, Qt.QueuedConnection)
|
||||
self.worker.progress_update.connect(self.update_progress, Qt.QueuedConnection)
|
||||
self.worker.step_completed.connect(self.on_step_completed, Qt.QueuedConnection)
|
||||
@ -3152,14 +3256,14 @@ class WaterQualityGUI(QMainWindow):
|
||||
def update_ui_for_training_mode(self):
|
||||
"""根据训练数据模式更新UI状态"""
|
||||
# 需要禁用的步骤ID（对应无训练数据模式下需要禁用的步骤）
|
||||
disabled_step_ids = ['step4', 'step5', 'step5_5', 'step6', 'step6_5', 'step6_75']
|
||||
disabled_step_ids = ['step4', 'step5', 'step8', 'step7', 'step8_non_empirical_modeling', 'step9']
|
||||
|
||||
# 更新标签页的启用/禁用状态
|
||||
step_id_to_tab = {
|
||||
'step1': 0, 'step2': 1, 'step3': 2, 'step4': 3,
|
||||
'step5': 4, 'step5_5': 5, 'step6': 6, 'step6_5': 7,
|
||||
'step6_75': 8, 'step7': 9, 'step8': 10, 'step8_5': 11,
|
||||
'step8_75': 12, 'step9': 13, 'step9_viz': 14
|
||||
'step5': 4, 'step8': 5, 'step7': 6, 'step8_non_empirical_modeling': 7,
|
||||
'step9': 8, 'step10': 9, 'step11_ml': 10, 'step11': 11,
|
||||
'step12': 12, 'step14': 13, 'step9_viz': 14
|
||||
}
|
||||
|
||||
for step_id in disabled_step_ids:
|
||||
|
||||
Reference in New Issue
Block a user