From e59703f163f8b56953be7e43b37fd40893ce760d Mon Sep 17 00:00:00 2001 From: DXC Date: Thu, 11 Jun 2026 17:44:24 +0800 Subject: [PATCH] =?UTF-8?q?=E7=BB=93=E6=9E=84=E4=BF=AE=E6=94=B9=EF=BC=8C?= =?UTF-8?q?=E5=90=8E=E7=AB=AF=E6=96=87=E4=BB=B6=E8=B7=9F=E5=89=8D=E7=AB=AF?= =?UTF-8?q?=E5=86=85=E5=AE=B9=E8=BF=9B=E8=A1=8C=E9=80=82=E9=85=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/gui/core/worker_thread.py | 113 +-- ...ap_panel.py => step10_watercolor_panel.py} | 8 +- src/gui/panels/step11_map_panel.py | 826 ++++++++++++++++++ ...tep11_viz_panel.py => step12_viz_panel.py} | 4 +- .../{step12_panel.py => step13_panel.py} | 2 +- ...report_panel.py => step13_report_panel.py} | 4 +- src/gui/panels/step4_sampling_panel.py | 4 +- src/gui/panels/step5_clean_panel.py | 4 +- src/gui/panels/step6_feature_panel.py | 4 +- src/gui/panels/step8_ml_train_panel.py | 638 ++++++++------ src/gui/panels/step9_ml_predict_panel.py | 8 +- src/gui/water_quality_gui.py | 191 ++-- 12 files changed, 1311 insertions(+), 495 deletions(-) rename src/gui/panels/{step10_map_panel.py => step10_watercolor_panel.py} (98%) create mode 100644 src/gui/panels/step11_map_panel.py rename src/gui/panels/{step11_viz_panel.py => step12_viz_panel.py} (99%) rename src/gui/panels/{step12_panel.py => step13_panel.py} (99%) rename src/gui/panels/{step12_report_panel.py => step13_report_panel.py} (98%) diff --git a/src/gui/core/worker_thread.py b/src/gui/core/worker_thread.py index 02ed34c..b8c30f2 100644 --- a/src/gui/core/worker_thread.py +++ b/src/gui/core/worker_thread.py @@ -272,10 +272,10 @@ class WorkerThread(QThread): ctx = PipelineContext( img_path=self.config.get('step1', {}).get('img_path'), water_mask_path=self.config.get('step1', {}).get('mask_path'), - csv_path=self.config.get('step4', {}).get('csv_path'), - boundary_path=self.config.get('step5', {}).get('boundary_path'), - boundary_shp_path=self.config.get('step14', {}).get('boundary_shp_path'), - formula_csv_path=self.config.get('step12', {}).get('formula_csv_path'), + csv_path=self.config.get('step4_sampling', {}).get('csv_path'), + boundary_path=self.config.get('step5_clean', {}).get('boundary_path'), + boundary_shp_path=self.config.get('step11_map', {}).get('boundary_shp_path'), + formula_csv_path=self.config.get('step8_non_empirical_modeling', {}).get('formula_csv_path'), work_dir=self.work_dir, user_config=self.config ) @@ -323,21 +323,16 @@ class WorkerThread(QThread): 'step1': 'step1_generate_water_mask', 'step2': 'step2_find_glint_area', 'step3': 'step3_remove_glint', - 'step4': 'step5_process_csv', - 'step5': 'step6_extract_spectra', - 'step7': 'step7_calc_indices', + 'step4_sampling': 'step4_sampling', + 'step5_clean': 'step5_process_csv', + 'step6_feature': 'step6_extract_spectra', 'step7_index': 'step7_calc_indices', - 'step8': 'step8_train_ml', 'step8_ml_train': 'step8_train_ml', 'step8_non_empirical_modeling': 'step8_non_empirical_modeling', 'step8_qaa': 'step8_qaa_inversion', - 'step9': 'step9_watercolor_inversion', 'step9_ml_predict': 'step9_predict_ml', - 'step10': 'step4_sampling', - 'step10_map': 'step10_map', - 'step11_ml': 'step9_predict_ml', - 'step11': 'step11_non_empirical_prediction', - 'step14': 'step10_map' + 'step10_watercolor': 'step9_watercolor_inversion', + 'step11_map': 'step10_map', } if step_name not in step_method_map: @@ -367,17 +362,9 @@ class WorkerThread(QThread): step_config['skip_dependency_check'] = True - if step_name == 'step14': - step_config.pop('step9_batch_mode', None) - step_config.pop('prediction_csv_dir', None) - step_config.pop('recursive_csv_scan', None) - - if step_name in ['step2', 'step3', 'step4', 'step5', 'step7', 'step10', 'step11_ml', 'step11', 'step12']: + if step_name in ['step2', 'step3', 'step4_sampling', 'step5_clean', 'step7_index', 'step9_ml_predict']: step_config.pop('output_path', None) - if step_name == 'step11' and 'models_dir' in step_config: - step_config['non_empirical_models_dir'] = step_config.pop('models_dir') - method = getattr(self.pipeline, method_name) result = method(**step_config) @@ -436,100 +423,76 @@ class WorkerThread(QThread): " → 请确认「耀斑去除」已成功运行，或重新配置路径。" ) - # ── 步骤4：实测水质数据 CSV ── - step4_cfg = config.get('step4', {}) + # ── 步骤4_sampling：实测水质数据 CSV ── + step4_cfg = config.get('step4_sampling', {}) csv_path = step4_cfg.get('csv_path') if csv_path and not os.path.isfile(csv_path): errors.append( - f"步骤 4：实测水质数据文件不存在：\n {csv_path}\n" + f"步骤 4_sampling：实测水质数据文件不存在：\n {csv_path}\n" " → 请检查 CSV 路径是否正确，或重新上传数据文件。" ) - # ── 步骤5：采样点平均光谱提取 ── - step5_cfg = config.get('step5', {}) + # ── 步骤5_clean：采样点平均光谱提取 ── + step5_cfg = config.get('step5_clean', {}) step5_csv = step5_cfg.get('csv_path') boundary_path = step5_cfg.get('boundary_path') if step5_csv and not os.path.isfile(step5_csv): errors.append( - f"步骤 5：实测水质数据文件不存在：\n {step5_csv}\n" + f"步骤 5_clean：实测水质数据文件不存在：\n {step5_csv}\n" " → 请检查「流程步骤-阶段五」中的 CSV 路径。" ) if boundary_path and not os.path.isfile(boundary_path): errors.append( - f"步骤 5：边界矢量文件不存在：\n {boundary_path}\n" + f"步骤 5_clean：边界矢量文件不存在：\n {boundary_path}\n" " → 请确认「流程步骤-阶段五」中已填写有效的边界 shp 路径。" ) - # ── 步骤6（水质光谱指数）：训练光谱 CSV ── - step6_cfg = config.get('step6', {}) + # ── 步骤6_feature（水质光谱指数）：训练光谱 CSV ── + step6_cfg = config.get('step6_feature', {}) training_csv = step6_cfg.get('training_csv_path') if training_csv and not os.path.isfile(training_csv): errors.append( - f"步骤 6（水质光谱指数）：训练光谱文件不存在：\n {training_csv}\n" - " → 请确认步骤 5 已成功运行并生成了训练光谱。" + f"步骤 6_feature（水质光谱指数）：训练光谱文件不存在：\n {training_csv}\n" + " → 请确认步骤 5_clean 已成功运行并生成了训练光谱。" ) - # ── 步骤7（ML 建模） ── - step7_cfg = config.get('step7', {}) + # ── 步骤8_ml_train（ML 建模） ── + step7_cfg = config.get('step8_ml_train', {}) step7_csv = step7_cfg.get('training_csv_path') if step7_csv and not os.path.isfile(step7_csv): errors.append( - f"步骤 7（ML 建模）：训练光谱文件不存在：\n {step7_csv}\n" - " → 请确认步骤 5 已成功运行并生成了训练光谱。" + f"步骤 8_ml_train（ML 建模）：训练光谱文件不存在：\n {step7_csv}\n" + " → 请确认步骤 5_clean 已成功运行并生成了训练光谱。" ) - # ── 步骤11 ML 预测：密集采样点 CSV + 模型目录 ── - step11_ml_cfg = config.get('step11_ml', {}) - ml_csv = step11_ml_cfg.get('sampling_csv_path') - models_dir = step11_ml_cfg.get('models_dir') + # ── 步骤9_ml_predict：密集采样点 CSV + 模型目录 ── + step9_cfg = config.get('step9_ml_predict', {}) + ml_csv = step9_cfg.get('sampling_csv_path') + models_dir = step9_cfg.get('models_dir') if ml_csv and not os.path.isfile(ml_csv): errors.append( - f"步骤 11 ML 预测：采样点 CSV 不存在：\n {ml_csv}\n" + f"步骤 9_ml_predict：采样点 CSV 不存在：\n {ml_csv}\n" " → 请确认「流程步骤-阶段七（采样点布设）」已成功运行。" ) if models_dir and not os.path.isdir(models_dir): errors.append( - f"步骤 11 ML 预测：模型目录不存在：\n {models_dir}\n" + f"步骤 9_ml_predict：模型目录不存在：\n {models_dir}\n" " → 请确认「流程步骤-阶段六（机器学习建模）」已成功运行。" ) - # ── 步骤11 回归预测：模型目录 ── - step11_cfg = config.get('step11', {}) - step11_csv = step11_cfg.get('sampling_csv_path') - step11_dir = step11_cfg.get('models_dir') - if step11_csv and not os.path.isfile(step11_csv): - errors.append( - f"步骤 11 回归预测：采样点 CSV 不存在：\n {step11_csv}\n" - " → 请确认「流程步骤-阶段七（采样点布设）」已成功运行。" - ) - if step11_dir and not os.path.isdir(step11_dir): - errors.append( - f"步骤 11 回归预测：模型目录不存在：\n {step11_dir}\n" - " → 请确认「流程步骤-阶段八（非经验建模）」已成功运行。" - ) - - # ── 步骤12 自定义回归预测：公式 CSV ── - step12_cfg = config.get('step12', {}) - formula_csv = step12_cfg.get('formula_csv_path') - if formula_csv and not os.path.isfile(formula_csv): - errors.append( - f"步骤 12（自定义回归预测）：公式 CSV 文件不存在：\n {formula_csv}\n" - " → 请确认「流程步骤-阶段十二」中已填写有效的公式文件路径。" - ) - - # ── 步骤14 专题图：预测结果 CSV + 边界 shp ── - step14_cfg = config.get('step14', {}) - pred_csv = step14_cfg.get('prediction_csv_path') - boundary_shp = step14_cfg.get('boundary_shp_path') + # ── 步骤11_map 专题图：预测结果 CSV + 边界 shp ── + step11_cfg = config.get('step11_map', {}) + pred_csv = step11_cfg.get('prediction_csv_path') + boundary_shp = step11_cfg.get('boundary_shp_path') if pred_csv and not os.path.isfile(pred_csv): errors.append( - f"步骤 14（专题图）：预测结果 CSV 不存在：\n {pred_csv}\n" + f"步骤 11_map（专题图）：预测结果 CSV 不存在：\n {pred_csv}\n" " → 请确认机器学习或回归预测步骤已成功运行。" ) if boundary_shp and not os.path.isfile(boundary_shp): errors.append( - f"步骤 14（专题图）：边界 shp 文件不存在：\n {boundary_shp}\n" - " → 请确认「流程步骤-阶段十四」中已填写有效的边界矢量文件路径。" + f"步骤 11_map（专题图）：边界 shp 文件不存在：\n {boundary_shp}\n" + " → 请确认「流程步骤-阶段十一」中已填写有效的边界矢量文件路径。" ) # ── 汇总报错：任一缺失立即抛出 PipelineHalt ── diff --git a/src/gui/panels/step10_map_panel.py b/src/gui/panels/step10_watercolor_panel.py similarity index 98% rename from src/gui/panels/step10_map_panel.py rename to src/gui/panels/step10_watercolor_panel.py index f2d9e45..7d1f4f9 100644 --- a/src/gui/panels/step10_map_panel.py +++ b/src/gui/panels/step10_watercolor_panel.py @@ -1,7 +1,7 @@ #!/usr/bin/env python # -*- coding: utf-8 -*- """ -Step9 面板 - 水色指数反演（直接处理去耀斑 BSQ 影像） +Step10 面板 - 水色指数反演（直接处理去耀斑 BSQ 影像） 将 waterindex.csv 中的公式直接应用于去耀斑高光谱影像， 输出各水质参数指数的 GeoTIFF 栅格图像。 @@ -98,8 +98,8 @@ class WaterIndexWorker(QThread): self.progress.emit(msg, pct) -class Step10MapPanel(QWidget): - """步骤10：专题图生成""" +class Step10WatercolorPanel(QWidget): + """步骤10：水色指数反演（直接处理 BSQ 影像）""" def __init__(self, parent=None): super().__init__(parent) @@ -115,7 +115,7 @@ class Step10MapPanel(QWidget): layout = QVBoxLayout() # ---- 标题 ---- - title = QLabel("步骤9：水色指数反演（高光谱影像直接处理）") + title = QLabel("步骤10：水色指数反演（高光谱影像直接处理）") title.setFont(QFont("Arial", 12, QFont.Bold)) layout.addWidget(title) diff --git a/src/gui/panels/step11_map_panel.py b/src/gui/panels/step11_map_panel.py new file mode 100644 index 0000000..014a105 --- /dev/null +++ b/src/gui/panels/step11_map_panel.py @@ -0,0 +1,826 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +""" +Step10 面板 - 专题图生成 +""" + +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, QComboBox, + QProgressBar, +) + +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 Step11MapBatchThread(QThread): + """专题图：按文件夹内多个预测 CSV 批量生成分布图。""" + + finished_ok = pyqtSignal(int) + failed = pyqtSignal(str) + log_message = pyqtSignal(str, str) + progress = pyqtSignal(int, int) # (current, total) + + def __init__(self, work_dir: str, csv_paths: List[str], step10_kwargs: dict, output_dir_optional: Optional[str]): + super().__init__() + self.work_dir = work_dir + self.csv_paths = csv_paths + self.step10_kwargs = step10_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.progress.emit(i + 1, n) + self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info") + kw = {**self.step10_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.step10_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 Step11GeoTIFFBatchThread(QThread): + """GeoTIFF 批量渲染：遍历文件夹下所有 .tif/.bsq 逐一渲染成分布图 PNG。""" + + finished_ok = pyqtSignal(int) + failed = pyqtSignal(str) + log_message = pyqtSignal(str, str) + progress = pyqtSignal(int, int) # (current, total) + + def __init__( + self, + tif_paths: List[str], + output_dir: str, + boundary_shp_path: Optional[str], + input_crs: str, + output_crs: str, + ): + super().__init__() + self.tif_paths = tif_paths + self.output_dir = output_dir + self.boundary_shp_path = boundary_shp_path + self.input_crs = input_crs + self.output_crs = output_crs + + def run(self): + mpl_prev = None + try: + import matplotlib + mpl_prev = matplotlib.get_backend() + except Exception: + pass + try: + import matplotlib.pyplot as plt + plt.switch_backend("Agg") + except Exception: + mpl_prev = None + try: + from src.postprocessing.map import ContentMapper + mapper = ContentMapper() + n = len(self.tif_paths) + for i, tif_path in enumerate(self.tif_paths): + self.progress.emit(i + 1, n) + tif_stem = Path(tif_path).stem + chinese_name = mapper._get_chinese_title(tif_stem) + output_png = str(Path(self.output_dir) / f"{chinese_name}_专题图.png") + self.log_message.emit(f"GeoTIFF 渲染 [{i + 1}/{n}] {tif_stem}", "info") + try: + mapper.visualize_raster( + raster_tif_path=tif_path, + output_file=output_png, + boundary_shp_path=self.boundary_shp_path, + nodata_value=-9999.0, + figsize=(14, 10), + alpha=0.9, + ) + except Exception as vis_err: + self.log_message.emit(f" ⚠️ 渲染失败，跳过: {vis_err}", "warning") + continue + self.finished_ok.emit(n) + except Exception as e: + self.failed.emit(f"{e}\n{traceback.format_exc()}") + finally: + if mpl_prev: + try: + import matplotlib.pyplot as plt + plt.switch_backend(mpl_prev) + except Exception: + pass + + +class Step11MapPanel(QWidget): + """步骤11：专题图生成""" + def __init__(self, parent=None): + super().__init__(parent) + self._batch_thread = None + self.init_ui() + + def init_ui(self): + layout = QVBoxLayout() + + hint = QLabel( + "独立运行：可选「单个 CSV」或「文件夹批量」（扫描目录下所有 .csv）。" + "GeoTIFF 栅格模式下，亦支持批量渲染步骤8输出的所有水色指数 GeoTIFF 文件。" + ) + hint.setWordWrap(True) + hint.setStyleSheet( + f"color: {ModernStylesheet.COLORS.get('text_secondary', '#666')};" + ) + layout.addWidget(hint) + + mode_row = QHBoxLayout() + self.mode_single_rb = QRadioButton("单个 CSV 文件") + self.mode_folder_rb = QRadioButton("文件夹批量") + self._mode_group = QButtonGroup(self) + self._mode_group.addButton(self.mode_single_rb, 0) + self._mode_group.addButton(self.mode_folder_rb, 1) + mode_row.addWidget(self.mode_single_rb) + mode_row.addWidget(self.mode_folder_rb) + mode_row.addStretch() + layout.addLayout(mode_row) + + # ---------- 渲染模式选择器（CSV vs GeoTIFF） ---------- + render_row = QHBoxLayout() + render_row.addWidget(QLabel("渲染模式:")) + self.render_mode_combo = QComboBox() + self.render_mode_combo.addItems(["CSV 插值模式", "GeoTIFF 栅格模式"]) + self.render_mode_combo.setMinimumWidth(180) + self.render_mode_combo.currentTextChanged.connect(self._toggle_input_mode) + render_row.addWidget(self.render_mode_combo) + render_row.addStretch() + layout.addLayout(render_row) + + # ---------- RadioButton 美化样式（选中状态为方形实心块，贴合主界面风格） ---------- + radio_style = """ + QRadioButton { + font-size: 14px; + spacing: 8px; + color: #333333; + } + QRadioButton::indicator { + width: 16px; + height: 16px; + border: 2px solid #999999; + border-radius: 3px; + background-color: white; + } + QRadioButton::indicator:checked { + border: 2px solid #0078d4; + background-color: #0078d4; + image: none; + } + QRadioButton::indicator:hover { + border: 2px solid #005a9e; + } + """ + self.mode_single_rb.setStyleSheet(radio_style) + self.mode_folder_rb.setStyleSheet(radio_style) + + self.prediction_csv_file = FileSelectWidget( + "预测结果CSV:", + "CSV Files (*.csv);;All Files (*.*)" + ) + layout.addWidget(self.prediction_csv_file) + + folder_row = QHBoxLayout() + self.prediction_csv_dir_label = QLabel("预测CSV目录:") + self.prediction_csv_dir_label.setMinimumWidth(120) + self.prediction_csv_dir_edit = QLineEdit() + self.prediction_csv_dir_edit.setPlaceholderText("选择含多个预测结果 CSV 的文件夹…") + pred_dir_btn = QPushButton("浏览…") + pred_dir_btn.setMaximumWidth(80) + pred_dir_btn.clicked.connect(self.browse_prediction_csv_dir) + folder_row.addWidget(self.prediction_csv_dir_label) + folder_row.addWidget(self.prediction_csv_dir_edit, 1) + folder_row.addWidget(pred_dir_btn) + self._folder_row_widget = QWidget() + self._folder_row_widget.setLayout(folder_row) + layout.addWidget(self._folder_row_widget) + + # ---------- GeoTIFF 栅格文件选择器 ---------- + self.geotiff_file = FileSelectWidget( + "水色指数 GeoTIFF:", + "GeoTIFF Files (*.tif);;All Files (*.*)" + ) + self.geotiff_file.line_edit.setPlaceholderText("选择步骤8输出的水色指数 GeoTIFF 文件…") + self.geotiff_file.setVisible(False) + layout.addWidget(self.geotiff_file) + + # ---------- GeoTIFF 文件夹批量选择器（GeoTIFF + 文件夹模式时显示） ---------- + geotiff_dir_row = QHBoxLayout() + self.geotiff_dir_label = QLabel("水色指数目录:") + self.geotiff_dir_label.setMinimumWidth(120) + self.geotiff_dir_edit = QLineEdit() + self.geotiff_dir_edit.setPlaceholderText("选择 8_WaterIndex_Images 文件夹（批量渲染）…") + geotiff_dir_btn = QPushButton("浏览…") + geotiff_dir_btn.setMaximumWidth(80) + geotiff_dir_btn.clicked.connect(self.browse_geotiff_dir) + geotiff_dir_row.addWidget(self.geotiff_dir_label) + geotiff_dir_row.addWidget(self.geotiff_dir_edit, 1) + geotiff_dir_row.addWidget(geotiff_dir_btn) + self._geotiff_dir_widget = QWidget() + self._geotiff_dir_widget.setLayout(geotiff_dir_row) + self._geotiff_dir_widget.setVisible(False) + layout.addWidget(self._geotiff_dir_widget) + + self.recursive_csv_cb = QCheckBox("包含子文件夹（递归扫描 *.csv）") + layout.addWidget(self.recursive_csv_cb) + + self.boundary_file = FileSelectWidget( + "边界文件:", + "Shapefiles (*.shp);;All Files (*.*)" + ) + layout.addWidget(self.boundary_file) + + # 参数设置 + params_group = QGroupBox("生成参数") + params_layout = QFormLayout() + + self.resolution = QDoubleSpinBox() + self.resolution.setRange(1, 1000) + self.resolution.setValue(30) + params_layout.addRow("分辨率(米):", self.resolution) + + self.input_crs = QLineEdit() + self.input_crs.setText("EPSG:32651") + params_layout.addRow("输入坐标系:", self.input_crs) + + self.output_crs = QLineEdit() + self.output_crs.setText("EPSG:4326") + params_layout.addRow("输出坐标系:", self.output_crs) + + self.show_points = QCheckBox("显示采样点") + params_layout.addRow("", self.show_points) + + self.use_diffusion = QCheckBox("启用距离扩散") + self.use_diffusion.setChecked(True) + params_layout.addRow("", self.use_diffusion) + + params_group.setLayout(params_layout) + layout.addWidget(params_group) + + # 输出目录 + self.output_dir = FileSelectWidget( + "输出分布图目录:", + "Directories;;All Files (*.*)" + ) + self.output_dir.line_edit.setPlaceholderText("留空→工作目录/14_visualization") + self.output_dir.browse_btn.clicked.disconnect() + self.output_dir.browse_btn.clicked.connect(self.browse_output_dir) + layout.addWidget(self.output_dir) + + # 启用步骤 + self.enable_checkbox = QCheckBox("启用此步骤") + self.enable_checkbox.setChecked(True) + layout.addWidget(self.enable_checkbox) + + # 独立运行按钮 + self.run_button = QPushButton("独立运行此步骤") + self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success')) + self.run_button.clicked.connect(self.run_step) + layout.addWidget(self.run_button) + + # 批量渲染进度条 + self.progress_bar = QProgressBar() + self.progress_bar.setVisible(False) + self.progress_bar.setMinimum(0) + self.progress_bar.setMaximum(100) + self.progress_bar.setValue(0) + layout.addWidget(self.progress_bar) + + layout.addStretch() + self.setLayout(layout) + + # 信号绑定与初始状态 + self.mode_single_rb.toggled.connect(self._toggle_input_mode) + self.mode_folder_rb.toggled.connect(self._toggle_input_mode) + self.mode_single_rb.setChecked(True) # 默认选中"单个 CSV" + self._toggle_input_mode() # 根据默认值设置初始显示状态 + + def _toggle_input_mode(self): + """槽函数：根据渲染模式和输入模式动态显示/隐藏对应的输入组件。""" + geotiff_mode = self.render_mode_combo.currentText() == "GeoTIFF 栅格模式" + folder_mode = self.mode_folder_rb.isChecked() + + # CSV 插值模式 + if not geotiff_mode: + self.prediction_csv_file.setVisible(not folder_mode) + self._folder_row_widget.setVisible(folder_mode) + self.recursive_csv_cb.setVisible(folder_mode) + self.geotiff_file.setVisible(False) + self._geotiff_dir_widget.setVisible(False) + # GeoTIFF 栅格模式 + else: + self.prediction_csv_file.setVisible(False) + self._folder_row_widget.setVisible(False) + self.recursive_csv_cb.setVisible(False) + # GeoTIFF + 文件夹批量 → 显示文件夹选择器；否则 → 显示单文件选择器 + self.geotiff_file.setVisible(not folder_mode) + self._geotiff_dir_widget.setVisible(folder_mode) + + def _get_default_work_dir(self): + """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取""" + if hasattr(self, 'work_dir') and self.work_dir: + return str(self.work_dir) + mw = self.window() + if mw and hasattr(mw, 'work_dir') and mw.work_dir: + return str(mw.work_dir) + return "" + + def browse_prediction_csv_dir(self): + default = self._get_default_work_dir() + if default: + default = 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 browse_geotiff_dir(self): + """浏览 GeoTIFF 文件夹（批量模式）""" + default = self._get_default_work_dir() + if default: + default = os.path.join(default, "8_WaterIndex_Images") + d = QFileDialog.getExistingDirectory( + self, "选择水色指数 GeoTIFF 文件夹", default + ) + if d: + self.geotiff_dir_edit.setText(d) + + def _collect_tif_paths_from_folder(self) -> List[str]: + """扫描所选文件夹，收集所有 .tif 和 .bsq 文件路径""" + folder = (self.geotiff_dir_edit.text() or "").strip() + if not folder or not os.path.isdir(folder): + return [] + root = Path(folder) + tif_files = sorted(root.glob("*.tif")) + bsq_files = sorted(root.glob("*.bsq")) + return [str(p) for p in tif_files + bsq_files if p.is_file()] + + def _step10_base_pipeline_kwargs(self) -> dict: + return { + 'boundary_shp_path': self.boundary_file.get_path(), + 'resolution': self.resolution.value(), + 'input_crs': self.input_crs.text(), + 'output_crs': self.output_crs.text(), + 'show_sample_points': self.show_points.isChecked(), + 'use_distance_diffusion': self.use_diffusion.isChecked(), + } + + def get_config(self): + pred_csv = (self.prediction_csv_file.get_path() or "").strip() + folder_mode = self.mode_folder_rb.isChecked() + pred_dir = (self.prediction_csv_dir_edit.text() or "").strip() + geotiff_path = (self.geotiff_file.get_path() or "").strip() + config = { + 'step10_batch_mode': 'folder' if folder_mode else 'single', + 'render_mode': self.render_mode_combo.currentText(), + 'prediction_csv_dir': pred_dir if pred_dir else None, + 'recursive_csv_scan': self.recursive_csv_cb.isChecked(), + 'prediction_csv_path': None if folder_mode else (pred_csv if pred_csv else None), + 'geotiff_path': geotiff_path if geotiff_path else None, + 'geotiff_dir': (self.geotiff_dir_edit.text() or "").strip() or None, + 'boundary_shp_path': self.boundary_file.get_path(), + 'resolution': self.resolution.value(), + 'input_crs': self.input_crs.text(), + 'output_crs': self.output_crs.text(), + 'show_sample_points': self.show_points.isChecked(), + 'use_distance_diffusion': self.use_diffusion.isChecked(), + } + out_dir = (self.output_dir.get_path() or "").strip() + if not folder_mode and pred_csv and out_dir: + stem = Path(pred_csv).stem + config['output_image_path'] = str(Path(out_dir) / f"{stem}_distribution.png") + else: + config['output_image_path'] = None + return config + + def set_config(self, config): + mode = config.get('step10_batch_mode', 'single') + if mode == 'folder': + self.mode_folder_rb.setChecked(True) + else: + self.mode_single_rb.setChecked(True) + render_mode = config.get('render_mode', 'CSV 插值模式') + idx = self.render_mode_combo.findText(render_mode) + if idx >= 0: + self.render_mode_combo.setCurrentIndex(idx) + if config.get('prediction_csv_dir'): + self.prediction_csv_dir_edit.setText(str(config['prediction_csv_dir'])) + if 'recursive_csv_scan' in config: + self.recursive_csv_cb.setChecked(bool(config['recursive_csv_scan'])) + if 'prediction_csv_path' in config and config['prediction_csv_path']: + self.prediction_csv_file.set_path(str(config['prediction_csv_path'])) + if 'geotiff_path' in config and config['geotiff_path']: + self.geotiff_file.set_path(str(config['geotiff_path'])) + if 'geotiff_dir' in config and config['geotiff_dir']: + self.geotiff_dir_edit.setText(str(config['geotiff_dir'])) + if 'boundary_shp_path' in config: + self.boundary_file.set_path(config['boundary_shp_path']) + if 'resolution' in config: + self.resolution.setValue(config['resolution']) + if 'input_crs' in config: + self.input_crs.setText(config['input_crs']) + if 'output_crs' in config: + self.output_crs.setText(config['output_crs']) + if 'show_sample_points' in config: + self.show_points.setChecked(config['show_sample_points']) + if 'use_distance_diffusion' in config: + self.use_diffusion.setChecked(config['use_distance_diffusion']) + if 'output_dir' in config and config['output_dir']: + self.output_dir.set_path(str(config['output_dir'])) + elif config.get('output_image_path'): + p = Path(str(config['output_image_path'])) + if p.parent and str(p.parent) != '.': + self.output_dir.set_path(str(p.parent)) + + def update_from_config(self, work_dir=None, pipeline=None): + """从全局配置自动填充预测结果目录 + + 优先使用 Step8（机器学习预测）的输出目录作为待预测 CSV 目录； + 其次回退到 Step8.5（回归预测）或 Step8.75（自定义回归预测）的输出目录。 + + Args: + work_dir: 工作目录路径 + pipeline: Pipeline 实例（未使用，保留接口兼容性） + """ + try: + import traceback + + if work_dir: + self.work_dir = work_dir + elif hasattr(self, 'work_dir') and self.work_dir: + pass + else: + self.work_dir = None + + main_window = self.window() + if not main_window: + return + + # 1. 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: + self.boundary_file.set_path("") + print("⚠️ 提示：专题图生成模块需传入标准矢量边界文件 (.shp)，请手动选择。") + + # 6. 自动探测 Step 8 输出的水色指数 GeoTIFF（GeoTIFF 渲染模式） + step8_out_dir = Path(self.work_dir) / "8_WaterIndex_Images" if self.work_dir else None + if step8_out_dir and step8_out_dir.is_dir(): + # GeoTIFF 批量模式：填充目录供批量渲染 + if not (self.geotiff_dir_edit.text() or "").strip(): + self.geotiff_dir_edit.setText(str(step8_out_dir)) + # GeoTIFF 单文件模式：默认选中第一个 + tif_files = sorted(step8_out_dir.glob("*.tif")) + if tif_files and not (self.geotiff_file.get_path() or "").strip(): + self.geotiff_file.set_path(str(tif_files[0])) + except Exception as e: + import traceback + print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}") + traceback.print_exc() + + def browse_output_dir(self): + """浏览输出目录""" + default = self._get_default_work_dir() + if default: + default = 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 _start_batch_run(self, csv_list, work_dir, base_kw, out_dir_opt, parent): + """封装 CSV 批量启动逻辑，统一处理信号连接和进度条""" + self.run_button.setEnabled(False) + self.progress_bar.setVisible(True) + self.progress_bar.setValue(0) + self._batch_thread = Step11MapBatchThread(work_dir, csv_list, base_kw, out_dir_opt) + main_win = parent + + def _batch_log(msg, lvl): + if hasattr(main_win, "log_message"): + main_win.log_message(msg, lvl) + + def _on_progress(cur, total): + if total > 0: + self.progress_bar.setMaximum(total) + self.progress_bar.setValue(cur) + self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)") + + self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection) + self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection) + self._batch_thread.finished_ok.connect(self._on_step10_batch_ok, Qt.QueuedConnection) + self._batch_thread.failed.connect(self._on_step10_batch_fail, Qt.QueuedConnection) + self._batch_thread.finished.connect( + lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)), + Qt.QueuedConnection, + ) + self._batch_thread.start() + if hasattr(parent, "log_message"): + parent.log_message(f"专题图批量：共 {len(csv_list)} 个 CSV，工作目录 {work_dir}", "info") + + def run_step(self): + """独立运行步骤11""" + if self._batch_thread and self._batch_thread.isRunning(): + QMessageBox.information(self, "提示", "批量任务正在运行，请稍候。") + return + + boundary_shp_path = self.boundary_file.get_path() + if not boundary_shp_path: + QMessageBox.warning(self, "输入验证失败", "请选择边界文件") + return + if not os.path.exists(boundary_shp_path): + QMessageBox.warning(self, "输入验证失败", "边界文件不存在") + return + + parent = self.parent() + while parent and not hasattr(parent, 'run_single_step'): + parent = parent.parent() + + if not parent or not hasattr(parent, 'run_single_step'): + QMessageBox.critical(self, "错误", "无法找到父级GUI对象") + return + + if self.mode_folder_rb.isChecked(): + # -------- CSV 插值批量 -------- + if self.render_mode_combo.currentText() != "GeoTIFF 栅格模式": + csv_list = self._collect_csv_paths_from_folder() + if not csv_list: + QMessageBox.warning( + self, + "输入验证失败", + "所选文件夹中未找到 .csv 文件，或目录无效。\n" + "可勾选「包含子文件夹」以递归扫描。", + ) + return + if not PIPELINE_AVAILABLE: + QMessageBox.critical(self, "错误", "Pipeline 模块不可用，无法批量生成专题图。") + return + work_dir = getattr(parent, "work_dir", None) or "./work_dir" + work_dir = str(work_dir) + base_kw = self._step10_base_pipeline_kwargs() + out_dir_opt = (self.output_dir.get_path() or "").strip() or None + self._start_batch_run(csv_list, work_dir, base_kw, out_dir_opt, parent) + return + + # -------- GeoTIFF 栅格批量 -------- + tif_list = self._collect_tif_paths_from_folder() + if not tif_list: + QMessageBox.warning( + self, + "输入验证失败", + "所选文件夹中未找到 .tif / .bsq 文件，\n" + "请确认目录包含步骤8输出的水色指数 GeoTIFF 文件。", + ) + return + + out_dir = (self.output_dir.get_path() or "").strip() + if not out_dir: + out_dir = os.path.join(self._get_default_work_dir(), "14_visualization") + os.makedirs(out_dir, exist_ok=True) + + self.run_button.setEnabled(False) + self.progress_bar.setVisible(True) + self.progress_bar.setValue(0) + self._batch_thread = Step11GeoTIFFBatchThread( + tif_paths=tif_list, + output_dir=out_dir, + boundary_shp_path=boundary_shp_path, + input_crs=self.input_crs.text(), + output_crs=self.output_crs.text(), + ) + main_win = parent + + def _batch_log(msg, lvl): + if hasattr(main_win, "log_message"): + main_win.log_message(msg, lvl) + + def _on_progress(cur, total): + if total > 0: + pct = int(cur / total * 100) + self.progress_bar.setMaximum(total) + self.progress_bar.setValue(cur) + self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)") + + self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection) + self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection) + self._batch_thread.finished_ok.connect(self._on_step10_batch_ok, Qt.QueuedConnection) + self._batch_thread.failed.connect(self._on_step10_batch_fail, Qt.QueuedConnection) + self._batch_thread.finished.connect( + lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)), + Qt.QueuedConnection, + ) + self._batch_thread.start() + if hasattr(parent, "log_message"): + parent.log_message(f"GeoTIFF 批量渲染：共 {len(tif_list)} 个文件 → {out_dir}", "info") + return + + # -------- GeoTIFF 栅格单文件模式 -------- + if self.render_mode_combo.currentText() == "GeoTIFF 栅格模式": + geotiff_path = (self.geotiff_file.get_path() or "").strip() + if not geotiff_path: + QMessageBox.warning(self, "输入验证失败", "请选择水色指数 GeoTIFF 文件") + return + if not os.path.isfile(geotiff_path): + QMessageBox.warning(self, "输入验证失败", f"GeoTIFF 文件不存在:\n{geotiff_path}") + return + + boundary_shp_path = self.boundary_file.get_path() + input_crs = self.input_crs.text() + output_crs = self.output_crs.text() + + # 构造输出路径 + out_dir = (self.output_dir.get_path() or "").strip() + if not out_dir: + out_dir = os.path.join(self._get_default_work_dir(), "14_visualization") + os.makedirs(out_dir, exist_ok=True) + tif_stem = Path(geotiff_path).stem + chinese_name = mapper._get_chinese_title(tif_stem) + output_png = os.path.join(out_dir, f"{chinese_name}_专题图.png") + + self.run_button.setEnabled(False) + try: + from src.postprocessing.map import ContentMapper + mapper = ContentMapper() + result_path = mapper.visualize_raster( + raster_tif_path=geotiff_path, + output_file=output_png, + boundary_shp_path=boundary_shp_path if boundary_shp_path else None, + nodata_value=-9999.0, + figsize=(14, 10), + alpha=0.9, + ) + self.run_button.setEnabled(True) + QMessageBox.information( + self, "完成", + f"GeoTIFF 栅格渲染完成！\n{result_path}" + ) + if hasattr(parent, "log_message"): + parent.log_message(f"Step10 GeoTIFF 渲染完成 → {result_path}", "info") + except Exception as e: + self.run_button.setEnabled(True) + QMessageBox.critical(self, "渲染失败", f"{e}\n{traceback.format_exc()[:500]}") + if hasattr(parent, "log_message"): + parent.log_message(str(e), "error") + return + + prediction_csv_path = (self.prediction_csv_file.get_path() or "").strip() + if not prediction_csv_path: + QMessageBox.warning( + self, + "输入验证失败", + "请选择「预测结果 CSV」文件，或切换到「文件夹批量」。", + ) + return + if not os.path.isfile(prediction_csv_path): + QMessageBox.warning(self, "输入验证失败", "预测结果 CSV 不存在或不是文件") + return + + config = self.get_config() + parent.run_single_step('step11_map', {'step11_map': config}) + + def _on_step10_batch_ok(self, n: int): + self.progress_bar.setVisible(False) + QMessageBox.information(self, "完成", f"已批量生成 {n} 个分布图。") + parent = self.parent() + while parent and not hasattr(parent, "log_message"): + parent = parent.parent() + if parent and hasattr(parent, "log_message"): + parent.log_message(f"专题图批量完成，共 {n} 个文件。", "info") + + def _on_step10_batch_fail(self, err: str): + self.progress_bar.setVisible(False) + QMessageBox.critical(self, "失败", f"批量生成中断：\n{err[:900]}") + parent = self.parent() + while parent and not hasattr(parent, "log_message"): + parent = parent.parent() + if parent and hasattr(parent, "log_message"): + parent.log_message(err, "error") diff --git a/src/gui/panels/step11_viz_panel.py b/src/gui/panels/step12_viz_panel.py similarity index 99% rename from src/gui/panels/step11_viz_panel.py rename to src/gui/panels/step12_viz_panel.py index f0ba0e9..8629325 100644 --- a/src/gui/panels/step11_viz_panel.py +++ b/src/gui/panels/step12_viz_panel.py @@ -1211,8 +1211,8 @@ class ChartBrowserDialog(QDialog): QMessageBox.critical(self, "错误", f"保存失败:\n{str(e)}") -class Step11VizPanel(QWidget): - """步骤11：可视化展示""" +class Step12VizPanel(QWidget): + """步骤12：可视化展示""" def __init__(self, parent=None): super().__init__(parent) self.work_dir = None diff --git a/src/gui/panels/step12_panel.py b/src/gui/panels/step13_panel.py similarity index 99% rename from src/gui/panels/step12_panel.py rename to src/gui/panels/step13_panel.py index ab97b71..22404bf 100644 --- a/src/gui/panels/step12_panel.py +++ b/src/gui/panels/step13_panel.py @@ -225,6 +225,6 @@ class Step12Panel(QWidget): parent = parent.parent() if parent and hasattr(parent, 'run_single_step'): - parent.run_single_step('step12', {'step12': config}) + parent.run_single_step('step13_report', {'step13_report': config}) else: QMessageBox.critical(self, "错误", "无法找到父级GUI对象") diff --git a/src/gui/panels/step12_report_panel.py b/src/gui/panels/step13_report_panel.py similarity index 98% rename from src/gui/panels/step12_report_panel.py rename to src/gui/panels/step13_report_panel.py index d0842a3..d911987 100644 --- a/src/gui/panels/step12_report_panel.py +++ b/src/gui/panels/step13_report_panel.py @@ -79,8 +79,8 @@ class ReportGenerateThread(QThread): self.failed.emit(f"{e}\n{traceback.format_exc()}") -class Step12ReportPanel(QWidget): - """步骤12：分析报告生成。AI 配置统一由 AISettingsDialog 管理，本面板不持有配置状态。""" +class Step13ReportPanel(QWidget): + """步骤13：分析报告生成。AI 配置统一由 AISettingsDialog 管理，本面板不持有配置状态。""" def __init__(self, main_window=None, parent=None): super().__init__(parent) diff --git a/src/gui/panels/step4_sampling_panel.py b/src/gui/panels/step4_sampling_panel.py index d62cb70..20b6b23 100644 --- a/src/gui/panels/step4_sampling_panel.py +++ b/src/gui/panels/step4_sampling_panel.py @@ -223,8 +223,8 @@ class Step4SamplingPanel(QWidget): main_window = self.window() if hasattr(main_window, 'run_single_step'): - config = {'step4': self.get_config()} - main_window.run_single_step('step4', config) + config = {'step4_sampling': self.get_config()} + main_window.run_single_step('step4_sampling', config) def _check_csv_exists(self): """检查 output csv 是否存在，驱动预览按钮启停""" diff --git a/src/gui/panels/step5_clean_panel.py b/src/gui/panels/step5_clean_panel.py index 8d696db..34f13f4 100644 --- a/src/gui/panels/step5_clean_panel.py +++ b/src/gui/panels/step5_clean_panel.py @@ -143,8 +143,8 @@ class Step5CleanPanel(QWidget): main_window = self.window() if hasattr(main_window, 'run_single_step'): - config = {'step5': self.get_config()} - main_window.run_single_step('step5', config) + config = {'step5_clean': self.get_config()} + main_window.run_single_step('step5_clean', config) def reset_preview(self, message="请选择CSV文件并点击刷新预览"): """重置预览表格""" diff --git a/src/gui/panels/step6_feature_panel.py b/src/gui/panels/step6_feature_panel.py index 5536254..af13e55 100644 --- a/src/gui/panels/step6_feature_panel.py +++ b/src/gui/panels/step6_feature_panel.py @@ -235,5 +235,5 @@ class Step6FeaturePanel(QWidget): # 获取主窗口并运行步骤 main_window = self.window() if hasattr(main_window, 'run_single_step'): - config = {'step5': self.get_config()} - main_window.run_single_step('step5', config) + config = {'step6_feature': self.get_config()} + main_window.run_single_step('step6_feature', config) diff --git a/src/gui/panels/step8_ml_train_panel.py b/src/gui/panels/step8_ml_train_panel.py index 1675c3e..7a39df3 100644 --- a/src/gui/panels/step8_ml_train_panel.py +++ b/src/gui/panels/step8_ml_train_panel.py @@ -5,345 +5,411 @@ Step8 面板 - 机器学习建模 """ import os -import sys -import pandas as pd -import numpy as np -from pathlib import Path -from typing import Dict, List, Optional, Tuple from PyQt5.QtWidgets import ( - QWidget, QVBoxLayout, QGroupBox, QGridLayout, - QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox, - QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView, - QRadioButton, QButtonGroup + QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout, + QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox, + QPushButton, QFileDialog, QMessageBox, ) from PyQt5.QtCore import Qt -from PyQt5.QtGui import QColor, QBrush, QFont from src.gui.components.custom_widgets import FileSelectWidget from src.gui.styles import ModernStylesheet -def get_resource_path(relative_path: str) -> str: - """适配开发与 PyInstaller 环境的路径获取逻辑。""" - if hasattr(sys, '_MEIPASS'): - internal = os.path.join(sys._MEIPASS, '_internal', relative_path) - if os.path.exists(internal): - return internal - return os.path.join(sys._MEIPASS, relative_path) +# ============================================================ +# 中文映射表（内部键名 -> 显示文本） +# ============================================================ - exe_dir = os.path.dirname(sys.executable) - internal = os.path.join(exe_dir, '_internal', relative_path) - if os.path.exists(internal): - return internal +# 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)', +} - base_dir = Path(__file__).resolve().parent.parent / "model" - return str(base_dir / os.path.basename(relative_path)) +# 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 Step8MlTrainPanel(QWidget): """步骤8：机器学习建模""" - COLOR_RATIO = QColor(255, 255, 255) - COLOR_CONCENTRATION = QColor(220, 240, 255) - COLOR_HEADER = QColor(245, 245, 245) - def __init__(self, parent=None): super().__init__(parent) - self.index_checkboxes: Dict[str, QListWidgetItem] = {} - self.work_dir: Optional[str] = None - self.builtin_formula_path = get_resource_path("waterindex.csv") - self._formula_type_map: Dict[str, str] = {} - self._formula_color_map: Dict[str, QColor] = {} - self._formula_coef_map: Dict[str, List[float]] = {} - self.init_ui() - self._auto_load_formulas() def init_ui(self): - main_layout = QVBoxLayout() - main_layout.setContentsMargins(20, 20, 20, 20) - main_layout.setSpacing(10) + layout = QVBoxLayout() - # 1. 公式配置源 (只读) - path_group = QGroupBox("公式配置源 (内置)") - path_layout = QVBoxLayout() - self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)") - self.formula_csv_widget.set_path(self.builtin_formula_path) - self.formula_csv_widget.set_read_only(True) - self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;") - path_layout.addWidget(self.formula_csv_widget) - path_group.setLayout(path_layout) - main_layout.addWidget(path_group) + # 标题 - # 2. 训练数据输入 - input_group = QGroupBox("输入样本数据") - input_layout = QVBoxLayout() - self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)") - input_layout.addWidget(self.training_data_widget) - input_group.setLayout(input_layout) - main_layout.addWidget(input_group) - # 3. 公式选择区 (分组 ListWidget) - self.formula_group = QGroupBox("待计算水质指数勾选") - formula_outer_layout = QVBoxLayout() + # 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) - btn_layout = QHBoxLayout() - self.select_all_btn = QPushButton("全选") - self.deselect_all_btn = QPushButton("清空") - self.select_ratio_btn = QPushButton("仅选比值型") - self.select_conc_btn = QPushButton("仅选浓度型") - self.select_all_btn.clicked.connect(self.select_all_formulas) - self.deselect_all_btn.clicked.connect(self.deselect_all_formulas) - self.select_ratio_btn.clicked.connect(self._select_ratio_only) - self.select_conc_btn.clicked.connect(self._select_conc_only) - btn_layout.addWidget(self.select_all_btn) - btn_layout.addWidget(self.deselect_all_btn) - btn_layout.addWidget(self.select_ratio_btn) - btn_layout.addWidget(self.select_conc_btn) - btn_layout.addStretch() + # 机器学习模型页面 + self.ml_page = QWidget() + self.create_ml_page() + layout.addWidget(self.ml_page) - self.refresh_button = QPushButton("重新加载") - self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False)) - btn_layout.addWidget(self.refresh_button) + # 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) - formula_outer_layout.addLayout(btn_layout) + # 启用步骤 + self.enable_checkbox = QCheckBox("启用此步骤") + self.enable_checkbox.setChecked(False) + layout.addWidget(self.enable_checkbox) - scroll = QScrollArea() - scroll.setWidgetResizable(True) - scroll.setMinimumHeight(280) - self.scroll_content = QWidget() - self.formula_layout = QVBoxLayout(self.scroll_content) - self.formula_layout.setContentsMargins(4, 4, 4, 4) - self.formula_layout.setSpacing(2) - self.formula_layout.setAlignment(Qt.AlignTop) + # 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.formula_list = QListWidget() - self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection) - self.formula_list.itemChanged.connect(self._on_item_changed) - self.formula_layout.addWidget(self.formula_list) + layout.addStretch() + self.setLayout(layout) - scroll.setWidget(self.scroll_content) - formula_outer_layout.addWidget(scroll) + def create_ml_page(self): + """创建机器学习模型页面""" + layout = QVBoxLayout() - self.formula_group.setLayout(formula_outer_layout) - main_layout.addWidget(self.formula_group) + # 参数设置 + params_group = QGroupBox("训练参数") + params_layout = QFormLayout() - # 4. 输出选项 - output_group = QGroupBox("输出模式") - output_layout = QVBoxLayout() + self.feature_start = QLineEdit() + self.feature_start.setText("374.285004") + params_layout.addRow("特征起始列:", self.feature_start) - mode_layout = QHBoxLayout() - self.mode_group = QButtonGroup() - self.radio_both = QRadioButton("两者皆出") - self.radio_wide = QRadioButton("仅宽表") - self.radio_single = QRadioButton("仅单文件") - self.mode_group.addButton(self.radio_both, 0) - self.mode_group.addButton(self.radio_wide, 1) - self.mode_group.addButton(self.radio_single, 2) - self.radio_both.setChecked(True) - mode_layout.addWidget(self.radio_both) - mode_layout.addWidget(self.radio_wide) - mode_layout.addWidget(self.radio_single) - mode_layout.addStretch() - output_layout.addLayout(mode_layout) + 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) - self.enable_checkbox = QCheckBox("启用计算流程") - self.enable_checkbox.setChecked(True) - output_layout.addWidget(self.enable_checkbox) + params_group.setLayout(params_layout) + layout.addWidget(params_group) - output_group.setLayout(output_layout) - main_layout.addWidget(output_group) + # 预处理方法 - 多选 + preproc_group = QGroupBox("预处理方法 (可多选)") + preproc_layout = QVBoxLayout() - # 5. 运行按钮 - self.run_button = QPushButton("立即执行计算") - self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success')) - self.run_button.setMinimumHeight(40) - self.run_button.clicked.connect(self.run_step) - main_layout.addWidget(self.run_button) + preproc_grid = QGridLayout() + self.preproc_checkboxes = {} + preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT'] - self.setLayout(main_layout) + 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) - def _on_item_changed(self, item: QListWidgetItem): - if item.checkState() == Qt.Checked: - bg_color = self.COLOR_RATIO - for name, ref_item in self.index_checkboxes.items(): - if ref_item is item: - bg_color = self._formula_color_map.get(name, self.COLOR_RATIO) - break - item.setBackground(QBrush(bg_color)) - else: - item.setBackground(QBrush(self.COLOR_RATIO)) + 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() - def _auto_load_formulas(self): - if os.path.exists(self.builtin_formula_path): - self.refresh_formulas(silent=True) - else: - print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}") + preproc_layout.addLayout(preproc_grid) + preproc_layout.addLayout(button_layout) + preproc_group.setLayout(preproc_layout) + layout.addWidget(preproc_group) - 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 + # 模型选择 - 多选 + model_group = QGroupBox("模型类型 (可多选)") + model_layout = QVBoxLayout() - try: - df = None - for enc in ('utf-8', 'gbk', 'utf-8-sig'): - try: - df = pd.read_csv(path, encoding=enc) - if 'Formula_Name' in df.columns: - break - except Exception: - continue + model_grid = QGridLayout() + self.model_checkboxes = {} - if df is None or 'Formula_Name' not in df.columns: - if not silent: - QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列") - return - - self._formula_type_map.clear() - self._formula_coef_map.clear() - for _, row in df.iterrows(): - name = str(row['Formula_Name']).strip() - if not name: - continue - ftype = str(row.get('Formula_Type', 'ratio')).strip().lower() - self._formula_type_map[name] = ftype - - coef_str = str(row.get('Coefficient', '')).strip() - if coef_str: - try: - coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()] - self._formula_coef_map[name] = coeffs - except Exception: - self._formula_coef_map[name] = [] - else: - self._formula_coef_map[name] = [] - - self.formula_list.clear() - self.index_checkboxes.clear() - - self._formula_color_map.clear() - for name, ftype in self._formula_type_map.items(): - item = QListWidgetItem(name, self.formula_list) - item.setCheckState(Qt.Checked) - if ftype == 'concentration': - bg_color = QColor(220, 240, 255) - else: - bg_color = self.COLOR_RATIO - self._formula_color_map[name] = bg_color - item.setBackground(QBrush(bg_color)) - self.index_checkboxes[name] = item - - self.formula_list.adjustSize() - print(f"✅ 加载 {len(self.index_checkboxes)} 个公式") - - except Exception as e: - if not silent: - QMessageBox.critical(self, "加载失败", f"原因: {str(e)}") - - def _select_ratio_only(self): - for name, item in self.index_checkboxes.items(): - ftype = self._formula_type_map.get(name, 'ratio') - item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked) - - def _select_conc_only(self): - for name, item in self.index_checkboxes.items(): - ftype = self._formula_type_map.get(name, 'ratio') - item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked) - - def select_all_formulas(self): - for item in self.index_checkboxes.values(): - item.setCheckState(Qt.Checked) - - def deselect_all_formulas(self): - for item in self.index_checkboxes.values(): - item.setCheckState(Qt.Unchecked) - - def get_config(self) -> Dict: - selected = [ - name for name, item in self.index_checkboxes.items() - if item.checkState() == Qt.Checked + 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']) ] - formula_coefficients = { - name: self._formula_coef_map.get(name, []) - for name in selected - } - return { - 'training_csv_path': self.training_data_widget.get_path(), - 'formula_csv_file': self.builtin_formula_path, - 'formula_names': selected, - 'formula_coefficients': formula_coefficients, - 'enabled': self.enable_checkbox.isChecked(), - 'output_mode': self.mode_group.checkedId(), - } - def set_config(self, config: Dict): + row = 0 + for group_name, models in model_groups: + group_label = QLabel(f"{group_name}") + 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_data_widget.set_path(config['training_csv_path']) - if 'formula_names' in config: - sel = set(config['formula_names']) - for name, item in self.index_checkboxes.items(): - item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked) - self.enable_checkbox.setChecked(config.get('enabled', True)) - if 'output_mode' in config: - btn = self.mode_group.button(config['output_mode']) - if btn: - btn.setChecked(True) + 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 - main = self.window() - if hasattr(main, 'step5_panel'): - p5 = main.step5_panel.output_file.get_path() - if p5: - if not os.path.isabs(p5): - p5 = os.path.join(self.work_dir or '', p5) - p5 = p5.replace('\\', '/') - self.training_data_widget.set_path(p5) + elif hasattr(self, 'work_dir') and self.work_dir: + pass + else: + self.work_dir = None - def _get_work_dir(self) -> Optional[str]: + # 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: - return self.work_dir - main = self.window() - if hasattr(main, 'work_dir') and main.work_dir: - return main.work_dir - return None - - def _get_coord_cols(self, df: pd.DataFrame) -> Tuple[str, str]: - coord_candidates = ['lon', 'lng', 'longitude', '经度', 'x', 'lon_utm', 'utm_x', 'pixel_x'] - lat_candidates = ['lat', 'latitude', '纬度', 'y', 'lat_utc', 'utm_y', 'pixel_y'] - - x_col, y_col = None, None - for col in df.columns: - cl = col.lower() - if x_col is None and any(c in cl for c in coord_candidates): - x_col = col - if y_col is None and any(c in cl for c in lat_candidates): - y_col = col - - if x_col is None and len(df.columns) >= 2: - x_col = df.columns[0] - if y_col is None and len(df.columns) >= 2: - y_col = df.columns[1] - - return x_col or 'x_coord', y_col or 'y_coord' + 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): - config = self.get_config() - - if not config['enabled']: - QMessageBox.information(self, "提示", "已禁用计算流程（启用计算流程未勾选）") - return - - training_path = config['training_csv_path'] - if not training_path or not os.path.exists(training_path): - QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件") + """独立运行步骤8""" + training_csv_path = self.training_csv_file.get_path() + if not training_csv_path: + QMessageBox.warning(self, "输入错误", "请选择训练数据CSV文件！") return main_window = self.window() if hasattr(main_window, 'run_single_step'): - pipeline_config = {'step8_ml_train': config} - main_window.run_single_step('step8_ml_train', pipeline_config) \ No newline at end of file + config = {'step8_ml_train': self.get_config()} + main_window.run_single_step('step8_ml_train', 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()] + } diff --git a/src/gui/panels/step9_ml_predict_panel.py b/src/gui/panels/step9_ml_predict_panel.py index bc22301..1576598 100644 --- a/src/gui/panels/step9_ml_predict_panel.py +++ b/src/gui/panels/step9_ml_predict_panel.py @@ -439,11 +439,11 @@ class Step9MlPredictPanel(QWidget): main_window = self.window() if hasattr(main_window, 'run_single_step'): config = { - 'step11_ml': self.get_config(), + 'step9_ml_predict': self.get_config(), '_external_models_dict': checked_dict, '_external_model_dir': self.external_model_dir, } - main_window.run_single_step('step11_ml', config) + main_window.run_single_step('step9_ml_predict', config) return # 默认流程：使用模型目录 @@ -454,5 +454,5 @@ class Step9MlPredictPanel(QWidget): 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) \ No newline at end of file + config = {'step9_ml_predict': self.get_config()} + main_window.run_single_step('step9_ml_predict', config) \ No newline at end of file diff --git a/src/gui/water_quality_gui.py b/src/gui/water_quality_gui.py index 35cdd85..9ec130b 100644 --- a/src/gui/water_quality_gui.py +++ b/src/gui/water_quality_gui.py @@ -117,17 +117,17 @@ from src.gui.components.custom_widgets import FileSelectWidget from src.gui.panels.step1_panel import Step1Panel from src.gui.panels.step2_panel import Step2Panel from src.gui.panels.step3_panel import Step3Panel -from src.gui.panels.step4_sampling_panel import Step4SamplingPanel # 采样点布设（原step10→新step4） +from src.gui.panels.step4_sampling_panel import Step4SamplingPanel # 采样点布设 from src.gui.panels.step5_clean_panel import Step5CleanPanel # 数据清洗 from src.gui.panels.step6_feature_panel import Step6FeaturePanel # 光谱特征 from src.gui.panels.step7_index_panel import Step7IndexPanel # 水质光谱指数 -from src.gui.panels.step10_map_panel import Step10MapPanel # 水色指数反演 +from src.gui.panels.step10_watercolor_panel import Step10WatercolorPanel # 水色指数反演 from src.gui.panels.step8_ml_train_panel import Step8MlTrainPanel # 机器学习建模 from src.gui.panels.step9_ml_predict_panel import Step9MlPredictPanel # 机器学习预测 -from src.gui.panels.step14_panel import Step14Panel from src.gui.dialogs import BandConfirmDialog, AISettingsDialog -from src.gui.panels.step11_viz_panel import Step11VizPanel # 可视化（覆盖旧 step11_viz_panel.py） -from src.gui.panels.step12_report_panel import Step12ReportPanel # 报告生成 +from src.gui.panels.step11_map_panel import Step11MapPanel # 专题图生成 +from src.gui.panels.step12_viz_panel import Step12VizPanel # 可视化 +from src.gui.panels.step13_report_panel import Step13ReportPanel # 报告生成 # Pipeline 核心异常（用于预检弹窗） from src.core.pipeline.runner import PipelineHalt @@ -1399,7 +1399,7 @@ class WaterQualityGUI(QMainWindow): 'step9_ml_predict': { 'predictions': '11_12_13_predictions/Machine_Learning_Prediction/' }, - 'step10_map': { + 'step11_map': { 'distribution_maps': '14_visualization/' } } @@ -1435,7 +1435,7 @@ class WaterQualityGUI(QMainWindow): 'sampling_csv_path': ('step4_sampling', 'sampling_points', 'sampling_csv_file'), 'models_dir': ('step8_ml_train', 'models', 'models_dir_file') }, - 'step10_map': { + 'step11_map': { 'prediction_csv_path': ('step9_ml_predict', 'predictions', 'prediction_csv_file') } } @@ -1826,9 +1826,10 @@ class WaterQualityGUI(QMainWindow): ], "阶段四：预测与成果输出": [ ("step9_ml_predict", "9. 机器学习预测"), - ("step10_map", "10. 专题图生成"), - ("step11_viz", "11. 可视化展示"), - ("step12_report", "12. 分析报告生成") + ("step10_watercolor", "10. 水色指数反演"), + ("step11_map", "11. 专题图生成"), + ("step12_viz", "12. 可视化展示"), + ("step13_report", "13. 分析报告生成") ] } @@ -1936,17 +1937,17 @@ class WaterQualityGUI(QMainWindow): self.step9_ml_predict_panel = Step9MlPredictPanel() self.step_stack.addTab(self.create_scroll_area(self.step9_ml_predict_panel), QIcon(self.get_icon_path("10.png")), "机器学习预测") - self.step10_map_panel = Step10MapPanel() - self.step_stack.addTab(self.create_scroll_area(self.step10_map_panel), QIcon(self.get_icon_path("10.png")), "专题图生成") + self.step10_watercolor_panel = Step10WatercolorPanel() + self.step_stack.addTab(self.create_scroll_area(self.step10_watercolor_panel), QIcon(self.get_icon_path("10.png")), "水色指数反演") - self.step14_panel = Step14Panel() - self.step_stack.addTab(self.create_scroll_area(self.step14_panel), QIcon(self.get_icon_path("11.png")), "专题图生成") + self.step11_map_panel = Step11MapPanel() + self.step_stack.addTab(self.create_scroll_area(self.step11_map_panel), QIcon(self.get_icon_path("10.png")), "专题图生成") - self.step11_viz_panel = Step11VizPanel() - self.step_stack.addTab(self.create_scroll_area(self.step11_viz_panel), QIcon(self.get_icon_path("9.png")), "可视化") + self.step12_viz_panel = Step12VizPanel() + self.step_stack.addTab(self.create_scroll_area(self.step12_viz_panel), QIcon(self.get_icon_path("9.png")), "可视化") - self.step12_report_panel = Step12ReportPanel(main_window=self) - self.step_stack.addTab(self.create_scroll_area(self.step12_report_panel), QIcon(self.get_icon_path("10.png")), "报告生成") + self.step13_report_panel = Step13ReportPanel(main_window=self) + self.step_stack.addTab(self.create_scroll_area(self.step13_report_panel), QIcon(self.get_icon_path("10.png")), "报告生成") # 连接Tab切换信号，实现双向同步（必须在step_stack创建后） self.step_stack.currentChanged.connect(self.on_tab_changed) @@ -2085,18 +2086,11 @@ class WaterQualityGUI(QMainWindow): # 根据步骤ID查找对应的tab索引 step_id_to_tab = { - 'step1': 0, - 'step2': 1, - 'step3': 2, - 'step4_sampling': 3, - 'step5_clean': 4, - 'step6_feature': 5, - 'step7_index': 6, - 'step8_ml_train': 7, - 'step9_ml_predict': 8, - 'step10_map': 9, - 'step11_viz': 11, - 'step12_report': 12, + 'step1': 0, 'step2': 1, 'step3': 2, 'step4_sampling': 3, + 'step5_clean': 4, 'step6_feature': 5, 'step7_index': 6, + 'step8_ml_train': 7, 'step9_ml_predict': 8, + 'step10_watercolor': 9, 'step11_map': 10, + 'step12_viz': 11, 'step13_report': 12, } if item_data in step_id_to_tab: @@ -2110,21 +2104,13 @@ class WaterQualityGUI(QMainWindow): if index < 0: return - # Tab索引到步骤ID的反向映射 + # Tab索引到步骤ID的反向映射（13个Tab，index 0-12） tab_to_step_id = { - 0: 'step1', - 1: 'step2', - 2: 'step3', - 3: 'step4_sampling', - 4: 'step5_clean', - 5: 'step6_feature', - 6: 'step7_index', - 7: 'step8_ml_train', - 8: 'step9_ml_predict', - 9: 'step10_map', - 10: None, # 遗留 step14_panel，保留 tab 但不加入 process_stages - 11: 'step11_viz', - 12: 'step12_report', + 0: 'step1', 1: 'step2', 2: 'step3', 3: 'step4_sampling', + 4: 'step5_clean', 5: 'step6_feature', 6: 'step7_index', + 7: 'step8_ml_train', 8: 'step9_ml_predict', + 9: 'step10_watercolor', 10: 'step11_map', + 11: 'step12_viz', 12: 'step13_report', } if index not in tab_to_step_id: @@ -2143,49 +2129,27 @@ class WaterQualityGUI(QMainWindow): self.step_list.setCurrentRow(row) break - # Step2 切换时自动填充数据流转路径 - if index == 1: - self.step2_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) + # 面板自动填充：统一 mapping 覆盖 index 0-12 + mapping = { + 0: (self.step1_panel, "Step1"), + 1: (self.step2_panel, "Step2"), + 2: (self.step3_panel, "Step3"), + 3: (self.step4_sampling_panel, "Step4"), + 4: (self.step5_clean_panel, "Step5"), + 5: (self.step6_feature_panel, "Step6"), + 6: (self.step7_index_panel, "Step7"), + 7: (self.step8_ml_train_panel, "Step8"), + 8: (self.step9_ml_predict_panel, "Step9"), + 9: (self.step10_watercolor_panel, "Step10"), # 水色指数反演 + 10: (self.step11_map_panel, "Step11"), # 专题图生成 + 11: (self.step12_viz_panel, "Step12"), + 12: (self.step13_report_panel, "Step13") + } - # Step3 切换时自动填充数据流转路径 - elif index == 2: - self.step3_panel.update_from_config(work_dir=self.work_dir) - - # Step4（采样点布设）切换时自动填充输出路径 - elif index == 3: - self.step4_sampling_panel.update_from_config(work_dir=self.work_dir) - - # Step5（数据清洗）切换时自动填充数据流转路径 - elif index == 4: - self.step5_clean_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step6（光谱特征）切换时自动填充输出路径 - elif index == 5: - self.step6_feature_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step7（水质光谱指数计算）切换时自动填充水质参数 CSV - elif index == 6: - self.step7_index_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step8（机器学习建模）切换时自动填充训练数据和输出路径 - elif index == 7: - self.step8_ml_train_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step9（机器学习预测）切换时自动填充采样光谱和模型目录 - elif index == 8: - self.step9_ml_predict_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step10（水色指数反演）切换时自动填充光谱数据和输出路径 - elif index == 9: - self.step10_map_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step12（专题图生成）切换时自动填充预测结果目录 - elif index == 10: - self.step14_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) - - # Step13（可视化分析）切换时自动推断图像目录并加载目录树 - elif index == 11: - self.step11_viz_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) + if index in mapping: + panel, _ = mapping[index] + if hasattr(panel, 'update_from_config'): + panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline) def apply_stylesheet(self): """应用样式表 - 应用现代化设计风格""" @@ -2234,12 +2198,12 @@ class WaterQualityGUI(QMainWindow): self.step7_index_panel.set_config(config['step7_index']) if 'step9_ml_predict' in config: self.step9_ml_predict_panel.set_config(config['step9_ml_predict']) - if 'step14' in config: - self.step14_panel.set_config(config['step14']) - if 'step11_viz' in config: - self.step11_viz_panel.set_config(config['step11_viz']) - if 'step12_report' in config: - self.step12_report_panel.set_config(config['step12_report']) + if 'step11_map' in config: + self.step11_map_panel.set_config(config['step11_map']) + if 'step12_viz' in config: + self.step12_viz_panel.set_config(config['step12_viz']) + if 'step13_report' in config: + self.step13_report_panel.set_config(config['step13_report']) self.config_file = file_path self.log_message(f"已加载配置: {file_path}", "info") @@ -2282,10 +2246,9 @@ class WaterQualityGUI(QMainWindow): 'step7_index': self.step7_index_panel.get_config(), 'step8_ml_train': self.step8_ml_train_panel.get_config(), 'step9_ml_predict': self.step9_ml_predict_panel.get_config(), - 'step10_map': self.step10_map_panel.get_config(), - 'step11_viz': self.step11_viz_panel.get_config(), - 'step12_report': self.step12_report_panel.get_config(), - 'step14': self.step14_panel.get_config(), + 'step11_map': self.step11_map_panel.get_config(), + 'step12_viz': self.step12_viz_panel.get_config(), + 'step13_report': self.step13_report_panel.get_config(), } return config @@ -2338,10 +2301,9 @@ class WaterQualityGUI(QMainWindow): 'step7_index': self.step7_index_panel, 'step8_ml_train': self.step8_ml_train_panel, 'step9_ml_predict': self.step9_ml_predict_panel, - 'step10_map': self.step10_map_panel, - 'step11_viz': self.step11_viz_panel, - 'step12_report': self.step12_report_panel, - 'step14': self.step14_panel, + 'step11_map': self.step11_map_panel, + 'step12_viz': self.step12_viz_panel, + 'step13_report': self.step13_report_panel, } return panel_map.get(step_id) @@ -2440,10 +2402,10 @@ class WaterQualityGUI(QMainWindow): '8_Regression_Modeling': 'step8_ml_train', '9_Custom_Regression_Modeling': 'step9_ml_predict', '11_12_13_predictions/Machine_Learning_Prediction': 'step9_ml_predict', - '11_12_13_predictions/Non_Empirical_Prediction': 'step10_map', - '11_12_13_predictions/Custom_Regression_Prediction': 'step11_viz', - '14_visualization': 'step12_report', - '14_geotiff_batch_rendering': 'step14' + '11_12_13_predictions/Non_Empirical_Prediction': 'step11_map', + '11_12_13_predictions/Custom_Regression_Prediction': 'step12_viz', + '14_visualization': 'step13_report', + '10_geotiff_batch_rendering': 'step11_map' } for subdir, step_ids in subdirs.items(): @@ -2493,7 +2455,7 @@ class WaterQualityGUI(QMainWindow): discovered_outputs[step_id]['water_indices'] = str(file_path) elif 'sampling_spectra' in file_name and step_id == 'step4_sampling': discovered_outputs[step_id]['sampling_points'] = str(file_path) - elif file_name.endswith('.csv') and step_id in ['step9_ml_predict', 'step10_map', 'step11_viz']: + elif file_name.endswith('.csv') and step_id in ['step9_ml_predict', 'step11_map', 'step12_viz']: discovered_outputs[step_id]['predictions'] = str(file_path) # 更新内部记录 @@ -2517,7 +2479,7 @@ class WaterQualityGUI(QMainWindow): self.scan_work_directory_for_files(work_path) step_order = ['step2', 'step3', 'step4_sampling', 'step5_clean', 'step6_feature', 'step7_index', - 'step8_ml_train', 'step9_ml_predict', 'step10_map', 'step11_viz', 'step12_report', 'step14'] + 'step8_ml_train', 'step9_ml_predict', 'step11_map', 'step12_viz', 'step13_report'] filled_count = 0 for step_id in step_order: @@ -2544,10 +2506,9 @@ class WaterQualityGUI(QMainWindow): ('step7_index', self.step7_index_panel), ('step8_ml_train', self.step8_ml_train_panel), ('step9_ml_predict', self.step9_ml_predict_panel), - ('step10_map', self.step10_map_panel), - ('step11_viz', self.step11_viz_panel), - ('step12_report', self.step12_report_panel), - ('step14', self.step14_panel) + ('step11_map', self.step11_map_panel), + ('step12_viz', self.step12_viz_panel), + ('step13_report', self.step13_report_panel), ] for step_id, panel in panels_with_dependencies: @@ -2617,10 +2578,10 @@ class WaterQualityGUI(QMainWindow): self.statusBar().showMessage(f"工作目录: {dir_path}") # 同步到可视化面板 - if hasattr(self, 'step11_viz_panel'): - self.step11_viz_panel.set_work_dir(dir_path) - if hasattr(self, 'step12_report_panel'): - self.step12_report_panel.set_work_dir(dir_path) + if hasattr(self, 'step12_viz_panel'): + self.step12_viz_panel.set_work_dir(dir_path) + if hasattr(self, 'step13_report_panel'): + self.step13_report_panel.set_work_dir(dir_path) def open_work_directory(self): """打开工作目录""" @@ -3179,7 +3140,7 @@ class WaterQualityGUI(QMainWindow): step_id_to_tab_training = { 'step1': 0, 'step2': 1, 'step3': 2, 'step4_sampling': 3, 'step5_clean': 4, 'step6_feature': 5, 'step7_index': 6, 'step9_ml_predict': 7, - 'step10_map': 8, 'step14': 10, 'step11_viz': 11, 'step12_report': 12 + 'step10_watercolor': 9, 'step11_map': 10, 'step12_viz': 11, 'step13_report': 12 } for step_id in disabled_step_ids: