WQ_GUI/src/gui/panels/step9_ml_predict_panel.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step11 面板 - 机器学习预测
"""

import os
import sys
from pathlib import Path

# 路径归一化 helper（与 pipeline.get_step_output_dir 互为表里）
_HERE = os.path.dirname(os.path.abspath(__file__))
if _HERE not in sys.path:
    sys.path.insert(0, _HERE)
from _step_path_resolver import get_step_output_path, resolve_step_widget, resolve_subdir

from PyQt5.QtWidgets import (
    QWidget, QVBoxLayout, QGroupBox, 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 Step9MlPredictPanel(QWidget):
    """步骤9：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._on_run_single_clicked)
        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 = resolve_subdir(default, 'ml_prediction')
        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
                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 Step4（采样点布设）读取全湖采样点 CSV 路径
            if main_window and hasattr(main_window, 'step4_sampling_panel'):
                step4_widget = getattr(main_window.step4_sampling_panel, 'output_file', None)
                step4_output_path = ""
                if hasattr(step4_widget, 'get_path'):
                    step4_output_path = step4_widget.get_path() or ""
                elif hasattr(step4_widget, 'text'):
                    step4_output_path = step4_widget.text() or ""

                if step4_output_path:
                    if not os.path.isabs(step4_output_path):
                        step4_output_path = os.path.join(self.work_dir or '', step4_output_path).replace('\\', '/')
                    existing = self.sampling_csv_file.get_path()
                    if not existing or not existing.strip():
                        self.sampling_csv_file.set_path(step4_output_path)

            # 2. 尝试从 Step8（监督建模）读取模型目录（修复张冠李戴：原代码 main_window.step9_panel 不存在）
            step8_models_dir = get_step_output_path(
                main_window, 'models_dir', work_dir=self.work_dir,
                widget_attr='output_dir', fallback_key='step8_ml_train',
            )
            if step8_models_dir:
                existing_models = self.models_dir_file.get_path()
                if not existing_models or not existing_models.strip():
                    self.models_dir_file.set_path(step8_models_dir)

            # 3. 自动填充输出路径（机器学习预测目录，归属 step9 → 9_ML_Prediction）
            #    注：9_ML_Prediction 是 prediction_dir 的子目录，用本地约定
            if self.work_dir:
                output_dir = resolve_subdir(self.work_dir, 'ml_prediction')
                os.makedirs(output_dir, exist_ok=True)
                existing_out = self.output_file.get_path()
                if not existing_out or not existing_out.strip():
                    self.output_file.set_path(output_dir)
        except Exception as e:
            import traceback
            print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}")
            traceback.print_exc()

    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 = resolve_subdir(default, 'ml_prediction')
        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 _on_run_single_clicked(self):
        """通过 EventBus 发布单步执行请求（解耦面板与 PipelineExecutor）。"""
        from src.gui.core.event_bus import global_event_bus

        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
            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
            config = {
                'step9_ml_predict': self.get_config(),
                '_external_models_dict': checked_dict,
                '_external_model_dir': self.external_model_dir,
            }
            global_event_bus.publish('RequestRunSingleStep', {
                'step_name': 'step9_ml_predict',
                'config': 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

        config = {'step9_ml_predict': self.get_config()}
        global_event_bus.publish('RequestRunSingleStep', {
            'step_name': 'step9_ml_predict',
            'config': config,
        })

    def run_step(self):
        """独立运行步骤11（旧版 parent 链上溯方式，保留兼容）。"""
        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
            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 = {
                    'step9_ml_predict': self.get_config(),
                    '_external_models_dict': checked_dict,
                    '_external_model_dir': self.external_model_dir,
                }
                main_window.run_single_step('step9_ml_predict', 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 = {'step9_ml_predict': self.get_config()}
            main_window.run_single_step('step9_ml_predict', config)