进一步优化save_result（提取函数)

app/export/__init__.py

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+"""导出模块：测试结果图片与 Excel 报告。"""
+from app.export.image_exporter import save_result_images
+from app.export.excel_exporter import export_excel_report, EXCEL_EXPORT_CONFIG
+
+__all__ = ["save_result_images", "export_excel_report", "EXCEL_EXPORT_CONFIG"]

app/export/excel_exporter.py

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+"""测试结果 Excel 导出（screen_module / sdr_movie / hdr_movie 统一实现）。"""
+import datetime
+import os
+import traceback
+
+
+EXCEL_EXPORT_CONFIG = {
+    "screen_module": {
+        "title": "屏模组性能测试数据报告",
+        "type_label": "屏模组",
+        "log_prefix": "屏模组",
+        "curve_type": "gamma",
+        "has_accuracy": False,
+        "column_widths": {"A": 18, "B": 18, "C": 18, "D": 18, "E": 18,
+                          "F": 15, "G": 15},
+    },
+    "sdr_movie": {
+        "title": "SDR Movie 性能测试数据报告",
+        "type_label": "SDR Movie",
+        "log_prefix": "SDR Movie",
+        "curve_type": "gamma",
+        "has_accuracy": True,
+        "column_widths": {c: 18 for c in "ABCDEFG"},
+    },
+    "hdr_movie": {
+        "title": "HDR Movie 性能测试数据报告",
+        "type_label": "HDR Movie",
+        "log_prefix": "HDR Movie",
+        "curve_type": "eotf",
+        "has_accuracy": True,
+        "column_widths": {c: 18 for c in "ABCDEFG"},
+    },
+}
+
+
+# ==================== 样式 ====================
+def _build_styles(Font, Alignment, PatternFill, Border, Side):
+    thin = Side(style="thin")
+    return {
+        "title_font": Font(name="微软雅黑", size=16, bold=True, color="FFFFFF"),
+        "title_fill": PatternFill(start_color="4472C4", end_color="4472C4",
+                                  fill_type="solid"),
+        "title_alignment": Alignment(horizontal="center", vertical="center"),
+        "section_font": Font(name="微软雅黑", size=13, bold=True, color="FFFFFF"),
+        "section_fill": PatternFill(start_color="5B9BD5", end_color="5B9BD5",
+                                    fill_type="solid"),
+        "section_alignment": Alignment(horizontal="center", vertical="center"),
+        "header_font": Font(name="微软雅黑", size=10, bold=True, color="FFFFFF"),
+        "header_fill": PatternFill(start_color="70AD47", end_color="70AD47",
+                                   fill_type="solid"),
+        "header_alignment": Alignment(horizontal="center", vertical="center",
+                                      wrap_text=True),
+        "data_font": Font(name="微软雅黑", size=10),
+        "data_alignment": Alignment(horizontal="center", vertical="center"),
+        "label_font": Font(name="微软雅黑", size=10, bold=True),
+        "thin_border": Border(left=thin, right=thin, top=thin, bottom=thin),
+    }
+
+
+# ==================== 通用写入 ====================
+def _write_title(ws, styles, title_text):
+    ws.merge_cells("A1:G1")
+    ws["A1"] = title_text
+    ws["A1"].font = styles["title_font"]
+    ws["A1"].fill = styles["title_fill"]
+    ws["A1"].alignment = styles["title_alignment"]
+    ws.row_dimensions[1].height = 35
+
+
+def _write_basic_info(ws, styles, row, type_label):
+    ws.merge_cells(f"A{row}:B{row}")
+    ws[f"A{row}"] = "📋 测试基本信息"
+    ws[f"A{row}"].font = styles["section_font"]
+    ws[f"A{row}"].fill = styles["section_fill"]
+    ws[f"A{row}"].alignment = styles["section_alignment"]
+    ws.row_dimensions[row].height = 25
+    row += 1
+
+    info_items = [
+        ("测试时间", datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")),
+        ("测试类型", type_label),
+    ]
+    for label, value in info_items:
+        ws[f"A{row}"] = label
+        ws[f"B{row}"] = value
+        ws[f"A{row}"].font = styles["label_font"]
+        ws[f"B{row}"].font = styles["data_font"]
+        ws[f"A{row}"].border = styles["thin_border"]
+        ws[f"B{row}"].border = styles["thin_border"]
+        row += 1
+    return row
+
+
+def _write_section_header(ws, styles, row, text, span="A{r}:G{r}"):
+    ws.merge_cells(span.format(r=row))
+    ws[f"A{row}"] = text
+    ws[f"A{row}"].font = styles["section_font"]
+    ws[f"A{row}"].fill = styles["section_fill"]
+    ws[f"A{row}"].alignment = styles["section_alignment"]
+    ws.row_dimensions[row].height = 25
+    return row + 1
+
+
+def _write_headers(ws, styles, row, headers):
+    for col_idx, header in enumerate(headers, start=1):
+        cell = ws.cell(row=row, column=col_idx)
+        cell.value = header
+        cell.font = styles["header_font"]
+        cell.fill = styles["header_fill"]
+        cell.alignment = styles["header_alignment"]
+        cell.border = styles["thin_border"]
+    return row + 1
+
+
+def _apply_row_style(ws, row, cols, styles, label_cols=()):
+    for col in cols:
+        cell = ws[f"{col}{row}"]
+        cell.font = (styles["label_font"] if col in label_cols
+                     else styles["data_font"])
+        cell.border = styles["thin_border"]
+
+
+def _apply_data_row(ws, row, cols, styles):
+    for col in cols:
+        cell = ws[f"{col}{row}"]
+        cell.font = styles["data_font"]
+        cell.alignment = styles["data_alignment"]
+        cell.border = styles["thin_border"]
+
+
+# ==================== 分区：色域 ====================
+def _section_gamut(ws, styles, row, results, log):
+    rgb_data = results.get_intermediate_data("gamut", "rgb")
+    gamut_final_result = None
+    if "gamut" in results.test_items:
+        gamut_final_result = results.test_items["gamut"].final_result
+
+    if not (rgb_data and len(rgb_data) >= 3):
+        return row
+
+    row = _write_section_header(ws, styles, row, "🎨 色域测试数据")
+
+    if gamut_final_result:
+        xy_coverage = gamut_final_result.get("coverage", 0)
+        uv_coverage = (
+            gamut_final_result.get("uv_coverage", 0)
+            or gamut_final_result.get("uv_space_coverage", 0)
+            or gamut_final_result.get("coverage_uv", 0)
+            or 0
+        )
+
+        ws[f"A{row}"] = "参考标准"
+        ws[f"B{row}"] = gamut_final_result.get("reference", "DCI-P3")
+        ws[f"A{row}"].font = styles["label_font"]
+        ws[f"B{row}"].font = styles["data_font"]
+        ws[f"A{row}"].border = styles["thin_border"]
+        ws[f"B{row}"].border = styles["thin_border"]
+        row += 1
+
+        ws[f"A{row}"] = "XY 色域覆盖率"
+        ws[f"B{row}"] = f"{xy_coverage:.2f}%"
+        ws[f"C{row}"] = "UV 色域覆盖率"
+        ws[f"D{row}"] = f"{uv_coverage:.2f}%"
+        _apply_row_style(ws, row, ["A", "B", "C", "D"], styles,
+                         label_cols=("A", "C"))
+        row += 1
+
+    row = _write_headers(
+        ws, styles, row,
+        ["点位", "x 坐标", "y 坐标", "亮度 (cd/m²)", "", "", ""],
+    )
+
+    rgb_labels = ["Red", "Green", "Blue"]
+    for i, result in enumerate(rgb_data[:3]):
+        x, y, lv = result[0], result[1], result[2]
+        ws[f"A{row}"] = rgb_labels[i]
+        ws[f"B{row}"] = x
+        ws[f"C{row}"] = y
+        ws[f"D{row}"] = lv
+        ws[f"B{row}"].number_format = "0.0000"
+        ws[f"C{row}"].number_format = "0.0000"
+        ws[f"D{row}"].number_format = "0.00"
+        _apply_data_row(ws, row, ["A", "B", "C", "D"], styles)
+        row += 1
+
+    log("  ✓ 添加色域数据")
+    return row + 1
+
+
+# ==================== 分区：Gamma / EOTF ====================
+def _section_curve(ws, styles, row, results, log, curve_type):
+    if curve_type == "gamma":
+        section_title = "📊 Gamma 曲线数据"
+        label_prefix = "Gamma"
+        data_key = "gamma"
+        value_header = "Gamma 值"
+    else:
+        section_title = "📊 EOTF 曲线数据"
+        label_prefix = "EOTF"
+        data_key = "eotf"
+        value_header = "EOTF 值"
+
+    gray_data = results.get_intermediate_data("shared", "gray")
+    if not gray_data:
+        gray_data = results.get_intermediate_data(curve_type, "gray")
+
+    curve_final_result = None
+    if curve_type in results.test_items:
+        curve_final_result = results.test_items[curve_type].final_result
+
+    if not (gray_data and len(gray_data) > 0 and curve_final_result):
+        return row
+
+    value_list = curve_final_result.get(data_key, [])
+    L_bar_list = curve_final_result.get("L_bar", [])
+
+    row = _write_section_header(ws, styles, row, section_title)
+
+    valid_values = [
+        item[3]
+        for item in value_list
+        if isinstance(item, (list, tuple))
+        and len(item) >= 4
+        and 0.5 < item[3] < 5.0
+    ]
+    if valid_values:
+        avg_v = sum(valid_values) / len(valid_values)
+        ws[f"A{row}"] = f"平均 {label_prefix}"
+        ws[f"B{row}"] = f"{avg_v:.3f}"
+        ws[f"C{row}"] = f"最大 {label_prefix}"
+        ws[f"D{row}"] = f"{max(valid_values):.3f}"
+        ws[f"E{row}"] = f"最小 {label_prefix}"
+        ws[f"F{row}"] = f"{min(valid_values):.3f}"
+        _apply_row_style(ws, row, ["A", "B", "C", "D", "E", "F"], styles,
+                         label_cols=("A", "C", "E"))
+        row += 1
+
+    row = _write_headers(
+        ws, styles, row,
+        ["灰阶 (%)", "x 坐标", "y 坐标", "实测亮度\n(cd/m²)",
+         "归一化亮度\n(L_bar)", value_header, ""],
+    )
+
+    total_points = len(gray_data)
+    for i in range(total_points - 1, -1, -1):
+        gray_level = (100 - int(i * 100 / (total_points - 1))
+                      if total_points > 1 else 0)
+        x, y, lv = gray_data[i][0], gray_data[i][1], gray_data[i][2]
+        L_bar_val = L_bar_list[i] if i < len(L_bar_list) else 0
+
+        val = None
+        if (i < len(value_list)
+                and isinstance(value_list[i], (list, tuple))
+                and len(value_list[i]) >= 4):
+            val = value_list[i][3]
+
+        ws[f"A{row}"] = gray_level
+        ws[f"B{row}"] = x
+        ws[f"C{row}"] = y
+        ws[f"D{row}"] = lv
+        ws[f"E{row}"] = L_bar_val
+
+        if val is not None and 0.5 < val < 5.0:
+            ws[f"F{row}"] = val
+            ws[f"F{row}"].number_format = "0.000"
+        else:
+            ws[f"F{row}"] = "N/A"
+
+        ws[f"A{row}"].number_format = "0"
+        ws[f"B{row}"].number_format = "0.0000"
+        ws[f"C{row}"].number_format = "0.0000"
+        ws[f"D{row}"].number_format = "0.00"
+        ws[f"E{row}"].number_format = "0.0000"
+        _apply_data_row(ws, row, ["A", "B", "C", "D", "E", "F"], styles)
+        row += 1
+
+    log(f"  ✓ 添加 {label_prefix} 数据")
+    return row + 1
+
+
+# ==================== 分区：色度一致性 ====================
+def _section_cct(ws, styles, row, results, log):
+    gray_data = results.get_intermediate_data("shared", "gray")
+    if not gray_data:
+        gray_data = results.get_intermediate_data("cct", "gray")
+    if not (gray_data and len(gray_data) > 1):
+        return row
+
+    gray_data_no_black = gray_data[:-1]
+
+    row = _write_section_header(ws, styles, row, "🌈 色度一致性数据")
+
+    x_coords = [d[0] for d in gray_data_no_black]
+    y_coords = [d[1] for d in gray_data_no_black]
+    ws[f"A{row}"] = "x 坐标范围"
+    ws[f"B{row}"] = f"{min(x_coords):.4f} ~ {max(x_coords):.4f}"
+    ws[f"C{row}"] = "y 坐标范围"
+    ws[f"D{row}"] = f"{min(y_coords):.4f} ~ {max(y_coords):.4f}"
+    _apply_row_style(ws, row, ["A", "B", "C", "D"], styles,
+                     label_cols=("A", "C"))
+    row += 1
+
+    row = _write_headers(
+        ws, styles, row,
+        ["灰阶 (%)", "x 坐标", "y 坐标", "亮度 (cd/m²)", "", "", ""],
+    )
+
+    total_points = len(gray_data)
+    for i in range(len(gray_data_no_black) - 1, -1, -1):
+        x, y, lv = (gray_data_no_black[i][0],
+                    gray_data_no_black[i][1],
+                    gray_data_no_black[i][2])
+        gray_level = (100 - int(i * 100 / (total_points - 1))
+                      if total_points > 1 else 0)
+        ws[f"A{row}"] = gray_level
+        ws[f"B{row}"] = x
+        ws[f"C{row}"] = y
+        ws[f"D{row}"] = lv
+        ws[f"A{row}"].number_format = "0"
+        ws[f"B{row}"].number_format = "0.0000"
+        ws[f"C{row}"].number_format = "0.0000"
+        ws[f"D{row}"].number_format = "0.00"
+        _apply_data_row(ws, row, ["A", "B", "C", "D"], styles)
+        row += 1
+
+    log("  ✓ 添加色度一致性数据")
+    return row + 1
+
+
+# ==================== 分区：对比度 ====================
+def _section_contrast(ws, styles, row, results, log):
+    contrast_final_result = None
+    if "contrast" in results.test_items:
+        contrast_final_result = results.test_items["contrast"].final_result
+    if not contrast_final_result:
+        return row
+
+    row = _write_section_header(ws, styles, row, "⚫⚪ 对比度测试数据")
+
+    max_lv = contrast_final_result.get("max_luminance", 0)
+    min_lv = contrast_final_result.get("min_luminance", 0)
+    contrast_ratio = contrast_final_result.get("contrast_ratio", 0)
+    info_items = [
+        ("最大亮度（白场）", f"{max_lv:.2f} cd/m²"),
+        ("最小亮度（黑场）", f"{min_lv:.4f} cd/m²"),
+        ("对比度", f"{contrast_ratio:.0f}:1"),
+    ]
+    for label, value in info_items:
+        ws[f"A{row}"] = label
+        ws[f"B{row}"] = value
+        ws[f"A{row}"].font = styles["label_font"]
+        ws[f"B{row}"].font = styles["data_font"]
+        ws[f"A{row}"].border = styles["thin_border"]
+        ws[f"B{row}"].border = styles["thin_border"]
+        row += 1
+
+    log("  ✓ 添加对比度数据")
+    return row + 1
+
+
+# ==================== 分区：色准 ====================
+def _section_accuracy(ws, styles, row, results, log):
+    accuracy_final_result = None
+    if "accuracy" in results.test_items:
+        accuracy_final_result = results.test_items["accuracy"].final_result
+    if not accuracy_final_result:
+        return row
+
+    row = _write_section_header(ws, styles, row, "🎯 色准测试数据")
+
+    avg_delta_e = accuracy_final_result.get("avg_delta_e", 0)
+    max_delta_e = accuracy_final_result.get("max_delta_e", 0)
+    min_delta_e = accuracy_final_result.get("min_delta_e", 0)
+    excellent_count = accuracy_final_result.get("excellent_count", 0)
+    good_count = accuracy_final_result.get("good_count", 0)
+    poor_count = accuracy_final_result.get("poor_count", 0)
+
+    ws[f"A{row}"] = "平均 ΔE"
+    ws[f"B{row}"] = f"{avg_delta_e:.2f}"
+    ws[f"C{row}"] = "最大 ΔE"
+    ws[f"D{row}"] = f"{max_delta_e:.2f}"
+    ws[f"E{row}"] = "最小 ΔE"
+    ws[f"F{row}"] = f"{min_delta_e:.2f}"
+    _apply_row_style(ws, row, ["A", "B", "C", "D", "E", "F"], styles,
+                     label_cols=("A", "C", "E"))
+    row += 1
+
+    ws[f"A{row}"] = "优秀 (ΔE<3)"
+    ws[f"B{row}"] = f"{excellent_count} 个"
+    ws[f"C{row}"] = "良好 (3≤ΔE<5)"
+    ws[f"D{row}"] = f"{good_count} 个"
+    ws[f"E{row}"] = "偏差 (ΔE≥5)"
+    ws[f"F{row}"] = f"{poor_count} 个"
+    _apply_row_style(ws, row, ["A", "B", "C", "D", "E", "F"], styles,
+                     label_cols=("A", "C", "E"))
+    row += 1
+
+    color_patches = accuracy_final_result.get("color_patches", [])
+    delta_e_values = accuracy_final_result.get("delta_e_values", [])
+    color_measurements = accuracy_final_result.get("color_measurements", [])
+
+    if color_patches and delta_e_values:
+        row = _write_headers(
+            ws, styles, row,
+            ["序号", "颜色名称", "x 坐标", "y 坐标",
+             "亮度 (cd/m²)", "ΔE 2000", "等级"],
+        )
+        for idx, (color_name, delta_e) in enumerate(
+                zip(color_patches, delta_e_values), start=1):
+            if delta_e < 3:
+                grade = "优秀"
+            elif delta_e < 5:
+                grade = "良好"
+            else:
+                grade = "偏差"
+
+            x_val, y_val, lv_val = "N/A", "N/A", "N/A"
+            if color_measurements and idx - 1 < len(color_measurements):
+                m = color_measurements[idx - 1]
+                if len(m) >= 3:
+                    x_val, y_val, lv_val = m[0], m[1], m[2]
+
+            ws[f"A{row}"] = idx
+            ws[f"B{row}"] = color_name
+            ws[f"C{row}"] = x_val
+            ws[f"D{row}"] = y_val
+            ws[f"E{row}"] = lv_val
+            ws[f"F{row}"] = delta_e
+            ws[f"G{row}"] = grade
+
+            ws[f"A{row}"].number_format = "0"
+            if isinstance(x_val, (int, float)):
+                ws[f"C{row}"].number_format = "0.0000"
+            if isinstance(y_val, (int, float)):
+                ws[f"D{row}"].number_format = "0.0000"
+            if isinstance(lv_val, (int, float)):
+                ws[f"E{row}"].number_format = "0.00"
+            ws[f"F{row}"].number_format = "0.00"
+
+            _apply_data_row(ws, row, ["A", "B", "C", "D", "E", "F", "G"], styles)
+            row += 1
+
+    log("  ✓ 添加色准数据（含 xy 坐标和亮度）")
+    return row + 1
+
+
+# ==================== 主入口 ====================
+def export_excel_report(result_dir, current_test_type, selected_items,
+                        results, log):
+    """根据测试类型生成统一格式的 Excel 报告。
+
+    仅 current_test_type ∈ EXCEL_EXPORT_CONFIG 时应调用本函数；
+    内部吞掉 ImportError（openpyxl 未装）与其他 Exception 并通过 log 记录。
+    """
+    if current_test_type not in EXCEL_EXPORT_CONFIG:
+        return
+    cfg = EXCEL_EXPORT_CONFIG[current_test_type]
+    try:
+        import openpyxl
+        from openpyxl.styles import (
+            Font, Alignment, PatternFill, Border, Side,
+        )
+
+        log("=" * 60)
+        log(f"开始生成{cfg['log_prefix']} Excel 数据报告...")
+
+        wb = openpyxl.Workbook()
+        ws = wb.active
+        ws.title = "测试数据"
+
+        styles = _build_styles(Font, Alignment, PatternFill, Border, Side)
+
+        _write_title(ws, styles, cfg["title"])
+        row = _write_basic_info(ws, styles, 3, cfg["type_label"])
+        row += 1  # 空行
+
+        if "gamut" in selected_items:
+            row = _section_gamut(ws, styles, row, results, log)
+        if cfg["curve_type"] == "gamma" and "gamma" in selected_items:
+            row = _section_curve(ws, styles, row, results, log, "gamma")
+        if cfg["curve_type"] == "eotf" and "eotf" in selected_items:
+            row = _section_curve(ws, styles, row, results, log, "eotf")
+        if "cct" in selected_items:
+            row = _section_cct(ws, styles, row, results, log)
+        if "contrast" in selected_items:
+            row = _section_contrast(ws, styles, row, results, log)
+        if cfg["has_accuracy"] and "accuracy" in selected_items:
+            row = _section_accuracy(ws, styles, row, results, log)
+
+        for col, width in cfg["column_widths"].items():
+            ws.column_dimensions[col].width = width
+
+        excel_path = os.path.join(result_dir, "测试数据.xlsx")
+        wb.save(excel_path)
+
+        log("✓ 已保存: 测试数据.xlsx")
+        log("=" * 60)
+
+    except ImportError:
+        log("⚠️ 未安装 openpyxl 库，跳过 Excel 导出")
+        log("   安装方法: pip install openpyxl")
+    except Exception as e:
+        log(f"⚠️ Excel 导出失败: {str(e)}")
+        log(traceback.format_exc())

app/export/image_exporter.py

@@ -0,0 +1,38 @@
+"""测试结果图表 PNG 导出。"""
+import os
+
+
+# (item_key, fig_attr, filename, allowed_test_types_or_None, default_bbox_inches_auto)
+IMAGE_SPECS = [
+    ("gamut", "gamut_fig", "色域测试结果.png", None, True),
+    ("gamma", "gamma_fig", "Gamma曲线测试结果.png",
+     {"screen_module", "sdr_movie"}, True),
+    ("eotf", "eotf_fig", "EOTF曲线测试结果.png", {"hdr_movie"}, True),
+    ("cct", "cct_fig", "色度一致性测试结果.png", None, True),
+    ("contrast", "contrast_fig", "对比度测试结果.png", None, False),
+    ("accuracy", "accuracy_fig", "色准测试结果.png",
+     {"sdr_movie", "hdr_movie"}, True),
+]
+
+
+def save_result_images(result_dir, current_test_type, selected_items,
+                       figure_provider, log):
+    """根据测试类型和已选项将各测试图表保存为 PNG。
+
+    figure_provider: callable(attr_name) -> matplotlib Figure 或 None
+    log: callable(msg)
+    """
+    for item_key, fig_attr, filename, allowed_types, default_bbox in IMAGE_SPECS:
+        if item_key not in selected_items:
+            continue
+        if allowed_types is not None and current_test_type not in allowed_types:
+            continue
+        fig = figure_provider(fig_attr)
+        if fig is None:
+            continue
+        path = os.path.join(result_dir, filename)
+        if default_bbox:
+            fig.savefig(path, dpi=300)
+        else:
+            fig.savefig(path, dpi=300, bbox_inches="tight")
+        log(f"✓ 已保存: {filename}")

pqAutomationApp.py

@@ -29,6 +29,11 @@ from colormath.color_objects import xyYColor, LabColor
 from colormath.color_conversions import convert_color
 from colormath.color_diff import delta_e_cie2000
 from app.views.pq_debug_panel import PQDebugPanel
+from app.export import (
+    save_result_images as _save_result_images_impl,
+    export_excel_report as _export_excel_report_impl,
+    EXCEL_EXPORT_CONFIG as _EXCEL_EXPORT_CONFIG,
+)
 
 # Step 0/1 重构：资源工具和纯算法已迁移到 app/ 包，这里重新导入以保持
 # 对原函数名/方法名的向后兼容（老代码内部仍用 self.calculate_* 调用）。
@@ -2864,37 +2869,9 @@ class PQAutomationApp:
         # ========== 延迟1秒后执行清理 ==========
         self.root.after(1000, cleanup_and_finish)
 
-    # ==================== Excel 导出配置 ====================
+    # ==================== 保存测试结果 ====================
-    _EXCEL_EXPORT_CONFIG = {
-        "screen_module": {
-            "title": "屏模组性能测试数据报告",
-            "type_label": "屏模组",
-            "log_prefix": "屏模组",
-            "curve_type": "gamma",
-            "has_accuracy": False,
-            "column_widths": {"A": 18, "B": 18, "C": 18, "D": 18, "E": 18, "F": 15, "G": 15},
-        },
-        "sdr_movie": {
-            "title": "SDR Movie 性能测试数据报告",
-            "type_label": "SDR Movie",
-            "log_prefix": "SDR Movie",
-            "curve_type": "gamma",
-            "has_accuracy": True,
-            "column_widths": {c: 18 for c in "ABCDEFG"},
-        },
-        "hdr_movie": {
-            "title": "HDR Movie 性能测试数据报告",
-            "type_label": "HDR Movie",
-            "log_prefix": "HDR Movie",
-            "curve_type": "eotf",
-            "has_accuracy": True,
-            "column_widths": {c: 18 for c in "ABCDEFG"},
-        },
-    }
-
-    # ==================== 主入口 ====================
     def save_results(self):
-        """保存测试结果（图片 + Excel）"""
+        """保存测试结果（图片 + Excel）。实现委派给 app.export。"""
         save_dir = filedialog.askdirectory(title="选择保存测试结果的目录")
         if not save_dir:
             return
@@ -2907,25 +2884,30 @@ class PQAutomationApp:
 
             current_test_type = self.test_type_var.get()
             selected_items = self.get_selected_test_items()
+            log = self.log_gui.log
 
-            self.log_gui.log(f"保存测试类型: {current_test_type}")
+            log(f"保存测试类型: {current_test_type}")
-            self.log_gui.log(f"已选测试项: {selected_items}")
+            log(f"已选测试项: {selected_items}")
 
             # 1) 图片
-            self._save_result_images(result_dir, current_test_type, selected_items)
+            _save_result_images_impl(
+                result_dir, current_test_type, selected_items,
+                lambda attr: getattr(self, attr, None),
+                log,
+            )
 
             # 2) Excel
-            if (
+            if (current_test_type in _EXCEL_EXPORT_CONFIG
-                current_test_type in self._EXCEL_EXPORT_CONFIG
+                    and hasattr(self, "results") and self.results):
-                and hasattr(self, "results")
+                _export_excel_report_impl(
-                and self.results
+                    result_dir, current_test_type, selected_items,
-            ):
+                    self.results, log,
-                self._export_excel_report(result_dir, current_test_type, selected_items)
+                )
 
             # 3) 成功提示
-            self.log_gui.log("=" * 50)
+            log("=" * 50)
-            self.log_gui.log(f"✅ 测试结果已保存到目录: {result_dir}")
+            log(f"✅ 测试结果已保存到目录: {result_dir}")
-            self.log_gui.log("=" * 50)
+            log("=" * 50)
             messagebox.showinfo("成功", f"测试结果已保存到目录:\n{result_dir}")
 
         except Exception as e:
@@ -2935,515 +2917,6 @@ class PQAutomationApp:
             self.log_gui.log(traceback.format_exc())
             messagebox.showerror("错误", f"保存测试结果失败: {str(e)}")
 
-    # ==================== 图片保存 ====================
-    def _save_result_images(self, result_dir, current_test_type, selected_items):
-        """根据测试类型和已选项保存各测试图表 PNG。"""
-        image_specs = [
-            ("gamut", "gamut_fig", "色域测试结果.png", None, True),
-            ("gamma", "gamma_fig", "Gamma曲线测试结果.png",
-             {"screen_module", "sdr_movie"}, True),
-            ("eotf", "eotf_fig", "EOTF曲线测试结果.png", {"hdr_movie"}, True),
-            ("cct", "cct_fig", "色度一致性测试结果.png", None, True),
-            ("contrast", "contrast_fig", "对比度测试结果.png", None, False),
-            ("accuracy", "accuracy_fig", "色准测试结果.png",
-             {"sdr_movie", "hdr_movie"}, True),
-        ]
-        for item_key, fig_attr, filename, allowed_types, default_bbox in image_specs:
-            if item_key not in selected_items:
-                continue
-            if allowed_types is not None and current_test_type not in allowed_types:
-                continue
-            fig = getattr(self, fig_attr, None)
-            if fig is None:
-                continue
-            path = os.path.join(result_dir, filename)
-            if default_bbox:
-                fig.savefig(path, dpi=300)
-            else:
-                fig.savefig(path, dpi=300, bbox_inches="tight")
-            self.log_gui.log(f"✓ 已保存: {filename}")
-
-    # ==================== Excel 导出总入口 ====================
-    def _export_excel_report(self, result_dir, current_test_type, selected_items):
-        """根据测试类型生成统一格式的 Excel 报告。"""
-        cfg = self._EXCEL_EXPORT_CONFIG[current_test_type]
-        try:
-            import openpyxl
-            from openpyxl.styles import (
-                Font,
-                Alignment,
-                PatternFill,
-                Border,
-                Side,
-            )
-
-            self.log_gui.log("=" * 60)
-            self.log_gui.log(f"开始生成{cfg['log_prefix']} Excel 数据报告...")
-
-            wb = openpyxl.Workbook()
-            ws = wb.active
-            ws.title = "测试数据"
-
-            styles = self._build_excel_styles(Font, Alignment, PatternFill, Border, Side)
-
-            self._excel_write_title(ws, styles, cfg["title"])
-            row = self._excel_write_basic_info(ws, styles, 3, cfg["type_label"])
-            row += 1  # 空行
-
-            if "gamut" in selected_items:
-                row = self._excel_section_gamut(ws, styles, row)
-            if cfg["curve_type"] == "gamma" and "gamma" in selected_items:
-                row = self._excel_section_curve(ws, styles, row, "gamma")
-            if cfg["curve_type"] == "eotf" and "eotf" in selected_items:
-                row = self._excel_section_curve(ws, styles, row, "eotf")
-            if "cct" in selected_items:
-                row = self._excel_section_cct(ws, styles, row)
-            if "contrast" in selected_items:
-                row = self._excel_section_contrast(ws, styles, row)
-            if cfg["has_accuracy"] and "accuracy" in selected_items:
-                row = self._excel_section_accuracy(ws, styles, row)
-
-            for col, width in cfg["column_widths"].items():
-                ws.column_dimensions[col].width = width
-
-            excel_path = os.path.join(result_dir, "测试数据.xlsx")
-            wb.save(excel_path)
-
-            self.log_gui.log("✓ 已保存: 测试数据.xlsx")
-            self.log_gui.log("=" * 60)
-
-        except ImportError:
-            self.log_gui.log("⚠️ 未安装 openpyxl 库，跳过 Excel 导出")
-            self.log_gui.log("   安装方法: pip install openpyxl")
-        except Exception as e:
-            self.log_gui.log(f"⚠️ Excel 导出失败: {str(e)}")
-            import traceback
-
-            self.log_gui.log(traceback.format_exc())
-
-    # ==================== 样式与通用写入 ====================
-    @staticmethod
-    def _build_excel_styles(Font, Alignment, PatternFill, Border, Side):
-        thin = Side(style="thin")
-        return {
-            "title_font": Font(name="微软雅黑", size=16, bold=True, color="FFFFFF"),
-            "title_fill": PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid"),
-            "title_alignment": Alignment(horizontal="center", vertical="center"),
-            "section_font": Font(name="微软雅黑", size=13, bold=True, color="FFFFFF"),
-            "section_fill": PatternFill(start_color="5B9BD5", end_color="5B9BD5", fill_type="solid"),
-            "section_alignment": Alignment(horizontal="center", vertical="center"),
-            "header_font": Font(name="微软雅黑", size=10, bold=True, color="FFFFFF"),
-            "header_fill": PatternFill(start_color="70AD47", end_color="70AD47", fill_type="solid"),
-            "header_alignment": Alignment(horizontal="center", vertical="center", wrap_text=True),
-            "data_font": Font(name="微软雅黑", size=10),
-            "data_alignment": Alignment(horizontal="center", vertical="center"),
-            "label_font": Font(name="微软雅黑", size=10, bold=True),
-            "thin_border": Border(left=thin, right=thin, top=thin, bottom=thin),
-        }
-
-    @staticmethod
-    def _excel_write_title(ws, styles, title_text):
-        ws.merge_cells("A1:G1")
-        ws["A1"] = title_text
-        ws["A1"].font = styles["title_font"]
-        ws["A1"].fill = styles["title_fill"]
-        ws["A1"].alignment = styles["title_alignment"]
-        ws.row_dimensions[1].height = 35
-
-    @staticmethod
-    def _excel_write_basic_info(ws, styles, row, type_label):
-        ws.merge_cells(f"A{row}:B{row}")
-        ws[f"A{row}"] = "📋 测试基本信息"
-        ws[f"A{row}"].font = styles["section_font"]
-        ws[f"A{row}"].fill = styles["section_fill"]
-        ws[f"A{row}"].alignment = styles["section_alignment"]
-        ws.row_dimensions[row].height = 25
-        row += 1
-
-        info_items = [
-            ("测试时间", datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")),
-            ("测试类型", type_label),
-        ]
-        for label, value in info_items:
-            ws[f"A{row}"] = label
-            ws[f"B{row}"] = value
-            ws[f"A{row}"].font = styles["label_font"]
-            ws[f"B{row}"].font = styles["data_font"]
-            ws[f"A{row}"].border = styles["thin_border"]
-            ws[f"B{row}"].border = styles["thin_border"]
-            row += 1
-        return row
-
-    @staticmethod
-    def _excel_write_section_header(ws, styles, row, text, span="A{r}:G{r}"):
-        ws.merge_cells(span.format(r=row))
-        ws[f"A{row}"] = text
-        ws[f"A{row}"].font = styles["section_font"]
-        ws[f"A{row}"].fill = styles["section_fill"]
-        ws[f"A{row}"].alignment = styles["section_alignment"]
-        ws.row_dimensions[row].height = 25
-        return row + 1
-
-    @staticmethod
-    def _excel_write_headers(ws, styles, row, headers):
-        for col_idx, header in enumerate(headers, start=1):
-            cell = ws.cell(row=row, column=col_idx)
-            cell.value = header
-            cell.font = styles["header_font"]
-            cell.fill = styles["header_fill"]
-            cell.alignment = styles["header_alignment"]
-            cell.border = styles["thin_border"]
-        return row + 1
-
-    @staticmethod
-    def _excel_apply_row_style(ws, row, cols, styles, label_cols=()):
-        """对一整行的指定列应用数据样式；label_cols 中的列使用粗体标签字体。"""
-        for col in cols:
-            cell = ws[f"{col}{row}"]
-            cell.font = styles["label_font"] if col in label_cols else styles["data_font"]
-            cell.border = styles["thin_border"]
-
-    @staticmethod
-    def _excel_apply_data_row(ws, row, cols, styles):
-        for col in cols:
-            cell = ws[f"{col}{row}"]
-            cell.font = styles["data_font"]
-            cell.alignment = styles["data_alignment"]
-            cell.border = styles["thin_border"]
-
-    # ==================== 分区：色域 ====================
-    def _excel_section_gamut(self, ws, styles, row):
-        rgb_data = self.results.get_intermediate_data("gamut", "rgb")
-        gamut_final_result = None
-        if "gamut" in self.results.test_items:
-            gamut_final_result = self.results.test_items["gamut"].final_result
-
-        if not (rgb_data and len(rgb_data) >= 3):
-            return row
-
-        row = self._excel_write_section_header(ws, styles, row, "🎨 色域测试数据")
-
-        if gamut_final_result:
-            xy_coverage = gamut_final_result.get("coverage", 0)
-            uv_coverage = (
-                gamut_final_result.get("uv_coverage", 0)
-                or gamut_final_result.get("uv_space_coverage", 0)
-                or gamut_final_result.get("coverage_uv", 0)
-                or 0
-            )
-
-            ws[f"A{row}"] = "参考标准"
-            ws[f"B{row}"] = gamut_final_result.get("reference", "DCI-P3")
-            ws[f"A{row}"].font = styles["label_font"]
-            ws[f"B{row}"].font = styles["data_font"]
-            ws[f"A{row}"].border = styles["thin_border"]
-            ws[f"B{row}"].border = styles["thin_border"]
-            row += 1
-
-            ws[f"A{row}"] = "XY 色域覆盖率"
-            ws[f"B{row}"] = f"{xy_coverage:.2f}%"
-            ws[f"C{row}"] = "UV 色域覆盖率"
-            ws[f"D{row}"] = f"{uv_coverage:.2f}%"
-            self._excel_apply_row_style(
-                ws, row, ["A", "B", "C", "D"], styles, label_cols=("A", "C")
-            )
-            row += 1
-
-        row = self._excel_write_headers(
-            ws, styles, row,
-            ["点位", "x 坐标", "y 坐标", "亮度 (cd/m²)", "", "", ""],
-        )
-
-        rgb_labels = ["Red", "Green", "Blue"]
-        for i, result in enumerate(rgb_data[:3]):
-            x, y, lv = result[0], result[1], result[2]
-            ws[f"A{row}"] = rgb_labels[i]
-            ws[f"B{row}"] = x
-            ws[f"C{row}"] = y
-            ws[f"D{row}"] = lv
-            ws[f"B{row}"].number_format = "0.0000"
-            ws[f"C{row}"].number_format = "0.0000"
-            ws[f"D{row}"].number_format = "0.00"
-            self._excel_apply_data_row(ws, row, ["A", "B", "C", "D"], styles)
-            row += 1
-
-        self.log_gui.log("  ✓ 添加色域数据")
-        return row + 1
-
-    # ==================== 分区：Gamma / EOTF（曲线类） ====================
-    def _excel_section_curve(self, ws, styles, row, curve_type):
-        """curve_type: 'gamma' 或 'eotf'。两者数据结构一致，仅 key/显示名不同。"""
-        if curve_type == "gamma":
-            section_title = "📊 Gamma 曲线数据"
-            label_prefix = "Gamma"
-            data_key = "gamma"
-            value_header = "Gamma 值"
-        else:
-            section_title = "📊 EOTF 曲线数据"
-            label_prefix = "EOTF"
-            data_key = "eotf"
-            value_header = "EOTF 值"
-
-        gray_data = self.results.get_intermediate_data("shared", "gray")
-        if not gray_data:
-            gray_data = self.results.get_intermediate_data(curve_type, "gray")
-
-        curve_final_result = None
-        if curve_type in self.results.test_items:
-            curve_final_result = self.results.test_items[curve_type].final_result
-
-        if not (gray_data and len(gray_data) > 0 and curve_final_result):
-            return row
-
-        value_list = curve_final_result.get(data_key, [])
-        L_bar_list = curve_final_result.get("L_bar", [])
-
-        row = self._excel_write_section_header(ws, styles, row, section_title)
-
-        # 统计
-        valid_values = [
-            item[3]
-            for item in value_list
-            if isinstance(item, (list, tuple))
-            and len(item) >= 4
-            and 0.5 < item[3] < 5.0
-        ]
-        if valid_values:
-            avg_v = sum(valid_values) / len(valid_values)
-            ws[f"A{row}"] = f"平均 {label_prefix}"
-            ws[f"B{row}"] = f"{avg_v:.3f}"
-            ws[f"C{row}"] = f"最大 {label_prefix}"
-            ws[f"D{row}"] = f"{max(valid_values):.3f}"
-            ws[f"E{row}"] = f"最小 {label_prefix}"
-            ws[f"F{row}"] = f"{min(valid_values):.3f}"
-            self._excel_apply_row_style(
-                ws, row, ["A", "B", "C", "D", "E", "F"],
-                styles, label_cols=("A", "C", "E"),
-            )
-            row += 1
-
-        # 数据表
-        row = self._excel_write_headers(
-            ws, styles, row,
-            ["灰阶 (%)", "x 坐标", "y 坐标", "实测亮度\n(cd/m²)",
-             "归一化亮度\n(L_bar)", value_header, ""],
-        )
-
-        total_points = len(gray_data)
-        for i in range(total_points - 1, -1, -1):
-            gray_level = (
-                100 - int(i * 100 / (total_points - 1)) if total_points > 1 else 0
-            )
-            x, y, lv = gray_data[i][0], gray_data[i][1], gray_data[i][2]
-            L_bar_val = L_bar_list[i] if i < len(L_bar_list) else 0
-
-            val = None
-            if (
-                i < len(value_list)
-                and isinstance(value_list[i], (list, tuple))
-                and len(value_list[i]) >= 4
-            ):
-                val = value_list[i][3]
-
-            ws[f"A{row}"] = gray_level
-            ws[f"B{row}"] = x
-            ws[f"C{row}"] = y
-            ws[f"D{row}"] = lv
-            ws[f"E{row}"] = L_bar_val
-
-            if val is not None and 0.5 < val < 5.0:
-                ws[f"F{row}"] = val
-                ws[f"F{row}"].number_format = "0.000"
-            else:
-                ws[f"F{row}"] = "N/A"
-
-            ws[f"A{row}"].number_format = "0"
-            ws[f"B{row}"].number_format = "0.0000"
-            ws[f"C{row}"].number_format = "0.0000"
-            ws[f"D{row}"].number_format = "0.00"
-            ws[f"E{row}"].number_format = "0.0000"
-            self._excel_apply_data_row(
-                ws, row, ["A", "B", "C", "D", "E", "F"], styles
-            )
-            row += 1
-
-        self.log_gui.log(f"  ✓ 添加 {label_prefix} 数据")
-        return row + 1
-
-    # ==================== 分区：色度一致性 ====================
-    def _excel_section_cct(self, ws, styles, row):
-        gray_data = self.results.get_intermediate_data("shared", "gray")
-        if not gray_data:
-            gray_data = self.results.get_intermediate_data("cct", "gray")
-        if not (gray_data and len(gray_data) > 1):
-            return row
-
-        gray_data_no_black = gray_data[:-1]
-
-        row = self._excel_write_section_header(ws, styles, row, "🌈 色度一致性数据")
-
-        x_coords = [d[0] for d in gray_data_no_black]
-        y_coords = [d[1] for d in gray_data_no_black]
-        ws[f"A{row}"] = "x 坐标范围"
-        ws[f"B{row}"] = f"{min(x_coords):.4f} ~ {max(x_coords):.4f}"
-        ws[f"C{row}"] = "y 坐标范围"
-        ws[f"D{row}"] = f"{min(y_coords):.4f} ~ {max(y_coords):.4f}"
-        self._excel_apply_row_style(
-            ws, row, ["A", "B", "C", "D"], styles, label_cols=("A", "C")
-        )
-        row += 1
-
-        row = self._excel_write_headers(
-            ws, styles, row,
-            ["灰阶 (%)", "x 坐标", "y 坐标", "亮度 (cd/m²)", "", "", ""],
-        )
-
-        total_points = len(gray_data)
-        for i in range(len(gray_data_no_black) - 1, -1, -1):
-            x, y, lv = (
-                gray_data_no_black[i][0],
-                gray_data_no_black[i][1],
-                gray_data_no_black[i][2],
-            )
-            gray_level = (
-                100 - int(i * 100 / (total_points - 1)) if total_points > 1 else 0
-            )
-            ws[f"A{row}"] = gray_level
-            ws[f"B{row}"] = x
-            ws[f"C{row}"] = y
-            ws[f"D{row}"] = lv
-            ws[f"A{row}"].number_format = "0"
-            ws[f"B{row}"].number_format = "0.0000"
-            ws[f"C{row}"].number_format = "0.0000"
-            ws[f"D{row}"].number_format = "0.00"
-            self._excel_apply_data_row(ws, row, ["A", "B", "C", "D"], styles)
-            row += 1
-
-        self.log_gui.log("  ✓ 添加色度一致性数据")
-        return row + 1
-
-    # ==================== 分区：对比度 ====================
-    def _excel_section_contrast(self, ws, styles, row):
-        contrast_final_result = None
-        if "contrast" in self.results.test_items:
-            contrast_final_result = self.results.test_items["contrast"].final_result
-        if not contrast_final_result:
-            return row
-
-        row = self._excel_write_section_header(ws, styles, row, "⚫⚪ 对比度测试数据")
-
-        max_lv = contrast_final_result.get("max_luminance", 0)
-        min_lv = contrast_final_result.get("min_luminance", 0)
-        contrast_ratio = contrast_final_result.get("contrast_ratio", 0)
-        info_items = [
-            ("最大亮度（白场）", f"{max_lv:.2f} cd/m²"),
-            ("最小亮度（黑场）", f"{min_lv:.4f} cd/m²"),
-            ("对比度", f"{contrast_ratio:.0f}:1"),
-        ]
-        for label, value in info_items:
-            ws[f"A{row}"] = label
-            ws[f"B{row}"] = value
-            ws[f"A{row}"].font = styles["label_font"]
-            ws[f"B{row}"].font = styles["data_font"]
-            ws[f"A{row}"].border = styles["thin_border"]
-            ws[f"B{row}"].border = styles["thin_border"]
-            row += 1
-
-        self.log_gui.log("  ✓ 添加对比度数据")
-        return row + 1
-
-    # ==================== 分区：色准（仅 SDR/HDR） ====================
-    def _excel_section_accuracy(self, ws, styles, row):
-        accuracy_final_result = None
-        if "accuracy" in self.results.test_items:
-            accuracy_final_result = self.results.test_items["accuracy"].final_result
-        if not accuracy_final_result:
-            return row
-
-        row = self._excel_write_section_header(ws, styles, row, "🎯 色准测试数据")
-
-        avg_delta_e = accuracy_final_result.get("avg_delta_e", 0)
-        max_delta_e = accuracy_final_result.get("max_delta_e", 0)
-        min_delta_e = accuracy_final_result.get("min_delta_e", 0)
-        excellent_count = accuracy_final_result.get("excellent_count", 0)
-        good_count = accuracy_final_result.get("good_count", 0)
-        poor_count = accuracy_final_result.get("poor_count", 0)
-
-        ws[f"A{row}"] = "平均 ΔE"
-        ws[f"B{row}"] = f"{avg_delta_e:.2f}"
-        ws[f"C{row}"] = "最大 ΔE"
-        ws[f"D{row}"] = f"{max_delta_e:.2f}"
-        ws[f"E{row}"] = "最小 ΔE"
-        ws[f"F{row}"] = f"{min_delta_e:.2f}"
-        self._excel_apply_row_style(
-            ws, row, ["A", "B", "C", "D", "E", "F"],
-            styles, label_cols=("A", "C", "E"),
-        )
-        row += 1
-
-        ws[f"A{row}"] = "优秀 (ΔE<3)"
-        ws[f"B{row}"] = f"{excellent_count} 个"
-        ws[f"C{row}"] = "良好 (3≤ΔE<5)"
-        ws[f"D{row}"] = f"{good_count} 个"
-        ws[f"E{row}"] = "偏差 (ΔE≥5)"
-        ws[f"F{row}"] = f"{poor_count} 个"
-        self._excel_apply_row_style(
-            ws, row, ["A", "B", "C", "D", "E", "F"],
-            styles, label_cols=("A", "C", "E"),
-        )
-        row += 1
-
-        color_patches = accuracy_final_result.get("color_patches", [])
-        delta_e_values = accuracy_final_result.get("delta_e_values", [])
-        color_measurements = accuracy_final_result.get("color_measurements", [])
-
-        if color_patches and delta_e_values:
-            row = self._excel_write_headers(
-                ws, styles, row,
-                ["序号", "颜色名称", "x 坐标", "y 坐标",
-                 "亮度 (cd/m²)", "ΔE 2000", "等级"],
-            )
-            for idx, (color_name, delta_e) in enumerate(
-                zip(color_patches, delta_e_values), start=1
-            ):
-                if delta_e < 3:
-                    grade = "优秀"
-                elif delta_e < 5:
-                    grade = "良好"
-                else:
-                    grade = "偏差"
-
-                x_val, y_val, lv_val = "N/A", "N/A", "N/A"
-                if color_measurements and idx - 1 < len(color_measurements):
-                    m = color_measurements[idx - 1]
-                    if len(m) >= 3:
-                        x_val, y_val, lv_val = m[0], m[1], m[2]
-
-                ws[f"A{row}"] = idx
-                ws[f"B{row}"] = color_name
-                ws[f"C{row}"] = x_val
-                ws[f"D{row}"] = y_val
-                ws[f"E{row}"] = lv_val
-                ws[f"F{row}"] = delta_e
-                ws[f"G{row}"] = grade
-
-                ws[f"A{row}"].number_format = "0"
-                if isinstance(x_val, (int, float)):
-                    ws[f"C{row}"].number_format = "0.0000"
-                if isinstance(y_val, (int, float)):
-                    ws[f"D{row}"].number_format = "0.0000"
-                if isinstance(lv_val, (int, float)):
-                    ws[f"E{row}"].number_format = "0.00"
-                ws[f"F{row}"].number_format = "0.00"
-
-                self._excel_apply_data_row(
-                    ws, row, ["A", "B", "C", "D", "E", "F", "G"], styles
-                )
-                row += 1
-
-        self.log_gui.log("  ✓ 添加色准数据（含 xy 坐标和亮度）")
-        return row + 1
-
     new_pq_results = _run_new_pq_results
     run_test = _run_run_test
     run_screen_module_test = _run_run_screen_module_test