Refine prediction workbook summary note

app/prediction.py

@@ -56,9 +56,13 @@ FEATURES = [
 
 ID_COLUMN = "管道编号"
 PIPE_AGE_COLUMN = "管龄（年）"
-REMAINING_LIFE_COLUMN = (
+REMAINING_LIFE_COLUMN = "剩余寿命（年）"
-    "预计剩余寿命（年）（管道健康状态 ≥0.5 的剩余年数；"
+REMAINING_LIFE_NOTE = (
-    "如管道健康状态在73年内均高于0.5，则为73减去当前管龄）"
+    "注：\n"
+    "剩余寿命计算方法为：\n"
+    "1）管道健康状态 ≥0.5 的剩余年数；\n"
+    "2）如管道健康状态在73年内均高于0.5（目前收集到模型数据管龄最大为73年），"
+    "那么管道剩余寿命为73减去当前管龄。"
 )
 LEGACY_PIPE_AGE_COLUMN = "管龄"
 COLUMN_ALIASES = {
@@ -549,6 +553,8 @@ def write_prediction_workbook(
     ]
 
     with pd.ExcelWriter(excel_path, engine="openpyxl") as writer:
+        from openpyxl.styles import Alignment
+
         summary_df = pd.DataFrame(
             summary_sheet_rows,
             columns=[ID_COLUMN, PIPE_AGE_COLUMN, "当前健康状态", "健康等级", REMAINING_LIFE_COLUMN],
@@ -564,6 +570,18 @@ def write_prediction_workbook(
         summary_worksheet = writer.book["结果摘要"]
         for cell in summary_worksheet["C"][1:]:
             cell.number_format = "0.00"
+        note_row = summary_worksheet.max_row + 2
+        summary_worksheet.merge_cells(
+            start_row=note_row,
+            start_column=1,
+            end_row=note_row + 3,
+            end_column=5,
+        )
+        note_cell = summary_worksheet.cell(note_row, 1)
+        note_cell.value = REMAINING_LIFE_NOTE
+        note_cell.alignment = Alignment(wrap_text=True, vertical="top")
+        for row_index in range(note_row, note_row + 4):
+            summary_worksheet.row_dimensions[row_index].height = 28
         sample_worksheet.freeze_panes = "A2"
         sample_worksheet.auto_filter.ref = sample_worksheet.dimensions
         sample_worksheet.column_dimensions["A"].width = 12

tests/test_prediction.py

@@ -212,8 +212,9 @@ class PredictionHelpersTest(unittest.TestCase):
                 summary_data.columns.tolist(),
                 [ID_COLUMN, PIPE_AGE_COLUMN, "当前健康状态", "健康等级", REMAINING_LIFE_COLUMN],
             )
-            self.assertEqual(summary_data[PIPE_AGE_COLUMN].tolist(), [10, 12])
+            summary_records = summary_data[summary_data[PIPE_AGE_COLUMN].notna()]
-            self.assertEqual(summary_data[REMAINING_LIFE_COLUMN].tolist(), [63, 61])
+            self.assertEqual(summary_records[PIPE_AGE_COLUMN].tolist(), [10, 12])
+            self.assertEqual(summary_records[REMAINING_LIFE_COLUMN].tolist(), [63, 61])
 
             sample_data = pd.read_excel(output_path, sheet_name="样本数据")
             self.assertEqual(sample_data.columns.tolist(), ["管龄（年）", "P001", "P002"])
@@ -229,8 +230,10 @@ class PredictionHelpersTest(unittest.TestCase):
             self.assertEqual(sample_worksheet.auto_filter.ref, "A1:C3")
             self.assertEqual(summary_worksheet["C2"].number_format, "0.00")
             self.assertEqual(sample_worksheet["B2"].number_format, "0.00")
-            self.assertIn("73减去当前管龄", summary_worksheet["E1"].value)
+            self.assertEqual(summary_worksheet["E1"].value, "剩余寿命（年）")
-            self.assertNotIn("73 - 当前管龄", summary_worksheet["E1"].value)
+            self.assertIn("A5:E8", [str(range_) for range_ in summary_worksheet.merged_cells.ranges])
+            self.assertIn("73减去当前管龄", summary_worksheet["A5"].value)
+            self.assertIn("目前收集到模型数据管龄最大为73年", summary_worksheet["A5"].value)
 
     def test_prediction_workbook_writes_pipe_ids_as_excel_text(self) -> None:
         predictions = [dummy_prediction("00123", [1], [0.9], 10, 0.9)]