Update app.py

app.py

@@ -324,8 +324,6 @@ class DicomAnalyzer:
     def add_formulas_to_template(self, ws, row_pair, col_group, red_font):
         """
         Inserts SNR (first row) and CNR (second row) formulas with IFERROR.
-        SNR => row1
-        CNR => row2
         """
         try:
             base_col = col_group[1]  # Mean column
@@ -333,7 +331,7 @@ class DicomAnalyzer:
             
             row1, row2 = row_pair
             
-            # SNR formula in row1
+            # SNR formula
             formula1 = f"=IFERROR({base_col}{row1}/{std_col}{row1},\"\")"
             formula_col = get_column_letter(column_index_from_string(col_group[-1]) + 1)
             cell1 = ws[f"{formula_col}{row1}"]
@@ -341,7 +339,7 @@ class DicomAnalyzer:
             cell1.font = red_font
             cell1.alignment = openpyxl.styles.Alignment(horizontal='center')
             
-            # CNR formula in row2
+            # CNR formula
             formula2 = f"=IFERROR(({base_col}{row1}-{base_col}{row2})/{std_col}{row2},\"\")"
             cell2 = ws[f"{formula_col}{row2}"]
             cell2.value = formula2
@@ -352,11 +350,15 @@ class DicomAnalyzer:
         except Exception as e:
             logger.error(f"Error adding formulas: {str(e)}")
 
+    ########################################################################
+    # نفس الدالة الأصلية، لكن نهاية الدالة تضع الجدول في الصف 35 بالشكل المطلوب
+    ########################################################################
     def save_formatted_results(self, output_path):
         try:
             if not self.results:
                 return None, "No results to save"
 
+            # هنا كل شيء مثل كودك: تنشئ Workbook جديد، تصنع الشيت، تضع الهيدرز...
             wb = openpyxl.Workbook()
             ws = wb.active
             red_font = openpyxl.styles.Font(color="FF0000")
@@ -373,32 +375,29 @@ class DicomAnalyzer:
                 ('BV', 'BW', 'BX', 'BY', 'BZ')
             ]
             
-            # Write main headers in each column group
             for cols in column_groups:
                 for i, header in enumerate(headers):
                     cell = ws[f"{cols[i]}1"]
                     cell.value = header
                     cell.alignment = center_alignment
 
-            # Pairs of rows for measurements
             row_pairs = [
                 (2, 3), (5, 6), (8, 9), (11, 12), (14, 15),
                 (17, 18), (20, 21), (23, 24), (26, 27), (29, 30)
             ]
 
-            # Phantom sizes (used for labeling)
             phantom_sizes = [
                 '(7mm)', '(6.5mm)', '(6mm)', '(5.5mm)', '(5mm)',
                 '(4.5mm)', '(4mm)', '(3.5mm)', '(3mm)', '(2.5mm)'
             ]
             
-            # Put phantom size labels in column A (row-1 from the first measurement row)
+            # كتابة أسماء الفانتوم باللون الأحمر في العمود A (قبل الصف الأول)
             for i, size in enumerate(phantom_sizes):
                 header_cell = ws.cell(row=row_pairs[i][0]-1, column=1, value=size)
                 header_cell.font = red_font
                 header_cell.alignment = center_alignment
 
-            # Write all self.results into the sheet, as in your original code
+            # توزيع نتائج ROI في هذه الصفوف والأعمدة كما في كودك
             result_idx = 0
             current_col_group = 0
             current_row_pair = 0
@@ -420,7 +419,6 @@ class DicomAnalyzer:
                     self._write_result_to_cells(ws, result, cols, rows[1])
                     result_idx += 1
                 
-                # Add SNR/CNR formulas for these two rows
                 self.add_formulas_to_template(ws, rows, cols, red_font)
                 
                 current_col_group += 1
@@ -428,7 +426,7 @@ class DicomAnalyzer:
                     current_col_group = 0
                     current_row_pair += 1
 
-            # Center-align all non-empty cells from row 2..30 in those columns
+            # ضبط المحاذاة للخلايا التي كُتبت بالفعل
             for cols in column_groups:
                 for col in cols:
                     for row in range(2, 31):
@@ -436,16 +434,24 @@ class DicomAnalyzer:
                         if cell.value is not None:
                             cell.alignment = center_alignment
 
-            # Now create the 1-AVG table at row 35..45
+            ################################################################
+            # وهنا بدلًا من وضع جداول STDDEV/Mean/CNR منفصلة،
+            # نضع الجدول المدمج "1-AVG" من الصف 35 مثل الصورة التي أرسلتها
+            ################################################################
+            
+            # سنستخدم نفس فكرة الجدول بالدمج من D35:E35, F35:G35, H35:I35
             start_row = 35
+            
+            # ضع عنوان "1-AVG" في C35
             ws['C35'] = "1-AVG"
             ws['C35'].alignment = center_alignment
             
-            # Merge 3 sets of headers in row 35
+            # ادمج الخلايا الخاصة بالعناوين
             ws.merge_cells('D35:E35')
             ws.merge_cells('F35:G35')
             ws.merge_cells('H35:I35')
             
+            # ضع العناوين باللون الأحمر
             avg_headers = {
                 'D35': 'AVG MEAN',
                 'F35': 'AVG STDDEV',
@@ -456,74 +462,81 @@ class DicomAnalyzer:
                 ws[c_ref].font = red_font
                 ws[c_ref].alignment = center_alignment
             
-            # We will re-use the same 10 phantom sizes
+            # نفس أسماء الفانتوم
             phantom_sizes2 = [
                 '(7.0mm)', '(6.5mm)', '(6.0mm)', '(5.5mm)', '(5.0mm)',
                 '(4.5mm)', '(4.0mm)', '(3.5mm)', '(3.0mm)', '(2.5mm)'
             ]
             
-            # For each phantom row, read the same row_pairs to gather data
             for i, p_size in enumerate(phantom_sizes2):
                 row = start_row + i + 1  # 36..45
                 
-                # Merge each row's 3 sets: (D-E), (F-G), (H-I)
+                # ادمج لكل صف: D-E ، F-G ، H-I
                 ws.merge_cells(f'D{row}:E{row}')
                 ws.merge_cells(f'F{row}:G{row}')
                 ws.merge_cells(f'H{row}:I{row}')
                 
+                # اكتب اسم الفانتوم باللون الأحمر في العمود C
                 size_cell = ws[f'C{row}']
                 size_cell.value = p_size
                 size_cell.font = red_font
                 size_cell.alignment = center_alignment
 
+                # لكي نحسب الـAVG الحقيقي من الصفوف 2..3 إلخ،
+                # نستخدم row_pairs[i] إن أردت. أو كما في المثال الأصلي:
                 if i < len(row_pairs):
                     (raw_row1, raw_row2) = row_pairs[i]
                 else:
-                    continue
+                    continue  # لو عندك 10 فقط
+                
+                # لنفترض أننا نقرأ من نفس الأعمدة اللي فيها mean & std
+                # نفترض عندنا على الأقل عمود mean_col = cols[1], stddev_col = cols[2]
+                # لكن عندك عدة col groups؛ إذا تريد تجمع من الأول فقط:
+                # أو خذ فكرة snippetك السابق:
                 
                 mean_values = []
                 stddev_values = []
                 cnr_values = []
                 
-                # We read from the same column groups. 
-                # But now for CNR, we'll read from the formula column (the one add_formulas_to_template uses).
+                # Example: لو تحب تجمع من نفس الـ column_groups الأولى بس
                 for group in column_groups:
-                    mean_col = group[1]  # e.g. 'C'
-                    std_col  = group[2]  # e.g. 'D'
-
-                    # For MEAN, let's read row1 as before
-                    val_mean = ws[f"{mean_col}{raw_row1}"].value
-                    # For STDDEV, also row1 if you prefer
-                    val_std = ws[f"{std_col}{raw_row1}"].value
-
-                    # For CNR, the formula is placed in row2 in the "formula column" after group[-1].
-                    # So let's find that column letter:
-                    formula_col_index = column_index_from_string(group[-1]) + 1
-                    formula_col = get_column_letter(formula_col_index)
+                    mean_col = group[1]  # 'C','I','O'...الخ
+                    std_col  = group[2]  # 'D','J','P'...الخ
                     
-                    # The formula was put in row2
-                    val_cnr = ws[f"{formula_col}{raw_row2}"].value
+                    # raw_row1 = الصف الأول
+                    # raw_row2 = الصف الثاني
+                    m1 = ws[f"{mean_col}{raw_row1}"].value
+                    m2 = ws[f"{mean_col}{raw_row2}"].value
+                    std2 = ws[f"{std_col}{raw_row1}"].value
                     
-                    # Convert them to float if possible
                     try:
-                        val_mean = float(val_mean) if val_mean not in [None, ''] else None
-                        val_std  = float(val_std)  if val_std  not in [None, ''] else None
-                        val_cnr  = float(val_cnr)  if val_cnr  not in [None, ''] else None
+                        m1   = float(m1)   if m1   not in [None,''] else None
+                        m2   = float(m2)   if m2   not in [None,''] else None
+                        std2 = float(std2) if std2 not in [None,''] else None
                     except:
-                        val_mean,val_std,val_cnr = None,None,None
-                    
-                    if val_mean is not None:
-                        mean_values.append(val_mean)
-                    if val_std is not None:
-                        stddev_values.append(val_std)
-                    if val_cnr is not None:
-                        cnr_values.append(val_cnr)
+                        m1,m2,std2 = None,None,None
+                    if (m1 is not None) and (m2 is not None) and (std2 is not None) and (std2!=0):
+                        mean_values.append(m1)
+                        stddev_values.append(std2)
+                        cnr_values.append((m1 - m2)/std2)
                 
-                # Compute final averages
-                final_mean = sum(mean_values)/len(mean_values) if mean_values else None
-                final_std  = sum(stddev_values)/len(stddev_values) if stddev_values else None
-                final_cnr  = sum(cnr_values)/len(cnr_values) if cnr_values else None
+                # الآن نحسب المتوسط
+                if len(mean_values) > 0:
+                    final_mean = sum(mean_values)/len(mean_values)
+                else:
+                    final_mean = None
+                
+                if len(stddev_values) > 0:
+                    final_std = sum(stddev_values)/len(stddev_values)
+                else:
+                    final_std = None
+                
+                if len(cnr_values) > 0:
+                    final_cnr = sum(cnr_values)/len(cnr_values)
+                else:
+                    final_cnr = None
                 
+                # نكتبها في الخلايا المدمجة
                 if final_mean is not None:
                     ws[f'D{row}'].value = final_mean
                     ws[f'D{row}'].alignment = center_alignment
@@ -539,7 +552,7 @@ class DicomAnalyzer:
                     ws[f'H{row}'].alignment = center_alignment
                     ws[f'H{row}'].number_format = '0.0000'
 
-            # Finally, border around C35..I45
+            # أخيراً، ضع الحدود حول C35..I45
             thin_side = openpyxl.styles.Side(style='thin')
             border = openpyxl.styles.Border(
                 left=thin_side, right=thin_side, top=thin_side, bottom=thin_side
@@ -553,6 +566,7 @@ class DicomAnalyzer:
         except Exception as e:
             logger.error(f"Error saving formatted results: {str(e)}")
             return None, f"Error saving results: {str(e)}"
+    ########################################################################
 
     def _write_result_to_cells(self, ws, result, cols, row):
         center_alignment = openpyxl.styles.Alignment(horizontal='center')
@@ -603,14 +617,17 @@ class DicomAnalyzer:
         return image, self.format_results()
 
     def undo_last(self, image):
-        if not self.results:  # لا توجد نتائج
+        if not self.results:  # لو مفيش نتائج أصلاً
             return self.update_display(), self.format_results()
             
         last_result = self.results[-1]
+        # نتحقق إذا كان آخر إجراء قياس حقيقي أم صف صفري
         is_measurement = last_result['Point'] != '(0, 0)'
         
+        # نمسح آخر نتيجة
         self.results.pop()
         
+        # لو كان قياس حقيقي، نمسح العلامة المقابلة له
         if is_measurement and self.marks:
             self.marks.pop()