Update app.py

app.py

@@ -324,16 +324,17 @@ 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.
+        (Same approach: col_group[-1] is the last column, so the formula goes in the next col.)
         """
         try:
             base_col = col_group[1]  # Mean column
-            std_col = col_group[2]   # StdDev column
+            std_col  = col_group[2]  # StdDev column
             
             row1, row2 = row_pair
             
             # SNR formula in row1
-            formula1 = f"=IFERROR({base_col}{row1}/{std_col}{row1},\"\")"
             formula_col = get_column_letter(column_index_from_string(col_group[-1]) + 1)
+            formula1 = f"=IFERROR({base_col}{row1}/{std_col}{row1},\"\")"
             cell1 = ws[f"{formula_col}{row1}"]
             cell1.value = formula1
             cell1.font = red_font
@@ -350,9 +351,6 @@ class DicomAnalyzer:
         except Exception as e:
             logger.error(f"Error adding formulas: {str(e)}")
 
-    ########################################################################
-    # التعديل الوحيد: في تجميع الـCNR نقرأ من خلية المعادلة بدلا من (m1 - m2)/std2
-    ########################################################################
     def save_formatted_results(self, output_path):
         try:
             if not self.results:
@@ -364,6 +362,7 @@ class DicomAnalyzer:
             center_alignment = openpyxl.styles.Alignment(horizontal='center')
             
             headers = ['Area', 'Mean', 'StdDev', 'Min', 'Max']
+
             column_groups = [
                 ('B', 'C', 'D', 'E', 'F'), ('H', 'I', 'J', 'K', 'L'),
                 ('N', 'O', 'P', 'Q', 'R'), ('T', 'U', 'V', 'W', 'X'),
@@ -373,14 +372,15 @@ class DicomAnalyzer:
                 ('BJ', 'BK', 'BL', 'BM', 'BN'), ('BP', 'BQ', 'BR', 'BS', 'BT'),
                 ('BV', 'BW', 'BX', 'BY', 'BZ')
             ]
-            
-            # Write table headers in row1
+
+            # Write headers in row1 for 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
 
+            # row pairs for 10 phantoms, each has row1 and row2
             row_pairs = [
                 (2, 3), (5, 6), (8, 9), (11, 12), (14, 15),
                 (17, 18), (20, 21), (23, 24), (26, 27), (29, 30)
@@ -391,13 +391,13 @@ class DicomAnalyzer:
                 '(4.5mm)', '(4mm)', '(3.5mm)', '(3mm)', '(2.5mm)'
             ]
             
-            # Phantom labels in column A
+            # Put phantom sizes in column A (above row1 for each pair)
             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 ROI results into the defined rows/columns
+            # Fill data from self.results in these row_pairs/column_groups
             result_idx = 0
             current_col_group = 0
             current_row_pair = 0
@@ -409,16 +409,19 @@ class DicomAnalyzer:
                 cols = column_groups[current_col_group]
                 rows = row_pairs[current_row_pair]
                 
+                # first measurement -> row1
                 if result_idx < len(self.results):
                     result = self.results[result_idx]
                     self._write_result_to_cells(ws, result, cols, rows[0])
                     result_idx += 1
                 
+                # second measurement -> row2
                 if result_idx < len(self.results):
                     result = self.results[result_idx]
                     self._write_result_to_cells(ws, result, cols, rows[1])
                     result_idx += 1
                 
+                # Insert SNR/CNR formulas in these 2 rows (mean, std dev columns to formula col)
                 self.add_formulas_to_template(ws, rows, cols, red_font)
                 
                 current_col_group += 1
@@ -426,7 +429,7 @@ class DicomAnalyzer:
                     current_col_group = 0
                     current_row_pair += 1
 
-            # Align cells for existing data
+            # center alignment for existing cells (2..30 in all column groups)
             for cols in column_groups:
                 for col in cols:
                     for row in range(2, 31):
@@ -434,122 +437,131 @@ class DicomAnalyzer:
                         if cell.value is not None:
                             cell.alignment = center_alignment
 
-            # Now build the "1-AVG" table from row 35
-            start_row = 35
-            ws['C35'] = "1-AVG"
-            ws['C35'].alignment = center_alignment
-            
-            ws.merge_cells('D35:E35')
-            ws.merge_cells('F35:G35')
-            ws.merge_cells('H35:I35')
-            
-            avg_headers = {
-                'D35': 'AVG MEAN',
-                'F35': 'AVG STDDEV',
-                'H35': 'AVG CNR'
-            }
-            for c_ref, text_val in avg_headers.items():
-                ws[c_ref] = text_val
-                ws[c_ref].font = red_font
-                ws[c_ref].alignment = center_alignment
-            
-            phantom_sizes2 = [
-                '(7.0mm)', '(6.5mm)', '(6.0mm)', '(5.5mm)', '(5.0mm)',
-                '(4.5mm)', '(4.0mm)', '(3.5mm)', '(3.0mm)', '(2.5mm)'
-            ]
+            # Now do the 3 sections: StdDev Averages, Mean Averages, CNR Averages
+
+            ##################
+            # 1) StdDev Averages
+            ##################
+            current_row = 32
+            stddev_header = ws.cell(row=current_row, column=1, value="StdDev Averages")
+            stddev_header.font = red_font
+            stddev_header.alignment = center_alignment
+            current_row += 1
             
-            # For each phantom row, gather Mean, STD, and read the CNR from the formula column
-            for i, p_size in enumerate(phantom_sizes2):
-                row = start_row + i + 1  # rows 36..45
+            for i, size in enumerate(phantom_sizes):
+                row_number = row_pairs[i][0]
+                stddev_values = []
                 
-                ws.merge_cells(f'D{row}:E{row}')
-                ws.merge_cells(f'F{row}:G{row}')
-                ws.merge_cells(f'H{row}:I{row}')
+                for cols in column_groups:
+                    stddev_col = cols[2]  # 'D','J','P'.. etc.
+                    cell_value = ws[f"{stddev_col}{row_number}"].value
+                    if cell_value not in [0, None, '']:
+                        stddev_values.append(float(cell_value))
                 
-                size_cell = ws[f'C{row}']
-                size_cell.value = p_size
-                size_cell.font = red_font
+                size_cell = ws.cell(row=current_row, column=1, value=size)
                 size_cell.alignment = center_alignment
 
-                if i >= len(row_pairs):
-                    continue
-                
-                (raw_row1, raw_row2) = row_pairs[i]
-                
+                if stddev_values:
+                    avg_stddev = sum(stddev_values) / len(stddev_values)
+                    avg_cell = ws.cell(row=current_row, column=2, value=avg_stddev)
+                    avg_cell.number_format = '0.000'
+                    avg_cell.alignment = center_alignment
+                current_row += 1
+
+            ##################
+            # 2) Mean Averages
+            ##################
+            current_row += 2
+            mean_header = ws.cell(row=current_row, column=1, value="Mean Averages")
+            mean_header.font = red_font
+            mean_header.alignment = center_alignment
+            current_row += 1
+
+            for i, size in enumerate(phantom_sizes):
+                row_number = row_pairs[i][0]  # we take the first row only (object)
                 mean_values = []
-                stddev_values = []
-                cnr_values = []
                 
-                # بدل ما نحسب (m1 - m2)/std2 مباشرة
-                # سنقرأ خلية المعادلة في row2 لكل مجموعة
-                for group in column_groups:
-                    mean_col = group[1]  # 'C' مثلاً
-                    std_col  = group[2]  # 'D' مثلاً
-
-                    # Read mean from row1 (if you want to average them)
-                    m1_val  = ws[f"{mean_col}{raw_row1}"].value
-                    if m1_val not in [None,'']:
-                        try:
-                            mean_values.append(float(m1_val))
-                        except:
-                            pass
-
-                    # Read std from row1 (if you want to average them)
-                    std_val = ws[f"{std_col}{raw_row1}"].value
-                    if std_val not in [None,'']:
-                        try:
-                            stddev_values.append(float(std_val))
-                        except:
-                            pass
-
-                    # ---- الأهم: CNR يأتي من صيغة المعادلة (العمود الذي يلي group[-1]) في الصف الثاني ----
-                    formula_col_index = column_index_from_string(group[-1]) + 1
-                    formula_col       = get_column_letter(formula_col_index)
-                    cnr_cell_value    = ws[f"{formula_col}{raw_row2}"].value  # حيث توجد =IFERROR((Mean1-Mean2)/Std2,"")
-
-                    if cnr_cell_value not in [None,'']:
-                        try:
-                            cnr_values.append(float(cnr_cell_value))
-                        except:
-                            pass
+                for cols in column_groups:
+                    mean_col = cols[1]  # 'C','I','O'.. etc.
+                    cell_value = ws[f"{mean_col}{row_number}"].value
+                    if cell_value not in [0, None, '']:
+                        mean_values.append(float(cell_value))
                 
-                # احسب المتوسطات
-                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
-
-                # اكتبهم في الجدول
-                if final_mean is not None:
-                    ws[f'D{row}'].value = final_mean
-                    ws[f'D{row}'].alignment = center_alignment
-                    ws[f'D{row}'].number_format = '0.0000'
+                size_cell = ws.cell(row=current_row, column=1, value=size)
+                size_cell.alignment = center_alignment
+
+                if mean_values:
+                    avg_mean = sum(mean_values) / len(mean_values)
+                    avg_cell = ws.cell(row=current_row, column=2, value=avg_mean)
+                    avg_cell.number_format = '0.000'
+                    avg_cell.alignment = center_alignment
+                current_row += 1
+
+            current_row += 2
+
+            ##################
+            # 3) CNR Averages (the snippet approach: build `=AVERAGE(...)` referencing each phantom's CNR cell)
+            ##################
+            cnr_header = ws.cell(row=current_row, column=1, value="CNR Averages")
+            cnr_header.font = red_font
+            cnr_header.alignment = center_alignment
+            current_row += 1
+            
+            for i, size in enumerate(phantom_sizes):
+                row_number = row_pairs[i][1]  # second row for each phantom
+                cnr_cells = []
+
+                # We'll collect references to the formula column for each column group and row2.
+                for cols in column_groups:
+                    # formula col is after the last col in group (like 'F' -> 'G')
+                    formula_col = get_column_letter(column_index_from_string(cols[-1]) + 1)
+                    cnr_cell_ref = f"{formula_col}{row_number}"
+
+                    # we also check if mean1,mean2,std2 are zero => skip or not. This is from the snippet logic.
+                    mean_col = cols[1]
+                    std_col  = cols[2]
+                    
+                    mean1_val = ws[f"{mean_col}{row_pairs[i][0]}"].value
+                    mean2_val = ws[f"{mean_col}{row_pairs[i][1]}"].value
+                    std2_val  = ws[f"{std_col}{row_pairs[i][1]}"].value
+
+                    try:
+                        mean1_val = float(mean1_val) if mean1_val not in [None, ''] else 0
+                        mean2_val = float(mean2_val) if mean2_val not in [None, ''] else 0
+                        std2_val  = float(std2_val)  if std2_val  not in [None, ''] else 0
+                    except:
+                        mean1_val, mean2_val, std2_val = 0, 0, 0
+
+                    if not (mean1_val == 0 and mean2_val == 0 and std2_val == 0):
+                        # i.e. valid ROI data => we add the formula cell reference to average later.
+                        cnr_cells.append(cnr_cell_ref)
                 
-                if final_std is not None:
-                    ws[f'F{row}'].value = final_std
-                    ws[f'F{row}'].alignment = center_alignment
-                    ws[f'F{row}'].number_format = '0.0000'
+                size_cell = ws.cell(row=current_row, column=1, value=size)
+                size_cell.alignment = center_alignment
+
+                if cnr_cells:
+                    # create a new formula to average those CNR cells:
+                    average_formula = f'=IFERROR(AVERAGE({",".join(cnr_cells)}), "")'
+                    avg_cell = ws.cell(row=current_row, column=2)
+                    avg_cell.value = average_formula
+                    avg_cell.number_format = '0.000'
+                    avg_cell.alignment = center_alignment
                 
-                if final_cnr is not None:
-                    ws[f'H{row}'].value = final_cnr
-                    ws[f'H{row}'].alignment = center_alignment
-                    ws[f'H{row}'].number_format = '0.0000'
-
-            # Border around 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
-            )
-            for r in range(35, 46):
-                for c in ['C','D','E','F','G','H','I']:
-                    ws[f'{c}{r}'].border = border
+                current_row += 1
 
-            # Finally save
+            # Finally, center-align from row 32.. up to current_row in columns 1..2
+            for row in range(32, current_row):
+                for col in range(1, 3):
+                    cell = ws.cell(row=row, column=col)
+                    cell.alignment = center_alignment
+
+            # Save workbook to disk
             wb.save(output_path)
             return output_path, f"Results saved successfully ({len(self.results)} measurements)"
+
         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')
@@ -600,7 +612,7 @@ class DicomAnalyzer:
         return image, self.format_results()
 
     def undo_last(self, image):
-        if not self.results:  
+        if not self.results:  # لو مفيش نتائج أصلاً
             return self.update_display(), self.format_results()
             
         last_result = self.results[-1]
@@ -663,7 +675,7 @@ def create_interface():
         - Use Zoom In/Out buttons or Reset View to adjust zoom level.
         - Use Reset All to clear all measurements.
         - "Save Results": basic Excel with raw data.
-        - "Save Formatted Results": Excel with advanced formatting & the 1-AVG table (including correct CNR averaging).
+        - "Save Formatted Results": Excel with advanced formatting & formulas (including average CNR).
         """)
 
         def update_diameter(x):