Update app.py

app.py

@@ -98,7 +98,6 @@ class DicomAnalyzer:
         except Exception as e:
             print(f"Error loading DICOM file: {str(e)}")
             return None, f"Error loading DICOM file: {str(e)}"
-
     def normalize_image(self, image):
         try:
             normalized = cv2.normalize(
@@ -275,49 +274,14 @@ class DicomAnalyzer:
         except Exception as e:
             print(f"Error updating display: {str(e)}")
             return self.original_display
-    def save_results(self):
-        """
-        Basic save function for raw results with improved error handling and logging
-        """
-        try:
-            if not self.results:
-                logger.warning("Attempted to save with no results")
-                return None, "No results to save"
-
-            df = pd.DataFrame(self.results)
-            columns_order = ['Area (mm²)', 'Mean', 'StdDev', 'Min', 'Max', 'Point']
-            df = df[columns_order]
-
-            timestamp = time.strftime("%Y%m%d_%H%M%S")
-            output_file = f"analysis_results_{timestamp}.xlsx"
-
-            with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
-                df.to_excel(writer, index=False, sheet_name='Results')
-                
-                worksheet = writer.sheets['Results']
-                for idx, col in enumerate(df.columns):
-                    max_length = max(
-                        df[col].astype(str).apply(len).max(),
-                        len(str(col))
-                    ) + 2
-                    worksheet.column_dimensions[get_column_letter(idx + 1)].width = max_length
-
-            logger.info(f"Results saved successfully to {output_file}")
-            return output_file, f"Results saved successfully to {output_file}"
-
-        except Exception as e:
-            error_msg = f"Error saving results: {str(e)}"
-            logger.error(error_msg)
-            logger.error(traceback.format_exc())
-            return None, error_msg
-
     def add_formulas_to_template(self, ws, row_pair, col_group, red_font):
         try:
-            base_col = col_group[1]
-            std_col = col_group[2]
+            base_col = col_group[1]  # Mean column
+            std_col = col_group[2]   # StdDev column
             
             row1, row2 = row_pair
             
+            # SNR Formula for first row
             formula1 = f"={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}"]
@@ -325,6 +289,7 @@ class DicomAnalyzer:
             cell1.font = red_font
             cell1.alignment = openpyxl.styles.Alignment(horizontal='center')
             
+            # CNR Formula for second row
             formula2 = f"=({base_col}{row1}-{base_col}{row2})/{std_col}{row2}"
             cell2 = ws[f"{formula_col}{row2}"]
             cell2.value = formula2
@@ -414,6 +379,60 @@ class DicomAnalyzer:
                         if cell.value is not None:
                             cell.alignment = center_alignment
 
+            # Add space before averages tables
+            current_row = 32
+
+            # Headers for StdDev Averages
+            ws.cell(row=current_row, column=1, value="StdDev Averages").font = red_font
+            current_row += 1
+            
+            # Calculate StdDev averages for each row pair
+            for i, size in enumerate(phantom_sizes):
+                row_number = row_pairs[i][0]  # First row only
+                stddev_values = []
+                
+                for cols in column_groups:
+                    stddev_col = cols[2]  # StdDev column
+                    cell_value = ws[f"{stddev_col}{row_number}"].value
+                    if cell_value not in [0, None, '']:  # Ignore zeros and empty values
+                        stddev_values.append(float(cell_value))
+                
+                if stddev_values:
+                    avg = sum(stddev_values) / len(stddev_values)
+                    ws.cell(row=current_row, column=1, value=size)
+                    ws.cell(row=current_row, column=2, value=avg).number_format = '0.000'
+                current_row += 1
+
+            current_row += 2  # Space between tables
+
+            # Headers for CNR Averages
+            ws.cell(row=current_row, column=1, value="CNR Averages").font = red_font
+            current_row += 1
+            
+            # Calculate CNR averages for each row pair
+            for i, size in enumerate(phantom_sizes):
+                row_number = row_pairs[i][1]  # Second row for CNR
+                cnr_values = []
+                
+                for cols in column_groups:
+                    formula_col = get_column_letter(column_index_from_string(cols[-1]) + 1)
+                    cell_value = ws[f"{formula_col}{row_number}"].value
+                    if isinstance(cell_value, str) and cell_value.startswith('='):
+                        cnr_values.append(f"={formula_col}{row_number}")
+                
+                if cnr_values:
+                    formula = f"=AVERAGE({','.join(cnr_values)})"
+                    ws.cell(row=current_row, column=1, value=size)
+                    cell = ws.cell(row=current_row, column=2, value=formula)
+                    cell.number_format = '0.000'
+                current_row += 1
+
+            # Format the tables
+            for row in range(32, current_row):
+                for col in range(1, 3):
+                    cell = ws.cell(row=row, column=col)
+                    cell.alignment = center_alignment
+
             wb.save(output_path)
             return output_path, f"Results saved successfully ({result_idx} measurements)"