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frontend.ui_main_menu

Main menu module for the Tkinter interface.

Overview

The ui_main_menu.py module contains the main application window and exit confirmation dialog for the Tkinter desktop interface.

Key Functions

Main Menu Creation

create_main_menu(normal_fitting_callback, single_fit_multiple_datasets_callback, multiple_fits_single_dataset_callback, all_fits_single_dataset_callback, watch_data_callback, help_callback) -> Tk

Create and display the main application menu window.

Parameters:

  • normal_fitting_callback: Function to call for normal fitting
  • single_fit_multiple_datasets_callback: Function to call for single fit on multiple datasets
  • multiple_fits_single_dataset_callback: Function to call for multiple fits on single dataset
  • all_fits_single_dataset_callback: Function to call for all fits on single dataset
  • watch_data_callback: Function to call for viewing data
  • help_callback: Function to display help information

Returns:

  • The main Tk window instance

Example:

from frontend.ui_main_menu import create_main_menu

def normal_fit():
    print("Normal fitting selected")

def view_data():
    print("View data selected")

menu = create_main_menu(
    normal_fitting_callback=normal_fit,
    single_fit_multiple_datasets_callback=lambda: print("Multiple datasets"),
    multiple_fits_single_dataset_callback=lambda: print("Multiple fits"),
    all_fits_single_dataset_callback=lambda: print("All fits"),
    watch_data_callback=view_data,
    help_callback=lambda: print("Help")
)

menu.mainloop()

Application Startup

start_main_menu(normal_fitting_callback, single_fit_multiple_datasets_callback, multiple_fits_single_dataset_callback, all_fits_single_dataset_callback, watch_data_callback, help_callback) -> None

Create and run the main application menu.

This is the entry point for the GUI application.

Parameters:

  • normal_fitting_callback: Function to call for normal fitting
  • single_fit_multiple_datasets_callback: Function to call for single fit on multiple datasets
  • multiple_fits_single_dataset_callback: Function to call for multiple fits on single dataset
  • all_fits_single_dataset_callback: Function to call for all fits on single dataset
  • watch_data_callback: Function to call for viewing data
  • help_callback: Function to display help information

Example:

from frontend.ui_main_menu import start_main_menu

# Define callbacks
def normal_fit():
    # Perform normal fitting
    pass

def view_data():
    # Show data viewer
    pass

# Start application
start_main_menu(
    normal_fitting_callback=normal_fit,
    single_fit_multiple_datasets_callback=lambda: None,
    multiple_fits_single_dataset_callback=lambda: None,
    all_fits_single_dataset_callback=lambda: None,
    watch_data_callback=view_data,
    help_callback=lambda: None
)

Exit Confirmation

show_exit_confirmation(parent_menu: Tk) -> None

Display exit confirmation dialog.

Parameters:

  • parent_menu: The parent menu window to close if user confirms exit

Example:

from frontend.ui_main_menu import show_exit_confirmation
from tkinter import Tk

root = Tk()
show_exit_confirmation(root)

close_application(menu: Tk) -> None

Close the application and exit.

Parameters:

  • menu: The main menu window to destroy

Menu Structure

The main menu displays:

  1. Logo: Application logo (if available)
  2. Welcome Message: Translated welcome text
  3. Action Buttons (in order):
    • Normal Fitting
    • Single Fit Multiple Datasets
    • Checker Fitting (Multiple fits on single dataset)
    • Total Fitting (All fits on single dataset)
    • Watch Data (View Data)
    • Information (Help dialog with collapsible sections; optional Donations button)
    • Configure (Configuration dialog to edit .env; saving restarts the app)
    • Exit
  4. Tooltips: Information and Configure buttons have tooltips (from menu.tooltip_information, menu.tooltip_config).
  5. Exit: Closes the application (with confirmation dialog when using the window close button or Exit).

UI Styling

The menu uses styling from config.UI_STYLE:

  • Background: Configurable background color
  • Foreground: Configurable text color
  • Fonts: Configurable font family and sizes
  • Buttons: Styled with consistent colors and sizes

Usage Examples

Complete Application Setup

from frontend.ui_main_menu import start_main_menu
from frontend.ui_dialogs import show_help_dialog
from fitting.workflow_controller import coordinate_data_loading
from frontend.ui_dialogs import (
    open_load_dialog, ask_variables
)

def normal_fitting():
    """Handle normal fitting mode."""
    result = coordinate_data_loading(
        parent_window=root,
        open_load_func=open_load_dialog,
        ask_variables_func=ask_variables
    )
    if result:
        # Perform fitting
        pass

def view_data():
    """Handle data viewing."""
    # Show data viewer
    pass

# Start application
start_main_menu(
    normal_fitting_callback=normal_fitting,
    single_fit_multiple_datasets_callback=lambda: None,
    multiple_fits_single_dataset_callback=lambda: None,
    all_fits_single_dataset_callback=lambda: None,
    watch_data_callback=view_data,
    help_callback=lambda: show_help_dialog(root)
)

Custom Menu with Logo

The menu automatically loads the logo from images/RegressionLab_logo_app.png if available:

from frontend.ui_main_menu import create_main_menu

menu = create_main_menu(
    normal_fitting_callback=lambda: None,
    single_fit_multiple_datasets_callback=lambda: None,
    multiple_fits_single_dataset_callback=lambda: None,
    all_fits_single_dataset_callback=lambda: None,
    watch_data_callback=lambda: None,
    help_callback=lambda: None
)

# Logo is automatically loaded and displayed if file exists
menu.mainloop()

Integration with Main Program

The main menu is typically used in main_program.py:

# main_program.py
from frontend.ui_main_menu import start_main_menu
from utils.logger import setup_logging, get_logger
from i18n import initialize_i18n

# Initialize
setup_logging()
initialize_i18n()

# Define callbacks
def normal_fitting():
    # Implementation
    pass

# ... other callbacks ...

# Start application
start_main_menu(
    normal_fitting_callback=normal_fitting,
    # ... other callbacks ...
)

Best Practices

  1. Callback Functions: Keep callbacks focused and simple

    def normal_fitting():
    # Simple, focused callback
    perform_fitting_workflow()

  2. Error Handling: Handle errors in callbacks

    def normal_fitting():
    try:
        perform_fitting_workflow()
    except Exception as e:
        messagebox.showerror("Error", str(e))

  3. State Management: Use global state or session objects if needed

    class AppState:
    def __init__(self):
        self.current_data = None
        self.current_fit = None

app_state = AppState()

def normal_fitting():
    result = coordinate_data_loading(...)
    if result:
        app_state.current_data = result[0]

Technical Details

Window Management

  • Window Type: Tk (root window)
  • Resizable: No (width and height fixed)
  • Fullscreen: No (can be configured)
  • Focus: First button receives focus

Logo Loading

The logo is loaded with PIL (Pillow) directly so that PNG transparency is preserved (no RGB conversion). The path is resolved from the project root using pathlib (project_root / 'images' / 'RegressionLab_logo_app.png').

  • Path: images/RegressionLab_logo_app.png (relative to project root)
  • Resizing: Scaled to max width 600px; height is proportional (aspect ratio preserved). Uses Image.Resampling.LANCZOS.
  • Fallback: Menu is shown without logo if the file is missing or loading fails (exception is caught).

Internationalization

All text is translated using the i18n module:

  • Menu title.
  • Welcome message.
  • Button labels.
  • Exit confirmation.

For more information about the UI, see Tkinter Guide.