SimpleGA/app.py at master · mbilalakmal/SimpleGA · GitHub

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# -----------------------------------------------------------
# This module defines the GUI.
#
# A GUI window asks user for:
# (1) Parameters which is to be evaluated,
# (2) range of values to test for the selected parameter,
# (3) values of remaining parameters
# (4) Trials - this is how many times each configuration is run
#
# After user describes everything, the app does heavy computing
# on the main thread (causing the GUI to hang) and draws a graph.
#
#
# (C) 2020 Muhammad Bilal Akmal, 17K-3669
# -----------------------------------------------------------

import PySimpleGUI as sg

import evaluation as ev

parameters = ['Chromosome Length'.ljust(20),
              'Population Size'.ljust(20),
              'Maximum Generations'.ljust(20)]

sg.theme('DarkBlue')

layout = [
    [sg.Text('')],  # padding
    [sg.Image(r'resources\icon.png'),
     sg.Text('SimpleGA', font=('Helvetica', 21))],  # Title

    [sg.Text('A program for parameters evaluation for a genetic algorithm.',
             font=('Helvetica', 12))
     ],  # subtitle

    [sg.Text('_' * 80)],
    [sg.Text('Evaluate Parameter: '),
     sg.Combo(
         values=parameters,
         default_value=parameters[0],
         enable_events=True,
         size=(24, 4),
         font=('Helvetica', 10),
         key='_COMBO_'
     )
     ],  # combobox with parameter selection
    [sg.Text('')],  # padding

    # range(start, stop, step)
    [
        sg.Text('Start'),
        sg.Spin([i for i in range(2, 10000)], initial_value=2, size=(6, 1), key='_START_'),
        sg.Text('   Stop'),
        sg.Spin([i for i in range(2, 10000)], initial_value=4, size=(6, 1), key='_STOP_'),
        sg.Text('   Step'),
        sg.Spin([i for i in range(1, 10000)], initial_value=1, size=(6, 1), key='_STEP_'),
    ],

    [sg.Text('')],  # padding
    [sg.Frame(title='   Other Parameters    ',
              layout=[
                  [sg.Text(parameters[1], key='_FIRST_', font='Courier 10'),
                   sg.Spin([i for i in range(2, 10000)], initial_value=2, size=(10, 1), key='_FIRST_VAL_')],
                  [sg.Text(parameters[2], key='_SECOND_', font='Courier 10'),
                   sg.Spin([i for i in range(2, 10000)], initial_value=2, size=(10, 1), key='_SECOND_VAL_')],
                  [sg.Text('')],  # padding
                  [sg.Text('Number of Trials'.ljust(20), font='Courier 10'),
                   sg.Spin([i for i in range(10, 10000, 10)], initial_value=10, size=(10, 1), key='_TRIALS_')],

              ],
              )],
    [sg.Text('')],  # padding
    [sg.Button('RUN ALGORITHM', bind_return_key=True)],
    [sg.Text('')],  # padding
]

window = sg.Window(
    title='Artificial Intelligence - Assignment 2',
    layout=layout,
    resizable=True,
    element_padding=(4, 4),
    element_justification='center'
)

while True:
    event, values = window.read()

    if event is None:
        break

    # check if combobox selection changed
    elif event == '_COMBO_':

        if values['_COMBO_'] == parameters[0]:
            window['_FIRST_'].update(parameters[1])
            window['_SECOND_'].update(parameters[2])

        elif values['_COMBO_'] == parameters[1]:
            window['_FIRST_'].update(parameters[2])
            window['_SECOND_'].update(parameters[0])

        elif values['_COMBO_'] == parameters[2]:
            window['_FIRST_'].update(parameters[0])
            window['_SECOND_'].update(parameters[1])

    # check if run algorithm button is clicked
    elif event == 'RUN ALGORITHM':

        start = int(values['_START_'])
        stop = int(values['_STOP_']) + 1  # closed interval
        step = int(values['_STEP_'])

        eval_parameter = values['_COMBO_']
        first_parameter = int(values['_FIRST_VAL_'])
        second_parameter = int(values['_SECOND_VAL_'])

        trials = int(values['_TRIALS_'])

        if eval_parameter == parameters[0]:
            ev.evaluate_chromosome_length(
                start=start,
                stop=stop,
                step=step,
                pop_size=first_parameter,
                max_gens=second_parameter,
                trials=trials
            )

        elif eval_parameter == parameters[1]:
            ev.evaluate_population_size(
                start=start,
                stop=stop,
                step=step,
                max_gens=first_parameter,
                chr_lnth=second_parameter,
                trials=trials
            )

        elif eval_parameter == parameters[2]:
            ev.evaluate_maximum_generations(
                start=start,
                stop=stop,
                step=step,
                chr_lnth=first_parameter,
                pop_size=second_parameter,
                trials=trials
            )

window.close()