pythonoopuser-interfacetkinterclassification
I am struggliing spilting the classifers catagory and displaying then in 2 rows. I am using python and tkinter to build this GUI
This my code.
import tkinter as tk
from tkinter import ttk, filedialog
class ClassifierSelectionApp:
def __init__(self, root):
self.root = root
style = ttk.Style()
style.configure("TButton", font=("Arial", 11), padding=5)
style.configure("TLabel", font=("Arial", 11))
# Main frame
main_frame = ttk.Frame(root, padding="10 10 10 10")
main_frame.grid(row=0, column=0, sticky=(tk.W, tk.E, tk.N, tk.S))
# Configure grid
for i in range(8): # Number of columns
main_frame.columnconfigure(i, weight=1)
for i in range(8): # Increased number of rows
main_frame.rowconfigure(i, weight=1)
# Training Data
self.label_train = ttk.Label(main_frame, text="Select Training Data:", style="TLabel")
self.label_train.grid(row=0, column=0, sticky='w', padx=5, pady=5)
self.button_train = ttk.Button(main_frame, text="Browse", command=self.browse_train, style="TButton")
self.button_train.grid(row=1, column=0, padx=5, pady=5)
# Testing Data
self.label_test = ttk.Label(main_frame, text="Select Testing Data:", style="TLabel")
self.label_test.grid(row=0, column=1, sticky='w', padx=5, pady=5)
self.button_test = ttk.Button(main_frame, text="Browse", command=self.browse_test, style="TButton")
self.button_test.grid(row=1, column=1, padx=5, pady=5)
# Category Labels
categories = ["Convolution based", "Deep learning", "Dictionary based",
"Distance based", "Feature based", "Interval based",
"Shapelet based", "Hybrid"]
for i, category in enumerate(categories):
label = ttk.Label(main_frame, text=category, font=("Arial", 11, "bold"))
label.grid(row=2, column=i, padx=5, pady=5, sticky='w') # Align to the left
# Row Labels and Checkbuttons
self.check_vars = []
rows_top = [
["Rocket Classifier", "CNN ", "MUSE", "K-NN", "Catch22", "Canonical Interval Forest", "Random Forest", "HIVECOTEV2"],
["Arsenal", "", "WEASEL", "Elastic Ensemble", "Fresh PRINCE", "DrCIF", "", ""],
["", "", "BOSS Ensemble", "", "", "RandomIntervalSpectralEnsemble", "", ""]
]
rows_bottom = [
["", "", "Contractable BOSS", "", "", "SupervisedTimeSeriesForest", "", ""],
["", "", "Individual BOSS", "", "", "TimeSeriesForestClassifier", "", ""],
["", "", "Temporal Dictionary Ensemble", "", "", "", "", ""]
]
# Determine the maximum width for each column
max_widths = [max(len(row[i]) for row in rows_top + rows_bottom if i < len(row) and row[i]) for i in range(len(categories))]
# Place the top half of the rows in the grid
for r, row in enumerate(rows_top):
row_vars = []
for c, item in enumerate(row):
if item:
var = tk.BooleanVar()
checkbutton = ttk.Checkbutton(main_frame, text=item, variable=var, width=max_widths[c])
checkbutton.grid(row=r+3, column=c, padx=5, pady=5, sticky='w') # Align to the left
row_vars.append(var)
else:
row_vars.append(None)
self.check_vars.append(row_vars)
# Place the bottom half of the rows in the grid, offset by the number of rows in rows_top
for r, row in enumerate(rows_bottom):
row_vars = []
for c, item in enumerate(row):
if item:
var = tk.BooleanVar()
checkbutton = ttk.Checkbutton(main_frame, text=item, variable=var, width=max_widths[c])
checkbutton.grid(row=r+3+len(rows_top), column=c, padx=5, pady=5, sticky='w') # Align to the left
row_vars.append(var)
else:
row_vars.append(None)
self.check_vars.append(row_vars)
def browse_train(self):
file_path = filedialog.askopenfilename()
print(f"Training data selected: {file_path}")
def browse_test(self):
file_path = filedialog.askopenfilename()
print(f"Testing data selected: {file_path}")
if __name__ == "__main__":
root = tk.Tk()
app = ClassifierSelectionApp(root)
root.mainloop()
Here is an image of what my GUI look like right now, I want to make it look more presentable. I don't want it to be so wide but I want also keep all of the option. Tried using chatgpt but it was useless.
I want to build an application that can classify time sereis data. To do this I have a libary called AEON toolkit and I have important all of the classifers I wanted.
All the classifers I am going to be using are neetly catagoried in their catagiores but the application looks too wide. And I dont want that.
Insted I want 4 classifers catagory displayed in one row and the other 4 displayed in the row right after. I tried multiple thing but could not find a way to do this.
Any help would be greatly appreciated.
Please note, if there is a better way of displaying this in tkinter I am open to suggestions.
Solution
It is more easier to layout those checkbuttons by putting related ones in frames:
...
class ClassifierSelectionApp:
def __init__(self, root):
self.root = root
style = ttk.Style()
style.configure("TButton", font=("Arial", 11), padding=5)
style.configure("TLabel", font=("Arial", 11))
# Main frame
main_frame = ttk.Frame(root, padding="10 10 10 10")
main_frame.grid(row=0, column=0, sticky=(tk.W, tk.E, tk.N, tk.S))
# Training Data
self.label_train = ttk.Label(main_frame, text="Select Training Data:", style="TLabel")
self.label_train.grid(row=0, column=0, sticky='w', padx=5, pady=5)
self.button_train = ttk.Button(main_frame, text="Browse", command=self.browse_train, style="TButton")
self.button_train.grid(row=1, column=0, padx=5, pady=5, sticky='w')
# Testing Data
self.label_test = ttk.Label(main_frame, text="Select Testing Data:", style="TLabel")
self.label_test.grid(row=0, column=1, sticky='w', padx=5, pady=5)
self.button_test = ttk.Button(main_frame, text="Browse", command=self.browse_test, style="TButton")
self.button_test.grid(row=1, column=1, padx=5, pady=5, sticky='w')
# Category frame
category_frame = ttk.Frame(root)
category_frame.grid(row=1, column=0)
# better use a dictionary to store the category data
categories = {
"Convolution based": ["Rocket Classifier", "Arsenal"],
"Deep learning": ["CNN"],
"Dictionary based": ["MUSE", "WEASEL", "BOSS Ensemble", "Contractable BOSS", "Individual BOSS", "Temporal Dictionary Ensemble"],
"Distance based": ["K-NN", "Elastic Ensemble"],
"Feature based": ["Catch22", "Fresh PRINCE"],
"Interval based": ["Canonical Interval Forest", "DrCIF", "Random Interval Spectral Ensemble", "Supervised Time Series Forest", "Time Series Forest Classifier"],
"Shapelet based": ["Random Forest"],
"Hybrid": ["TIVECOTEV2"],
}
# calculate number of columns for two rows
columns = int(len(categories) / 2 + 0.5)
self.check_vars = {}
for i, (category, items) in enumerate(categories.items()):
self.check_vars[category] = []
# determine the row and column
row, col = divmod(i, columns)
# create a frame for this category
frame = ttk.Frame(category_frame)
frame.grid(row=row, column=col, sticky='nsew', padx=5, pady=5)
ttk.Label(frame, text=category, font=('Arial', 11, 'bold')).pack(padx=5, pady=5, anchor='w')
for item in items:
var = tk.BooleanVar()
ttk.Checkbutton(frame, text=item, variable=var).pack(anchor='w', padx=5, pady=5)
self.check_vars[category].append(var)
...
Result:
