from tkinter import *
from tkinter import messagebox
import pickle
import numpy as np
from sklearn.preprocessing import StandardScaler

window = Tk()
window.minsize(width=600, height=600)
window.config(padx=50, pady=50)
window.config(background="#ffffff")
window.title("Regresja")

canvas = Canvas(width=250, height=150, highlightthickness=0, background="#ffffff")
house = PhotoImage(file="house.png")
canvas.create_image(140,75, image=house)
canvas.grid(column=0, row=0, columnspan=2, padx=60)

tytul = Label()
tytul.config(text="Wycena wartości mieszkania na podstawie danych z serwisu otodom.pl", padx=70, pady=50, background="#ffffff")
tytul.grid(column=0, row=1, columnspan=2)


metraz = Label()
metraz.config(text="Metraż", pady=20, background="#ffffff")
metraz.grid(column=0, row=2)

metraz_entry = Entry()
metraz_entry.grid(column=0, row=3)

pietro_entry = Entry()
pietro_entry.grid(column=1, row=3)


pietro = Label()
pietro.config(text="Piętro", pady=20, background="#ffffff")
pietro.grid(column=1, row=2)


przewidywania = Label()
przewidywania.config(text="Przewidywanie:", pady=20, padx=5, background="#ffffff")
przewidywania.grid(column=0, row=5, sticky='e')

wartosc_regresji = Label()
wartosc_regresji.config(text="Wartosć przewidywana", background="#ffffff")
wartosc_regresji.grid(column=1, row=5, sticky='w')

model = pickle.load(open("model.pkl", 'rb'))


def val_numbers():
    max_metraz = 100000
    max_piętro = 100
    metraz = metraz_entry.get()
    pietro = pietro_entry.get()
    if metraz == "" or not metraz.isdigit() or pietro=="" or not pietro.isdigit():
        messagebox.showinfo(title="Error", message=f"Please provide valid data")
    elif int(metraz) < 0 or int(metraz) > max_metraz or int(pietro) < 0 or int(pietro) > max_piętro:
        messagebox.showinfo(title="Error", message=f"Please provide numbers between 0 to 100 for floors and 0 to 100.000 for metric area.")
    else:
        confirm = messagebox.askyesno(title="Confirm", message="Do you want to start prediction?")
        if confirm == True:
            array = np.array([[int(pietro_entry.get()),float(metraz_entry.get())]])
            scaler = StandardScaler()
            transformed_data = scaler.fit_transform(array)
            prediction = model.predict(transformed_data)
            wartosc_regresji.config(text=f'{round(prediction[0][0], 2)} PLN')
            

start_button = Button(command=val_numbers)
start_button.config(text="Start", background="#000000", foreground="#ffffff")
start_button.grid(column=0, row=4, columnspan=2, sticky="s", pady=20)

window.mainloop()