# tk_pattern_function_indexify2.py

# tk_pattern_function_indexify2.py

import tkinter as tk

def neural_network(pattern, index):
    # define the neural network function
    def fn(x):
        # use the weighing nodes to determine the value at the given index
        output = 0
        for i, p in enumerate(pattern):
            output += ord(p) * (x**i)
        return output

    return fn


def train():
    # run the neural network in a loop until the result matches the expected result
    global go
    go = True

    # retrieve the user-entered values from the entry widgets
    pattern = pattern_entry.get()
    index = int(index_entry.get())
    expected_result = expected_result_entry.get()

    # find the pattern string by training the neural network
    fn = neural_network(pattern, index)
    result = fn(index)
    while go and (result != expected_result):
        # adjust the weights of the nodes
        for i, p in enumerate(pattern):
            pattern[i] = chr(max(0, ord(p)))
        fn = neural_network(pattern, index)
        result = fn(index)

    if not go:
        print("Cancel Was Pressed\n")

    # create the fn_code template string
    fn_code = "def fn(x):\n"
    for i, p in enumerate(pattern):
        fn_code += f"    output += {ord(p)} * (x**{i})\n"
    fn_code += "    return output"

    # print the fn_code template string and the fn function
    print(fn_code)
    print(fn)

def stop_neural_network():
    # stop the neural network loop
    global go
    go = False

# create the Tkinter GUI
root = tk.Tk()
root.title("tk_pattern_function_indexify")

# create the entry widgets for the pattern, index, and expected result
pattern_label = tk.Label(root, text="Enter The Incomplete Pattern:")
pattern_entry = tk.Entry(root, width=200)
index_label = tk.Label(root, text="Enter A Test Index:")
index_entry = tk.Entry(root, width=200)
expected_result_label = tk.Label(root, text="Enter An Expected Result By The Test Index:")
expected_result_entry = tk.Entry(root, width=200)

# create the train and stop buttons
train_button = tk.Button(root, text="Train", command=train)
stop_button = tk.Button(root, text="Cancel", command=stop_neural_network)

# pack the entry widgets and buttons into the GUI
pattern_label.pack()
pattern_entry.pack()
index_label.pack()
index_entry.pack()
expected_result_label.pack()
expected_result_entry.pack()
train_button.pack()
stop_button.pack()

# run the Tkinter event loop
root.mainloop()