# predict_slide.py

# predict_slide.py # failed

import cmath
import math
import random

waves = 200
test_length = 1000
data_at_zero = [random.randint(0, 256) for _ in range(waves)]
amps = []
while len(amps) < waves:
    rndu = random.uniform(0, 1)
    if rndu not in amps:
        amps += [rndu]
data = []
for i in range(1, test_length + 1):
    data += [abs(int(sum([data_at_zero[j] * math.sin(amps[j] * i) for j in range(waves)]) % 512 - 256))]

print(data, end='\n\n\n')

window_size = 10
AI = {'window': [1] * window_size}

def AI_Predicts():
    global AI
    prediction = int(sum(AI['window']) / len(AI['window']))
    return prediction

i = test_length + 1
while 1:
    prediction = AI_Predicts()
    data = abs(int(sum([data_at_zero[j] * math.sin(amps[j] * i) for j in range(waves)]) % 512 - 256))
    valid = prediction == data
    oops = ''
    if not valid:
        oops = '!' * 20 + ' '
    print(f'{oops}at:{i} sum_of_waves: {prediction} == answer: {data} is {valid}')

    # Update the window with the actual new data point
    AI['window'].pop(0)
    AI['window'].append(data)

    i += 1