import numpy as np

def converge(v,p):
    i = 0
    while (np.max(np.abs(v - np.mean(v))) > 1):
        v = np.matmul(p, v)
        i += 1
    return i

def create_vector(max):
    np.random.seed(0)  # For reproducibility
    vector = np.random.randint(0, 1000, size=(max, 1))  # Random integers
    while np.any(np.abs(np.diff(vector.flatten())) < 100):  # Ensure the difference is at least 100
        vector = np.random.randint(0, 1000, size=(max, 1))
    return vector

v = create_vector(3)
p = np.array([
    [0.500000, 0.250000, 0.250000],
    [0.250000, 0.375000, 0.375000],
    [0.000000, 0.250000, 0.750000]
])

print(converge(v,p))