import numpy as np
from sklearn.linear_model import LogisticRegression
from .models import User
from .twitter import vectorize_tweet


def predict_user(user1_name, user2_name, tweet_text):
    """
    Determine and return which user is more likely to say a given Tweet.
    
    Example: predict_user('ausen', 'elonmusk', 'Lambda School Rocks!')
    Returns 1 corresponding to 1st user passed in, or 0 for second.
    """
    user1 = User.query.filter(User.name == user1_name).one()
    user2 = User.query.filter(User.name == user2_name).one()
    user1_vect = 
np.array([tweet.vect for tweet in user1.tweets])