instagram.py

def PredictionsWithConstantFollowers(model, followerCount, scaller, maxVal):
    followers = followerCount * np.ones(24)
    hours = np.arange(1, 25)
    
    # defining vector 
    featureVector = np.zeros((24, 2))
    featureVector[:, 0] = followers
    featureVector [:, 1] = hours
    
    # doing scalling
    featureVector = scaller.transform(featureVector)
    predictions = model.predict(featureVector)
    predictions = (maxValLikes * predictions).astype('int')
    
    plt.figure(figsize= (10, 10))
    plt.plot(hours, predictions)
    plt.style.use('seaborn-whitegrid')
    plt.scatter(hours, predictions, color = 'g')
    plt.grid(True)
    plt.xlabel('hours since posted')
    plt.ylabel('Likes')
    plt.title('Likes progression with ' + str(followerCount) +' followers')
    plt.show()
    
PredictionsWithConstantFollowers(gbr, 100, stdSc, maxValLikes)