#PREDICT Predict whether the label is 0 or 1 using learned logistic
#regression parameters theta
#   p = PREDICT(theta, X) computes the predictions for X using a
#   threshold at 0.5 (i.e., if sigmoid(theta'*x) >= 0.5, predict 1)

#m = size(X, 1); # Number of training examples

# You need to return the following variables correctly
#p = zeros(m, 1);

# ====================== YOUR CODE HERE ======================
# Instructions: Complete the following code to make predictions using
#               your learned logistic regression parameters.
#               You should set p to a vector of 0's and 1's
#
import numpy as np
from sigmoid import sigmoid

def predict(theta, X):
    m = X.shape[0]
    n = X.shape[1]

    return sigmoid(np.dot(X,theta)) >= 0.5
