findClosestCentroids  <- function(X, centroids) {
  
  #   Computes the centroid memberships for every example
  # 
  #   idx <- findClosestCentroids(X, centroids) returns the closest centroids
  #   in idx for a dataset X where each row is a single example. idx = m x 1
  #   vector of centroid assignments (i.e. each entry in range [1..K])
  #
  
  # Set K
  K <- nrow(centroids)
  
  # You need to return the following variables correctly.
  idx <- rep(0, dim(X)[1])
  
  # ======================== YOUR CODE HERE ======================== 
  # Instructions: Go over every example, find its closest centroid, and store
  #               the index inside idx at the appropriate location.
  #               Concretely, idx[i] should contain the index of the centroid
  #               closest to example i. Hence, it should be a value in the
  #               range 1..K
  #
  # Note: You can use a for-loop over the examples to compute this.
  # Hint: To compute || u - v ||, use sqrt(sum((u-v)^2))
  #
  

  # ==============================================================
  return(idx)
}