Using the program JULIA:

**Make a **function in your file with the signature : function partition data(data, centroids). Assume that the input variable data is a collection of vectors that we wish to cluster, and that centroids is a collection of vectors that represent our current guesses for the centroid of each cluster. For each vector data[i] in data, your function should find the nearest centroid to said vector. Your function should return a Julia vector of length length(data) that contains the new cluster index assigned to each input data vector. For example, if the closest centroid to the vector data[i] is centroid[j], then the ith entry in the vector you return should be j.