Exercise

# Compute adjacency matrix

Now, you'll get some practice using matrices and sparse matrix multiplication to compute projections! In this exercise, you'll use the matrix multiplication operator `@`

that was introduced in Python 3.5.

You'll continue working with the American Revolution graph. The two partitions of interest here are `'people'`

and `'clubs'`

.

Instructions

**100 XP**

- Get the list of people and list of clubs from the graph
`G`

using the`get_nodes_from_partition()`

function that you defined in the previous chapter. This function accepts two parameters: A graph, and a partition. - Compute the biadjacency matrix using
`nx.bipartite.biadjacency_matrix()`

, setting the`row_order`

parameter to`people_nodes`

and the`column_order`

parameter to`clubs_nodes`

. Remember to also pass in the graph`G`

. - Compute the user-user projection by multiplying (with the
`@`

operator) the biadjacency matrix`bi_matrix`

by its transposition,`bi_matrix.T`

.