fastRG

Samples generalized random product graphs, a generalization of a broad class of network models. Given matrices X, S, and Y with with non-negative entries, samples a matrix with expectation XSY^T and independent Poisson or Bernoulli entries using the fastRG algorithm of Rohe et al. (2017) https://www.jmlr.org/papers/v19/17-128.html. The algorithm first samples the number of edges and then puts them down one-by-one. As a result it is O(m) where m is the number of edges, a dramatic improvement over element-wise algorithms that which require O(n^2) operations to sample a random graph, where n is the number of nodes.

Last 30 days

This package has been downloaded 186 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,983 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 31 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.