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+# Linking numbers in random graphs
+
+This repository contains the Python code for computing linking numbers for
+links in random linear embeddings of graphs.
+
+This code was used for [Erica Flapan and Kenji Kozai. Linking number and writhe
+in random linear embeddings of graphs, J. Math. Chem. 54 (2016),
+1117-1133](http://link.springer.com/article/10.1007/s10910-016-0610-2).
+
+## Contents
+
+- [random_triangle_links_parallel.py](random_triangle_links_parallel.py):
+  computes the value of q by taking 1 billion triangle-triangle links randomly
+  embedded in [0,1]x[0,1]x[0,1], and computing the average linking number
+- [random_graphs.py](random_graphs.py):
+  computes the linking number of all links in a random (n,p) graph, with as
+  many samples as desired. The output is given in a list, where the first entry
+  in the list is the number of links with linking number 0, the second entry is
+  the number of links with linking number 1, etc. Parallel computations are
+  distributed so each process computes the same number of samples.
+- [random_graphs2.py](random_graphs2.py):
+  same as above, except the parallel computations are done one at a time, and
+  once one sample is finished, another is begun on the completed process.
+  This is optimized to distribute the load better for larger samples.
+  For small sample sizes, random_graphs.py is better due to the parallelization 
+  overhead.