There is an arbitrary constant in the formula -- or maybe a redundancy of constants -- in p_dist and theta and w_u.
Each of them have arbitrary scaling. So, as long as p_dist is a constant value times a probability density function you are OK.
If you decrease all the distances by a factor of 10 you can increase the threshold by a factor of 100 and get the same results.
There is actually no randomness in the assignment of edges. The randomness occurs in the placement of the nodes.
Then a threshold is applied to find the edges.
So, following what the docs say will work fine. But you can also have p_dist return values that don't have total probability density equal to 1.
Looks like more comprehensive docs would have helped in this case. I don't know the history but it's likely that the docs follow the
paper's description, while the code (and default) follow a more practical approach. We should open an issue or PR to get the docs
expanded.
Thanks!