Thanks Tiago for the reply. Here is a script for generating a random regular
graph as an example:
def generate_rrg(n, k):
g = gt.random_graph(n, deg_sampler = lambda : k, directed = False,
verbose = True, n_iter = 1000)
return g
Since verbose is True, this prints what is happening. Now when I run
generate_rrg(n = 10, k = 11), the following is printed and script never stops:
adding vertices: 1 of 10 (10%)
This is giving me impression that the algorithm is adding one vertex at a time.
Since every time added vertex has degree 11 in this case, the algorithm is not
moving ahead because that will lead to multi/self edges (if my interpretation
is right). The verbose message looks difficult to explain using your
description. Am I missing something obvious?
Thanks and regards,
SS
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‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐
On Friday, September 4, 2020 12:44 PM, Tiago de Paula Peixoto <[email protected]>
wrote:
> Am 28.08.20 um 12:09 schrieb Snehal Shekatkar:
>
> > Hi Tiago,
> > From the documentation of deg_sampler: "This function is called once per
> > vertex, but may be called more times, if the degree sequence cannot be used
> > to build a graph."
> > Now suppose my deg_sampler sometimes returns values greater than N-1, and
> > if I don't want to generate a graph with multi-edges and self-loops, such
> > values will be discarded. But suppose for first few vertices, drawn values
> > were less than N (and hence are accepted) and the next value is greater
> > than N-1. Now will all the values generated so far discarded or only the
> > last value? I feel that discarding only the last value will create a bias
> > if I want to sample degrees from a particular probability distribution.
> > Could you please clarify this?
>
> What the algorithm does is to sample the degrees for all vertices first,
> and check if the final sequence is graphical. If it's not, then a random
> node is selected, and its degree is re-sampled, and the test is done
> again. This is repeated, until the sequence obtained is graphical.
>
> Best,
> Tiago
>
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Tiago de Paula Peixoto [email protected]
>
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