Basically, I discovered that a call to shortest_distance returns a distance
map where certain node entries are missing (I need 349, I only get 328).
Weird thing is that some of the missing nodes are intermediaries for other
nodes that *are* present in the distance map.
The link contains a MWE, which I tested on an older py2 setup, as well as an
up-to-date Docker container. Results are the same.
Would be very grateful for a solution, because I need to be certain about
results correctness before I can proceed with this (very fast!) library.
This is a numerical precision problem. You have very low edge weights
(1e-6) combined with very large values (1000000), which cause
differences to be lost to finite precision. If you replace all values
1000000 (which I assume mean infinite weight) by numpy.inf, you actually
get a more stable calculation, and no missing nodes in your example.
An even better alternative is to actually remove the "infinite weight"
edges using an edge filter.
Best,
Tiago
Ps. I note you are using Python 2, but current versions of graph-tool
only support Python 3.
One question though. Apart from the edge filter which will make Dijkstra
calculation faster, can I also get around storing lots of Inf values in an
edgepropertymap ? Suppose, I only want to route along highways. Right now, I
would have an edgepropertymap with 98% inf values (all roads lower than
highway), which is wasted memory.