Topic: @mahmsakr preparation for PR
Once that
- Contributor name has been added to modified files
- Contributor name is on the license of new files
- Contributor name is been added to the Contributors List
From the console terminal:
# make sure that you are in the correct branch
git checkout combinationsSQL
# update to latest main repo contents
git fetch upstream
# Put your work on top of what develop
git rebase upstream/developOnce you have updated the repo, the following that I forgot to mention on our last meeting must be done:
in
doc/src/release_notes.rstin the corresponding 3.1.0 release notes add.. rubric:: New functions * pgr_dijkstra(combinations)- Commit and push
From the github website:
- make a PR to develop branch
end of topic
I was adding the boost functionality to the function pgr_depthFirstSearch (pgRouting/GSoC-pgRouting#38) I was implementing.
For this I was supposed to use boost::depth_first_search - for directed graphs, and boost::undirected_dfs - for undirected graphs.
In the current implementation, I have used pgrouting::UndirectedGraph(#L117) and called boost::depth_first_search, yet the function gives the correct result, as expected, for the undirected graph. The documentation for boost::depth_first_search says the graph Graph& g should be directed, however in the current implementation, I use undirected graph with it, and it is working alright.
Moreover, in the pgrouting, we have the functions pgr_primDFS and pgr_kruskalDFS, both of which work only for Undirected Graphs, but in the implementation, I see that the function calls the boost::depth_first_search which is supposed to take only Directed Graphs as input.
As the current implementation works good on calling boost::depth_first_search for both directed and undirected graphs, I don't consider the need to use boost::undirected_dfs as everything is working fine.
Anyone has any idea why does the boost::depth_first_search still works for undirected graphs?
https://docs.pgrouting.org/doxy/3.0/classpgrouting_1_1graph_1_1Pgr__base__graph.html
The branch https://github.com/mahmsakr/pgrouting/tree/combinationsSQL is almost ready and to merge the interruptions to that branch the following has to be done:
Dear pgrouting-community,
we are big fans of your work! And are especially using the driving-distance feature of the pgrouting library.
There is one known issue with this function though, that is summarized in the issue #584.
With the help of @vjeranc I was exploring possibilities to fix this.
In this attempt we were having some preliminary results that are summarized in the PDF attached.
We wanted to contact you because so far the best fix for us seemed to be a custom dijkstra-function as we were not managing to fix this using Boost.
Therefore, we wanted to hear your opinion on that. Is this something that could be accepted? Looking forward to discuss with you.
Best,
Elias
@EPajares Hi, starting a discussion:
For simplicity suppose there is a graph G(E,V) where E= {(u,v,cost=10)} AND V={u,v} and a driving distance of 4 departing from
u=======+----------------------------v
then between vertex u & v at the "+" its where the driving distance is reached
From the documentation this are the possible columns
RETURNS SET OF (seq, [start_vid,] node, edge, cost, agg_cost)What would the result be with this graph?
RETURNS SET OF (seq, [start_vid,] node, edge, cost, agg_cost, partial_edge) We would have in the response all current edges + all edges that can only be "partially traversed" in the reality and are currently not in the response. With the additional parameter 'partial_edge' we could mark all edges that can only be "partially traversed". With post-processing we could use the cost, agg_cost and max_cost to extrapolate along the edge. But this also means that we would probably not have a node at the position "+" but would also create this one with post-processing.
https://travis-ci.org/github/rajhim2/GSoC-pgRouting/jobs/694570795#L1878
Your result file contains
SELECT * FROM pgr_kargersContraction(whereas it should be
SELECT * FROM _pgr_kargersContraction(according to your queries.
kruskalBFS function (an already-implemented function).The pgTAP tests are failing for the
kruskalBFS-edge-cases: https://travis-ci.org/github/krashish8/GSoC-pgRouting/jobs/694577924#L1323
This is the result file. The main queries lie in the *.test.sql file - https://github.com/rajhim2/GSoC-pgRouting/blob/him/docqueries/kargersContraction/doc-pgr_kargersContraction.test.sql
In your case, all the three queries are calling the underscored function, so, I guess, if you change it to the main function, then the test will pass.
@EPajares Hi, starting a discussion:
For simplicity suppose there is a graph G(E,V) where E= {(u,v,cost=10)} AND V={u,v} and a driving distance of 4 departing from
u=======+----------------------------v
then between vertex u & v at the "+" its where the driving distance is reached
From the documentation this are the possible columnsRETURNS SET OF (seq, [start_vid,] node, edge, cost, agg_cost)What would the result be with this graph?
@cvvergara
The result also does not need to contain additional columns. The partial edges can have agg_cost=drivingDistance and cost of the edge can stay the same. User would then check the predecessor agg_cost of the node at edge to figure out the partially traveled part.
The result would be (seq, [start_vid,] node, edge, cost, agg_cost) = (1, u, v, 1, 10, 4). Given that predecessor of v using edge 1 is u and agg_cost at u is 0 then it's simple to figure out the partially traveled part.
I'm understand that implicitly marking the partial edges in this way complicates the function unnecessarily but I have not figured out a simpler way without adding an extra column in the result.
cost is reduced to match the partial travel time, then one can find all the partial edges easily. Edges are found by comparing the cost of the input edges with same edge id and the output edges. This is definitely more elegant than finding the predecessors and checking the agg_cost for the predecessor.
tailswith default value FALSE- OR
vertex_endingwith default TRUE
@cvvergara Yeah, the naming can be related to tree leaves, given that the current result is a spanning tree, this would extend the leaves with partial edges that end at a place between vertices of the real edge.
The implementation of the fix can be made in such a way to keep the current results. What worries me the most is the fact that the fix requires a custom dijkstra implementation and does not use any of the datastructures used by all of the graph algorithms in pgrouting codebase. I'm confident that the code is correct and performs well.
@EPajares and I will do exhaustive testing to see that the examples deemed previously incorrect (without partial edges or tails as you call it) are now fully correct.
The reason why the pgr_drivingDistance function is useful is for finding isochrones. In this case all the nodes at which agg_cost is less than the given drivingDistance are not useful.
Maybe that deserves a new function name?
Why are the results incorrect given that definition?
note that we are not finding edges that are within the distance
the results on the edges is a spanning graph, its not a minimum spanning graph, its just a spanning graph.
Give me a counter example, an execution, where the nodes are not within the distance.
Note that: A node on the "tail" is not within the distance because its further away than distance. So this is not what I am asking for.
@cvvergara When one wants to find isochrones, then pgr_drivingDistance obviously gives incomplete results. It gives correct results according to the definition but incomplete for a particular use case. @EPajares had many examples where he wanted to find isochrones but was using the pgr_drivingDistance and getting incomplete results. These are the examples that my fix is going to cover.
Given that the interest is in isochrones and not in nodes that are reached in time <= drivingDistance, I asked if the fix maybe deserves a new function name and probably a different result.