Fix custom weight attribute for Mehlhorn #6681
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Using a custom weight attribute in the Mehlhorn implementation gave a KeyError. Reason: Edges in G_1_prime are given "weight" attributes, but upon updating, the weight (=/= "weight") of the existing edge in G_1_prime is get. Fix: set and get only "weight" attributes for G_1_prime.
MridulS
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May 3, 2023
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Thanks @kalkoen! Could you also add a test for this in the tests file https://github.com/networkx/networkx/blob/main/networkx/algorithms/approximation/tests/test_steinertree.py?
rossbar
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Mar 8, 2024
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I took the liberty of pushing up a couple tests for cases where the edge attribute name is something other than the default "weight". The first test covers the bugfix (i.e. fails on current main) - the second covers a similar scenario, but with multigraphs.
This LGTM but should get another pair of eyes. Thanks @kalkoen !
cvanelteren
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Apr 22, 2024
* Fix custom weight attribute for Mehlhorn Using a custom weight attribute in the Mehlhorn implementation gave a KeyError. Reason: Edges in G_1_prime are given "weight" attributes, but upon updating, the weight (=/= "weight") of the existing edge in G_1_prime is get. Fix: set and get only "weight" attributes for G_1_prime. * Add test for non-default edge attr weight. * TST: parametrize on steiner method. * Add test for multigraph with non-default edge attr. --------- Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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Using a custom weight attribute in the Mehlhorn implementation gave a KeyError. Reason: Edges in G_1_prime are given "weight" attributes, but upon updating, the weight (=/= "weight") of the existing edge in G_1_prime is get. Fix: set and get only "weight" attributes for G_1_prime.