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The second point was always the first plus num_genes // 2, so every child took exactly half of its genes from its second parent. Draw 2 different points in [0, num_genes] instead, every pair equally likely. This also fixes the TypeError with a single gene. Fixes ahmedfgad#370
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Fixes #370.
two_points_crossoverdrew only the first point; the second was always the first plusnum_genes // 2. This draws both points: 2 different values in[0, num_genes], sorted, with every pair equally likely. The genes between them still come from the second parent, as before.It also fixes the single-gene case, where the float
numpy.zeros(...)points raised aTypeErrorwhen slicing: the points are now 0 and 1, so the gene is copied from the second parent, as the old comment intended.Test:
test_two_points_crossover_manual_callintests/test_crossover_mutation.pychecks that the genes from the second parent form one block and that every block length from 1 tonum_genesoccurs. It fails on master and passes with this change.pytest tests(withouttest_kerasga.pyandtest_torchga.py, which need TensorFlow and PyTorch): 872 passed, 1 skipped. The only failure istest_submodule_versions.py::test_changed_submodule_is_version_bumped[utils], sincepygad/utilschanged; I left the version bump to you for the release.