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The genetic algorithm examples (within the first two notebooks) are amenable to begin structured as a function (or two) which could be held in a separate .py file, which might simplify the workflow somewhat for these sections.
Many of the variables could be turned into function arguments, and the solution generalized such that no code changes are required when switching to two parent arrays under the 2D scenario. This would also allow some checks/try-repeat loops for the instances where np.nan pops up due to division-by-zero.
The text was updated successfully, but these errors were encountered:
The genetic algorithm examples (within the first two notebooks) are amenable to begin structured as a function (or two) which could be held in a separate
.py
file, which might simplify the workflow somewhat for these sections.Many of the variables could be turned into function arguments, and the solution generalized such that no code changes are required when switching to two parent arrays under the 2D scenario. This would also allow some checks/try-repeat loops for the instances where
np.nan
pops up due to division-by-zero.The text was updated successfully, but these errors were encountered: