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badania-operacyjne's Issues

better city graph

Create the graph of the real city. Remember about representation we agreed on (junctions and stops are vertices, junctions with value 0 and stops with preprocessed value, also stops have degree <= 2).

Or at least make current generated graph meet the aforementioned conditions.

do gridsearch

when #17 and maybe others are done do grid search of the hiperparameters
Hiperparameters to optimize:

  • survival function
  • mutations probabilities
  • sanitizers

Do that for many fitness functions, but do not compare results numerically.

add metrics

add metrics to allow monitoring:

  • number of mutaions (per type)
  • number of crosses (per type)
  • more...

add typing to best_paths

Determine type of best_paths that is used everywhere and type its usages. Ideally use type aliases to not repeat weird nested type in N places.

Fitness function modifies graph

This somehow prints different results:

# calculating fitness for all organisms
population_with_fitness: List[Tuple[Genotype, float]] = [
    (organism, self.fitness_function(organism, self.G))
    for organism in population
]

print(population_with_fitness[0][1])

population_with_fitness: List[Tuple[Genotype, float]] = [
    (organism, self.fitness_function(organism, self.G))
    for organism in population
]

print(population_with_fitness[0][1])

This is related:

G.graph["points"][np.where(lines_stopping_count == 0)] = 0
lines_stopping_count[np.where(lines_stopping_count == 0)] = 1

poprawienie dokumentacji

Merytoryczne

  • Funkcja K(Si) opisać co robi
  • Aplikacja
  • Jak wygenerowalsmy odległości ścieżek (Floyd Warshal)
  • Jak z przystanków są krawedzie wygenerowane

Typing

  • usunąć puste pola
  • Poprawić ortograficzne błędy
  • Źródła i podsumowanie

better survival function

implement some variations of survival function
ideas:

  • add some randomness so bad specimens can get lucky

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