2020-05-11 15:58:47 +02:00
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# Podprojekt Szi
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### Opis
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Tematem podprojektu jest rozpoznawanie posiłków.
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Użyty jest algorytm genetyczny.
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### Dane
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Posiłki, ich nazwa oraz rodzaj.
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2020-05-11 16:14:53 +02:00
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2020-05-11 15:58:47 +02:00
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menu = Context.fromstring(''' |meat|salad|meal|drink|cold|hot |
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Pork | X | | X | | | X |
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Espresso | | | | X | | X |
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Green Tea | | | | X | X | |
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Greek Salad| | X | X | | X | |
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Pizza | | | X | | | X |''')
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Za pomocy graphviz możemy narysować grafy z poniższego kodu:
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2020-05-11 16:14:53 +02:00
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2020-05-11 15:58:47 +02:00
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digraph Lattice {
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node [label="" shape=circle style=filled width=.25]
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edge [dir=none labeldistance=1.5 minlen=2]
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c0
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c1
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c1 -> c1 [color=transparent headlabel=Pork labelangle=270]
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c1 -> c1 [color=transparent labelangle=90 taillabel=meat]
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c1 -> c0
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c2
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c2 -> c2 [color=transparent headlabel="Green Tea" labelangle=270]
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c2 -> c2 [color=transparent labelangle=90 taillabel=cold]
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c2 -> c0
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c3
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c3 -> c3 [color=transparent headlabel="Greek Salad" labelangle=270]
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c3 -> c3 [color=transparent labelangle=90 taillabel=salad]
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c3 -> c0
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c4
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c4 -> c4 [color=transparent headlabel=Espresso labelangle=270]
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c4 -> c4 [color=transparent labelangle=90 taillabel=drink]
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c4 -> c2
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c5
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c5 -> c1
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c5 -> c3
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c5 -> c4
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}
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Dane testowe:
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func_input = ['meal']
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2020-05-11 16:13:58 +02:00
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2020-05-11 15:58:47 +02:00
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Dane wyjściowe:
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2020-05-11 16:13:58 +02:00
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2020-05-11 15:58:47 +02:00
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['Pork', 'Greek Salad', 'Pizza']
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2020-05-11 16:13:58 +02:00
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2020-05-11 15:58:47 +02:00
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### Implementacja
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Główna część:
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2020-05-11 16:14:53 +02:00
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2020-05-11 15:58:47 +02:00
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gen_num = 20 #generations
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gen_sol = 6 #solutions
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gen_par_mating = 2 #how many solutions we select
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mut_per_gen = 10
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mut_num_gen = None
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crossover = "two_points"
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muta_type = "scramble"
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par_keep = 1 #keep only one parent
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init_range_l = -2 #low
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init_range_h = -5 #high
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...
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### Biblioteki
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* concepts
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* pygad (algorytm genetyczny)
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* random
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* numpy
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