examples
Co-authored-by: Sebastian Piotrowski <sebpio@st.amu.edu.pl> Co-authored-by: Ladislaus3III <Ladislaus3III@users.noreply.github.com> Co-authored-by: Marcin Matoga <marmat35@st.amu.edu.pl>
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generate_examples.py
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generate_examples.py
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#author: Kuba Henyk
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import random
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class ExampleGenerator():
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@staticmethod
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def generate():
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list = [[]]
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for i in range(1000):
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while True:
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c = [random.randrange(0, 21), random.randrange(5, 41), random.randrange(1, 61), random.randrange(0, 11), random.randrange(0, 2), random.randrange(0, 2), random.randrange(0, 2), random.randrange(0, 2)]
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if c in list:
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continue
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else:
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break
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list.append(c)
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f = open("dane.txt", "w")
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for i in range(len(list)):
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if i != 0:
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#glebokosc
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if list[i][0] <= 19:
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#rozmiar
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if list[i][1] <= 39:
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#masa
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if list[i][2] <= 58:
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#moc
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if list[i][3] <= 9:
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#szkodliwosc
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if list[i][4] == 1:
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#zabawka
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if list[i][5] == 1:
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#stan
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if list[i][6] == 1:
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#teledysk
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if list[i][7] == 1:
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list[i].append(2)
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else:
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list[i].append(5)
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else:
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list[i].append(4)
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else:
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list[i].append(3)
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else:
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list[i].append(1)
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else:
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list[i].append(1)
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else:
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list[i].append(1)
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else:
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list[i].append(1)
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else:
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list[i].append(1)
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for i in range(len(list)):
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if i == 0:
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continue
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else:
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for j in range(len(list[i])):
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f.write(str(list[i][j]) + ' ')
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f.write("\n")
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f.close()
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20
main.py
20
main.py
@ -2,12 +2,19 @@ import pygame as pg
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import sys
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import ctypes
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from os import path
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from matplotlib import pyplot
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from sklearn import datasets
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from sklearn.tree import DecisionTreeClassifier
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from sklearn import tree
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from maze import *
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from grid import *
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from settings import *
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from sprites import *
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from graphsearch import *
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from astar2 import *
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from generate_examples import *
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class Game:
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@ -115,6 +122,19 @@ class Game:
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self.graph_move(player_moves)
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self.wentyl_bezpieczenstwa = 1
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# Test.run()
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if event.key == pg.K_F5:
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ExampleGenerator.generate()
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if event.key == pg.K_F6:
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X = [[6,15,31,5,0,0,1,0],[6,36,5,8,1,1,1,0],
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[13,40,29,3,0,0,0,0], [15,25,23,7,0,0,1,1],
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[17,34,5,5,1,1,0,1], [3,9,28,8,0,0,1,0],
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[18,38,43,6,1,1,1,1], [3,8,53,4,1,1,1,1],
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[9,40,47,1,1,0,1,1],[11,23,31,5,0,0,1,1]]
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Y = [1,5,1,1,4,1,2,2,1,1]
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clf = tree.DecisionTreeClassifier()
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clf = clf.fit(X,Y)
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tree.plot_tree(clf)
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15
poklad/test.txt
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15
poklad/test.txt
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if głebokość <= 5 [1, 20] - dalej, else oflagować
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rozmiar <= 20 [5, 40] - dalej, else oflagować
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masa <= 30 [1, 60] - dalej, else oflagować
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moc <= 5 kiloton [0, 10] - dalej, else oflagować
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czy jest szkodliwy: nie/tak [0,1] - dalej, else oflagować
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czy jest zabawką : nie/tak [0,1] - dalej, else sprzedać na allegro
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czy jest w dobrym stanie: nie/tak [0,1] - zdetonować, czarny rynek
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czy jest teledyskiem: nie/tak [0,1] - zdetonować, obejrzeć
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głebokość | rozmiar | masa | moc | czy jest szkodliwy | czy jest zabawką | czy jest w dobrym stanie | czy jest teledyskiem
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4 5 10 3kt nie nie tak nie
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^sprzedać na czarnym rynku
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