parent
2e1edf91c4
commit
c7e8b64c2f
167
main.py
167
main.py
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@ -1,6 +1,9 @@
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import pygame
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import random
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import time
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import pandas as pd
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import math
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import matplotlib.pyplot as plt
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kuchnia_xy = 0
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pozycja_startowa = 0
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@ -11,6 +14,7 @@ blockSize = 60
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rows = 14
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columns = 24
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# -----------------------------Inicjacja klas
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class Kelner:
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def __init__(self, x, y):
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@ -61,7 +65,6 @@ class Kelner:
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self.x -= 1
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self.stanPrzestrzeni[0] -= 1
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def wykonajAkcje(self, ruchy):
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if self.indexRuchu < len(ruchy):
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akcja = ruchy[self.indexRuchu]
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@ -85,6 +88,7 @@ class Stolik:
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def wklej(self):
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screen.blit(stolikImg, (self.x * blockSize, self.y * blockSize))
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class Przeszkoda:
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def __init__(self, x, y, typ):
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self.x = x
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@ -104,10 +108,12 @@ class Przeszkoda:
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elif self.typ == "dywan":
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screen.blit(dywanImg, (self.x * blockSize, self.y * blockSize))
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# -----------------Przeszukiwanie przestrzeni stanów
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import heapq
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def a_star(start, cel, stoliki, przeszkody):
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queue = [] # Kolejka priorytetowa
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heapq.heappush(queue, (0, start)) # (koszt, stan)
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@ -163,7 +169,8 @@ def generuj_nastepniki_i_ruchy(stan, stoliki, przeszkody):
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if 0 <= nowy_x < columns and 0 <= nowy_y < rows:
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# sprawdzamy, czy następny stan nie wchodzi w stolik
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if not any(stolik.x == nowy_x and stolik.y == nowy_y for stolik in stoliki):
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koszt = next((przeszkoda.cena for przeszkoda in przeszkody if przeszkoda.x == nowy_x and przeszkoda.y == nowy_y), 1)
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koszt = next(
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(przeszkoda.cena for przeszkoda in przeszkody if przeszkoda.x == nowy_x and przeszkoda.y == nowy_y), 1)
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ruchy.append(((nowy_x, nowy_y, kierunek), 'F', koszt))
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return ruchy
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@ -179,6 +186,78 @@ def odtworz_ruchy(poprzednicy, cel):
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ruchy.reverse()
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return ruchy
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def licz_entropie(data, target_column):
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total_rows = len(data)
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target_values = data[target_column].unique()
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entropy = 0
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for value in target_values:
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value_count = len(data[data[target_column] == value])
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proportion = value_count / total_rows
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entropy -= proportion * math.log2(proportion)
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return entropy
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def licz_zysk(atrybut,korzen,data):
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entropia_wazona = 0
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unique_values = data[atrybut].unique()
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for value in unique_values:
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subset = data[data[atrybut] == value]
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proportion = len(subset) / len(data)
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entropia_wazona += proportion * licz_entropie(subset, data.columns[-1])
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zysk = korzen - entropia_wazona
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return zysk
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def szukaj_split(z, atrybuty):
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max = 0
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max_atr = "None"
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for atrybut in atrybuty:
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if z[atrybut]>max:
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max = z[atrybut]
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max_atr = atrybut
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return max_atr
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def GenerujDane(ques):
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k = [0,0,0,0,0,0,0,0]
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for n in range(8):
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k[n] = random.choice([0,1])
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print(ques[n] + str(k[n]))
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return k
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def id3(data,mode,klient):
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zysk = {}
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korzen = licz_entropie(data,data.columns[-1])
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lista = data.columns
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for atrybut in lista[:-1]:
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zysk[atrybut] = licz_zysk(atrybut,korzen,data)
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split = szukaj_split(zysk, data.head(0).columns[:-1])
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if split == "None":
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wynik = data.iloc[0, -1]
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if wynik == 1 and mode == "klient":
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print("Klient zadowolony!")
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elif wynik == 0 and mode == "klient":
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print("Klient niezadowolony!")
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print("---------------------------------------------------------------------------------------")
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else:
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#print("Split: " + str(split))
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subset0 = data[data[split] == 0]
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subset0 = subset0.drop([split], axis=1)
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subset1 = data[data[split] == 1]
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subset1 = subset1.drop([split], axis=1)
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#print("Klient: " + str(klient))
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if len(subset0) < len(data) and len(subset1) < len(data):
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if mode == "klient":
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if klient[split] == 0:
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frames.append(subset0)
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else:
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frames.append(subset1)
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elif mode == "full":
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frames.append(subset0)
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frames.append(subset1)
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if len(frames) > 0:
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newData = frames.pop()
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id3(newData,mode, klient)
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start = (0, 0, 0) # Początkowy stan
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cel = (0, 0) # Docelowe współrzędne
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@ -211,7 +290,8 @@ else:
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juzbyly = []
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for j in range(1, rows):
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for i in range(columns):
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if (random.randrange(7) == 0) and ((i,j-1) not in juzbyly) and (((i-1,j-1) not in juzbyly) or ((i+1,j-1) not in juzbyly)):
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if (random.randrange(7) == 0) and ((i, j - 1) not in juzbyly) and (
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((i - 1, j - 1) not in juzbyly) or ((i + 1, j - 1) not in juzbyly)):
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stoliki.append(Stolik(i, j))
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juzbyly.append((i, j))
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elif random.randrange(9) == 0:
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@ -219,7 +299,6 @@ else:
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elif random.randrange(12) == 0:
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przeszkody.append(Przeszkoda(i, j, "dywan"))
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# stoliki = []
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# for i in range(rows)
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@ -245,12 +324,15 @@ sliskaPodlogaImg = pygame.transform.scale(sliskaPodlogaImg, (blockSize, blockSiz
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dywanImg = pygame.image.load("dywan.png")
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dywanImg = pygame.transform.scale(dywanImg, (blockSize, blockSize))
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def kuchnia(x, y):
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screen.blit(kitchenImg, (x * blockSize, y * blockSize))
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def menu(x, y):
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screen.blit(menuImg, (x * blockSize, y * blockSize))
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def wypiszOkno():
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screen.fill((0, 0, 0))
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for x in range(0, width, blockSize):
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@ -259,6 +341,27 @@ def wypiszOkno():
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pygame.draw.rect(screen, (200, 200, 200), rect, 1) # -------------Wypisz kratę -TA
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# pygame.draw.rect(screen, (0, 0, 0), rect, 1) #-------------Wypisz kratę -TA
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def czyZadowolony():
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data = pd.read_csv('zbior_uczacy.csv')
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frames = []
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frames.append(data)
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ques = ["Czy klient sie usmiecha? ", "Czy zostawil napiwek? ", "Czy zachowywal sie grzecznie? ",
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"Czy zjadl cala porcje? ", "Czy zlozyl dodatkowe zamowienia? ",
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"Czy wyrazil zainteresowanie karta stalego klienta? ", "Czy zarezerwowal stolik na przyszlosc? ",
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"Czy zabral wizytowke? "]
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k = GenerujDane(ques)
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atrybuty = []
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for column in data.columns[:-1]:
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atrybuty.append(column)
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klient = {}
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i = 0
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for atr in atrybuty:
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klient[atr] = k[i]
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i = i + 1
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while len(frames) > 0:
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data = frames.pop()
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id3(data, "klient", klient)
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run = True
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# czcionka = pygame.font.SysFont('Arial',50)
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@ -267,6 +370,44 @@ licznik = 0
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ruchy = []
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cel2 = []
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klient = {}
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frames = []
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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from sklearn.model_selection import train_test_split
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from sklearn.tree import plot_tree, DecisionTreeClassifier
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data = pd.read_csv('zbior_uczacy.csv')
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data.head()
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#print(heart_data)
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data_x = data.drop('Zadowolony', axis=1)
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data_y = data['Zadowolony']
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data_x_encoded = pd.get_dummies(data_x, drop_first = True)
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data_x_encoded.head()
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best_acc = 0
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from sklearn.tree import DecisionTreeClassifier
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from sklearn.metrics import accuracy_score
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X_train, X_test, y_train, y_test = train_test_split(data_x_encoded, data_y, test_size=0.3)
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dtree = DecisionTreeClassifier(max_depth=100)
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dtree.fit(X_train, y_train)
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fig = plt.figure(figsize=((25,20)))
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plot_tree(dtree,
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feature_names=data_x_encoded.columns,
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class_names=['niezadowolony', 'zadowolony'],
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impurity=False,
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proportion=False,
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filled=True)
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fig.savefig('tree.png')
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while run:
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cel2 = list(cel)
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@ -298,12 +439,13 @@ while run:
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print("Szukam ścieżki do stolika...")
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ruchy = a_star(tuple(kelner.stanPrzestrzeni), cel, stoliki, przeszkody)
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kelner.stan = "odbiera"
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if ruchy:
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print("Znaleziono ścieżkę ruchów: ", ruchy)
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czyZadowolony()
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else:
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print("Nie znaleziono ścieżki do celu.")
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# ----------Losuje stoliki, które dokonają zamówienia
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if kelner.stan == "stoi":
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for stolik in stoliki:
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@ -317,10 +459,10 @@ while run:
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# print(f"{kelner.x} {kelner.y}")-------------Wypisuje wspolrzedne kelnera
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# ----------------Zmiana pozycji kelnera
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if kelner.chodzi == True and licznik % (101 - kelner.speed) == 0 and kelner.stanPrzestrzeni[:2] != cel2: #ograniczenie prędkości
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if kelner.chodzi == True and licznik % (101 - kelner.speed) == 0 and kelner.stanPrzestrzeni[
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:2] != cel2: # ograniczenie prędkości
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kelner.wykonajAkcje(ruchy)
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if kelner.stanPrzestrzeni[:2] == cel2:
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if kelner.stan == "odbiera" and kelner.x == kelner.stolik_docelowy.x and kelner.y == kelner.stolik_docelowy.y - 1:
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kelner.stolik_docelowy.zamowione = False
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@ -335,7 +477,6 @@ while run:
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elif kelner.stan == "wraca" and kelner.x == kuchnia_xy and kelner.y == kuchnia_xy:
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kelner.stan = "stoi"
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time.sleep(0.001)
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key = pygame.key.get_pressed()
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@ -343,4 +484,14 @@ while run:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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run = False
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#------------------------------------------------------------------------------------------------------------------
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'''
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frames.clear()
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frames.append(data)
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while len(frames) > 0:
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data = frames.pop()
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id3(data,"full")
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'''
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pygame.quit()
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@ -0,0 +1,257 @@
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Usmiech,Napiwek,Grzeczny,Zjadl,DodZam,Karta,Rezerwacja,Wizytowka,Zadowolony
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0,0,0,0,0,0,0,0,0
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0,0,0,0,0,0,0,1,0
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0,0,0,0,0,0,1,0,0
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0,0,0,0,0,0,1,1,0
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0,0,0,0,0,1,0,0,0
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0,0,0,0,0,1,0,1,0
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0,0,0,0,0,1,1,0,0
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0,0,0,0,0,1,1,1,0
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0,0,0,0,1,0,0,0,0
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0,0,0,0,1,0,0,1,0
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0,0,0,0,1,0,1,0,0
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0,0,0,0,1,0,1,1,0
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0,0,0,0,1,1,0,0,0
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0,0,0,0,1,1,0,1,0
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0,0,0,0,1,1,1,0,0
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0,0,0,0,1,1,1,1,0
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0,0,0,1,0,0,0,0,0
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0,0,0,1,0,0,0,1,0
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0,0,0,1,0,0,1,0,0
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0,0,0,1,0,0,1,1,0
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0,0,0,1,0,1,0,0,0
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0,0,0,1,0,1,0,1,0
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0,0,0,1,0,1,1,0,0
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0,0,0,1,0,1,1,1,1
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0,0,0,1,1,0,0,0,0
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0,0,0,1,1,0,0,1,0
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0,0,0,1,1,0,1,0,0
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0,0,0,1,1,0,1,1,1
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0,0,0,1,1,1,0,0,0
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0,0,0,1,1,1,0,1,1
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0,0,0,1,1,1,1,0,1
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0,0,0,1,1,1,1,1,1
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||||
0,0,1,0,0,0,0,0,0
|
||||
0,0,1,0,0,0,0,1,0
|
||||
0,0,1,0,0,0,1,0,0
|
||||
0,0,1,0,0,0,1,1,0
|
||||
0,0,1,0,0,1,0,0,0
|
||||
0,0,1,0,0,1,0,1,0
|
||||
0,0,1,0,0,1,1,0,0
|
||||
0,0,1,0,0,1,1,1,1
|
||||
0,0,1,0,1,0,0,0,0
|
||||
0,0,1,0,1,0,0,1,1
|
||||
0,0,1,0,1,0,1,0,1
|
||||
0,0,1,0,1,0,1,1,1
|
||||
0,0,1,0,1,1,0,0,0
|
||||
0,0,1,0,1,1,0,1,1
|
||||
0,0,1,0,1,1,1,0,1
|
||||
0,0,1,0,1,1,1,1,1
|
||||
0,0,1,1,0,0,0,0,1
|
||||
0,0,1,1,0,0,0,1,1
|
||||
0,0,1,1,0,0,1,0,1
|
||||
0,0,1,1,0,0,1,1,1
|
||||
0,0,1,1,0,1,0,0,1
|
||||
0,0,1,1,0,1,0,1,1
|
||||
0,0,1,1,0,1,1,0,1
|
||||
0,0,1,1,0,1,1,1,1
|
||||
0,0,1,1,1,0,0,0,1
|
||||
0,0,1,1,1,0,0,1,1
|
||||
0,0,1,1,1,0,1,0,1
|
||||
0,0,1,1,1,0,1,1,1
|
||||
0,0,1,1,1,1,0,0,1
|
||||
0,0,1,1,1,1,0,1,1
|
||||
0,0,1,1,1,1,1,0,1
|
||||
0,0,1,1,1,1,1,1,1
|
||||
0,1,0,0,0,0,0,0,0
|
||||
0,1,0,0,0,0,0,1,1
|
||||
0,1,0,0,0,0,1,0,1
|
||||
0,1,0,0,0,0,1,1,1
|
||||
0,1,0,0,0,1,0,0,1
|
||||
0,1,0,0,0,1,0,1,1
|
||||
0,1,0,0,0,1,1,0,1
|
||||
0,1,0,0,0,1,1,1,1
|
||||
0,1,0,0,1,0,0,0,1
|
||||
0,1,0,0,1,0,0,1,1
|
||||
0,1,0,0,1,0,1,0,1
|
||||
0,1,0,0,1,0,1,1,1
|
||||
0,1,0,0,1,1,0,0,1
|
||||
0,1,0,0,1,1,0,1,1
|
||||
0,1,0,0,1,1,1,0,1
|
||||
0,1,0,0,1,1,1,1,1
|
||||
0,1,0,1,0,0,0,0,1
|
||||
0,1,0,1,0,0,0,1,1
|
||||
0,1,0,1,0,0,1,0,1
|
||||
0,1,0,1,0,0,1,1,1
|
||||
0,1,0,1,0,1,0,0,1
|
||||
0,1,0,1,0,1,0,1,1
|
||||
0,1,0,1,0,1,1,0,1
|
||||
0,1,0,1,0,1,1,1,1
|
||||
0,1,0,1,1,0,0,0,1
|
||||
0,1,0,1,1,0,0,1,1
|
||||
0,1,0,1,1,0,1,0,1
|
||||
0,1,0,1,1,0,1,1,1
|
||||
0,1,0,1,1,1,0,0,1
|
||||
0,1,0,1,1,1,0,1,1
|
||||
0,1,0,1,1,1,1,0,1
|
||||
0,1,0,1,1,1,1,1,1
|
||||
0,1,1,0,0,0,0,0,1
|
||||
0,1,1,0,0,0,0,1,1
|
||||
0,1,1,0,0,0,1,0,1
|
||||
0,1,1,0,0,0,1,1,1
|
||||
0,1,1,0,0,1,0,0,1
|
||||
0,1,1,0,0,1,0,1,1
|
||||
0,1,1,0,0,1,1,0,1
|
||||
0,1,1,0,0,1,1,1,1
|
||||
0,1,1,0,1,0,0,0,1
|
||||
0,1,1,0,1,0,0,1,1
|
||||
0,1,1,0,1,0,1,0,1
|
||||
0,1,1,0,1,0,1,1,1
|
||||
0,1,1,0,1,1,0,0,1
|
||||
0,1,1,0,1,1,0,1,1
|
||||
0,1,1,0,1,1,1,0,1
|
||||
0,1,1,0,1,1,1,1,1
|
||||
0,1,1,1,0,0,0,0,1
|
||||
0,1,1,1,0,0,0,1,1
|
||||
0,1,1,1,0,0,1,0,1
|
||||
0,1,1,1,0,0,1,1,1
|
||||
0,1,1,1,0,1,0,0,1
|
||||
0,1,1,1,0,1,0,1,1
|
||||
0,1,1,1,0,1,1,0,1
|
||||
0,1,1,1,0,1,1,1,1
|
||||
0,1,1,1,1,0,0,0,1
|
||||
0,1,1,1,1,0,0,1,1
|
||||
0,1,1,1,1,0,1,0,1
|
||||
0,1,1,1,1,0,1,1,1
|
||||
0,1,1,1,1,1,0,0,1
|
||||
0,1,1,1,1,1,0,1,1
|
||||
0,1,1,1,1,1,1,0,1
|
||||
0,1,1,1,1,1,1,1,1
|
||||
1,0,0,0,0,0,0,0,0
|
||||
1,0,0,0,0,0,0,1,0
|
||||
1,0,0,0,0,0,1,0,0
|
||||
1,0,0,0,0,0,1,1,1
|
||||
1,0,0,0,0,1,0,0,0
|
||||
1,0,0,0,0,1,0,1,1
|
||||
1,0,0,0,0,1,1,0,1
|
||||
1,0,0,0,0,1,1,1,1
|
||||
1,0,0,0,1,0,0,0,0
|
||||
1,0,0,0,1,0,0,1,1
|
||||
1,0,0,0,1,0,1,0,1
|
||||
1,0,0,0,1,0,1,1,1
|
||||
1,0,0,0,1,1,0,0,1
|
||||
1,0,0,0,1,1,0,1,1
|
||||
1,0,0,0,1,1,1,0,1
|
||||
1,0,0,0,1,1,1,1,1
|
||||
1,0,0,1,0,0,0,0,0
|
||||
1,0,0,1,0,0,0,1,1
|
||||
1,0,0,1,0,0,1,0,1
|
||||
1,0,0,1,0,0,1,1,1
|
||||
1,0,0,1,0,1,0,0,1
|
||||
1,0,0,1,0,1,0,1,1
|
||||
1,0,0,1,0,1,1,0,1
|
||||
1,0,0,1,0,1,1,1,1
|
||||
1,0,0,1,1,0,0,0,1
|
||||
1,0,0,1,1,0,0,1,1
|
||||
1,0,0,1,1,0,1,0,1
|
||||
1,0,0,1,1,0,1,1,1
|
||||
1,0,0,1,1,1,0,0,1
|
||||
1,0,0,1,1,1,0,1,1
|
||||
1,0,0,1,1,1,1,0,1
|
||||
1,0,0,1,1,1,1,1,1
|
||||
1,0,1,0,0,0,0,0,1
|
||||
1,0,1,0,0,0,0,1,1
|
||||
1,0,1,0,0,0,1,0,1
|
||||
1,0,1,0,0,0,1,1,1
|
||||
1,0,1,0,0,1,0,0,1
|
||||
1,0,1,0,0,1,0,1,1
|
||||
1,0,1,0,0,1,1,0,1
|
||||
1,0,1,0,0,1,1,1,1
|
||||
1,0,1,0,1,0,0,0,1
|
||||
1,0,1,0,1,0,0,1,1
|
||||
1,0,1,0,1,0,1,0,1
|
||||
1,0,1,0,1,0,1,1,1
|
||||
1,0,1,0,1,1,0,0,1
|
||||
1,0,1,0,1,1,0,1,1
|
||||
1,0,1,0,1,1,1,0,1
|
||||
1,0,1,0,1,1,1,1,1
|
||||
1,0,1,1,0,0,0,0,1
|
||||
1,0,1,1,0,0,0,1,1
|
||||
1,0,1,1,0,0,1,0,1
|
||||
1,0,1,1,0,0,1,1,1
|
||||
1,0,1,1,0,1,0,0,1
|
||||
1,0,1,1,0,1,0,1,1
|
||||
1,0,1,1,0,1,1,0,1
|
||||
1,0,1,1,0,1,1,1,1
|
||||
1,0,1,1,1,0,0,0,1
|
||||
1,0,1,1,1,0,0,1,1
|
||||
1,0,1,1,1,0,1,0,1
|
||||
1,0,1,1,1,0,1,1,1
|
||||
1,0,1,1,1,1,0,0,1
|
||||
1,0,1,1,1,1,0,1,1
|
||||
1,0,1,1,1,1,1,0,1
|
||||
1,0,1,1,1,1,1,1,1
|
||||
1,1,0,0,0,0,0,0,1
|
||||
1,1,0,0,0,0,0,1,1
|
||||
1,1,0,0,0,0,1,0,1
|
||||
1,1,0,0,0,0,1,1,1
|
||||
1,1,0,0,0,1,0,0,1
|
||||
1,1,0,0,0,1,0,1,1
|
||||
1,1,0,0,0,1,1,0,1
|
||||
1,1,0,0,0,1,1,1,1
|
||||
1,1,0,0,1,0,0,0,1
|
||||
1,1,0,0,1,0,0,1,1
|
||||
1,1,0,0,1,0,1,0,1
|
||||
1,1,0,0,1,0,1,1,1
|
||||
1,1,0,0,1,1,0,0,1
|
||||
1,1,0,0,1,1,0,1,1
|
||||
1,1,0,0,1,1,1,0,1
|
||||
1,1,0,0,1,1,1,1,1
|
||||
1,1,0,1,0,0,0,0,1
|
||||
1,1,0,1,0,0,0,1,1
|
||||
1,1,0,1,0,0,1,0,1
|
||||
1,1,0,1,0,0,1,1,1
|
||||
1,1,0,1,0,1,0,0,1
|
||||
1,1,0,1,0,1,0,1,1
|
||||
1,1,0,1,0,1,1,0,1
|
||||
1,1,0,1,0,1,1,1,1
|
||||
1,1,0,1,1,0,0,0,1
|
||||
1,1,0,1,1,0,0,1,1
|
||||
1,1,0,1,1,0,1,0,1
|
||||
1,1,0,1,1,0,1,1,1
|
||||
1,1,0,1,1,1,0,0,1
|
||||
1,1,0,1,1,1,0,1,1
|
||||
1,1,0,1,1,1,1,0,1
|
||||
1,1,0,1,1,1,1,1,1
|
||||
1,1,1,0,0,0,0,0,1
|
||||
1,1,1,0,0,0,0,1,1
|
||||
1,1,1,0,0,0,1,0,1
|
||||
1,1,1,0,0,0,1,1,1
|
||||
1,1,1,0,0,1,0,0,1
|
||||
1,1,1,0,0,1,0,1,1
|
||||
1,1,1,0,0,1,1,0,1
|
||||
1,1,1,0,0,1,1,1,1
|
||||
1,1,1,0,1,0,0,0,1
|
||||
1,1,1,0,1,0,0,1,1
|
||||
1,1,1,0,1,0,1,0,1
|
||||
1,1,1,0,1,0,1,1,1
|
||||
1,1,1,0,1,1,0,0,1
|
||||
1,1,1,0,1,1,0,1,1
|
||||
1,1,1,0,1,1,1,0,1
|
||||
1,1,1,0,1,1,1,1,1
|
||||
1,1,1,1,0,0,0,0,1
|
||||
1,1,1,1,0,0,0,1,1
|
||||
1,1,1,1,0,0,1,0,1
|
||||
1,1,1,1,0,0,1,1,1
|
||||
1,1,1,1,0,1,0,0,1
|
||||
1,1,1,1,0,1,0,1,1
|
||||
1,1,1,1,0,1,1,0,1
|
||||
1,1,1,1,0,1,1,1,1
|
||||
1,1,1,1,1,0,0,0,1
|
||||
1,1,1,1,1,0,0,1,1
|
||||
1,1,1,1,1,0,1,0,1
|
||||
1,1,1,1,1,0,1,1,1
|
||||
1,1,1,1,1,1,0,0,1
|
||||
1,1,1,1,1,1,0,1,1
|
||||
1,1,1,1,1,1,1,0,1
|
||||
1,1,1,1,1,1,1,1,1
|
||||
|
Loading…
Reference in New Issue