1
0
forked from s444399/AI

porządkowanie funkcji zmiany nazw metod

This commit is contained in:
tomasz 2020-05-19 13:59:22 +02:00
parent e184f519eb
commit 7635791b1b
36 changed files with 342 additions and 286 deletions

View File

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@ -16,7 +16,6 @@ class Data:
self.doWykresu = []
def genMap(self, mapa):
tmpMap =[]
tmpMap = mapa.copy()
for regal in self.zajeteRegaly:
tmpMap[regal[0]][regal[1]] = 2

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@ -1,35 +1,10 @@
from genetyczny.funkcje import *
from unboxOnTheFloor import UnboxOnTheFloor
from box import Box
from AStar import AStar
import random
from easygui import *
from genetyczny.Data import Data
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
def start(data, wheel):
ileGeneracji = 500
ileWPopulacji = 16
fragment = 0.5
mutacja = 0.05
unbox = 1
data.kordyWozka = (wheel.ns, wheel.we)
data.jakLiczycKoszt = unbox
randomPopulation = genRandomPopulation(data, ileWPopulacji)
for i in range(ileGeneracji):
if i == 0:
best2 = dwieNajlepsze(randomPopulation, data)
else:
x = genPopulacje(data,best2[0], best2[1], ileWPopulacji, fragment, mutacja)
best2 = dwieNajlepsze(x, data)
del x
data.histZmian.append(data.best[1])
rysujWykres(data, ileGeneracji, 0, 2000)
@ -105,6 +80,7 @@ def zbierzBox(gen,data, moves, kordStartowy):
continue
break
def rysujWykres(data, x, yStart, yEnd):
plt.axis([0, x,yStart, yEnd])
@ -118,6 +94,108 @@ def rysujWykres(data, x, yStart, yEnd):
plt.show()
def znajdzUnbox(data,mapa):
unboxy = []
iterator = 0
ostatniWiersz = len(mapa) -1
for x in mapa[ostatniWiersz]:
if (isinstance(x, UnboxOnTheFloor)):
unboxy.append((ostatniWiersz, iterator))
iterator += 1
data.unbox = unboxy
def policzCost(mapaBoxy, poczatek, koniec):
astar = AStar()
koszt = astar.search(poczatek, koniec, mapaBoxy, 1, 0)
return koszt
def wybierzUnbox(gen, jakLiczycKoszt): #funkcja ustawiajaca jaki unbox
if(jakLiczycKoszt == 0):
x = random.choice([gen.unbox1, gen.unbox2])
if(x == gen.unbox1):
y = 0
else:
y= 1
return (x,y)
elif(jakLiczycKoszt == 1):
return (gen.unbox1,0)
elif(jakLiczycKoszt == 2):
return (gen.unbox2,1)
elif(jakLiczycKoszt == 3):
x = min(gen.unbox1,gen.unbox2)
if(x == gen.unbox1):
y = 0
else:
y = 1
return (x,y)
def randomBox(mapa, regals, ile):
regals = regals
mapa = mapa
tupleList = []
ileRegalow = len(regals)
iteration = 0
while iteration < ileRegalow and iteration < ile:
regal = random.choice(regals)
if regal in tupleList:
continue
else:
tupleList.append(regal)
iteration+=1
for (i,j,x) in tupleList:
box = Box()
mapa[i][j].put(box)
"""
for t in tupleList:
listaRegalow.append((t[0],t[1]))
data.zajeteRegaly = listaRegalow
"""
return mapa
def znajdzBox(mapa, regals):
zajeteRegaly = []
for (x,y,z) in regals:
shelf = mapa[x][y]
tmp = shelf.occupied
if(tmp == True):
zajeteRegaly.append((x,y))
return zajeteRegaly
#wybiera z populacji dwa najlepsze chromosomy
def updateMap(data, map, mapForAstar, regals):
data.mapa = map
znajdzUnbox(data, map)
data.zajeteRegaly = znajdzBox(map, regals)
data.astarMap = data.genMap(mapForAstar)
def mutate(wspMutacji, chrom): #w zaleznosci od tego jak wiele mutwac wybierz pary i zamien miejscami
ileWChrom = len(chrom)
ileZmian = round(ileWChrom * wspMutacji)
for i in range(ileZmian):
pom = None
pierw = random.randint(0,ileWChrom - 1)
drug = random.randint(0,ileWChrom - 1)
pom = chrom[pierw]
chrom[pierw] = chrom[drug]
chrom[drug] = pom
return chrom
def okno():
good = True
fieldValues = multenterbox("Wprowadź warunki początkowe", "Start algorytmu genetycznego", ["Ile chrom. w generacji", "Wielkosc dziedziczonego fragmentu (x>0 and x<1)", "Wartosc mutacji (x>0 and x<1)", "Unbox: (0or 1 or 2 or 2)", "Ile generacji"])
@ -153,7 +231,4 @@ def okno():
msgbox("Wartość nie jest liczbą", "Błąd")
good = False
if(good == True):
return [fieldValues[0], fieldValues[1], fieldValues[2],fieldValues[3]]
return [fieldValues[0], fieldValues[1], fieldValues[2],fieldValues[3]]

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@ -1,10 +1,31 @@
from Mapa.unboxOnTheFloor import UnboxOnTheFloor
from genetyczny.Gene import Gene
from Mapa.box import Box
from AStar import AStar
import random
import numpy
from funkcje import *
from Gene import Gene
def start(data, wheel):
ileGeneracji = 20
ileWPopulacji = 16
fragment = 0.5
mutacja = 0.05
unbox = 3
data.kordyWozka = (wheel.ns, wheel.we)
data.jakLiczycKoszt = unbox
randomPopulation = genRandomPopulation(data, ileWPopulacji)
for i in range(ileGeneracji):
if i == 0:
best2 = dwieNajlepsze(randomPopulation, data)
else:
x = genPopulacje(data,best2[0], best2[1], ileWPopulacji, fragment, mutacja)
best2 = dwieNajlepsze(x, data)
del x
data.histZmian.append(data.best[1])
rysujWykres(data, ileGeneracji, 0, 2000)
@ -21,23 +42,7 @@ def generateGeny(data):
geny.append(g)
return geny
def znajdzUnbox(data,mapa):
unboxy = []
iterator = 0
ostatniWiersz = len(mapa) -1
for x in mapa[ostatniWiersz]:
if (isinstance(x, UnboxOnTheFloor)):
unboxy.append((ostatniWiersz, iterator))
iterator += 1
data.unbox = unboxy
def policzCost(mapaBoxy, poczatek, koniec):
astar = AStar()
koszt = astar.search(poczatek, koniec, mapaBoxy, 1, 0)
return koszt
def genRandomChromosome(data):
chromosome = generateGeny(data)
@ -82,63 +87,7 @@ def fitness(chromosome, data):
return koszt
def wybierzUnbox(gen, jakLiczycKoszt): #funkcja ustawiajaca jaki unbox
if(jakLiczycKoszt == 0):
x = random.choice([gen.unbox1, gen.unbox2])
if(x == gen.unbox1):
y = 0
else:
y= 1
return (x,y)
elif(jakLiczycKoszt == 1):
return (gen.unbox1,0)
elif(jakLiczycKoszt == 2):
return (gen.unbox2,1)
elif(jakLiczycKoszt == 3):
x = min(gen.unbox1,gen.unbox2)
if(x == gen.unbox1):
y = 0
else:
y = 1
return (x,y)
def randomBox(mapa, regals, ile):
regals = regals
mapa = mapa
tupleList = []
ileRegalow = len(regals)
iteration = 0
while iteration < ileRegalow and iteration < ile:
regal = random.choice(regals)
if regal in tupleList:
continue
else:
tupleList.append(regal)
iteration+=1
for (i,j,x) in tupleList:
box = Box()
mapa[i][j].put(box)
"""
for t in tupleList:
listaRegalow.append((t[0],t[1]))
data.zajeteRegaly = listaRegalow
"""
return mapa
def znajdzBox(mapa, regals):
zajeteRegaly = []
for (x,y,z) in regals:
shelf = mapa[x][y]
tmp = shelf.occupied
if(tmp == True):
zajeteRegaly.append((x,y))
return zajeteRegaly
#wybiera z populacji dwa najlepsze chromosomy
def dwieNajlepsze(populacja, data):
tmpPopulacja = populacja[:]
chromFitness = []
@ -167,18 +116,6 @@ def dwieNajlepsze(populacja, data):
return (pierwsza, druga)
def genPopulacje(data,pierwszy, drugi, ileWPopulacji, fragmentLiczba, wspMutacji):
ileWChrom = len(pierwszy)
fragment = round(fragmentLiczba*ileWChrom)
if(fragment == 1):
fragment +=1
nowaPopulacja = []
for i in range(ileWPopulacji):
nowaPopulacja.append(crossover(data,pierwszy,drugi,fragment, wspMutacji))
return nowaPopulacja
def crossover(data,pierwszy, drugi, fragmentLiczba, wspMutacji):
ileWChrom = len(pierwszy)
tmp = random.randint(0, ileWChrom-fragmentLiczba)
@ -220,21 +157,14 @@ def crossover(data,pierwszy, drugi, fragmentLiczba, wspMutacji):
return nowyChrom
def updateMap(data, map, mapForAstar, regals):
data.mapa = map
def genPopulacje(data,pierwszy, drugi, ileWPopulacji, fragmentLiczba, wspMutacji):
ileWChrom = len(pierwszy)
fragment = round(fragmentLiczba*ileWChrom)
if(fragment == 1):
fragment +=1
nowaPopulacja = []
znajdzUnbox(data, map)
data.zajeteRegaly = znajdzBox(map, regals)
data.astarMap = data.genMap(mapForAstar)
for i in range(ileWPopulacji):
nowaPopulacja.append(crossover(data,pierwszy,drugi,fragment, wspMutacji))
def mutate(wspMutacji, chrom): #w zaleznosci od tego jak wiele mutwac wybierz pary i zamien miejscami
ileWChrom = len(chrom)
ileZmian = round(ileWChrom * wspMutacji)
for i in range(ileZmian):
pom = None
pierw = random.randint(0,ileWChrom - 1)
drug = random.randint(0,ileWChrom - 1)
pom = chrom[pierw]
chrom[pierw] = chrom[drug]
chrom[drug] = pom
return chrom
return nowaPopulacja

0
opis/LechT.md Normal file
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@ -1,21 +1,17 @@
import pygame
from os import sys
from Mapa.generate import Generate
from Mapa.floor import Floor
from Mapa.wall import Wall
from Mapa.shelf import Shelf
from genetyczny.funkcje import *
from generate import Generate
from floor import Floor
from wall import Wall
from shelf import Shelf
from wheel import Wheel
from Mapa.boxOnTheFloor import BoxOnTheFloor
from Mapa.box import Box
from Mapa.unboxOnTheFloor import UnboxOnTheFloor
from AStar import AStar
from boxOnTheFloor import BoxOnTheFloor
import easygui
from neurons import Neurons
from whereDecision import WhereDecision
from Evencik import Evencik
from genetyczny.Data import Data
from genetyczny.eee import *
from Data import Data
from genetyczne import *
class MainWindow:
def __init__(self, szerokosc, wysokosc, kruche, latwopalne, radioaktywne, niebezpieczne):
@ -61,7 +57,7 @@ class MainWindow:
self.map = randomBox(self.map, self.regals, 15)
updateMap(self.data, self.map, self.mapForAStar, self.regals)
generateGeny(self.data)
#################################################
@ -165,6 +161,7 @@ class MainWindow:
continue
break
self.data.zajeteRegaly = znajdzBox(self.map, self.regals)
def draw(self):
self.screen.fill((33,69,108))
for i in range(len(self.map)):

View File

@ -1,8 +1,8 @@
import pygame
from Mapa.floor import Floor
from Mapa.boxOnTheFloor import BoxOnTheFloor
from Mapa.unboxOnTheFloor import UnboxOnTheFloor
from Mapa.shelf import Shelf
from floor import Floor
from boxOnTheFloor import BoxOnTheFloor
from unboxOnTheFloor import UnboxOnTheFloor
from shelf import Shelf
class Wheel:
def __init__(self, screen, cell):