def __init__(self):
super().__init__()
self.geometry("790x480")
self.title("Computer Intelligence")
self.runType = 0
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111)
self.ax.axis('equal')
self.canvas = FigureCanvasTkAgg(self.fig, master=self)
self.fuzzyAlgorithm = FuzzyAlgorithmHw1()
self.mathAlgorithm = MathAlgorithm()
self.file = File()
self.orbitData = [[], []]
self.recordIndex = 0
self.carStartInfo, self.endArea, self.track = self.file.getTrackData(
'case01.txt')
self.car = Car(self.carStartInfo[:2], self.carStartInfo[2], self.ax,
self.track, self.endArea)
self.car.draw(False)
self.componment()
self.update()
def __init__(self):
self.iteration = 500
self.dimension = 3
self.genePoolSize = 1000
self.genePool = []
self.minFitness = 10000
self.matingRate = 0.6
self.mutationRate = 0.01
self.bestGene = None
self.file = File()
def __init__(self):
self.__WINDOW = tk.Tk()
self.__WINDOW.title("Neural Network HW_01")
self.__WINDOW.resizable(0, 0)
self.__WINDOW.geometry("750x650+100+100")
self.__WINDOW.protocol("WM_DELETE_WINDOW", self._closeWindow)
self.__FILE = File()
self._component()
self.__FIGURE_PLT = figurePlt(self.__WINDOW, 2, -2)
self.__WINDOW.mainloop()
class Crawler:
def __init__(self):
self.todo = File("./data/todo.txt")
self.done = File("./data/done.txt")
def crawl(self):
while (True):
if self.todo.is_empty():
break
print("Start new crawl")
url = self.todo.pop()
print("scrape url: {}".format(url))
links = Scraper.scrape(url)
print(links)
for link in links:
self.todo.add(link)
self.done.add(url)
print("save files")
self.todo.save()
self.done.save()
def __init__(self, learnRate, endRound, fileName):
self.__LEARN_RATE = learnRate
self.__END_ROUND = endRound
self.__DATA_WITH_WEIGHT, maxDataRange, minDataRange = File().getFileContent(fileName, -1)
self.__DATA_FOR_TRAINING, self.__DATA_FOR_TESTING = self.randomDataTo2Array(self.__DATA_WITH_WEIGHT)
self.__DATA_LENGTH = len(self.__DATA_WITH_WEIGHT[0]) - 2
self.__DATA_WITH_WEIGHT_LENGTH = self.__DATA_LENGTH + 1
self.__W = self.randomWeight()
self.__E = []
for i in self.__DATA_WITH_WEIGHT:
if i[self.__DATA_LENGTH + 1] not in self.__E:
self.__E.append(i[self.__DATA_LENGTH + 1])
def __init__(self):
self.todo = File("./data/todo.txt")
self.done = File("./data/done.txt")
class UiLayout:
def __init__(self):
self.__WINDOW = tk.Tk()
self.__WINDOW.title("Neural Network HW_01")
self.__WINDOW.resizable(0, 0)
self.__WINDOW.geometry("750x650+100+100")
self.__WINDOW.protocol("WM_DELETE_WINDOW", self._closeWindow)
self.__FILE = File()
self._component()
self.__FIGURE_PLT = figurePlt(self.__WINDOW, 2, -2)
self.__WINDOW.mainloop()
def checkValueIsFloat(self, value):
try:
float(value)
return True
except ValueError:
return False
def _startCalcu(self):
self.__FIGURE_PLT.clearPlt()
learnRate = self.learnRate_tf.get()
endTime = self.endCondition_tf.get()
if self.checkValueIsFloat(learnRate) and self.checkValueIsFloat(
endTime):
self.errorMsg_lb_var.set('')
fileName = self.fileOptionValue.get()
data, maxRangeNum, minRangeNum = self.__FILE.getFileContent(
fileName, 1)
__PERCEPTRON = Perceptron(float(learnRate), float(endTime),
fileName)
self.showStartW_lb_var.set('起始鍵結值:' +
str(__PERCEPTRON.getWeight()))
__PERCEPTRON.perceptronCalcu('training')
testingDataIndex = __PERCEPTRON.getTestingDataIndex()
arr = __PERCEPTRON.getWeightYToZero()
self.__FIGURE_PLT.resetDataRagne(maxRangeNum, minRangeNum)
self.__FIGURE_PLT.updateCanvasForPoint(data, testingDataIndex)
self.__FIGURE_PLT.updateCanvasForLine(arr)
self.showEndW_lb_var.set('結束鍵結值:' + str(__PERCEPTRON.getWeight()))
self.showTrainingRate_lb_var.set(
'訓練辨識率:' + str(__PERCEPTRON.getDataSuccessRate('training')) +
'%')
self.showTestingRate_lb_var.set(
'測試辨識率:' + str(__PERCEPTRON.getDataSuccessRate('testing')) +
'%')
else:
self.errorMsg_lb_var.set('請輸入學習率與收斂條件')
def _closeWindow(self):
self.__WINDOW.quit()
self.__WINDOW.destroy()
def _component(self):
self.learnRate_lb = tk.Label(self.__WINDOW,
text='學習率',
font=('Arial', 10))
self.learnRate_lb.grid(row=0)
self.learnRate_tf = tk.Entry(self.__WINDOW, )
self.learnRate_tf.grid(row=0, column=1)
self.endCondition_lb = tk.Label(self.__WINDOW,
text='收斂條件',
font=('Arial', 10))
self.endCondition_lb.grid(row=1)
self.endCondition_tf = tk.Entry(self.__WINDOW, )
self.endCondition_tf.grid(row=1, column=1)
fileOptions = self.__FILE.getDataSetFileName()
self.fileOptionValue = tk.StringVar(self.__WINDOW)
self.fileOptionValue.set(fileOptions[0])
self.fileOption_lb = tk.Label(self.__WINDOW,
text='請選擇檔案',
font=('Arial', 10))
self.fileOption_lb.grid(row=2)
self.fileOption_op = tk.OptionMenu(self.__WINDOW, self.fileOptionValue,
*fileOptions)
self.fileOption_op.grid(row=2, column=1)
self.startCalcu_bt = tk.Button(self.__WINDOW,
text="開始",
command=self._startCalcu,
width=10)
self.startCalcu_bt.grid(row=0,
rowspan=2,
column=2,
columnspan=2,
padx=10,
pady=5)
self.closeWindow_bt = tk.Button(self.__WINDOW,
text="離開",
command=self._closeWindow,
width=10)
self.closeWindow_bt.grid(row=0,
column=4,
columnspan=2,
rowspan=2,
padx=10,
pady=5)
self.errorMsg_lb_var = tk.StringVar()
errorMsg_lb = tk.Label(self.__WINDOW,
textvariable=self.errorMsg_lb_var,
font=('Arial', 10))
errorMsg_lb.grid(row=4, columnspan=2)
self.showStartW_lb_var = tk.StringVar()
self.showStartW_lb_var.set('起始鍵結值:')
showW_lb = tk.Label(self.__WINDOW,
textvariable=self.showStartW_lb_var,
font=('Arial', 10))
showW_lb.grid(row=6, column=0)
self.showEndW_lb_var = tk.StringVar()
self.showEndW_lb_var.set('結束鍵結值:')
showW_lb = tk.Label(self.__WINDOW,
textvariable=self.showEndW_lb_var,
font=('Arial', 10))
showW_lb.grid(row=6, column=2)
self.showTrainingRate_lb_var = tk.StringVar()
self.showTrainingRate_lb_var.set('訓練辨識率:')
showTrainingRate_lb = tk.Label(
self.__WINDOW,
textvariable=self.showTrainingRate_lb_var,
font=('Arial', 10))
showTrainingRate_lb.grid(row=7, column=0)
self.showTestingRate_lb_var = tk.StringVar()
self.showTestingRate_lb_var.set('測試辨識率:')
showTestingRate_lb = tk.Label(self.__WINDOW,
textvariable=self.showTestingRate_lb_var,
font=('Arial', 10))
showTestingRate_lb.grid(row=7, column=1)
class Hw1Layout(tk.Tk):
def __init__(self):
super().__init__()
self.geometry("790x480")
self.title("Computer Intelligence")
self.runType = 0
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111)
self.ax.axis('equal')
self.canvas = FigureCanvasTkAgg(self.fig, master=self)
self.fuzzyAlgorithm = FuzzyAlgorithmHw1()
self.mathAlgorithm = MathAlgorithm()
self.file = File()
self.orbitData = [[], []]
self.recordIndex = 0
self.carStartInfo, self.endArea, self.track = self.file.getTrackData(
'case01.txt')
self.car = Car(self.carStartInfo[:2], self.carStartInfo[2], self.ax,
self.track, self.endArea)
self.car.draw(False)
self.componment()
self.update()
def update(self):
if self.runType != 0:
self.ax.clear()
self.car.draw(True)
if self.runType == 1:
carState = self.car.updateCarPos()
# self.runType = 0
self.orbitData[0].append([
self.car.getSensorToTrackDistance('front'),
self.car.getSensorToTrackDistance('right'),
self.car.getSensorToTrackDistance('left'),
self.car.getcarSteeringWheelAngle(),
])
self.orbitData[1].append([
self.car.carCenterPos[0], self.car.carCenterPos[1],
self.car.getSensorToTrackDistance('front'),
self.car.getSensorToTrackDistance('right'),
self.car.getSensorToTrackDistance('left'),
self.car.getcarSteeringWheelAngle()
])
# print(self.orbitData)
if carState:
self.runType = 0
else:
self.updateCarInfoLb()
fsDistance = self.car.getSensorToTrackDistance('front')
rsDistance = self.car.getSensorToTrackDistance('right')
lsDistance = self.car.getSensorToTrackDistance('left')
steeringWheelAngle = self.fuzzyAlgorithm.fuzzySystem(
fsDistance, rsDistance, lsDistance)
self.car.setcarSteeringWheelAngle(steeringWheelAngle)
if self.runType == 0:
self.ax.clear()
self.car.draw(True)
self.updateCarInfoLb()
self.file.writeContentToFile(self.orbitData[0],
'train4D.txt')
self.file.writeContentToFile(self.orbitData[1],
'train6D.txt')
self.orbitData = [[], []]
elif self.runType == 2:
record4D = self.file.getCarRecord('train4D.txt')
self.car.setcarSteeringWheelAngle(
record4D[self.recordIndex][3])
self.recordIndex += 1
carState = self.car.updateCarPos()
self.updateCarInfoLb()
if carState: self.recordIndex = len(record4D)
if len(record4D) == self.recordIndex:
self.runType = 0
self.recordIndex = 0
elif self.runType == 3:
record6D = self.file.getCarRecord('train6D.txt')
self.car.setcarSteeringWheelAngle(
record6D[self.recordIndex][5])
self.recordIndex += 1
carState = self.car.updateCarPos()
self.updateCarInfoLb()
if carState: self.recordIndex = len(record6D)
if len(record6D) == self.recordIndex:
self.runType = 0
self.recordIndex = 0
self.canvas.draw()
self.after(100, self.update)
def updateCarInfoLb(self):
fsDistance = self.car.getSensorToTrackDistance('front')
rsDistance = self.car.getSensorToTrackDistance('right')
lsDistance = self.car.getSensorToTrackDistance('left')
self.fsDistance_lb_var.set(fsDistance)
self.rsDistance_lb_var.set(rsDistance)
self.lsDistance_lb_var.set(lsDistance)
self.carAngle_lb_var.set(self.car.getCarAngle())
self.carSteeringWheelAngle_lb_var.set(
self.car.getcarSteeringWheelAngle())
def componment(self):
plot_widget = self.canvas.get_tk_widget().place(x=180, y=0)
infoPos = (10, 100)
valueX = 100
self.start_bt = tk.Button(self,
text="開始",
command=self.startBt,
width=15,
height=2)
self.start_bt.place(x=10, y=10)
fileOptions = self.file.getAllTrackFilename()
self.fileOptionValue = tk.StringVar('')
self.fileOptionValue.set(fileOptions[0])
self.fileOption_lb = tk.Label(self, text='更換軌道', font=('Arial', 10))
self.fileOption_lb.place(x=infoPos[0], y=infoPos[1] - 35)
self.fileOption_op = tk.OptionMenu(self, self.fileOptionValue,
*fileOptions)
self.fileOption_op.place(x=infoPos[0], y=infoPos[1] - 15)
carAngle_tx = tk.Label(self, text='自走車角度 :', font=('Arial', 10))
carAngle_tx.place(x=infoPos[0], y=infoPos[1] + 20)
self.carAngle_lb_var = tk.StringVar()
self.carAngle_lb_var.set(str(self.car.getCarAngle()))
carAngle_lb = tk.Label(self,
textvariable=self.carAngle_lb_var,
font=('Arial', 10))
carAngle_lb.place(x=infoPos[0] + valueX, y=infoPos[1] + 20)
carSteeringWheelAngle_tx = tk.Label(self,
text='方向盤角度 :',
font=('Arial', 10))
carSteeringWheelAngle_tx.place(x=infoPos[0], y=infoPos[1] + 40)
self.carSteeringWheelAngle_lb_var = tk.StringVar()
self.carSteeringWheelAngle_lb_var.set(
str(self.car.getcarSteeringWheelAngle()))
carSteeringWheelAngle_lb = tk.Label(
self,
textvariable=self.carSteeringWheelAngle_lb_var,
font=('Arial', 10))
carSteeringWheelAngle_lb.place(x=infoPos[0] + valueX,
y=infoPos[1] + 40)
fsDistance_tx = tk.Label(self, text='前感測器距離 :', font=('Arial', 10))
fsDistance_tx.place(x=infoPos[0], y=infoPos[1] + 60)
self.fsDistance_lb_var = tk.StringVar()
self.fsDistance_lb_var.set(0)
fsDistance_lb = tk.Label(self,
textvariable=self.fsDistance_lb_var,
font=('Arial', 10))
fsDistance_lb.place(x=infoPos[0] + valueX, y=infoPos[1] + 60)
rsDistance_tx = tk.Label(self, text='右感測器距離 :', font=('Arial', 10))
rsDistance_tx.place(x=infoPos[0], y=infoPos[1] + 80)
self.rsDistance_lb_var = tk.StringVar()
self.rsDistance_lb_var.set(0)
rsDistance_lb = tk.Label(self,
textvariable=self.rsDistance_lb_var,
font=('Arial', 10))
rsDistance_lb.place(x=infoPos[0] + valueX, y=infoPos[1] + 80)
lsDistance_tx = tk.Label(self, text='左感測器距離 :', font=('Arial', 10))
lsDistance_tx.place(x=infoPos[0], y=infoPos[1] + 100)
self.lsDistance_lb_var = tk.StringVar()
self.lsDistance_lb_var.set(0)
lsDistance_lb = tk.Label(self,
textvariable=self.lsDistance_lb_var,
font=('Arial', 10))
lsDistance_lb.place(x=infoPos[0] + valueX, y=infoPos[1] + 100)
self.readTrack_bt = tk.Button(self,
text="讀取 4D 記錄",
command=self.readTrackBt,
width=15,
height=2)
self.readTrack_bt.place(x=infoPos[0], y=infoPos[1] + 150)
self.readHistory_bt = tk.Button(self,
text="讀取 6D 記錄",
command=self.readHistoryBt,
width=15,
height=2)
self.readHistory_bt.place(x=infoPos[0], y=infoPos[1] + 200)
def startBt(self):
carStartInfo, endArea, track = self.file.getTrackData(
self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 1
def readTrackBt(self):
carStartInfo, endArea, track = self.file.getTrackData(
self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 2
def readHistoryBt(self):
carStartInfo, endArea, track = self.file.getTrackData(
self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 3
class Hw2Layout(tk.Tk):
def __init__(self):
super().__init__()
self.geometry("790x480")
self.title("Computer Intelligence - Gene & RBFN")
self.runType = 0
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111)
self.ax.axis('equal')
self.canvas = FigureCanvasTkAgg(self.fig, master=self)
self.GeneAlgorithm = GeneAlgorithm()
self.mathAlgorithm = MathAlgorithm()
self.file = File()
self.orbitData = [[], []]
self.recordIndex = 0
self.carStartInfo, self.endArea, self.track = self.file.getTrackData('case01.txt')
self.car = Car(self.carStartInfo[:2], self.carStartInfo[2], self.ax, self.track, self.endArea)
self.car.draw(False)
self.componment()
self.update()
def update(self):
if self.runType != 0:
self.ax.clear()
self.car.draw(True)
if self.runType == 1:
carState = self.car.updateCarPos()
self.orbitData[0].append([
self.car.getSensorToTrackDistance('front'),
self.car.getSensorToTrackDistance('right'),
self.car.getSensorToTrackDistance('left'),
self.car.getcarSteeringWheelAngle(),
])
self.orbitData[1].append([
self.car.carCenterPos[0],
self.car.carCenterPos[1],
self.car.getSensorToTrackDistance('front'),
self.car.getSensorToTrackDistance('right'),
self.car.getSensorToTrackDistance('left'),
self.car.getcarSteeringWheelAngle()
])
if carState:
self.runType = 0
else:
self.updateCarInfoLb()
fsDistance = self.car.getSensorToTrackDistance('front')
rsDistance = self.car.getSensorToTrackDistance('right')
lsDistance = self.car.getSensorToTrackDistance('left')
if int(self.data_vb_var.get()) == 1:
steeringWheelAngle = self.GeneAlgorithm.testingFor4D(fsDistance, rsDistance, lsDistance)
else:
steeringWheelAngle = self.GeneAlgorithm.testingFor6D(self.car.carCenterPos[0], self.car.carCenterPos[1], fsDistance, rsDistance, lsDistance)
self.car.setcarSteeringWheelAngle(steeringWheelAngle)
if self.runType == 0:
self.ax.clear()
self.car.draw(True)
self.updateCarInfoLb()
self.file.writeContentToFile(self.orbitData[0], 'train4D.txt')
self.file.writeContentToFile(self.orbitData[1], 'train6D.txt')
self.orbitData = [[], []]
elif self.runType == 2:
record4D = self.file.getCarRecord('train4D.txt')
self.car.setcarSteeringWheelAngle(record4D[self.recordIndex][3])
self.recordIndex += 1
carState = self.car.updateCarPos()
self.updateCarInfoLb()
if carState: self.recordIndex = len(record4D)
if len(record4D) == self.recordIndex:
self.runType = 0
self.recordIndex = 0
elif self.runType == 3:
record6D = self.file.getCarRecord('train6D.txt')
self.car.setcarSteeringWheelAngle(record6D[self.recordIndex][5])
self.recordIndex += 1
carState = self.car.updateCarPos()
self.updateCarInfoLb()
if carState: self.recordIndex = len(record6D)
if len(record6D) == self.recordIndex:
self.runType = 0
self.recordIndex = 0
self.canvas.draw()
self.after(100, self.update)
def updateCarInfoLb(self):
fsDistance = self.car.getSensorToTrackDistance('front')
rsDistance = self.car.getSensorToTrackDistance('right')
lsDistance = self.car.getSensorToTrackDistance('left')
self.fsDistance_lb_var.set(fsDistance)
self.rsDistance_lb_var.set(rsDistance)
self.lsDistance_lb_var.set(lsDistance)
self.carAngle_lb_var.set(self.car.getCarAngle())
self.carSteeringWheelAngle_lb_var.set(round(self.car.getcarSteeringWheelAngle(), 4))
def componment(self):
plot_widget = self.canvas.get_tk_widget().place(x = 180, y = 0)
genePos = (10, 0)
self.algorithmSection_lb = tk.Label(self, text = 'Gene & RBFN 訓練', font = ('Arial', 12))
self.algorithmSection_lb.place(x = genePos[0], y = genePos[1])
self.start_training = tk.Button(self, text = "開始訓練", command = self.startTrain, width = 10, height = 1)
self.start_training.place(x = genePos[0], y = genePos[1] + 25)
self.data_vb_var = tk.StringVar()
self.data_vb_var.set(1)
self.data4D_lb = tk.Label(self, text = '訓練資料集', font = ('Arial', 10))
self.data4D_lb.place(x = genePos[0], y = genePos[1] + 50)
self.data4D_rb = tk.Radiobutton(self, text="4D", variable=self.data_vb_var, value=1)
self.data4D_rb.place(x = genePos[0] + 70, y = genePos[1] + 50)
self.data6D_rb = tk.Radiobutton(self, text="6D", variable=self.data_vb_var, value=2)
self.data6D_rb.place(x = genePos[0] + 115, y = genePos[1] + 50)
self.iterationTimes_lb = tk.Label(self, text = '迭代次數', font = ('Arial', 10))
self.iterationTimes_lb.place(x = genePos[0], y = genePos[1] + 70)
self.iterationTimes_lb_var = tk.StringVar()
self.iterationTimes_lb_var.set('10')
self.iterationTimes_tx = tk.Entry(self, width = 10, textvariable = self.iterationTimes_lb_var)
self.iterationTimes_tx.place(x = genePos[0] + 70, y = genePos[1] + 70)
self.genePoolSize_lb = tk.Label(self, text = '族群大小', font = ('Arial', 10))
self.genePoolSize_lb.place(x = genePos[0], y = genePos[1] + 90)
self.genePoolSize_lb_var = tk.StringVar()
self.genePoolSize_lb_var.set('100')
self.genePoolSize_tx = tk.Entry(self, width = 10, textvariable = self.genePoolSize_lb_var)
self.genePoolSize_tx.place(x = genePos[0] + 70, y = genePos[1] + 90)
self.mating_lb = tk.Label(self, text = '交配機率', font = ('Arial', 10))
self.mating_lb.place(x = genePos[0], y = genePos[1] + 110)
self.mating_lb_var = tk.StringVar()
self.mating_lb_var.set('0.6')
self.mating_tx = tk.Entry(self, width = 10, textvariable = self.mating_lb_var)
self.mating_tx.place(x = genePos[0] + 70, y = genePos[1] + 110)
self.mutation_lb = tk.Label(self, text = '突變機率', font = ('Arial', 10))
self.mutation_lb.place(x = genePos[0], y = genePos[1] + 130)
self.mutation_lb_var = tk.StringVar()
self.mutation_lb_var.set('0.01')
self.mutation_tx = tk.Entry(self, width = 10, textvariable = self.mutation_lb_var)
self.mutation_tx.place(x = genePos[0] + 70, y = genePos[1] + 130)
infoPos = (10, 250)
valueX = 100
fileOptions = self.file.getAllTrackFilename()
self.fileOptionValue = tk.StringVar('')
self.fileOptionValue.set(fileOptions[0])
self.carSection_lb = tk.Label(self, text = '自動車控制', font = ('Arial', 12))
self.carSection_lb.place(x = infoPos[0], y = infoPos[1] - 90)
self.start_bt = tk.Button(self, text = "開始測試", command = self.startBt, width = 10, height = 1)
self.start_bt.place(x = infoPos[0], y = infoPos[1] - 65)
self.fileOption_lb = tk.Label(self, text = '更換軌道', font = ('Arial', 10))
self.fileOption_lb.place(x = infoPos[0], y = infoPos[1] - 35)
self.fileOption_op = tk.OptionMenu(self, self.fileOptionValue, *fileOptions)
self.fileOption_op.place(x = infoPos[0], y = infoPos[1] - 15)
carAngle_tx = tk.Label(self, text = '自走車角度 :', font = ('Arial', 10))
carAngle_tx.place(x = infoPos[0], y = infoPos[1] + 20)
self.carAngle_lb_var = tk.StringVar()
self.carAngle_lb_var.set(str(self.car.getCarAngle()))
carAngle_lb = tk.Label(self, textvariable = self.carAngle_lb_var, font = ('Arial', 10))
carAngle_lb.place(x = infoPos[0] + valueX, y = infoPos[1] + 20)
carSteeringWheelAngle_tx = tk.Label(self, text = '方向盤角度 :', font = ('Arial', 10))
carSteeringWheelAngle_tx.place(x = infoPos[0], y = infoPos[1] + 40)
self.carSteeringWheelAngle_lb_var = tk.StringVar()
self.carSteeringWheelAngle_lb_var.set(str(self.car.getcarSteeringWheelAngle()))
carSteeringWheelAngle_lb = tk.Label(self, textvariable = self.carSteeringWheelAngle_lb_var, font = ('Arial', 10))
carSteeringWheelAngle_lb.place(x = infoPos[0] + valueX, y = infoPos[1] + 40)
fsDistance_tx = tk.Label(self, text = '前感測器距離 :', font = ('Arial', 10))
fsDistance_tx.place(x = infoPos[0], y = infoPos[1] + 60)
self.fsDistance_lb_var = tk.StringVar()
self.fsDistance_lb_var.set(0)
fsDistance_lb = tk.Label(self, textvariable = self.fsDistance_lb_var, font = ('Arial', 10))
fsDistance_lb.place(x = infoPos[0] + valueX, y = infoPos[1] + 60)
rsDistance_tx = tk.Label(self, text = '右感測器距離 :', font = ('Arial', 10))
rsDistance_tx.place(x = infoPos[0], y = infoPos[1] + 80)
self.rsDistance_lb_var = tk.StringVar()
self.rsDistance_lb_var.set(0)
rsDistance_lb = tk.Label(self, textvariable = self.rsDistance_lb_var, font = ('Arial', 10))
rsDistance_lb.place(x = infoPos[0] + valueX, y = infoPos[1] + 80)
lsDistance_tx = tk.Label(self, text = '左感測器距離 :', font = ('Arial', 10))
lsDistance_tx.place(x = infoPos[0], y = infoPos[1] + 100)
self.lsDistance_lb_var = tk.StringVar()
self.lsDistance_lb_var.set(0)
lsDistance_lb = tk.Label(self, textvariable = self.lsDistance_lb_var, font = ('Arial', 10))
lsDistance_lb.place(x = infoPos[0] + valueX, y = infoPos[1] + 100)
# self.readTrack_bt = tk.Button(self, text = "讀取 4D 記錄", command = self.readTrackBt, width = 15, height = 2)
# self.readTrack_bt.place(x = infoPos[0], y = infoPos[1] + 150)
# self.readHistory_bt = tk.Button(self, text = "讀取 6D 記錄", command = self.readHistoryBt, width = 15, height = 2)
# self.readHistory_bt.place(x = infoPos[0], y = infoPos[1] + 200)
self.loadDataSection_lb = tk.Label(self, text = '讀取檔案', font = ('Arial', 12))
self.loadDataSection_lb.place(x = infoPos[0], y = infoPos[1] + 140)
self.readHistory4D_bt = tk.Button(self, text = "讀取 RBFN 4D", command = self.readHistoryRBFN4D, width = 12, height = 1)
self.readHistory4D_bt.place(x = infoPos[0], y = infoPos[1] + 165)
# self.readHistory6D_bt = tk.Button(self, text = "讀取 RBFN 6D", command = self.readHistoryRBFN6D, width = 12, height = 1)
# self.readHistory6D_bt.place(x = infoPos[0], y = infoPos[1] + 195)
def startBt(self):
carStartInfo, endArea, track = self.file.getTrackData(self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 1
def readTrackBt(self):
carStartInfo, endArea, track = self.file.getTrackData(self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 2
def readHistoryBt(self):
carStartInfo, endArea, track = self.file.getTrackData(self.fileOptionValue.get())
self.car.resetCarState(carStartInfo[:2], carStartInfo[2])
self.car.setTrack(track)
self.car.setEndArea(endArea)
self.runType = 3
def readHistoryRBFN4D(self):
vector = self.file.getRBFNParam()
self.GeneAlgorithm.loadRBFN(vector, 3)
def readHistoryRBFN6D(self):
vector = self.file.getRBFNParam()
self.GeneAlgorithm.loadRBFN(vector, 5)
def startTrain(self):
dimension = 3 if int(self.data_vb_var.get()) == 1 else 5
iteration = int(self.iterationTimes_lb_var.get())
genePoolSize = int(self.genePoolSize_lb_var.get())
matingRate = float(self.mating_lb_var.get())
mutationRate = float(self.mutation_lb_var.get())
print(dimension)
self.GeneAlgorithm.setGeneParam(dimension, genePoolSize, matingRate, mutationRate, 100000)
for index in range(iteration):
self.GeneAlgorithm.training()
print('Iteration ', index)
print(self.GeneAlgorithm.minFitness)
self.file.writeRBFNParamToFile(self.GeneAlgorithm.bestGene.vector)
class GeneAlgorithm():
def __init__(self):
self.iteration = 500
self.dimension = 3
self.genePoolSize = 1000
self.genePool = []
self.minFitness = 10000
self.matingRate = 0.6
self.mutationRate = 0.01
self.bestGene = None
self.file = File()
def training(self):
for index in range(self.genePoolSize):
if random.random() < self.matingRate:
val = int(random.random() * (self.genePoolSize - 1))
self.geneMating(self.genePool[index], self.genePool[val])
for index in range(self.genePoolSize):
if random.random() < self.mutationRate:
self.geneMutation(self.genePool[index])
self.getBestGene()
def testingFor4D(self, fSen, rSen, lSen):
return self.bestGene.RBFN.getOutput([fSen, rSen, lSen]) * 80 - 40
def testingFor6D(self, x, y, fSen, rSen, lSen):
return self.bestGene.RBFN.getOutput([x, y, fSen, rSen, lSen]) * 80 - 40
def geneMating(self, geneA, geneB):
sigmaVal = (random.random() - 0.5) * 2 * self.matingRate
geneAVector = np.array(geneA.vector) + sigmaVal * (np.array(geneA.vector) - np.array(geneB.vector))
geneBVector = np.array(geneB.vector) - sigmaVal * (np.array(geneA.vector) - np.array(geneB.vector))
geneA.updateVector(geneAVector)
geneB.updateVector(geneBVector)
def geneMutation(self, gene):
sigmaVal = (random.random() - 0.5) * 2 * self.mutationRate
geneVector = np.array(gene.vector) + sigmaVal * random.random() * np.array(gene.vector)
gene.updateVector(geneVector)
def getBestGene(self):
for geneIndex in range(self.genePoolSize):
fit = self.genePool[geneIndex].getFitness(self.wheelRecord, self.senRecord)
if fit < self.minFitness:
self.minFitness = fit
self.bestGene = copy.deepcopy(self.genePool[geneIndex])
def setGeneParam(self, dimension, genePoolSize, matingRate, mutationRate, minFitness):
self.dimension = dimension
self.genePoolSize = genePoolSize
self.matingRate = matingRate
self.mutationRate = mutationRate
self.minFitness = minFitness
fileName = 'train4D.txt' if self.dimension == 3 else 'train6D.txt'
self.senRecord, self.wheelRecord = self.file.getCarRecordForGene(fileName)
self.recordNormalization()
self.genePool = []
for size in range(self.genePoolSize):
self.genePool.append(Gene(self.dimension))
def recordNormalization(self):
for index, wheel in enumerate(self.wheelRecord):
self.wheelRecord[index] = (np.array(wheel) + 40) / 80
def loadRBFN(self, vector, dataDimension):
print('loadRBFN')
self.bestGene = Gene(dataDimension)
self.bestGene.updateVector(vector)
# 4vector = [
# 0.27413031070271554,-0.2165564702584432,0.43570801383368407,0.25766919736016813,0.8162115275208734,0.8162821060763124,0.8202941611263892,0.42819618155989114,0.08077460452911274,5.824353208226845,13.444845433520543,25.843555157662887,24.72074663331964,27.2452876319428,4.26792413219178,29.879182972982075,17.71580854125198,6.590448633825639,0.8439619974605179,25.090933045508315,15.210407312007572,26.40874256181456,25.714038156109435,29.958432120639543,0.3486954447339934,29.887137298021543,22.942949780787536,23.7447902299137,19.17562948615331,7.703035677504062,6.924410903031947,14.185147813621386,10.955673223625558,3.9415175026251936,9.477755884503381,0.2730688547204743,8.259032578761945,2.933900572696063,3.3994091470723804,9.982899337717233,1.196458072994222
# ]
# vector6d =[0.3314577730610375, 1.2183321081726128, 1.557934622746724, 0.3080828456782288, 0.7291432017815879, 1.2314183874778006, 2.155807295701578,0.39081250852022686, 0.7434143743221118, 0.008997195643978547, 1.7810518811343055, 9.383480543728732, 23.748940099019297, 10.043168670510601, 13.860769542424523, 24.46494545450288, 28.202942918756225, 24.877126793973563, 3.9222106689879697, 29.877963667569002, 28.396347719098557, 9.421677792657011, 11.162980712345448, 0.3468052347140606, 10.342886386409214, 24.974118896811085, 7.540382128022785, 1.0953311755495911, 29.998498548958363, 0.046913219247201376, 1.1011038377052575, 4.306768631106814, 29.998561290785688, 12.449489740729295, 1.927979889073564, 26.479774776775724, 0.5121427432301313, 22.80113107160742, 2.072223997473536, 0.004049267680546706, 0.006525454347247486, 29.938221316682128, 13.288957250131268, 8.925158752355541, 29.95244316597126, 3.4456902434559478, 0.2788639194474892, 14.472981799950828, 2.8857602683878203, 6.79775252348321, 9.998534643282436, 0.6543266933167925, 1.0037529895699917, 3.091226193327437, 9.985620674857863, 9.065722780560979, 9.016848732343306]