Организация дополнительного потока для тяжелых расчетов
В программе по аппроксимации функции нейронной сетью, нейронная сеть медленно аппроксимирует исходную функцию(то есть тренируется и предсказывает значения функции) даже на моем ноутбуке с процессором intel core i5 9300h, выражается это в медленном рендеринге графика в форме scatter, мне как-то советовали организовать доп. поток для тяжелых расчётов, чтобы процесс аппроксимации был быстрее, но я не знаю как это сделать в рамках данной программы, код:
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'funcAprox.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.Qt import *
import numpy as np
from sympy import *
from pyqtgraph import PlotWidget
import pyqtgraph as pg
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(1778, 783)
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.setStyleSheet("background-color: rgb(10, 170, 0);\n"
"background-color: rgb(73, 152, 255);")
self.centralwidget.setObjectName("centralwidget")
self.graphicsView = PlotWidget(self.centralwidget)
self.graphicsView.setGeometry(QtCore.QRect(450, 30, 621, 631))
self.graphicsView.setObjectName("graphicsView")
self.graphicsView.setBackgroundBrush(QColor("white"))
self.pushButton = QtWidgets.QPushButton(self.centralwidget)
self.pushButton.setGeometry(QtCore.QRect(20, 460, 341, 41))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.pushButton.setFont(font)
self.pushButton.setStyleSheet("background: rgb(90, 211, 255)")
self.pushButton.setObjectName("pushButton")
self.pushButton_2 = QtWidgets.QPushButton(self.centralwidget)
self.pushButton_2.setGeometry(QtCore.QRect(20, 580, 341, 41))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.pushButton_2.setFont(font)
self.pushButton_2.setStyleSheet("background: rgb(90, 211, 255)")
self.pushButton_2.setObjectName("pushButton_2")
self.label_4 = QtWidgets.QLabel(self.centralwidget)
self.label_4.setGeometry(QtCore.QRect(20, 240, 331, 21))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.label_4.setFont(font)
self.label_4.setObjectName("label_4")
self.label_5 = QtWidgets.QLabel(self.centralwidget)
self.label_5.setGeometry(QtCore.QRect(20, 310, 411, 21))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.label_5.setFont(font)
self.label_5.setObjectName("label_5")
#Вид функции
self.textEdit_6 = QtWidgets.QTextEdit(self.centralwidget)
self.textEdit_6.setGeometry(QtCore.QRect(20, 410, 221, 31))
self.textEdit_6.setStyleSheet("background: rgb(255, 255, 255)")
self.textEdit_6.setObjectName("textEdit_6")
self.textEdit_6.setPlainText("sin(x)*10 + x**2")
self.label_6 = QtWidgets.QLabel(self.centralwidget)
self.label_6.setGeometry(QtCore.QRect(20, 380, 391, 21))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.label_6.setFont(font)
self.label_6.setObjectName("label_6")
#Кол-во эпох
self.textEdit_7 = QtWidgets.QTextEdit(self.centralwidget)
self.textEdit_7.setGeometry(QtCore.QRect(20, 340, 221, 31))
self.textEdit_7.setStyleSheet("background: rgb(255, 255, 255)")
self.textEdit_7.setObjectName("textEdit_7")
self.textEdit_7.setPlainText("100")
#Скорость обучения
self.textEdit_8 = QtWidgets.QTextEdit(self.centralwidget)
self.textEdit_8.setGeometry(QtCore.QRect(20, 270, 221, 31))
self.textEdit_8.setStyleSheet("background: rgb(255, 255, 255)")
self.textEdit_8.setObjectName("textEdit_8")
self.textEdit_8.setPlainText("0.0001")
self.pushButton_3 = QtWidgets.QPushButton(self.centralwidget)
self.pushButton_3.setGeometry(QtCore.QRect(20, 520, 341, 41))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.pushButton_3.setFont(font)
self.pushButton_3.setStyleSheet("background: rgb(90, 211, 255)")
self.pushButton_3.setObjectName("pushButton_3")
#Объём выборочных данных
self.textEdit_11 = QtWidgets.QTextEdit(self.centralwidget)
self.textEdit_11.setGeometry(QtCore.QRect(20, 130, 221, 31))
self.textEdit_11.setStyleSheet("background: rgb(255, 255, 255)")
self.textEdit_11.setObjectName("textEdit_11")
self.textEdit_11.setPlainText("100")
self.label = QtWidgets.QLabel(self.centralwidget)
self.label.setGeometry(QtCore.QRect(20, 100, 291, 21))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.label.setFont(font)
self.label.setObjectName("label")
self.label_2 = QtWidgets.QLabel(self.centralwidget)
self.label_2.setGeometry(QtCore.QRect(20, 170, 351, 21))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
font.setWeight(75)
self.label_2.setFont(font)
self.label_2.setObjectName("label_2")
#Скрытый слой
self.textEdit_10 = QtWidgets.QTextEdit(self.centralwidget)
self.textEdit_10.setGeometry(QtCore.QRect(20, 200, 221, 31))
self.textEdit_10.setStyleSheet("background: rgb(255, 255, 255)")
self.textEdit_10.setObjectName("textEdit_10")
self.textEdit_10.setPlainText("50")
self.label_3 = QtWidgets.QLabel(self.centralwidget)
self.label_3.setGeometry(QtCore.QRect(10, 20, 421, 71))
font = QtGui.QFont()
font.setPointSize(7)
font.setBold(True)
font.setWeight(75)
self.label_3.setFont(font)
self.label_3.setObjectName("label_3")
self.graphicsView_2 = PlotWidget(self.centralwidget)
self.graphicsView_2.setGeometry(QtCore.QRect(1080, 30, 621, 631))
self.graphicsView_2.setObjectName("graphicsView_2")
self.graphicsView_2.setBackgroundBrush(QColor("white"))
MainWindow.setCentralWidget(self.centralwidget)
self.statusbar = QtWidgets.QStatusBar(MainWindow)
self.statusbar.setObjectName("statusbar")
MainWindow.setStatusBar(self.statusbar)
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
_translate = QtCore.QCoreApplication.translate
MainWindow.setWindowTitle(_translate("MainWindow", "Аппроксимация функции нейронной сетью"))
self.pushButton.setText(_translate("MainWindow", "Построить аппроксимацию функции"))
self.pushButton_2.setText(_translate("MainWindow", "Очистить графич.поверхность"))
self.label_4.setText(_translate("MainWindow", "Скорость обучения(learning rate)"))
self.label_5.setText(_translate("MainWindow", "Количество эпох обучения(number of epoch)"))
self.label_6.setText(_translate("MainWindow", "Задайте вид функции f(x):"))
self.pushButton_3.setText(_translate("MainWindow", "Остановить процесс"))
self.label.setText(_translate("MainWindow", "Объём выборочных данных"))
self.label_2.setText(_translate("MainWindow", "Количество нейронов в скрытом слое"))
self.label_3.setText(_translate("MainWindow", "*Количество нейронов во входном слое и выходном всегда 1"))
#Модифицированная нейросеть
class PartyNN(object):
def __init__(self, learning_rate=0.1, input_nodes=1, hidden_nodes=5, output_nodes=1):
input_nodes+=1
self.weights_0_1 = np.random.normal(0.0, hidden_nodes ** -0.5, (hidden_nodes, input_nodes))
self.weights_1_2 = np.random.normal(0.0, output_nodes ** -0.5, (output_nodes, hidden_nodes))
self.sigmoid_mapper = np.vectorize(self.sigmoid)
self.learning_rate = np.array([learning_rate])
def set_lr(lr):
self.learning_rate = np.array([lr])
def sigmoid(self, x):
return 1 / (1 + np.exp(-x))
def predict(self, inputs):
inputs = np.concatenate((inputs,[1]))
inputs_1 = np.dot(self.weights_0_1, inputs)
outputs_1 = self.sigmoid_mapper(inputs_1)
inputs_2 = np.dot(self.weights_1_2, outputs_1)
#outputs_2 = self.sigmoid_mapper(inputs_2)
outputs_2 = inputs_2
return outputs_2
def train(self, inputs, expected_predict):
inputs = np.concatenate((inputs,[1]))
inputs_1 = np.dot(self.weights_0_1, inputs)
outputs_1 = self.sigmoid_mapper(inputs_1)
inputs_2 = np.dot(self.weights_1_2, outputs_1)
#outputs_2 = self.sigmoid_mapper(inputs_2)
outputs_2 = inputs_2
actual_predict = outputs_2[0]
error_layer_2 = np.array([actual_predict - expected_predict])
gradient_layer_2 = 1 # Здесь что-то я не так сделал. Нужно учитывать вес# actual_predict * (1 - actual_predict)
weights_delta_layer_2 = error_layer_2 * gradient_layer_2
self.weights_1_2 -= (np.dot(weights_delta_layer_2, outputs_1.reshape(1, len(outputs_1)))) * self.learning_rate
error_layer_1 = weights_delta_layer_2 * self.weights_1_2
gradient_layer_1 = outputs_1 * (1 - outputs_1)
weights_delta_layer_1 = error_layer_1 * gradient_layer_1
self.weights_0_1 -= np.dot(inputs.reshape(len(inputs), 1), weights_delta_layer_1).T * self.learning_rate
class MainWindow(QtWidgets.QMainWindow, Ui_MainWindow):
def __init__(self):
super().__init__()
self.setupUi(self)
self.pushButton.clicked.connect(self.start_func) # +++
self.pushButton_2.clicked.connect(self.clear) # !!!
self.pushButton_3.clicked.connect(self.stop_start)
def initMainWindow(self):
self.flag = True
self.pcenter = 0
self.prange = 10
self.step = 0.1
s = Symbol('x')
self.expr = self.textEdit_6.toPlainText()
self.expr_1 = sympify(self.expr)
self.func = lambdify(s, self.expr)
period = np.arange(self.pcenter-self.prange, self.pcenter+self.prange, self.step)
lr = float(self.textEdit_8.toPlainText())
self.myNN = PartyNN(learning_rate=lr, input_nodes=1, hidden_nodes=int(self.textEdit_10.toPlainText()), output_nodes=1)
self.set_count = int(self.textEdit_11.toPlainText())
rand_set = np.random.random(self.set_count)*2*self.prange-self.prange+self.pcenter
def start_func(self): # +++
self.initMainWindow() # +++
self.draw() # +++
def clear(self):
self.flag = False # +++
# self.graphicsView.clear() # ---
QtCore.QTimer.singleShot(4000, self.graphicsView.clear) # +++
self.graphicsView_2.clear()
def stop_start(self):
self.flag = not self.flag
if self.flag:
self.pushButton_3.setText("Остановить процесс аппроксимации")
self.draw()
else:
self.pushButton_3.setText("Возобновить процесс аппроксимации")
#Функция обучения
def Train(self):
rand_set = np.random.random(self.set_count)*2*self.prange-self.prange+self.pcenter
for x in range(0, self.set_count-1):
self.myNN.train([rand_set[x]], self.func(rand_set[x]))
def MSE(y, Y):
return np.mean((y-Y)**2)
def draw(self):
period = np.arange(self.pcenter-self.prange, self.pcenter+self.prange, self.step)
epochs = int(self.textEdit_7.toPlainText())
self.graphicsView.addLegend()
self.graphicsView_2.addLegend()
self.graphicsView.showGrid(x = True, y = True, alpha = 1.0)
self.graphicsView_2.showGrid(x = True, y = True, alpha = 1.0)
for e in range(epochs):
for tr in range(50):
self.Train()
app.processEvents()
if not self.flag:
break
self.graphicsView.clear()
self.graphicsView.plot(period, self.func(period),pen=pg.mkPen('g',width=3),name = 'Исходная функция f(x):'+self.textEdit_6.toPlainText())
rand_set = np.random.random(self.set_count)*2*self.prange-self.prange+self.pcenter
result_set=np.zeros(100)
MSEe = []
for x in range(0, self.set_count-1):
result_set[x] = self.myNN.predict([rand_set[x]])
MSEe.append(np.mean(self.func(rand_set[x]) - result_set[x])**2)
self.graphicsView.plot([rand_set[x]],[result_set[x]], pen=(1,2),symbol='o')
app.processEvents()
self.graphicsView_2.clear()
self.graphicsView_2.plot(MSEe,pen=pg.mkPen('b',width=3),name='MSE(график среднеквадратич. ошибки)')
if not self.flag:
break
def closeEvent(self, event):
reply = QMessageBox.question\
(self, 'Информация',
"Вы уверены, что хотите уйти?",
QMessageBox.Yes,
QMessageBox.No)
if reply == QMessageBox.Yes:
self.flag = False
event.accept()
else:
event.ignore()
if __name__ == "__main__":
import sys
app = QtWidgets.QApplication(sys.argv)
w = MainWindow()
w.show()
sys.exit(app.exec_())