main_diabetics.py

import sys
from PyQt6 import QtWidgets,QtGui
from pyqtgraph import PlotWidget, plot
import pyqtgraph as pg

from PyQt6.QtWidgets import QWidget,QHBoxLayout, QApplication,QSlider, QMainWindow,QLabel, QPushButton,QHBoxLayout, QVBoxLayout, QGridLayout, QCheckBox
from PyQt6.QtCore import Qt
from PyQt6.QtGui import QAction, QIcon,QPalette, QColor

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


import matplotlib
import matplotlib.pyplot as plt
from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
matplotlib.use('Qt5Agg')

from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn import svm
from sklearn.metrics import accuracy_score

from PyQt6 import QtGui


diabetes = pd.read_csv('diabetes_clean_03042021.csv')


# highest correlation ----   x=age y=blood pressure


class MplCanvas(FigureCanvas):

    def __init__(self, parent=None, width=5, height=2, dpi=100):
        self.figure = Figure(figsize=(width, height), dpi=dpi)
        self.axes = self.figure.add_subplot(111)
        super(MplCanvas, self).__init__(self.figure)

class secondWindow(QMainWindow):
    def __init__(self):
        super().__init__()
        # use global data

        global diabetes
        
        widget_histogram = QWidget()

        # Vertical Layout
        histogram_layout = QVBoxLayout()
        
        # Create a new Canvas
        self.histogram_screen = MplCanvas(self, width=5, height=2, dpi=100)

        diabetes.hist(ax=self.histogram_screen.axes)
 
        histogram_layout.addWidget(self.histogram_screen)
        self.setCentralWidget(widget_histogram)
        widget_histogram.setLayout(histogram_layout)
        self.setMinimumSize(1500, 1000)


class thirdWindow(QMainWindow):

    def __init__(self):
        super().__init__()

        global diabetes

        self.graphWidget = pg.PlotWidget()
        self.setCentralWidget(self.graphWidget)

        self.x = diabetes["BMI"]
        self.y = diabetes["Outcome"]


        self.graphWidget.setBackground('w')
        self.graphWidget.setLabel("left", "Diabetic Or Not Diabetic")
        self.graphWidget.setLabel("bottom", "BMI")

        pen = pg.mkPen(color=(255, 0, 0))
        self.data_line =  self.graphWidget.plot(self.x, self.y, pen=pen)
        self.setMinimumSize(800, 400)


class MainWindow(QMainWindow):

    def design(self):

        layout3 = QHBoxLayout()
        MainLayout = QHBoxLayout()
        leftVerticalLayout = QVBoxLayout()
        RightVerticalLayout = QVBoxLayout()
        
         
        # setting window icon
        self.setWindowIcon(QtGui.QIcon('health.png'))
        #setting screen min size
        self.setMinimumSize(1200, 800)

        mainLabel = QLabel(" Women Diabetics Prediction System")
        leftVerticalLayout.addWidget(mainLabel)

        
        
        # checkbox button pregnancies
        pregnanciesLabel = QLabel("Pregnancies", alignment=Qt.AlignmentFlag.AlignCenter)
        pregnant_instruction = QLabel("Please click the box if Pregnant.", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(pregnanciesLabel)
        leftVerticalLayout.addWidget(pregnant_instruction)
        self.pregnancies_checkbox = QCheckBox(text="Not Pregnant")
        leftVerticalLayout.addWidget(self.pregnancies_checkbox)
        self.pregnancies_checkbox.stateChanged.connect(self.Pregnancies_onStateChanged)

        # Silder button  glucose 
        self.Glucose = QSlider(Qt.Orientation.Horizontal)
        self.Glucose.setMinimum(30)
        self.Glucose.setMaximum(200)
        self.Glucose.valueChanged.connect(self.updateSlider_Glucose)
        self.Glucose.setGeometry(5, 3, 20, 20)
        self.selectedValue_glucose = QLabel(self)
        self.selectedValue_glucose.setText(str(30))
        glocoseLabel = QLabel("Glucose [30 - 200]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(glocoseLabel)
        leftVerticalLayout.addWidget(self.Glucose)
        leftVerticalLayout.addWidget(self.selectedValue_glucose)


        # Silder button  blood pressure 
        self.BloodPressure = QSlider(Qt.Orientation.Horizontal)
        self.BloodPressure.setMinimum(30)
        self.BloodPressure.setMaximum(120)
        self.BloodPressure.valueChanged.connect(self.updateSlider_BloodPressure)
        self.BloodPressure.setGeometry(5, 3, 20, 20)
        self.selectedValue_blood = QLabel(self)
        self.selectedValue_blood.setText(str(30))
        bloodpressureLabel = QLabel("Blood Pressure [30 - 120]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(bloodpressureLabel)
        leftVerticalLayout.addWidget(self.BloodPressure)
        leftVerticalLayout.addWidget(self.selectedValue_blood)


        # Silder button  skin thickness 
        self.SkinThickness = QSlider(Qt.Orientation.Horizontal)
        self.SkinThickness.setMinimum(0)
        self.SkinThickness.setMaximum(100)
        self.SkinThickness.valueChanged.connect(self.updateSlider_skinThickness)
        self.SkinThickness.setGeometry(5, 3, 20, 20)
        self.selectedValue_skin = QLabel(self)
        self.selectedValue_skin.setText(str(0))
        skinThicknessLabel = QLabel("Skin Thickness[0 - 100]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(skinThicknessLabel)
        leftVerticalLayout.addWidget(self.SkinThickness)
        leftVerticalLayout.addWidget(self.selectedValue_skin)


        # Silder button  Insulin 
        self.Insulin = QSlider(Qt.Orientation.Horizontal)
        self.Insulin.setMinimum(5)
        self.Insulin.setMaximum(700)
        self.Insulin.valueChanged.connect(self.updateSlider_insulin)
        self.Insulin.setGeometry(5, 3, 20, 20)
        self.selectedValue_insulin = QLabel(self)
        self.selectedValue_insulin.setText(str(5))
        insulinLabel = QLabel("Insulin [5 - 700]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(insulinLabel)
        leftVerticalLayout.addWidget(self.Insulin)
        leftVerticalLayout.addWidget(self.selectedValue_insulin)




        # Silder button  BMI
        self.BMI = QSlider(Qt.Orientation.Horizontal)
        self.BMI.setMinimum(10)
        self.BMI.setMaximum(80)
        self.BMI.valueChanged.connect(self.updateSlider_BMI)
        self.BMI.setGeometry(5, 3, 20, 20)
        self.selectedValue_BMI = QLabel(self)
        self.selectedValue_BMI.setText(str(10))
        bmiLabel = QLabel("BMI [10 - 80]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(bmiLabel)
        leftVerticalLayout.addWidget(self.BMI)
        leftVerticalLayout.addWidget(self.selectedValue_BMI)


        # Silder button  DiabetesPredegreeFunction
        self.DiabetesPredegreeFunction = QSlider(Qt.Orientation.Horizontal)
        self.DiabetesPredegreeFunction.setMinimum(0)
        self.DiabetesPredegreeFunction.setMaximum(4)
        self.DiabetesPredegreeFunction.setTickInterval(4)
        self.DiabetesPredegreeFunction.valueChanged.connect(self.updateSlider_dibeticsPredegree)
        self.DiabetesPredegreeFunction.setGeometry(5, 3, 20, 20)
        self.selectedValue_predegree = QLabel(self)
        self.selectedValue_predegree.setText(str(0))
        label7 = QLabel("Diabetes Predegree Func [0 - 4]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(label7)
        leftVerticalLayout.addWidget(self.DiabetesPredegreeFunction)
        leftVerticalLayout.addWidget(self.selectedValue_predegree)



        # Silder button  Age
        self.age = QSlider(Qt.Orientation.Horizontal)
        self.age.setMinimum(18)
        self.age.setMaximum(150)
        self.age.valueChanged.connect(self.updateSlider_Age)
        self.age.setGeometry(5, 3, 20, 20)
        self.selectedValue_age = QLabel(self)
        self.selectedValue_age.setText(str(18))
        label8 = QLabel("Age [18 - 150]", alignment=Qt.AlignmentFlag.AlignCenter)
        leftVerticalLayout.addWidget(label8)
        leftVerticalLayout.addWidget(self.age)
        leftVerticalLayout.addWidget(self.selectedValue_age)


        # Push button  Predict
        self.predict = QPushButton("Predict")
        leftVerticalLayout.addWidget(self.predict)
        self.predict.clicked.connect(self.predictiveSystem)
        self.predictedValue = QLabel(" Prediction: None", self)
        leftVerticalLayout.addWidget(self.predictedValue)


        ####----------------Main Window Graph ------------
    
        self.setWindowTitle('Women Diabetics Prediction')

        x = diabetes["Age"]
        y = diabetes["Glucose"]
        

        fig = Figure()
        ax =fig.add_subplot(111)
     
        ax.set_title('Glucose Levels Across Age:Predicting Diabetes Risk.')
        x_label= ax.set_xlabel('Age')
        y_label = ax.set_ylabel('Glucose')
        
        #ax.bar(x,y)
        ax.bar(x,y)
        graph =FigureCanvas(fig)


        ###--------Connecting (all the buttons to left vertical layout) & (graph to the right vertical layout)
        RightVerticalLayout.addWidget(graph)
        MainLayout.addLayout(leftVerticalLayout) 
        MainLayout.addLayout(RightVerticalLayout)
        
       
        mainWidget = QWidget()
        mainWidget.setLayout(MainLayout)
        self.setCentralWidget(mainWidget)




       

        # menu

        # action 1 from menu
        self.window2 = None 
        histogram_action = QAction(QIcon("chart-medium.png"), "Histogram", self)
        histogram_action.setStatusTip("View Histogram.")
        histogram_action.triggered.connect(self.show_hist_window)

        # action 2 from menu
        self.window3 = None 
        plot_action = QAction(QIcon("plot.png"), "Plot Graph", self)
        plot_action.setStatusTip("Real Time Graph")
        plot_action.triggered.connect(self.show_realTime_window)

        menu = self.menuBar()
        file_menu = menu.addMenu("&Menu")
        file_menu.addAction(histogram_action)
        file_menu.addAction(plot_action)




    def Pregnancies_onStateChanged(self):
        if self.pregnancies_checkbox.isChecked():
            self.pregnancies_checkbox.setText("Pregnant")
        else:
            self.pregnancies_checkbox.setText("Not Pregnant") 

    def updateSlider_pregnancies(self):
        val = self.pregnancies.value()
        self.selectedValue_preg.setText(str(val))
    def updateSlider_Glucose(self):
        val = self.Glucose.value()
        self.selectedValue_glucose.setText(str(val))
    def updateSlider_BloodPressure(self):
        val = self.BloodPressure.value()
        self.selectedValue_blood.setText(str(val))
    def updateSlider_skinThickness(self):
        val = self.SkinThickness.value()
        self.selectedValue_skin.setText(str(val))
    def updateSlider_insulin(self):
        val = self.Insulin.value()
        self.selectedValue_insulin.setText(str(val))
    def updateSlider_BMI(self):
        val = self.BMI.value()
        self.selectedValue_BMI.setText(str(val))
    def updateSlider_dibeticsPredegree(self):
        val = self.DiabetesPredegreeFunction.value()
        self.selectedValue_predegree.setText(str(val))
    def updateSlider_Age(self):
        val = self.age.value()
        self.selectedValue_age.setText(str(val))

    def show_hist_window(self):
        if self.window2 is None:
            self.window2 = secondWindow()
        self.window2.show()

    def show_realTime_window(self):
        if self.window3 is None:
            self.window3 = thirdWindow()
        self.window3.show()

    def generateData(self):
        global diabetes
        self.diabetes = pd.read_csv('diabetes_clean_03042021.csv')
        print("self.diabetes.head(8):")
        print(self.diabetes.head(10))
        print("self.diabetes.tail(5): ")
        print(self.diabetes.tail(5))
        print("self.diabetes.info():")
        print(self.diabetes.info())

        # number of rows and columns
        print("Rows: ", self.diabetes.shape[0])
        print("Columns: ", self.diabetes.shape[1])
        print("self.diabetes.describe(): ")
        print(self.diabetes.describe())
        print("Total Diabetic(1) and Non-diabetic(0) patient:", self.diabetes['Outcome'].value_counts())
        print("[Mean] grouped by diabetic(1) and Non-diabetic(0) patient: ")
        print(self.diabetes.groupby('Outcome').mean())

        # ----------- Machine learning ------
        print("-----Training data-----")
        x = self.diabetes.drop(columns='Outcome', axis=1)  # data
        y = self.diabetes['Outcome']  # model

        # Data Standardization
        self.scaler = StandardScaler()
        self.scaler.fit(x)
        standardized_data = self.scaler.transform(x)
        # print(standardized_data)

        x = standardized_data  # data
        y = self.diabetes['Outcome']  # model

        # Train Test Split
        x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)
        # test_size = 0.20 means 20% test data  and 80% train data

        # print(x.shape, x_train.shape, x_test.shape)

        # Training The Model with SVM Algorithm
        self. svm_classifier = svm.SVC(kernel='linear')
        # training the support vector machine classifier
        self.svm_classifier.fit(x_train, y_train)

        # Accuracy Check
        # Train Data
        x_train_prediction = self.svm_classifier.predict(x_train)
        training_data_accuracy = accuracy_score(x_train_prediction, y_train)
        print("Accuracy Score of the training data: ", training_data_accuracy)

        # Test data
        x_test_prediction = self.svm_classifier.predict(x_test)
        test_data_accuracy = accuracy_score(x_test_prediction, y_test)
        print("Accuracy Score of the testing data: ", test_data_accuracy)


        # correlation ---- highest  x=age y=blood pressure
        corr_matrix = self.diabetes.corr()
        print("self.diabetes.corr(): ", corr_matrix)
        
        if (x_test_prediction[0] == 0):
            result = print("The person is not diabetic. ")
        else:
            result = print("The person is diabetic. ")

    # calculating the values for the predictive System
    def predictiveSystem(self):
        global result
        from random import randint
        count = randint(0, 767)
        
        # converting checkbox value into  0 or 1
        if self.pregnancies_checkbox.isChecked() == True:
            pregnancies_checkbox = 1
        else:
            pregnancies_checkbox = 0

        Glucose = self.Glucose.value()
        BloodPressure =self.BloodPressure.value()
        SkinThickness = self.SkinThickness.value()
        Insulin = self.Insulin.value()
        bmi = self.BMI.value()
        DiabetesPedigreeFunction = self.DiabetesPredegreeFunction.value()
        Age = self.age.value()

        # inputData = [value,1, 110, 92, 0, 0, 37.6,0.191, 30]
        sampleData = [count, pregnancies_checkbox, Glucose, BloodPressure, SkinThickness, Insulin, bmi, DiabetesPedigreeFunction,
                      Age]

        # change the input data to numpy array
        sampleData_numpy = np.asarray(sampleData)

        # reshaping array as we are predicting for one instance
        reshaping = sampleData_numpy.reshape(1, -1)

        # standardize the input data
        standardize_sampleData = self.scaler.transform(reshaping)
        # print(std_data)

        prediction = self.svm_classifier.predict(standardize_sampleData)
        print(prediction)
        if (prediction[0] == 0):
            
            self.predictedValue.setText("Prediction: The person is not diabetic. ")
        else:
            
            self.predictedValue.setText("Prediction: The person is  diabetic. ")




if __name__ == '__main__':
        app = QApplication(sys.argv)
        
        with open("style.css", "r") as file:
            app.setStyleSheet(file.read())
            
        window = MainWindow()
        #window.setFixedSize(1200,800)
        
   
        window.design()
        window.generateData()

        window.show()

        sys.exit(app.exec())