Technex/ml.py at master · CaptainLazarus/Technex · GitHub

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import json
import os
import math
import pandas as pd
import numpy as np
import keras.models
from keras.layers import Dense
from keras.layers import LSTM
from keras.models import model_from_json


from tkinter import *
from tkinter.ttk import Combobox

from tkinter.filedialog import askopenfile

root = Tk()
root.geometry('1000x1000')


#Loads Model
def loadModel():
    with open('model.json','r') as f:
        model_json = json.load(f)
    model = model_from_json(json.dumps(model_json))
    model.load_weights('model.h5')
    return model


#Return Array for input of LSTM
def clean(fileName):
    params=[]
    # y=[]
    data = pd.read_csv(fileName , sep='|')
    data.drop(['EtCO2','Fibrinogen', 'Unit1', 'Unit2', 'BaseExcess', 'DBP', 'Hct', 'Hgb', 'PTT', 'WBC', 'pH','HCO3','FiO2', 'PaCO2', 'Platelets', 'Magnesium',  'Phosphate',  'Potassium', 'Bilirubin_total',  'TroponinI','SaO2', 'AST','BUN', 'Alkalinephos', 'Bilirubin_direct','Glucose','Lactate', 'Calcium',  'Chloride', 'Creatinine' ],axis = 1,inplace = True)

    data.dropna(thresh=data.shape[1]*0.40,how='all',inplace = True)
    # La_1 = data['SepsisLabel'].sum()
    # if La_1:
    #     y.append(1)
    # else:
    #     y.append(0)
    data.drop(['SepsisLabel'],axis = 1,inplace = True)
    data = data.apply(lambda x: x.fillna(x.median()),axis=0)
    data = data.fillna(0)
    if len(data) < 40:
        Pad = pd.DataFrame({'HR':0.0 ,'O2Sat':0.0, 'Temp':0.0 , 'SBP':0.0, 'MAP':0.0, 'Resp':0.0, 'Age':0.0, 'Gender': 0 ,'HospAdmTime':0.0, 'ICULOS':0}, index =[item for item in range(0,40-len(data))])
        data = pd.concat([Pad, data]).reset_index(drop = True)
    elif len(data) >40:
        data = data[len(data)-40::1]
    data = data.values
    params.append(data)
    return params


def open_file():
    file = askopenfile(mode ='r', filetypes =[('PSV Files', '*.psv')])
    if file is not None:
        Model = loadModel()
        print("Model Loaded")
        X_test = clean(file)
        print("OK")
        print(X_test)

        X_test = np.reshape(X_test,(1,40,10))

        y_pred = Model.predict(X_test)
        #print(y_pred)

        if (y_pred <= 0.2):
            print("no Sepsis")
        else:
            print("Sepsis Go to Hospital")

v0=IntVar()
v0.set(1)
r1 = Button(root, text ='Upload File ', command = lambda:open_file())
r1.place(x=200,y=50)
l1 = Label(root, text = "Sepsis")
l1.place(x=200,y=210)
e1 = Entry(root)
e1.place(x=200,y=240)
r1 = Button(root, text ='Download Report')
r1.place(x=200,y=400)


root.title('Sepsis Identification')
root.geometry("600x500+10+10")
root.mainloop()