Delete src/test.py

src/test.py

@@ -1,116 +0,0 @@
-''''
-Author        : Rupesh Garsondiya
-github        : @Rupeshgarsondiya
-Organization  : L.J University
-
-'''
-
-import time
-import streamlit as st
-import pandas as pd
-import numpy as np
-from sklearn.preprocessing  import StandardScaler
-from train import *
-
-
-class test :
-    
-    def __init__(self):
-        pass
-    
-    def predict_data(self):
-        
-        st.sidebar.title("Select Parameter ")
-        mt = Model_Train()
-        S_algo,Pipeline = mt.train_model()
-        df = None
-        options = ["Google Pixel 5", "OnePlus 9", "Samsung Galaxy S21", "Xiaomi Mi 11",'iPhone 12']
-
-        selected_option = st.sidebar.selectbox("Select phone model :", options)
-
-        if selected_option in options:
-            encoded_model = [1 if  i == selected_option else 0 for i in options]
-            df = pd.DataFrame([encoded_model], columns=options)
-        
-
-
-        options1 = ["Android",'IOS']
-
-        
-        
-
-        if selected_option =='iPhone 12':
-            selected_option1 = st.sidebar.selectbox("Select  OS :", 'IOS')
-            encoded_os = [0,1]
-        else :
-            encoded_os = [1,0]
-            selected_option1 = st.sidebar.selectbox("Select  OS :", 'Android')
-        df[options1] = encoded_os
-        
-
-        options2 = ['Female','Male']
-        selected_option2 = st.sidebar.radio("Select Gender :", options2)
-        encoded_gender = [1 if  i == selected_option2 else 0 for i in options2]
-        df[options2] = encoded_gender
-
-
-        app_time = st.sidebar.number_input('Enter app time : ',min_value=0.0,max_value=24.0,value=0.0)
-        df['App_Time(hours/day)'] = app_time
-      
-
-        screen_time = st.sidebar.number_input('Enter your screen  time : ',min_value=0.0,max_value=24.0,value=0.0)
-        df['screen_Time(hours/day)'] = screen_time
-        
-
-        battary = st.sidebar.number_input('Enter battary drain(mAh) : ',min_value=100.0,max_value=6000.0,value=100.0)
-        df['Battery_Drain(mAh)'] = battary
-       
-
-        no_app = st.sidebar.number_input('Enter  number of apps installed : ',min_value=5.0,max_value=50.0,value=5.0)
-        df['Installed_app'] = no_app
-
-
-        data_use = st.sidebar.number_input('Enter  data usage (GB) : ',min_value=0.0,max_value=10.0,value=0.0)
-        df['Data_Usage(GB)'] = data_use
-
-        
-        age = st.sidebar.number_input('Enter your age : ',min_value=15.0,max_value=100.0,value=15.0)
-        df['Age'] = age
-        
-        if st.button("Submit"):
-            st.write("Processing...")
-            time.sleep(2)
-            prediction = S_algo.predict(df)
-            if prediction==1:
-
-                st.write('Output :  Occasional Users')
-            elif prediction==2:
-                 st.write('Output : Casual Users ')
-            elif prediction==3:
-                st.write('Output : content consumer : ')
-            elif prediction==4:
-               st.write('Output  :  Social Media Enthusiasts')
-            else :
-               st.write('Output  : Power Users')
-        
-        
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-        
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-      
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