app.py

import joblib
import streamlit as st
import matplotlib.pyplot as plt
import pandas as pd
st.title('daylight')

@st.cache_resource
def models():
    model0=joblib.load('deskudi.json')
    model3=joblib.load( 'DGP.json')
    model4=joblib.load('RAMM5.json')
    model5=joblib.load( 'RAMMG.json')
    
    model6=joblib.load('Room ASE.json')
    model7=joblib.load('Room sDA.json')
    
    model8=joblib.load('Room UDI150 50.json')
    model9=joblib.load('Room UDI150-300 50.json')
    model10=joblib.load('Room UDI300-3000 50.json')
    model11=joblib.load('Room UDI3000 5.json')
    
    model12=joblib.load('time DGP0 34.json')
    model13=joblib.load('time DGP0 38.json')
    model14=joblib.load('time DGP0 45.json')
    return model0,model4, model5,model6,model7,model8,model9,model10,model11,model12,model13,model14
    
model0,model4, model5,model6,model7,model8,model9,model10,model11,model12,model13,model14=models()
st.sidebar.title('Inputs:')
st.sidebar.markdown('Fill all of the inputs')

st.sidebar.header('Dimention')

i1=st.sidebar.slider('Width',value=24)
i01=st.sidebar.slider('Depth',value=24)
i2=st.sidebar.slider( 'Win Width 1',value=10)
i3=st.sidebar.slider('Win Width 2')

i04=st.sidebar.slider('Altitude')
i4=st.sidebar.slider('Azimuth')


i5=st.sidebar.slider('Distance to façade')
i6=st.sidebar.slider('View direction')
i7=st.sidebar.slider('shading type')

desk=model0.predict([[i1,i01,i2,i3,i5,i7]])
#dgp=model3.predict([[i1,i01,i2,i3,i04,i4,i5,i6,i7]])
ramm5=model4.predict([[i1,i01,i2,i3,i04,i4,i5,i6,i7]])
rammg=model5.predict([[i1,i01,i2,i3,i04,i4,i5,i6,i7]])

ASE=model6.predict([[i1,i01,i2,i3,i7]])
SDA=model7.predict([[i1,i01,i2,i3,i7]])

UDI1=model8.predict([[i1,i01,i2,i3,i7]])
UDI2=model9.predict([[i1,i01,i2,i3,i7]])
UDI3=model10.predict([[i1,i01,i2,i3,i7]])
UDI4=model11.predict([[i1,i01,i2,i3,i7]])
   
DGP1=model12.predict([[i1,i01,i2,i3,i5,i6,i7]])
DGP2=model13.predict([[i1,i01,i2,i3,i5,i6,i7]])
DGP3=model14.predict([[i1,i01,i2,i3,i5,i6,i7]])	   
	   
output=[desk[0][1],desk[0][1],desk[0][2],ramm5[0],rammg[0],ASE[0],SDA[0],UDI1[0],UDI2[0],UDI3[0],UDI4[0],DGP1[0],DGP2[0],DGP3[0]]
df=pd.DataFrame(output,columns=['index'],index=['desk mean UDI150-300','desk mean UDI300-3000','desk mean UDI3000','RAMM5','RAMMG','Room ASE','Room sDA','Room UDI150 50','Room UDI150-300 50','Room UDI300-3000 50','Room UDI3000 5','time DGP0 34','time DGP0 38','time DGP0 45'])

st.write(df)