Update app.py

app.py

@@ -1,47 +1,82 @@
+import joblib
 import streamlit as st
-from OpenGL.GL import *
-from OpenGL.GLU import *
-from PyQt5.QtWidgets import QApplication
-import sys
-
-class Cube:
-    def __init__(self):
-        self.vertices = ((1.0,-1,-1),(1,1,-1),(-1,1,-1),(-1,-1,-1),(1,-1,1),(1,1,1),(-1,-1,1),(-1,1,1))
-        self.edges = ((0,1),(0,3),(0,4),(1,2),(1,5),(2,3),(2,6),(3,7),(4,5),(4,7),(5,6),(6,7))
-        
-    def draw(self):
-        glBegin(GL_LINES)
-        for edge in self.edges:
-            for vertex in edge:
-                glVertex3fv(self.vertices[vertex])
-        glEnd()
-
-def main():
-    app = QApplication(sys.argv)
-    cube = Cube()
-    
-    st.set_option('dephrecation.showPyplotGlobalUse', False)
-    st.title("3D Cube")
-    
-    # Create an OpenGL context
-    gl_viewport = st_gl(GLsizei(st._get_metric_impl("devicePixelRatio") * 600), GLsizei(st._get_metric_impl("devicePixelRatio") * 600))
-    st_gl_make_current(gl_viewport)
-    
-    # Set up projection
-    gluPerspective(45, 1, 0.1, 50.0)
-    glTranslatef(0.0, 0.0, -5.0)
+import matplotlib.pyplot as plt
+import pandas as pd
+import plotly.express as px
+import numpy as np
+from geneticalgorithm import geneticalgorithm as ga
+
+
+
+
+st.title('Indoor temperature')
+
+
+ 
+model=joblib.load('temperature.json')
+st.sidebar.title('Inputs:')
+st.sidebar.header('Dimention')
+
+i1=st.sidebar.slider('Outdoor wind speed',value=10,min_value=1,max_value=20)
+i2=st.sidebar.slider('Outdoor wind direction',value=24)
+i3=st.sidebar.slider('Radiation')
+i4=st.sidebar.slider( 'Humidity',value=10)
+i5=st.sidebar.slider('Outdoor Drybulb temperature',value=10)
+i6=st.sidebar.radio('Window opening1',[0,1])
+i7=st.sidebar.radio('Window opening2',[0,1])
+i8=st.sidebar.slider('luminance',value=10)
+i9=st.sidebar.slider('T',value=10)
+st.sidebar.markdown("gas=1,propain=2,wood=3")
+i10=st.sidebar.selectbox("f_t1",[1,2,3])
+if i10=="gas":
+    i10=1
+elif i10=="propain":
+    i10=2
+elif i10=="wood":
+    i10=3
+elif i10=="electricity":
+    i10=5
+else:
+    i10=4
+st.header(i10)
+
+
+
+
+
+p=model.predict([[i1,i2,i3,i4,i5,i6,i7,i8,i9]])
+
+output=[p[0][0],p[0][1],p[0][2]]
+
+st.write(output)
+
+
+
+
+df=pd.DataFrame(output,columns=['Temperature'],index=['15th','30th','45th'])
+plot=pd.DataFrame({'Time':[15,30,45],'T':output})
+#graph
+fig=px.line(plot,x='Time',y='T')
+
+st.plotly_chart(fig)
+st.write(df)
+
+
+#optimization
+def f(X):
+    t= abs(22.5 - model.predict([[i1,i2,i3,i4,i5,X[0],X[1],i8,i9]])[0][0])
     
-    # Draw the cube
-    glEnable(GL_DEPTH_TEST)
-    while True:
-        for event in QApplication.instance().flushEvents():
-            if event.type() == QEvent.Close:
-                sys.exit()
-                
-        glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
-        cube.draw()
-        glRotatef(1, 1, 1, 1)
-        st_gl_swap(gl_viewport)
-        
-if __name__ == '__main__':
-    main()
+    return t
+
+
+button1=st.button('TAP to Suggestion!!')
+if button1:
+    varbound=np.array([[0,1]]*2)
+    with st.spinner('Wait for optimizing ...'):
+        optimization=ga(function=f,dimension=2,variable_type='int',variable_boundaries=varbound)
+        optimization.run()
+        st.write ('for next 15th minutes to reach thermal comfort Opening situation of the first window is  '+str(optimization.best_variable[0])+'    and Opening situation of the second window is   '+str(optimization.best_variable[1]))
+    r="optimized indoor temperature {}".format(round(model.predict([[i1,i2,i3,i4,i5,optimization.best_variable[0],optimization.best_variable[1],i8,i9]])[0][0],1))
+    st.success(r) 
+
+