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import streamlit
import pickle
import numpy
# web app on your desktop local host
#run on your pycharm terminal ' streamlit run app.py '
# if using command window ensure the path is correct.. c:\users\idom...\pycharm..\machin learing>
# that is pionting to your python file
loaded_model = pickle.load(open('MWmodel.sav','rb'))
#create function to handle predicition
def microwave_fault_prediction (user_input_data):
#convert to array
Input_array = numpy.asarray(user_input_data)
Input_array_reshaped = Input_array.reshape(1, -1)
make_prediction = loaded_model.predict(Input_array_reshaped)
print(make_prediction) # make_prediction= [10], pos is 0
if make_prediction== 0:
return 'site is up'
elif make_prediction == 1:
return'site is down: fault: 1. inteference 2. misalignment 3. one of the odu is faulty'
elif make_prediction == 2:
return 'site is down: fault: 1. NO power at remote site(A),2.ODU offline remote site(A)(check alarm \'IF cable open\') '
elif make_prediction == 3:
return 'site is down: fault:1.ODu hunged at remote site(A), reset power at both sites(A,B)'
elif make_prediction == 4:
return 'site is down: fault: 1. cascaded cable faulty at hub Site (B), 2. ODU/IDU/If cable offline,at remote end'
elif make_prediction == 5:
return'site is down: fault: 1 ODU at hub site(B)degraded( reset ODU, reterminate IF cable,check alarm)'
elif make_prediction == 6:
return 'site is down: faulty: if power is okay, odu burnt at either remote site (A) OR (B)'
else: # do feature elimination for data irrelevant to outcome
return 'case 7: site status cannot be determined by RSL data'
#construct interface for user data input
def main():
#give a title
streamlit.title('microwave fault detection web app')
#get input data from user
RSLA = streamlit.number_input('Site A Local end: enter RSL of the site, it must be negative number, input zero for no supervision',min_value=-99, max_value=0, value=-30, step=1,key= 'rsla')
#key= 'rslb' is to distinguish two similar widgets 'text_input' in streamlit
RSLB = streamlit.number_input('Site B Remote end: enter RSL of the Hub site, it must be negative number, input zero for no supervision',min_value=-99, max_value=0, value=-30, step=1,key= 'rslb')
#code for prediction
detection ="" #declare this variable to hold result like empty list
#mylist = []
if streamlit.button('click here for fault prediction'):
detection=microwave_fault_prediction([RSLA,RSLB])
#convert inputs into a single parameter using list [1,2]
#microwave_fault_prediction ...call the function to process input
streamlit.success(detection)
if __name__ == '__main__':
main()
# web app on your desktop local host
#run on your pycharm terminal ' streamlit run microwaveAPP.py '
# if using command window ensure the path is correct.. c:\users\idom...\pycharm..\machin learing>
# that is pionting to your python file
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