EEG Hardware Predictive Maintenance (Python)

'''assessNet is a program designed to perform preventative maintenance
on nets used in EEG recordings.
must be run in the directory containing:
   exported RedCap session data (csv)
   net noise information (xlsx)
   warranty information (xlsx)
for orgranization all this information should always be kept in the same directory'''
#bc ┌( ಠ_ಠ)┘@thirdBrainPrograms
import sys
import matplotlib.pyplot as plt
import pandas as pd

#import data at beginning to speed processing
#add your file to be analyzed --> add .csv --> exported from RedCap
#analyzed in four week intervals
sessData = pd.read_csv(r'COBRAHardwareTrackin_DATA_2021-10-21_1606.csv')
#read in the netnoise data --> review in four week intervals
noiseData = pd.read_excel('COBRA_nets.xlsx', sheet_name='WeeklyNetNoise10.18_11.15')
#warranty info
data = pd.read_excel('COBRA_nets.xlsx', sheet_name='WarrantyInfo', nrows=12)
data = data.loc[:, ~data.columns.str.contains('^Unnamed')]
i=data[data['Expired']== 0]
#implement password protection
password = input("Enter a password to unlock the analysis: ")
if password != 'your password here':
    sys.exit()
else:
    print('\n')
    #third brain programs logo
    print('       ┌( ಠ_ಠ)┘')
    print('\n')
    print('WELCOME TO ASSESS-NET!!')
    print('\n')

while True:
    #session analysis pipeline
    #checks for general hardware performance over time for a single net
    #pick your cap --> assessNet imports all the session data for a particular EEG net
    #for the past four weeks
    x = sessData.loc[sessData['cap'] == input('Please enter the three letter cap identifier: ')]
    z = x['cap'].to_string(index=False)
    print("\n")
    print("SESSION")
    print("\n")
    #checks for first initial net noise stats
    print("The session net noise stats for the past four weeks for this cap are:")
    print(x['netnoisnum'].to_string(index=False))
    print("\n")
    #these next three metrics are meant to check net degradation over time
    #during the course of the experiment.
    #checks the first impendance
    print("The first timepoint impedance stats for the past four weeks for this cap are:")
    print(x['firstimpbad'].to_string(index=False))
    print("\n")
    #checks the second impendance
    print("The second timepoint impedance stats for the past four weeks for this cap are:")
    print(x['secondimpbad'].to_string(index=False))
    print("\n")
    #checks the third impendance
    print("The third timepoint impedance stats for the past four weeks for this cap are:")
    print(x['thirdimpbad'].to_string(index=False))
    print("\n")
    #any bad channels noted in net log?
    print("The bad channels for the past four weeks for this cap are:")
    print(x['chan'].to_string(index=False))
    print("\n")

    #results of cumulative weekly testing --> baseline net noise tests
    #for the past four weeks
    y = noiseData.loc[noiseData['Net'] == z]
    print("\n")
    print("NET NOISE")
    print("\n")
    print("The cumulative questionable channels for the past four weeks for this net are: ")
    print("\n")
    print(y['Cumulative Channels'].to_string(index=False))
    print("\n")
    print("The cumulative bad channels for the past four weeks for this net are: ")
    print("\n")
    print(y['Bad Channels'].to_string(index=False))
    print("\n")

    #todo --> put in the ratio of cumulative channels / 128
    #and bad channels / 128 as two pie charts that will
    #pop up when the user executes the code for a given net
    #get the data
    questionableCh = y['Cumulative Count'].to_string(index=False)
    badCh = y['Bad Count'].to_string(index=False)
    #change to int for chart
    questInt = int(questionableCh)
    badInt = int(badCh)
    goodChannels = 128 - (questInt + badInt)
    #create the piechart
    pieLabels = ['Number of Questionable Channels : ' + str(questInt), 'Number of Bad Channels: ' + str(badInt), 'Number of Good Channels: ' + str(goodChannels)]
    pieData = [questInt, badInt, goodChannels]
    plt.pie(pieData, labels = pieLabels)
    plt.legend(loc="upper left")
    plt.show()

    #ask user if they want to get more net stats
    anotherNet = input('Would you like to check another net (Yes or No): ')
    if anotherNet.lower() == ('no'):
        break
    else:
        continue

#warranty reminder at the end --> reminds the user of nets still
#within the warranty timeframe
print('\n')
print('As a reminder, these nets are still under warranty: ')
print('\n')
print(i.to_string(index=False))