QY Calculation

QYCal.py

"""
# date: Wed Mar 9 HKT 2022
# naming conventions: 'La.dat', 'Lb.dat', 'Lc.dat', 'Pb.dat', 'Pc.dat'
# package requirement: numpy, scipy, matplotlib
"""

import numpy as np
import matplotlib.pyplot as plt
from scipy import integrate

files = ['La.dat', 'Lb.dat', 'Lc.dat', 'Pb.dat', 'Pc.dat']
int_array = [0, 0, 0, 0, 0]
i = 0

for file in files:
    data = np.loadtxt(file, delimiter='\t', skiprows=1)
    xData, yData = np.hsplit(data, 2)
    y = yData.reshape((1, len(yData)))
    int_y = integrate.simps(y)
    int_array[i] = int_y[0]
    print(file.replace('.dat', '') + ' => ' + str(int_array[i]))
    i += 1
    plt.plot(xData, yData)

# https://doi.org/10.1002/adma.19970090308
A = 1 - (int_array[2]/int_array[1])
QY = (int_array[4]-(1-A)*int_array[3]) / (int_array[0] * A)

print('\nA  = 1 - (Lc/Lb)')
print('QY = [Pc - (1-A)*Pb] / [La * A]')
print('   = ' + str(QY * 100) + ' %')

plt.xlabel('Wavelength / nm')
plt.ylabel('PL counts / a.u.')
plt.yscale('log')
plt.legend(files)
plt.title('PLQY: ' + str(QY * 100) + ' %', {'color': 'red', 'fontsize': '18'})
plt.show()