In [1]:
from numpy import *
In [2]:
from scipy import interpolate
In [3]:
import matplotlib.pyplot as plt
In [4]:
f = genfromtxt("oled-flux.dat", delimiter=",")
In [5]:
total_power = sum(f[:,1:6],axis=1)
In [6]:
glass_power = f[:,7]
In [7]:
waveguide_power = sum(f[:,8:11],axis=1)
In [8]:
glass = glass_power/total_power
In [9]:
waveguide = waveguide_power/total_power
In [10]:
aluminum = 1-glass-waveguide
In [11]:
lambdas_linear = linspace(0.4,0.8,100)
In [12]:
lambdas = 1/f[:,0]
In [13]:
g_linear = interpolate.interp1d(lambdas,glass,kind='cubic')
In [14]:
w_linear = interpolate.interp1d(lambdas,waveguide,kind='cubic')
In [15]:
a_linear = interpolate.interp1d(lambdas,aluminum,kind='cubic')
In [16]:
glass_linear = g_linear(lambdas_linear)
In [17]:
waveguide_linear = w_linear(lambdas_linear)
In [18]:
aluminum_linear = a_linear(lambdas_linear)
In [19]:
plt.plot(lambdas_linear,glass_linear,'b-',label='glass');
In [20]:
plt.plot(lambdas_linear,waveguide_linear,'r-',label='organic + ITO');
In [21]:
plt.plot(lambdas_linear,aluminum_linear,'g-',label='aluminum');
In [22]:
plt.xlabel("wavelength (um)"); plt.ylabel("fraction of total power");
In [23]:
plt.axis([0.4, 0.8, 0, 1]);
In [24]:
plt.xticks([t for t in arange(0.4,0.9,0.1)]);
In [25]:
plt.legend(loc='upper right');
In [26]:
plt.show()
In [27]:
print("glass: %0.6f (mean), %0.6f (std. dev.)" % (mean(glass_linear),std(glass_linear)))
glass: 0.091677 (mean), 0.022714 (std. dev.)
In [28]:
print("waveguide: %0.6f (mean), %0.6f (std. dev.)" % (mean(waveguide_linear),std(waveguide_linear)))
waveguide: 0.224012 (mean), 0.023975 (std. dev.)
In [29]:
print("aluminum: %0.6f (mean), %0.6f (std. dev.)" % (mean(aluminum_linear),std(aluminum_linear)))
aluminum: 0.684311 (mean), 0.044364 (std. dev.)