Clover reflectance and transmittance spectrum

In [1]:

    

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

wv = np.arange(400, 2501)
fig, [axs1, axs2] = plt.subplots ( nrows=2, ncols=1, \
                                  sharex=True, sharey=True, \
                                 figsize=(10,10))
refl = np.loadtxt("data/LOPEX93/refl.001.dat").reshape((5,2101))
r_mean = refl.mean ( axis=0 )
r_std = refl.std ( axis=0 )
axs1.plot ( wv, r_mean, '-')
axs1.fill_between ( wv, r_mean-1.96*r_std, \
                  r_mean + 1.96*r_std, color="0.8")

trans = np.loadtxt("data/LOPEX93/trans.001.dat").reshape((5,2101))
t_mean = trans.mean ( axis=0 )
t_std = trans.std ( axis=0 )
axs2.plot ( wv, t_mean, '-', color="#66C2A5")
axs2.fill_between ( wv, t_mean-1.96*t_std, \
                  t_mean + 1.96*t_std, color="0.8")
axs2.set_xlim(400, 2500)
axs2.set_xlabel("Wavelength [nm]")
axs2.set_ylabel ("Transmittance [-]")
axs1.set_ylabel ("Reflectance [-]")
fig.savefig("LOPEX_clover_spectrum.png", dpi=200)


    

In [ ]: