def plot_distribution(E, H, nx, x, lamda, filename):
rgb = w2rgb.wavelength_to_rgb(lamda * 1e9, gamma=1)
plt.rcParams.update({'font.size': 18})
fig, ax1 = plt.subplots(figsize=(10.0, 4.0))
ax1.plot(np.asarray(x) / 1e-9, E, color=rgb, linewidth=3, label='$|E|^2$')
ax1.plot(np.asarray(x) / 1e-9,
H,
color='gray',
linewidth=2,
linestyle='--',
label='$|H|^2$')
ax1.set_ylim(0)
plt.legend()
ax2 = ax1.twinx()
nx = np.squeeze(nx)
ax2.fill_between(np.asarray(x) / 1e-9,
np.squeeze(np.abs(nx)),
np.zeros(len(nx)) + np.min(np.abs(nx)) - 0.1,
color='cy')
ax2.set_ylim(np.min(np.abs(nx)) - 0.1, np.max(np.abs(nx) + 0.5))
ax1.set_xlabel('distance [nm]')
ax1.set_ylabel('normalized [a.u.]')
ax2.set_ylabel('refractive index', color=(0, 0.8, 0.8))
plt.xlim(x[0] / 1e-9, x[-1] / 1e-9)
plt.title('$\lambda : $' + str(np.around(lamda * 1e9, 3)) + ' nm')
plt.tight_layout()
ax1.set_zorder(ax2.get_zorder() + 1)
ax1.patch.set_visible(False)
plt.savefig(filename + '.png')
mf.save_fig(fig, filename)
plt.clf()
def read_and_plot_refractive_index_spectrum(filename):
# this method reads a specific file format for refractive index spectrum.
# it has the following format
# line 1: (it is passed - you can put here any comments you have)
# line 2: 0.5, 1, 1 (the first element is wavelength in um and the 2nd and 3rd is real and imag of refractive index)
# ...
#(this is the format given by the website for .csv file : https://refractiveindex.info/)
# be careful : some data donot have real and imaginary in the same wavelength. You need to prepare the file accordingly.
f = open(filename)
name = filename.split('\\')[-1]
name = name.split('.')[0]
f = open(filename)
f.readline()
mat_lamda = []
mat_n = []
complex_n = True
for line in f:
mat_lamda.append(np.float(line.split(',')[0]) * 1e-6)
try:
mat_n.append(
np.float(line.split(',')[1]) +
1j * np.float(line.split(',')[2]))
except IndexError:
mat_n.append(np.float(line.split(',')[1]))
complex_n = False
mat_lamda = np.asarray(mat_lamda)
plt.rcParams.update({'font.size': 15})
fig, ax = plt.subplots(figsize=(6.0, 4.0))
plt.plot(mat_lamda / 1e-9,
np.real(mat_n),
'-o',
color='darkred',
linewidth=3,
label='$n$')
if complex_n:
plt.plot(mat_lamda / 1e-9,
np.imag(mat_n),
'-o',
color='k',
linewidth=3,
label='$\kappa$')
# #fmat = interp1d(mat_lamda, mat_n)
# plt.plot(np.linspace(mat_lamda[0],mat_lamda[-1],1000)/1e-9,np.imag(fmat(np.linspace(mat_lamda[0],mat_lamda[-1],1000))), '-o')
plt.xlim(mat_lamda[0] / 1e-9, mat_lamda[-1] / 1e-9)
plt.grid()
plt.xlabel('wavelength [nm]')
plt.ylabel("refractive index $n_{c} = n + j \kappa$")
plt.title(name)
plt.legend()
plt.tight_layout()
mf.save_fig(fig, '..\\PLOTS\\refractive_indices\\' + name)
n_mat = [mat_lamda, mat_n]
return n_mat
def plot_spectrum(T, R, lamdas, filename):
# T = np.asarray(T)
plt.rcParams.update({'font.size': 18})
fig, ax = plt.subplots(figsize=(6.0, 4.0))
plt.grid(zorder=20)
plt.plot(lamdas / 1e-9, T, 'darkred', linewidth=2)
plt.fill_between(lamdas / 1e-9,
T,
np.zeros(len(T)),
color='darkred',
linewidth=2,
zorder=10,
label='T')
plt.plot(lamdas / 1e-9, R + T, 'k', linestyle='--', label='T + R')
plt.xlim(lamdas[0] / 1e-9, lamdas[-1] / 1e-9)
plt.xlabel('wavelength [nm]')
plt.ylabel('normalized intenstiy')
#plt.legend(loc = 'best')#, bbox_to_anchor=(1.5, 1, 0, 0) )
plt.ylim(0, 1 + 0.05)
plt.tight_layout()
plt.savefig(filename + 'T.png')
mf.save_fig(fig, filename + 'T')
plt.clf()
plt.rcParams.update({'font.size': 18})
fig, ax = plt.subplots(figsize=(6.0, 4.0))
plt.grid(zorder=20)
plt.plot(lamdas / 1e-9, R, 'darkgreen', linewidth=2)
plt.fill_between(lamdas / 1e-9,
R,
np.zeros(len(T)),
color='darkgreen',
linewidth=2,
zorder=10,
label='R')
# plt.plot(lamdas/1e-9, R+T ,'k',linestyle = '--', label = 'T + R')
plt.xlim(lamdas[0] / 1e-9, lamdas[-1] / 1e-9)
plt.xlabel('wavelength [nm]')
plt.ylabel('normalized intensity')
# plt.legend(loc = 'best')#, bbox_to_anchor=(1.5, 1, 0, 0) )
plt.ylim(0, 1 + 0.05)
plt.tight_layout()
plt.savefig(filename + 'R.png')
mf.save_fig(fig, filename + 'R')
plt.clf()