def example3():
""" SE rate for Silicon to air semi-infinite half spaces."""
# """Plot leaky and guided SE rates and then sum for randomly orientated dipole."""
lam0 = 1540
# Create structure
st = SPE()
st.add_layer(0.5 * lam0, 1.45)
st.add_layer(100, 1.65)
st.add_layer(500, 1.45)
st.add_layer(0.5 * lam0, 1)
st.set_vacuum_wavelength(lam0)
st.info()
# Calculate
res = st.calc_spe_structure(th_pow=11)
z = res['z']
# Convert z into z/lam0 and center
z = st.calc_z_to_lambda(z)
# ------- Plots -------
# Plot data
fig, ax1 = plt.subplots()
if st.supports_guiding():
ax1.plot(z, res['leaky']['avg'] + res['guided']['avg'], label='Avg')
ax1.plot(z,
res['leaky']['parallel'] + res['guided']['parallel'],
'--',
label=r'$\parallel$')
ax1.plot(z,
res['leaky']['perpendicular'] +
res['guided']['perpendicular'],
'-.',
label=r'$\bot$')
else:
ax1.plot(z, res['leaky']['avg'], label='Avg')
ax1.plot(z, res['leaky']['parallel'], '--', label=r'$\parallel$')
ax1.plot(z, res['leaky']['perpendicular'], '-.', label=r'$\bot$')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z [$\lambda$]')
ax1.legend(fontsize='small')
ax1.set_ylim(0, ax1.get_ylim()[1])
bounds = ax1.get_ylim()
# Draw rectangles for the refractive index
ax2 = ax1.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.15)
ax2.add_patch(rect) # Note: add to ax1 so that zorder has effect
ax2.set_ylabel('n')
ax2.set_ylim(bounds)
ax1.set_zorder(ax2.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
ax1.set_xlim([min(z), max(z)])
if SAVE:
plt.savefig('../Images/Air')
plt.show()
def example1():
""" SE rate for Silicon to air semi-infinite half spaces."""
from lifetmm.SPE import SPE
import pandas as pd
from lifetmm.Materials import n_1540nm as sample
"""Plot leaky and guided SE rates and then sum for randomly orientated dipole."""
# Load Sample Data
df = pd.read_csv('../Data/Screening.csv', index_col='Sample ID')
n = df.loc[sample]['n']
d = df.loc[sample]['d'] * 1e3 # in nm not um
chip = {'Sample ID': sample, 'n': n, 'd': d}
# Create Structure
st = SPE()
st.set_vacuum_wavelength(lam0)
st.add_layer(d_clad * lam0, n_dict['SiO2'])
st.add_layer(chip['d'], chip['n'])
st.add_layer(d_clad * lam0, n_dict['Air'])
st.info()
# Calculate
res = st.calc_spe_structure(th_pow=11)
z = res['z']
z = st.calc_z_to_lambda(z)
# ------- Plots -------
fig, (ax1, ax2) = plt.subplots(2, 1, sharex='col', sharey='none')
ax1.plot(z, res['leaky']['avg'])
if st.supports_guiding():
ax2.plot(z, res['guided']['avg'])
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_xlabel('Position z ($\lambda$)')
ax1.set_title('Leaky')
ax2.set_title('Guided')
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
ax2.axvline(x=zb, color='k', lw=2)
# Draw rectangles for the refractive index
ax1b = ax1.twinx()
ax2b = ax2.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.2)
ax1b.add_patch(rect)
ax1b.set_ylabel('n')
ax1b.set_ylim(0, 1.5 * max(st.n_list.real))
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.2)
ax2b.add_patch(rect)
ax2b.set_ylabel('n')
ax2b.set_ylim(0, 1.5 * max(st.n_list.real))
ax1.set_zorder(ax1b.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
ax2.set_zorder(ax2b.get_zorder() + 1) # put ax1 in front of ax2
ax2.patch.set_visible(False) # hide ax1'canvas'
if SAVE:
plt.savefig('../Images/{}_individual'.format(chip['Sample ID']))
fig, ax1 = plt.subplots()
if st.supports_guiding():
ax1.plot(z, res['leaky']['avg'] + res['guided']['avg'], label='Avg')
else:
ax1.plot(z, res['leaky']['avg'], label='Avg')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z ($\lambda$)')
ax1.legend()
# Draw rectangles for the refractive index
ax2 = ax1.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.15)
ax2.add_patch(rect) # Note: add to ax1 so that zorder has effect
ax2.set_ylabel('n')
ax2.set_ylim(0, 1.5 * max(st.n_list.real))
ax1.set_zorder(ax2.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
if SAVE:
plt.savefig('../Images/{}_total'.format(chip['Sample ID']))
plt.show()