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- import numpy as np
- def evalDrudeParams(R, WLs):
- GammaB = 3.5 * 10**13
- Gamma = GammaB + ((1.4 * 10**6) / (R * 10**-9))
- w = (2 * np.pi * 3 * 1E8) / (WLs * 1E-9)
- wp = 1.4
- return w, wp, Gamma
- def eps_r(w, wp, Gamma):
- return 5 - (w**2 * (wp * 1E16)**2) / (w**4 - w**2 * Gamma**2)
- def eps_i(w, wp, Gamma):
- return (w * (wp * 1E16)**2 * Gamma) / (w**4 - w**2 * Gamma**2)
- def eps_drude(w, wp, Gamma):
- return eps_r(w, wp, Gamma) + 1j * eps_i(w, wp, Gamma)
- def get_d_params(WL_min, WL_max, d_param_filename):
- from_disk = np.loadtxt(d_param_filename[0])
- omega_star_ratio = from_disk[0, :]
- d_perp = from_disk[1, :] + 1j*from_disk[2, :]
- from_disk = np.loadtxt(d_param_filename[1])
- d_parl = from_disk[1, :] + 1j*from_disk[2, :]
- c = 299792458 # m/s
- h_reduced = 6.5821e-16 # eV s
- omega_p_star = 3.81 # eV
- # min_lim_omega_star_ratio = 0.87
- # max_lim_omega_star_ratio = 0.99
- d_perp_in, d_parl_in = [],[]
- WLs_nm = []
- om_rat_plot = []
- WL_d = 2*np.pi/((omega_star_ratio * omega_p_star/c)/h_reduced)*1e9 # nm
- for i in range(len(omega_star_ratio)):
- if WL_d[i] > WL_max:
- continue
- if WL_d[i] < WL_min:
- continue
- # om_star_rat = omega_star_ratio[i]
- # if (om_star_rat < min_lim_omega_star_ratio
- # or om_star_rat > max_lim_omega_star_ratio):
- # continue
- # om_rat_plot.append(om_star_rat)
- WLs_nm.append(WL_d[i])
- d_perp_in.append(d_perp[i])
- d_parl_in.append(d_parl[i])
- WLs_nm = np.array(WLs_nm)
- d_perp_in = np.array(d_perp_in)
- d_parl_in = np.array(d_parl_in)
- return WLs_nm, d_perp_in, d_parl_in
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