#!/usr/bin/env python3 # -*- coding: UTF-8 -*- import numpy as np import matplotlib.pyplot as plt import os from scipy.special import hankel2 as H2n c = 299792458.0 eps_0 = 8.854187817e-12 # F/m pi = np.pi verbose = 6 # r of monitor r = 146.513e-9 #debug = True debug = False def read_data(dirname): data = {} WLs = [] for r,d,f in os.walk(dirname): for fname in f: WLs.append(fname) for fname in WLs: fdata = np.transpose( np.genfromtxt(dirname+"/"+fname, delimiter=", ",skip_header=1 ,dtype=None, encoding = None , converters={0: lambda s: complex(s), 1: lambda s: complex(s), 2: lambda s: complex(s.replace('i', 'j')), 3: lambda s: complex(s.replace('i', 'j')), 4: lambda s: complex(s.replace('i', 'j')), 5: lambda s: complex(s.replace('i', 'j')), 6: lambda s: complex(s.replace('i', 'j')), 7: lambda s: complex(s.replace('i', 'j')), 8: lambda s: complex(s.replace('i', 'j')) } ) ) data[float(fname[2:-4])]=fdata if debug: break return data def find_nearest(array,value): idx = (np.abs(array-value)).argmin() return array[idx],idx def get_WLs_idx(WLs, data): dist = 1 #mkm mmedia = 1 # vacuum shift = 1 # one mesh step WLs_idx = [] for wl in WLs: val, idx = find_nearest(data[dist][mmedia][shift][0,:],wl*1e-9) WLs_idx.append(idx) return WLs_idx # def check_field_match(data_in_air, data_in_gold,wl_idx,z_vec,kappa1,kappa2,eps2): # z = z_vec[i]*1e-9 # if verbose > 8: print("z =",z) # H1_0 = H1[i]/np.exp(-kappa1[wl_idx]*z) # H2_0 = H2[i]/np.exp(-kappa2[wl_idx]*z) # E1_0 = E1[i]/np.exp(-kappa1[wl_idx]*z) # E2_0 = E2[i]/np.exp(-kappa2[wl_idx]*z) # E2_0e = E2[i]/np.exp(-kappa2[wl_idx]*z)*eps2[wl_idx] # if verbose > 8: # print("H0 air (%5.4g %+5.4gj)"%(np.real(H1_0), np.imag(H1_0)), # " from H1 (%5.4g %+5.4gj)"%(np.real(H1[i]), np.imag(H1[i]))) def analyze(data,wl): # print(data[0,:]) # all z values #data = "z, dip.power, Ex, Ey, Ez, Hx, Hy, Hz, n_Au" # 0, 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 " lambd = wl omega = 2*pi*c/lambd eps_d = complex(1) # air, z>0 eps_m = data[8,0]**2 # metal, z<0 dip_power = data[1,0] z = data[0,:] idx_d = np.nonzero(z>1e-10) idx_0 = np.nonzero(np.logical_and(z<=1e-10, z>=-1e-10)) idx_m = np.nonzero(z<-1e-10) z_d = z[idx_d] z_0 = z[idx_0] z_m = z[idx_m] if (not np.array_equal(np.hstack((z_m, z_0, z_d)), z)): print("ERROR! loosing z values!") raise Ex = data[2,:] Ex_m = data[2,idx_m][0] Ey_m = data[3,idx_m][0] Ez_m = data[4,idx_m][0] Hx_m = data[5,idx_m][0] Hy_m = data[6,idx_m][0] Hz_m = data[7,idx_m][0] E_m = np.transpose(np.array([Ex_m,Ey_m,Ez_m])) H_m = np.transpose(np.array([Hx_m,Hy_m,Hz_m])) Ex_d = data[2,idx_d][0] Ey_d = data[3,idx_d][0] Ez_d = data[4,idx_d][0] Hx_d = data[5,idx_d][0] Hy_d = data[6,idx_d][0] Hz_d = data[7,idx_d][0] E_d = np.transpose(np.array([Ex_d,Ey_d,Ez_d])) H_d = np.transpose(np.array([Hx_d,Hy_d,Hz_d])) k_0 = omega/c #air k_sp = k_0*np.sqrt(eps_d*eps_m/(eps_d+eps_m)) # eq5, supmat chi_d = np.sqrt( eps_d*k_0**2 - k_sp**2 ) # desc. after eq6c, supmat chi_m = np.sqrt( eps_m*k_0**2 - k_sp**2 ) # desc. after eq6c, supmat h_sp_d = np.exp(1j*chi_d*z_d) # eq6a, supmat e_sp_x_d = chi_d/(omega*eps_0*eps_d)*np.exp(1j*chi_d*z_d) # eq6b, supmat e_sp_z_d = k_sp/(omega*eps_0*eps_d)*np.exp(1j*chi_d*z_d) # eq6c, supmat h_sp_m = np.exp(1j*-chi_m*z_m) # eq6a, supmat e_sp_x_m = -chi_m/(omega*eps_0*eps_m)*np.exp(1j*-chi_m*z_m) # eq6b, supmat e_sp_z_m = k_sp/(omega*eps_0*eps_m)*np.exp(1j*-chi_m*z_m) # eq6c, supmat zero_m = np.zeros(len(h_sp_m)) zero_d = np.zeros(len(h_sp_d)) E_minus_sp_0_m = np.transpose([1j*H2n(1,k_sp*r)*e_sp_x_m, zero_m, H2n(0,k_sp*r)*e_sp_z_m]) # eq11, supmat, replace E_plus to E_minus and H1n to H2n H_minus_sp_0_m = np.transpose([zero_m, 1j*H2n(1,k_sp*r)*h_sp_m, zero_m]) # eq11, supmat, replace E_plus to E_minus and H1n to H2n E_minus_sp_0_d = np.transpose([1j*H2n(1,k_sp*r)*e_sp_x_d, zero_d, H2n(0,k_sp*r)*e_sp_z_d]) # eq11, supmat, replace E_plus to E_minus and H1n to H2n H_minus_sp_0_d = np.transpose([zero_d, 1j*H2n(1,k_sp*r)*h_sp_d, zero_d]) # eq11, supmat, replace E_plus to E_minus and H1n to H2n # E_m H_m E_d H_d N_sp_0 = (((-1)**0) * (4.0j/(omega*eps_0*k_sp)) * (eps_d**2 - eps_m**2) / ((eps_m*eps_d)**(3/2)) ) tmp_m = np.cross(E_minus_sp_0_m,H_m) - np.cross(E_m, H_minus_sp_0_m) radail_pojeciton_m = np.transpose(tmp_m)[0] integrand_m = (2*pi/N_sp_0)*radail_pojeciton_m*r tmp_d = np.cross(E_minus_sp_0_d,H_d) - np.cross(E_d, H_minus_sp_0_d) radail_pojeciton_d = np.transpose(tmp_d)[0] integrand_d = (2*pi/N_sp_0)*radail_pojeciton_d*r A_sp_0_m = np.trapz(integrand_m, z_m) A_sp_0_d = np.trapz(integrand_d, z_d) A_sp_0 = A_sp_0_m + A_sp_0_d return np.absolute(A_sp_0)**2 # print("S from full field",np.real(np.cross(E,np.conj(H)))) # print("H0 air (%5.4g %+5.4gj)"%(np.real(H1_0[wl_idx]), np.imag(H1_0[wl_idx])), # " from H1 (%5.4g %+5.4gj)"%(np.real(H1[0][wl_idx]), np.imag(H1[0][wl_idx]))) # #plasmon_power = 1.0/2.0 * np.real( E1[0] * np.conj(H1[0])) # TODO check minus sign!! # plasmon_power = -1.0/2.0 * 2.0*np.pi*R * ( # TODO check minus sign!! # np.real( E1_0 * np.conj(H1_0) ) # / (2.0 * np.real(kappa1)) # + # np.real( E2_0 * np.conj(H1_0) ) # / (2.0 * np.real(kappa2)) # )* np.exp( 2.0*np.imag(k_spp)*R ) # TODO check minus sign!! # #print(np.abs(plasmon_power/ dip_power)) # eta0 = plasmon_power[0]/ dip_power[0] *100 # ppw = plasmon_power[0] # print("\n") # print(dirname) # print("Power: plasmon %4.3g W of dipoles %4.3g W, efficiency %5.3g%% from:"%(ppw, float(np.abs(dip_power[0])),float(np.abs( eta0))), ppw, eta0) # plt.plot(lambd*1e9, plasmon_power/ dip_power) # plt.ylim(0,0.04) # plt.xlim(550,800) # #plt.plot(lambd*1e9, np.real(eps2)) # # plt.plot(lambd*1e9, np.real(k_spp)) # # plt.plot(lambd*1e9, k_0) # #plt.semilogy(lambd*1e9, np.absolute(plasmon_power/ dip_power)) # # # legend = [] # # # legend.append(zshift[shift]+"@"+str(WLs[i])+" nm") # # # plt.legend(legend) # # # #plt.xlabel(r'THz') # plt.xlabel(r'$\lambda$, nm') # plt.ylabel(r'$P_{spp}/P_{dipole}$',labelpad=-5) # #plt.title(' R = '+str(core_r)+' nm') # plt.savefig(dirname+"_power_ratio."+file_ext) # plt.clf() # plt.close() file_ext="pdf" def main (): if verbose > 5: print("r =",r) dirname="bigourdan-Au-sub-dipole-W.fsp.1D.monitor_1.results" data = read_data(dirname) WLs = [] A2 = [] for wl in data: WLs.append(wl) A2.append(analyze(data[wl],wl)) #print(WLs) WLs1 = np.array(WLs) A21 = np.array(A2) dirname="bigourdan-Au-sub-Cyl-dipole-W.fsp.1D.monitor_1.results" data = read_data(dirname) WLs = [] A2 = [] for wl in data: WLs.append(wl) A2.append(analyze(data[wl],wl)) #print(WLs) WLs2 = np.array(WLs) A22 = np.array(A2) # data = np.vstack((WLs,A2)) # print(np.sort(data)) plt.plot(WLs1*1e9, A21*275, linestyle='None', marker='o', color="black",label="x 275, no ant.") plt.plot(WLs2*1e9, A22, linestyle='None', marker='*', color="red", label="with antena") plt.legend() plt.xlabel(r'$\lambda$, nm') plt.ylim(0,0.2) plt.ylabel(r'$|A_{sp}|^2$',labelpad=-1) #plt.title(dirname) plt.savefig(dirname+"_A2."+file_ext) plt.clf() plt.close() main()