def infoR(doftotal, val):
if r.topt == 1:
pthick = [thick[i] * doftotal[i] for i in range(Nlayer)]
dofold = doftotal[Nlayer:]
else:
pthick = thick
dofold = doftotal
df = f_symmetry(dofold, Mx, My, xsym, ysym, Nlayer=Nlayer)
dof = b_filter(df, bproj)
if r.inverse == 1:
val = 1 / val
rho = mload
rhor = mload
for i in range(Nlayer):
mtmp = lam0 * pthick[i] * mstruct[i].density * np.mean(
dof[i * Nx * Ny:(i + 1) * Nx * Ny])
rho = rho + mtmp
rhor = rhor + mtmp
rho = rho**r.mpower
F = np.mean(gamma * beta / (1 - beta)**2)
R = 1. / (1e9 * val * 2 * laserP / cons.c**3 / rho / F / beta[-1])
return (R, np.mean(dof), (rhor - mload) / mload,
[pthick[i] * lam0 * 1e9 for i in range(Nlayer)])
def infoR(dofold,val):
df = f_symmetry(dofold,Mx,My,xsym,ysym,Nlayer=Nlayer)
dof = b_filter(df,bproj)
rho = 0.
mT = mload
for i in range(Nlayer):
mT = mT + thickness[i]*area*mstruct[i].density*np.mean(dof[i*Nx*Ny:(i+1)*Nx*Ny])
rho = rho + 1e3*thickness[i]*mstruct[i].density*np.mean(dof[i*Nx*Ny:(i+1)*Nx*Ny])
F = np.mean(gamma*beta*cons.c/(1-beta)**2)
if RTmethod == 'D':
R = 1./(1e9*val*2*laserP*area/cons.c**2/mT/F/beta[-1])
elif RTmethod == 'W':
R = np.sqrt(rho)/val*(F/cons.c)*beta[-1]
else:
raise Exception('RTmethod undefined')
return (R,np.mean(dof))
def rcwa_assembly(dofold,freq,theta,phi,planewave):
'''
planewave:{'p_amp',...}
'''
df = f_symmetry(dofold,Mx,My,xsym,ysym,Nlayer=Nlayer)
dof = b_filter(df,bproj)
obj = rcwa.RCWA_obj(nG,L1,L2,freq,theta,phi,verbose=0)
obj.Add_LayerUniform(thick0,epsuniform)
epsdiff=[]
for i in range(Nlayer):
epsdiff.append(mstruct[i].epsilon(lam0/np.real(freq),x_type = 'lambda')-epsbkg)
obj.Add_LayerGrid(thick[i],epsdiff[i],epsbkg,Nx,Ny)
obj.Add_LayerUniform(thickN,epsuniform)
obj.Init_Setup(Gmethod=0)
obj.MakeExcitationPlanewave(planewave['p_amp'],planewave['p_phase'],planewave['s_amp'],planewave['s_phase'],order = 0)
obj.GridLayer_getDOF(dof)
return obj,dof,epsdiff
def infoR(doftotal, val):
if r.topt == 1 and r.Popt == 0:
pthick = [
r.tmin / lam0 + (thick[i] - r.tmin / lam0) * doftotal[i]
for i in range(Nlayer)
]
pscale = 1.
dofold = doftotal[Nlayer:]
elif r.topt == 0 and r.Popt == 1:
pthick = thick
pscale = 1. + (r.Periodmax - r.Period) / r.Period * doftotal[0]
dofold = doftotal[1:]
elif r.topt == 1 and r.Popt == 1:
pscale = 1. + (r.Periodmax - r.Period) / r.Period * doftotal[0]
pthick = [
r.tmin / lam0 + (thick[i] - r.tmin / lam0) * doftotal[1 + i]
for i in range(Nlayer)
]
dofold = doftotal[Nlayer + 1:]
else:
pscale = 1.
pthick = thick
dofold = doftotal
df = f_symmetry(dofold, Mx, My, xsym, ysym, Nlayer=Nlayer)
dof = b_filter(df, bproj)
if r.inverse == 1:
val = 1 / val
rho = mload
rhor = mload
for i in range(Nlayer):
mtmp = lam0 * pthick[i] * mstruct[i].density * np.mean(
dof[i * Nx * Ny:(i + 1) * Nx * Ny])
rho = rho + mtmp
rhor = rhor + mtmp
rho = rho**r.mpower
F = np.mean(gamma * beta / (1 - beta)**2)
R = 1. / (1e9 * val * 2 * laserP / cons.c**3 / rho / F / beta[-1])
return (R, np.mean(dof), (rhor - mload) / mload, 1e6 * pscale * r.Period,
[pthick[i] * lam0 * 1e9 for i in range(Nlayer)])