131 lines
7.3 KiB
Cython
131 lines
7.3 KiB
Cython
import math
|
|
import numpy as np
|
|
cimport numpy as np
|
|
nx = None
|
|
|
|
cdef double _s3 = math.sqrt(3)
|
|
|
|
from scipy.constants import c
|
|
from .timetrack import _time_b, _time_e
|
|
from .tmatrices import symz_indexarrays
|
|
from .hexpoints import hexlattice_get_AB
|
|
|
|
cpdef hexlattice_zsym_getSVD(int lMax, TMatrices_om, double epsilon_b, double hexside, size_t maxlayer, double omega, klist, gaussianSigma=False, int onlyNmin=0, verbose=False):
|
|
cdef np.ndarray[np.npy_double, ndim = 2] klist_c = klist
|
|
btime = _time_b(verbose)
|
|
cdef size_t nelem = lMax * (lMax + 2)
|
|
_n2id = np.identity(2*nelem)
|
|
_n2id.shape = (2,nelem,2,nelem)
|
|
cdef np.ndarray[np.npy_double, ndim = 4] n2id = _n2id
|
|
cdef double nan = float('nan')
|
|
k_0 = omega * math.sqrt(epsilon_b) / c
|
|
tdic = hexlattice_get_AB(lMax,k_0*hexside,maxlayer)
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] a_self = tdic['a_self'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] b_self = tdic['b_self'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] a_u2d = tdic['a_u2d'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] b_u2d = tdic['b_u2d'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] a_d2u = tdic['a_d2u'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] b_d2u = tdic['b_d2u'][:,:nelem,:nelem]
|
|
cdef np.ndarray[np.npy_double, ndim = 2] unitcell_translations = tdic['self_tr']*hexside*_s3
|
|
cdef np.ndarray[np.npy_double, ndim = 2] u2d_translations = tdic['u2d_tr']*hexside*_s3
|
|
cdef np.ndarray[np.npy_double, ndim = 2] d2u_translations = tdic['d2u_tr']*hexside*_s3
|
|
|
|
cdef np.ndarray[np.npy_double, ndim = 1] unitcell_envelope, u2d_envelope, d2u_envelope
|
|
if gaussianSigma:
|
|
sbtime = _time_b(verbose, step='Calculating gaussian envelope')
|
|
unitcell_envelope = np.exp(-np.sum(tdic['self_tr']**2,axis=-1)/(2*gaussianSigma**2))
|
|
u2d_envelope = np.exp(-np.sum(tdic['u2d_tr']**2,axis=-1)/(2*gaussianSigma**2))
|
|
d2u_envelope = np.exp(-np.sum(tdic['d2u_tr']**2,axis=-1)/(2*gaussianSigma**2))
|
|
_time_e(sbtime, verbose, step='Calculating gaussian envelope')
|
|
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 3] svUfullTElist, svVfullTElist, svUfullTMlist, svVfullTMlist
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 2] svSfullTElist, svSfullTMlist
|
|
cdef np.ndarray[np.npy_double, ndim = 2] minsvTElist, minsvTMlist
|
|
|
|
#TMatrices_om = TMatrices_interp(omega)
|
|
if(not onlyNmin):
|
|
svUfullTElist = np.full((klist_c.shape[0], 2*nelem, 2*nelem), np.nan, dtype=complex)
|
|
svVfullTElist = np.full((klist_c.shape[0], 2*nelem, 2*nelem), np.nan, dtype=complex)
|
|
svSfullTElist = np.full((klist_c.shape[0], 2*nelem), np.nan, dtype=complex)
|
|
svUfullTMlist = np.full((klist_c.shape[0], 2*nelem, 2*nelem), np.nan, dtype=complex)
|
|
svVfullTMlist = np.full((klist_c.shape[0], 2*nelem, 2*nelem), np.nan, dtype=complex)
|
|
svSfullTMlist = np.full((klist_c.shape[0], 2*nelem), np.nan, dtype=complex)
|
|
else:
|
|
minsvTElist = np.full((klist_c.shape[0], onlyNmin),np.nan)
|
|
minsvTMlist = np.full((klist_c.shape[0], onlyNmin),np.nan)
|
|
|
|
cdef np.ndarray[np.npy_cdouble] leftmatrixlist = np.full((klist_c.shape[0],2,2,nelem,2,2,nelem),np.nan,dtype=complex)
|
|
cdef np.ndarray[np.npy_bool, ndim=1] isNaNlist = np.zeros((klist_c.shape[0]), dtype=bool)
|
|
|
|
sbtime = _time_b(verbose, step='Initialization of matrices for SVD for a given list of k\'s')
|
|
# sem nějaká rozumná smyčka
|
|
|
|
# declarations for the ki loop:
|
|
cdef size_t ki
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 1] phases_self
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 1] phases_u2d
|
|
cdef np.ndarray[np.npy_cdouble, ndim = 1] phases_d2u
|
|
cdef np.ndarray[np.npy_cdouble, ndim=6] leftmatrix
|
|
cdef np.ndarray[np.npy_double, ndim=1] k
|
|
cdef int j
|
|
|
|
for ki in range(klist_c.shape[0]):
|
|
k = klist_c[ki]
|
|
if (k_0*k_0 - k[0]*k[0] - k[1]*k[1] < 0):
|
|
isNaNlist[ki] = True
|
|
continue
|
|
|
|
phases_self = np.exp(1j*np.tensordot(k,unitcell_translations,axes=(0,-1)))
|
|
phases_u2d = np.exp(1j*np.tensordot(k,u2d_translations,axes=(0,-1)))
|
|
phases_d2u = np.exp(1j*np.tensordot(k,d2u_translations,axes=(0,-1)))
|
|
if gaussianSigma:
|
|
phases_self *= unitcell_envelope
|
|
phases_u2d *= u2d_envelope
|
|
phases_d2u *= d2u_envelope
|
|
leftmatrix = np.zeros((2,2,nelem, 2,2,nelem), dtype=complex)
|
|
# 0:[u,E<--u,E ]
|
|
# 1:[d,M<--d,M ]
|
|
leftmatrix[0,0,:,0,0,:] = np.tensordot(a_self,phases_self, axes=(0,-1)) # u2u, E2E
|
|
leftmatrix[1,0,:,1,0,:] = leftmatrix[0,0,:,0,0,:] # d2d, E2E
|
|
leftmatrix[0,1,:,0,1,:] = leftmatrix[0,0,:,0,0,:] # u2u, M2M
|
|
leftmatrix[1,1,:,1,1,:] = leftmatrix[0,0,:,0,0,:] # d2d, M2M
|
|
leftmatrix[0,0,:,0,1,:] = np.tensordot(b_self,phases_self, axes=(0,-1)) # u2u, M2E
|
|
leftmatrix[0,1,:,0,0,:] = leftmatrix[0,0,:,0,1,:] # u2u, E2M
|
|
leftmatrix[1,1,:,1,0,:] = leftmatrix[0,0,:,0,1,:] # d2d, E2M
|
|
leftmatrix[1,0,:,1,1,:] = leftmatrix[0,0,:,0,1,:] # d2d, M2E
|
|
leftmatrix[0,0,:,1,0,:] = np.tensordot(a_d2u, phases_d2u,axes=(0,-1)) #d2u,E2E
|
|
leftmatrix[0,1,:,1,1,:] = leftmatrix[0,0,:,1,0,:] #d2u, M2M
|
|
leftmatrix[1,0,:,0,0,:] = np.tensordot(a_u2d, phases_u2d,axes=(0,-1)) #u2d,E2E
|
|
leftmatrix[1,1,:,0,1,:] = leftmatrix[1,0,:,0,0,:] #u2d, M2M
|
|
leftmatrix[0,0,:,1,1,:] = np.tensordot(b_d2u, phases_d2u,axes=(0,-1)) #d2u,M2E
|
|
leftmatrix[0,1,:,1,0,:] = leftmatrix[0,0,:,1,1,:] #d2u, E2M
|
|
leftmatrix[1,0,:,0,1,:] = np.tensordot(b_u2d, phases_u2d,axes=(0,-1)) #u2d,M2E
|
|
leftmatrix[1,1,:,0,0,:] = leftmatrix[1,0,:,0,1,:] #u2d, E2M
|
|
#leftmatrix is now the translation matrix T
|
|
for j in range(2):
|
|
leftmatrix[j] = -np.tensordot(TMatrices_om[j], leftmatrix[j], axes=([-2,-1],[0,1]))
|
|
# at this point, jth row of leftmatrix is that of -MT
|
|
leftmatrix[j,:,:,j,:,:] += n2id
|
|
#now we are done, 1-MT
|
|
|
|
leftmatrixlist[ki] = leftmatrix
|
|
|
|
nnlist = np.logical_not(isNaNlist)
|
|
leftmatrixlist_s = np.reshape(leftmatrixlist,(klist_c.shape[0], 2*2*nelem,2*2*nelem))[nnlist]
|
|
TEc, TMc = symz_indexarrays(lMax, 2)
|
|
leftmatrixlist_TE = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TEc,TEc)]
|
|
leftmatrixlist_TM = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TMc,TMc)]
|
|
_time_e(sbtime, verbose, step='Initializing matrices for SVD for a given list of k\'s')
|
|
|
|
sbtime = _time_b(verbose, step='Calculating SVDs for a given list of k\'s.')
|
|
if(not onlyNmin):
|
|
svUfullTElist[nnlist], svSfullTElist[nnlist], svVfullTElist[nnlist] = np.linalg.svd(leftmatrixlist_TE, compute_uv=True)
|
|
svUfullTMlist[nnlist], svSfullTMlist[nnlist], svVfullTMlist[nnlist] = np.linalg.svd(leftmatrixlist_TM, compute_uv=True)
|
|
_time_e(sbtime, verbose, step='Calculating SVDs for a given list of k\'s.')
|
|
return ((svUfullTElist, svSfullTElist, svVfullTElist), (svUfullTMlist, svSfullTMlist, svVfullTMlist))
|
|
else:
|
|
minsvTElist[nnlist] = np.linalg.svd(leftmatrixlist_TE, compute_uv=False)[...,-onlyNmin:]
|
|
minsvTMlist[nnlist] = np.linalg.svd(leftmatrixlist_TM, compute_uv=False)[...,-onlyNmin:]
|
|
_time_e(sbtime, verbose, step='Calculating SVDs for a given list of k\'s.')
|
|
return (minsvTElist, minsvTMlist)
|