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Obecný scatter, zahájena třída s mřížkou 

Former-commit-id: a6479f00e8639a7656913da298844b176ba5d45a
This commit is contained in:
Marek Nečada 2016-12-21 21:54:53 +02:00
parent b642991bb1
commit 478c93276f
1 changed files with 35 additions and 5 deletions
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38
qpms/lattices.py
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@ -131,7 +131,22 @@ class Scattering(object):
_time_e(btime, verbose) _time_e(btime, verbose)
def scatter(self, pq_0, verbose = False): def scatter(self, pq_0, verbose = False):
pass '''
pq_0 is (N, nelem, 2)-shaped array
'''
btime = _time_b(verbose)
self.prepare(verbose=verbose)
pq_0 = np.broadcast_to(pq_0, (self.N,2,self.nelem))
MP_0 = np.empty((N,2,nelem),dtype=np.complex_)
for j in range(self.N):
MP_0[j] = np.tensordot(self.TMatrices[j], pq_0[j],axes=[-2,-1],[-2,-1])
MP_0.shape = (N*2*self.nelem,)
solvebtime = _time_b(verbose,step='Solving the linear equation')
ab = scipy.linalg.lu_solve(self.lupiv, MP_0)
_time_e(solvebtime, verbose, step='Solving the linear equation')
ab.shape = (N,2,nelem)
_time_e(btime, verbose)
return ab
def scatter_constmultipole(self, pq_0_c, verbose = False): def scatter_constmultipole(self, pq_0_c, verbose = False):
btime = _time_b(verbose) btime = _time_b(verbose)
@ -155,6 +170,21 @@ class Scattering(object):
_time_e(btime, verbose) _time_e(btime, verbose)
return ab return ab
class Scattering_lattice(Scattering): class Scattering_2D_lattice(Scattering):
def __init__(self): def __init__(self, rectcell_dims, rectcell_elem_positions, cellspec, k_0, rectcell_TMatrices = None, TMatrices = None, lMax = None, verbose=False, J_scat=3):
pass '''
cellspec: dvojice ve tvaru (seznam_zaplněnosti, seznam_pozic)
'''
if (rectcell_TMatrices is None) == (TMatrices is None):
raise ValueError('Either rectcell_TMatrices or TMatrices has to be given')
###self.positions = ZDE JSEM SKONČIL
self.J_scat = J_scat
self.positions = positions
self.interaction_matrix = None
self.N = positions.shape[0]
self.k_0 = k_0
self.lMax = lMax if lMax else nelem2lMax(TMatrices.shape[-1])
nelem = lMax * (lMax + 2) #!
self.nelem = nelem #!
self.prepared = False
self.TMatrices = np.broadcast_to(TMatrices, (self.N,2,nelem,2,nelem)) def __init__(self):