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loading tmatrices from the new scuff-tmatrix versions 

Former-commit-id: fe8b6c63e859ea18cf3415deee38258aa7bde50c
This commit is contained in:
Marek Nečada 2018-05-16 21:04:15 +03:00
parent 12f9191a09
commit cbab332c34
1 changed files with 20 additions and 8 deletions
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26
qpms/tmatrices.py
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@ -146,21 +146,33 @@ def parity_yy(lmax):
def _scuffTMatrixConvert_EM_01(EM):
#print(EM)
if (EM == b'E'):
return 0
elif (EM == b'M'):
return 1
elif (EM == b'M'):
return 0
else:
return None
def loadScuffTMatrices(fileName, normalisation = 1):
def loadScuffTMatrices(fileName, normalisation = 1, version = 'old'):
"""
TODO doc
version describes version of scuff-em. It is either 'old' or 'new'
"""
oldversion = (version == 'old')
μm = 1e-6
table = np.genfromtxt(fileName,
converters={1: _scuffTMatrixConvert_EM_01, 4: _scuffTMatrixConvert_EM_01},
dtype=[('freq', '<f8'), ('outc_type', '<i8'), ('outc_l', '<i8'), ('outc_m', '<i8'),
('inc_type', '<i8'), ('inc_l', '<i8'), ('inc_m', '<i8'), ('Treal', '<f8'), ('Timag', '<f8')]
converters={1: _scuffTMatrixConvert_EM_01, 4: _scuffTMatrixConvert_EM_01} if oldversion else None,
skip_header = 0 if oldversion else 5,
usecols = None if oldversion else (0, 2, 3, 4, 6, 7, 8, 9, 10),
dtype=[('freq', '<f8'),
('outc_type', '<i8'), ('outc_l', '<i8'), ('outc_m', '<i8'),
('inc_type', '<i8'), ('inc_l', '<i8'), ('inc_m', '<i8'),
('Treal', '<f8'), ('Timag', '<f8')]
if oldversion else
[('freq', '<f8'),
('outc_l', '<i8'), ('outc_m', '<i8'), ('outc_type', '<i8'),
('inc_l', '<i8'), ('inc_m', '<i8'), ('inc_type', '<i8'),
('Treal', '<f8'), ('Timag', '<f8')]
)
lMax=np.max(table['outc_l'])
my,ny = get_mn_y(lMax)
@ -180,7 +192,7 @@ def loadScuffTMatrices(fileName, normalisation = 1):
TMatrices = np.zeros((len(freqs),2,nelem,2,nelem),dtype=complex)
for inc_type in [0,1]:
for outc_type in [0,1]:
TMatrices[:,1-outc_type,:,1-inc_type,:] = TMatrices_tmp_real[:,:,outc_type,:,inc_type]+1j*TMatrices_tmp_imag[:,:,outc_type,:,inc_type]
TMatrices[:,outc_type,:,inc_type,:] = TMatrices_tmp_real[:,:,outc_type,:,inc_type]+1j*TMatrices_tmp_imag[:,:,outc_type,:,inc_type]
# IMPORTANT: now we are going from Reid's/Kristensson's/Jackson's/whoseever convention to Taylor's convention
if normalisation == 1:
TMatrices[:,:,:,:,:] = TMatrices[:,:,:,:,:] * np.sqrt(ny*(ny+1))[ň,ň,ň,ň,:] / np.sqrt(ny*(ny+1))[ň,ň,:,ň,ň]