def rmass(self):
"""reduced mass for a path"""
if self.__rmass is None:
amass = 0
for label, iz, ipot, x, y, z in self.geom:
m = atomic_mass(iz, _larch=self._larch)
amass += 1.0/max(1., m)
self.__rmass = 1./amass
return self.__rmass
def material_mu(name, energy, density=None, kind='total', _larch=None):
"""
material_mu(name, energy, density=None, kind='total')
return X-ray attenuation length (in 1/cm) for a material by name or formula
arguments
---------
name: chemical formul or name of material from materials list.
energy: energy or array of energies in eV
density: material density (gr/cm^3). If None, and material is a
known material, that density will be used.
kind: 'photo' or 'total' (default) for whether to
return photo-absorption or total cross-section.
returns
-------
mu, absorption length in 1/cm
notes
-----
1. material names are not case sensitive,
chemical compounds are case sensitive.
2. mu_elam() is used for mu calculation.
example
-------
>>> print material_mu('H2O', 10000.0)
5.32986401658495
"""
_materials = get_materials(_larch)
formula = None
mater = _materials.get(name.lower(), None)
if mater is not None:
formula, density = mater
else:
for key, val in _materials.items():
if name.lower() == val[0].lower(): # match formula
formula, density = val
break
# default to using passed in name as a formula
if formula is None:
formula = name
if density is None:
raise Warning('material_mu(): must give density for unknown materials')
mass_tot, mu = 0.0, 0.0
for elem, frac in chemparse(formula).items():
mass = frac * atomic_mass(elem, _larch=_larch)
mu += mass * mu_elam(elem, energy, kind=kind, _larch=_larch)
mass_tot += mass
return density*mu/mass_tot
def sigma2_debye(t, theta, path=None, _larch=None):
"""calculate sigma2 for a Feff Path wih the correlated Debye model
sigma2 = sigma2_debye(t, theta, path=None)
Parameters:
-----------
t sample temperature (in K)
theta Debye temperature (in K)
path FeffPath to cacluate sigma2 for [None]
if path is None, the 'current path'
(_sys.paramGroup._feffdat) is used.
"""
global FEFF6LIB
if FEFF6LIB is None:
FEFF6LIB = get_dll('feff6')
FEFF6LIB.sigma2_debye.restype = ctypes.c_double
if path is None:
try:
path = _larch.symtable._sys.paramGroup
except:
pass
try:
fdat = path._feffdat
except:
return 0.00
if theta < 1.e-5: theta = 1.e-5
if t < 1.e-5: t = 1.e-5
npts = len(fdat.geom)
nat = ctypes.pointer(ctypes.c_int(npts))
t = ctypes.pointer(ctypes.c_double(t))
th = ctypes.pointer(ctypes.c_double(theta))
rs = ctypes.pointer(ctypes.c_double(fdat.rnorman))
ax = (npts*ctypes.c_double)()
ay = (npts*ctypes.c_double)()
az = (npts*ctypes.c_double)()
am = (npts*ctypes.c_double)()
for i, dat in enumerate(fdat.geom):
s, iz, ip, x, y, z = dat
ax[i], ay[i], az[i], am[i] = x, y, z, atomic_mass(iz, _larch=_larch)
return FEFF6LIB.sigma2_debye(nat, t, th, rs, ax, ay, az, am)
def material_mu_components(name, energy, density=None, kind='total',
_larch=None):
"""material_mu_components: absorption coefficient (in 1/cm) for a compound
arguments
---------
name: material name or compound formula
energy: energy or array of energies at which to calculate mu
density: compound density in gr/cm^3
kind: cross-section to use ('total', 'photo') for mu_elam())
returns
-------
dictionary of data for constructing mu per element,
with elements 'mass' (total mass), 'density', and
'elements' (list of atomic symbols for elements in material).
For each element, there will be an item (atomic symbol as key)
with tuple of (stoichiometric fraction, atomic mass, mu)
larch> material_mu_components('quartz', 10000)
{'Si': (1, 28.0855, 33.879432430185062), 'elements': ['Si', 'O'],
'mass': 60.0843, 'O': (2.0, 15.9994, 5.9528248152970837), 'density': 2.65}
"""
_materials = get_materials(_larch)
mater = _materials.get(name.lower(), None)
if mater is None:
formula = name
if density is None:
raise Warning('material_mu(): must give density for unknown materials')
else:
formula, density = mater
out = {'mass': 0.0, 'density': density, 'elements':[]}
for atom, frac in chemparse(formula).items():
mass = atomic_mass(atom, _larch=_larch)
mu = mu_elam(atom, energy, kind=kind, _larch=_larch)
out['mass'] += frac*mass
out[atom] = (frac, mass, mu)
out['elements'].append(atom)
return out
def __read(self, filename):
try:
lines = open(filename, 'r').readlines()
except:
print( 'Error reading file %s ' % filename)
return
self.filename = filename
mode = 'header'
self.potentials, self.geom = [], []
data = []
pcounter = 0
iline = 0
for line in lines:
iline += 1
line = line[:-1]
if line.startswith('#'): line = line[1:]
line = line.strip()
if iline == 1:
self.title = line[:64].strip()
self.version = line[64:].strip()
continue
if line.startswith('k') and line.endswith('real[p]@#'):
mode = 'arrays'
continue
elif '----' in line[2:10]:
mode = 'path'
continue
#
if (mode == 'header' and
line.startswith('Abs') or line.startswith('Pot')):
words = line.replace('=', ' ').split()
ipot, z, rmt, rnm = (0, 0, 0, 0)
words.pop(0)
if line.startswith('Pot'):
ipot = int(words.pop(0))
iz = int(words[1])
rmt = float(words[3])
rnm = float(words[5])
self.potentials.append((ipot, iz, rmt, rnm))
elif mode == 'header' and line.startswith('Gam_ch'):
words = line.replace('=', ' ').split(' ', 2)
self.gam_ch = float(words[1])
self.exch = words[2]
elif mode == 'header' and line.startswith('Mu'):
words = line.replace('=', ' ').split()
self.mu = float(words[1])
self.kf = float(words[3])
self.vint = float(words[5])
self.rs_int= float(words[7])
elif mode == 'path':
pcounter += 1
if pcounter == 1:
w = [float(x) for x in line.split()[:5]]
self.__nleg__ = int(w.pop(0))
self.degen, self.__reff__, self.rnorman, self.edge = w
elif pcounter > 2:
words = line.split()
xyz = [float(x) for x in words[:3]]
ipot = int(words[3])
iz = int(words[4])
if len(words) > 5:
lab = words[5]
else:
lab = atomic_symbol(iz)
amass = atomic_mass(iz)
geom = [lab, iz, ipot, amass] + xyz
self.geom.append(tuple(geom))
elif mode == 'arrays':
d = np.array([float(x) for x in line.split()])
if len(d) == 7:
data.append(d)
data = np.array(data).transpose()
self.k = data[0]
self.real_phc = data[1]
self.mag_feff = data[2]
self.pha_feff = data[3]
self.red_fact = data[4]
self.lam = data[5]
self.rep = data[6]
self.pha = data[1] + data[3]
self.amp = data[2] * data[4]
self.__rmass = None # reduced mass of path
def __read(self, filename):
try:
lines = open(filename, 'r').readlines()
except:
print('Error reading file %s ' % filename)
return
self.filename = filename
mode = 'header'
self.potentials, self.geom = [], []
data = []
pcounter = 0
iline = 0
for line in lines:
iline += 1
line = line[:-1]
if line.startswith('#'): line = line[1:]
line = line.strip()
if iline == 1:
self.title = line[:64].strip()
self.version = line[64:].strip()
continue
if line.startswith('k') and line.endswith('real[p]@#'):
mode = 'arrays'
continue
elif '----' in line[2:10]:
mode = 'path'
continue
#
if (mode == 'header' and line.startswith('Abs')
or line.startswith('Pot')):
words = line.replace('=', ' ').split()
ipot, z, rmt, rnm = (0, 0, 0, 0)
words.pop(0)
if line.startswith('Pot'):
ipot = int(words.pop(0))
iz = int(words[1])
rmt = float(words[3])
rnm = float(words[5])
self.potentials.append((ipot, iz, rmt, rnm))
elif mode == 'header' and line.startswith('Gam_ch'):
words = line.replace('=', ' ').split(' ', 2)
self.gam_ch = float(words[1])
self.exch = words[2]
elif mode == 'header' and line.startswith('Mu'):
words = line.replace('=', ' ').split()
self.mu = float(words[1])
self.kf = float(words[3])
self.vint = float(words[5])
self.rs_int = float(words[7])
elif mode == 'path':
pcounter += 1
if pcounter == 1:
w = [float(x) for x in line.split()[:5]]
self.__nleg__ = int(w.pop(0))
self.degen, self.__reff__, self.rnorman, self.edge = w
elif pcounter > 2:
words = line.split()
xyz = [float(x) for x in words[:3]]
ipot = int(words[3])
iz = int(words[4])
if len(words) > 5:
lab = words[5]
else:
lab = atomic_symbol(iz, _larch=self._larch)
amass = atomic_mass(iz, _larch=self._larch)
geom = [lab, iz, ipot, amass] + xyz
self.geom.append(tuple(geom))
elif mode == 'arrays':
d = np.array([float(x) for x in line.split()])
if len(d) == 7:
data.append(d)
data = np.array(data).transpose()
self.k = data[0]
self.real_phc = data[1]
self.mag_feff = data[2]
self.pha_feff = data[3]
self.red_fact = data[4]
self.lam = data[5]
self.rep = data[6]
self.pha = data[1] + data[3]
self.amp = data[2] * data[4]
self.__rmass = None # reduced mass of path