def readline(self, descr):
words = descr.split()
self.descr = descr
self.name = words[0]
i = 1
if self.name in ['H2', 'HD', 'CO']:
if len(words) == 4:
self.J = -1
self.nu = -1
else:
if len(words) == 6:
self.nu = int(words[i])
i += 1
elif len(words) == 5:
self.nu = 0
self.J = int(words[i])
self.stat = (2 * self.J + 1) * (2 * (self.J % 2) + 1)
i += 1
if self.name in ['OI', 'CI', 'SiII']:
if len(words) == 5:
self.J = int(words[1])
i += 1
else:
self.J = -1
self.get_ioniz()
self.col = a(float(words[i]), float(words[i + 1]), float(words[i + 2]))
def readline(self, descr):
"""
Method to read species data from the line
Used by reading data from file
"""
words = descr.split()
self.descr = descr
self.name = words[0]
i = 1
if self.name in ['H2', 'HD', 'CO']:
if len(words) == 4:
self.J = -1
self.nu = -1
else:
if len(words) == 6:
self.nu = int(words[i])
i += 1
elif len(words) == 5:
self.nu = 0
self.J = int(words[i])
self.stat = (2*self.J+1)*(2*(self.J%2)+1)
i += 1
if self.name in ['OI', 'CI', 'SiII']:
if len(words) == 5:
self.J = int(words[1])
i += 1
else:
self.J = -1
self.get_ioniz()
self.col = a(float(words[i]), float(words[i+1]), float(words[i+2]))
def depletion(element, logN, logNref, ref='Zn', mode=None):
"""
Return the value of the depletion of element using Asplund 2009 data
parameters:
- element : name of the element
- logN : column density of element
- logNH : column density of reference element for the depletion
- ref : name of the reference element, Zn is default
- mode : if mode == 'Solar' include solar uncertainties in result
"""
element = e(element).get_element_name()
element_ref = e(ref).get_element_name()
if isinstance(logN, a) or isinstance(logNref, a):
if mode == 'Solar':
return (logN / logNref * a(Asplund2009(element_ref), 'l') / a(Asplund2009(element), 'l')).log()
else:
return (logN / logNref * 10 ** (Asplund2009(element_ref)[0] - Asplund2009(element)[0])).log()
def __init__(self, name='', col=0, plus=0, minus=0):
self.name = name
self.elem = ''
self.nu = -1
self.J = -1
self.stat = -1
self.col = a(col, plus, minus)
self.mod = 0
self.ioniz = 0
self.descr = self.name
if col != 0:
self.descr += ' ' + str(col)
# for line modeling:
self.logN = 0
self.b = 0
self.b_ind = 0
def __init__(self, *args, **kwargs):
# representation name SiII, OI*, HD
self.name = args[0]
# short desciprion of element, like Si
self.el = self.get_element_name()
# set column density:
if len(args) == 1:
self.col = a()
elif len(args) == 2:
if isinstance(args[1], str):
self.col = a(args[1])
elif isinstance(args[1], a):
self.col = args[1]
elif isinstance(args[1], (int, float)):
self.col = a(args[1], 0, 0)
elif len(args) == 4:
if 'f' in kwargs.keys():
self.col = a(args[1], args[2], args[3], kwargs['f'])
else:
self.col = a(args[1], args[2], args[3], )
self.nu = None
self.J = None
if 'j' in self.name:
self.J = int(self.name[int(self.name.index('j'))+1:])
self.b = None
for k in kwargs.items():
if k[0] == 'b' and isinstance(k[1], (list, tuple)):
setattr(self, k[0], a(k[1][0], k[1][1], k[1][2], 'd'))
else:
setattr(self, k[0], k[1])
# refresh representation for molecules
self.name = self.__repr__()
self.mend = None
self.fine = self.name.count('*')
self.statw()
self.ionstate()
self.lines = []
# for line modeling:
self.logN = self.col.val
if self.b is not None:
self.b_ = self.b.val
# some additional parameters:
self.mod = 0
def metallicity(element, logN, logNH, mode=None):
"""
Return the value of the metallicity using Asplund 2009 data
parameters:
- element : name of the element
- logN : column density of element
- logNH : column density of HI
- mode : if mode == 'Solar' include solar uncertainties in result
"""
element = e(element).get_element_name()
if isinstance(logN, a) or isinstance(logNH, a):
if not isinstance(logNH, a):
logNH = 10**logNH
if mode == 'Solar':
return (logN / logNH / a(Asplund2009(element), 'l')).log()
else:
return (logN / logNH / 10**(Asplund2009(element)[0])).log()
if isinstance(logN, float) and isinstance(logNH, float):
return logN - logNH - Asplund2009(element)[0]
def abundance(element, logNH, me, mode=None):
"""
Return the value of the abundance of element at specified metallicity using Asplund 2009 data
parameters:
- element : name of the element
- logNH : column density of HI
- me : metallicity
- mode : if mode == 'Solar' include solar uncertainties in result
return: N
- N : abundance of element in log, or a() object
"""
element = e(element).get_element_name()
if isinstance(me, a) or isinstance(logNH, a):
if mode == 'Solar':
return (logNH * me * a(Asplund2009(element), 'l')).log()
else:
return (logNH * me * 10**(Asplund2009(element)[0])).log()
if isinstance(me, float) or isinstance(logNH, float):
return me + logNH + Asplund2009(element)[0]
if __name__ == '__main__':
if 0:
d = DLAlist.DLA_SDSS()
d = DLAlist()
print(d)
if 0:
H2 = H2list.Malec(1)
for line in H2:
print(line)
if 0:
HI = HIlist.HIset()
for line in HI:
print(line, line.l, line.f, line.g)
if 0:
N = a('14.47^{+0.09}_{-0.07}', 'l')
print(N)
HI = a('19.88^{+0.01}_{-0.01}', 'l')
print(metallicity('O_I', N, HI))
if 0:
HI = a('19.88^{+0.01}_{-0.01}', 'l')
me = a('-1.2^{+0.1}_{-0.1}', 'l')
print(abundance('OI', HI, me))
if 1:
A = atomicData()
#A.readCO()
#print(A.list('SiII'))
A.makedatabase()
#A.makedatabase()