def __readCDMS(self):
'''
Read data from CDMS line list catalogs for a specific molecule.
'''
data = DataIO.readFile(self.fn,\
replace_spaces=0)
print 'Reading data from CDMS database for'
print self.fn
#-- If the uncertainties are negative, change the unit of min/max to
# cm-1
uncertainties = [float(line[13:21]) for line in data]
if min(uncertainties) < 0 and max(uncertainties) == 0:
self.x_min = self.x_min.to(1. / u.cm, equivalencies=u.spectral())
self.x_max = self.x_max.to(1. / u.cm, equivalencies=u.spectral())
elif min(uncertainties) < 0 and max(uncertainties) > 0:
raise ValueError('Uncertainties in CDMS input file for ' + \
'file %s are ambiguous.'\
%self.fn)
data = self.__parseCatalog(data)
#-- If unit was changed, change the f values to MHz, the default unit
rcm = u.Unit("1 / cm")
if self.x_min.unit == rcm:
data = sorted([[
(entry *
rcm).to(u.MHz, equivalencies=u.spectral()) if not i else entry
for i, entry in enumerate(line)
] for line in data])
self.line_list = data
def getKey(k,data=None,fn=None):
'''
Retrieve data from an ALI inputfile.
Returns the line following the line that contains the given key.
@param k: The unique input key word for which the ALI inputfile is
searched.
@type k: str
@keyword data: The data, ie a file read by readFile with delimiter set to ''
A filename must be given if data is None.
(default: None)
@type data: list[str]
@keyword fn: The ALI input filename. Only used if data is None.
(default: None)
@type fn: str
@return: The line following the line that contains given key
@rtype: str
'''
if data is None:
data = DataIO.readFile(filename=fn,delimiter=None,replace_spaces=0)
i = DataIO.findKey(0,data,k)
return data[i+1].replace('\n','')
def __readCDMS(self):
'''
Read data from CDMS line list catalogs for a specific molecule.
'''
data = DataIO.readFile(self.fn,\
replace_spaces=0)
print 'Reading data from CDMS database for'
print self.fn
#-- If the uncertainties are negative, change the unit of min/max to
# cm-1
uncertainties = [float(line[13:21]) for line in data]
if min(uncertainties) < 0 and max(uncertainties) == 0:
self.x_min = self.x_min.to(1./u.cm,equivalencies=u.spectral())
self.x_max = self.x_max.to(1./u.cm,equivalencies=u.spectral())
elif min(uncertainties) < 0 and max(uncertainties) > 0:
raise ValueError('Uncertainties in CDMS input file for ' + \
'file %s are ambiguous.'\
%self.fn)
data = self.__parseCatalog(data)
#-- If unit was changed, change the f values to MHz, the default unit
rcm = u.Unit("1 / cm")
if self.x_min.unit == rcm:
data = sorted([[(entry*rcm).to(u.MHz,equivalencies=u.spectral())
if not i else entry
for i,entry in enumerate(line)]
for line in data])
self.line_list = data
def readFile(self, wildcard="*", *args, **kwargs):
"""
Read a filename and store its contents in the Reader object.
The contents are stored in a dictionary, with the filename as key. Note
that one filename can refer to multiple files with the use of a wildcard
character. This character can be replaced upon calling this method.
The contents can be returned with the method getFile.
If the file is not found, an empty list is stored instead.
Additional args/kwargs are passed to DataIO.readFile (such as delimiter
and replace_spaces)
@keyword wildcard: if a wildcard character is present in the filename,
it can be replaced here.
(default: '*')
@type wildcard: string
"""
# -- Replace the wildcard if it is present.
fn = self.fn.replace("*", wildcard)
# -- Read the file
self["contents"][fn] = DataIO.readFile(fn, *args, **kwargs)
def readCDMS(self):
'''
Read data from CDMS line list catalogs for a specific molecule.
'''
data = DataIO.readFile(os.path.join(cc.path.ll,\
self.molecule.molecule+'_CDMS.dat'),\
replace_spaces=0)
print 'Reading data from CDMS database for %s.' % self.molecule.molecule
uncertainties = [float(line[13:21]) for line in data]
if min(uncertainties) < 0 and max(uncertainties) == 0:
input_xmin = self.x_min
input_xmax = self.x_max
self.x_min = (self.c / (input_xmin * 10**6))**-1
self.x_max = (self.c / (input_xmax * 10**6))**-1
self.input_unit = 'cm-1'
elif min(uncertainties) < 0 and max(uncertainties) > 0:
raise ValueError('Uncertainties in CDMS input file for ' + \
'molecule %s are ambiguous.'\
%self.molecule.molecule)
data = self.parseStandardCatalog(data, 'CDMS')
if self.input_unit == 'cm-1':
data = sorted([[i == 0 \
and self.c*entry*10**-6 \
or entry \
for i,entry in enumerate(line)]
for line in data])
self.line_list.extend(data)
def readFile(self, wildcard='*', *args, **kwargs):
'''
Read a filename and store its contents in the Reader object.
The contents are stored in a dictionary, with the filename as key. Note
that one filename can refer to multiple files with the use of a wildcard
character. This character can be replaced upon calling this method.
The contents can be returned with the method getFile.
If the file is not found, an empty list is stored instead.
Additional args/kwargs are passed to DataIO.readFile (such as delimiter
and replace_spaces)
@keyword wildcard: if a wildcard character is present in the filename,
it can be replaced here.
(default: '*')
@type wildcard: string
'''
#-- Replace the wildcard if it is present.
fn = self.fn.replace('*', wildcard)
#-- Read the file
self['contents'][fn] = DataIO.readFile(fn, *args, **kwargs)
def readCDMS(self):
'''
Read data from CDMS line list catalogs for a specific molecule.
'''
data = DataIO.readFile(os.path.join(cc.path.ll,\
self.molecule.molecule+'_CDMS.dat'),\
replace_spaces=0)
print 'Reading data from CDMS database for %s.'%self.molecule.molecule
uncertainties = [float(line[13:21]) for line in data]
if min(uncertainties) < 0 and max(uncertainties) == 0:
input_xmin = self.x_min
input_xmax = self.x_max
self.x_min = (self.c/(input_xmin*10**6))**-1
self.x_max = (self.c/(input_xmax*10**6))**-1
self.input_unit = 'cm-1'
elif min(uncertainties) < 0 and max(uncertainties) > 0:
raise ValueError('Uncertainties in CDMS input file for ' + \
'molecule %s are ambiguous.'\
%self.molecule.molecule)
data = self.parseStandardCatalog(data,'CDMS')
if self.input_unit == 'cm-1':
data = sorted([[i == 0 \
and self.c*entry*10**-6 \
or entry \
for i,entry in enumerate(line)]
for line in data])
self.line_list.extend(data)
def __init__(self,path_chemistry='runTest',replace_db_entry=0,db=None,\
single_session=0):
"""
Initializing an instance of ModelingSession.
@keyword db: the Chemistry database
(default: None)
@type db: Database()
@keyword replace_db_entry: replace an entry in the Chemistry database with
a newly calculated model with a new model id
(for instance if some general data not
included in the inputfiles is changed)
(default: 0)
@type replace_db_entry: bool
@keyword path_chemistry: modeling folder in Chemistry home
(default: 'runTest')
@type path_chemistry: string
@keyword new_entries: The new model_ids when replace_db_entry is 1
of other models in the grid. These are not
replaced!
(default: [])
@type new_entries: list[str]
@keyword single_session: If this is the only CC session. Speeds up db
check.
(default: 0)
@type single_session: bool
"""
super(Chemistry, self).__init__(code='Chemistry',path=path_chemistry,\
replace_db_entry=replace_db_entry,\
single_session=single_session)
#-- Convenience path
cc.path.cout = os.path.join(cc.path.chemistry,self.path)
#DataIO.testFolderExistence(os.path.join(cc.path.mout,\
#'data_for_gastronoom'))
self.db = db
#-- If an chemistry model is in progress, the model manager will hold until
# the other cc session is finished.
self.in_progress = False
#- Read standard input file with all parameters that should be included
#- as well as some dust specific information
self.inputfilename = os.path.join(cc.path.aux,'inputChemistry.dat')
self.standard_inputfile = DataIO.readDict(self.inputfilename,\
convert_floats=1,\
convert_ints=1,\
comment_chars=['#','*'])
chemistry_keys = os.path.join(cc.path.aux,'Input_Keywords_Chemistry.dat')
self.chemistry_keywords = [line.strip()
for line in DataIO.readFile(chemistry_keys)
if line]
def __readJPL(self):
'''
Read data from JPL line list catalogs for a specific molecule.
'''
data = DataIO.readFile(self.fn,\
replace_spaces=0)
print 'Reading data from JPL database for'
print self.fn
data = self.__parseCatalog(data)
self.line_list = data
def getExtinctionCurve(gal_position='ism',curve_type='chiar_tielens',\
av_to_ak_conv=0.112):
"""
Read extinction curve.
@keyword gal_position: galactic position star: 'ism' or 'gc'. Difference of
extinction curve for ISM or galactic center
(as for chiar_tielens), if no difference
(as for cardelli) this parameter is ignored.
(default: 'ism')
@type gal_position: string
@keyword curve_type: type of extinction curve
('chiar_tielens' or 'cardelli')
(default: 'chiar_tielens')
@type curve_type: string
@keyword av_to_ak_conv: V-band to K-band conversion factor for extinction
correction
(default: 0.112)
@type av_to_ak_conv: float
@return: The wavelength grid and extinction curve values
@rtype: (array,array)
"""
extcurve_input = DataIO.readFile(os.path.join(cc.path.aux,\
curve_type + '.dat'),\
delimiter=' ')
extcurve_x = [float(row[0]) for row in extcurve_input if row[0][0] != '#']
if gal_position.lower() == 'ism' and curve_type.lower() == 'chiar_tielens':
extcurve_y = [float(row[2])
for row in extcurve_input
if row[0][0] != '#' and len(row) == 3]
#- Cut off excess wavelengths
extcurve_x = extcurve_x[:len(extcurve_y)]
elif curve_type.lower() == 'cardelli':
#- putting wavelength in micron
extcurve_x = array(extcurve_x)*10**(-4)
extcurve_y = [float(row[1])
for row in extcurve_input
if row[0][0] != '#']
#- Put values to Alambda/Ak
extcurve_y = array(extcurve_y)/(3.1*av_to_ak_conv)
else:
extcurve_y = [float(row[1])
for row in extcurve_input
if row[0][0] != '#']
return (array(extcurve_x),array(extcurve_y))
def readJPL(self):
'''
Read data from JPL line list catalogs for a specific molecule.
'''
data = DataIO.readFile(os.path.join(cc.path.ll,\
self.molecule.molecule+'_JPL.dat'),\
replace_spaces=0)
print 'Reading data from JPL database for %s.' % self.molecule.molecule
data = self.parseStandardCatalog(data, 'JPL')
self.line_list.extend(data)
def __readJPL(self):
'''
Read data from JPL line list catalogs for a specific molecule.
'''
data = DataIO.readFile(self.fn,\
replace_spaces=0)
print 'Reading data from JPL database for'
print self.fn
data = self.__parseCatalog(data)
self.line_list = data
def readJPL(self):
'''
Read data from JPL line list catalogs for a specific molecule.
'''
data = DataIO.readFile(os.path.join(cc.path.ll,\
self.molecule.molecule+'_JPL.dat'),\
replace_spaces=0)
print 'Reading data from JPL database for %s.'%self.molecule.molecule
data = self.parseStandardCatalog(data,'JPL')
self.line_list.extend(data)
def __init__(self,code,path,replace_db_entry=0,new_entries=[],\
single_session=0):
"""
Initializing an instance of ModelingSession.
@param code: code for which the modelingsession is created
@type code: string
@param path: modeling output folder in the code's home folder
@type path: string
@keyword replace_db_entry: replace an entry in the database with a
newly calculated model with a new model id
(eg if some general data not included in
the inputfiles is changed)
(default: 0)
@type replace_db_entry: bool
@keyword new_entries: The new model_ids when replace_db_entry is 1
of other models in the grid. These are not
replaced!
(default: [])
@type new_entries: list[str]
@keyword single_session: If this is the only CC session. Speeds up db
check.
(default: 0)
@type single_session: bool
"""
self.path = path
self.code = code
self.model_id = ''
self.replace_db_entry = replace_db_entry
self.new_entries = new_entries
self.single_session = single_session
if code == 'Chemistry':
self.mutable = []
else:
mutablefile = os.path.join(cc.path.aux,\
'Mutable_Parameters_%s.dat'%code)
self.mutable = [
line[0] for line in DataIO.readFile(mutablefile, delimiter=' ')
if ' '.join(line)
]
self.mutable = [line for line in self.mutable if line[0] != '#']
fout = os.path.join(getattr(cc.path, self.code.lower()), self.path)
DataIO.testFolderExistence(os.path.join(fout, 'models'))
def __init__(self,code,path,replace_db_entry=0,new_entries=[],\
single_session=0):
"""
Initializing an instance of ModelingSession.
@param code: code for which the modelingsession is created
@type code: string
@param path: modeling output folder in the code's home folder
@type path: string
@keyword replace_db_entry: replace an entry in the database with a
newly calculated model with a new model id
(eg if some general data not included in
the inputfiles is changed)
(default: 0)
@type replace_db_entry: bool
@keyword new_entries: The new model_ids when replace_db_entry is 1
of other models in the grid. These are not
replaced!
(default: [])
@type new_entries: list[str]
@keyword single_session: If this is the only CC session. Speeds up db
check.
(default: 0)
@type single_session: bool
"""
self.path = path
self.code = code
self.model_id = ''
self.replace_db_entry = replace_db_entry
self.new_entries = new_entries
self.single_session = single_session
if code == 'Chemistry':
self.mutable = []
else:
mutablefile = os.path.join(cc.path.aux,\
'Mutable_Parameters_%s.dat'%code)
self.mutable = [line[0]
for line in DataIO.readFile(mutablefile,delimiter=' ')
if ' '.join(line)]
self.mutable = [line for line in self.mutable if line[0] != '#']
fout = os.path.join(getattr(cc.path,self.code.lower()),self.path)
DataIO.testFolderExistence(os.path.join(fout,'models'))
def setSpecies(self, species):
"""
Change the species of the current CustomOpacity instance.
@param species: the species short name
@type species: string
"""
self.species = species
self.index = DataIO.getInputData(keyword='SPECIES_SHORT',\
filename='Dust.dat')\
.index(self.species)
self.filename = DataIO.getInputData(keyword='PART_FILE',\
filename='Dust.dat',\
rindex=self.index)
fn = os.path.join(cc.path.mopac, self.filename)
self.input_data = DataIO.readFile(filename=fn, delimiter=' ')
def setSpecies(self,species):
"""
Change the species of the current CustomOpacity instance.
@param species: the species short name
@type species: string
"""
self.species = species
self.index = DataIO.getInputData(keyword='SPECIES_SHORT',\
filename='Dust.dat')\
.index(self.species)
self.filename = DataIO.getInputData(keyword='PART_FILE',\
filename='Dust.dat',\
rindex=self.index)
fn = os.path.join(cc.path.mopac,self.filename)
self.input_data = DataIO.readFile(filename=fn,delimiter=' ')
def readFile(self, filename, delimiter = ' '):
'''
Read a filename and store its contents in the OutputReader.
The contents are stored in a dictionary, with the filename as key.
The contents can be returned when running getFile.
@param filename: The filename of the outputfile, including filepath
@type filename: string
@keyword delimiter: The delimiter character used in this file.
(default: ' ')
@type delimiter: string
'''
try:
self.contents[filename] = DataIO.readFile(filename, delimiter)
except IOError:
self.contents[filename] = None
def readKappas(self,species):
"""
Read kappas (cm2/g) and Q_ext/a (cm-1) for a dust species from the
MCMax INPUT files.
This also reads the absorption and scattering kappas separately.
@param species: The dust species (from Dust.dat)
@type species: string
"""
if self.waves.has_key(species):
return
try:
ispecies = self.lspecies.index(species)
except ValueError:
print 'Species not found in Dust.dat.'
return
fn = os.path.join(cc.path.mopac,self.lfilenames[ispecies])
sd = self.lspec_dens[ispecies]
if fn[-9:] == '.particle':
part_file = DataIO.readFile(filename=fn,delimiter=' ')
wav = array([float(q[0])
for q in part_file if len(q) == 4])
kappa = [array([float(q[1])
for q in part_file if len(q) == 4]),
array([float(q[2])
for q in part_file if len(q) == 4]),
array([float(q[3])
for q in part_file if len(q) == 4])]
else:
part_file = DataIO.readCols(filename=fn)
wav = part_file[0]
kappa = part_file[1:]
self.waves[species] = wav
self.kappas[species] = kappa
self.qext_a[species] = array(kappa) * 4/3. * sd
def readKappas(self, species):
"""
Read kappas (cm2/g) and Q_ext/a (cm-1) for a dust species from the
MCMax INPUT files.
This also reads the absorption and scattering kappas separately.
@param species: The dust species (from Dust.dat)
@type species: string
"""
if self.waves.has_key(species):
return
try:
ispecies = self.lspecies.index(species)
except ValueError:
print "Species not found in Dust.dat."
return
fn = os.path.join(cc.path.mopac, self.lfilenames[ispecies])
sd = self.lspec_dens[ispecies]
if fn[-9:] == ".particle":
part_file = DataIO.readFile(filename=fn, delimiter=" ")
wav = array([float(q[0]) for q in part_file if len(q) == 4])
kappa = [
array([float(q[1]) for q in part_file if len(q) == 4]),
array([float(q[2]) for q in part_file if len(q) == 4]),
array([float(q[3]) for q in part_file if len(q) == 4]),
]
else:
part_file = DataIO.readCols(filename=fn)
wav = part_file[0]
kappa = part_file[1:]
self.spec_dens[species] = sd
self.fns[species] = fn
self.waves[species] = wav
self.kappas[species] = kappa
self.qext_a[species] = array(kappa) * 4 / 3.0 * sd
def readAnalyse(self, star):
'''
Reads the output of the analyse routine performed.
@keyword star: Star object containing the chemistry model
@type star: Star()
@return: Dictionary containing the analyse output for every
molecule, eg analyse['SiO']. The analyse radius is
also included (analyse['radius']).
@rtype: dict()
'''
#- Read in analyse.out
filename = os.path.join(cc.path.cout,'models',\
star['LAST_CHEMISTRY_MODEL'],'analyse.out')
data = DataIO.readFile(filename)
data = [x.split() for x in data]
#- Initialise output dictionary
analyse = dict()
#- Determine and save routine radius
radius = float(data[0][-2])
index = np.where([len(i)==2 for i in data])[0]
analyse['radius'] = radius
#- Save analyse routine output in dictionary per molecule
for ii in range(len(index[:-1])):
name = data[index[ii]][1][1:]
analyse[name] = dict()
analyse[name]['MAIN'] = data[index[ii]+1:index[ii+1]-1]
analyse[name]['DRATE'] = data[index[ii+1]-1][1]
analyse[name]['PRATE'] = data[index[ii+1]-1][3]
return analyse
def changeKey(k,v,data=None,fn=None):
'''
Update an ALI inputfile with new information.
Takes an input key and value. The file is searched for the key, and the
value is inserted on the next line.
The content is then returned. This method does not save the file.
@param k: The unique input key word for which the ALI inputfile is
searched.
@type k: str
@param v: The value inserted on the next line after key. Must be a
formatted string; no formatting is done here.
@type v: str
@keyword data: The data, ie a file read by readFile with delimiter set to ''
A filename must be given if data is None.
(default: None)
@type data: list[str]
@keyword fn: The ALI input filename. Only used if data is None.
(default: None)
@type fn: str
@return: The data as read from a file or as adapted from the original
@rtype: list[str]
'''
if data is None:
data = DataIO.readFile(filename=fn,delimiter=None,replace_spaces=0)
data = [line.replace('\n','') for line in data]
i = DataIO.findKey(0,data,k)
data[i+1] = v
return data
def readAnalyse(self, star):
'''
Reads the output of the analyse routine performed.
@keyword star: Star object containing the chemistry model
@type star: Star()
@return: Dictionary containing the analyse output for every
molecule, eg analyse['SiO']. The analyse radius is
also included (analyse['radius']).
@rtype: dict()
'''
#- Read in analyse.out
filename = os.path.join(cc.path.cout,'models',\
star['LAST_CHEMISTRY_MODEL'],'analyse.out')
data = DataIO.readFile(filename)
data = [x.split() for x in data]
#- Initialise output dictionary
analyse = dict()
#- Determine and save routine radius
radius = float(data[0][-2])
index = np.where([len(i) == 2 for i in data])[0]
analyse['radius'] = radius
#- Save analyse routine output in dictionary per molecule
for ii in range(len(index[:-1])):
name = data[index[ii]][1][1:]
analyse[name] = dict()
analyse[name]['MAIN'] = data[index[ii] + 1:index[ii + 1] - 1]
analyse[name]['DRATE'] = data[index[ii + 1] - 1][1]
analyse[name]['PRATE'] = data[index[ii + 1] - 1][3]
return analyse
def read(self):
'''
Read the Lamda file, including molecular spectroscopy and collision
rates.
Each level and transition is stored as an index, following the
prescription of MolReader and CollisReader.
'''
#-- Read the files lines, and set the single number properties.
d = DataIO.readFile(self.fn)
self['pars'] = dict()
pars = ['molecule','mol_weight','ny']
dtypes = [str,float,int]
indices = [1,3,5]
for i,p,dt in zip(indices,pars,dtypes):
self['pars'][p] = dt(d[i].split()[0])
#-- Read the levels and their properties. Swap columns 1 and 2 to match
# MlineReader's format.
d1 = np.genfromtxt(self.fn,skip_header=7,max_rows=self['pars']['ny'],\
dtype='i8,f8,f8',usecols=(0,2,1),\
names=['index','weight','energy'])
self['level'] = d1
#-- Determine the index from ny and preset lines
index = 7 + self['pars']['ny'] + 1
self['pars']['nline'] = int(d[index].split()[0])
#-- Read the transitions and their properties. Swap columns 3 and 4 to
# match MlineReader's format.
d2 = np.genfromtxt(self.fn,usecols=[0,1,2,4,3],dtype='i8,i8,i8,f8,f8',\
skip_header=index+2,max_rows=self['pars']['nline'],\
names=['index','lup','llow','frequency','einsteinA'])
self['trans'] = d2
#-- Continue single line parameters.
index += 1 + self['pars']['nline'] + 2
self['pars']['npartners'] = int(d[index].split()[0])
index += 2
self['pars']['partners'] = d[index:index+self['pars']['npartners']]
index += self['pars']['npartners'] + 1
self['pars']['ncoll_trans'] = int(d[index].split()[0])
index += 2
self['pars']['ncoll_temp'] = int(d[index].split()[0])
index += 2
self['coll_temp'] = np.array(d[index].split(),dtype=float)
#-- Read the collision rates.
d3 = np.genfromtxt(self.fn,usecols=[0,1,2],dtype='i8,i8,i8',\
skip_header=index+2,names=['index','lup','llow'])
d4 = np.genfromtxt(self.fn,skip_header=index+2,\
usecols=range(3,3+self['pars']['ncoll_temp']))
dtype = [('index',int),('lup',int),('llow',int),('rates',np.ndarray)]
self['coll_trans'] = np.empty(shape=(self['pars']['ncoll_trans'],),\
dtype=dtype)
self['coll_trans']['index'] = d3['index']
self['coll_trans']['lup'] = d3['lup']
self['coll_trans']['llow'] = d3['llow']
for i in range(self['pars']['ncoll_trans']):
self['coll_trans']['rates'][i] = d4[i,:]
def __init__(self,path_gastronoom='runTest',vic=None,sphinx=0,\
replace_db_entry=0,cool_db=None,ml_db=None,sph_db=None,\
skip_cooling=0,recover_sphinxfiles=0,\
new_entries=[]):
"""
Initializing an instance of a GASTRoNOoM modeling session.
A single cooling model and a given set of molecules and transitions are
calculated here or are retrieved from the databases.
@keyword path_gastronoom: modeling folder in GASTRoNOoM home
(default: 'runTest')
@type path_gastronoom: string
@keyword vic: the vic manager for running sphinx models on VIC3
(default: None)
@type vic: Vic()
@keyword sphinx: Running Sphinx?
(default: 0)
@type sphinx: bool
@keyword replace_db_entry: replace an entry in the databases with a
newly calculated model with a new model id
(e.g. if some general data not included in
the inputfiles is changed)
(default: 0)
@type replace_db_entry: bool
@keyword new_entries: The new model_ids when replace_db_entry is 1
of other models in the grid. These are not
replaced!
(default: [])
@type new_entries: list[str]
@keyword skip_cooling: Skip running cooling in case a model is not
found in the database, for instance if it is
already known that the model will fail
(default: 0)
@type skip_cooling: bool
@keyword recover_sphinxfiles: Try to recover sphinx files from the disk
in case they were correctly calculated,
but not saved to the database for one
reason or another.
(default: 0)
@type recover_sphinxfiles: bool
@keyword cool_db: the cooling database
(default: None)
@type cool_db: Database()
@keyword ml_db: the mline database
(default: None)
@type ml_db: Database()
@keyword sph_db: the sphinx database
(default: None)
@type sph_db: Database()
"""
super(Gastronoom,self).__init__(code='GASTRoNOoM',\
path=path_gastronoom,\
replace_db_entry=replace_db_entry,\
new_entries=new_entries)
#-- Convenience path
cc.path.gout = os.path.join(cc.path.gastronoom,self.path)
self.vic = vic
self.trans_in_progress = []
self.sphinx = sphinx
cool_keys = os.path.join(cc.path.aux,'Input_Keywords_Cooling.dat')
ml_keys = os.path.join(cc.path.aux,'Input_Keywords_Mline.dat')
sph_keys = os.path.join(cc.path.aux,'Input_Keywords_Sphinx.dat')
self.cooling_keywords = [line.strip()
for line in DataIO.readFile(cool_keys)
if line]
self.mline_keywords = [line.strip()
for line in DataIO.readFile(ml_keys)
if line]
self.sphinx_keywords = [line.strip()
for line in DataIO.readFile(sph_keys)
if line]
DataIO.testFolderExistence(os.path.join(cc.path.gout,'data_for_mcmax'))
self.trans_bools = []
self.mline_done = False
self.cool_done = False
self.cooling_molec_keys = ['ENHANCE_ABUNDANCE_FACTOR',\
'ABUNDANCE_FILENAME',\
'NUMBER_INPUT_ABUNDANCE_VALUES',\
'KEYWORD_TABLE','MOLECULE_TABLE',\
'ISOTOPE_TABLE']
self.no_ab_molecs = ['12C16O','13C16O','1H1H16O','p1H1H16O',\
'1H1H17O','p1H1H17O','1H1H18O','p1H1H18O']
#- Read standard input file with all parameters that should be included
filename = os.path.join(cc.path.aux,'inputGASTRoNOoM.dat')
self.standard_inputfile = DataIO.readDict(filename,\
comment_chars=['#','!'])
self.skip_cooling = skip_cooling
self.recover_sphinxfiles = recover_sphinxfiles
self.cool_db = cool_db
self.ml_db = ml_db
self.sph_db = sph_db
def __init__(self,star_name='model',inputfilename=None,\
path='codeJun2010',code='GASTRoNOoM'):
"""
Initializing an instance of PlottingSession.
@keyword star_name: name of the star from Star.dat, use default only
when never using any star model specific things
(default: "model")
@type star_name: string
@keyword path: Output modeling folder in code home folder
(default: 'codeJun2010')
@type path: string
@keyword inputfilename: name of inputfile that is also copied to the
output folder of the plots,
if None nothing is copied
(default: None)
@type inputfilename: string
@keyword code: the modeling code
(default: GASTRoNOoM)
@type code: string
"""
self.inputfilename = inputfilename
self.star_name = star_name
self.star_index = DataIO.getInputData(path=cc.path.usr)\
.index(self.star_name)
self.star_name_plots = DataIO.getInputData(path=cc.path.usr,
keyword='STAR_NAME_PLOTS',\
remove_underscore=1,\
rindex=self.star_index)
#-- Can't use convenience paths here through cc.path, because the
# module is not code specific. Within a single pything session, there
# may be multiple instances of PlottingSession
self.path = path
fn_mcm = os.path.join(cc.path.aux, 'Mutable_Parameters_MCMax.dat')
self.mutable_mcmax = [
line[0] for line in DataIO.readFile(fn_mcm, delimiter=' ')
if ''.join(line).strip()
]
self.mutable_mcmax = [
line for line in self.mutable_mcmax if line[0] != '#'
]
fn_gas = os.path.join(cc.path.aux, 'Mutable_Parameters_GASTRoNOoM.dat')
self.mutable_gastronoom = [line[0]
for line in DataIO.readFile(fn_gas,\
delimiter=' ')
if ''.join(line).strip()]
self.mutable_gastronoom = [
line for line in self.mutable_gastronoom if line[0] != '#'
]
self.mutable = self.mutable_mcmax + self.mutable_gastronoom
self.plot_id = 'plot_%.4i-%.2i-%.2ih%.2i-%.2i-%.2i' \
%(gmtime()[0],gmtime()[1],gmtime()[2],\
gmtime()[3],gmtime()[4],gmtime()[5])
self.code = code
#-- Folder management and copying inputfile to plot output folder
pout = os.path.join(getattr(cc.path,self.code.lower()),self.path,\
'stars')
pstar = os.path.join(pout, self.star_name)
self.pplot = os.path.join(pstar, self.plot_id)
for pp in [pout, pstar, self.pplot]:
DataIO.testFolderExistence(pp)
if self.inputfilename <> None:
ipfn = os.path.split(self.inputfilename)[1]
newf = os.path.join(self.pplot, ipfn)
subprocess.call(['cp %s %s' % (self.inputfilename, newf)],
shell=True)
def makeJobFile(self):
'''
Make the job file that will run the loop on VIC3 and copy the cooling
and mline output to VIC3.
@return: to be printed strings once all the copying is done, which
shows how many transitions are being calculated for which
sphinx model id
@rtype: list[string]
'''
model_id = self.models[self.current_model]
vic_server = '*****@*****.**'%self.account
jobfiles = []
printing = []
for model_id_sphinx in self.sphinx_model_ids[self.current_model]:
these_trans = [trans
for trans in self.transitions[self.current_model]
if trans.getModelId() == model_id_sphinx]
models_in_job = (int(log10(len(these_trans))))**2
if not models_in_job: models_in_job = 1
job_number = len(these_trans)%models_in_job==0.0 \
and len(these_trans)/models_in_job \
or int(len(these_trans)/models_in_job)+1
#- job_number: this is the number of jobs you want to queue
job_number = job_number/8+1
time_per_job = self.time_per_sphinx*models_in_job
walltimestring = '%.2i:00:00'%(int(time_per_job/60)+1)
#- Create job file
jobfile = DataIO.readFile(os.path.join(cc.path.gastronoom,\
'vic_job_example.sh'))
new_jobfile = []
for line in jobfile:
#if line.find('#PBS -l nodes=1:ppn=8') != -1:
# new_line = line.replace('ppn=8','ppn=%i'%)
if line.split('=')[0].find('#PBS -l walltime') != -1:
new_line = '='.join([line.split('=')[0],walltimestring])
elif line.split('=')[0].find('export COCODEHOME') != -1:
new_line = line.replace('vsc30226',self.account)\
.replace('/302/','/%s/'%self.disk)
elif line.split('=')[0].find('export COCODEDATA') != -1:
new_line = '='.join([line.split('=')[0],\
os.path.join(line.split('=')[1],model_id+'_'+\
str(self.current_model)+'/')])\
.replace('vsc30226',self.account)\
.replace('/302/','/%s/'%self.disk)
elif line.find('for i in $(seq 1 1)') != -1:
new_line = 'for i in $(seq 1 %i)'%models_in_job
elif line.split('=')[0].find('export MODELNUMBER') != -1:
new_line = '='.join([line.split('=')[0],line.split('=')[1]\
.replace('model_id',model_id_sphinx)])
else:
new_line = line
new_jobfile.append(new_line)
#- Save job file, change permission and copy to VIC
local_folder = os.path.join(cc.path.gastronoom,\
self.path,'models',model_id_sphinx)
jobfilename_vic = '/user/leuven/'+self.disk+'/' + self.account + \
'/COCode/vic_job_' + model_id_sphinx + '.sh'
jobfilename_local = os.path.join(local_folder,'vic_input',\
'vic_job_%s.sh'%model_id_sphinx)
DataIO.writeFile(jobfilename_local,new_jobfile)
subprocess.call(['chmod +x %s'%jobfilename_local],shell=True)
subprocess.call(['scp %s %s:%s'%(jobfilename_local,vic_server,\
jobfilename_vic)],shell=True)
jobfiles.append((jobfilename_vic,job_number))
#- Make the output folder on VIC
vic_folder = '/data/leuven/%s/%s/COCode/output/%s/'\
%(self.disk,self.account,model_id_sphinx)
subprocess.call('ssh %s mkdir %s'%(vic_server,vic_folder),\
shell=True)
#-copy required GASTRoNOoM files, molecule specific.
these_molecules = set(['sampling'] + \
[trans.molecule.molecule
for trans in these_trans])
to_be_copied = ['coolfgr*','input%s.dat'%model_id_sphinx]
to_be_copied.extend(['cool*_%s.dat'%molec
for molec in these_molecules])
to_be_copied.extend(['ml*_%s.dat'%molec
for molec in these_molecules
if molec != 'sampling'])
for filecopy in to_be_copied:
subprocess.call(['scp %s %s:%s.'\
%(os.path.join(local_folder,filecopy),\
vic_server,vic_folder)], shell=True)
#- number of nodes*number of cpus=amount of times to queue it
printing.append('Running %i jobs with %i models each for ID %s.' \
%(job_number*7, models_in_job,model_id_sphinx))
#- Create the run-jobs file.
runjobsfile = DataIO.readFile(os.path.join(cc.path.gastronoom,\
'vic_run_jobs_example.sh'))
new_runjobsfile = []
for i,job in enumerate(jobfiles):
for line in runjobsfile:
if line.find('#!/bin/bash -l') != -1 and i == 0:
new_line = line
elif line.find('cd COCode') != -1 and i == 0:
new_line = 'cd /user/leuven/'+self.disk+'/'+ self.account+\
'/COCode/'
elif line.find('module load worker') != -1 and i == 0:
new_line = line
elif line.find('for i in $(seq 1 1) ;') != -1:
new_line = 'for i in $(seq 1 %i) ;' %(job[1])
elif line.find('do wsub -A dummy -t 1-8 -batch') != -1:
new_line = line.replace('vic_job_example.sh',\
os.path.split(job[0])[1])
if not self.credits_acc is None:
new_line = new_line.replace('-A dummy',\
'-A %s'%self.credits_acc)
else:
new_line = new_line.replace('-A dummy ','')
elif line.find('done') != -1:
new_line = line
else:
new_line = ''
new_runjobsfile.append(new_line)
#- Run-jobs file: Write, change permission and copy to VIC
runjobsfilename_local = os.path.join(cc.path.gastronoom,self.path,\
'models',model_id,'vic_input',\
'vic_run_jobs_%s_%s.sh'\
%(model_id,\
str(self.current_model)))
runjobsfilename_vic = '/user/leuven/%s/%s/COCode/vic_run_jobs_%s_%s.sh'\
%(self.disk,self.account,model_id,\
str(self.current_model))
DataIO.writeFile(runjobsfilename_local,new_runjobsfile)
subprocess.call(['chmod +x %s'%runjobsfilename_local],shell=True)
subprocess.call(['scp %s %s:%s'\
%(runjobsfilename_local,vic_server,\
runjobsfilename_vic)],shell=True)
return printing
def makeJobFile(self):
'''
Make the job file that will run the loop on VIC3 and copy the cooling
and mline output to VIC3.
@return: to be printed strings once all the copying is done, which
shows how many transitions are being calculated for which
sphinx model id
@rtype: list[string]
'''
model_id = self.models[self.current_model]
vic_server = '*****@*****.**' % self.account
jobfiles = []
printing = []
for model_id_sphinx in self.sphinx_model_ids[self.current_model]:
these_trans = [
trans for trans in self.transitions[self.current_model]
if trans.getModelId() == model_id_sphinx
]
models_in_job = (int(log10(len(these_trans))))**2
if not models_in_job: models_in_job = 1
job_number = len(these_trans)%models_in_job==0.0 \
and len(these_trans)/models_in_job \
or int(len(these_trans)/models_in_job)+1
#- job_number: this is the number of jobs you want to queue
job_number = job_number / 8 + 1
time_per_job = self.time_per_sphinx * models_in_job
walltimestring = '%.2i:00:00' % (int(time_per_job / 60) + 1)
#- Create job file
jobfile = DataIO.readFile(os.path.join(cc.path.gastronoom,\
'vic_job_example.sh'))
new_jobfile = []
for line in jobfile:
#if line.find('#PBS -l nodes=1:ppn=8') != -1:
# new_line = line.replace('ppn=8','ppn=%i'%)
if line.split('=')[0].find('#PBS -l walltime') != -1:
new_line = '='.join([line.split('=')[0], walltimestring])
elif line.split('=')[0].find('export COCODEHOME') != -1:
new_line = line.replace('vsc30226',self.account)\
.replace('/302/','/%s/'%self.disk)
elif line.split('=')[0].find('export COCODEDATA') != -1:
new_line = '='.join([line.split('=')[0],\
os.path.join(line.split('=')[1],model_id+'_'+\
str(self.current_model)+'/')])\
.replace('vsc30226',self.account)\
.replace('/302/','/%s/'%self.disk)
elif line.find('for i in $(seq 1 1)') != -1:
new_line = 'for i in $(seq 1 %i)' % models_in_job
elif line.split('=')[0].find('export MODELNUMBER') != -1:
new_line = '='.join([line.split('=')[0],line.split('=')[1]\
.replace('model_id',model_id_sphinx)])
else:
new_line = line
new_jobfile.append(new_line)
#- Save job file, change permission and copy to VIC
local_folder = os.path.join(cc.path.gastronoom,\
self.path,'models',model_id_sphinx)
jobfilename_vic = '/user/leuven/'+self.disk+'/' + self.account + \
'/COCode/vic_job_' + model_id_sphinx + '.sh'
jobfilename_local = os.path.join(local_folder,'vic_input',\
'vic_job_%s.sh'%model_id_sphinx)
DataIO.writeFile(jobfilename_local, new_jobfile)
subprocess.call(['chmod +x %s' % jobfilename_local], shell=True)
subprocess.call(['scp %s %s:%s'%(jobfilename_local,vic_server,\
jobfilename_vic)],shell=True)
jobfiles.append((jobfilename_vic, job_number))
#- Make the output folder on VIC
vic_folder = '/data/leuven/%s/%s/COCode/output/%s/'\
%(self.disk,self.account,model_id_sphinx)
subprocess.call('ssh %s mkdir %s'%(vic_server,vic_folder),\
shell=True)
#-copy required GASTRoNOoM files, molecule specific.
these_molecules = set(['sampling'] + \
[trans.molecule.molecule
for trans in these_trans])
to_be_copied = ['coolfgr*', 'input%s.dat' % model_id_sphinx]
to_be_copied.extend(
['cool*_%s.dat' % molec for molec in these_molecules])
to_be_copied.extend([
'ml*_%s.dat' % molec for molec in these_molecules
if molec != 'sampling'
])
for filecopy in to_be_copied:
subprocess.call(['scp %s %s:%s.'\
%(os.path.join(local_folder,filecopy),\
vic_server,vic_folder)], shell=True)
#- number of nodes*number of cpus=amount of times to queue it
printing.append('Running %i jobs with %i models each for ID %s.' \
%(job_number*7, models_in_job,model_id_sphinx))
#- Create the run-jobs file.
runjobsfile = DataIO.readFile(os.path.join(cc.path.gastronoom,\
'vic_run_jobs_example.sh'))
new_runjobsfile = []
for i, job in enumerate(jobfiles):
for line in runjobsfile:
if line.find('#!/bin/bash -l') != -1 and i == 0:
new_line = line
elif line.find('cd COCode') != -1 and i == 0:
new_line = 'cd /user/leuven/'+self.disk+'/'+ self.account+\
'/COCode/'
elif line.find('module load worker') != -1 and i == 0:
new_line = line
elif line.find('for i in $(seq 1 1) ;') != -1:
new_line = 'for i in $(seq 1 %i) ;' % (job[1])
elif line.find('do wsub -A dummy -t 1-8 -batch') != -1:
new_line = line.replace('vic_job_example.sh',\
os.path.split(job[0])[1])
if self.credits_acc <> None:
new_line = new_line.replace('-A dummy',\
'-A %s'%self.credits_acc)
else:
new_line = new_line.replace('-A dummy ', '')
elif line.find('done') != -1:
new_line = line
else:
new_line = ''
new_runjobsfile.append(new_line)
#- Run-jobs file: Write, change permission and copy to VIC
runjobsfilename_local = os.path.join(cc.path.gastronoom,self.path,\
'models',model_id,'vic_input',\
'vic_run_jobs_%s_%s.sh'\
%(model_id,\
str(self.current_model)))
runjobsfilename_vic = '/user/leuven/%s/%s/COCode/vic_run_jobs_%s_%s.sh'\
%(self.disk,self.account,model_id,\
str(self.current_model))
DataIO.writeFile(runjobsfilename_local, new_runjobsfile)
subprocess.call(['chmod +x %s' % runjobsfilename_local], shell=True)
subprocess.call(['scp %s %s:%s'\
%(runjobsfilename_local,vic_server,\
runjobsfilename_vic)],shell=True)
return printing
def __init__(self,star_name='model',inputfilename=None,\
path='codeJun2010',code='GASTRoNOoM'):
"""
Initializing an instance of PlottingSession.
@keyword star_name: name of the star from Star.dat, use default only
when never using any star model specific things
(default: "model")
@type star_name: string
@keyword path: Output modeling folder in code home folder
(default: 'codeJun2010')
@type path: string
@keyword inputfilename: name of inputfile that is also copied to the
output folder of the plots,
if None nothing is copied
(default: None)
@type inputfilename: string
@keyword code: the modeling code
(default: GASTRoNOoM)
@type code: string
"""
self.inputfilename = inputfilename
self.star_name = star_name
self.star_index = DataIO.getInputData(path=cc.path.usr)\
.index(self.star_name)
self.star_name_plots = DataIO.getInputData(path=cc.path.usr,
keyword='STAR_NAME_PLOTS',\
remove_underscore=1,\
rindex=self.star_index)
#-- Can't use convenience paths here through cc.path, because the
# module is not code specific. Within a single pything session, there
# may be multiple instances of PlottingSession
self.path = path
fn_mcm = os.path.join(cc.path.aux,'Mutable_Parameters_MCMax.dat')
self.mutable_mcmax = [line[0]
for line in DataIO.readFile(fn_mcm,delimiter=' ')
if ''.join(line).strip()]
self.mutable_mcmax = [line
for line in self.mutable_mcmax
if line[0] != '#']
fn_gas = os.path.join(cc.path.aux,'Mutable_Parameters_GASTRoNOoM.dat')
self.mutable_gastronoom = [line[0]
for line in DataIO.readFile(fn_gas,\
delimiter=' ')
if ''.join(line).strip()]
self.mutable_gastronoom = [line
for line in self.mutable_gastronoom
if line[0] != '#']
self.mutable = self.mutable_mcmax + self.mutable_gastronoom
self.plot_id = 'plot_%.4i-%.2i-%.2ih%.2i-%.2i-%.2i' \
%(gmtime()[0],gmtime()[1],gmtime()[2],\
gmtime()[3],gmtime()[4],gmtime()[5])
self.code = code
#-- Folder management and copying inputfile to plot output folder
pout = os.path.join(getattr(cc.path,self.code.lower()),self.path,\
'stars')
pstar = os.path.join(pout,self.star_name)
self.pplot = os.path.join(pstar,self.plot_id)
for pp in [pout,pstar,self.pplot]:
DataIO.testFolderExistence(pp)
if self.inputfilename <> None:
ipfn = os.path.split(self.inputfilename)[1]
newf = os.path.join(self.pplot,ipfn)
subprocess.call(['cp %s %s'%(self.inputfilename,newf)],shell=True)
def makeMoleculeFromDb(molec_id,molecule,path_gastronoom='codeSep2010',\
mline_db=None):
'''
Make a Molecule() from a database, based on model_id and molec_id.
Returns None if the molecule is not available in the database.
@param molec_id: the model_id of the molecule
@type molec_id: string
@param molecule: the short hand name of the molecule
@type molecule: string
@keyword path_gastronoom: the output path in the ~/GASTRoNOoM/. directory
(default: codeSep2010)
@type path_gastronoom: string
@keyword mline_db: The mline database, which can be passed in case one
wants to reduce overhead. Not required though.
(default: None)
@type mline_db: Database()
@return: the molecule with all its information embedded
@rtype: Molecule()
'''
#-- Convenience path
cc.path.gout = os.path.join(cc.path.gastronoom,path_gastronoom)
#-- Retrieve cooling id log
cooling_log = os.path.join(cc.path.gout,'models',molec_id,'cooling_id.log')
if os.path.isfile(cooling_log):
model_id = DataIO.readFile(cooling_log)[0]
#- ie mline id is the same as model id, the first calced for this id
else:
model_id = molec_id
if mline_db is None:
molec_db = Database(os.path.join(cc.path.gout,\
'GASTRoNOoM_mline_models.db'))
else:
molec_db = mline_db
if not molec_db.has_key(model_id) \
or not molec_db[model_id].has_key(molec_id) \
or not molec_db[model_id][molec_id].has_key(molecule):
return None
molec_dict = molec_db[model_id][molec_id][molecule].copy()
extra_pars = molec_dict['MOLECULE'].split()[1:]
for k,v in zip(['ny_low','ny_up','nline','n_impact','n_impact_extra'],\
extra_pars):
molec_dict[k] = int(v)
for key in ['MOLECULE','CHANGE_DUST_TO_GAS_FOR_ML_SP',\
'NUMBER_INPUT_ABUNDANCE_VALUES','KEYWORD_TABLE',\
'MOLECULE_TABLE','ISOTOPE_TABLE']:
if molec_dict.has_key(key):
del molec_dict[key]
molec_dict = dict([(k.lower(),v) for k,v in molec_dict.items()])
molec_dict['path_gastronoom'] = path_gastronoom
molec = Molecule(molecule=molecule,**molec_dict)
molec.setModelId(molec_id)
return molec
def __init__(self,molecule,ny_up=0,ny_low=0,nline=0,n_impact=0,\
n_impact_extra=0,abun_molec=1.0e-10,abun_molec_rinner=1.0e-10,\
abun_molec_re=1.0e-10,rmax_molec=1.,itera=0,lte_request=None,\
use_collis_radiat_switch=0,dust_to_gas_change_ml_sp=0,\
use_no_maser_option=0,use_maser_in_sphinx=1,\
fehler=1e-4,xdex=2.,n_freq=30,start_approx=0,\
use_fraction_level_corr=1,fraction_level_corr=0.8,\
number_level_max_corr=1e-12,\
ratio_12c_to_13c=0,ratio_16o_to_17o=0,ratio_16o_to_18o=0,\
opr=0,r_outer=0,outer_r_mode='MAMON',abundance_filename=None,\
change_fraction_filename=None,set_keyword_change_abundance=0,\
set_keyword_change_temperature=0,enhance_abundance_factor=0,\
new_temperature_filename=None,linelist=0,starfile='',\
path_gastronoom=None):
'''
Initiate a Molecule class, setting all values for the allowed
transition parameters to zero (by default).
@param molecule: shorthand name of the molecule
@type molecule: string
@keyword ny_up: number of levels in first vibration state v=1
(default: 0)
@type ny_up: int
@keyword ny_low: number of levels in the ground vibration state v=0
(default: 0)
@type ny_low: int
@keyword nline: number of allowed transitions in molecule
(default: 0)
@type nline: int
@keyword n_impact: number of depth points in radius mesh
(default: 0)
@type n_impact: int
@keyword n_impact_extra: number of depth points in radius_mesh
(< n_impact) used for variable mass-loss
(0 if constant mdot)
(default: 0)
@type n_impact_extra: int
@keyword itera: number of iterations in mline for molecule, LTE
approximation if zero
(default: 0)
@type itera: string
@keyword abun_molec: molecular abundance at the stellar radius.
Default is arbitrary, and used if molecule is co
or h2o.
(default: 1.0e-10)
@type abun_molec: float
@keyword abun_molec_rinner: molecular abundance at inner shell radius.
Default is arbitrary, and used if molecule
is co or h2o.
(default: 1.0e-10)
@type abun_molec_rinner: float
@keyword abun_molec_re: molecular abundance at rmax_molec. Default is
arbitrary, and used if molecule is co or h2o.
(default: 1.0e-10)
@type abun_molec_re: float
@keyword rmax_molec: The radius from which the Willacy abundance
profiles are used. They are rescaled to
abun_molec_re. Default is arbitrary, and used if
molecule is co or h2o.
(default: 1.)
@type rmax_molec: float
@keyword use_collis_radiat_switch: in case of unstable mline, such as
for para h2o sometimes
(default: 0)
@type use_collis_radiat_switch: bool
@keyword fehler: convergence criterium in mline
(default: 1e-4)
@type fehler: float
@keyword xdex: Controls the distribution of the impact parameters in the
interval between R_STAR and R_OUTER.
(default: 2.)
@type xdex: float
@keyword n_freq: Number of frequency points in line profile
(default: 30)
@type n_freq: int
@keyword start_approx: set to 0 when one wants to start with LTE-approx
as starting n(NY,N_IMPACT); set to 1 when
starting from another model - with same NY,
N_IMPACT, ...
(default: 0)
@type start_approx: bool
@keyword use_fraction_level_corr: set to 1 if one wants to put a limit
on the level-population correction
(BES3).
(default: 1)
@type use_fraction_level_corr: bool
@keyword fraction_level_corr: user-defined fraction for maximum change
in level-population correction; useful in
case of H2O
(default: 0.8)
@type fraction_level_corr: float
@keyword number_level_max_corr: user-defined level population. Only the
level corrections for levels with a
higher level population will be used to
determine convergence criterion
(default: 1e-12)
@type number_level_max_corr: float
@keyword ratio_12c_to_13c: 12c/13c ratio, only relevant for 13co and
other molecules with that isotope
(default: 0)
@type ratio_12c_to_13c: int
@keyword ratio_16o_to_17o: 16o/17o ratio, only relevant for h2_17o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_17o: int
@keyword ratio_16o_to_18o: 16o/18o ratio, only relevant for h2_18o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_18o: int
@keyword opr: ortho-to-para water ratio, only relevant for ph2o,
ph2_17o,ph2_18o and other molecules with para h2o
(default: 0)
@type opr: int
@keyword r_outer: the outer radius of the shell for this molecule,
0 if MAMON
(default: 0)
@type r_outer: float
@keyword lte_request: using LTE in mline only (with or without
collision rates: determined by itera), if default
lte_request is 0 if itera != 0 and 1 if itera ==0
(default: 0)
@type lte_request: bool
@keyword outer_r_mode: the mode used for calculating r_outer
(FIXED or MAMON)
(default: 'MAMON')
@type outer_r_mode: string
@keyword dust_to_gas_change_ml_sp: if 0 not used, otherwise this is an
alternative value for the
dust-to-gas ratio in mline/sphinx
for this molecule and its
transitions.
(default: 0)
@type dust_to_gas_change_ml_sp: float
@keyword abundance_filename: if enhance_abundance_factor is not zero,
this includes the filename and/or path
to the file that includes the profile.
(default: None)
@type abundance_filename: string
@keyword enhance_abundance_factor: if 0 the Willacy abundance profiles
are uses, if not zero the
abundance_filename is used and
scaled with the factor given here.
THIS DOES NOT RESCALE ABUNDANCES BY
WILLACY! Only used for filename
abundances, hence why this parameter
also turns this feature on/off
(default: 0)
@type enhance_abundance_factor: float
@keyword set_keyword_change_abundance: Change the abundance calculated
in cooling by a radius dependent
factor
(default: 0)
@type set_keyword_change_abundance: bool
@keyword change_fraction_filename: the filename of the enhancement
factors if
set_keyword_change_abundance != 0
(default: None)
@type change_fraction_filename: string
@keyword set_keyword_change_temperature: Use a different temperature
structure in mline and sphinx
(default: 0)
@type set_keyword_change_temperature: bool
@keyword new_temperature_filename: the filename for the temperature
structure if
set_keyword_change_temperature != 0
(default: None)
@type new_temperature_filename: string
@keyword use_no_maser_option: Do not allow masers (neg opacs) in mline
RT by setting negative line opacs to 1e-60
If use_maser_in_sphinx is on, mline
will do a final run including masers
anyway to see what would happen if they
were inluded by allowing negative opacs
for the line profile calculations in
sphinx (but not for the convergence in
mline).
(default: 0)
@type use_no_maser_option: bool
@keyword use_maser_in_sphinx: When on, does a final mline run including
masers, allowing negative opacities. When
off, sets the masing line opacities to
1e-60 when writing out the ml3 file.
(default: 1)
@type use_maser_in_sphinx: bool
@keyword linelist: The molecule is created for the LineList module. No
radiative information is read from GASTRoNOoM input
files.
(default: 0)
@type linelist: bool
@keyword starfile: input filename for a stellar input spectrum (either
user defined or from a model atmosphere spectrum)
(default: '')
@type starfile: str
@keyword path_gastronoom: model output folder in the GASTRoNOoM home
(default: None)
@type path_gastronoom: string
'''
self.molecule = str(molecule)
self.ny_up = int(ny_up)
self.ny_low = int(ny_low)
self.nline = int(nline)
self.n_impact = int(n_impact)
self.n_impact_extra = int(n_impact_extra)
self.path_gastronoom = path_gastronoom
self.molecule_index = DataIO.getInputData(keyword='TYPE_SHORT',\
filename='Molecule.dat')\
.index(self.molecule)
mdata = ['MOLEC_TYPE','NAME_SHORT','NAME_PLOT',\
'SPEC_INDICES','USE_INDICES_DAT']
attrs = ['molecule_full','molecule_short','molecule_plot',\
'spec_indices','use_indices_dat']
mfloat = [0,0,0,1,1]
for k,a,mf in zip(mdata,attrs,mfloat):
setattr(self,a,DataIO.getInputData(keyword=k,make_float=mf,\
filename='Molecule.dat',\
rindex=self.molecule_index,))
self.itera = int(itera)
#- lte_request may be undefined, but then it would be faulty input,
#- where we do want the code to crash...
if self.itera==0 and lte_request is None:
self.lte_request = 1
#- Normally u never use lte if taking into account collision rates
elif self.itera != 0:
self.lte_request = 0
elif self.itera==0 and lte_request is not None:
self.lte_request = lte_request
self.abun_molec = abun_molec
self.abun_molec_rinner = abun_molec_rinner
self.abun_molec_re = abun_molec_re
self.rmax_molec = rmax_molec
self.use_collis_radiat_switch = int(use_collis_radiat_switch)
self.ratio_12c_to_13c = ratio_12c_to_13c
self.ratio_16o_to_17o = ratio_16o_to_17o
self.ratio_16o_to_18o = ratio_16o_to_18o
self.opr = opr
self.dust_to_gas_change_ml_sp = float(dust_to_gas_change_ml_sp)
self.use_no_maser_option = int(use_no_maser_option)
self.use_maser_in_sphinx = int(use_maser_in_sphinx)
self.fehler = fehler
self.xdex = xdex
self.n_freq = int(n_freq)
self.start_approx = int(start_approx)
self.use_fraction_level_corr = int(use_fraction_level_corr)
self.fraction_level_corr = fraction_level_corr
self.number_level_max_corr = number_level_max_corr
#-- Set the molecule inputfiles for abundance and temperature, applying
# the path from Path.dat if the file does not exist or the path to the
# file is not given. (eg a subfolder might be given, but that works)
for k in ['abundance_filename','change_fraction_filename',\
'new_temperature_filename']:
fn = locals()[k]
if fn and not (os.path.isfile(fn) and os.path.split(fn)[0]):
fn = os.path.join(cc.path.molf,fn)
setattr(self,k,fn)
else:
setattr(self,k,fn)
self.enhance_abundance_factor = float(enhance_abundance_factor)
self.set_keyword_change_abundance = int(set_keyword_change_abundance)
self.set_keyword_change_temperature = \
int(set_keyword_change_temperature)
#-- Mainly for plotting purposes: The relative, multiplicative abundance
# factor with respect to main isotope (and OPR) is calculated
# This does not take into account enhance_abundance_factor!
self.abun_factor = self.getAbunFactor()
self.outer_r_mode = outer_r_mode
if self.outer_r_mode == 'MAMON': self.r_outer = 0
else: self.r_outer = float(r_outer)
self.__model_id = None
if not linelist:
if self.use_indices_dat:
tag = '_'.join([self.molecule,str(self.ny_low),\
str(self.ny_up),str(self.nline)])
i = DataIO.getInputData(start_index=4,keyword='MOLECULE',\
filename='Indices.dat').index(tag)
fn = DataIO.getInputData(path=cc.path.usr,keyword='RADIAT',\
filename='Indices.dat',start_index=4,\
rindex=i)
fn = os.path.join(cc.path.gdata,'radiat_backup',fn)
else:
fn = os.path.join(cc.path.gdata,'%s_radiat.dat'%self.molecule)
self.radiat = RadiatReader.RadiatReader(fn=fn,nline=self.nline,
ny=self.ny_up+self.ny_low)
if self.spec_indices:
if self.use_indices_dat:
f = DataIO.getInputData(path=cc.path.usr,start_index=4,\
keyword='INDICES',rindex=i,\
filename='Indices.dat')
filename = os.path.join(cc.path.gdata,'indices_backup',f)
else:
filename = os.path.join(cc.path.gdata,\
'{}_indices.dat'.format(self.molecule))
rf = DataIO.readFile(filename,' ')
self.radiat_indices = [[int(i) for i in line] for line in rf]
else:
self.radiat = None
self.radiat_indices = None
self.starfile = starfile
self.mline = None
def __init__(self,star_name='model',inputfilename=None,\
path='',code='GASTRoNOoM',fn_add_star=1):
"""
Initializing an instance of PlottingSession.
@keyword star_name: name of the star from Star.dat, use default only
when never using any star model specific things
(default: "model")
@type star_name: string
@keyword path: Output modeling folder in code home folder
(default: '')
@type path: string
@keyword inputfilename: name of inputfile that is also copied to the
output folder of the plots,
if None nothing is copied
(default: None)
@type inputfilename: string
@keyword code: the modeling code
(default: GASTRoNOoM)
@type code: string
@keyword fn_add_star: Add the star name to the requested plot filename.
Only relevant if fn_plt is given in a sub method.
(default: 1)
@type fn_add_star: bool
"""
self.inputfilename = inputfilename
self.star_name = star_name
self.star_index = DataIO.getInputData(
path=cc.path.usr).index(star_name)
self.star_name_plots = DataIO.getInputData(path=cc.path.usr,
keyword='STAR_NAME_PLOTS',\
remove_underscore=1,\
rindex=self.star_index)
#-- Can't use convenience paths here through cc.path, because the
# module is not code specific. Within a single python session, there
# may be multiple instances of PlottingSession
if not path:
print('Warning! %s model output folder not set.' % code)
self.path = path
fn_mcm = os.path.join(cc.path.aux, 'Mutable_Parameters_MCMax.dat')
self.mutable_mcmax = [
line[0] for line in DataIO.readFile(fn_mcm, delimiter=' ')
if ''.join(line).strip()
]
self.mutable_mcmax = [
line for line in self.mutable_mcmax if line[0] != '#'
]
fn_gas = os.path.join(cc.path.aux, 'Mutable_Parameters_GASTRoNOoM.dat')
self.mutable_gastronoom = [line[0]
for line in DataIO.readFile(fn_gas,\
delimiter=' ')
if ''.join(line).strip()]
self.mutable_gastronoom = [
line for line in self.mutable_gastronoom if line[0] != '#'
]
self.mutable = self.mutable_mcmax + self.mutable_gastronoom
self.plot_id = 'plot_%.4i-%.2i-%.2ih%.2i-%.2i-%.2i' \
%(gmtime()[0],gmtime()[1],gmtime()[2],\
gmtime()[3],gmtime()[4],gmtime()[5])
self.code = code
#-- Folder management and copying inputfile to plot output folder
pout = os.path.join(getattr(cc.path,self.code.lower()),self.path,\
'stars')
pstar = os.path.join(pout, self.star_name)
self.pplot = os.path.join(pstar, self.plot_id)
for pp in [pout, pstar]:
DataIO.testFolderExistence(pp)
self.fn_add_star = fn_add_star
def __init__(self,molecule,ny_up=0,ny_low=0,nline=0,n_impact=0,\
n_impact_extra=0,abun_molec=1.0e-10,abun_molec_rinner=1.0e-10,\
abun_molec_re=1.0e-10,rmax_molec=1.,itera=0,lte_request=None,\
use_collis_radiat_switch=0,dust_to_gas_change_ml_sp=0,\
ratio_12c_to_13c=0,ratio_16o_to_17o=0,ratio_16o_to_18o=0,\
opr=0,r_outer=0,outer_r_mode='MAMON',abundance_filename=None,\
change_fraction_filename=None,set_keyword_change_abundance=0,\
set_keyword_change_temperature=0,enhance_abundance_factor=0,\
new_temperature_filename=None,linelist=0,starfile=''):
'''
Initiate a Molecule class, setting all values for the allowed
transition parameters to zero (by default).
@param molecule: shorthand name of the molecule
@type molecule: string
@keyword ny_up: number of levels in first vibration state v=1
(default: 0)
@type ny_up: int
@keyword ny_low: number of levels in the ground vibration state v=0
(default: 0)
@type ny_low: int
@keyword nline: number of allowed transitions in molecule
(default: 0)
@type nline: int
@keyword n_impact: number of depth points in radius mesh
(default: 0)
@type n_impact: int
@keyword n_impact_extra: number of depth points in radius_mesh
(< n_impact) used for variable mass-loss
(0 if constant mdot)
(default: 0)
@type n_impact_extra: int
@keyword itera: number of iterations in mline for molecule, LTE
approximation if zero
(default: 0)
@type itera: string
@keyword abun_molec: molecular abundance at the stellar radius.
Default is arbitrary, and used if molecule is co
or h2o.
(default: 1.0e-10)
@type abun_molec: float
@keyword abun_molec_rinner: molecular abundance at inner shell radius.
Default is arbitrary, and used if molecule
is co or h2o.
(default: 1.0e-10)
@type abun_molec_rinner: float
@keyword abun_molec_re: molecular abundance at rmax_molec. Default is
arbitrary, and used if molecule is co or h2o.
(default: 1.0e-10)
@type abun_molec_re: float
@keyword rmax_molec: The radius from which the Willacy abundance
profiles are used. They are rescaled to
abun_molec_re. Default is arbitrary, and used if
molecule is co or h2o.
(default: 1.)
@type rmax_molec: float
@keyword use_collis_radiat_switch: in case of unstable mline, such as
for para h2o sometimes
(default: 0)
@type use_collis_radiat_switch: bool
@keyword ratio_12c_to_13c: 12c/13c ratio, only relevant for 13co and
other molecules with that isotope
(default: 0)
@type ratio_12c_to_13c: int
@keyword ratio_16o_to_17o: 16o/17o ratio, only relevant for h2_17o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_17o: int
@keyword ratio_16o_to_18o: 16o/18o ratio, only relevant for h2_18o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_18o: int
@keyword opr: ortho-to-para water ratio, only relevant for ph2o,
ph2_17o,ph2_18o and other molecules with para h2o
(default: 0)
@type opr: int
@keyword r_outer: the outer radius of the shell for this molecule,
0 if MAMON
(default: 0)
@type r_outer: float
@keyword lte_request: using LTE in mline only (with or without
collision rates: determined by itera), if default
lte_request is 0 if itera != 0 and 1 if itera ==0
(default: 0)
@type lte_request: bool
@keyword outer_r_mode: the mode used for calculating r_outer
(FIXED or MAMON)
(default: 'MAMON')
@type outer_r_mode: string
@keyword dust_to_gas_change_ml_sp: if 0 not used, otherwise this is an
alternative value for the
dust-to-gas ratio in mline/sphinx
for this molecule and its
transitions.
(default: 0)
@type dust_to_gas_change_ml_sp: float
@keyword abundance_filename: if enhance_abundance_factor is not zero,
this includes the filename and/or path
to the file that includes the profile.
(default: None)
@type abundance_filename: string
@keyword enhance_abundance_factor: if 0 the Willacy abundance profiles
are uses, if not zero the
abundance_filename is used and
scaled with the factor given here.
THIS DOES NOT RESCALE ABUNDANCES BY
WILLACY! Only used for filename
abundances, hence why this parameter
also turns this feature on/off
(default: 0)
@type enhance_abundance_factor: float
@keyword set_keyword_change_abundance: Change the abundance calculated
in cooling by a radius dependent
factor
(default: 0)
@type set_keyword_change_abundance: bool
@keyword change_fraction_filename: the filename of the enhancement
factors if
set_keyword_change_abundance != 0
(default: None)
@type change_fraction_filename: string
@keyword set_keyword_change_temperature: Use a different temperature
structure in mline and sphinx
(default: 0)
@type set_keyword_change_temperature: bool
@keyword new_temperature_filename: the filename for the temperature
structure if
set_keyword_change_temperature != 0
(default: None)
@type new_temperature_filename: string
@keyword linelist: The molecule is created for the LineList module. No
radiative information is read from GASTRoNOoM input
files.
(default: 0)
@type linelist: bool
@keyword starfile: input filename for a stellar input spectrum (either
user defined or from a model atmosphere spectrum)
(default: '')
@type starfile: str
'''
self.molecule = str(molecule)
self.ny_up = int(ny_up)
self.ny_low = int(ny_low)
self.nline = int(nline)
self.n_impact = int(n_impact)
self.n_impact_extra = int(n_impact_extra)
self.molecule_index = DataIO.getInputData(keyword='TYPE_SHORT',\
filename='Molecule.dat')\
.index(self.molecule)
mdata = ['MOLEC_TYPE','NAME_SHORT','NAME_PLOT',\
'SPEC_INDICES','USE_INDICES_DAT']
attrs = ['molecule_full','molecule_short','molecule_plot',\
'spec_indices','use_indices_dat']
mfloat = [0, 0, 0, 1, 1]
for k, a, mf in zip(mdata, attrs, mfloat):
setattr(self,a,DataIO.getInputData(keyword=k,make_float=mf,\
filename='Molecule.dat',\
rindex=self.molecule_index,))
self.itera = int(itera)
#- lte_request may be undefined, but then it would be faulty input,
#- where we do want the code to crash...
if self.itera == 0 and lte_request is None:
self.lte_request = 1
#- Normally u never use lte if taking into account collision rates
elif self.itera != 0:
self.lte_request = 0
elif self.itera == 0 and lte_request is not None:
self.lte_request = lte_request
self.abun_molec = abun_molec
self.abun_molec_rinner = abun_molec_rinner
self.abun_molec_re = abun_molec_re
self.rmax_molec = rmax_molec
self.use_collis_radiat_switch = use_collis_radiat_switch
self.ratio_12c_to_13c = ratio_12c_to_13c
self.ratio_16o_to_17o = ratio_16o_to_17o
self.ratio_16o_to_18o = ratio_16o_to_18o
self.opr = opr
self.dust_to_gas_change_ml_sp = float(dust_to_gas_change_ml_sp)
self.enhance_abundance_factor = float(enhance_abundance_factor)
self.abundance_filename = abundance_filename
#-- Mainly for plotting purposes: The relative, multiplicative abundance
# factor with respect to main isotope (and OPR) is calculated
# This does not take into account enhance_abundance_factor!
self.abun_factor = self.getAbunFactor()
self.outer_r_mode = outer_r_mode
if self.outer_r_mode == 'MAMON': self.r_outer = 0
else: self.r_outer = float(r_outer)
self.set_keyword_change_abundance = int(set_keyword_change_abundance)
self.change_fraction_filename = change_fraction_filename
self.set_keyword_change_temperature = \
int(set_keyword_change_temperature)
self.new_temperature_filename = new_temperature_filename
self.__model_id = None
if not linelist:
if self.use_indices_dat:
tag = '_'.join([self.molecule,str(self.ny_low),\
str(self.ny_up),str(self.nline)])
i = DataIO.getInputData(start_index=4,keyword='MOLECULE',\
filename='Indices.dat').index(tag)
self.indices_index = i
self.radiat = Radiat.Radiat(molecule=self)
if self.spec_indices:
if self.use_indices_dat:
f = DataIO.getInputData(path=cc.path.usr,start_index=4,\
keyword='INDICES',rindex=i,\
filename='Indices.dat')
filename = os.path.join(cc.path.gdata, 'indices_backup', f)
else:
filename = os.path.join(cc.path.gdata,\
'%s_indices.dat'%self.molecule)
rf = DataIO.readFile(filename, ' ')
self.radiat_indices = [[int(i) for i in line] for line in rf]
else:
self.radiat = None
self.radiat_indices = None
self.starfile = starfile
def __init__(self,path_gastronoom='runTest',vic=None,sphinx=0,\
replace_db_entry=0,cool_db=None,ml_db=None,sph_db=None,\
skip_cooling=0,recover_sphinxfiles=0,\
new_entries=[]):
"""
Initializing an instance of a GASTRoNOoM modeling session.
A single cooling model and a given set of molecules and transitions are
calculated here or are retrieved from the databases.
@keyword path_gastronoom: modeling folder in GASTRoNOoM home
(default: 'runTest')
@type path_gastronoom: string
@keyword vic: the vic manager for running sphinx models on VIC3
(default: None)
@type vic: Vic()
@keyword sphinx: Running Sphinx?
(default: 0)
@type sphinx: bool
@keyword replace_db_entry: replace an entry in the databases with a
newly calculated model with a new model id
(e.g. if some general data not included in
the inputfiles is changed)
(default: 0)
@type replace_db_entry: bool
@keyword new_entries: The new model_ids when replace_db_entry is 1
of other models in the grid. These are not
replaced!
(default: [])
@type new_entries: list[str]
@keyword skip_cooling: Skip running cooling in case a model is not
found in the database, for instance if it is
already known that the model will fail
(default: 0)
@type skip_cooling: bool
@keyword recover_sphinxfiles: Try to recover sphinx files from the disk
in case they were correctly calculated,
but not saved to the database for one
reason or another.
(default: 0)
@type recover_sphinxfiles: bool
@keyword cool_db: the cooling database
(default: None)
@type cool_db: Database()
@keyword ml_db: the mline database
(default: None)
@type ml_db: Database()
@keyword sph_db: the sphinx database
(default: None)
@type sph_db: Database()
"""
super(Gastronoom,self).__init__(code='GASTRoNOoM',\
path=path_gastronoom,\
replace_db_entry=replace_db_entry,\
new_entries=new_entries)
#-- Convenience path
cc.path.gout = os.path.join(cc.path.gastronoom, self.path)
self.vic = vic
self.trans_in_progress = []
self.sphinx = sphinx
cool_keys = os.path.join(cc.path.aux, 'Input_Keywords_Cooling.dat')
ml_keys = os.path.join(cc.path.aux, 'Input_Keywords_Mline.dat')
sph_keys = os.path.join(cc.path.aux, 'Input_Keywords_Sphinx.dat')
self.cooling_keywords = [
line.strip() for line in DataIO.readFile(cool_keys) if line
]
self.mline_keywords = [
line.strip() for line in DataIO.readFile(ml_keys) if line
]
self.sphinx_keywords = [
line.strip() for line in DataIO.readFile(sph_keys) if line
]
DataIO.testFolderExistence(os.path.join(cc.path.gout,
'data_for_mcmax'))
self.trans_bools = []
self.mline_done = False
self.cool_done = False
self.cooling_molec_keys = ['ENHANCE_ABUNDANCE_FACTOR',\
'ABUNDANCE_FILENAME',\
'NUMBER_INPUT_ABUNDANCE_VALUES',\
'KEYWORD_TABLE','MOLECULE_TABLE',\
'ISOTOPE_TABLE']
self.no_ab_molecs = ['12C16O','13C16O','1H1H16O','p1H1H16O',\
'1H1H17O','p1H1H17O','1H1H18O','p1H1H18O']
#- Read standard input file with all parameters that should be included
filename = os.path.join(cc.path.aux, 'inputGASTRoNOoM.dat')
self.standard_inputfile = DataIO.readDict(filename,\
comment_chars=['#','!'])
self.skip_cooling = skip_cooling
self.recover_sphinxfiles = recover_sphinxfiles
self.cool_db = cool_db
self.ml_db = ml_db
self.sph_db = sph_db
def makeMoleculeFromDb(molec_id,molecule,path_gastronoom='codeSep2010',\
mline_db=None):
'''
Make a Molecule() from a database, based on model_id and molec_id.
Returns None if the molecule is not available in the database.
@param molec_id: the model_id of the molecule
@type molec_id: string
@param molecule: the short hand name of the molecule
@type molecule: string
@keyword path_gastronoom: the output path in the ~/GASTRoNOoM/. directory
(default: codeSep2010)
@type path_gastronoom: string
@keyword mline_db: The mline database, which can be passed in case one
wants to reduce overhead. Not required though.
(default: None)
@type mline_db: Database()
@return: the molecule with all its information embedded
@rtype: Molecule()
'''
#-- Convenience path
cc.path.gout = os.path.join(cc.path.gastronoom,path_gastronoom)
#-- Retrieve cooling id log
cooling_log = os.path.join(cc.path.gout,'models',molec_id,'cooling_id.log')
if os.path.isfile(cooling_log):
model_id = DataIO.readFile(cooling_log)[0]
#- ie mline id is the same as model id, the first calced for this id
else:
model_id = molec_id
if mline_db is None:
molec_db = Database(os.path.join(cc.path.gout,\
'GASTRoNOoM_mline_models.db'))
else:
molec_db = mline_db
if not molec_db.has_key(model_id) \
or not molec_db[model_id].has_key(molec_id) \
or not molec_db[model_id][molec_id].has_key(molecule):
return None
molec_dict = molec_db[model_id][molec_id][molecule].copy()
extra_pars = molec_dict['MOLECULE'].split()[1:]
for k,v in zip(['ny_low','ny_up','nline','n_impact','n_impact_extra'],\
extra_pars):
molec_dict[k] = int(v)
for key in ['MOLECULE','CHANGE_DUST_TO_GAS_FOR_ML_SP',\
'NUMBER_INPUT_ABUNDANCE_VALUES','KEYWORD_TABLE',\
'MOLECULE_TABLE','ISOTOPE_TABLE']:
if molec_dict.has_key(key):
del molec_dict[key]
molec_dict = dict([(k.lower(),v) for k,v in molec_dict.items()])
molec = Molecule(molecule=molecule,**molec_dict)
molec.setModelId(molec_id)
return molec
def __init__(self,star_name='model',inputfilename=None,\
path='',code='GASTRoNOoM',fn_add_star=1):
"""
Initializing an instance of PlottingSession.
@keyword star_name: name of the star from Star.dat, use default only
when never using any star model specific things
(default: "model")
@type star_name: string
@keyword path: Output modeling folder in code home folder
(default: '')
@type path: string
@keyword inputfilename: name of inputfile that is also copied to the
output folder of the plots,
if None nothing is copied
(default: None)
@type inputfilename: string
@keyword code: the modeling code
(default: GASTRoNOoM)
@type code: string
@keyword fn_add_star: Add the star name to the requested plot filename.
Only relevant if fn_plt is given in a sub method.
(default: 1)
@type fn_add_star: bool
"""
self.inputfilename = inputfilename
self.star_name = star_name
self.star_index = DataIO.getInputData(path=cc.path.usr).index(star_name)
self.star_name_plots = DataIO.getInputData(path=cc.path.usr,
keyword='STAR_NAME_PLOTS',\
remove_underscore=1,\
rindex=self.star_index)
#-- Can't use convenience paths here through cc.path, because the
# module is not code specific. Within a single python session, there
# may be multiple instances of PlottingSession
if not path:
print('Warning! %s model output folder not set.'%code)
self.path = path
fn_mcm = os.path.join(cc.path.aux,'Mutable_Parameters_MCMax.dat')
self.mutable_mcmax = [line[0]
for line in DataIO.readFile(fn_mcm,delimiter=' ')
if ''.join(line).strip()]
self.mutable_mcmax = [line
for line in self.mutable_mcmax
if line[0] != '#']
fn_gas = os.path.join(cc.path.aux,'Mutable_Parameters_GASTRoNOoM.dat')
self.mutable_gastronoom = [line[0]
for line in DataIO.readFile(fn_gas,\
delimiter=' ')
if ''.join(line).strip()]
self.mutable_gastronoom = [line
for line in self.mutable_gastronoom
if line[0] != '#']
self.mutable = self.mutable_mcmax + self.mutable_gastronoom
self.plot_id = 'plot_%.4i-%.2i-%.2ih%.2i-%.2i-%.2i' \
%(gmtime()[0],gmtime()[1],gmtime()[2],\
gmtime()[3],gmtime()[4],gmtime()[5])
self.code = code
#-- Folder management and copying inputfile to plot output folder
pout = os.path.join(getattr(cc.path,self.code.lower()),self.path,\
'stars')
pstar = os.path.join(pout,self.star_name)
self.pplot = os.path.join(pstar,self.plot_id)
for pp in [pout,pstar]:
DataIO.testFolderExistence(pp)
self.fn_add_star = fn_add_star
def read(self):
'''
Read the Lamda file, including molecular spectroscopy and collision
rates.
Each level and transition is stored as an index, following the
prescription of MolReader and CollisReader.
'''
#-- Read the files lines, and set the single number properties.
d = DataIO.readFile(self.fn)
self['pars'] = dict()
pars = ['molecule', 'mol_weight', 'ny']
dtypes = [str, float, int]
indices = [1, 3, 5]
for i, p, dt in zip(indices, pars, dtypes):
self['pars'][p] = dt(d[i].split()[0])
#-- Read the levels and their properties. Swap columns 1 and 2 to match
# MlineReader's format.
d1 = np.genfromtxt(self.fn,skip_header=7,max_rows=self['pars']['ny'],\
dtype='i8,f8,f8',usecols=(0,2,1),\
names=['index','weight','energy'])
self['level'] = d1
#-- Determine the index from ny and preset lines
index = 7 + self['pars']['ny'] + 1
self['pars']['nline'] = int(d[index].split()[0])
#-- Read the transitions and their properties. Swap columns 3 and 4 to
# match MlineReader's format.
d2 = np.genfromtxt(self.fn,usecols=[0,1,2,4,3],dtype='i8,i8,i8,f8,f8',\
skip_header=index+2,max_rows=self['pars']['nline'],\
names=['index','lup','llow','frequency','einsteinA'])
self['trans'] = d2
#-- Continue single line parameters.
index += 1 + self['pars']['nline'] + 2
self['pars']['npartners'] = int(d[index].split()[0])
index += 2
self['pars']['partners'] = d[index:index + self['pars']['npartners']]
index += self['pars']['npartners'] + 1
self['pars']['ncoll_trans'] = int(d[index].split()[0])
index += 2
self['pars']['ncoll_temp'] = int(d[index].split()[0])
index += 2
self['coll_temp'] = np.array(d[index].split(), dtype=float)
#-- Read the collision rates.
d3 = np.genfromtxt(self.fn,usecols=[0,1,2],dtype='i8,i8,i8',\
skip_header=index+2,names=['index','lup','llow'])
d4 = np.genfromtxt(self.fn,skip_header=index+2,\
usecols=range(3,3+self['pars']['ncoll_temp']))
dtype = [('index', int), ('lup', int), ('llow', int),
('rates', np.ndarray)]
self['coll_trans'] = np.empty(shape=(self['pars']['ncoll_trans'],),\
dtype=dtype)
self['coll_trans']['index'] = d3['index']
self['coll_trans']['lup'] = d3['lup']
self['coll_trans']['llow'] = d3['llow']
for i in range(self['pars']['ncoll_trans']):
self['coll_trans']['rates'][i] = d4[i, :]
def __init__(self,molecule,ny_up=0,ny_low=0,nline=0,n_impact=0,\
n_impact_extra=0,abun_molec=1.0e-10,abun_molec_rinner=1.0e-10,\
abun_molec_re=1.0e-10,rmax_molec=1.,itera=0,lte_request=None,\
use_collis_radiat_switch=0,dust_to_gas_change_ml_sp=0,\
ratio_12c_to_13c=0,ratio_16o_to_17o=0,ratio_16o_to_18o=0,\
opr=0,r_outer=0,outer_r_mode='MAMON',abundance_filename=None,\
change_fraction_filename=None,set_keyword_change_abundance=0,\
set_keyword_change_temperature=0,enhance_abundance_factor=0,\
new_temperature_filename=None,linelist=0,starfile=''):
'''
Initiate a Molecule class, setting all values for the allowed
transition parameters to zero (by default).
@param molecule: shorthand name of the molecule
@type molecule: string
@keyword ny_up: number of levels in first vibration state v=1
(default: 0)
@type ny_up: int
@keyword ny_low: number of levels in the ground vibration state v=0
(default: 0)
@type ny_low: int
@keyword nline: number of allowed transitions in molecule
(default: 0)
@type nline: int
@keyword n_impact: number of depth points in radius mesh
(default: 0)
@type n_impact: int
@keyword n_impact_extra: number of depth points in radius_mesh
(< n_impact) used for variable mass-loss
(0 if constant mdot)
(default: 0)
@type n_impact_extra: int
@keyword itera: number of iterations in mline for molecule, LTE
approximation if zero
(default: 0)
@type itera: string
@keyword abun_molec: molecular abundance at the stellar radius.
Default is arbitrary, and used if molecule is co
or h2o.
(default: 1.0e-10)
@type abun_molec: float
@keyword abun_molec_rinner: molecular abundance at inner shell radius.
Default is arbitrary, and used if molecule
is co or h2o.
(default: 1.0e-10)
@type abun_molec_rinner: float
@keyword abun_molec_re: molecular abundance at rmax_molec. Default is
arbitrary, and used if molecule is co or h2o.
(default: 1.0e-10)
@type abun_molec_re: float
@keyword rmax_molec: The radius from which the Willacy abundance
profiles are used. They are rescaled to
abun_molec_re. Default is arbitrary, and used if
molecule is co or h2o.
(default: 1.)
@type rmax_molec: float
@keyword use_collis_radiat_switch: in case of unstable mline, such as
for para h2o sometimes
(default: 0)
@type use_collis_radiat_switch: bool
@keyword ratio_12c_to_13c: 12c/13c ratio, only relevant for 13co and
other molecules with that isotope
(default: 0)
@type ratio_12c_to_13c: int
@keyword ratio_16o_to_17o: 16o/17o ratio, only relevant for h2_17o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_17o: int
@keyword ratio_16o_to_18o: 16o/18o ratio, only relevant for h2_18o and
other molecules with that isotope
(default: 0)
@type ratio_16o_to_18o: int
@keyword opr: ortho-to-para water ratio, only relevant for ph2o,
ph2_17o,ph2_18o and other molecules with para h2o
(default: 0)
@type opr: int
@keyword r_outer: the outer radius of the shell for this molecule,
0 if MAMON
(default: 0)
@type r_outer: float
@keyword lte_request: using LTE in mline only (with or without
collision rates: determined by itera), if default
lte_request is 0 if itera != 0 and 1 if itera ==0
(default: 0)
@type lte_request: bool
@keyword outer_r_mode: the mode used for calculating r_outer
(FIXED or MAMON)
(default: 'MAMON')
@type outer_r_mode: string
@keyword dust_to_gas_change_ml_sp: if 0 not used, otherwise this is an
alternative value for the
dust-to-gas ratio in mline/sphinx
for this molecule and its
transitions.
(default: 0)
@type dust_to_gas_change_ml_sp: float
@keyword abundance_filename: if enhance_abundance_factor is not zero,
this includes the filename and/or path
to the file that includes the profile.
(default: None)
@type abundance_filename: string
@keyword enhance_abundance_factor: if 0 the Willacy abundance profiles
are uses, if not zero the
abundance_filename is used and
scaled with the factor given here.
THIS DOES NOT RESCALE ABUNDANCES BY
WILLACY! Only used for filename
abundances, hence why this parameter
also turns this feature on/off
(default: 0)
@type enhance_abundance_factor: float
@keyword set_keyword_change_abundance: Change the abundance calculated
in cooling by a radius dependent
factor
(default: 0)
@type set_keyword_change_abundance: bool
@keyword change_fraction_filename: the filename of the enhancement
factors if
set_keyword_change_abundance != 0
(default: None)
@type change_fraction_filename: string
@keyword set_keyword_change_temperature: Use a different temperature
structure in mline and sphinx
(default: 0)
@type set_keyword_change_temperature: bool
@keyword new_temperature_filename: the filename for the temperature
structure if
set_keyword_change_temperature != 0
(default: None)
@type new_temperature_filename: string
@keyword linelist: The molecule is created for the LineList module. No
radiative information is read from GASTRoNOoM input
files.
(default: 0)
@type linelist: bool
@keyword starfile: input filename for a stellar input spectrum (either
user defined or from a model atmosphere spectrum)
(default: '')
@type starfile: str
'''
self.molecule = str(molecule)
self.ny_up = int(ny_up)
self.ny_low = int(ny_low)
self.nline = int(nline)
self.n_impact = int(n_impact)
self.n_impact_extra = int(n_impact_extra)
self.molecule_index = DataIO.getInputData(keyword='TYPE_SHORT',\
filename='Molecule.dat')\
.index(self.molecule)
mdata = ['MOLEC_TYPE','NAME_SHORT','NAME_PLOT',\
'SPEC_INDICES','USE_INDICES_DAT']
attrs = ['molecule_full','molecule_short','molecule_plot',\
'spec_indices','use_indices_dat']
mfloat = [0,0,0,1,1]
for k,a,mf in zip(mdata,attrs,mfloat):
setattr(self,a,DataIO.getInputData(keyword=k,make_float=mf,\
filename='Molecule.dat',\
rindex=self.molecule_index,))
self.itera = int(itera)
#- lte_request may be undefined, but then it would be faulty input,
#- where we do want the code to crash...
if self.itera==0 and lte_request is None:
self.lte_request = 1
#- Normally u never use lte if taking into account collision rates
elif self.itera != 0:
self.lte_request = 0
elif self.itera==0 and lte_request is not None:
self.lte_request = lte_request
self.abun_molec = abun_molec
self.abun_molec_rinner = abun_molec_rinner
self.abun_molec_re = abun_molec_re
self.rmax_molec = rmax_molec
self.use_collis_radiat_switch = use_collis_radiat_switch
self.ratio_12c_to_13c = ratio_12c_to_13c
self.ratio_16o_to_17o = ratio_16o_to_17o
self.ratio_16o_to_18o = ratio_16o_to_18o
self.opr = opr
self.dust_to_gas_change_ml_sp = float(dust_to_gas_change_ml_sp)
self.enhance_abundance_factor = float(enhance_abundance_factor)
self.abundance_filename = abundance_filename
#-- Mainly for plotting purposes: The relative, multiplicative abundance
# factor with respect to main isotope (and OPR) is calculated
# This does not take into account enhance_abundance_factor!
self.abun_factor = self.getAbunFactor()
self.outer_r_mode = outer_r_mode
if self.outer_r_mode == 'MAMON': self.r_outer = 0
else: self.r_outer = float(r_outer)
self.set_keyword_change_abundance = int(set_keyword_change_abundance)
self.change_fraction_filename = change_fraction_filename
self.set_keyword_change_temperature = \
int(set_keyword_change_temperature)
self.new_temperature_filename = new_temperature_filename
self.__model_id = None
if not linelist:
if self.use_indices_dat:
tag = '_'.join([self.molecule,str(self.ny_low),\
str(self.ny_up),str(self.nline)])
i = DataIO.getInputData(start_index=4,keyword='MOLECULE',\
filename='Indices.dat').index(tag)
self.indices_index = i
self.radiat = Radiat.Radiat(molecule=self)
if self.spec_indices:
if self.use_indices_dat:
f = DataIO.getInputData(path=cc.path.usr,start_index=4,\
keyword='INDICES',rindex=i,\
filename='Indices.dat')
filename = os.path.join(cc.path.gdata,'indices_backup',f)
else:
filename = os.path.join(cc.path.gdata,\
'%s_indices.dat'%self.molecule)
rf = DataIO.readFile(filename,' ')
self.radiat_indices = [[int(i) for i in line] for line in rf]
else:
self.radiat = None
self.radiat_indices = None
self.starfile = starfile
def appendResults(self):
'''
Append results at the end of the inputfile.
'''
print '** Appending results to inputfile and copying to output folders.'
print '***********************************'
#-- Check if the transition was intended to be calculated, and if it was
#-- successful (ie don't add if it had already been done)
timestring = '%.4i-%.2i-%.2ih%.2i-%.2i-%.2i'\
%(time.gmtime()[0],time.gmtime()[1],time.gmtime()[2],\
time.gmtime()[3],time.gmtime()[4],time.gmtime()[5])
appendage = []
if self.model_manager.trans_bool_list:
model_ids_list = [list(set([(trans.molecule.molecule,\
trans.getModelId())
for boolean,trans in zip(trans_bool,\
star['GAS_LINES'])
if trans.getModelId() \
and (not trans_bool \
or self.append_results)]))
for star,trans_bool in zip(self.star_grid,\
self.model_manager.trans_bool_list)]
#-- all unique molecules over all stars
molec_list = list(set([molec
for model_ids in model_ids_list
for molec,model_id in model_ids
if model_ids]))
#-- all unique modelids for every star separately
model_id_unique = [list(set([model_id
for molec,model_id in model_ids]))
for model_ids in model_ids_list]
if [modelids for modelids in model_ids_list if modelids] != []:
appendage += \
['#########################################',\
'## Successfully calculated transition model_ids on %s:'\
%timestring]
appendage.extend(['## molecule %s'%molec
for molec in molec_list])
for i,(star,model_ids) in enumerate(zip(self.star_grid,\
model_ids_list)):
if model_ids:
appendage += ['## For Model %i : cooling id %s'\
%(i+1,star['LAST_GASTRONOOM_MODEL'])] + \
['#molecule %s #%s' %(molecule,model_id)
for molecule,model_id in model_ids] + \
['########']
for star,model_ids in zip(self.star_grid,model_id_unique):
for model_id in model_ids:
try:
i = 0
while True:
dummy = DataIO.readFile(\
os.path.join(cc.path.gout,'models',model_id,\
os.path.split(self.inputfilename)[1]+\
'_%s_%i'%(model_id,i)))
i += 1
except IOError:
subprocess.call(['cp %s %s'%(self.inputfilename,\
os.path.join(cc.path.gout,\
'models',model_id,\
os.path.split(self.inputfilename)[1]+\
'_%s_%i'%(model_id,i)))],shell=True)
if self.model_manager.mcmax_done_list:
model_ids = [star['LAST_MCMAX_MODEL']
for star,boolean in zip(self.star_grid,\
self.model_manager.mcmax_done_list)
if boolean or self.append_results]
if model_ids:
appendage += ['#########################################',\
'## MCMax model_ids associated with this grid on %s:'\
%timestring]
appendage += ['#%s'%model_id for model_id in model_ids]
for model_id in model_ids:
try:
i = 0
while True:
dummy = DataIO.readFile(os.path.join(\
cc.path.mout,'models',model_id,\
os.path.split(self.inputfilename)[1]+\
'_%s_%i'%(model_id,i)))
i += 1
except IOError:
subprocess.call(['cp %s %s'%(self.inputfilename,os.path.join(\
cc.path.mout,'models',model_id,\
os.path.split(self.inputfilename)[1]+\
'_%s_%i'%(model_id,i)))],shell=True)
if appendage: DataIO.writeFile(filename=self.inputfilename,\
input_lines=appendage+['\n'],mode='a')
def doChemistry(self,star):
"""
Running Chemistry.
@param star: The parameter set for this session
@type star: Star()
"""
print '***********************************'
#- Create the input dictionary for this Chemistry run
print '** Making input file for Chemistry'
#-- Add the previous model_id to the list of new entries, so it does
# not get deleted if replace_db_entry == 1.
if self.model_id:
self.new_entries.append(self.model_id)
self.model_id = ''
self.command_list = dict()
# Bijzonder gevallen hier ipv in loop over orig
# Dan is input_lines/command_list wat er in de database staat
# input_lines = d
if star['PERFORM_ROUTINE'] == 0:
self.command_list['ROUTINE_RADIUS'] = 0
else:
self.command_list['ROUTINE_RADIUS'] = star['ROUTINE_RADIUS']
#*star['R_STAR']*star.Rsun
self.command_list['R_STAR'] = star['R_STAR']*star.Rsun
#self.command_list['R_INNER_CHEM'] = star['R_INNER_CHEM']*\
#star['R_STAR']*star.Rsun
#self.command_list['R_OUTER_CHEM'] = star['R_OUTER_CHEM']*\
#star['R_STAR']*star.Rsun
self.command_list['REACTIONS_FILE'] = '"'+os.path.join(cc.path.csource,\
'rates',star['REACTIONS_FILE'])+'"'
self.command_list['SPECIES_FILE'] = '"'+os.path.join(cc.path.csource,\
'specs',star['SPECIES_FILE'])+'"'
self.command_list['FILECO'] = '"'+os.path.join(cc.path.csource,\
'shielding',star['FILECO'])+'"'
self.command_list['FILEN2'] = '"'+os.path.join(cc.path.csource,\
star['FILEN2'])+'"'
add_keys = [k
for k in self.standard_inputfile.keys()
if not self.command_list.has_key(k)]
[self.setCommandKey(k,star,star_key=k.upper(),\
alternative=self.standard_inputfile[k])
for k in add_keys]
print '** DONE!'
print '***********************************'
#-- Check the Chemistry database if the model was calculated before
modelbool = self.checkDatabase()
#-- if no match found in database, calculate new model with new model id
#-- if the calculation did not fail, add entry to database for new model
if not modelbool:
input_dict = self.command_list.copy()
input_lines = []
orig = DataIO.readFile(self.inputfilename)
for i,s in enumerate(orig):
split = s.split()
if s[0] == '!':
input_lines.append(s)
else:
input_lines.append(" ".join(split[0:2])+' '+\
str(self.command_list[split[0]]))
output_folder = os.path.join(cc.path.cout,'models',self.model_id)
DataIO.testFolderExistence(output_folder)
input_lines.append('OUTPUT_FOLDER = "' +\
output_folder+'/"')
input_filename = os.path.join(cc.path.cout,'models',\
'inputChemistry_%s.txt'%self.model_id)
DataIO.writeFile(filename=input_filename,input_lines=input_lines)
#subprocess.call(' '.join([cc.path.ccode,input_filename]),shell=True)
subprocess.call(' '.join([os.path.join(cc.path.csource,'csmodel'),input_filename]),shell=True)
# files die worden aangemaakt op einde, test of successvol
testf1 = os.path.join(output_folder,'cscoldens.out')
testf2 = os.path.join(output_folder,'csfrac.out')
if os.path.exists(testf1) and os.path.exists(testf2) and \
os.path.isfile(testf1) and os.path.isfile(testf2):
del self.db[self.model_id]['IN_PROGRESS']
self.db.addChangedKey(self.model_id)
else:
print '** Model calculation failed. No entry is added to ' + \
'the database.'
del self.db[self.model_id]
self.model_id = ''
if not self.single_session: self.db.sync()
#- Note that the model manager now adds/changes MUTABLE input keys,
#- which MAY be overwritten by the input file inputComboCode.dat
print '***********************************'
