Source Code for Module ComboCode.cc.tools.readers.LamdaReader

  1  # -*- coding: utf-8 -*- 
  2   
  3  """ 
  4  A class for reading Lamda molecular data files. See: 
  5  http://home.strw.leidenuniv.nl/~moldata/ 
  6   
  7  Author: R. Lombaert 
  8   
  9  """ 
 10   
 11  import os 
 12  import numpy as np 
 13   
 14  from cc.tools.readers.CollisReader import CollisReader 
 15  from cc.tools.readers.MolReader import MolReader 
 16  from cc.tools.io import DataIO 
 17   
 18   
 19   
 20 -class LamdaReader(MolReader,CollisReader): 
 21       
 22      ''' 
 23      A Reader for Lamda molecular data files.  
 24       
 25      For more information on the Lamda molecular data files, see: 
 26      http://home.strw.leidenuniv.nl/~moldata/ 
 27      Lamda files are the input spectroscopic and collisional data files for  
 28      MCP/ALI. 
 29   
 30      Provides methods to manage molecular spectroscopic data (excitation  
 31      levels, Einstein A coefficients, transitions, etc) through inheritance from  
 32      the MolReader class, and methods to manage collisional rate data through  
 33      inheritance from the CollisReader class.  
 34       
 35      Note that both parents have methods getTI, getTUpper, getTLower. It  
 36      functions the same, and the default will be MolReader's method. If you want  
 37      to retrieve trans indices for the collision rates, specify the itype as  
 38      'coll_trans'. 
 39       
 40      ''' 
 41       
 42 -    def __init__(self,fn,*args,**kwargs): 
 43           
 44          ''' 
 45          Creating a LamdaReader object ready for reading Lamda molecular data. 
 46           
 47          A full filename is required. 
 48           
 49          Additional args/kwargs are used for the dict creation of the parent of  
 50          Reader. 
 51           
 52          @param fn: The lamda data filename, including filepath. 
 53          @type fn: string         
 54           
 55          ''' 
 56   
 57          super(LamdaReader, self).__init__(fn=fn,*args,**kwargs) 
 58          self.read() 
 59           
 60   
 61   
 62 -    def read(self): 
 63       
 64          ''' 
 65          Read the Lamda file, including molecular spectroscopy and collision  
 66          rates. 
 67           
 68          Each level and transition is stored as an index, following the  
 69          prescription of MolReader and CollisReader. 
 70           
 71          ''' 
 72           
 73          #-- Read the files lines, and set the single number properties. 
 74          d = DataIO.readFile(self.fn) 
 75          self['pars'] = dict() 
 76          pars = ['molecule','mol_weight','ny'] 
 77          dtypes = [str,float,int] 
 78          indices = [1,3,5] 
 79          for i,p,dt in zip(indices,pars,dtypes): 
 80              self['pars'][p] = dt(d[i].split()[0]) 
 81           
 82          #-- Read the levels and their properties. Swap columns 1 and 2 to match 
 83          #   MlineReader's format. 
 84          d1 = np.genfromtxt(self.fn,skip_header=7,max_rows=self['pars']['ny'],\ 
 85                             dtype='i8,f8,f8',usecols=(0,2,1),\ 
 86                             names=['index','weight','energy']) 
 87          self['level'] = d1 
 88           
 89          #-- Determine the index from ny and preset lines 
 90          index = 7 + self['pars']['ny'] + 1 
 91          self['pars']['nline'] = int(d[index].split()[0]) 
 92           
 93          #-- Read the transitions and their properties. Swap columns 3 and 4 to 
 94          #   match MlineReader's format. 
 95          d2 = np.genfromtxt(self.fn,usecols=[0,1,2,4,3],dtype='i8,i8,i8,f8,f8',\ 
 96                             skip_header=index+2,max_rows=self['pars']['nline'],\ 
 97                             names=['index','lup','llow','frequency','einsteinA']) 
 98          self['trans'] = d2 
 99           
100          #-- Continue single line parameters. 
101          index += 1 + self['pars']['nline'] + 2 
102          self['pars']['npartners'] = int(d[index].split()[0]) 
103          index += 2 
104          self['pars']['partners'] = d[index:index+self['pars']['npartners']] 
105          index += self['pars']['npartners'] + 1 
106          self['pars']['ncoll_trans'] = int(d[index].split()[0]) 
107          index += 2 
108          self['pars']['ncoll_temp'] = int(d[index].split()[0]) 
109          index += 2 
110          self['coll_temp'] = np.array(d[index].split(),dtype=float) 
111           
112          #-- Read the collision rates.  
113          d3 = np.genfromtxt(self.fn,usecols=[0,1,2],dtype='i8,i8,i8',\ 
114                             skip_header=index+2,names=['index','lup','llow']) 
115          d4 = np.genfromtxt(self.fn,skip_header=index+2,\ 
116                             usecols=range(3,3+self['pars']['ncoll_temp']))         
117          dtype = [('index',int),('lup',int),('llow',int),('rates',np.ndarray)] 
118          self['coll_trans'] = np.empty(shape=(self['pars']['ncoll_trans'],),\ 
119                                        dtype=dtype) 
120          self['coll_trans']['index'] = d3['index'] 
121          self['coll_trans']['lup'] = d3['lup'] 
122          self['coll_trans']['llow'] = d3['llow'] 
123          for i in range(self['pars']['ncoll_trans']): 
124              self['coll_trans']['rates'][i] = d4[i,:] 
125