original_docstring: 
          Create a dictionary of surface type and its respective DDF.
  
          Convention: [0=off-glacier, 1=ice, 2=snow, 3=firn, 4=debris]
  
          To-do list
          ----------
          - Add option_surfacetype_initial to specify an AAR ratio and apply this to estimate initial conditions
  
          Parameters
          ----------
          modelprms : dictionary
              Model parameters may include kp (precipitation factor), precgrad (precipitation gradient), ddfsnow, ddfice,
              tsnow_threshold (temperature threshold for snow/rain), tbias (temperature bias)
          include_firn : Boolean
              Option to include or exclude firn (specified in pygem_pygem_prms.py)
          option_ddf_firn : int
              Option for the degree day factor of firn to be the average of snow and ice or a different value
  
          Returns
          -------
          surfacetype_ddf_dict : dictionary
              Dictionary relating the surface types with their respective degree day factors
          
docstring: Create a dictionary of surface type and its respective DDF.
  
  
  
  Add option_surfacetype_initial to specify an AAR ratio and apply this to estimate initial conditions
  
  Parameters
  
  modelprms : dictionary
  Model parameters may include kp (precipitation factor), precgrad (precipitation gradient), ddfsnow, ddfice,
  tsnow_threshold (temperature threshold for snow/rain), tbias (temperature bias)
  include_firn : Boolean
  Option to include or exclude firn (specified in pygem_pygem_prms.py)
  option_ddf_firn : int
  Option for the degree day factor of firn to be the average of snow and ice or a different value
  
  Returns
  
  surfacetype_ddf_dict : dictionary
  Dictionary relating the surface types with their respective degree day factors
docstring_tokens: Create a dictionary of surface type and its respective DDF . Add option_surfacetype_initial to specify an AAR ratio and apply this to estimate initial conditions Parameters modelprms : dictionary Model parameters may include kp ( precipitation factor ) precgrad ( precipitation gradient ) ddfsnow ddfice tsnow_threshold ( temperature threshold for snow / rain ) tbias ( temperature bias ) include_firn : Boolean Option to include or exclude firn ( specified in pygem_pygem_prms . py ) option_ddf_firn : int Option for the degree day factor of firn to be the average of snow and ice or a different value Returns surfacetype_ddf_dict : dictionary Dictionary relating the surface types with their respective degree day factors
code: def _surfacetypeDDFdict(self, modelprms, include_firn=pygem_prms.include_firn,
                              option_ddf_firn=pygem_prms.option_ddf_firn):
          """
          Create a dictionary of surface type and its respective DDF.
  
          Convention: [0=off-glacier, 1=ice, 2=snow, 3=firn, 4=debris]
  
          To-do list
          ----------
          - Add option_surfacetype_initial to specify an AAR ratio and apply this to estimate initial conditions
  
          Parameters
          ----------
          modelprms : dictionary
              Model parameters may include kp (precipitation factor), precgrad (precipitation gradient), ddfsnow, ddfice,
              tsnow_threshold (temperature threshold for snow/rain), tbias (temperature bias)
          include_firn : Boolean
              Option to include or exclude firn (specified in pygem_pygem_prms.py)
          option_ddf_firn : int
              Option for the degree day factor of firn to be the average of snow and ice or a different value
  
          Returns
          -------
          surfacetype_ddf_dict : dictionary
              Dictionary relating the surface types with their respective degree day factors
          """
          surfacetype_ddf_dict = {
                  0: modelprms['ddfsnow'],
                  1: modelprms['ddfice'],
                  2: modelprms['ddfsnow']}
          if include_firn:
              if option_ddf_firn == 0:
                  surfacetype_ddf_dict[3] = modelprms['ddfsnow']
              elif option_ddf_firn == 1:
                  surfacetype_ddf_dict[3] = np.mean([modelprms['ddfsnow'],modelprms['ddfice']])
          return surfacetype_ddf_dict
code_tokens: def _surfacetypeDDFdict ( self , modelprms , include_firn = pygem_prms . include_firn , option_ddf_firn = pygem_prms . option_ddf_firn ) : surfacetype_ddf_dict = { 0 : modelprms [ 'ddfsnow' ] , 1 : modelprms [ 'ddfice' ] , 2 : modelprms [ 'ddfsnow' ] } if include_firn : if option_ddf_firn == 0 : surfacetype_ddf_dict [ 3 ] = modelprms [ 'ddfsnow' ] elif option_ddf_firn == 1 : surfacetype_ddf_dict [ 3 ] = np . mean ( [ modelprms [ 'ddfsnow' ] , modelprms [ 'ddfice' ] ] ) return surfacetype_ddf_dict
short_docstring: Create a dictionary of surface type and its respective DDF.
short_docstring_tokens: Create a dictionary of surface type and its respective DDF .
comment: """
          Create a dictionary of surface type and its respective DDF.
  
          Convention: [0=off-glacier, 1=ice, 2=snow, 3=firn, 4=debris]
  
          To-do list
          ----------
          - Add option_surfacetype_initial to specify an AAR ratio and apply this to estimate initial conditions
  
          Parameters
          ----------
          modelprms : dictionary
              Model parameters may include kp (precipitation factor), precgrad (precipitation gradient), ddfsnow, ddfice,
              tsnow_threshold (temperature threshold for snow/rain), tbias (temperature bias)
          include_firn : Boolean
              Option to include or exclude firn (specified in pygem_pygem_prms.py)
          option_ddf_firn : int
              Option for the degree day factor of firn to be the average of snow and ice or a different value
  
          Returns
          -------
          surfacetype_ddf_dict : dictionary
              Dictionary relating the surface types with their respective degree day factors
          """