new_contents: ''' Represents a Ferret variable that is part of a forecast-model-run collection '''
  
  from __future__ import print_function
  
  import pyferret
  
  _fmrc_var_qualifier = '__new_fmrc_variable__'
  
  class FerFMRCVar(pyferret.FerVar):
      '''
      FerVar that is part of a FerFMRC (forecast-model-run collection dataset).
      Such a Ferret variable has restrictions on the time and forecast axes,
      and has special transformations to better view the quality of the forecast 
      represented by this variable.
      '''
  
      def __init__(self, qual):
          '''
          Creates a FerFMRCVar, which is a FerVar that is part of a FerFMRC 
          (forecast-model-run collection dataset).  FerFMRCVar objects should 
          only be created by an FerFMRC object; this constructor should never 
          be called directly.
          '''
          super(FerFMRCVar, self).__init__()
          if not qual == __fmrc_var_qualifier:
             raise  ValueError('FerFMRCVar objects should only be created by FerFMRC dataset objects')
  
      def diagform(self):
          '''
          Returns an anonymous FerVar that is the transformation of this FerFMRCVar 
          to a "diagonal" form, where the T (time) axis is the date forecasted and 
          the F (forecast) axis is the date the forecast was made.
          '''
          if (not self._varname) or (not self._dsetname):
              raise ValueError('Invalid FerFMRCVar object')
          # TF_TIMES is an automatically generated variable for FMRC datasets in Ferret
          # TF_CAL_T is an automatically generated axis for FMRC datasets in Ferret
          diagdefn = '%s[d=%s,gt(TF_TIMES[d=%s])=TF_CAL_T[d=%s]]' % \
                     (self._varname, self._dsetname, self._dsetname, self._dsetname)
          diagvar = pyferret.FerVar(defn=diagdefn, title=self._title)
          diagvar._requires.add(self._varname.upper())
          diagvar._requires.add("TF_TIMES")
          return diagvar
  
      def skillform(self):
          '''
          Returns an anonymous FerVar that is the transformation of this FerFMRCVar 
          to the "skill" form, where the T (time) axis is the date forecasted and 
          the F (forecast) axis is the lead time for the date forecasted (forecasted
          time minus time that the forecast was made).
          '''
          if (not self._varname) or (not self._dsetname):
              raise ValueError('Invalid FerFMRCVar object')
          # TF_TIMES is an automatically generated variable for FMRC datasets in Ferret
          # TF_CAL_T is an automatically generated axis for FMRC datasets in Ferret
          # TF_LAG_F is an automatically generated axis for FMRC datasets in Ferret
          skilldefn = '%s[d=%s,gt(TF_TIMES[d=%s])=TF_CAL_T[d=%s],gf(TF_TIMES[d=%s])=TF_LAG_F[d=%s]]' % \
                     (self._varname, self._dsetname, self._dsetname, self._dsetname, self._dsetname, self._dsetname)
          skillvar = pyferret.FerVar(defn=skilldefn, title=self._title)
          skillvar._requires.add(self._varname.upper())
          skillvar._requires.add("TF_TIMES")
          return skillvar
  
  
subject: Add FerFMRCVar