original_docstring: 
      Converts the realization DataSet to a DataArray
      @ In, rlzDataset, xr.dataset, the data set containing the batched realizations
      @ In, vars, list, the list of decision variables
      @ Out, dataset, xr.dataarray, a data array containing the realization with
                     dims = ['chromosome','Gene']
                     chromosomes are named 0,1,2...
                     Genes are named after variables to be sampled
    
docstring: Converts the realization DataSet to a DataArray
  @ In, rlzDataset, xr.dataset, the data set containing the batched realizations
  @ In, vars, list, the list of decision variables
  @ Out, dataset, xr.dataarray, a data array containing the realization with
  dims = ['chromosome','Gene']
  chromosomes are named 0,1,2
  Genes are named after variables to be sampled
docstring_tokens: Converts the realization DataSet to a DataArray @ In rlzDataset xr . dataset the data set containing the batched realizations @ In vars list the list of decision variables @ Out dataset xr . dataarray a data array containing the realization with dims = [ ' chromosome ' ' Gene ' ] chromosomes are named 0 1 2 Genes are named after variables to be sampled
code: def datasetToDataArray(rlzDataset,vars):
    """
      Converts the realization DataSet to a DataArray
      @ In, rlzDataset, xr.dataset, the data set containing the batched realizations
      @ In, vars, list, the list of decision variables
      @ Out, dataset, xr.dataarray, a data array containing the realization with
                     dims = ['chromosome','Gene']
                     chromosomes are named 0,1,2...
                     Genes are named after variables to be sampled
    """
    dataset = xr.DataArray(np.atleast_2d(rlzDataset[vars].to_array().transpose()),
                              dims=['chromosome','Gene'],
                              coords={'chromosome': np.arange(rlzDataset[vars[0]].data.size),
                                      'Gene':vars})
    return dataset
code_tokens: def datasetToDataArray ( rlzDataset , vars ) : dataset = xr . DataArray ( np . atleast_2d ( rlzDataset [ vars ] . to_array ( ) . transpose ( ) ) , dims = [ 'chromosome' , 'Gene' ] , coords = { 'chromosome' : np . arange ( rlzDataset [ vars [ 0 ] ] . data . size ) , 'Gene' : vars } ) return dataset
short_docstring: Converts the realization DataSet to a DataArray
  @ In, rlzDataset, xr.dataset, the data set containing the batched realizations
  @ In, vars, list, the list of decision variables
  @ Out, dataset, xr.dataarray, a data array containing the realization with
  dims = ['chromosome','Gene']
  chromosomes are named 0,1,2...
short_docstring_tokens: Converts the realization DataSet to a DataArray @ In rlzDataset xr . dataset the data set containing the batched realizations @ In vars list the list of decision variables @ Out dataset xr . dataarray a data array containing the realization with dims = [ ' chromosome ' ' Gene ' ] chromosomes are named 0 1 2 ...
comment: """
      Converts the realization DataSet to a DataArray
      @ In, rlzDataset, xr.dataset, the data set containing the batched realizations
      @ In, vars, list, the list of decision variables
      @ Out, dataset, xr.dataarray, a data array containing the realization with
                     dims = ['chromosome','Gene']
                     chromosomes are named 0,1,2...
                     Genes are named after variables to be sampled
    """