class_docstr: Fixed size vector of length 86 containing raw fractional elemental
  compositions in the compound. The 86 chosen elements are based on the
  original implementation at https://github.com/NU-CUCIS/ElemNet.
  
  Returns a vector containing fractional compositions of each element
  in the compound.
  
  References
  ----------
  .. [1] Jha, D., Ward, L., Paul, A. et al. Sci Rep 8, 17593 (2018).
      https://doi.org/10.1038/s41598-018-35934-y
  
  Examples
  --------
  >>> import deepchem as dc
  >>> comp = "Fe2O3"
  >>> featurizer = dc.feat.ElemNetFeaturizer()
  >>> features = featurizer.featurize([comp])
  >>> type(features[0])
  <class 'numpy.ndarray'>
  >>> features[0].shape
  (86,)
  >>> round(sum(features[0]))
  1
  
  Note
  ----
  This class requires Pymatgen to be installed.
docstr: Converts a dictionary containing element names and corresponding
  compositional fractions into a vector of fractions.
  
  Parameters
  ----------
  comp: collections.defaultdict object
      Dictionary mapping element names to fractional compositions.
  
  Returns
  -------
  fractions: np.ndarray
      Vector of fractional compositions of each element.
docstr_tok: ["Converts","a","dictionary","containing","element","names","and","corresponding","compositional","fractions","into","a","vector","of","fractions",".","Parameters","--","--","--","--","--","comp",":","collections.defaultdict","object","Dictionary","mapping","element","names","to","fractional","compositions",".","Returns","--","--","--","-","fractions",":","np.ndarray","Vector","of","fractional","compositions","of","each","element","."]
code: def get_vector(self, comp: DefaultDict) -> Optional[np.ndarray]:
      """
      Converts a dictionary containing element names and corresponding
      compositional fractions into a vector of fractions.
  
      Parameters
      ----------
      comp: collections.defaultdict object
          Dictionary mapping element names to fractional compositions.
  
      Returns
      -------
      fractions: np.ndarray
          Vector of fractional compositions of each element.
      """
      if all(e in elements_tl for e in comp):
          return np.array(
              [comp[e] if e in comp else 0 for e in elements_tl],
              np.float32,
          )
      else:
          return None
  
file_path: deepchem/deepchem/feat/material_featurizers/elemnet_featurizer.py
imports: import numpy
  from typing import DefaultDict, Optional
  from deepchem.utils.typing import PymatgenComposition
  from deepchem.feat import MaterialCompositionFeaturizer
label_desc: Use image node_id 1 for calling the ElemNetFeaturizer obj's underlying member method code with example usage: obj.get_vector(comp) and returns: np, None