class_docstr: Modality that contains features in general
  
  Parameters
  ----------
  features: numpy.ndarray or scipy.sparse.csr_matrix, default = None
      Numpy 2d-array that the row indices are aligned with user/item in `ids`.
  
  ids: List, default = None
      List of user/item ids that the indices are aligned with `corpus`.
      If None, the indices of provided `features` will be used as `ids`.
  
  normalized: bool, default = False
      Whether the features will be normalized using min-max normalization.
class_docstr_tok: ["Modality","that","contains","features","in","general","Parameters","--","--","--","--","--","features",":","numpy.ndarray","or","scipy.sparse.csr_matrix",",","default","=","None","Numpy","2d-array","that","the","row","indices","are","aligned","with","user\/item","in","`","ids","`",".","ids",":","List",",","default","=","None","List","of","user\/item","ids","that","the","indices","are","aligned","with","`","corpus","`",".","If","None",",","the","indices","of","provided","`","features","`","will","be","used","as","`","ids","`",".","normalized",":","bool",",","default","=","False","Whether","the","features","will","be","normalized","using","min-max","normalization","."]
docstr: Return the whole feature matrix
          
docstr_tok: ["Return","the","whole","feature","matrix"]
code: def features(self):
      """Return the whole feature matrix"""
      return self.__features
  
file_path: cornac/cornac/data/modality.py
imports: import numpy
label_desc: Use image node_id 2 for calling the FeatureModality obj's underlying member method code with example usage: obj.features() and returns: self