class_docstr: The base class for all transformation objects.
  This class implements a single transformation (history)
  and some various niceties.
class_docstr_tok: ["The","base","class","for","all","transformation","objects",".","This","class","implements","a","single","transformation","(","history",")","and","some","various","niceties","."]
docstr: Get the parameters for this object.  Returns as a dict.
  
  Parameters
  ----------
  deep : bool
      Recurse on nested objects
  
  Returns
  -------
  params : dict
      A dictionary containing all parameters for this object
docstr_tok: ["Get","the","parameters","for","this","object",".","Returns","as","a","dict",".","Parameters","--","--","--","--","--","deep",":","bool","Recurse","on","nested","objects","Returns","--","--","--","-","params",":","dict","A","dictionary","containing","all","parameters","for","this","object"]
code: def get_params(self, deep=True):
      """Get the parameters for this object.  Returns as a dict.
  
      Parameters
      ----------
      deep : bool
          Recurse on nested objects
  
      Returns
      -------
      params : dict
          A dictionary containing all parameters for this object
      """
  
      out = dict(__class__=self.__class__, params=dict())
  
      for key in self._get_param_names():
          value = getattr(self, key, None)
  
          if deep and hasattr(value, "get_params"):
              deep_items = value.get_params().items()
              out["params"][key] = dict(__class__=value.__class__)
              out["params"][key].update(
                  (k, val) for k, val in deep_items
              )
          else:
              out["params"][key] = value
  
      return out
  
imports: import numpy
  import copy
  from collections import OrderedDict
  import itertools
  import six
  import inspect
label_desc: Use image node_id 2 for calling the BaseTransformer obj's underlying member method code with example usage: obj.get_params(deep) and returns: out