1 ###############################################################################
  2 class BaseEstimator(object):
  3     """Base class for all estimators in scikit-learn
  4 
  5     Notes
  6     -----
  7     All estimators should specify all the parameters that can be set
  8     at the class level in their __init__ as explicit keyword
  9     arguments (no *args, **kwargs).
 10     """
 11 
 12     @classmethod
 13     def _get_param_names(cls):
 14         """Get parameter names for the estimator"""
 15         try:
 16             # fetch the constructor or the original constructor before
 17             # deprecation wrapping if any
 18             init = getattr(cls.__init__, ‘deprecated_original‘, cls.__init__)
 19 
 20             # introspect the constructor arguments to find the model parameters
 21             # to represent
 22             args, varargs, kw, default = inspect.getargspec(init)
 23             if not varargs is None:
 24                 raise RuntimeError("scikit-learn estimators should always "
 25                                    "specify their parameters in the signature"
 26                                    " of their __init__ (no varargs)."
 27                                    " %s doesn‘t follow this convention."
 28                                    % (cls, ))
 29             # Remove ‘self‘
 30             # XXX: This is going to fail if the init is a staticmethod, but
 31             # who would do this?
 32             args.pop(0)
 33         except TypeError:
 34             # No explicit __init__
 35             args = []
 36         args.sort()
 37         return args
 38 
 39     def get_params(self, deep=True):
 40         """Get parameters for this estimator.
 41 
 42         Parameters
 43         ----------
 44         deep: boolean, optional
 45             If True, will return the parameters for this estimator and
 46             contained subobjects that are estimators.
 47 
 48         Returns
 49         -------
 50         params : mapping of string to any
 51             Parameter names mapped to their values.
 52         """
 53         out = dict()
 54         for key in self._get_param_names():
 55             # We need deprecation warnings to always be on in order to
 56             # catch deprecated param values.
 57             # This is set in utils/__init__.py but it gets overwritten
 58             # when running under python3 somehow.
 59             warnings.simplefilter("always", DeprecationWarning)
 60             try:
 61                 with warnings.catch_warnings(record=True) as w:
 62                     value = getattr(self, key, None)
 63                 if len(w) and w[0].category == DeprecationWarning:
 64                 # if the parameter is deprecated, don‘t show it
 65                     continue
 66             finally:
 67                 warnings.filters.pop(0)
 68 
 69             # XXX: should we rather test if instance of estimator?
 70             if deep and hasattr(value, ‘get_params‘):
 71                 deep_items = value.get_params().items()
 72                 out.update((key + ‘__‘ + k, val) for k, val in deep_items)
 73             out[key] = value
 74         return out
 75 
 76     def set_params(self, **params):
 77         """Set the parameters of this estimator.
 78 
 79         The method works on simple estimators as well as on nested objects
 80         (such as pipelines). The former have parameters of the form
 81         ``<component>__<parameter>`` so that it‘s possible to update each
 82         component of a nested object.
 83 
 84         Returns
 85         -------
 86         self
 87         """
 88         if not params:
 89             # Simple optimisation to gain speed (inspect is slow)
 90             return self
 91         valid_params = self.get_params(deep=True)
 92         for key, value in six.iteritems(params):
 93             split = key.split(‘__‘, 1)
 94             if len(split) > 1:
 95                 # nested objects case
 96                 name, sub_name = split
 97                 if not name in valid_params:
 98                     raise ValueError(‘Invalid parameter %s for estimator %s‘ %
 99                                      (name, self))
100                 sub_object = valid_params[name]
101                 sub_object.set_params(**{sub_name: value})
102             else:
103                 # simple objects case
104                 if not key in valid_params:
105                     raise ValueError(‘Invalid parameter %s ‘ ‘for estimator %s‘
106                                      % (key, self.__class__.__name__))
107                 setattr(self, key, value)
108         return self
109 
110     def __repr__(self):
111         class_name = self.__class__.__name__
112         return ‘%s(%s)‘ % (class_name, _pprint(self.get_params(deep=False),
113                                                offset=len(class_name),),)
114 
115     def __str__(self):
116         class_name = self.__class__.__name__
117         return ‘%s(%s)‘ % (class_name,
118                            _pprint(self.get_params(deep=True),
119                                    offset=len(class_name), printer=str,),)