def validate_X(self, X):
obj = copy.deepcopy(X)
if 'ldf_' not in obj:
obj = Development().fit_transform(obj)
if len(obj.ddims) - len(obj.ldf_.ddims) == 1:
obj = TailConstant().fit_transform(obj)
return obj
def validate_X(self, X):
obj = X.copy()
if "ldf_" not in obj:
obj = Development().fit_transform(obj)
if len(obj.ddims) - len(obj.ldf_.ddims) == 1:
obj = TailConstant().fit_transform(obj)
return obj
def validate_X(self, X):
obj = copy.copy(X)
if 'ldf_' not in obj:
obj = Development().fit_transform(obj)
if len(obj.ddims) - len(obj.ldf_.ddims) == 1:
obj = TailConstant().fit_transform(obj)
for item in ['cdf_', 'ldf_', 'average_']:
setattr(self, item, getattr(obj, item, None))
return obj
def validate_X(self, X):
obj = copy.deepcopy(X)
if obj.__dict__.get('ldf_', None) is None:
obj = Development().fit_transform(obj)
if len(obj.ddims) - len(obj.ldf_.ddims) == 1:
obj = TailConstant().fit_transform(obj)
self.cdf_ = obj.__dict__.get('cdf_', None)
self.ldf_ = obj.__dict__.get('ldf_', None)
self.average_ = obj.__dict__.get('average_', None)
return obj