(self, *args, resampling_rate = 0.5, min_samples_advance = 1, **kwargs)
Iteration class to resample new configurations along side keeping the good ones
			in SuccessiveHalving.
			
			Parameters:
			-----------
				resampling_rate: float
					fraction of configurations that are resampled at each stage
				min_samples_advance:int
					number of samples that are guaranteed to proceed to the next
					stage regardless of the fraction.
Iteration class to resample new configurations along side keeping the good ones
			in SuccessiveHalving.
			
			Parameters:
			-----------
				resampling_rate: float
					fraction of configurations that are resampled at each stage
				min_samples_advance:int
					number of samples that are guaranteed to proceed to the next
					stage regardless of the fraction.
Iteration class to resample new configurations along side keeping the good ones in SuccessiveHalving . Parameters : ----------- resampling_rate : float fraction of configurations that are resampled at each stage min_samples_advance : int number of samples that are guaranteed to proceed to the next stage regardless of the fraction .
def __init__(self, *args, resampling_rate = 0.5, min_samples_advance = 1, **kwargs):
		"""
			Iteration class to resample new configurations along side keeping the good ones
			in SuccessiveHalving.
			
			Parameters:
			-----------
				resampling_rate: float
					fraction of configurations that are resampled at each stage
				min_samples_advance:int
					number of samples that are guaranteed to proceed to the next
					stage regardless of the fraction.
		
		"""
		self.resampling_rate = resampling_rate
		self.min_samples_advance = min_samples_advance
def __init__ ( self , * args , resampling_rate = 0.5 , min_samples_advance = 1 , * * kwargs ) : self . resampling_rate = resampling_rate self . min_samples_advance = min_samples_advance