(self, domain, nsamples)
:param domain: Optimization :class:`~.domain.Domain`.
        :param nsamples: number of random points to use
:param domain: Optimization :class:`~.domain.Domain`.
        :param nsamples: number of random points to use
: param domain : Optimization : class : ~ . domain . Domain . : param nsamples : number of random points to use
def __init__(self, domain, nsamples):
        """
        :param domain: Optimization :class:`~.domain.Domain`.
        :param nsamples: number of random points to use
        """
        super(MCOptimizer, self).__init__(domain, exclude_gradient=True)
        self._nsamples = nsamples
        # Clear the initial data points
        self.set_initial(np.empty((0, self.domain.size)))
def __init__ ( self , domain , nsamples ) : super ( MCOptimizer , self ) . __init__ ( domain , exclude_gradient = True ) self . _nsamples = nsamples # Clear the initial data points self . set_initial ( np . empty ( ( 0 , self . domain . size ) ) )