# indices = np.array([np.where((np.log(ls_irr_long/ls_irr[1] + 1.) > binedgeold) & (np.log(ls_irr_long/ls_irr[1] + 1.) <= binedge))[k] for k in range(2)]).transpose()
# # indices = np.where((np.log(ls_irr_long/ls_irr[1] + 1.) > binedgeold) & (np.log(ls_irr_long/ls_irr[1] + 1.) <= binedge))[k] for k in range(2)]).transpose()
if(isinstance(x,type(self)))and(np.all(self.para==x.para))and(self.discrete==x.discrete)and(np.all(self._meta_vars()==x._meta_vars())):## data types are ignored
if(isinstance(x,type(self)))and(np.all(self.para==x.para))and(self.discrete==x.discrete)and(np.all(self.vol==x.vol))and(np.all(self._meta_vars()==x._meta_vars())):## data types are ignored
returnTrue
returnFalse
def__ne__(self,x):## __ne__ : self <> x
if(isinstance(x,space)):
if(notisinstance(x,type(self)))or(np.any(self.para!=x.para))or(self.discrete!=x.discrete)or(np.any(self._meta_vars()!=x._meta_vars())):## data types are ignored
if(notisinstance(x,type(self)))or(np.any(self.para!=x.para))or(self.discrete!=x.discrete)or(np.any(self.vol!=x.vol))or(np.any(self._meta_vars()!=x._meta_vars())):## data types are ignored