def list_priors(self):

		prior_list = []
		prior_desc = []
		param_trans = []

		for i in range(self.param_no):
			param_trans.append(self.param_desc[i]['prior'].transform_name)
			x = self.param_desc[i]['prior']
			if isinstance(x, ifr.Normal):
				prior_list.append('Normal')
				prior_desc.append('mu0: ' + str(self.param_desc[i]['prior'].mu0) + ', sigma0: ' + str(self.param_desc[i]['prior'].sigma0))
			elif isinstance(x, ifr.InverseGamma):
				prior_list.append('Inverse Gamma')
				prior_desc.append('alpha: ' + str(self.param_desc[i]['prior'].alpha) + ', beta: ' + str(self.param_desc[i]['prior'].beta))
			elif isinstance(x, ifr.Uniform):
				prior_list.append('Uniform')
				prior_desc.append('n/a (non-informative)')
			else:
				raise Exception("Error - prior distribution not detected!")

		data = []

		for i in range(self.param_no):
			data.append({'param_index': len(data), 'param_name': self.param_desc[i]['name'], 'param_prior': prior_list[i], 'param_prior_params': prior_desc[i], 'param_trans': param_trans[i]})

		fmt = [
			('Index','param_index',6),		
			('Parameter','param_name',25),
			('Prior Type','param_prior',10),
			('Prior Parameters', 'param_prior_params', 25),
			('Transformation','param_trans',20)]
		
		print( op.TablePrinter(fmt, ul='=')(data) )
Return a range of values from sorted set ``key`` between
dataset/ETHPy150Open RJT1990/pyflux/pyflux/tsm.py/TSM.list_priors--crossover with--dataset/ETHPy150Open gmr/mredis/mredis/client.py/MRedis.zrange