add constant to mle loss

class MLELoss(Loss):

	def __init__(self, *args, **kwargs):

		super().__init__(*args, **kwargs)

		# usefull constant to make optimal loss closer to 0

		# it can affect relative convergence criteria

		pos_data = self.data[self.data>0]

		self.constant = -(pos_data-pos_data*np.log(pos_data)).sum()

	def loss(self, params):

		fit = self.fit(params)

		return (fit-self.data*np.log(fit)).sum()

		return (fit-self.data*np.log(fit)).sum() + self.constant

	@property

	def dloss_dfit(self):