def set_params0(self, data=None, weights=None): if data is not None: mean, std = mean_std_fun(data, weights) else: mean, std = self._mean, self._std self.xi = mean return np.array([std, 1. / std, mean, 1. / std])
def update_p0(self, data, weights=None, i_std=7): self.params0 = self.kernel.set_params0(data, weights) mean, std = mathstats.mean_std_fun(data, weights) self.i_min = mean-std*i_std self.i_max = mean+std*i_std self._itick_setup()