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()
