def _update_y_transform(self):
<EOL>sorted_data_indices = self._yi_sorted<EOL>sorted_xtransforms = []<EOL>for xt in self.x_transforms:<EOL><INDENT>sorted_xt = sort_vector(xt, sorted_data_indices)<EOL>sorted_xtransforms.append(sorted_xt)<EOL><DEDENT>sum_of_x_transformations_choppy = numpy.sum(sorted_xtransforms, axis=<NUM_LIT:0>)<EOL>y_sorted = sort_vector(self.y, sorted_data_indices)<EOL>smooth = perform_smooth(y_sorted, sum_of_x_transformations_choppy,<EOL>smoother_cls=self._smoother_cls)<EOL>sum_of_x_transformations_smooth = smooth.smooth_result<EOL>sum_of_x_transformations_smooth -= numpy.mean(sum_of_x_transformations_smooth)<EOL>sum_of_x_transformations_smooth /= numpy.std(sum_of_x_transformations_smooth)<EOL>self.y_transform = unsort_vector(sum_of_x_transformations_smooth, sorted_data_indices)<EOL>
Update the y-transform (theta).

y-transform theta is forced to have mean = 0 and stddev = 1.

This is the second conditional expectation