dora/active_sampling/gp_sampler.py
def update_y_mean(self):
        """
        Update the mean of the target outputs.

        .. note :: [Properties Modified]
                    y_mean,
                    n_tasks

        .. note :: At anytime, 'y_mean' should be the mean of all the output
                   targets including the virtual ones, since that is what
                   we are training upon
        """
        if not self.y:
            return
        self.y_mean = self.y().mean(axis=0) if len(self.y) else None

        # Make sure the number of stacks recorded is consistent
        if self.n_tasks is None:
            self.n_tasks = self.y_mean.shape[0]
        else:
            assert self.n_tasks == self.y_mean.shape[0]

        Update the mean of the target outputs.

        .. note :: [Properties Modified]
                    y_mean,
                    n_tasks

        .. note :: At anytime, 'y_mean' should be the mean of all the output
                   targets including the virtual ones, since that is what
                   we are training upon
        
Update the mean of the target outputs.

note :: At anytime, 'y_mean' should be the mean of all the output
targets including the virtual ones, since that is what
we are training upon
Update the mean of the target outputs . note :: At anytime ' y_mean ' should be the mean of all the output targets including the virtual ones since that is what we are training upon
def update_y_mean(self):
        if not self.y:
            return
        self.y_mean = self.y().mean(axis=0) if len(self.y) else None
        if self.n_tasks is None:
            self.n_tasks = self.y_mean.shape[0]
        else:
            assert self.n_tasks == self.y_mean.shape[0]
def update_y_mean ( self ) : if not self . y : return self . y_mean = self . y ( ) . mean ( axis = 0 ) if len ( self . y ) else None if self . n_tasks is None : self . n_tasks = self . y_mean . shape [ 0 ] else : assert self . n_tasks == self . y_mean . shape [ 0 ]
Update the mean of the target outputs.
Update the mean of the target outputs .
"""
        Update the mean of the target outputs.

        .. note :: [Properties Modified]
                    y_mean,
                    n_tasks

        .. note :: At anytime, 'y_mean' should be the mean of all the output
                   targets including the virtual ones, since that is what
                   we are training upon
        """ # Make sure the number of stacks recorded is consistent
self