point_cloud.py 文件源码

def flatten(self, ind):
        '''
        Transform the set of points so that the subset of markers given as argument is
        as close as flat (wrt z-axis) as possible.

        Parameters
        ----------
        ind : list of bools
            Lists of marker indices that should be all in the same subspace
        '''

        # Transform references to indices if needed
        ind = [self.key2ind(s) for s in ind]

        # center point cloud around the group of indices
        centroid = self.X[:,ind].mean(axis=1, keepdims=True)
        X_centered = self.X - centroid

        # The rotation is given by left matrix of SVD
        U,S,V = la.svd(X_centered[:,ind], full_matrices=False)

        self.X = np.dot(U.T, X_centered) + centroid