公式:
从黎曼空间投影到切空间,其中P为黎曼均值,也是切空间的参考中心点,Pi是要投影到切空间的点。
从切空间投影回来,其中Si为切空间中的向量。
Matlab
function Tcov = CovToTan(cov,Mcov)
Cm12 = Mcov^(-1/2);
X_new = logm(Cm12 * cov * Cm12);
C12 = Mcov^(1/2);
Tcov = Mupper(C12 * X_new * C12);
end
function Cov = TanToCov(vec,Mcov)
X = Munupper(vec);
Cm12 = Mcov^(-1/2);
X = Cm12 * X * Cm12;
C12 = Mcov^(1/2);
Cov = C12 * expm(X) * C12;
end
function T = Mupper(X)
% Upper triangular part vectorization with diagonal preservation.
% This function keeps the upper triangular part of the matrix and
% vectorizes it while multiplying non-diagonal elements by sqrt(2).
% Get the size of X
[M, N] = size(X);
% Check if matrices are square
if M ~= N
error('Matrices must be square');
end
% Initialize T with zeros
T = zeros(M, M, 'like', X);
% Calculate the multiplier for non-diagonal elements
multiplier = sqrt(2);
% Fill T with the upper triangular part, preserving the diagonal
for i = 1:M
for j = i:M
if i == j
T(i, j) = X(i, j); % Diagonal element remains the same
else
T(i, j) = X(i, j) * multiplier; % Non-diagonal elements multiplied by sqrt(2)
end
end
end
% Flatten the upper triangular part of T to a vector
T = T(triu(true(size(T))) == 1);
T = T';
end
function X = Munupper(T, n)
% Reverse the operation to reconstruct the matrix from its upper triangular part.
% Calculate the size of the square matrix based on the length of the input vector T
n = round((sqrt(1 + 8 * length(T)) - 1) / 2);
% Check if T is a valid upper triangular vector
m = n * (n + 1) / 2;
if numel(T) ~= m
error('Invalid input. Input vector size does not match the expected size for upper triangular vectors.');
end
% Initialize the symmetric matrix X with zeros
X = zeros(n, n, 'like', T);
% Calculate the indices for the upper triangular part
[I, J] = find(triu(ones(n)));
% Reverse the vectorization and apply the appropriate scaling to non-diagonal elements
for k = 1:numel(I)
i = I(k);
j = J(k);
if i == j
X(i, j) = T(k); % Diagonal elements remain the same
else
X(i, j) = T(k) / sqrt(2); % Reverse scaling for non-diagonal elements
X(j, i) = X(i, j); % Symmetric matrix
end
end
end