|Apply automatic differentiation to computing the Euclidean gradient
|Computes the cost and the gradient at x via AD in one call
|Computes the Riemannian gradient and the cost at x via AD in one call for
|Convert the data type of x from dlarray into double
|Convert dlx which stores complex numbers in a structure into double
|Computes the Euclidean gradient of the cost function at x via AD.
|Computes the Euclidean Hessian of the cost function at x along xdot via AD.
|Find the indices of the anchors for the anchoredrotationsfactory
|Computes the Riemannian gradient of the cost function at x via AD for
|Compute the Euclidean inner product between x and y
|Determine if x contains a NaN value
|Preprocess automatic differentiation for a manopt problem structure
|Automatic differentation (AD) in Manopt requires the following:
|Convert the data type of x from numeric into dlarray
|Convert x into a particular data structure to store complex numbers