 autograd | Apply automatic differentiation to computing the Euclidean gradient |
| costgradcompute | Computes the cost and the gradient at x via AD in one call |
| costgradcomputefixedrankembedded | Computes the Riemannian gradient and the cost at x via AD in one call for |
| dl2mat | Convert the data type of x from dlarray into double |
| dl2mat_complex | Convert dlx which stores complex numbers in a structure into double |
| egradcompute | Computes the Euclidean gradient of the cost function at x via AD. |
| ehesscompute | Computes the Euclidean Hessian of the cost function at x along xdot via AD. |
| findA_anchors | Find the indices of the anchors for the anchoredrotationsfactory |
| gradcomputefixedrankembedded | Computes the Riemannian gradient of the cost function at x via AD for |
| innerprodgeneral | Compute the Euclidean inner product between x and y |
| isNaNgeneral | Determine if x contains a NaN value |
| manoptAD | Preprocess automatic differentiation for a manopt problem structure |
| manoptADhelp | Automatic differentation (AD) in Manopt requires the following: |
| mat2dl | Convert the data type of x from numeric into dlarray |
| mat2dl_complex | Convert x into a particular data structure to store complex numbers |
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