Internal functions
ManifoldDiff.CurrentDiffBackend — TypeCurrentDiffBackend(backend)A mutable struct for storing the current differentiation backend in a global constant _current_default_differential_backend.
See also
default_differential_backend, set_default_differential_backend!
ManifoldDiff._current_default_differential_backend — Constant_current_default_differential_backendThe instance of CurrentDiffBackend that stores the globally default differentiation backend.
ManifoldDiff._hessian — Function_hessian(f, p[, backend])Compute the Hessian of a callable f at point p computed using the given backend. If the backend is not explicitly specified, it is obtained using the function default_differential_backend.
This function calculates plain Euclidean Hessian.
ManifoldDiff._jacobian — Function_jacobian(f, p[, backend])Compute the Jacobian of a callable f at point p computed using the given backend. If the backend is not explicitly specified, it is obtained using the function default_differential_backend.
This function calculates plain Euclidean Jacobians, for Riemannian Jacobian calculation see for example gradient.
ManifoldDiff._gradient — Function_gradient(f, p[, backend])Compute the gradient of a callable f at point p computed using the given backend. If the backend is not explicitly specified, it is obtained using the function default_differential_backend.
This function calculates plain Euclidean gradients, for Riemannian gradient calculation see for example gradient.
ManifoldDiff._derivative — Function_derivative(f, t[, backend])Compute the derivative of a callable f at time t computed using the given backend. If the backend is not explicitly specified, it is obtained using the function default_differential_backend.
This function calculates plain Euclidean derivatives, for Riemannian differentiation see for example differential.