Internal functions

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.

Note

Not specifying the backend explicitly will usually result in a type instability and decreased performance.

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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.

Note

Not specifying the backend explicitly will usually result in a type instability and decreased performance.

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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.

Note

Not specifying the backend explicitly will usually result in a type instability and decreased performance.

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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.

Note

Not specifying the backend explicitly will usually result in a type instability and decreased performance.

source