Update the SPDX banner to `LICENSE.md` and cross-reference `extract_strain`
from the small-strain docstring so readers know where gradients are consumed.
Bring the inline examples in `compute_jacobian` / `physical_derivatives`
docstrings in line with parametrized reference topologies and `Lagrange{1}`,
and drop a broken cross-reference to external tensor types.
- Point the SPDX banner at `LICENSE.md` on the default branch.
- Use `Triangle{3}` / `Tetrahedron{4}` instances with `Lagrange{1}` in the
derivative snippets.
- Replace the `[Tensor](@ref)` bullet with an explicit note that tensors come
from the **Tensors.jl** dependency.
- Illustrate quadrature iteration from a concrete `Tri3()` topology handle.
- Implement compute_strain() for small strain tensor calculation
- Zero allocation with NTuple inputs and Tensors.jl
- Type stable (@inferred passes)
- Complete test suite with 4 test cases (uniaxial, shear, rigid body, performance)
- Performance validated: 0 allocations, ~110ns median
- Add to test suite in runtests.jl
- Export from JuliaFEM module
Resolves user story #0001
New file src/geometry/jacobian.jl implementing geometric transformations:
- compute_jacobian(X, dN_dξ) computes J = ∂x/∂ξ using tensor products
- physical_derivatives(J, dN_dξ) transforms derivatives to physical space
- Full Tensors.jl integration with Vec and Tensor types
- Zero-allocation tuple-based API for performance
- AbstractVector overloads for compatibility
- Comprehensive docstrings with 2D/3D examples
- 169 lines with mathematical definitions and usage patterns
Jukka Aho