Deal with non-contiguous numpy arrays #8
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works only for eigen 3.4 and >=C++11, streaming works for all versions and avoids enforcing specific version of Eigen (which is not availabel in apt)
…numpy views fixes Missed solutions #4
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Use nanobind's built-in Eigen typecasters that relax the row-major requirements for going from python to C++ in the IK functions, which fixes #4.
The problem was that numpy can create views of a matrix that do not correspond to the actual order in which the data is stored (non-contiguous), whereas the C++ type casting code assumed the matrix to be stored in row-major order.
So we were actually computing IK for a different matrix (that was not even necessarily a valid SE3 pose)
A test case has been added to verify non-contiguous numpy arrays provide the same results and to avoid future regression.
This PR also simplifies the codebase as the type casting for numpy arrays to Eigen matrices is now handled by nanobind.
PR also updates the CI workflows, as they were broken