Implement interpolation on parallelepiped grids (issue #242) #281
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- Add is_orthogonal() method to detect non-orthogonal grids - Add _interpolate_parallelepiped() method using scipy.interpn with coordinate transformation - Add _closest_point_general() method for non-orthogonal grids - Modify interpolate() to automatically select interpolation method - Update closest_point() to work with non-orthogonal axes - Add comprehensive tests for non-orthogonal interpolation - Add example demonstrating parallelepiped interpolation functionality - Maintain full backward compatibility with existing orthogonal grids Uses inverse Jacobian matrix (axes^(-1)) for coordinate transformation: grid_coords = (cartesian_coords - origin) × axes^(-1) All 33 cubic grid tests pass, including 2 new tests for non-orthogonal functionality.
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Issue #242 Fix
Problem:
The grid library only supported interpolation on orthogonal grids (axes aligned with Cartesian coordinates). It couldn't handle parallelepiped grids (non-orthogonal, skewed axes).
Solution:
Added support for non-orthogonal grids using coordinate transformation with the inverse Jacobian matrix.
Key Changes Made: