Native dense LAP and windowed cleanup kernels for point-to-grid assignment.
Project description
megalap
megalap is a Python package with a native C++ core and nanobind bindings for point-to-grid assignment.
The public API has three functions:
linear_sum_assignment(cost_matrix)window_cleanup(points, initial_assignment, rows, cols, budget_seconds, ...)snap_to_grid(points, width=None, height=None, cleanup_seconds=30.0, ...)
Install
python -m pip install megalap
To run the matplotlib example from the source tree:
python -m pip install -e '.[examples]'
python examples/basic_usage.py
API
linear_sum_assignment(cost_matrix)
Solve a dense square linear assignment problem with the native C++ Jonker-Volgenant implementation.
Returns:
row_ind:int64NumPy array of shape(n,)col_ind:int64NumPy array of shape(n,)total_cost: Pythonfloat
window_cleanup(points, initial_assignment, rows, cols, budget_seconds, ...)
Run the overlapping-window cleanup kernel using native C++ threads.
Key options:
window_size=6num_threads=Noneto usestd::thread::hardware_concurrency()num_threads=1to force serial executionfixed_suffix_countto keep a suffix of target cells fixed
Returns a dict with:
assignmentpasses_completedelapsed_sfinal_cost
snap_to_grid(points, width=None, height=None, cleanup_seconds=30.0, ...)
High-level wrapper for snapping a 2D point cloud onto a destination grid.
Behavior:
- chooses a destination grid automatically when
widthandheightare omitted - prefers exact rectangular sizes with aspect ratio in
[1:1, 2:1] - falls back to a near-square enclosing grid in that same band when exact factors do not exist
- pads with edge ghost points when the chosen grid has more cells than real points
- runs the native LAP solver and
30sof cleanup by default - set
cleanup_seconds=0.0to disable cleanup
Returns:
grid_points:(n, 2)float64 NumPy array of assigned destination points in original point orderassignment:(n,)int64 NumPy array of destination-grid indices in original point order(width, height): destination-grid size tuple
More
- Source repository: https://github.com/kylemcdonald/megalap
- Issue tracker: https://github.com/kylemcdonald/megalap/issues
- Example scripts: https://github.com/kylemcdonald/megalap/tree/main/examples
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