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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:

  1. linear_sum_assignment(cost_matrix)
  2. window_cleanup(points, initial_assignment, rows, cols, budget_seconds, ...)
  3. 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: int64 NumPy array of shape (n,)
  • col_ind: int64 NumPy array of shape (n,)
  • total_cost: Python float

window_cleanup(points, initial_assignment, rows, cols, budget_seconds, ...)

Run the overlapping-window cleanup kernel using native C++ threads.

Key options:

  • window_size=6
  • num_threads=None to use std::thread::hardware_concurrency()
  • num_threads=1 to force serial execution
  • fixed_suffix_count to keep a suffix of target cells fixed

Returns a dict with:

  • assignment
  • passes_completed
  • elapsed_s
  • final_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 width and height are 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 30s of cleanup by default
  • set cleanup_seconds=0.0 to disable cleanup

Returns:

  • grid_points: (n, 2) float64 NumPy array of assigned destination points in original point order
  • assignment: (n,) int64 NumPy array of destination-grid indices in original point order
  • (width, height): destination-grid size tuple

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