treeIDW 1.0.2

A package for KD-tree optimized inverse distance weighting interpolation.

treeIDW

treeIDW is a Python library for performing Inverse Distance Weighting (IDW) interpolation using an efficient KD-tree-based selection strategy.
It is designed to be easy to use for newcomers while offering fine-grained control and performance-oriented options for advanced users in numerical methods and spatial data analysis.

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Key Features

• Efficient IDW interpolation using KD-tree nearest-neighbor selection
• Automatic exclusion of boundary nodes with negligible contribution
• Optimized numerical kernels powered by numba
• Scalable to large datasets (millions of interpolation points)
• Simple API with expert-level tunable parameters

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Installation

treeIDW is available on PyPI.

pip install treeIDW

Development installation (from source)

git clone https://github.com/Dorian210/treeIDW
cd treeIDW
pip install -e .

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Dependencies

The core dependencies are:

• numpy
• scipy
• numba

These are automatically installed when using pip.

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Package Structure

• treeIDW.treeIDW
  Core IDW interpolation engine.
  Uses a KD-tree to select only boundary nodes with significant influence, improving both accuracy and performance.

• treeIDW.helper_functions
  Low-level, performance-critical routines for IDW weight computation.
  Implemented with numba, including vectorized and parallelized variants.

• treeIDW.weight_function
  Definition of the IDW weight function.
  The default implementation uses inverse squared distance, but custom weight laws can be implemented if needed.

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Examples

Example scripts are provided in the examples/ directory:

• Graphical demonstration
  Interpolation of a rotating vector field inside a square domain.

• Large-scale computation
  Propagation of a scalar field from 1,000 boundary nodes to 1,000,000 internal points, highlighting scalability.

• Logo generation
  The generation process of the treeIDW logo itself, where the letters “IDW” are encoded as a vector field and interpolated on a 2D grid.

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Documentation

• Online documentation: https://dorian210.github.io/treeIDW/
• API reference is also available in the docs/ directory of the repository.

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Contributions

This project is currently not open to active development contributions.
However, bug reports and suggestions are welcome via the issue tracker.

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License

This project is distributed under the CeCILL License.
See LICENSE.txt for details.