TFInterpy is a Python package for spatial interpolation. A high-performance version of several interpolation algorithms is implemented based on TensorFlow. Including parallelizable IDW and Kriging algorithms. So far, tfinterpy is the **fastest open source Kriging** algorithm, which can reduce the operation time of large-scale interpolation tasks by an order of magnitude.
Project description
TFInterpy
TFInterpy is a Python package for spatial interpolation. A high-performance version of several interpolation algorithms is implemented based on TensorFlow. Including parallelizable IDW and Kriging algorithms. So far, tfinterpy is the fastest open source Kriging algorithm, which can reduce the operation time of large-scale interpolation tasks by an order of magnitude
Link to our paper
TFInterpy: A high-performance spatial interpolation Python package
(https://doi.org/10.1016/j.softx.2022.101229)
Performance comparison (unit: second)
| Grid size | GeostatsPy-OK | PyKrige-OK | TFInterpy-OK | TFInterpy-TFOK(GPU) | TFInterpy-TFOK(CPU) |
|---|---|---|---|---|---|
| 1x104 | 23.977 | 1.258 | 0.828 | 2.070 | 0.979 |
| 1x105 | 230.299 | 12.264 | 8.140 | 6.239 | 2.067 |
| 1x106 | 2011.351 | 121.711 | 82.397 | 45.737 | 11.683 |
| 1x107 | 2784.843 | 1250.980 | 849.974 | 452.567 | 112.331 |
Screenshots
Snapshot of GUI tool.
Requirements
Minimum usage requirements: Python 3+, Numpy, SciPy
TensorFlow based algorithm: TensorFlow 2
GSLIB file support: Pandas
3D visualization: VTK
GUI Tool: PyQT5
Usage
All examples are stored on the github homepage
Install tfinterpy
pip install tfinterpy
Then install dependencies
Full dependencies : (To avoid package version issues, the specific version numbers tested in Python3.9 are listed here)
pip install matplotlib==3.9.4
pip install numpy==2.0.2
pip install pandas==2.2.3
pip install PyQt5==5.15.11
pip install scipy==1.13.1
pip install tensorflow==2.18.0
pip install vtk==9.4.1
Notice! You may do not need to install all dependencies
- If you only need to use the most basic interpolation algorithm, install the following package. (see "examples/" for usage)
pip install numpy==2.0.2 pip install scipy==1.13.1 - If you need to use TensorFlow-based interpolation algorithms, you need to install tensorflow. (see "examples/tf" for usage)
or (Use GPU for computing)pip install tensorflow==2.18.0pip install tensorflow-gpu==2.18.0 - If you need to use the built-in GUI tools (see "examples/gui" for usage) provided, please install full dependencies as above list.
netcdf4 also needs to be installed to run the examples in the examples folder:
pip install netCDF4==1.7.2
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