TFInterpy: A high-performance spatial interpolation Python package
Interpolation algorithms are essential tools for spatial analysis. The Kriging method satisfies the best linear unbiased estimation and is widely used in scenarios where high accuracy is required. But the program running time may be unacceptably long when using the Kriging method for large dataset....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711022001479 |
| _version_ | 1811187356513861632 |
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| author | Zhiwen Chen Baorong Zhong |
| author_facet | Zhiwen Chen Baorong Zhong |
| author_sort | Zhiwen Chen |
| collection | DOAJ |
| description | Interpolation algorithms are essential tools for spatial analysis. The Kriging method satisfies the best linear unbiased estimation and is widely used in scenarios where high accuracy is required. But the program running time may be unacceptably long when using the Kriging method for large dataset. To solve the problem, we developed TFInterpy based on the TensorFlow framework. This Python package provides an open-source, cross-platform, easy-to-use API for interpolation algorithms and achieves significant speedups when applied to large-scale tasks. |
| first_indexed | 2024-04-11T14:00:50Z |
| format | Article |
| id | doaj.art-cc6d74bac9dd4ec2a097620fe1e520a5 |
| institution | Directory Open Access Journal |
| issn | 2352-7110 |
| language | English |
| last_indexed | 2024-04-11T14:00:50Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj.art-cc6d74bac9dd4ec2a097620fe1e520a52022-12-22T04:20:08ZengElsevierSoftwareX2352-71102022-12-0120101229TFInterpy: A high-performance spatial interpolation Python packageZhiwen Chen0Baorong Zhong1School of Computer Science, Yangtze University, Jingzhou, 434000, ChinaCorresponding author.; School of Computer Science, Yangtze University, Jingzhou, 434000, ChinaInterpolation algorithms are essential tools for spatial analysis. The Kriging method satisfies the best linear unbiased estimation and is widely used in scenarios where high accuracy is required. But the program running time may be unacceptably long when using the Kriging method for large dataset. To solve the problem, we developed TFInterpy based on the TensorFlow framework. This Python package provides an open-source, cross-platform, easy-to-use API for interpolation algorithms and achieves significant speedups when applied to large-scale tasks.http://www.sciencedirect.com/science/article/pii/S2352711022001479PythonTensorFlowInterpolationKriging |
| spellingShingle | Zhiwen Chen Baorong Zhong TFInterpy: A high-performance spatial interpolation Python package SoftwareX Python TensorFlow Interpolation Kriging |
| title | TFInterpy: A high-performance spatial interpolation Python package |
| title_full | TFInterpy: A high-performance spatial interpolation Python package |
| title_fullStr | TFInterpy: A high-performance spatial interpolation Python package |
| title_full_unstemmed | TFInterpy: A high-performance spatial interpolation Python package |
| title_short | TFInterpy: A high-performance spatial interpolation Python package |
| title_sort | tfinterpy a high performance spatial interpolation python package |
| topic | Python TensorFlow Interpolation Kriging |
| url | http://www.sciencedirect.com/science/article/pii/S2352711022001479 |
| work_keys_str_mv | AT zhiwenchen tfinterpyahighperformancespatialinterpolationpythonpackage AT baorongzhong tfinterpyahighperformancespatialinterpolationpythonpackage |