CRISPy
Computational Ridge Identification with SCMS for Python
This code is a python implementation of the generalized Subspace Constrained Mean Shift (SCMS) algorithm, translated and modified from the R-code developed by Yen-Chi Chen (University of Washington).
Please cite the following papers when using the code:
- Ozertem, Umut, and Deniz Erdogmus. "Locally Defined Principal Curves and Surfaces." The Journal of Machine Learning Research 12 (2011): 1249-1286.
- Chen, Yen-Chi, Christopher Genovese, Christopher R. Genovese, and Larry Wasserman. "Generalized Mode and Ridge Estimation." (2014): arXiv :1406.1803
- Chen, Yen-Chi, Shirley Ho, Peter E. Freeman, Christopher R. Genovese, and Larry Wasserman. "Cosmic Web Reconstruction through Density Ridges: Method and Algorithm." MNRAS 454 1140 (2015) arXiv: 1501.05303
- Chen, Michael Chun-Yuan, et al. "Velocity-Coherent Filaments in NGC 1333: Evidence for Accretion Flow?" ApJ (2019, submitted)
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Release files for astro-crispy 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| astro-crispy-0.1.0.tar.gz | 4.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| astro_crispy-0.1.0-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 21.7 kB
Release files / astro-crispy-0.1.0.tar.gz
| Download URL | astro-crispy-0.1.0.tar.gz |
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| Size | 4.4 kB |
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Release files / astro_crispy-0.1.0-py2-none-any.whl
| Download URL | astro_crispy-0.1.0-py2-none-any.whl |
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| Size | 17.3 kB |
| Tags | Python 2 |
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