Whittaker core functionality used in the modape package
State-of-the art whittaker smoother, implemented as fast C-extension through Cython and including a V-curve optimization of the smoothing parameter.
Includes the following variations of the whittaker smoother with 2nd order differences:
- ws2d: Whittaker with fixed smoothing parameter (
s
) - ws2dp: Whittaker with fixed smoothing parameter (
s
) and expectile smoothing using asymmetric weights - ws2doptv: Whittaker with V-curve optimization of the smoothing parameter (
s
) - ws2doptvp: Whittaker with V-curve optimization of the smoothing parameter (
s
) and expectile smoothing using asymmetric weights
Dependencies:
vam.whittaker depends on numpy. For building the c-extension, Cython is required.
Installation from PyPI:
$ pip install vam.whittaker
Installation from github:
$ git clone https://github.com/WFP-VAM/vam.whittaker
$ cd vam.whittaker
$ pip install .
import vam.whittaker
# or
from vam.whittaker import * # ws2d, ws2dp, ws2doptv, ws2optvp, lag1corr
For examples on the usage of the different functions, check out the modape jupyter notebook!
If you find a bug, see a typo, have some kind of troubles running the module or just simply want to have a feature added, please submit an issue!
- v1.0.0:
- initial release
- v1.0.1:
- minor version issue fix
- v2.0.0:
- new function wsdp & fix for ws2doptvp
- v2.0.1:
- minor bugfix in wsdp
- v2.0.2:
- distribute built extension on pypi
- v2.0.3:
- restructure and improve packaging
- v2.0.6:
- fix module import and wheel packaging
References:
P. H. C. Eilers, V. Pesendorfer and R. Bonifacio, "Automatic smoothing of remote sensing data," 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), Brugge, 2017, pp. 1-3. doi: 10.1109/Multi-Temp.2017.8076705 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8076705&isnumber=8035194
Core Whittaker function adapted from whit2
function from R package ptw:
Bloemberg, T. G. et al. (2010) "Improved Parametric Time Warping for Proteomics", Chemometrics and Intelligent Laboratory Systems, 104 (1), 65-74
Wehrens, R. et al. (2015) "Fast parametric warping of peak lists", Bioinformatics, in press.