vam.whittaker

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

Installation

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 .

Usage

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!

Bugs, typos & feature requests

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!

CHANGES

• 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

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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.