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icoshift

public
17 stars
10 forks
3 issues

Commits

List of commits on branch master.
Unverified
b8a82811c83020a605f170b51dd672136f9d2313

Fixes co-shift pre-processing with intervals

committed 10 years ago
Unverified
5a927ec9021207bbf57ad6c90c482ad763a7891c

More bugfixes; most failures occurring at the same point in the code

committed 10 years ago
Unverified
7b6ab0c64771ea909483e2fc74f603e587976f0c

...

committed 10 years ago
Unverified
8c00816007e11ee21195955f49a435c703842102

Segmental alignment fixes; for all average, median, max and average2

committed 10 years ago
Unverified
bd9e59ae44adfedb97461d5d4dd8e36e1b6f4cf4

Fix 'max' target

committed 10 years ago
Unverified
1670813952c696fd718daa1254c77d58bdb5b293

Misc fixes

committed 10 years ago

README

The README file for this repository.

icoshift

A versatile tool for the rapid alignment of 1D NMR spectra

This package is a Python implementation of the icoshift algorithm as described by Francesco Savorani and Giorgio Tomasi. It uses correlation shifting of spectral intervals and employs an FFT engine that aligns all spectra simultaneously.

The Matlab algorithm is demonstrated to be faster than similar methods found in the literature making full-resolution alignment of large datasets feasible and thus avoiding down-sampling steps such as binning. The algorithm uses missing values as a filling alternative in order to avoid spectral artifacts at the segment boundaries.

It has been converted to Python using SMOP followed by hand re-coding using test datasets to check output at various steps. Better (and more complicated) test cases to come.

The interface remains identical to the Matlab version at present.

Here Be Dragons

Conversion from one programming language to another is not straightforward. Particularly problematic from MATLAB to Python is the change from zero-based to one-based indexing. The implementation has been fixed to work and produce comparable output for all inputs, however issues with some datasets or settings may remain. Full tests to confirm equivalence to the MATLAB algorithm to follow.

But it works.

Thanks

Thanks to Francesco Savorani and Giorgio Tomasi for the original neat and well documented algorithm.