Metadata-Version: 2.1
Name: pyicoshift
Version: 0.0.3
Summary: Python 3 Version of icoshift
Author-email: Sebastian Krossa <sebastian.krossa@ntnu.no>
License: MIT License        
        Copyright (c) 2019 Sebastian Krossa        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.        
        This work is a derivative of the matlab icoshift implementation of Francesco Savorani,
        published under following license:        
        # TODO newer icoshift version is without license - maybe contact the guy prior publication
        http://www.models.life.ku.dk/icoshift        
        Copyright (c) 2014, Francesco Savorani
        All rights reserved.        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:        
        * Redistributions of source code must retain the above copyright notice, this
          list of conditions and the following disclaimer.        
        * Redistributions in binary form must reproduce the above copyright notice,
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        * Neither the name of University of Copenhagen - Dept. of Food Science nor the names of its
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        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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Project-URL: Homepage, https://github.com/sekro/pyicoshift
Project-URL: Bug Tracker, https://github.com/sekro/pyicoshift/issues
Keywords: icoshift,nmr,alignment
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy (>=1.23.3)
Requires-Dist: nmrglue (>=0.9)
Requires-Dist: matplotlib (>=3.6.0)
Requires-Dist: scipy (>=1.9.1)
Requires-Dist: scikit-learn (>=1.1.2)
Requires-Dist: statsmodels (>=0.13.2)

# pyicoshift

This is a rewrite in python of the [icoshift](https://www.sciencedirect.com/science/article/abs/pii/S1090780709003334) for MATLAB by F. Savorani, G. Tomasi, S.B. Engelsen.
This implementation provides all the core features as icoshift for matlab version XXX.

Snapshot of the original [icoshift webpage](https://web.archive.org/web/20220303211331/www.models.life.ku.dk/icoshift)

## New, additional features:
 * New target mode: select the signal with the highest correlation with all input signals
 as target.
 * Auto interval picking: detected peaks get clustered based on distance and intervaled accordingly
 * Some utility functions for more convinient import of Bruker NMR data
 * Autophasing based on the "automics" algorithm
 * Experimental multi-threading support for the optimal shift finding phase
 * Experimental syntethic target generation from HMDB spectra

## Install

pip install pyicoshift
 
## Usage

Instance a new object of the class Icoshift, asign signals, choose intervals and target mode, call run()
; see scripts in test folder for some examples

