Metadata-Version: 2.1
Name: msalign
Version: 0.0.8
Summary: msalign: Signal calibration and alignment by reference peaks
Home-page: https://github.com/lukasz-migas/msalign
Author: Lukasz Migas
Author-email: lukas.migas@yahoo.com
Maintainer: Lukasz Migas
Maintainer-email: lukas.migas@yahoo.com
License: Apache license 2.0
Download-URL: https://github.com/lukasz-migas/msalign
Description: # msalign - signal calibration and alignment
        
        [![Build Status](https://travis-ci.com/lukasz-migas/msalign.svg?branch=master)](https://travis-ci.com/lukasz-migas/msalign)
        [![codecov](https://codecov.io/gh/lukasz-migas/msalign/branch/master/graph/badge.svg)](https://codecov.io/gh/lukasz-migas/msalign)
        [![Requirements Status](https://requires.io/github/lukasz-migas/msalign/requirements.svg?branch=master)](https://requires.io/github/lukasz-migas/msalign/requirements/?branch=master)
        [![CodeFactor](https://www.codefactor.io/repository/github/lukasz-migas/msalign/badge)](https://www.codefactor.io/repository/github/lukasz-migas/msalign)
        
        [![Wheel](https://img.shields.io/pypi/wheel/msalign.svg)](https://pypi.org/project/msalign/)
        [![Versions](https://img.shields.io/pypi/pyversions/msalign.svg)](https://pypi.org/project/msalign/)
        
        This package was inspired by MATLAB's [msalign](https://mathworks.com/help/bioinfo/ref/msalign.html) function which
        allows alignment of multiple signals to reference peaks.
        
        ## Installation
        
        ```python
        pip install msalign
        ```
        
        or
        
        ```python
        pip install git+https://github.com/lukasz-migas/msalign.git
        ```
        
        ## Usage
        
        Usage is relatively straightforward. Simply import the function `msalign` from the package and provide `xvals`, `zvals`
        and `peaks`. Other parameters can be passed-in using `kwargs`.
        
        ```python
        import numpy as np
        from msalign import msalign
        
        
        fname = r"./example_data/msalign_test_data.csv"
        data = np.genfromtxt(fname, delimiter=",")
        xvals = data[1:, 0]
        zvals = data[1:, 1:].T
        
        peaks = [3991.4, 4598, 7964, 9160]
        kwargs = dict(
            iterations=5,
            weights=[60, 100, 60, 100],
            resolution=100,
            grid_steps=20,
            ratio=2.5,
            shift_range=[-100, 100],
            )
        
        zvals_new = msalign(xvals, zvals, peaks, **kwargs)
        ```
        
        ## Reference
        
        Monchamp, P., Andrade-Cetto, L., Zhang, J.Y., and Henson, R. (2007) Signal Processing Methods for Mass
        Spectrometry. In Systems Bioinformatics: An Engineering Case-Based Approach, G. Alterovitz and M.F. Ramoni, eds.
        Artech House Publishers).
        
        [MATLAB's msalign](https://mathworks.com/help/bioinfo/ref/msalign.html)
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Natural Language :: English
Description-Content-Type: text/markdown
