Metadata-Version: 2.1
Name: msalign
Version: 0.0.6
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
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
Requires-Dist: numpy (>=1.9.3)
Requires-Dist: scipy (>=0.14.0)

# msalign - signal calibration and alignment

[![Build Status](https://travis-ci.com/lukasz-migas/msalign.svg?branch=master)](https://travis-ci.com/lukasz-migas/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)

