https://github.com/qedsoftware/brukeropusreader

Python package for reading Bruker OPUS files.
https://github.com/qedsoftware/brukeropusreader

absorption bruker bruker-opus ftir interferograms mpa opus python soil spectra spectral spectrometry spectroscopy

Last synced: 27 days ago
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Python package for reading Bruker OPUS files.

• Host: GitHub
• URL: https://github.com/qedsoftware/brukeropusreader
• Owner: qedsoftware
• License: lgpl-3.0
• Created: 2017-08-17T15:21:35.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2023-09-14T22:57:39.000Z (about 1 year ago)
• Last Synced: 2024-09-23T09:08:07.375Z (3 months ago)
• Topics: absorption, bruker, bruker-opus, ftir, interferograms, mpa, opus, python, soil, spectra, spectral, spectrometry, spectroscopy
• Language: Python
• Homepage: https://qed.ai
• Size: 49.8 KB
• Stars: 57
• Watchers: 11
• Forks: 34
• Open Issues: 16
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# Bruker OPUS Reader

## Introduction

The brukeropusreader Python package enables reading the binary OPUS files generated by Bruker spectrometers.

## Installation

### Install with pip

```pip install brukeropusreader```

## Usage

`read_file` parses OPUS file and returns `OpusData` object:

```

from brukeropusreader import read_file

opus_data = read_file('opus_file.0')

```

`OpusData` is a dict consisting of all fields found in opus file:

```

print(f'Parsed fields: '

      f'{list(opus_data.keys())}')

print(f'Absorption spectrum: '

      f'{opus_data["AB"]}'

```

For full code see [example](example.py).

## Algorithm

Algorithm taken from

https://bitbucket.org/hirschbeutel/ono/src/default/ono/bruker_opus_filereader.py

Author: @twagner

## Contact

For developer issues, please start a ticket in Github. 

You can also write to the dev team directly at [email protected]. 

For other issues, please write to: [email protected]

## License

This project is released under the terms of the LGPLv3 license, which is included in LICENSE.txt.

--

QED | https://qed.ai