# OCTAVVS: Open Chemometrics Toolbox for Analysis and Visualization of Vibrational Spectroscopy data
OCTAVVS is a set of graphical tools for high-throughput preprocessing and
analysis of vibrational spectroscopy data. Currently, the preprocessing is
primarily geared towards images from infrared absorption spectroscopy with
focal plane array detectors.
There are two/three separate tools in the current version:
**preprocessing** deals with atmospheric correction, resonant Mie scattering
correction, baseline correction and normalization.
**decomposition** decomposes observed spectra into nonnegative concentrations and
spectra using the MCR-ALS algorithm, performs K-means clustering on the MCR-ALS
concentrations (or on the input data), and allows the user to manually annotate
clusters and export the annotated data.
The decomposition tool supersedes two earlier tools:
**mcr_als** decomposes observed spectra into nonnegative concentrations and
spectra using the MCR-ALS algorithm.
**clustering** performs K-means clustering on the concentrations inferred by
MCR-ALS.
## Installation on Windows, Mac or Linux
OCCTAVS needs a working Python 3 environment with various packages. The
easiest way to get this is through the Conda package management system.
Download and install the Python 3.7 (or later) version of [Miniconda](https://docs.conda.io/en/latest/miniconda.html).
There are some platform-specific differences during installation:
* On **Windows**: The default options are good (no need to have Conda modify your path).
After installation, start a Conda console (found in the Start menu).
* On **Mac OS X**: The default options are good. (But _if_ you choose to not
let Conda modify your path, you can specify the full path to the commands
in the following steps.)
After installation, start Terminal.
* On **Linux**: Make the Miniconda .sh package executable and run it. When it asks about
running conda init, it wants to modify your ``$PATH`` in .bashrc. This can be fine, but on some
Linux distributions (notably OpenSUSE) it breaks KDE when logging in. A suggested workaround
is to change ``$PATH`` manually when needed. An alias in .bashrc can be convenient:
``alias startconda='export PATH=~/miniconda3/bin:"$PATH"'``
From the console, install OCTAVVS and its dependencies: ``conda install -c ctroein octavvs``
## Finding and using OCTAVVS
The easiest way to access the OCTAVVS tools is through desktop shortcuts
which are created by running the ``oct_make_icons`` script from the command prompt.
(We are not entirely sure if this works on all Mac OS X versions)
Regardless of whether you created icons, the scripts
``oct_preprocessing`` and ``oct_decomposition``
can be run straight from the console (Conda console or terminal window, as described above).
The location of the OCTAVVS scripts will depend on where you installed Conda.
Within the Conda directory, the three scripts will be in ``bin`` whereas
the actual Python code will be located in ``lib/python3.7/site-packages/octavvs``.
## Test data
Test data from two 64x64 images of _Paxillus_ hyphae growing on lignin can be
[downloaded here](http://cbbp.thep.lu.se/~carl/octavvs/octavvs_test_data.zip) (zip archive, 47 MB).
## Upgrading to the latest version
Information about the most recent release of OCTAVVS can be found on its
[PyPI page](https://pypi.org/project/octavvs), as well as on its
[Anaconda Cloud page](https://anaconda.org/ctroein/octavvs).
To upgrade to the most recent version, do ``conda update -c ctroein octavvs`` in the Conda console / Terminal.
Information about released versions can be found [here](https://github.com/ctroein/octavvs/blob/master/HISTORY.md).
## Bug reports and code repository
The main project homepage is its [GitHub page](https://github.com/ctroein/octavvs),
where developers can access the OCTAVVS code and submit bug reports and patches etc.
Questions, bug reports and other feedback may be sent to corresponding author Carl Troein <carl@thep.lu.se>.
## Installation through pip
Users familiar with Python could also install OCTAVVS through pip as an alternative to Anaconda,
as new releases will be made to PyPI in parallel with releases to Anaconda Cloud.
Note that pyqt and opencv sometimes don't work when installed through pip, depending on your system etc.
Raw data
{
"_id": null,
"home_page": "https://github.com/ctroein/octavvs",
"name": "octavvs",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": null,
"keywords": null,
"author": "Syahril Siregar, Carl Troein, Michiel Op De Beeck et al.",
"author_email": "carl@thep.lu.se",
"download_url": "https://files.pythonhosted.org/packages/8e/26/4e9fee28679c6e77465254d941d76cb7767cf37720c8cada35c12a27f00e/octavvs-0.1.29.tar.gz",
"platform": null,
"description": "# OCTAVVS: Open Chemometrics Toolbox for Analysis and Visualization of Vibrational Spectroscopy data\n\nOCTAVVS is a set of graphical tools for high-throughput preprocessing and\nanalysis of vibrational spectroscopy data. Currently, the preprocessing is\nprimarily geared towards images from infrared absorption spectroscopy with\nfocal plane array detectors.\n\nThere are two/three separate tools in the current version:\n\n**preprocessing** deals with atmospheric correction, resonant Mie scattering\ncorrection, baseline correction and normalization.\n\n**decomposition** decomposes observed spectra into nonnegative concentrations and\nspectra using the MCR-ALS algorithm, performs K-means clustering on the MCR-ALS\nconcentrations (or on the input data), and allows the user to manually annotate\nclusters and export the annotated data.\n\nThe decomposition tool supersedes two earlier tools:\n\n**mcr_als** decomposes observed spectra into nonnegative concentrations and\nspectra using the MCR-ALS algorithm.\n\n**clustering** performs K-means clustering on the concentrations inferred by\nMCR-ALS.\n\n## Installation on Windows, Mac or Linux\n\nOCCTAVS needs a working Python 3 environment with various packages. The\neasiest way to get this is through the Conda package management system.\n\nDownload and install the Python 3.7 (or later) version of [Miniconda](https://docs.conda.io/en/latest/miniconda.html).\nThere are some platform-specific differences during installation:\n\n* On **Windows**: The default options are good (no need to have Conda modify your path). \nAfter installation, start a Conda console (found in the Start menu).\n\n* On **Mac OS X**: The default options are good. (But _if_ you choose to not\nlet Conda modify your path, you can specify the full path to the commands\nin the following steps.) \nAfter installation, start Terminal. \n\n* On **Linux**: Make the Miniconda .sh package executable and run it. When it asks about\nrunning conda init, it wants to modify your ``$PATH`` in .bashrc. This can be fine, but on some\nLinux distributions (notably OpenSUSE) it breaks KDE when logging in. A suggested workaround\nis to change ``$PATH`` manually when needed. An alias in .bashrc can be convenient: \n``alias startconda='export PATH=~/miniconda3/bin:\"$PATH\"'``\n\nFrom the console, install OCTAVVS and its dependencies: ``conda install -c ctroein octavvs``\n\n## Finding and using OCTAVVS\n\nThe easiest way to access the OCTAVVS tools is through desktop shortcuts\nwhich are created by running the ``oct_make_icons`` script from the command prompt.\n(We are not entirely sure if this works on all Mac OS X versions)\n\nRegardless of whether you created icons, the scripts\n``oct_preprocessing`` and ``oct_decomposition``\ncan be run straight from the console (Conda console or terminal window, as described above).\n\nThe location of the OCTAVVS scripts will depend on where you installed Conda.\nWithin the Conda directory, the three scripts will be in ``bin`` whereas\nthe actual Python code will be located in ``lib/python3.7/site-packages/octavvs``.\n\n## Test data\n\nTest data from two 64x64 images of _Paxillus_ hyphae growing on lignin can be\n[downloaded here](http://cbbp.thep.lu.se/~carl/octavvs/octavvs_test_data.zip) (zip archive, 47 MB).\n\n## Upgrading to the latest version\n\nInformation about the most recent release of OCTAVVS can be found on its\n[PyPI page](https://pypi.org/project/octavvs), as well as on its\n[Anaconda Cloud page](https://anaconda.org/ctroein/octavvs).\n\nTo upgrade to the most recent version, do ``conda update -c ctroein octavvs`` in the Conda console / Terminal.\n\nInformation about released versions can be found [here](https://github.com/ctroein/octavvs/blob/master/HISTORY.md).\n\n## Bug reports and code repository\n\nThe main project homepage is its [GitHub page](https://github.com/ctroein/octavvs),\nwhere developers can access the OCTAVVS code and submit bug reports and patches etc.\n\nQuestions, bug reports and other feedback may be sent to corresponding author Carl Troein <carl@thep.lu.se>.\n\n\n## Installation through pip\n\nUsers familiar with Python could also install OCTAVVS through pip as an alternative to Anaconda,\nas new releases will be made to PyPI in parallel with releases to Anaconda Cloud.\nNote that pyqt and opencv sometimes don't work when installed through pip, depending on your system etc.\n\n",
"bugtrack_url": null,
"license": null,
"summary": "Open Chemometrics Toolkit for Analysis and Visualization of Vibrational Spectroscopy data",
"version": "0.1.29",
"project_urls": {
"Homepage": "https://github.com/ctroein/octavvs"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "eec23b8f7b290965a890eef8b7224ec49d674fd40be46e25418809b1affb6a46",
"md5": "a44b32d4d2c854164e57e9bbe3743be4",
"sha256": "463455e4f9bf8dfeda5a2ac1e77c36ef2a3eabdc66864ad79502c211a2f03d0e"
},
"downloads": -1,
"filename": "octavvs-0.1.29-py3-none-any.whl",
"has_sig": false,
"md5_digest": "a44b32d4d2c854164e57e9bbe3743be4",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 3234982,
"upload_time": "2024-08-03T19:39:33",
"upload_time_iso_8601": "2024-08-03T19:39:33.023545Z",
"url": "https://files.pythonhosted.org/packages/ee/c2/3b8f7b290965a890eef8b7224ec49d674fd40be46e25418809b1affb6a46/octavvs-0.1.29-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "8e264e9fee28679c6e77465254d941d76cb7767cf37720c8cada35c12a27f00e",
"md5": "9789568a6ca60f20790bcad9f03d7b16",
"sha256": "9ee2dc94dead12375ec5153f7e222a9e0254aacb1a3397f9470b9d458600faf6"
},
"downloads": -1,
"filename": "octavvs-0.1.29.tar.gz",
"has_sig": false,
"md5_digest": "9789568a6ca60f20790bcad9f03d7b16",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 3182174,
"upload_time": "2024-08-03T19:39:37",
"upload_time_iso_8601": "2024-08-03T19:39:37.815100Z",
"url": "https://files.pythonhosted.org/packages/8e/26/4e9fee28679c6e77465254d941d76cb7767cf37720c8cada35c12a27f00e/octavvs-0.1.29.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-08-03 19:39:37",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ctroein",
"github_project": "octavvs",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "octavvs"
}
JSON
