| Name | cotede JSON |
| Version |
0.23.9
JSON |
| download |
| home_page | |
| Summary | Quality Control of Oceanographic Data |
| upload_time | 2023-06-13 03:12:18 |
| maintainer | |
| docs_url | None |
| author | Guilherme Castelão |
| requires_python | >=3.8 |
| license | Copyright (c) 2011-2023, Guilherme Pimenta Castelão 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, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the CoTeDe Team nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
oceanography
ocean data
quality control
ctd
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
|
| coveralls test coverage |
No coveralls.
|
======
CoTeDe
======
.. image:: https://joss.theoj.org/papers/10.21105/joss.02063/status.svg
:target: https://doi.org/10.21105/joss.02063
.. image:: https://zenodo.org/badge/10284681.svg
:target: https://zenodo.org/badge/latestdoi/10284681
.. image:: https://readthedocs.org/projects/cotede/badge/?version=latest
:target: https://cotede.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://img.shields.io/travis/castelao/CoTeDe.svg
:target: https://travis-ci.org/castelao/CoTeDe
.. image:: https://codecov.io/gh/castelao/CoTeDe/branch/master/graph/badge.svg
:target: https://codecov.io/gh/castelao/CoTeDe
.. image:: https://img.shields.io/pypi/v/cotede.svg
:target: https://pypi.python.org/pypi/cotede
.. image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/castelao/CoTeDe/master?filepath=docs%2Fnotebooks
`CoTeDe <http://cotede.castelao.net>`_ is an Open Source Python package to quality control (QC) oceanographic data such as temperature and salinity.
It was designed to attend individual scientists as well as real-time operations on large data centers.
To achieve that, CoTeDe is highly customizable, giving the user full control to compose the desired set of tests including the specific parameters of each test, or choose from a list of preset QC procedures.
I believe that we can do better than we have been doing with more flexible classification techniques, which includes machine learning. My goal is to minimize the burden on manual expert QC improving the consistency, performance, and reliability of the QC procedure for oceanographic data, especially for real-time operations.
CoTeDe is the result from several generations of quality control systems that started in 2006 with real-time QC of TSGs and were later expanded for other platforms including CTDs, XBTs, gliders, and others.
----------
Why CoTeDe
----------
CoTeDe contains several QC procedures that can be easily combined in different ways:
- Pre-set standard tests according to the recommendations by GTSPP, EGOOS, XBT, Argo or QARTOD;
- Custom set of tests, including user defined thresholds;
- Two different fuzzy logic approaches: as proposed by Timms et. al 2011 & Morello et. al. 2014, and using usual defuzification by the bisector;
- A novel approach based on Anomaly Detection, described by `Castelao 2021 <https://doi.org/10.1016/j.cageo.2021.104803>`_ (available since 2014 `<http://arxiv.org/abs/1503.02714>`_).
Each measuring platform is a different realm with its own procedures, metadata, and meaningful visualization.
So CoTeDe focuses on providing a robust framework with the procedures and lets each application, and the user, to decide how to drive the QC.
For instance, the `pySeabird package <http://seabird.castelao.net>`_ is another package that understands CTD and uses CoTeDe as a plugin to QC.
-------------
Documentation
-------------
A detailed documentation is available at http://cotede.readthedocs.org, while a collection of notebooks with examples is available at
http://nbviewer.ipython.org/github/castelao/CoTeDe/tree/master/docs/notebooks/
--------
Citation
--------
If you use CoTeDe, or replicate part of it, in your work/package, please consider including the reference:
Castelão, G. P., (2020). A Framework to Quality Control Oceanographic Data. Journal of Open Source Software, 5(48), 2063, https://doi.org/10.21105/joss.02063
::
@article{Castelao2020,
doi = {10.21105/joss.02063},
url = {https://doi.org/10.21105/joss.02063},
year = {2020},
publisher = {The Open Journal},
volume = {5},
number = {48},
pages = {2063},
author = {Guilherme P. Castelao},
title = {A Framework to Quality Control Oceanographic Data},
journal = {Journal of Open Source Software}
}
For the Anomaly Detection techinique specifically, which was implemented in CoTeDe, please include the reference:
Castelão, G. P. (2021). A Machine Learning Approach to Quality Control Oceanographic Data. Computers & Geosciences, https://doi.org/10.1016/j.cageo.2021.104803
::
@article{Castelao2021,
doi = {10.1016/j.cageo.2021.104803},
url = {https://doi.org/10.1016/j.cageo.2021.104803},
year = {2021},
publisher = {Elsevier},
author = {Guilherme P. Castelao},
title = {A Machine Learning Approach to Quality Control Oceanographic Data},
journal = {Computers and Geosciences}
}
If you are concerned about reproducibility, please include the DOI provided by Zenodo on the top of this page, which is associated with a specific release (version).
Raw data
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"description": "======\nCoTeDe\n======\n\n.. image:: https://joss.theoj.org/papers/10.21105/joss.02063/status.svg\n :target: https://doi.org/10.21105/joss.02063\n\n.. image:: https://zenodo.org/badge/10284681.svg\n :target: https://zenodo.org/badge/latestdoi/10284681\n\n.. image:: https://readthedocs.org/projects/cotede/badge/?version=latest\n :target: https://cotede.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: https://img.shields.io/travis/castelao/CoTeDe.svg\n :target: https://travis-ci.org/castelao/CoTeDe\n\n.. image:: https://codecov.io/gh/castelao/CoTeDe/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/castelao/CoTeDe\n\n.. image:: https://img.shields.io/pypi/v/cotede.svg\n :target: https://pypi.python.org/pypi/cotede\n\n.. image:: https://mybinder.org/badge_logo.svg\n :target: https://mybinder.org/v2/gh/castelao/CoTeDe/master?filepath=docs%2Fnotebooks\n\n\n`CoTeDe <http://cotede.castelao.net>`_ is an Open Source Python package to quality control (QC) oceanographic data such as temperature and salinity.\nIt was designed to attend individual scientists as well as real-time operations on large data centers.\nTo achieve that, CoTeDe is highly customizable, giving the user full control to compose the desired set of tests including the specific parameters of each test, or choose from a list of preset QC procedures.\n\nI believe that we can do better than we have been doing with more flexible classification techniques, which includes machine learning. My goal is to minimize the burden on manual expert QC improving the consistency, performance, and reliability of the QC procedure for oceanographic data, especially for real-time operations.\n\nCoTeDe is the result from several generations of quality control systems that started in 2006 with real-time QC of TSGs and were later expanded for other platforms including CTDs, XBTs, gliders, and others.\n\n\n----------\nWhy CoTeDe\n----------\n\nCoTeDe contains several QC procedures that can be easily combined in different ways:\n\n- Pre-set standard tests according to the recommendations by GTSPP, EGOOS, XBT, Argo or QARTOD;\n- Custom set of tests, including user defined thresholds;\n- Two different fuzzy logic approaches: as proposed by Timms et. al 2011 & Morello et. al. 2014, and using usual defuzification by the bisector;\n- A novel approach based on Anomaly Detection, described by `Castelao 2021 <https://doi.org/10.1016/j.cageo.2021.104803>`_ (available since 2014 `<http://arxiv.org/abs/1503.02714>`_).\n\nEach measuring platform is a different realm with its own procedures, metadata, and meaningful visualization. \nSo CoTeDe focuses on providing a robust framework with the procedures and lets each application, and the user, to decide how to drive the QC.\nFor instance, the `pySeabird package <http://seabird.castelao.net>`_ is another package that understands CTD and uses CoTeDe as a plugin to QC.\n\n-------------\nDocumentation\n-------------\n\nA detailed documentation is available at http://cotede.readthedocs.org, while a collection of notebooks with examples is available at\nhttp://nbviewer.ipython.org/github/castelao/CoTeDe/tree/master/docs/notebooks/\n\n--------\nCitation\n--------\n\nIf you use CoTeDe, or replicate part of it, in your work/package, please consider including the reference:\n\nCastel\u00e3o, G. P., (2020). A Framework to Quality Control Oceanographic Data. Journal of Open Source Software, 5(48), 2063, https://doi.org/10.21105/joss.02063\n\n::\n\n @article{Castelao2020,\n doi = {10.21105/joss.02063},\n url = {https://doi.org/10.21105/joss.02063},\n year = {2020},\n publisher = {The Open Journal},\n volume = {5},\n number = {48},\n pages = {2063},\n author = {Guilherme P. Castelao},\n title = {A Framework to Quality Control Oceanographic Data},\n journal = {Journal of Open Source Software}\n }\n\nFor the Anomaly Detection techinique specifically, which was implemented in CoTeDe, please include the reference:\n\nCastel\u00e3o, G. P. (2021). A Machine Learning Approach to Quality Control Oceanographic Data. Computers & Geosciences, https://doi.org/10.1016/j.cageo.2021.104803\n\n::\n\n @article{Castelao2021,\n doi = {10.1016/j.cageo.2021.104803},\n url = {https://doi.org/10.1016/j.cageo.2021.104803},\n year = {2021},\n publisher = {Elsevier},\n author = {Guilherme P. Castelao},\n title = {A Machine Learning Approach to Quality Control Oceanographic Data},\n journal = {Computers and Geosciences}\n }\n\nIf you are concerned about reproducibility, please include the DOI provided by Zenodo on the top of this page, which is associated with a specific release (version).\n",
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