.. image:: https://readthedocs.org/projects/flux-data-qaqc/badge/?version=latest
:target: https://flux-data-qaqc.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://github.com/Open-ET/flux-data-qaqc/actions/workflows/fluxdataqaqc_tests.yml/badge.svg
:target: https://github.com/Open-ET/flux-data-qaqc/actions/workflows/fluxdataqaqc_tests.yml
:alt: Automated tests
flux-data-qaqc
================
``flux-data-qaqc`` provides a framework to create reproducible workflows for validation and analysis of eddy covariance data. The package is intended for those who need to post-process flux data, particularly for generating daily and monthly evapotranspiration (ET) timeseries estimates with energy balance closure corrections applied. Applications where this software may be useful include analysis of eddy covariance data, hydrologic or atmospheric model validation, and irrigation and water consumption studies.
Key functionalities and tools include:
* data validation with methods for quality-based filtering
* time series tools, e.g. gap-filling and temporal aggregation
* energy balance closure algorithms and other meterological calculations
* data provenance, e.g. from metadata management and file structure
* downloading and management of `gridMET <http://www.climatologylab.org/gridmet.html>`__ meterological data
* customizable and interactive visualizations
* built-in unit conversions and batch processing tools
Documentation
-------------
`ReadTheDocs <https://flux-data-qaqc.readthedocs.io/>`_
Installation
------------
Using PIP:
.. code-block:: bash
pip install fluxdataqaqc
PIP should install the necessary dependencies however it is recommended to use
conda and first install the provided virtual environment. This is useful to
avoid changing your local Python environment. Note, ``flux-data-qaqc`` has been
tested for Python 3.7+, although it may work with versions greater than or
equal to 3.4.
First make sure you have the ``fluxdataqaqc`` environment file, you can download it `here <https://raw.githubusercontent.com/Open-ET/flux-data-qaqc/master/environment.yml?token=AB3BJKUKL2ELEM7WPLYLXFC45WQOG>`_. Next to install run,
.. code-block:: bash
conda env create -f environment.yml
To activate the environment before using the ``flux-data-qaqc`` package run,
.. code-block:: bash
conda activate fluxdataqaqc
Now install using PIP:
.. code-block:: bash
pip install fluxdataqaqc
Now all package modules and tools should be available in your Python environment PATH and able to be imported. Note if you did not install the Conda virtual environment above, PIP should install dependencies automatically but be sure to be using a version of Python above or equal to 3.4. To test that everything has installed correctly by opening a Python interpretor or IDE and run the following:
.. code-block:: python
import fluxdataqaqc
and
.. code-block:: python
from fluxdataqaqc import Data, QaQc, Plot
If everything has been installed correctly you should get no errors.
How to cite
-----------
Volk et al., (2021). flux-data-qaqc: A Python Package for Energy Balance Closure and Post-Processing of Eddy Flux Data. Journal of Open Source Software, 6(66), 3418, https://doi.org/10.21105/joss.03418
Raw data
{
"_id": null,
"home_page": "https://github.com/Open-ET/flux-data-qaqc",
"name": "fluxdataqaqc",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": null,
"keywords": null,
"author": "John Volk",
"author_email": "john.volk@dri.edu",
"download_url": "https://files.pythonhosted.org/packages/ea/47/44841fb217a392e0ea0af5617d44477c22a157a555ef6a9124373802be67/fluxdataqaqc-0.2.2.tar.gz",
"platform": "Windows",
"description": ".. image:: https://readthedocs.org/projects/flux-data-qaqc/badge/?version=latest\n :target: https://flux-data-qaqc.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: https://github.com/Open-ET/flux-data-qaqc/actions/workflows/fluxdataqaqc_tests.yml/badge.svg\n :target: https://github.com/Open-ET/flux-data-qaqc/actions/workflows/fluxdataqaqc_tests.yml\n :alt: Automated tests\n\nflux-data-qaqc\n================\n\n``flux-data-qaqc`` provides a framework to create reproducible workflows for validation and analysis of eddy covariance data. The package is intended for those who need to post-process flux data, particularly for generating daily and monthly evapotranspiration (ET) timeseries estimates with energy balance closure corrections applied. Applications where this software may be useful include analysis of eddy covariance data, hydrologic or atmospheric model validation, and irrigation and water consumption studies. \n\nKey functionalities and tools include:\n\n* data validation with methods for quality-based filtering\n* time series tools, e.g. gap-filling and temporal aggregation\n* energy balance closure algorithms and other meterological calculations\n* data provenance, e.g. from metadata management and file structure\n* downloading and management of `gridMET <http://www.climatologylab.org/gridmet.html>`__ meterological data\n* customizable and interactive visualizations\n* built-in unit conversions and batch processing tools\n\nDocumentation\n-------------\n\n`ReadTheDocs <https://flux-data-qaqc.readthedocs.io/>`_\n\nInstallation\n------------\n\nUsing PIP:\n\n.. code-block:: bash\n\n pip install fluxdataqaqc\n\nPIP should install the necessary dependencies however it is recommended to use\nconda and first install the provided virtual environment. This is useful to\navoid changing your local Python environment. Note, ``flux-data-qaqc`` has been\ntested for Python 3.7+, although it may work with versions greater than or\nequal to 3.4.\n\nFirst make sure you have the ``fluxdataqaqc`` environment file, you can download it `here <https://raw.githubusercontent.com/Open-ET/flux-data-qaqc/master/environment.yml?token=AB3BJKUKL2ELEM7WPLYLXFC45WQOG>`_. Next to install run,\n\n.. code-block:: bash\n\n conda env create -f environment.yml\n\nTo activate the environment before using the ``flux-data-qaqc`` package run,\n\n.. code-block:: bash\n\n conda activate fluxdataqaqc\n\nNow install using PIP:\n\n.. code-block:: bash\n\n pip install fluxdataqaqc\n\nNow all package modules and tools should be available in your Python environment PATH and able to be imported. Note if you did not install the Conda virtual environment above, PIP should install dependencies automatically but be sure to be using a version of Python above or equal to 3.4. To test that everything has installed correctly by opening a Python interpretor or IDE and run the following:\n\n.. code-block:: python\n\n import fluxdataqaqc\n\nand \n\n.. code-block:: python\n\n from fluxdataqaqc import Data, QaQc, Plot\n\nIf everything has been installed correctly you should get no errors. \n\n\nHow to cite\n-----------\n\nVolk et al., (2021). flux-data-qaqc: A Python Package for Energy Balance Closure and Post-Processing of Eddy Flux Data. Journal of Open Source Software, 6(66), 3418, https://doi.org/10.21105/joss.03418\n\n",
"bugtrack_url": null,
"license": "BSD3",
"summary": "Tools for QA/QC of eddy covariance station data",
"version": "0.2.2",
"project_urls": {
"Homepage": "https://github.com/Open-ET/flux-data-qaqc"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "b85f1d9c9e2df417ae15623bc25052ddcdf0acac10bc40da01fcbde70c06fa47",
"md5": "93f1951befbe21b4f31a6d144f6f7384",
"sha256": "7dda57d3e4c6f32c0bd9d28794322a33bf15e6c22042b21ed3732a7a32613a79"
},
"downloads": -1,
"filename": "fluxdataqaqc-0.2.2-py2.py3-none-any.whl",
"has_sig": false,
"md5_digest": "93f1951befbe21b4f31a6d144f6f7384",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": ">=3.7",
"size": 54086,
"upload_time": "2024-12-09T17:50:23",
"upload_time_iso_8601": "2024-12-09T17:50:23.415480Z",
"url": "https://files.pythonhosted.org/packages/b8/5f/1d9c9e2df417ae15623bc25052ddcdf0acac10bc40da01fcbde70c06fa47/fluxdataqaqc-0.2.2-py2.py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ea4744841fb217a392e0ea0af5617d44477c22a157a555ef6a9124373802be67",
"md5": "766c89b011399a0308260406956515df",
"sha256": "e525de3f3718f1bfc23f474b3063cb7717e8ccb12775406c39a098017fcc0bc7"
},
"downloads": -1,
"filename": "fluxdataqaqc-0.2.2.tar.gz",
"has_sig": false,
"md5_digest": "766c89b011399a0308260406956515df",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 90225720,
"upload_time": "2024-12-09T17:50:58",
"upload_time_iso_8601": "2024-12-09T17:50:58.176990Z",
"url": "https://files.pythonhosted.org/packages/ea/47/44841fb217a392e0ea0af5617d44477c22a157a555ef6a9124373802be67/fluxdataqaqc-0.2.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-09 17:50:58",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Open-ET",
"github_project": "flux-data-qaqc",
"travis_ci": true,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "bokeh",
"specs": [
[
"==",
"3.1.1"
]
]
},
{
"name": "numpy",
"specs": [
[
"==",
"1.24.3"
]
]
},
{
"name": "openpyxl",
"specs": [
[
"==",
"3.0.10"
]
]
},
{
"name": "pandas",
"specs": [
[
"==",
"2.0.3"
]
]
},
{
"name": "pytest",
"specs": [
[
"==",
"7.4.0"
]
]
},
{
"name": "refet",
"specs": [
[
"==",
"0.4.2"
]
]
},
{
"name": "scikit_learn",
"specs": [
[
"==",
"1.3.0"
]
]
},
{
"name": "setuptools",
"specs": [
[
"==",
"68.0.0"
]
]
},
{
"name": "xarray",
"specs": [
[
"==",
"2023.1.0"
]
]
}
],
"lcname": "fluxdataqaqc"
}
JSON
