Metadata-Version: 1.2
Name: fluxdataqaqc
Version: 0.1.5
Summary: Tools for QA/QC of eddy covariance station data
Home-page: https://github.com/Open-ET/flux-data-qaqc
Author: John Volk
Author-email: john.volk@dri.edu
License: BSD3
Description: .. 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
        
        
        flux-data-qaqc
        ================
        
        ``flux-data-qaqc`` provides a framework to create reproducible workflows for the post-processing and analysis of eddy covariance time series data.
        
        Notable uses:
        
        * 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
        * facilitating batch processing 
        
        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. 
        
        
Platform: Windows
Platform: Linux
Platform: Mac OS X
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.7
Classifier: Environment :: Console
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.7
