terndata.flux 1.0.6

TERN flux data access library

terndata.flux

This is a Python package to work with TERN eddy covariance flux data. It provides API methods to explore and access flux datasets from the TERN Ecosystem processes Flux tower, The library will enable users to access all Flux data from THREDDS/DAP server (i.e. dap.tern.org.au).

Build

Buid the package wheel locally (docker required):

make build

Build the API documentation (set a Github personal token in envvars first):

make doc

To run unittests:

make test

OR

Run the script below in Python virtual environment:
    ./ci-scripts/run-tests.sh

Installation

Install from pypi:

pip install terndata.flux

API Methods

See the API documentation generated from the code (see above).

Getting started

The following examples are provided to help you get started, with sample output (as indicated by >>>) where appropriate:

    import terndata.flux as flux 
    # Get sites where flux data is available
    flux.get_sites()
    >>> site           longitude   latitude  ...                start                  end                     geometry
    AdelaideRiver      131.117800 -13.076900  ...  2007-10-17 11:30:00  2009-05-24 06:00:00    POINT (131.1178 -13.0769)
    AliceSpringsMulga  133.249000 -22.283000  ...  2010-09-03 00:00:00  2025-01-28 10:00:00      POINT (133.249 -22.283)
    AlpinePeatland     147.320833 -36.862222  ...  2017-04-12 18:30:00  2022-06-20 23:30:00  POINT (147.32083 -36.86222)
    Boyagin            116.938559 -32.477093  ...  2017-10-20 13:00:00  2025-02-02 00:00:00  POINT (116.93856 -32.47709)
    ...

    # get the versions available for the site
    flux.get_versions("AdelaideRiver")
    >>> ['2020', '2021_v1', '2022_v1', '2022_v2', '2023_v1', '2023_v2', '2024_v1', '2024_v2']
    
    # Get the processing-levels available for a site and version
    flux.get_processing_levels("AdelaideRiver", "2024_v2")
    >>> ['L3', 'L4', 'L5', 'L6']

    # Get a 30min dataset from a site, and of a version and processing-level.
    flux.get_dataset("AdelaideRiver", "2024_v2", "L3")
    >>> <xarray.Dataset> Size: 18MB
    Dimensions:             (time: 28070, latitude: 1, longitude: 1)
    Coordinates:
    * time                (time) datetime64[ns] 225kB 2007-10-17T11:30:00 ... 2...
    * latitude            (latitude) float64 8B -13.08
    * longitude           (longitude) float64 8B 131.1 
    ...

    # Get a daily dataset
    flux.get_l6_dataset("AdelaideRiver", "2024_v2", "daily")

    # Get 30min datasets from multiple sites
    sites = ["AdelaideRiver", "Warra"]
    flux.get_datasets(sites, "2024_v2", "L6")
    >>> {'AdelaideRiver': <xarray.Dataset> Size: 24MB
    Dimensions:             (time: 28070, latitude: 1, longitude: 1)
    Coordinates:
    * time                (time) datetime64[ns] 225kB 2007-10-17T11:30:00 ... 2...
    * latitude            (latitude) float64 8B -13.08
    * longitude           (longitude) float64 8B 131.1
    Data variables: (12/142)
    ...
    'Warra': <xarray.Dataset> Size: 191MB
    Dimensions:                  (time: 149851, latitude: 1, longitude: 1)
    Coordinates:
    * time                     (time) datetime64[ns] 1MB 2013-03-05T15:00:00 .....
    * latitude                 (latitude) float64 8B -43.1
    * longitude                (longitude) float64 8B 146.7
    Data variables: (12/210)
    ...
    }

    # Get a subset of 30min dataset from multiple sites, slice to 2 variables
    flux.get_subsets(["AdelaideRiver", "Warra"],  "2024_v2", "L3", ["AH", "CO2"])
    >>> {'AdelaideRiver': <xarray.Dataset> Size: 674kB
    Dimensions:    (time: 28070, latitude: 1, longitude: 1)
    Coordinates:
    * time       (time) datetime64[ns] 225kB 2007-10-17T11:30:00 ... 2009-05-24...
    * latitude   (latitude) float64 8B -13.08
    * longitude  (longitude) float64 8B 131.1
    Data variables:
        AH         (time, latitude, longitude) float64 225kB ...
        CO2        (time, latitude, longitude) float64 225kB ...
    ...
    'Warra': <xarray.Dataset> Size: 4MB
    Dimensions:    (time: 149851, latitude: 1, longitude: 1)
    Coordinates:
    * time       (time) datetime64[ns] 1MB 2013-03-05T15:00:00 ... 2021-09-21T1...
    * latitude   (latitude) float64 8B -43.1
    * longitude  (longitude) float64 8B 146.7
    Data variables:
        AH         (time, latitude, longitude) float64 1MB ...
        CO2        (time, latitude, longitude) float64 1MB ...
    ...

    # Export dataset as Excel workbook
    flux.export_as_excel("/home/user/excel_output.xlsx", "AdelaideRiver", "2024_v2", "L6")
    >>> '/home/user/excel_output.xlsx'

    # Export dataset as oneflux csv format
    flux.export_oneflux_csv("output_dir", "AdelaideRiver", "2024_v2", "L4")
    >>> ['output_dir/AU-Adr_qcv_2007.csv', 'output_dir/AU-Adr_qcv_2008.csv', 'output_dir/AU-Adr_qcv_2009.csv']

Dependencies

• xarray
• netcdf4
• packaging
• numpy
• pandas
• requests
• matplotlib
• defusedxml
• xlsxwriter
• xlrd
• matplotlib

Who do I talk to?

• please contact [e-mail] for any issues in the repository

How to cite

Yong Liaw, Gerhard Weis, Javier Sanchez Gonzalez, Siddeswara Guru, Peter Isaac, Ian McHugh. terndata.flux: A Python package for Accessing TERN Flux data. https://pypi.org/project/terndata.flux/