pynldas2

Access hourly NLDAS2 forcing data, part of HyRiver software stack

https://github.com/hyriver/pynldas2

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
    Links to: joss.theoj.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (4.9%) to scientific vocabulary

Keywords

climate forcing hydrology python

Keywords from Contributors

asyncio mesh sequences networks digital-elevation-model pde interactive urban daymet hacking
Last synced: 6 months ago · JSON representation ·

Repository

Access hourly NLDAS2 forcing data, part of HyRiver software stack

Basic Info
  • Host: GitHub
  • Owner: hyriver
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage: https://docs.hyriver.io
  • Size: 354 KB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 2
  • Open Issues: 1
  • Releases: 15
Topics
climate forcing hydrology python
Created about 3 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog Contributing Funding License Code of conduct Citation Authors

README.rst

.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/pynldas2_logo.png
    :target: https://github.com/hyriver/HyRiver

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    :target: https://joss.theoj.org/papers/b0df2f6192f0a18b9e622a3edff52e77
    :alt: JOSS

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    :target: https://github.com/hyriver/hydrosignatures/actions/workflows/test.yml
    :alt: Github Actions

================ ====================================================================
Package          Description
================ ====================================================================
PyNHD_           Navigate and subset NHDPlus (MR and HR) using web services
Py3DEP_          Access topographic data through National Map's 3DEP web service
PyGeoHydro_      Access NWIS, NID, WQP, eHydro, NLCD, CAMELS, and SSEBop databases
PyDaymet_        Access daily, monthly, and annual climate data via Daymet
PyGridMET_       Access daily climate data via GridMET
PyNLDAS2_        Access hourly NLDAS-2 data via web services
HydroSignatures_ A collection of tools for computing hydrological signatures
AsyncRetriever_  High-level API for asynchronous requests with persistent caching
PyGeoOGC_        Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services
PyGeoUtils_      Utilities for manipulating geospatial, (Geo)JSON, and (Geo)TIFF data
================ ====================================================================

.. _PyGeoHydro: https://github.com/hyriver/pygeohydro
.. _AsyncRetriever: https://github.com/hyriver/async-retriever
.. _PyGeoOGC: https://github.com/hyriver/pygeoogc
.. _PyGeoUtils: https://github.com/hyriver/pygeoutils
.. _PyNHD: https://github.com/hyriver/pynhd
.. _Py3DEP: https://github.com/hyriver/py3dep
.. _PyDaymet: https://github.com/hyriver/pydaymet
.. _PyGridMET: https://github.com/hyriver/pygridmet
.. _PyNLDAS2: https://github.com/hyriver/pynldas2
.. _HydroSignatures: https://github.com/hyriver/hydrosignatures

PyNLDAS2: Hourly NLDAS-2 Forcing Data
-------------------------------------

.. image:: https://img.shields.io/pypi/v/pynldas2.svg
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    :target: https://anaconda.org/conda-forge/pynldas2
    :alt: Conda Version

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    :target: https://codecov.io/gh/hyriver/pynldas2
    :alt: CodeCov

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    :alt: Python Versions

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    :target: https://pepy.tech/project/pynldas2
    :alt: Downloads

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   :alt: CodeFactor

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    :target: https://mybinder.org/v2/gh/hyriver/HyRiver-examples/main?urlpath=lab/tree/notebooks
    :alt: Binder

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Features
--------

PyNLDAS2 is a part of `HyRiver `__ software stack that
is designed to aid in hydroclimate analysis through web services. This package
provides access `NLDAS-2 Forcing dataset `__
via `Hydrology Data Rods `__.
Currently, only hourly data is supported. There are three main functions:

- ``get_bycoords``: Forcing data for a list of coordinates as a ``pandas.DataFrame`` or
  ``xarray.Dataset``,
- ``get_bygeom``: Forcing data within a geometry as a ``xarray.Dataset``,
- ``get_grid_mask``: NLDAS2
  `land/water grid mask `__
  as a ``xarray.Dataset``.

Both ``get_bygeom`` and ``get_bycoords`` functions save the intermediate files
returned by the web service in a local cache folder (``./cache`` in the current
directory). The cache folder is created automatically when the functions are
called for the first time. The cache folder is used to store the intermediate
files to avoid re-downloading them. These two functions allow modifying the
web service calls via two options:

- ``conn_timeout``: Sets the connection timeout in seconds. The default value
  is 5 minutes. This can be increaseed for larger requests. If running these
  functions fails with a connection timeout error, try increasing this value.
- ``validate_filesize``: If ``True``, the functions compares the file size
  of the previously cached files in the ``./cache`` folder, if they exist, with
  their size on the remote server. If the sizes do not match, the cached files are
  removed and they will be re-download. By default this is set to ``False`` since
  the files on the server rarely change. So, if a request has already been cached
  there shouldn't be a need for re-donwloading them from scratch. However, if you
  suspect that the files on the server have changed or the functions fails to process
  the cached files, you can set this to ``True`` or manually delete the cached
  files in the ``./cache`` folder.

You can find some example notebooks
`here `__.
You can also try using PyNLDAS2 without installing
it on your system by clicking on the binder badge. A Jupyter Lab
instance with the HyRiver stack pre-installed will be launched in your web browser,
and you can start coding!

Moreover, requests for additional functionalities can be submitted via
`issue tracker `__.

Citation
--------
If you use any of HyRiver packages in your research, we appreciate citations:

.. code-block:: bibtex

    @article{Chegini_2021,
        author = {Chegini, Taher and Li, Hong-Yi and Leung, L. Ruby},
        doi = {10.21105/joss.03175},
        journal = {Journal of Open Source Software},
        month = {10},
        number = {66},
        pages = {1--3},
        title = {{HyRiver: Hydroclimate Data Retriever}},
        volume = {6},
        year = {2021}
    }

Installation
------------

You can install ``pynldas2`` using ``pip``:

.. code-block:: console

    $ pip install pynldas2

Alternatively, ``pynldas2`` can be installed from the ``conda-forge`` repository
using `Conda `__:

.. code-block:: console

    $ conda install -c conda-forge pynldas2

Quick start
-----------

The NLDAS2 database provides forcing data at 1/8th-degree grid spacing and range
from 01 Jan 1979 to present. Let's take a look at NLDAS2 grid mask that includes
land, water, soil, and vegetation masks:


.. code-block:: python

    import pynldas2 as nldas

    grid = nldas.get_grid_mask()

.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_grid.png
    :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb

Next, we use `PyGeoHydro `__ to get the
geometry of a HUC8 with ID of 1306003, then we get the forcing data within the
obtained geometry.

.. code-block:: python

    from pygeohydro import WBD

    huc8 = WBD("huc8")
    geometry = huc8.byids("huc8", "13060003").geometry[0]
    clm = nldas.get_bygeom(geometry, "2010-01-01", "2010-01-31", 4326)

.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_humidity.png
    :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb

Road Map
--------

- [ ] Add PET calculation functions similar to
  `PyDaymet `__ but at hourly timescale.
- [ ] Add a command line interfaces.

Contributing
------------

Contributions are appreciated and very welcomed. Please read
`CONTRIBUTING.rst `__
for instructions.

Owner

  • Name: HyRiver
  • Login: hyriver
  • Kind: organization
  • Location: United States of America

A suite of Python packages that provides a unified API for retrieving geospatial/temporal data from various web services

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Chegini"
  given-names: "Taher"
  orcid: "https://orcid.org/0000-0002-5430-6000"
- family-names: "Li"
  given-names: "Hong-Yi"
  orcid: "https://orcid.org/0000-0002-9807-3851"
- family-names: "Leung"
  given-names: "L. Ruby"
  orcid: "https://orcid.org/0000-0002-3221-9467"
title: "HyRiver: Hydroclimate Data Retriever"
version: 0.11
doi: 10.21105/joss.03175
date-released: 2021-10-27
url: "https://github.com/cheginit/HyRiver"
preferred-citation:
  type: article
  authors:
  - family-names: "Chegini"
    given-names: "Taher"
    orcid: "https://orcid.org/0000-0002-5430-6000"
  - family-names: "Li"
    given-names: "Hong-Yi"
    orcid: "https://orcid.org/0000-0002-9807-3851"
  - family-names: "Leung"
    given-names: "L. Ruby"
    orcid: "https://orcid.org/0000-0002-3221-9467"
  doi: "10.21105/joss.03175"
  journal: "Journal of Open Source Software"
  month: 10
  start: 1
  end: 3
  title: "HyRiver: Hydroclimate Data Retriever"
  issue: 66
  volume: 6
  year: 2021

GitHub Events

Total
  • Create event: 5
  • Release event: 3
  • Issues event: 1
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 3
  • Push event: 7
  • Pull request event: 3
Last Year
  • Create event: 5
  • Release event: 3
  • Issues event: 1
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 3
  • Push event: 7
  • Pull request event: 3

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 228
  • Total Committers: 4
  • Avg Commits per committer: 57.0
  • Development Distribution Score (DDS): 0.057
Past Year
  • Commits: 185
  • Committers: 4
  • Avg Commits per committer: 46.25
  • Development Distribution Score (DDS): 0.065
Top Committers
Name Email Commits
Taher Chegini c****t@g****m 215
Taher Chegini t****i@g****m 5
dependabot[bot] 4****] 4
Luc Rébillout L****d 4

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 10
  • Average time to close issues: 4 days
  • Average time to close pull requests: 1 day
  • Total issue authors: 2
  • Total pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 2.0
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 9
Past Year
  • Issues: 1
  • Pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 day
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 2.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 3
Top Authors
Issue Authors
  • LucRSquared (2)
  • cheginit (1)
Pull Request Authors
  • dependabot[bot] (14)
  • LucRSquared (1)
Top Labels
Issue Labels
enhancement (2) bug (1)
Pull Request Labels
dependencies (14)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 286 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 15
  • Total maintainers: 1
pypi.org: pynldas2

Get NLDAS2 forcing data.

  • Versions: 15
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 286 Last month
Rankings
Dependent packages count: 6.6%
Downloads: 17.1%
Average: 24.8%
Forks count: 30.5%
Dependent repos count: 30.6%
Stargazers count: 39.1%
Maintainers (1)
Last synced: 6 months ago

Dependencies

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pyproject.toml pypi
  • async-retriever >=0.3.12
  • h5netcdf *
  • numpy >=1.21
  • pandas >=1
  • pygeoutils >=0.13.12
  • pyproj >=2.2
  • rioxarray >=0.11
  • xarray >=2022.03
ci/requirements/environment.yml pypi