| Name | pynldas2 JSON |
| Version |
0.18.0
JSON |
| download |
| home_page | None |
| Summary | Get NLDAS2 forcing data. |
| upload_time | 2024-10-06 16:39:48 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/pynldas2_logo.png
:target: https://github.com/hyriver/HyRiver
|
.. image:: https://joss.theoj.org/papers/b0df2f6192f0a18b9e622a3edff52e77/status.svg
:target: https://joss.theoj.org/papers/b0df2f6192f0a18b9e622a3edff52e77
:alt: JOSS
|
.. |pygeohydro| image:: https://github.com/hyriver/pygeohydro/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pygeohydro/actions/workflows/test.yml
:alt: Github Actions
.. |pygeoogc| image:: https://github.com/hyriver/pygeoogc/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pygeoogc/actions/workflows/test.yml
:alt: Github Actions
.. |pygeoutils| image:: https://github.com/hyriver/pygeoutils/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pygeoutils/actions/workflows/test.yml
:alt: Github Actions
.. |pynhd| image:: https://github.com/hyriver/pynhd/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pynhd/actions/workflows/test.yml
:alt: Github Actions
.. |py3dep| image:: https://github.com/hyriver/py3dep/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/py3dep/actions/workflows/test.yml
:alt: Github Actions
.. |pydaymet| image:: https://github.com/hyriver/pydaymet/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pydaymet/actions/workflows/test.yml
:alt: Github Actions
.. |pygridmet| image:: https://github.com/hyriver/pygridmet/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pygridmet/actions/workflows/test.yml
:alt: Github Actions
.. |pynldas2| image:: https://github.com/hyriver/pynldas2/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/pynldas2/actions/workflows/test.yml
:alt: Github Actions
.. |async| image:: https://github.com/hyriver/async-retriever/actions/workflows/test.yml/badge.svg
:target: https://github.com/hyriver/async-retriever/actions/workflows/test.yml
:alt: Github Actions
.. |signatures| image:: https://github.com/hyriver/hydrosignatures/actions/workflows/test.yml/badge.svg
: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
:target: https://pypi.python.org/pypi/pynldas2
:alt: PyPi
.. image:: https://img.shields.io/conda/vn/conda-forge/pynldas2.svg
:target: https://anaconda.org/conda-forge/pynldas2
:alt: Conda Version
.. image:: https://codecov.io/gh/hyriver/pynldas2/branch/main/graph/badge.svg
:target: https://codecov.io/gh/hyriver/pynldas2
:alt: CodeCov
.. image:: https://img.shields.io/pypi/pyversions/pynldas2.svg
:target: https://pypi.python.org/pypi/pynldas2
:alt: Python Versions
.. image:: https://static.pepy.tech/badge/pynldas2
:target: https://pepy.tech/project/pynldas2
:alt: Downloads
|
.. image:: https://www.codefactor.io/repository/github/hyriver/pynldas2/badge
:target: https://www.codefactor.io/repository/github/hyriver/pynldas2
:alt: CodeFactor
.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
:target: https://github.com/astral-sh/ruff
:alt: Ruff
.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
:target: https://github.com/pre-commit/pre-commit
:alt: pre-commit
.. image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/hyriver/HyRiver-examples/main?urlpath=lab/tree/notebooks
:alt: Binder
|
Features
--------
PyNLDAS2 is a part of `HyRiver <https://github.com/hyriver/HyRiver>`__ software stack that
is designed to aid in hydroclimate analysis through web services. This package
provides access `NLDAS-2 Forcing dataset <https://ldas.gsfc.nasa.gov/nldas/v2/forcing>`__
via `Hydrology Data Rods <https://disc.gsfc.nasa.gov/information/tools?title=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 <https://ldas.gsfc.nasa.gov/nldas/specifications>`__
as a ``xarray.Dataset``.
PyNLDAS2 only provides access to the hourly NLDAS2 dataset, so if you need to access
other NASA climate datasets you can check out
`tsgettoolbox <https://pypi.org/project/tsgettoolbox/>`__ developed by
`Tim Cera <https://github.com/timcera>`__.
Moreover, under the hood, PyNLDAS2 uses
`PyGeoOGC <https://github.com/hyriver/pygeoogc>`__ and
`AsyncRetriever <https://github.com/hyriver/async-retriever>`__ packages
for making requests in parallel and storing responses in chunks. This improves the
reliability and speed of data retrieval significantly.
You can control the request/response caching behavior and verbosity of the package
by setting the following environment variables:
* ``HYRIVER_CACHE_NAME``: Path to the caching SQLite database for asynchronous HTTP
requests. It defaults to ``./cache/aiohttp_cache.sqlite``
* ``HYRIVER_CACHE_NAME_HTTP``: Path to the caching SQLite database for HTTP requests.
It defaults to ``./cache/http_cache.sqlite``
* ``HYRIVER_CACHE_EXPIRE``: Expiration time for cached requests in seconds. It defaults to
one week.
* ``HYRIVER_CACHE_DISABLE``: Disable reading/writing from/to the cache. The default is false.
* ``HYRIVER_SSL_CERT``: Path to a SSL certificate file.
For example, in your code before making any requests you can do:
.. code-block:: python
import os
os.environ["HYRIVER_CACHE_NAME"] = "path/to/aiohttp_cache.sqlite"
os.environ["HYRIVER_CACHE_NAME_HTTP"] = "path/to/http_cache.sqlite"
os.environ["HYRIVER_CACHE_EXPIRE"] = "3600"
os.environ["HYRIVER_CACHE_DISABLE"] = "true"
os.environ["HYRIVER_SSL_CERT"] = "path/to/cert.pem"
You can find some example notebooks `here <https://github.com/hyriver/HyRiver-examples>`__.
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 <https://github.com/hyriver/pynldas2/issues>`__.
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 <https://docs.conda.io/en/latest/>`__:
.. 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 <https://github.com/hyriver/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 <https://github.com/hyriver/pydaymet>`__ but at hourly timescale.
- [ ] Add a command line interfaces.
Contributing
------------
Contributions are appreciated and very welcomed. Please read
`CONTRIBUTING.rst <https://github.com/hyriver/pynldas2/blob/main/CONTRIBUTING.rst>`__
for instructions.
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services\nHydroSignatures_ A collection of tools for computing hydrological signatures\nAsyncRetriever_ High-level API for asynchronous requests with persistent caching\nPyGeoOGC_ Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services\nPyGeoUtils_ Utilities for manipulating geospatial, (Geo)JSON, and (Geo)TIFF data\n================ ====================================================================\n\n.. _PyGeoHydro: https://github.com/hyriver/pygeohydro\n.. _AsyncRetriever: https://github.com/hyriver/async-retriever\n.. _PyGeoOGC: https://github.com/hyriver/pygeoogc\n.. _PyGeoUtils: https://github.com/hyriver/pygeoutils\n.. _PyNHD: https://github.com/hyriver/pynhd\n.. _Py3DEP: https://github.com/hyriver/py3dep\n.. _PyDaymet: https://github.com/hyriver/pydaymet\n.. _PyGridMET: https://github.com/hyriver/pygridmet\n.. _PyNLDAS2: https://github.com/hyriver/pynldas2\n.. _HydroSignatures: https://github.com/hyriver/hydrosignatures\n\nPyNLDAS2: Hourly NLDAS-2 Forcing Data\n-------------------------------------\n\n.. image:: https://img.shields.io/pypi/v/pynldas2.svg\n :target: https://pypi.python.org/pypi/pynldas2\n :alt: PyPi\n\n.. image:: https://img.shields.io/conda/vn/conda-forge/pynldas2.svg\n :target: https://anaconda.org/conda-forge/pynldas2\n :alt: Conda Version\n\n.. image:: https://codecov.io/gh/hyriver/pynldas2/branch/main/graph/badge.svg\n :target: https://codecov.io/gh/hyriver/pynldas2\n :alt: CodeCov\n\n.. image:: https://img.shields.io/pypi/pyversions/pynldas2.svg\n :target: https://pypi.python.org/pypi/pynldas2\n :alt: Python Versions\n\n.. image:: https://static.pepy.tech/badge/pynldas2\n :target: https://pepy.tech/project/pynldas2\n :alt: Downloads\n\n|\n\n.. image:: https://www.codefactor.io/repository/github/hyriver/pynldas2/badge\n :target: https://www.codefactor.io/repository/github/hyriver/pynldas2\n :alt: CodeFactor\n\n.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json\n :target: https://github.com/astral-sh/ruff\n :alt: Ruff\n\n.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white\n :target: https://github.com/pre-commit/pre-commit\n :alt: pre-commit\n\n.. image:: https://mybinder.org/badge_logo.svg\n :target: https://mybinder.org/v2/gh/hyriver/HyRiver-examples/main?urlpath=lab/tree/notebooks\n :alt: Binder\n\n|\n\nFeatures\n--------\n\nPyNLDAS2 is a part of `HyRiver <https://github.com/hyriver/HyRiver>`__ software stack that\nis designed to aid in hydroclimate analysis through web services. This package\nprovides access `NLDAS-2 Forcing dataset <https://ldas.gsfc.nasa.gov/nldas/v2/forcing>`__\nvia `Hydrology Data Rods <https://disc.gsfc.nasa.gov/information/tools?title=Hydrology+Data+Rods>`__.\nCurrently, only hourly data is supported. There are three main functions:\n\n- ``get_bycoords``: Forcing data for a list of coordinates as a ``pandas.DataFrame`` or\n ``xarray.Dataset``,\n- ``get_bygeom``: Forcing data within a geometry as a ``xarray.Dataset``,\n- ``get_grid_mask``: NLDAS2\n `land/water grid mask <https://ldas.gsfc.nasa.gov/nldas/specifications>`__\n as a ``xarray.Dataset``.\n\nPyNLDAS2 only provides access to the hourly NLDAS2 dataset, so if you need to access\nother NASA climate datasets you can check out\n`tsgettoolbox <https://pypi.org/project/tsgettoolbox/>`__ developed by\n`Tim Cera <https://github.com/timcera>`__.\n\nMoreover, under the hood, PyNLDAS2 uses\n`PyGeoOGC <https://github.com/hyriver/pygeoogc>`__ and\n`AsyncRetriever <https://github.com/hyriver/async-retriever>`__ packages\nfor making requests in parallel and storing responses in chunks. This improves the\nreliability and speed of data retrieval significantly.\n\nYou can control the request/response caching behavior and verbosity of the package\nby setting the following environment variables:\n\n* ``HYRIVER_CACHE_NAME``: Path to the caching SQLite database for asynchronous HTTP\n requests. It defaults to ``./cache/aiohttp_cache.sqlite``\n* ``HYRIVER_CACHE_NAME_HTTP``: Path to the caching SQLite database for HTTP requests.\n It defaults to ``./cache/http_cache.sqlite``\n* ``HYRIVER_CACHE_EXPIRE``: Expiration time for cached requests in seconds. It defaults to\n one week.\n* ``HYRIVER_CACHE_DISABLE``: Disable reading/writing from/to the cache. The default is false.\n* ``HYRIVER_SSL_CERT``: Path to a SSL certificate file.\n\nFor example, in your code before making any requests you can do:\n\n.. code-block:: python\n\n import os\n\n os.environ[\"HYRIVER_CACHE_NAME\"] = \"path/to/aiohttp_cache.sqlite\"\n os.environ[\"HYRIVER_CACHE_NAME_HTTP\"] = \"path/to/http_cache.sqlite\"\n os.environ[\"HYRIVER_CACHE_EXPIRE\"] = \"3600\"\n os.environ[\"HYRIVER_CACHE_DISABLE\"] = \"true\"\n os.environ[\"HYRIVER_SSL_CERT\"] = \"path/to/cert.pem\"\n\nYou can find some example notebooks `here <https://github.com/hyriver/HyRiver-examples>`__.\n\nYou can also try using PyNLDAS2 without installing\nit on your system by clicking on the binder badge. A Jupyter Lab\ninstance with the HyRiver stack pre-installed will be launched in your web browser, and you\ncan start coding!\n\nMoreover, requests for additional functionalities can be submitted via\n`issue tracker <https://github.com/hyriver/pynldas2/issues>`__.\n\nCitation\n--------\nIf you use any of HyRiver packages in your research, we appreciate citations:\n\n.. code-block:: bibtex\n\n @article{Chegini_2021,\n author = {Chegini, Taher and Li, Hong-Yi and Leung, L. Ruby},\n doi = {10.21105/joss.03175},\n journal = {Journal of Open Source Software},\n month = {10},\n number = {66},\n pages = {1--3},\n title = {{HyRiver: Hydroclimate Data Retriever}},\n volume = {6},\n year = {2021}\n }\n\nInstallation\n------------\n\nYou can install ``pynldas2`` using ``pip``:\n\n.. code-block:: console\n\n $ pip install pynldas2\n\nAlternatively, ``pynldas2`` can be installed from the ``conda-forge`` repository\nusing `Conda <https://docs.conda.io/en/latest/>`__:\n\n.. code-block:: console\n\n $ conda install -c conda-forge pynldas2\n\nQuick start\n-----------\n\nThe NLDAS2 database provides forcing data at 1/8th-degree grid spacing and range\nfrom 01 Jan 1979 to present. Let's take a look at NLDAS2 grid mask that includes\nland, water, soil, and vegetation masks:\n\n\n.. code-block:: python\n\n import pynldas2 as nldas\n\n grid = nldas.get_grid_mask()\n\n.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_grid.png\n :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb\n\nNext, we use `PyGeoHydro <https://github.com/hyriver/pygeohydro>`__ to get the\ngeometry of a HUC8 with ID of 1306003, then we get the forcing data within the\nobtained geometry.\n\n.. code-block:: python\n\n from pygeohydro import WBD\n\n huc8 = WBD(\"huc8\")\n geometry = huc8.byids(\"huc8\", \"13060003\").geometry[0]\n clm = nldas.get_bygeom(geometry, \"2010-01-01\", \"2010-01-31\", 4326)\n\n.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_humidity.png\n :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb\n\nRoad Map\n--------\n\n- [ ] Add PET calculation functions similar to\n `PyDaymet <https://github.com/hyriver/pydaymet>`__ but at hourly timescale.\n- [ ] Add a command line interfaces.\n\nContributing\n------------\n\nContributions are appreciated and very welcomed. Please read\n`CONTRIBUTING.rst <https://github.com/hyriver/pynldas2/blob/main/CONTRIBUTING.rst>`__\nfor instructions.\n",
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