Metadata-Version: 2.1
Name: pydaymet
Version: 0.10.2
Summary: Access the climate data from the Daymet database through its RESTful service.
Home-page: https://github.com/cheginit/pydaymet
Author: Taher Chegini
Author-email: cheginit@gmail.com
License: MIT
Project-URL: Issues, https://github.com/cheginit/pydaymet/issues
Project-URL: CI, https://github.com/cheginit/pydaymet/actions
Project-URL: Changelog, https://github.com/cheginit/pydaymet/blob/master/HISTORY.rst
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            :target: https://github.com/cheginit/pydaymet
        
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        =========== ==================================================================== ============
        Package     Description                                                          Status
        =========== ==================================================================== ============
        PyGeoHydro_ Access NWIS, NID, HCDN 2009, NLCD, and SSEBop databases              |pygeohydro|
        PyGeoOGC_   Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services    |pygeoogc|
        PyGeoUtils_ Convert responses from PyGeoOGC's supported web services to datasets |pygeoutils|
        PyNHD_      Navigate and subset NHDPlus (MR and HR) using web services           |pynhd|
        Py3DEP_     Access topographic data through National Map's 3DEP web service      |py3dep|
        PyDaymet_   Access Daymet for daily climate data both single pixel and gridded   |pydaymet|
        =========== ==================================================================== ============
        
        .. _PyGeoHydro: https://github.com/cheginit/pygeohydro
        .. _PyGeoOGC: https://github.com/cheginit/pygeoogc
        .. _PyGeoUtils: https://github.com/cheginit/pygeoutils
        .. _PyNHD: https://github.com/cheginit/pynhd
        .. _Py3DEP: https://github.com/cheginit/py3dep
        .. _PyDaymet: https://github.com/cheginit/pydaymet
        
        PyDaymet: Daily climate data through Daymet
        -------------------------------------------
        
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        Features
        --------
        
        PyDaymet is a part of `HyRiver <https://github.com/cheginit/HyRiver>`__ software stack that
        is designed to aid in watershed analysis through web services. This package provides
        an interface to access to daily climate data through the `Daymet <https://daymet.ornl.gov/>`__
        RESTful service. Both single pixel and gridded data can be requested which are returned as
        ``pandas.DataFrame`` and ``xarray.Dataset``, respectively. Climate data is available for CONUS,
        Hawaii, and Puerto Rico. Additionally, PyDaymet can compute Potential EvapoTranspiration (PET)
        using `UN-FAO 56 paper <http://www.fao.org/docrep/X0490E/X0490E00.htm>`__ method for both single
        pixel and gridded data.
        
        Note that starting from version ``0.9.0``, the recently released version of Daymet database
        is used. You can check the release information `here <https://daac.ornl.gov/DAYMET/guides/Daymet_Daily_V4.html>`_.
        Moreover, there's a new function called ``get_bycoords`` that is an alternative to ``get_byloc``
        for getting climate data at a single pixel. This new function uses THREDDS data server
        with NetCDF Subset Service (NCSS), and supports getting monthly and annual summaries directly
        from the server. You can pass ``time_scale`` as ``daily``, ``monthly``, or ``annual``
        to ``get_bygeom`` or ``get_bycoords`` functions to download the respective summaries.
        ``get_bycoords`` will replace ``get_byloc`` in  the future.
        So, please consider migrating your code by replacing ``get_byloc`` with ``get_bycoords``. The
        input arguments of ``get_bycoords`` is identical to ``get_bygeom``. Another difference
        between ``get_byloc`` and ``get_bycoords`` is column names where ``get_bycoords`` uses
        the units that are returned by NCSS server. Moreover, both ``get_bygeom`` and ``get_bycoords``
        accept an additional argument called ``region`` for passing the region of interest.
        
        You can try using PyDaymet without installing it on you system by clicking on the binder badge
        below the PyDaymet banner. A Jupyter notebook instance with the stack
        pre-installed will be launched in your web browser and you can start coding!
        
        Please note that since this project is in early development stages, while the provided
        functionalities should be stable, changes in APIs are possible in new releases. But we
        appreciate it if you give this project a try and provide feedback. Contributions are most welcome.
        
        Moreover, requests for additional functionalities can be submitted via
        `issue tracker <https://github.com/cheginit/pydaymet/issues>`__.
        
        Installation
        ------------
        
        You can install PyDaymet using ``pip`` after installing ``libgdal`` on your system
        (for example, in Ubuntu run ``sudo apt install libgdal-dev``):
        
        .. code-block:: console
        
            $ pip install pydaymet
        
        Alternatively, PyDaymet can be installed from the ``conda-forge`` repository
        using `Conda <https://docs.conda.io/en/latest/>`__:
        
        .. code-block:: console
        
            $ conda install -c conda-forge pydaymet
        
        Quick start
        -----------
        
        PyDaymet offers two functions for getting climate data; ``get_bycoords`` and ``get_bygeom``.
        The arguments of these functions are identical except the first argument where the latter
        should be polygon and the former should be a coordinate (a tuple of length two as in (x, y)).
        The input geometry or coordinate can be in any valid CRS (defaults to EPSG:4326). The ``dates``
        argument can be either a tuple of length two like ``(start_str, end_str)`` or a list of years
        like ``[2000, 2005]``. It is noted that both functions have a ``pet`` flag for computing PET.
        Additionally, we can pass ``time_scale`` to get daily, monthly or annual summaries. This flag
        by default is set to daily.
        
        .. code-block:: python
        
            from pynhd import NLDI
            import pydaymet as daymet
        
            geometry = NLDI().get_basins("01031500").geometry[0]
        
            var = ["prcp", "tmin"]
            dates = ("2000-01-01", "2000-06-30")
        
            daily = daymet.get_bygeom(geometry, dates, variables=var, pet=True)
            monthly = daymet.get_bygeom(geometry, dates, variables=var, time_scale="monthly")
        
        .. image:: https://raw.githubusercontent.com/cheginit/HyRiver-examples/main/notebooks/_static/daymet_grid.png
            :target: https://github.com/cheginit/HyRiver-examples/blob/main/notebooks/daymet.ipynb
            :width: 400
        
        If the input geometry (or coordinate) is in a CRS other than EPSG:4326, we should pass
        it to the functions.
        
        .. code-block:: python
        
            coords = (-1431147.7928, 318483.4618)
            crs = "epsg:3542"
            dates = ("2000-01-01", "2006-12-31")
            annual = daymet.get_bycoords(
                coords, dates, variables=var, loc_crs=crs, time_scale="annual"
            )
        
        .. image:: https://raw.githubusercontent.com/cheginit/HyRiver-examples/main/notebooks/_static/daymet_loc.png
            :target: https://github.com/cheginit/HyRiver-examples/blob/main/notebooks/daymet.ipynb
            :width: 400
        
        Next, let's get annual total precipitation for Hawaii and Puerto Rico for 2010.
        
        .. code-block:: python
        
            hi_ext = (-160.3055, 17.9539, -154.7715, 23.5186)
            pr_ext = (-67.9927, 16.8443, -64.1195, 19.9381)
            hi = daymet.get_bygeom(hi_ext, 2010, variables="prcp", region="hi", time_scale="annual")
            pr = daymet.get_bygeom(pr_ext, 2010, variables="prcp", region="pr", time_scale="annual")
        
        Some example plots are shown below:
        
        .. image:: https://raw.githubusercontent.com/cheginit/HyRiver-examples/main/notebooks/_static/hi.png
            :target: https://github.com/cheginit/HyRiver-examples/blob/main/notebooks/daymet.ipynb
            :width: 400
        
        .. image:: https://raw.githubusercontent.com/cheginit/HyRiver-examples/main/notebooks/_static/pr.png
            :target: https://github.com/cheginit/HyRiver-examples/blob/main/notebooks/daymet.ipynb
            :width: 400
        
        Contributing
        ------------
        
        Contributions are very welcomed. Please read
        `CONTRIBUTING.rst <https://github.com/cheginit/pygeoogc/blob/main/CONTRIBUTING.rst>`__
        file for instructions.
        
        Credits
        -------
        Credits to `Koen Hufkens <https://github.com/khufkens>`__ for his implementation of
        accessing the Daymet RESTful service, `daymetpy <https://github.com/bluegreen-labs/daymetpy>`__.
        
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: test
