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grib2io-interp: Interpolation Component Package for grib2io

License: MIT

Python 3.8 Python 3.9 Python 3.10 Python 3.11

Build Linux

PyPI PyPI - Downloads

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Introduction

grib2io-interp is an interpolation component package for grib2io. This package provides a Python interface to the NCEPLIBS-ip Fortran library via a NumPy/F2PY extension module. Originally, grib2io-interp was a part of the grib2io package, but since it requires NumPy.distutils to build and install, it needs to be handled separately from the main grib2io source that are using setuptools. This package contains an extension module, interpolate, that provides interfaces to Fortran subroutines and these subroutines serve as wrappers to NCEPLIBS-ip subroutines. The following table illustrates the mapping:

grib2io-interp NCEPLIBS-ip
interpolate.interpolate_scalar ipolates_grib2
interpolate.interpolate_vector ipolatev_grib2

Important

It is recommended that you use grib2io.interpolate function to access the interpolation subroutines provided by grib2io-interp.

Documentation

NOAA-MDL/grib2io-interp

Required Software

Despite this package being a component for grib2io, grib2io is not a formal dependency for grib2io-interp.

  • Python 3.8, 3.9, 3.10, and 3.11
  • NCEPLIBS-ip 4.1.0+
  • NCEPLIBS-sp 2.5.0+ (IMPORTANT: required if NCEPLIBS-ip < v5.0.0)
  • setuptools 61.0+
  • NumPy 1.22+ (NumPy v2.x not supported at this time)
  • Fortran Compiler: GNU (gfortran) and Intel (ifort) have been tested.

NCEPLIBS-ip

Note

Beginning with NCEPLIBS-ip v5.0.0, the NCEP Spectral Interpolation (NCEPLIBS-sp) library is now integrated into NCEPLIBS-ip.

Note

Beginning with NCEPLIBS-ip v5.1.0, you can now interpolate from Rotated Lat/Lon Arakawa B and E Grids (Grid Definition Template numbers 32768 and 32769).

Installation

pip

If NCEPLIBS-ip has been installed to custom location (i.e. not default paths), then define the root of the installation via environment variable IP_DIR. If the NCEPLIBS-ip version is < 5.0.0, then you will need to install NCEPLIBS-sp and if installed to a custom location, then define the root of the installation via environment variable SP_DIR.

pip install grib2io-interp

Important

If the above pip install command fails, try the following:

SETUPTOOLS_USE_DISTUTILS=stdlib pip install grib2io-interp

conda

All required libraries are available in conda-forge.

conda install -c conda-forge grib2io-interp

Build and Install from Source

  • Clone GitHub repository or download a source release from GitHub or PyPI.

  • Edit setup.cfg to define the NCEPLIBS-ip library installation path OR define IP_DIR environment variable.

  • Build and install. Use --user to install into personal space ($HOME/.local).

pip install .

To build with Intel compilers, perform the following

pip install . --config-settings="--build-option=build --fcompiler=intelem"

Note

Building with static libraries

The default behavior for building grib2io-interp is to build against shared-object libraries. However, in production environments, it is beneficial to build against static library files. grib2io-interp (v1.2.0+) allows for this type of build configuration. To build against static library files, set the environment variable, USE_STATIC_LIBS="True" before your build/install command. For example,

export USE_STATIC_LIBS="True"
pip install . --config-settings="--build-option=build ==fcompiler=gnu95"

Development

The development evolution of grib2io-interp will mainly focus on how best to serve that purpose and its primary user's -- mainly meteorologists, physical scientists, and software developers supporting the missions within NOAA's National Weather Service (NWS) and National Centers for Environmental Prediction (NCEP), and other NOAA organizations.

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an 'as is' basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.