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A framework for meteorological data in R

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harp

A framework for meteorological data in R

{harp} is a meta-package that attaches functionality from the {harpIO}, {harpPoint}, {harpVis} and {harpSpatial} packages to your session.

Installation

if (!require("remotes")) {
  install.packages("remotes")
}
remotes::install_github("harphub/harp")

System libraries

harp packages use the {meteogrid} package for interpolation and the geogrid class for storing gridded data. This package makes use of the PROJ library for handling projections. If you do not have PROJ installed you can install with:

sudo apt-get install libproj-dev

If you do not have sudo rights, try installing a user local version, or speak to your system administrator.

If you have the PROJ libraries installed in a standard location (e.g. /usr/local) {meteogrid} will install without problems. However, if the PROJ libraries are in a non standard location, you need to tell the install function where they are:

remotes::install_github(
  "harphub/harp",
  configure.args = c(
    meteogrid = "--with-proj=/path/to/proj"
  )
)

Alternatively you can set environment variables

export PROJ4_DIR=/path/to/proj

If you include these environment variables in your .bashrc file, or equivalent, you won’t need to worry about it when you wish to install an update to meteogrid.

Or you can set compiler and linker options in the file $HOME/.R/Makevars

CPPFLAGS=-I/path/to/proj/include
LDFLAGS=-L/path/to/proj/lib -Wl,-rpath,/path/to/proj/lib

In this case you only have to set them once and not worry about it when you wish to install an update to {meteogrid}.

When setting environment variables or creating a Makevars file, R must be restarted for the changes to take effect before running remotes::install_github("harphub/harp").

Learning harp

Currently the best learning resource for getting started with harp is the 2022 training course website that includes a number of worked examples. There are plans to make an online book available in 2024 that will go into harp’s functionalities in more detail.

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A framework for meteorological data in R

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