Package license: GPL (>= 2)
Feedstock license: BSD 3-Clause
Summary: For curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get started and for an overview. The fields source code is deliberately commented and provides useful explanations of numerical details as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI doi:10.5065/D6W957CT.
Current build status
Current release info
r-fields from the
conda-forge channel can be achieved by adding
conda-forge to your channels with:
conda config --add channels conda-forge
conda-forge channel has been enabled,
r-fields can be installed with:
conda install r-fields
It is possible to list all of the versions of
r-fields available on your platform with:
conda search r-fields --channel conda-forge
conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.
A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by CircleCI, AppVeyor and TravisCI it is possible to build and upload installable packages to the conda-forge Anaconda-Cloud channel for Linux, Windows and OSX respectively.
To manage the continuous integration and simplify feedstock maintenance
conda-smithy has been developed.
conda-forge.yml within this repository, it is possible to re-render all of
this feedstock's supporting files (e.g. the CI configuration files) with
conda smithy rerender.
For more information please check the conda-forge documentation.
feedstock - the conda recipe (raw material), supporting scripts and CI configuration.
conda-smithy - the tool which helps orchestrate the feedstock.
Its primary use is in the construction of the CI
and simplify the management of many feedstocks.
conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)
If you would like to improve the r-fields recipe or build a new
package version, please fork this repository and submit a PR. Upon submission,
your changes will be run on the appropriate platforms to give the reviewer an
opportunity to confirm that the changes result in a successful build. Once
merged, the recipe will be re-built and uploaded automatically to the
conda-forge channel, whereupon the built conda packages will be available for
everybody to install and use from the
Note that all branches in the conda-forge/r-fields-feedstock are
immediately built and any created packages are uploaded, so PRs should be based
on branches in forks and branches in the main repository should only be used to
build distinct package versions.
In order to produce a uniquely identifiable distribution: