Heat maps are commonly used to display the spatial distribution of a response observed on a two-dimensional grid. The autoimage package provides convenient functions for constructing multiple heat maps in unified, seamless way, particularly when working with projected coordinates. The autoimage package natively supports: 1. automatic inclusion of a color scale with the plotted image, 2. construction of heat maps for responses observed on regular or irregular grids, as well as non-gridded data, 3. construction of a matrix of heat maps with a common color scale, 4. construction of a matrix of heat maps with individual color scales, 5. projecting coordinates before plotting, 6. easily adding geographic borders, points, and other features to the heat maps. After comparing the autoimage package’s capabilities for constructing heat maps to those of existing tools, a carefully selected set of examples is used to highlight the capabilities of the autoimage package.
autoimage, fields, lattice, sp, ggplot2, spatstat, gridExtra, cowplot, akima, mapproj, gear, viridisLite, maps
Spatial, Graphics, SpatioTemporal, Multivariate, NumericalMathematics, Phylogenetics, Survival
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For attribution, please cite this work as
French, "The R Journal: autoimage: Multiple Heat Maps for Projected Coordinates", The R Journal, 2017
BibTeX citation
@article{RJ-2017-025,
author = {French, Joshua P.},
title = {The R Journal: autoimage: Multiple Heat Maps for Projected Coordinates},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2017-025},
doi = {10.32614/RJ-2017-025},
volume = {9},
issue = {1},
issn = {2073-4859},
pages = {284-297}
}