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mapmate

mapmate (map animate) is an R package for map animation. It is used to generate and save a sequence of plots to disk as a still image sequence intended for later use in data animation production.

Here is the complete online documentation and tutorials with code examples.

Installation and bug reporting

You can install snapverse from github with:

# install.packages('devtools')
devtools::install_github("leonawicz/mapmate")

Please file a minimal reproducible example of any clear bug at github.

Introduction and basic example

The mapmate package is used for map- and globe-based data animation pre-production. Specifically, mapmate functions are used to generate and save to disk a series of map graphics that make up a still image sequence, which can then be used in video editing and rendering software of the user's choice. This package does not make simple animations directly within R, which can be done with packages like animation. mapmate is more specific to maps, hence the name, and particularly suited to 3D globe plots of the Earth. Functionality and fine-grain user control of inputs and outputs are limited in the current package version.

library(mapmate)
library(dplyr)
data(annualtemps)
annualtemps
#> # A tibble: 55,080 x 4
#>          lon      lat  Year     z
#>        <dbl>    <dbl> <int> <dbl>
#>  1 -176.6667 53.66633  2010  1.09
#>  2 -176.6667 66.99967  2010  3.21
#>  3 -176.6667 73.66633  2010  2.76
#>  4 -170.0000 53.66633  2010  0.91
#>  5 -170.0000 60.33300  2010  2.47
#>  6 -170.0000 66.99967  2010  2.73
#>  7 -163.3333 20.33300  2010  0.19
#>  8 -163.3333 53.66633  2010  0.79
#>  9 -163.3333 60.33300  2010  1.43
#> 10 -163.3333 66.99967  2010  1.28
#> # ... with 55,070 more rows

library(RColorBrewer)
pal <- rev(brewer.pal(11, "RdYlBu"))

temps <- mutate(annualtemps, frameID = Year - min(Year) + 1)
frame1 <- filter(temps, frameID == 1)  # subset to first frame
id <- "frameID"

save_map(frame1, z.name = "z", id = id, ortho = FALSE, col = pal, type = "maptiles", 
    save.plot = FALSE, return.plot = TRUE)
save_map(frame1, z.name = "z", id = id, col = pal, type = "maptiles", save.plot = FALSE, 
    return.plot = TRUE)

The above is only a very basic initial example of static 2D and 3D maps. See the introduction vignette for more complete and typical usage examples:

  • Generate a data frame containing monthly map data (optionally seasonal or annual aggregate average data) in the form of an n-year moving or rolling average based on an input data frame of raw monthly data.
  • Generate a sequence of still frames of:
    • map data for use in a flat map animation.
    • dynamic/temporally changing map data projected onto a static globe (3D Earth)
    • static map data projected onto rotating globe
    • dynamic map data projected onto rotating globe
  • Parallel processing examples using mclapply
  • Convenient iterator wrapper function
  • Comparison of map tiles, map lines, and polygons
  • Non-map data example (time series line growth)

This and other vignettes covering more examples, including network maps with great circle arcs and generating video with ffmpeg, can be found at the mapmate website.

Other features and functionality will be added in future package versions.

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Version

Version

0.3.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Last Published

May 6th, 2018

Functions in mapmate (0.3.1)

borders

Global national political borders
do_projection

Project points onto globe
gc_endpoints

Generate a table of location pair samples
gc_paths

Generate a table of incremental great circle arc segments
runOrtho

Run Shiny app example
save_map

Save maps to disk
annualtemps

2010-2099 global projected annual average temperature anomalies
bathymetry

Spatially aggregated example global bathymetry surface
get_lonlat_seq

Generate a sequence of coordinates
get_ma

Obtain moving average map series
save_seq

Save a sequence of still images to disk
save_ts

Save time series plots
ffmpeg

Make video from still image sequence
gc_arcs

Generate a table of great circle arcs
monthlytemps

2010-2099 single map grid cell projected monthly average temperatures anomalies
network

Simulated set of world cities locations and population-based weights
pad_frames

Pad the end of list of data frames
project_to_hemisphere

Identidy visible points on an arbitrary global hemishpere view.