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Please edit that file --\u003e\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$set(collapse = TRUE, comment = \"#\u003e\", warning = FALSE,\n  fig.path = \"man/figures/README-\", fig.height = 8, fig.width = 8, dpi = 300, out.width = \"100%\")\n\n```\n\n# SOmap \u003cimg src=\"man/figures/logo.png\" align=\"right\" /\u003e\n\nThe goal of SOmap is to make publication quality round Southern Ocean maps in polar projections with little effort. This package is still very much a work in progress contact me with any questions or suggestions.\n\n## Installation\nThe development version from [GitHub](https://github.com/AustralianAntarcticDivision/SOmap) with:\n\n```{r eval = FALSE}\ninstall.packages(\"SOmap\", repos = c(SCAR = \"https://scar.r-universe.dev\",\n                                    CRAN = \"https://cloud.r-project.org\"))\n\n## or\n\n## install.packages(\"remotes\") ## if needed\nremotes::install_github(\"AustralianAntarcticDivision/SOmap\")\n\n```\n## Example\n\nTo make a simple map you can use the following function; use `? SOmap` to see all the options for modifying layers.\n\n\n```{r examplemap, message = FALSE, warning = FALSE}\nlibrary(SOmap)\nSOmap()\n```\n\nThere is also `SOmanagement()` which provides management layers for the Southern Ocean and `SOleg()` which gives custom rounded legends for added map layers.\n\n\n```{r management}\n## custom colours\nspiritedMedium \u003c- colorRampPalette(c(\"#4D4140\", \"#596F7E\", \"#168B98\",\n                                     \"#ED5B67\", \"#E27766\", \"#DAAD50\", \"#EAC3A6\"))\nspirited \u003c- spiritedMedium(80)\n\nSOmap(trim = -40)\n## add an example sea ice raster, which is bundled with SOmap\nplot(ice, col = spirited, add = TRUE, legend = FALSE, alpha = 0.95)\nSOleg(ice, position = \"topright\", col = spirited, ticks = 6,\n      tlabs = c(\"0\", \"20\", \"40\", \"60\", \"80\", \"100\"),\n      trim = -40, label = \"Sea Ice\", type = \"continuous\")\n\n## add the exclusive economic zones management layer\nSOmanagement(eez = TRUE)\n```\n\nCurved legends can be either continuous (as above) or discrete. \n```{r, echo=FALSE}\ncentroids\u003c-data.frame(pop = structure(1:8, .Label = c(\"1\", \"2\", \"3\",\"4\", \"5\", \"6\", \"7\", \"8\"), class = \"factor\"), lon = c(7.36921794861538, 76.0083253690476, 88.1945661849315, 134.966444407778,  -178.009759,-164.882487618519, -80.8082988510345, -30.1700251934884), lat = c(-63.6191794892308,-53.1358253619048, -65.0577956330822, -65.0150925555556, -72.891637562451, -63.3747530640741, -68.9245057482759, -60.3177015502326))\n\ncoordinates(centroids)\u003c-c(\"lon\", \"lat\")\nprojection(centroids)\u003c- \"+proj=longlat +datum=WGS84\"\ncentroids\u003c-spTransform(centroids,CRS(projection(SOmap::Bathy)))\n```\n\n\n\n```{r SOleg}\nspirited8 \u003c- spiritedMedium(8)\n\nSOmap()\nplot(centroids, col=spirited8, add=TRUE, pch=19)\nSOleg(centroids,position = \"topright\", col = spirited8, ticks = 8,\n      tlabs =1:8, label = \"Centroids\", type = \"discrete\")\n\n```\n\n\nAn **automatic** plot function `SOmap_auto()` will take any data in the form of longitude and latitude vectors and create a guess at a map.\n\n```{r automap, fig.height = 5, fig.width = 5}\nellie \u003c- SOmap_data$mirounga_leonina\n\n## construct and plot the map\nSOmap_auto(ellie$lon, ellie$lat)\n```\n\nThe `SOmap_auto()`, `SOmap()`, and `SOmap2()` functions return the data used to make the map so that further customization can be made. Plotting or printing the returned object will cause the map to be displayed in the graphics device.\n\n```{r automap2, fig.height = 5, fig.width = 5} \ndata(\"albatross\", package = \"adehabitatLT\")\n## convert the albatross data to a single matrix of lon, lat points\nalbatrack \u003c- do.call(rbind, lapply(albatross, function(z) terra::project(rbind(as.matrix(z[, c(\"x\", \"y\")]), NA), from  = \"+proj=utm +zone=42 +south +datum=WGS84\", to = \"EPSG:4326\")))\n\n## construct the map and return it, but don't plot it\nalb_map \u003c- SOmap_auto(albatrack[, 1], albatrack[, 2])\n\n```\n\nModifying this map object is currently a rather experimental process (proceed at your own risk!) but, for example, if we wished to change the points to be blue rather than red:\n\n```{r automap3, fig.height = 5, fig.width = 5}\nalb_map$pcol \u003c- \"blue\"\n## plot it\nalb_map\n```\n\nWe could also decide we want a reversed bathymetry color and cyan lines between the dots. \n\n```{r automap4, fig.height = 5, fig.width = 5}\n# change the line color \nalb_map$lcol \u003c- \"cyan\"\n# reverse the bathymetry\nalb_map$bathy_palette\u003c-rev(alb_map$bathy_palette)\n\n## plot it\nalb_map\n```\n\n\nObjects from `sf`, `sp`, or `raster` can also be used, but note that they will be used for their extents only and will not automatically be plotted. But we can plot them easily with `SOplot`:\n\n```{r automap-spatial, fig.height = 5, fig.width = 5}\n## use the bundled fronts data as an example\nmydata \u003c- SOmap_data$fronts_orsi\nSOmap_auto(mydata, target = \"laea\", centre_lon = 147)\nSOplot(mydata, col = 2)\n\n```\n\n## Easy projections\n\n`SOmap` goes with the philosophy \"we actually rather like ourselves, and care about our experience\" and so there are some easy ways to work with projections, and \u003cquote\u003ejust map it!\u003c/quote\u003e. \n\n```{r auto-setup}\nset.seed(1)\namap \u003c- SOmap_auto(input_points = FALSE, input_lines = FALSE)\namap\n```\n\nTo add data to this plot we can just do so. \n\n```{r just-map-it}\namap\nSOplot(SOmap_data$seaice_oct, lwd = 3, col = \"blue\", lty = 2)\n```\n\n`SOplot()` will add data by default, and can take spatial objects or even raw longitude and latitude values (we like you). 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