R/wmappoints.R
In RebeccaStubbs/woodson: Woodson Mapping Suite
#' Map Plotting Utility for Gridded Data
#'
#' @description Simplified plotting utilitity for evenly spaced points (raster data)
#'
#' @param geometry A data table with an x and a y column, as well as a geographic id.
#' @param xcol String; the name of the column that is the x values for the grid
#' @param ycol String; the name of the column that is the y values for the grid
#' @param geog_id string; the column name for the unique geogrpahic ID
#' @param variable string; the column with values you wich to plot
#' @param sizevar The variable you intend to use to scale the size ofthe points.
#' @param outline_map Another SpatialPolygons object that you want to use the
#' outlines from. Make sure your outline map and main map have the same projection.
#' @param data A data.table that contains the data you want to map
#' (must contain geog_id, and the variable of interest, if specified.
#' If a series dimension and/or series sequence is defined,
#' those must also exist in this data set)
#' @param transparency default=1, (totally opaque).
#' @param sizerange default c(0,5), the range of sizes your points can be if you
#' use the sizevar argument.
#' @param sizetitle Default "" no title. The legend title for your size legend.
#' @param pointsize Default=1. If no size variable is defined, you can define
#' a point size.
#' @param pointsize default=16, a solid filled dot. Only use symbols that have fill.
#' @param histogram logical; the plot will contain a histogram of the values
#' @param hist_color If a character string for a color (or colors) are entered
#' (ex:"grey"), the histogram will be that color rather than the color ramp
#' used for the main map.
#' @param dist_stats Vertical lines on the histogram plot showing summary
#' statistics. To show this, provide a vector of numeric values (between 0
#' and 1) to serve as quantiles, and the options "mean" and "sd" can also be
#' included. example: c("mean","sd",.1,.5,.9). Default=NULL.
#' @param mean_color The color of lines you want to represent mean and standard
#' deviation statistics, only relevant if dist_stats!=NULL. Default="red".
#' @param quantile_color The color of lines you want to represent the median and
#' quantile lines on the histogram, only relevant if dist_stats!=NULL.
#' @param return_map_object_only you can assign the function to a variable, and
#' store the map plot portion of this ggplot object so that you can combine
#' it with other graphics at will. This will never return the histogram.
#' @param destination_folder A string file path to a folder you want a PDF
#' created in that will hold your map(s)
#' @param color_ramp A list of colors that will serve as the colors you
#' "stretch" through based on your data values. This will default to a color
#' scheme described in woodson pallettes called "Easter to Earth" that
#' displays variation well when there are many geographic units. See woodson
#' palletes for more options, or create your own.
#' @param outline_size A numeric value that specifies how large you want your
#' white outlines to be if you have specified an outline you want shown on
#' your map. Default value is .1.
#' @param outline_color What color you want the outline of the additional
#' geography to be (if provided). This can be any color r recognizes
#' suggestions might be "black","yellow", or "white". Default is white.
#' @param override_scale Values that will be used to stretch the color ramp
#' instead of the min/max values present in the entire data set. Should
#' either be structured "c(min,max)", with numeric values, or be
#' "each_dimension", which will create a map series where each individual map
#' in a series will based on the min/max from that subset of data.
#' @param override_size_scale Values that will be used to stretch the size ramp
#' instead of the min/max values present in the entire data set. Should
#' either be structured "c(min,max)", with numeric values, or be
#' "each_dimension", which will create a map series where each individual map
#' in a series will based on the min/max from that subset of data.
#' @param color_value_breaks How you want the colors "stretched" across the
#' range of minimum/maximum values. Default is NULL/ uniform distribution
#' stretched across the color ramp from the minimum and maximum data values
#' provided. Vector must begin with 0 and end with 1.
#' @param diverging_centerpoint Accepts any numeric value between the minimum
#' and maximum of your data set. Sets the center of your color scheme to the
#' value defined. This is meant to be used with diverging color schemes. It
#' will override any previously defined color_value_breaks. Default=NULL.
#' @param map_title A string that serves as the basis for your map title (if no
#' dimensions are specified, the title will be as it is specified. If a
#' dimension is specified, a phrase constructed using the series dimension
#' and what you are mapping will be added to the plot title [ex="year:1990"].
#' @param additional_variable_name_string This is an additonal string that you
#' want to add to the name of the PDF to describe any other breakdowns you
#' might be using. For example, if you had to map something by year, age,
#' sex, you would first need to subset your data to be one age/sex group
#' before plotting it out by year. If you subset your data in a loop, you
#' could use this string to specify something along the lines of
#' paste0("age_ ",a," _ sex _",s).
#' @param fontfamily The name of the font family you want to use for the text
#' on the plot. Default is 'serif'.
#' @param fontsize The base/minimum size of the text on your graphic.
#' Default is NULL.
#' @param title_justification Where ("left","center",or "right) you want the title
#' and subtitle. Default is "center".
#' @param title_font_size How large you want the title font to be. No default;
#' default values based on ggthemes tufte()'s default.
#' @param title_font_face Special properties of the title font.
#' Options include "plain", "bold", "italic". Default is plain.
#' @param series_dimension A string-- the name of the column that will serve as
#' the variable you loop through to create a series map. For example, year.
#' @param series_sequence A vector c(x,y,z...) that specifies a subset of the
#' series dimensions you want to map. For example, if you have a data set
#' that contains all years between 1980-2014, you can specify that you only
#' want to plot out every other year by setting series sequence to be
#' seq(1980,2014,2). This function will make sure all of the items you
#' speficy actually exist within your series_dimension.
#' @param legend_name Title above the legend. Default is NULL.
#' @param legend_position Where you want the legend to go. Options are
#' "top","bottom","right","left", and "none". Default is "bottom".
#' @param legend_font_size How large you want the legend font to be.
#' No default; default values based on ggthemes tufte()'s default.
#' @param legend_font_face Special properties of the legend font. Options
#' include "plain", "bold", "italic". Default is plain.
#' @param legend_bar_width How fat you want the color bar that serves as the
#' legend to be. Default value is 0.4.
#' @param legend_bar_length How long you want the color bar that serves as the
#' legend to be. Default value is 20.
#' @param legend_breaks An optional vector of the values you want to label in
#' your legend's color scale.
#' @param legend_labels An optional vector of the character strings you want to
#' use to label your legend's color scale (must be same length as
#' legend_breaks)
#' @param scramble_colors Logical; Scrambles the input color ramp's values.
#' useful for categorical data.
#' @param patch_width width of color swatches in legend when categorical data
#' is used. Default is .25.
#' @param patch_height height of color swatches in legend when categorical data
#' is used. Default is .25.
#' @param label_position Position of category labels in legend when categorical
#' data is used. Default= "right".
#' @param verbose logical; Whether you want print statements from the function
#' scramble_colors=FALSE,
#'
#' @return ggplot object or None (plots written to pdf)
#'
#' @examples see https://rpubs.com/BeccaStubbs/introduction_to_woodson_mapping_suite
#'
#' @export
wmappoints<-function(geometry,
xcol,
ycol,
geog_id,
variable,
# Optional data/geometry
outline_map=NULL, #
data=NULL,
sizevar=NULL,
# Point-based options
transparency=1,
sizerange=c(0,5),
sizetitle="",
pointsize=1,
pointsymbol=16, # a solid filled dot
# What elements of the map do you want the function to return?
histogram=FALSE,
hist_color=NULL,
dist_stats=NULL,
mean_color="red",
quantile_color="black",
return_map_object_only=FALSE,
destination_folder=NULL,
# Inputs for the color scheme of the maps
color_ramp=wpal("easter_to_earth"),
outline_size=.1,
outline_color="white",
override_scale=NULL,
override_size_scale=NULL,
color_value_breaks=NULL,
diverging_centerpoint=NULL,
# Inputs for text
map_title=" ",
map_subtitle=NULL,
title_justification="center",
additional_variable_name_string=NULL,
title_font_size=NULL,
title_font_face="plain",
# Fonts
fontfamily="serif",
fontsize=12,
# Inputs for generating series-maps
series_dimension=NULL,
series_sequence=NULL,
# Inputs for map Legend
legend_name=NULL,
legend_position="bottom",
legend_font_size=NULL,
legend_font_face="plain",
# Inputs for numeric data only
legend_bar_width=.4,
legend_bar_length=20,
legend_breaks=NULL,
legend_labels=NULL,
# Inputs for categorical data only
scramble_colors=FALSE,
label_position="right",
# Do you want print statements?
verbose=F){
# Copying objects such that the original data sets are unaltered
data_is_null<-is.null(data)
geometry<-copy(geometry)
setnames(geometry,xcol,"lon"); setnames(geometry,ycol,"lat")
outline_map<-copy(outline_map)
data<-copy(data)
if(variable==geog_id){stop("Your variable and geog_id are the same.")}
if(!is.null(sizevar)){
if(variable==sizevar){stop("Your variable and size-variable are the same.")}
if(geog_id==sizevar){stop("Your geog_id and size-variable are the same.")}
}
#print("aftererror")
# Getting the data object ready to join to the fortified spatial object (either from the chloropleth map's data.table, or from an external data.table)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Check to make sure the geog_id specified is within the chloropleth map's data table
if(!(geog_id %in% names(geometry))) stop("That geographic ID does not appear to exist within your chloropleth map object.")
setnames(geometry,geog_id,"geog_id")
# If External Data is Specified
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if (!is.null(data)){
# Check that the geog_id is within the external data set, rename it to "geog_id"
if(!(geog_id %in% names(data))) stop("That geographic ID does not appear to exist within your data set.")
setnames(data,geog_id,"geog_id")
# Check thta the variable name exists in either the data set or the geometry
if( (!variable %in% names(data)) & (!variable %in% names(geometry)) ) stop(paste0("That variable, ",variable," does not appear to exist within your data set or geometry."))
# Check that it doesn't exist in BOTh the data set and the geometry
if( (variable %in% names(data)) & (variable %in% names(geometry))) stop("The variable you defined for color exists in both your geometry and the additoinal data set.")
# Check that the variable name exists in either the data or the geometry
if ( (!variable %in% names(data)) & (!variable %in% names(geometry)) ) stop("The variable you defined as the size of the points does not appear to exist within your data set.")
if (variable %in% names(geometry)) setnames(geometry,variable,"variable")
if (variable %in% names(data)) setnames(data,variable,"variable")
# If a size variable is defined...
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if(!is.null(sizevar)){
# Check that it doesn't exist in BOTH the data and the geometry
if( (sizevar %in% names(data)) & (sizevar %in% names(geometry))) stop("The variable you defined for size exists in both your geometry and the additoinal data set.")
# rename it in either the data or the geometry
if(sizevar %in% names(data)) {
if(!is.numeric(data[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(data,sizevar,"sizevar")
}
if(sizevar %in% names(geometry)){
if(!is.numeric(geometry[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(geometry,sizevar,"sizevar")
}
}
}else{ # If external data is NOT specified
if(!is.null(sizevar)){
if(!sizevar %in% names(geometry)) stop(paste0("You haven't provided an additional data set, and it looks like your size variable, ",sizevar," doesn't exist in your geometry object."))
if(!is.numeric(geometry[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(geometry,sizevar,"sizevar")
}
data<-copy(geometry)
if(!(variable %in% names(data))) stop(paste0("That variable, ",variable," does not appear to exist in the data attributes of your spatial object."))
setnames(data,variable,"variable")
}
# checking whether the data is a factor/ordered: this will make it be mapped with a discrete scale.
if (is.factor(data[["variable"]])|is.ordered(data[["variable"]])){discrete_scale<-TRUE}else{discrete_scale<-FALSE}
if (is.character(data[["variable"]])){
print("Character data being converted to a factor. If you'd like a specific order to your levels, please transform your variable into a factor or ordered data type with appropriate ordering. ")
data[,variable:=as.factor(variable)]
discrete_scale<-TRUE}
if(discrete_scale&histogram){histogram<-F; print("Sorry, histogram/bar graph functionality is not yet supported in this version of the mapping suite for categorical data. No histogram will be printed.")}
# Making sure that there are the right number of colors in the color ramp, by sampling and then scrambling (optional)
# the color pallette chosen.
pallette<-colorRampPalette(color_ramp)
color_list<-pallette(nlevels(data[["variable"]]))
if(scramble_colors==T){
color_list<-color_list[sample(1:length(color_list))]
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Defining "map dims"; the levels of the series dimension you want to map
# First, discovering or defining the "series dimension"
if (!is.null(series_dimension)){ # If you plan to loop through miltiple dimensions...
if(!(series_dimension %in% names(data))) stop("That series dimension (what you want to iterate through) does not appear to exist within your data set.")
setnames(data,series_dimension,"series_dimension")
}else{
data[,series_dimension:="*&^! no dimensions"]
}
# Restricting the mapping to only *some* levels of that dimension, if desired
if (is.null(series_sequence)){
map_dims<-unique(data$series_dimension)
}else{
for (select_dimension in series_sequence){
if(!(select_dimension %in% unique(data$series_dimension))) stop(paste0("The dimension ",select_dimension," does not appear to exist in the column you have specified to hold your dimensions."))
}
map_dims<-series_sequence
}
# determining the "hjust" of the title
if(title_justification=="left"){title_justification<-0}
if(title_justification=="center"){title_justification<-.5}
if(title_justification=="right"){title_justification<-1}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Fortifying the Map(s) and Joining on the Data
# "fortifying" the Rdata shapefiles
if (!is.null(outline_map)){outline_map<-data.table(suppressWarnings(fortify(outline_map)))} # If an outline map is specified, fortify the outline map as well.
# creating one long, huge object that you can subset by merging together the data and the forfified geometry
if(data_is_null==F){ # if there is extra data provided, merge it on, then sub-select down.
orig_rows<-nrow(geometry)
data<-merge(data, geometry, by="geog_id", allow.cartesian=T)
after_rows<-nrow(data)
if(orig_rows<after_rows&is.null(series_dimension))print("You are mapping more than one data observation per geometry, and you have not specified a series dimension to map over. Did you intend to subset your data further before passing it to this funciton?")
}
if(!is.null(sizevar)){
data<-data[, list(geog_id=as.character(geog_id), variable, lon, lat, series_dimension, sizevar)]
}else{
data<-data[, list(geog_id=as.character(geog_id), variable, lon, lat, series_dimension)]
}
###########################################
## LOOPING ACROSS DIMENSIONS
###########################################
# Starting a PDF, if desired
if (!is.null(destination_folder)){pdf(paste0(destination_folder,variable,additional_variable_name_string,".pdf"))}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Starting the Loop
for (select_dimension in map_dims){ #for each dimension you want to plot...
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Determining map title
main_map_title<-map_title
if(verbose) print(main_map_title)
# Determining map subtitle
if (select_dimension=="*&^! no dimensions"){
main_map_subtitle<-map_subtitle
}else{
main_map_subtitle<-paste0(map_subtitle," ",select_dimension)}
if(verbose) print(main_map_subtitle)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Subsetting the Data
subset<-copy(data[series_dimension==select_dimension]) # Sub-setting the fortified object to map out 1 layer/dimension (ex: year) of the variable of interest
#####################
# If Data is Numeric
#####################
if(discrete_scale==F){ # If the data is numeric...
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Defining Boundaries and Properties of the Color Ramp
# If an override was provided, setting minimum to the first in the list, and maximum to the second in the list provided.
if (!is.null(override_scale)){
if(is.numeric(override_scale)){
minimum<-override_scale[1]
maximum<-override_scale[2]
}else{
if(override_scale=="each_dimension"){
maximum<-max(subset[["variable"]])
minimum<-min(subset[["variable"]])
}else{stop("Any character input other than 'each_dimension', which will produce a color ramp from the min/max of each dimension, is not recognized.")}
}
}else{ #Otherwise, set the min/max of the scale to the min/max of ALL dimensions of the variable.
maximum<-max(data[["variable"]])
minimum<-min(data[["variable"]])
}
if(!is.null(sizevar)){
if (!is.null(override_size_scale)){
if(is.numeric(override_size_scale)){
sizeminimum<-override_size_scale[1]
sizemaximum<-override_size_scale[2]
}else{
if(override_size_scale=="each_dimension"){
sizemaximum<-max(subset[["sizevar"]])
sizeminimum<-min(subset[["sizevar"]])
}else{stop("Any character input other than 'each_dimension', which will produce a color ramp from the min/max of each dimension, is not recognized.")}
}
}else{ #Otherwise, set the min/max of the scale to the min/max of ALL dimensions of the variable.
sizemaximum<-max(data[["sizevar"]])
sizeminimum<-min(data[["sizevar"]])
}
}
# Determining the diverging centerpoint in relation to the min/max, if desired
if(!is.null(diverging_centerpoint)){
if(diverging_centerpoint>maximum){stop("The diverging centerpoint provided is greater than the maximum value in the data set.")}
if(diverging_centerpoint<minimum){stop("The diverging centerpoint provided is less than the minimum value in the data set.")}
# Finding what where the specified break point is as a fraction of the total color range
value_range<-maximum-minimum
difference_from_minimum<-diverging_centerpoint-minimum
break_value<-difference_from_minimum/value_range
color_value_breaks<-c(0,break_value,1)
if(verbose) print(paste0("Centering color ramp at ",diverging_centerpoint,". Any other color breaks provided have been overridden."))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Creating the Map Plot in GGPlot2
if(!is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=subset,aes(x=lon, y=lat, color=variable,size=sizevar),alpha=transparency)+
scale_size_continuous(name=sizetitle,range = sizerange, limits=c(sizeminimum,sizemaximum))
}
if(is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=subset,aes(x=lon, y=lat, color=variable),size=pointsize)
}
map_plot<-map_plot+
scale_x_continuous("", breaks=NULL) +
scale_y_continuous("", breaks=NULL) +
coord_fixed(ratio=1)+
labs(title = main_map_title, subtitle=main_map_subtitle) +
theme_tufte(base_size = fontsize, base_family = fontfamily)+
theme(plot.title=element_text(hjust = title_justification),plot.subtitle=element_text(hjust = title_justification))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding the color ramp!
if(!is.null(legend_breaks)&!is.null(legend_labels)){
map_plot<-map_plot+scale_color_gradientn(colours=rev(color_ramp),
limits=c(minimum, maximum),
values=color_value_breaks,
breaks=legend_breaks,
labels=legend_labels,
scale_name="")
}else{
map_plot<-map_plot+scale_color_gradientn(colours=rev(color_ramp),
limits=c(minimum, maximum),
values=color_value_breaks)
} # Why have this if-clause? If the value of legend_breaks is NULL, then you end up not getting a legend at all. Lame!
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding a legend
if(is.null(sizevar)){
if (legend_position %in% c("bottom","top")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_width, barwidth=legend_bar_length, label=TRUE, ticks=FALSE )) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("right","left")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_length, barwidth=legend_bar_width, label=TRUE, ticks=FALSE )) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
}else{
if (legend_position %in% c("bottom","top")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_width, barwidth=legend_bar_length, label=TRUE, ticks=FALSE ),
size=guide_legend(title=sizetitle,title.position="top")) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("right","left")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_length, barwidth=legend_bar_width, label=TRUE, ticks=FALSE ),
size=guide_legend(title=sizetitle,title.position="top")) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Making a histogram of the distribution of that dimension's values
if (histogram==TRUE){ # If you have specified that you do want the histogram at the bottom:
if(!is.null(hist_color)){hist_color_ramp<-hist_color}else{hist_color_ramp<-color_ramp}
histo<-histogram_colorstats(datavector=subset$variable,
color_ramp=hist_color_ramp,
minimum=minimum,
maximum=maximum,
color_value_breaks=color_value_breaks,
dist_stats=dist_stats,
mean_color=mean_color,
quantile_color=quantile_color)
}# If histogam==T
} # if data is numeric
#################################
# If Data is Categorical/Ordinal
#################################
if (discrete_scale==T){
if(!is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=na.omit(subset),aes(x=lon, y=lat, color=variable,size=sizevar),alpha=transparency)+
scale_size_continuous(name=sizetitle,range = sizerange)
}
if(is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=na.omit(subset),aes(x=lon, y=lat, color=variable),size=pointsize)
}
map_plot<-map_plot+
scale_x_continuous("", breaks=NULL) +
scale_y_continuous("", breaks=NULL) +
coord_fixed(ratio=1)+
labs(title = main_map_title, subtitle=main_map_subtitle) +
theme_tufte(base_size = fontsize, base_family = fontfamily)+
theme(plot.title=element_text(hjust = title_justification),plot.subtitle=element_text(hjust = title_justification))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding the color ramp!
map_plot<-map_plot+scale_fill_manual(values=rev(color_list),drop = FALSE)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding a legend
map_plot<-map_plot+guides(fill=guide_legend(title=legend_name,
keywidth=patch_width,
keyheight=patch_height,
label.position = label_position))+
theme(legend.position=legend_position)
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
# Adding a "histogram" (really, in this case, a bar chart) to the bottom of the image: This is in BETA and is not currently a funcitonality in v 1.1.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if (histogram==TRUE){ # If you have specified that you do want the histogram at the bottom:
#histo<-qplot(variable, data=subset, geom="bar", fill=variable)+scale_fill_manual(values=color_list)
histo<-ggplot(na.omit(subset), aes(x=variable, fill=variable)) +
geom_bar() +
labs(x=NULL, y=NULL) +
scale_fill_manual(values=rev(color_list))+theme_tufte(base_size = fontsize, base_family = fontfamily)+theme(legend.position="none",
axis.ticks.x=element_blank(),
axis.ticks.y=element_blank())+theme(plot.title=element_text(hjust = 0.5))
}# If histogam==T
} # if it's ordinal/categorical
#######################################
# For All Data Types
#######################################
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding Title and Legend Formatting
map_plot<-map_plot + theme(plot.title = element_text(size = title_font_size, face=title_font_face))+ #Adding custom title that might override the legend stuff
theme(legend.text = element_text(size = legend_font_size, face=legend_font_face))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding Outline Map, if desired
if (!is.null(outline_map)){
map_plot<-map_plot+geom_path(data = outline_map,
aes(x = long, y = lat, group = group),
color = outline_color, size = outline_size)}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## If you just want the map plot as an object you can pass to other things...
if (return_map_object_only==TRUE){return(map_plot)}else{
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Printing the Plot:
if (histogram==TRUE){# Combining Histogram and Map to plot into a single image.
grid.newpage() # Starting a new page
pushViewport(viewport(layout = grid.layout(5, 1))) # Defining the ratio of the histogram to map to be 5 sections vertically, 1 horizontally
vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y) # Defining a function that allows setting the layout of the viewport
print(map_plot, vp = vplayout(1:4, 1)) # Printing the map plot to the viewport in vertical slots 1-4, covering all the x-space
print(histo, vp = vplayout(5, 1)) # Printing the histogram to the bottom of the map:
}else{print(map_plot)} #If you didn't want the histogram, just print out the map!
} # Closing the "if return map object=TRUE" clause
} # Closing the loop of dimensions
if (length(destination_folder)>0){dev.off();print("PDF ready to view.")} #If you were writing this to a PDF, you can close it, and check it out!
} # Closing Function!
RebeccaStubbs/woodson documentation built on May 9, 2019, 9:37 a.m.
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#' Map Plotting Utility for Gridded Data
#'
#' @description Simplified plotting utilitity for evenly spaced points (raster data)
#'
#' @param geometry A data table with an x and a y column, as well as a geographic id.
#' @param xcol String; the name of the column that is the x values for the grid
#' @param ycol String; the name of the column that is the y values for the grid
#' @param geog_id string; the column name for the unique geogrpahic ID
#' @param variable string; the column with values you wich to plot
#' @param sizevar The variable you intend to use to scale the size ofthe points.
#' @param outline_map Another SpatialPolygons object that you want to use the
#' outlines from. Make sure your outline map and main map have the same projection.
#' @param data A data.table that contains the data you want to map
#' (must contain geog_id, and the variable of interest, if specified.
#' If a series dimension and/or series sequence is defined,
#' those must also exist in this data set)
#' @param transparency default=1, (totally opaque).
#' @param sizerange default c(0,5), the range of sizes your points can be if you
#' use the sizevar argument.
#' @param sizetitle Default "" no title. The legend title for your size legend.
#' @param pointsize Default=1. If no size variable is defined, you can define
#' a point size.
#' @param pointsize default=16, a solid filled dot. Only use symbols that have fill.
#' @param histogram logical; the plot will contain a histogram of the values
#' @param hist_color If a character string for a color (or colors) are entered
#' (ex:"grey"), the histogram will be that color rather than the color ramp
#' used for the main map.
#' @param dist_stats Vertical lines on the histogram plot showing summary
#' statistics. To show this, provide a vector of numeric values (between 0
#' and 1) to serve as quantiles, and the options "mean" and "sd" can also be
#' included. example: c("mean","sd",.1,.5,.9). Default=NULL.
#' @param mean_color The color of lines you want to represent mean and standard
#' deviation statistics, only relevant if dist_stats!=NULL. Default="red".
#' @param quantile_color The color of lines you want to represent the median and
#' quantile lines on the histogram, only relevant if dist_stats!=NULL.
#' @param return_map_object_only you can assign the function to a variable, and
#' store the map plot portion of this ggplot object so that you can combine
#' it with other graphics at will. This will never return the histogram.
#' @param destination_folder A string file path to a folder you want a PDF
#' created in that will hold your map(s)
#' @param color_ramp A list of colors that will serve as the colors you
#' "stretch" through based on your data values. This will default to a color
#' scheme described in woodson pallettes called "Easter to Earth" that
#' displays variation well when there are many geographic units. See woodson
#' palletes for more options, or create your own.
#' @param outline_size A numeric value that specifies how large you want your
#' white outlines to be if you have specified an outline you want shown on
#' your map. Default value is .1.
#' @param outline_color What color you want the outline of the additional
#' geography to be (if provided). This can be any color r recognizes
#' suggestions might be "black","yellow", or "white". Default is white.
#' @param override_scale Values that will be used to stretch the color ramp
#' instead of the min/max values present in the entire data set. Should
#' either be structured "c(min,max)", with numeric values, or be
#' "each_dimension", which will create a map series where each individual map
#' in a series will based on the min/max from that subset of data.
#' @param override_size_scale Values that will be used to stretch the size ramp
#' instead of the min/max values present in the entire data set. Should
#' either be structured "c(min,max)", with numeric values, or be
#' "each_dimension", which will create a map series where each individual map
#' in a series will based on the min/max from that subset of data.
#' @param color_value_breaks How you want the colors "stretched" across the
#' range of minimum/maximum values. Default is NULL/ uniform distribution
#' stretched across the color ramp from the minimum and maximum data values
#' provided. Vector must begin with 0 and end with 1.
#' @param diverging_centerpoint Accepts any numeric value between the minimum
#' and maximum of your data set. Sets the center of your color scheme to the
#' value defined. This is meant to be used with diverging color schemes. It
#' will override any previously defined color_value_breaks. Default=NULL.
#' @param map_title A string that serves as the basis for your map title (if no
#' dimensions are specified, the title will be as it is specified. If a
#' dimension is specified, a phrase constructed using the series dimension
#' and what you are mapping will be added to the plot title [ex="year:1990"].
#' @param additional_variable_name_string This is an additonal string that you
#' want to add to the name of the PDF to describe any other breakdowns you
#' might be using. For example, if you had to map something by year, age,
#' sex, you would first need to subset your data to be one age/sex group
#' before plotting it out by year. If you subset your data in a loop, you
#' could use this string to specify something along the lines of
#' paste0("age_ ",a," _ sex _",s).
#' @param fontfamily The name of the font family you want to use for the text
#' on the plot. Default is 'serif'.
#' @param fontsize The base/minimum size of the text on your graphic.
#' Default is NULL.
#' @param title_justification Where ("left","center",or "right) you want the title
#' and subtitle. Default is "center".
#' @param title_font_size How large you want the title font to be. No default;
#' default values based on ggthemes tufte()'s default.
#' @param title_font_face Special properties of the title font.
#' Options include "plain", "bold", "italic". Default is plain.
#' @param series_dimension A string-- the name of the column that will serve as
#' the variable you loop through to create a series map. For example, year.
#' @param series_sequence A vector c(x,y,z...) that specifies a subset of the
#' series dimensions you want to map. For example, if you have a data set
#' that contains all years between 1980-2014, you can specify that you only
#' want to plot out every other year by setting series sequence to be
#' seq(1980,2014,2). This function will make sure all of the items you
#' speficy actually exist within your series_dimension.
#' @param legend_name Title above the legend. Default is NULL.
#' @param legend_position Where you want the legend to go. Options are
#' "top","bottom","right","left", and "none". Default is "bottom".
#' @param legend_font_size How large you want the legend font to be.
#' No default; default values based on ggthemes tufte()'s default.
#' @param legend_font_face Special properties of the legend font. Options
#' include "plain", "bold", "italic". Default is plain.
#' @param legend_bar_width How fat you want the color bar that serves as the
#' legend to be. Default value is 0.4.
#' @param legend_bar_length How long you want the color bar that serves as the
#' legend to be. Default value is 20.
#' @param legend_breaks An optional vector of the values you want to label in
#' your legend's color scale.
#' @param legend_labels An optional vector of the character strings you want to
#' use to label your legend's color scale (must be same length as
#' legend_breaks)
#' @param scramble_colors Logical; Scrambles the input color ramp's values.
#' useful for categorical data.
#' @param patch_width width of color swatches in legend when categorical data
#' is used. Default is .25.
#' @param patch_height height of color swatches in legend when categorical data
#' is used. Default is .25.
#' @param label_position Position of category labels in legend when categorical
#' data is used. Default= "right".
#' @param verbose logical; Whether you want print statements from the function
#' scramble_colors=FALSE,
#'
#' @return ggplot object or None (plots written to pdf)
#'
#' @examples see https://rpubs.com/BeccaStubbs/introduction_to_woodson_mapping_suite
#'
#' @export
wmappoints<-function(geometry,
xcol,
ycol,
geog_id,
variable,
# Optional data/geometry
outline_map=NULL, #
data=NULL,
sizevar=NULL,
# Point-based options
transparency=1,
sizerange=c(0,5),
sizetitle="",
pointsize=1,
pointsymbol=16, # a solid filled dot
# What elements of the map do you want the function to return?
histogram=FALSE,
hist_color=NULL,
dist_stats=NULL,
mean_color="red",
quantile_color="black",
return_map_object_only=FALSE,
destination_folder=NULL,
# Inputs for the color scheme of the maps
color_ramp=wpal("easter_to_earth"),
outline_size=.1,
outline_color="white",
override_scale=NULL,
override_size_scale=NULL,
color_value_breaks=NULL,
diverging_centerpoint=NULL,
# Inputs for text
map_title=" ",
map_subtitle=NULL,
title_justification="center",
additional_variable_name_string=NULL,
title_font_size=NULL,
title_font_face="plain",
# Fonts
fontfamily="serif",
fontsize=12,
# Inputs for generating series-maps
series_dimension=NULL,
series_sequence=NULL,
# Inputs for map Legend
legend_name=NULL,
legend_position="bottom",
legend_font_size=NULL,
legend_font_face="plain",
# Inputs for numeric data only
legend_bar_width=.4,
legend_bar_length=20,
legend_breaks=NULL,
legend_labels=NULL,
# Inputs for categorical data only
scramble_colors=FALSE,
label_position="right",
# Do you want print statements?
verbose=F){
# Copying objects such that the original data sets are unaltered
data_is_null<-is.null(data)
geometry<-copy(geometry)
setnames(geometry,xcol,"lon"); setnames(geometry,ycol,"lat")
outline_map<-copy(outline_map)
data<-copy(data)
if(variable==geog_id){stop("Your variable and geog_id are the same.")}
if(!is.null(sizevar)){
if(variable==sizevar){stop("Your variable and size-variable are the same.")}
if(geog_id==sizevar){stop("Your geog_id and size-variable are the same.")}
}
#print("aftererror")
# Getting the data object ready to join to the fortified spatial object (either from the chloropleth map's data.table, or from an external data.table)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Check to make sure the geog_id specified is within the chloropleth map's data table
if(!(geog_id %in% names(geometry))) stop("That geographic ID does not appear to exist within your chloropleth map object.")
setnames(geometry,geog_id,"geog_id")
# If External Data is Specified
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if (!is.null(data)){
# Check that the geog_id is within the external data set, rename it to "geog_id"
if(!(geog_id %in% names(data))) stop("That geographic ID does not appear to exist within your data set.")
setnames(data,geog_id,"geog_id")
# Check thta the variable name exists in either the data set or the geometry
if( (!variable %in% names(data)) & (!variable %in% names(geometry)) ) stop(paste0("That variable, ",variable," does not appear to exist within your data set or geometry."))
# Check that it doesn't exist in BOTh the data set and the geometry
if( (variable %in% names(data)) & (variable %in% names(geometry))) stop("The variable you defined for color exists in both your geometry and the additoinal data set.")
# Check that the variable name exists in either the data or the geometry
if ( (!variable %in% names(data)) & (!variable %in% names(geometry)) ) stop("The variable you defined as the size of the points does not appear to exist within your data set.")
if (variable %in% names(geometry)) setnames(geometry,variable,"variable")
if (variable %in% names(data)) setnames(data,variable,"variable")
# If a size variable is defined...
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if(!is.null(sizevar)){
# Check that it doesn't exist in BOTH the data and the geometry
if( (sizevar %in% names(data)) & (sizevar %in% names(geometry))) stop("The variable you defined for size exists in both your geometry and the additoinal data set.")
# rename it in either the data or the geometry
if(sizevar %in% names(data)) {
if(!is.numeric(data[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(data,sizevar,"sizevar")
}
if(sizevar %in% names(geometry)){
if(!is.numeric(geometry[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(geometry,sizevar,"sizevar")
}
}
}else{ # If external data is NOT specified
if(!is.null(sizevar)){
if(!sizevar %in% names(geometry)) stop(paste0("You haven't provided an additional data set, and it looks like your size variable, ",sizevar," doesn't exist in your geometry object."))
if(!is.numeric(geometry[[sizevar]])) stop(paste0("You need to provide a numeric variable to the sizevar argument. You provided: ",sizevar))
setnames(geometry,sizevar,"sizevar")
}
data<-copy(geometry)
if(!(variable %in% names(data))) stop(paste0("That variable, ",variable," does not appear to exist in the data attributes of your spatial object."))
setnames(data,variable,"variable")
}
# checking whether the data is a factor/ordered: this will make it be mapped with a discrete scale.
if (is.factor(data[["variable"]])|is.ordered(data[["variable"]])){discrete_scale<-TRUE}else{discrete_scale<-FALSE}
if (is.character(data[["variable"]])){
print("Character data being converted to a factor. If you'd like a specific order to your levels, please transform your variable into a factor or ordered data type with appropriate ordering. ")
data[,variable:=as.factor(variable)]
discrete_scale<-TRUE}
if(discrete_scale&histogram){histogram<-F; print("Sorry, histogram/bar graph functionality is not yet supported in this version of the mapping suite for categorical data. No histogram will be printed.")}
# Making sure that there are the right number of colors in the color ramp, by sampling and then scrambling (optional)
# the color pallette chosen.
pallette<-colorRampPalette(color_ramp)
color_list<-pallette(nlevels(data[["variable"]]))
if(scramble_colors==T){
color_list<-color_list[sample(1:length(color_list))]
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Defining "map dims"; the levels of the series dimension you want to map
# First, discovering or defining the "series dimension"
if (!is.null(series_dimension)){ # If you plan to loop through miltiple dimensions...
if(!(series_dimension %in% names(data))) stop("That series dimension (what you want to iterate through) does not appear to exist within your data set.")
setnames(data,series_dimension,"series_dimension")
}else{
data[,series_dimension:="*&^! no dimensions"]
}
# Restricting the mapping to only *some* levels of that dimension, if desired
if (is.null(series_sequence)){
map_dims<-unique(data$series_dimension)
}else{
for (select_dimension in series_sequence){
if(!(select_dimension %in% unique(data$series_dimension))) stop(paste0("The dimension ",select_dimension," does not appear to exist in the column you have specified to hold your dimensions."))
}
map_dims<-series_sequence
}
# determining the "hjust" of the title
if(title_justification=="left"){title_justification<-0}
if(title_justification=="center"){title_justification<-.5}
if(title_justification=="right"){title_justification<-1}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Fortifying the Map(s) and Joining on the Data
# "fortifying" the Rdata shapefiles
if (!is.null(outline_map)){outline_map<-data.table(suppressWarnings(fortify(outline_map)))} # If an outline map is specified, fortify the outline map as well.
# creating one long, huge object that you can subset by merging together the data and the forfified geometry
if(data_is_null==F){ # if there is extra data provided, merge it on, then sub-select down.
orig_rows<-nrow(geometry)
data<-merge(data, geometry, by="geog_id", allow.cartesian=T)
after_rows<-nrow(data)
if(orig_rows<after_rows&is.null(series_dimension))print("You are mapping more than one data observation per geometry, and you have not specified a series dimension to map over. Did you intend to subset your data further before passing it to this funciton?")
}
if(!is.null(sizevar)){
data<-data[, list(geog_id=as.character(geog_id), variable, lon, lat, series_dimension, sizevar)]
}else{
data<-data[, list(geog_id=as.character(geog_id), variable, lon, lat, series_dimension)]
}
###########################################
## LOOPING ACROSS DIMENSIONS
###########################################
# Starting a PDF, if desired
if (!is.null(destination_folder)){pdf(paste0(destination_folder,variable,additional_variable_name_string,".pdf"))}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Starting the Loop
for (select_dimension in map_dims){ #for each dimension you want to plot...
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Determining map title
main_map_title<-map_title
if(verbose) print(main_map_title)
# Determining map subtitle
if (select_dimension=="*&^! no dimensions"){
main_map_subtitle<-map_subtitle
}else{
main_map_subtitle<-paste0(map_subtitle," ",select_dimension)}
if(verbose) print(main_map_subtitle)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Subsetting the Data
subset<-copy(data[series_dimension==select_dimension]) # Sub-setting the fortified object to map out 1 layer/dimension (ex: year) of the variable of interest
#####################
# If Data is Numeric
#####################
if(discrete_scale==F){ # If the data is numeric...
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Defining Boundaries and Properties of the Color Ramp
# If an override was provided, setting minimum to the first in the list, and maximum to the second in the list provided.
if (!is.null(override_scale)){
if(is.numeric(override_scale)){
minimum<-override_scale[1]
maximum<-override_scale[2]
}else{
if(override_scale=="each_dimension"){
maximum<-max(subset[["variable"]])
minimum<-min(subset[["variable"]])
}else{stop("Any character input other than 'each_dimension', which will produce a color ramp from the min/max of each dimension, is not recognized.")}
}
}else{ #Otherwise, set the min/max of the scale to the min/max of ALL dimensions of the variable.
maximum<-max(data[["variable"]])
minimum<-min(data[["variable"]])
}
if(!is.null(sizevar)){
if (!is.null(override_size_scale)){
if(is.numeric(override_size_scale)){
sizeminimum<-override_size_scale[1]
sizemaximum<-override_size_scale[2]
}else{
if(override_size_scale=="each_dimension"){
sizemaximum<-max(subset[["sizevar"]])
sizeminimum<-min(subset[["sizevar"]])
}else{stop("Any character input other than 'each_dimension', which will produce a color ramp from the min/max of each dimension, is not recognized.")}
}
}else{ #Otherwise, set the min/max of the scale to the min/max of ALL dimensions of the variable.
sizemaximum<-max(data[["sizevar"]])
sizeminimum<-min(data[["sizevar"]])
}
}
# Determining the diverging centerpoint in relation to the min/max, if desired
if(!is.null(diverging_centerpoint)){
if(diverging_centerpoint>maximum){stop("The diverging centerpoint provided is greater than the maximum value in the data set.")}
if(diverging_centerpoint<minimum){stop("The diverging centerpoint provided is less than the minimum value in the data set.")}
# Finding what where the specified break point is as a fraction of the total color range
value_range<-maximum-minimum
difference_from_minimum<-diverging_centerpoint-minimum
break_value<-difference_from_minimum/value_range
color_value_breaks<-c(0,break_value,1)
if(verbose) print(paste0("Centering color ramp at ",diverging_centerpoint,". Any other color breaks provided have been overridden."))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Creating the Map Plot in GGPlot2
if(!is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=subset,aes(x=lon, y=lat, color=variable,size=sizevar),alpha=transparency)+
scale_size_continuous(name=sizetitle,range = sizerange, limits=c(sizeminimum,sizemaximum))
}
if(is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=subset,aes(x=lon, y=lat, color=variable),size=pointsize)
}
map_plot<-map_plot+
scale_x_continuous("", breaks=NULL) +
scale_y_continuous("", breaks=NULL) +
coord_fixed(ratio=1)+
labs(title = main_map_title, subtitle=main_map_subtitle) +
theme_tufte(base_size = fontsize, base_family = fontfamily)+
theme(plot.title=element_text(hjust = title_justification),plot.subtitle=element_text(hjust = title_justification))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding the color ramp!
if(!is.null(legend_breaks)&!is.null(legend_labels)){
map_plot<-map_plot+scale_color_gradientn(colours=rev(color_ramp),
limits=c(minimum, maximum),
values=color_value_breaks,
breaks=legend_breaks,
labels=legend_labels,
scale_name="")
}else{
map_plot<-map_plot+scale_color_gradientn(colours=rev(color_ramp),
limits=c(minimum, maximum),
values=color_value_breaks)
} # Why have this if-clause? If the value of legend_breaks is NULL, then you end up not getting a legend at all. Lame!
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding a legend
if(is.null(sizevar)){
if (legend_position %in% c("bottom","top")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_width, barwidth=legend_bar_length, label=TRUE, ticks=FALSE )) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("right","left")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_length, barwidth=legend_bar_width, label=TRUE, ticks=FALSE )) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
}else{
if (legend_position %in% c("bottom","top")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_width, barwidth=legend_bar_length, label=TRUE, ticks=FALSE ),
size=guide_legend(title=sizetitle,title.position="top")) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("right","left")){
map_plot<-map_plot+
guides(color=guide_colourbar(title=legend_name, title.position="top", barheight=legend_bar_length, barwidth=legend_bar_width, label=TRUE, ticks=FALSE ),
size=guide_legend(title=sizetitle,title.position="top")) +
theme(legend.position=legend_position,legend.title=element_text(size=legend_font_size))}
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Making a histogram of the distribution of that dimension's values
if (histogram==TRUE){ # If you have specified that you do want the histogram at the bottom:
if(!is.null(hist_color)){hist_color_ramp<-hist_color}else{hist_color_ramp<-color_ramp}
histo<-histogram_colorstats(datavector=subset$variable,
color_ramp=hist_color_ramp,
minimum=minimum,
maximum=maximum,
color_value_breaks=color_value_breaks,
dist_stats=dist_stats,
mean_color=mean_color,
quantile_color=quantile_color)
}# If histogam==T
} # if data is numeric
#################################
# If Data is Categorical/Ordinal
#################################
if (discrete_scale==T){
if(!is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=na.omit(subset),aes(x=lon, y=lat, color=variable,size=sizevar),alpha=transparency)+
scale_size_continuous(name=sizetitle,range = sizerange)
}
if(is.null(sizevar)){
map_plot<-ggplot() + geom_point(data=na.omit(subset),aes(x=lon, y=lat, color=variable),size=pointsize)
}
map_plot<-map_plot+
scale_x_continuous("", breaks=NULL) +
scale_y_continuous("", breaks=NULL) +
coord_fixed(ratio=1)+
labs(title = main_map_title, subtitle=main_map_subtitle) +
theme_tufte(base_size = fontsize, base_family = fontfamily)+
theme(plot.title=element_text(hjust = title_justification),plot.subtitle=element_text(hjust = title_justification))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding the color ramp!
map_plot<-map_plot+scale_fill_manual(values=rev(color_list),drop = FALSE)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding a legend
map_plot<-map_plot+guides(fill=guide_legend(title=legend_name,
keywidth=patch_width,
keyheight=patch_height,
label.position = label_position))+
theme(legend.position=legend_position)
if (legend_position %in% c("none")){
map_plot<-map_plot+theme(legend.position="none")
}
# Adding a "histogram" (really, in this case, a bar chart) to the bottom of the image: This is in BETA and is not currently a funcitonality in v 1.1.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if (histogram==TRUE){ # If you have specified that you do want the histogram at the bottom:
#histo<-qplot(variable, data=subset, geom="bar", fill=variable)+scale_fill_manual(values=color_list)
histo<-ggplot(na.omit(subset), aes(x=variable, fill=variable)) +
geom_bar() +
labs(x=NULL, y=NULL) +
scale_fill_manual(values=rev(color_list))+theme_tufte(base_size = fontsize, base_family = fontfamily)+theme(legend.position="none",
axis.ticks.x=element_blank(),
axis.ticks.y=element_blank())+theme(plot.title=element_text(hjust = 0.5))
}# If histogam==T
} # if it's ordinal/categorical
#######################################
# For All Data Types
#######################################
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding Title and Legend Formatting
map_plot<-map_plot + theme(plot.title = element_text(size = title_font_size, face=title_font_face))+ #Adding custom title that might override the legend stuff
theme(legend.text = element_text(size = legend_font_size, face=legend_font_face))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Adding Outline Map, if desired
if (!is.null(outline_map)){
map_plot<-map_plot+geom_path(data = outline_map,
aes(x = long, y = lat, group = group),
color = outline_color, size = outline_size)}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## If you just want the map plot as an object you can pass to other things...
if (return_map_object_only==TRUE){return(map_plot)}else{
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Printing the Plot:
if (histogram==TRUE){# Combining Histogram and Map to plot into a single image.
grid.newpage() # Starting a new page
pushViewport(viewport(layout = grid.layout(5, 1))) # Defining the ratio of the histogram to map to be 5 sections vertically, 1 horizontally
vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y) # Defining a function that allows setting the layout of the viewport
print(map_plot, vp = vplayout(1:4, 1)) # Printing the map plot to the viewport in vertical slots 1-4, covering all the x-space
print(histo, vp = vplayout(5, 1)) # Printing the histogram to the bottom of the map:
}else{print(map_plot)} #If you didn't want the histogram, just print out the map!
} # Closing the "if return map object=TRUE" clause
} # Closing the loop of dimensions
if (length(destination_folder)>0){dev.off();print("PDF ready to view.")} #If you were writing this to a PDF, you can close it, and check it out!
} # Closing Function!
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