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Mapping_Country_Events.R
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Mapping_Country_Events.R
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#### Script for by-country mapping of event data with all datasets
#### # by Mark Simpson
#### Set working directory ####
# Mark's home computer
#setwd("C:/Users/kramp_000/SkyDrive/Documents/502 Project Online/502 Project")
# Mark's office computer
setwd("W:/Mark OneDrive/OneDrive/Documents/502 Project Online/502 Project")
# Mark's laptop
#### Load packages ####
# install.packages("ggplot2")
# install.packages("dplyr")
# install.packages("tidyr")
#
# install.packages("GISTools")
# install.packages("rgdal")
# install.packages("maps")
#
# install.packages("ggmap")
# install.packages("countrycode")
library(ggplot2)
library(dplyr)
library(tidyr)
library(GISTools)
library(rgdal)
library(maps)
library(ggmap)
library(countrycode)
#### Load Datasets ####
# ICEWS read pipeline
ICEWS <- read.csv(file ="Processed/ICEWS_Geo_Select.csv", fill = TRUE) %>%
# Format date
mutate(Event.Date = as.Date(Event.Date)) %>%
# Filter to year range overlapped with other datasets
filter(Event.Date > "1994-12-31" & Event.Date < "2005-01-01") %>%
# Create new column for year
mutate(year = format(Event.Date, "%Y")) %>%
# rename quad_class to match Phoenix datasets
rename( cameo.root = quad_class) %>%
# rename latitude to match Phoenix datasets
rename( lat = Latitude) %>%
# rename longitude to match Phoenix datasets
rename( lon = Longitude) %>%
# rename latitude to match Phoenix datasets
rename( story_date = Event.Date)
head(ICEWS)
# NYT read pipeline
NYT <- read.csv(file ="Processed/NYT_Geolocated.csv") %>%
# Format date
mutate(story_date = as.Date(story_date, format="%m/%d/%Y") ) %>%
# Filter to year range overlapped with other datasets
filter(story_date > "1994-12-31" & story_date < "2005-01-01")
# Create new field and populate according to cameo code
NYT$cameo.root[NYT$quad_class == 0] <- "Neutral"
NYT$cameo.root[NYT$quad_class == 1] <- "Verbal cooperation"
NYT$cameo.root[NYT$quad_class == 2] <- "Material cooperation"
NYT$cameo.root[NYT$quad_class == 3] <- "Verbal conflict"
NYT$cameo.root[NYT$quad_class == 4] <- "Material conflict"
# SWB read pipeline
SWB <- read.csv(file ="Processed/SWB_Geolocated.csv") %>%
# Format date
mutate(story_date = as.Date(story_date, format="%m/%d/%Y") ) %>%
# Filter to year range overlapped with other datasets
filter(story_date > "1994-12-31" & story_date < "2005-01-01")
# Create new field and populate according to cameo code
SWB$cameo.root[SWB$quad_class == 0] <- "Neutral"
SWB$cameo.root[SWB$quad_class == 1] <- "Verbal cooperation"
SWB$cameo.root[SWB$quad_class == 2] <- "Material cooperation"
SWB$cameo.root[SWB$quad_class == 3] <- "Verbal conflict"
SWB$cameo.root[SWB$quad_class == 4] <- "Material conflict"
# FBIS read pipeline
FBIS <- read.csv(file ="Processed/FBIS_Geolocated.csv") %>%
# Format date
mutate(story_date = as.Date(story_date, format="%m/%d/%Y") ) %>%
# Filter to year range overlapped with other datasets
filter(story_date > "1994-12-31" & story_date < "2005-01-01")
# Create new field and populate according to cameo code
FBIS$cameo.root[FBIS$quad_class == 0] <- "Neutral"
FBIS$cameo.root[FBIS$quad_class == 1] <- "Verbal cooperation"
FBIS$cameo.root[FBIS$quad_class == 2] <- "Material cooperation"
FBIS$cameo.root[FBIS$quad_class == 3] <- "Verbal conflict"
FBIS$cameo.root[FBIS$quad_class == 4] <- "Material conflict"
#### Create Lists of countries to map ####
# Every country in any dataset
naive.c <- sort( unique( c(
as.character( unique( ICEWS$countryname)),
as.character( unique( NYT$countryname)),
as.character( unique( SWB$countryname)),
as.character( unique( FBIS$countryname))
) ) )
# Manually created list of countries that will not work with ggmap bounding box
no.bb.countries <- sort(c("SGP", "VAT", "MAC", "SMR", "GIB", "DJI", "LCA", "MCO",
"SYC", "BLZ", "CYM", "GLP", "GRD", "STP", "VGB", "BMU"))
# Manually created list of Countries that will not loop properly
ultra.bad <- sort(c("USA", "RUS", "FIN", "ATA", "TUV", "TON", "ATF", "SGS", "REU",
"SJM", "ABW", "AIA", "AND", "ANT", "ATG", "BLM", "BRB", "CCK",
"COK", "CPV", "CUW", "CXR", "DMA", "FLK", "FRO", "FSM", "GGY",
"HMD", "IMN", "JEY", "KIR", "KNA", "MAF", "MDV", "MHL", "MSR",
"MYT", "NFK", "NIU", "NRU", "PCN", "PLW", "REU", "SGS", "SHN",
"SJM", "SPM", "SXM", "TCA", "TKL", "TON", "VCT", "VIR", "VUT",
"WLF", "XKX", "BES", "ALA", "IOT"))
# Create master list of countries to loop (all countries minus ultra.bad )
countries <- setdiff(naive.c , ultra.bad)
#### Set Colors and Shapes Block ####
# Manually set shapes for event types, called in ggmap later
event.shape <- c("Neutral" = 23,
"Verbal cooperation" = 1,
"Material cooperation" = 21,
"Verbal conflict" = 2,
"Material conflict" = 24)
# Manually set sizes for event types, called in ggmap later
event.size <- c("Neutral" = 1,
"Verbal cooperation" = 2,
"Material cooperation" = 1,
"Verbal conflict" = 2,
"Material conflict" = 1)
# Manually set sizes for event types, called in ggmap later
event.fill <- c("Neutral" = "forestgreen",
"Verbal cooperation" = NA,
"Material cooperation" = "dodgerblue4",
"Verbal conflict" = NA,
"Material conflict" = "red3")
# Manually set colors for event types, called in ggmap later
event.color <- c("Neutral" = "forestgreen",
"Verbal cooperation" = "dodgerblue3",
"Material cooperation" = "dodgerblue4",
"Verbal conflict" = "tomato",
"Material conflict" = "red3")
# Color scheme for the different sources
source.color <- c("NYT" = "blue",
"SWB" = "darkorchid",
"FBIS" = "springgreen4",
"ICEWS" = "firebrick")
# Manually set shapes for sources
source.shape <- c("NYT" = 21,
"SWB" = 22,
"FBIS" = 23,
"ICEWS" = 24)
#### Looping ###
# Loop outline
# set country
# get ggmap
# if statement on good/bad
# map points by type I
# map points by type N
# map points by type S
# map points by type F
# Set directory for output
#dir <- "C:/Users/kramp_000/Desktop/Maps/maps2/"
#
dir <- "W:/Mark OneDrive/OneDrive/Documents/502 Project Online/502 Project/Plots/Maps/Maps/"
length(countries)
# Start massive loop
for (i in 1:length(countries)){
#### Loop setup ####
# Assign by index, sets up everything else
country <- countries[i]
cat( c("Starting", country, "loop"))
# get full name using countrycode package
long.name <- countrycode(country, "iso3c", "country.name")
# subset dataset by country name
ICEWS.sub <- ICEWS %>% filter(countryname == country)
NYT.sub <- NYT %>% filter(countryname == country)
SWB.sub <- SWB %>% filter(countryname == country)
FBIS.sub <- FBIS %>% filter(countryname == country)
# if in no bounding box list...
if(country %in% no.bb.countries == TRUE){
# Get map by long name
map <- get_map(long.name, color = "bw")
# Otherwise...
} else {
# Get bounding box using ICEWS, fudge factor
bbox <- make_bbox(lon, lat, FBIS.sub, f = .4)
# Get map for bounding box
map <- get_map(bbox, color = "bw")
}
# set basemap
base.map <- ggmap(map, darken = c(0.5, "white"))
##### Map set 1: Events by Type #####
# Mapping all events by type per dataset per country
cat("Map set 1")
# Set title suffix
end.title <- "Events, 1995-2004"
#### ICEWS ####
dataset <- "ICEWS"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = ICEWS.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### NYT ####
dataset <- "NYT"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = NYT.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### SWB ####
dataset <- "SWB"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = SWB.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### FBIS ####
dataset <- "FBIS"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = FBIS.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
##### Map set 2, Events by Source #####
cat("Map set 2")
# Set attributes for this map
p.alpha = .2
p.size = .5
# Plots events by source
map.print <- base.map +
# ICEWS
geom_point(data = ICEWS.sub,
aes(x = lon,
y = lat,
shape = "ICEWS",
color = "ICEWS",
fill = "ICEWS"),
alpha = p.alpha,
size = p.size) +
# Add NYT points with right color
geom_point(data = NYT.sub,
aes(x = lon,
y = lat,
shape = "NYT",
color = "NYT",
fill = "NYT"),
alpha = p.alpha,
size = p.size) +
# Add SWB points with right color
geom_point(data = SWB.sub,
aes(x = lon,
y = lat,
shape = "SWB",
color = "SWB",
fill = "SWB"),
alpha = p.alpha,
size = p.size) +
# FBIS points with right color
geom_point(data = FBIS.sub,
aes(x = lon,
y = lat,
shape = "FBIS",
color = "FBIS",
fill = "FBIS"),
alpha = p.alpha,
size = p.size) +
# # Assign source colors and shapes, defined earlier
scale_color_manual(name = "Source", values = source.color ) +
scale_fill_manual(name = "Source", values = source.color ) +
scale_shape_manual(name = "Source", values = source.shape ) +
# # This resent the alpha to make the legend legible
# guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Events_by_Source", ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
##### Map set 3, Mean Centers by Type #####
cat("Map set 3")
# Set attributes for this map
p.alpha = .2
p.size = 2
p.shape = 4
# Manually set shapes for event types, with mean center
event.shape.2 <- c("Neutral" = 18,
"Verbal cooperation" = 1,
"Material cooperation" = 20,
"Verbal conflict" = 2,
"Material conflict" = 17,
"All events" = 4)
# Manually set sizes for event types, called in ggmap later
event.size.2 <- c("Neutral" = 1.5,
"Verbal cooperation" = 2,
"Material cooperation" = 1.5,
"Verbal conflict" = 2,
"Material conflict" = 1.5,
"All events" = 3)
# Plots events by source
map.print <- base.map +
#### ICEWS Mean Centers ####
# All events
geom_point(data = ICEWS.sub,
aes(x = mean(lon),
y = mean(lat),
shape = "All events",
color = "ICEWS",
fill = "ICEWS",
size = "All events")) +
# Neutral events
geom_point(data = filter(ICEWS.sub, cameo.root == "Neutral"),
aes(x = mean(lon),
y = mean(lat),
shape = "Neutral",
color = "ICEWS",
fill = "ICEWS",
size = "Neutral")) +
# Verbal cooperation events
geom_point(data = filter(ICEWS.sub, cameo.root == "Verbal cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal cooperation",
color = "ICEWS",
size = "Verbal cooperation"),
alpha = p.alpha) +
# Verbal conflict events
geom_point(data = filter(ICEWS.sub, cameo.root == "Verbal conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal conflict",
color = "ICEWS",
size = "Verbal conflict"),
alpha = p.alpha) +
# Material cooperation events
geom_point(data = filter(ICEWS.sub, cameo.root == "Material cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material cooperation",
color = "ICEWS",
fill = "ICEWS",
size = "Material cooperation"),
alpha = p.alpha) +
# Material conflict events
geom_point(data = filter(ICEWS.sub, cameo.root == "Material conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material conflict",
color = "ICEWS",
fill = "ICEWS",
size = "Material conflict"),
alpha = p.alpha) +
#### NYT Mean Centers ####
# All events
geom_point(data = NYT.sub,
aes(x = mean(lon),
y = mean(lat),
shape = "All events",
color = "NYT",
fill = "NYT",
size = "All events")) +
# Neutral events
geom_point(data = filter(NYT.sub, cameo.root == "Neutral"),
aes(x = mean(lon),
y = mean(lat),
shape = "Neutral",
color = "NYT",
fill = "NYT",
size = "Neutral")) +
# Verbal cooperation events
geom_point(data = filter(NYT.sub, cameo.root == "Verbal cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal cooperation",
color = "NYT",
size = "Verbal cooperation"),
alpha = p.alpha) +
# Verbal conflict events
geom_point(data = filter(NYT.sub, cameo.root == "Verbal conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal conflict",
color = "NYT",
size = "Verbal conflict"),
alpha = p.alpha) +
# Material cooperation events
geom_point(data = filter(NYT.sub, cameo.root == "Material cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material cooperation",
color = "NYT",
fill = "NYT",
size = "Material cooperation"),
alpha = p.alpha) +
# Material conflict events
geom_point(data = filter(NYT.sub, cameo.root == "Material conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material conflict",
color = "NYT",
fill = "NYT",
size = "Material conflict"),
alpha = p.alpha) +
#### SWB Mean Centers ####
# All events
geom_point(data = SWB.sub,
aes(x = mean(lon),
y = mean(lat),
shape = "All events",
color = "SWB",
fill = "SWB",
size = "All events")) +
# Neutral events
geom_point(data = filter(SWB.sub, cameo.root == "Neutral"),
aes(x = mean(lon),
y = mean(lat),
shape = "Neutral",
color = "SWB",
fill = "SWB",
size = "Neutral")) +
# Verbal cooperation events
geom_point(data = filter(SWB.sub, cameo.root == "Verbal cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal cooperation",
color = "SWB",
size = "Verbal cooperation"),
alpha = p.alpha) +
# Verbal conflict events
geom_point(data = filter(SWB.sub, cameo.root == "Verbal conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal conflict",
color = "SWB",
size = "Verbal conflict"),
alpha = p.alpha) +
# Material cooperation events
geom_point(data = filter(SWB.sub, cameo.root == "Material cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material cooperation",
color = "SWB",
fill = "SWB",
size = "Material cooperation"),
alpha = p.alpha) +
# Material conflict events
geom_point(data = filter(SWB.sub, cameo.root == "Material conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material conflict",
color = "SWB",
fill = "SWB",
size = "Material conflict"),
alpha = p.alpha) +
#### FBIS Mean Centers ####
# All events
geom_point(data = FBIS.sub,
aes(x = mean(lon),
y = mean(lat),
shape = "All events",
color = "FBIS",
fill = "FBIS",
size = "All events")) +
# Neutral events
geom_point(data = filter(FBIS.sub, cameo.root == "Neutral"),
aes(x = mean(lon),
y = mean(lat),
shape = "Neutral",
color = "FBIS",
fill = "FBIS",
size = "Neutral")) +
# Verbal cooperation events
geom_point(data = filter(FBIS.sub, cameo.root == "Verbal cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal cooperation",
color = "FBIS",
size = "Verbal cooperation"),
alpha = p.alpha) +
# Verbal conflict events
geom_point(data = filter(FBIS.sub, cameo.root == "Verbal conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Verbal conflict",
color = "FBIS",
size = "Verbal conflict"),
alpha = p.alpha) +
# Material cooperation events
geom_point(data = filter(FBIS.sub, cameo.root == "Material cooperation"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material cooperation",
color = "FBIS",
fill = "FBIS",
size = "Material cooperation"),
alpha = p.alpha) +
# Material conflict events
geom_point(data = filter(FBIS.sub, cameo.root == "Material conflict"),
aes(x = mean(lon),
y = mean(lat),
shape = "Material conflict",
color = "FBIS",
fill = "FBIS",
size = "Material conflict"),
alpha = p.alpha) +
#### Titles and Scales ####
# Assign source colors and shapes, defined earlier
scale_color_manual(name = "Source", values = source.color) +
scale_fill_manual(name = "Source", values = source.color) +
scale_shape_manual(name = "Event Type", values = event.shape.2 ) +
scale_size_manual(name = "Event Type", values = event.size.2) +
# # This resent the alpha to make the legend legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(long.name, "Mean Centers of", end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Mean_Center_Type", ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
cat(c(country, "complete."))
}
#### United States ####
#### Loop setup ####
# Assign by index, sets up everything else
country <- "USA"
cat( c("Starting", country, "loop"))
# get full name using countrycode package
long.name <- countrycode(country, "iso3c", "country.name")
# subset dataset by country name
ICEWS.sub <- ICEWS %>% filter(countryname == country)
NYT.sub <- NYT %>% filter(countryname == country)
SWB.sub <- SWB %>% filter(countryname == country)
FBIS.sub <- FBIS %>% filter(countryname == country)
# Get map by long name
map <- get_map(location = c(lon = -120,lat = 45),
zoom = 3,
color = "bw")
# set basemap
base.map <- ggmap(map, darken = c(0.5, "white"))
base.map
##### Map set 1: Events by Type #####
# Mapping all events by type per dataset per country
cat("Map set 1")
# Set title suffix
end.title <- "Events, 1995-2004"
#### ICEWS ####
dataset <- "ICEWS"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = ICEWS.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### NYT ####
dataset <- "NYT"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = NYT.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### SWB ####
dataset <- "SWB"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = SWB.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +
# Mess with theme for readability, taking away axis labels
theme(title = element_text(size = 12, face = "bold"),
legend.text = element_text(size = 12),
axis.text = element_blank(),
axis.ticks = element_blank())
# Put together filename with dir path
filename <- paste0(dir, country, "_Event_Types_", dataset, ".png")
# Save as png with cairo driver
ggsave(map.print, file = filename, width = 8, height = 6, type = "cairo-png", dpi = 300)
####
#### FBIS ####
dataset <- "FBIS"
# Plots events by type
map.print <- base.map +
# Add points, map to variables
geom_point(data = FBIS.sub,
aes( x = lon,
y = lat,
color = cameo.root,
shape = cameo.root,
size = cameo.root,
fill = cameo.root),
alpha = .6) +
# Manual aesthetic mappings
scale_size_manual(name = "Event Type", values = event.size) +
scale_colour_manual(name = "Event Type", values = event.color) +
scale_fill_manual(name = "Event Type", values = event.fill) +
scale_shape_manual(name = "Event Type", values = event.shape) +
# Legend title, reset alpha to make the symbols legible
guides(color = guide_legend(override.aes = list(alpha = 1))) +
# Add labels by combining the long.name with dataset title
labs( title = paste(dataset, long.name, end.title),
x = NULL,
y = NULL) +