inst/plot_importation_estimates_detection.R
In HopkinsIDD/covidImportation: Estimating the Number of Imported COVID-19 Cases
##' Plot the estimated and reported number of importations over time
##'
##' Author: Shaun Truelove
##' email: shauntruelove@jhu.edu
##' Updated: 31 Jan 2020
# SETUP -------------------------------------------------------------------
if (!exists("version")){ version <- "1" }
if (!exists("batch")){ batch <- "1" }
if (!exists("project_name")){ project_name <- "california_import" }
import_sim_file <- file.path("output",project_name, sprintf("covid_importation_sim_%s_batch_detect_v%s.RData", batch, version))
options(scipen=999)
if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse)
if(!require('RColorBrewer')) install.packages('RColorBrewer'); library(RColorBrewer)
if(!require('grid')) install.packages('grid'); library(grid)
if(!require('gridExtra')) install.packages('gridExtra'); library(gridExtra)
# LOAD SUMMARIZED SIMULATION RESULTS ---------------------------------------------------------------
# Destination by time
import_results_desttime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_detect_v%s.csv", version)))
import_results_desttime_detect$t <- as.Date(import_results_desttime_detect$t)
t_values <- sort(unique(import_results_desttime_detect$t))
import_results_desttime_detect <- import_results_desttime_detect %>%
mutate(t = factor(as.character(t))) %>%
mutate(t_num = as.integer(t))
# Source by time, single destination
import_results_sourcetime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_sourcetime_detect_v%s.csv", version)))
import_results_sourcetime_detect$t <- as.Date(import_results_sourcetime_detect$t)
t_values <- sort(unique(import_results_sourcetime_detect$t))
import_results_sourcetime_detect <- import_results_sourcetime_detect %>%
mutate(t = factor(as.character(t))) %>%
mutate(t_num = as.integer(t))
#
# # Destination by time, Cumulative
# import_results_desttime_cum <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_cumulative_detect_v%s.csv", version)))
# import_results_desttime_cum$t <- as.Date(import_results_desttime_cum$t)
# t_values <- sort(unique(import_results_desttime_cum$t))
# import_results_desttime_cum <- import_results_desttime_cum %>%
# mutate(t = factor(as.character(t))) %>%
# mutate(t_num = as.integer(t))
# t_limits <- as.Date(c("2020-01-01","2020-01-27"))
if (!exists("t_limits")){ t_limits <- range(t_values) }
#
# # FUNCTIONS ---------------------------------------------------------------
#
# plot_imports <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2]))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean)) +
# #geom_hline(yintercept=0)+
# geom_line(aes(color='Detected', linetype="Detected"), size=1.2) +
# geom_ribbon(aes(ymin=import_ll, ymax=import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") +
# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0,0.25), "cm"))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# plot_imports_barchart <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3",
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2]))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill='Detected')) +
# geom_bar(stat="identity", color="black") +
# geom_errorbar(aes(ymin=import_ll, ymax=import_ul), width=.4) +
# ylab("Detected imported nCoV cases (n)") +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0.25,0.25), "cm")) +
# guides(fill=guide_legend(title = element_blank()))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# # Barchart plot of importations stacked by source
# plot_imports_stackedsource <- function(data=import_results_sourcetime, t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 8, leg.title.size = 10,
# rep_col = "indianred2", est_col = "blue3",
# time_int = 5){ # time interval for x-axis
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# t_values <- as.character(unique(sort(data$t)))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=source)) +
# geom_bar(position="stack", stat="identity", color="black") +
# ylab("Detected imported nCoV cases (n)") +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20),
# legend.key.size=unit(8, "pt"),
# legend.key = element_blank(),
# legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025),
# plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) +
# guides(fill=guide_legend(title = element_blank(), ncol=1))
# return(p)
# }
#
#
#
#
#
#
# # For plotting importions from multiple regions
# plot_imports_byregion <- function(data=import_results_desttime_byregion, t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# plot_legend=TRUE){
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
#
# p <- ggplot(data=data, aes(x=t_num, color=region, fill=region)) +
# geom_line(data=data, aes(y=import_mean), size=1.2) +
# geom_ribbon(data=data, aes(ymin=import_ll, ymax=import_ul, fill=region), alpha=est_ribbon_alpha) +
# #geom_line(data=data, aes(y=rep_import, color="Reported"), size=1.2) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(name="Imported cases", values=c(Reported=rep_col, Estimated=est_col)) +
# scale_color_manual(values=c("grey50", brewer.pal(3,"Dark2"), "red"), guide=guide_legend(title="Detected imported cases")) +
#
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size), axis.text.x = element_text(size=x.size, angle = 90, hjust = 1),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.1, .90), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.margin = unit(c(.5,1,.25,.25), "cm"))
#
# p + facet_grid(region ~ .)
#
#
# return(p)
# }
#
#
#
#
# plot_cum_imports <- function(data=import_results_desttime_cum, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (region_!="All"){
# data <- data %>% filter(region==region_)
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=cum_import_mean)) +
# geom_line(data=data, aes(color='Detected', linetype="Detected"), size=1.2) +
# geom_ribbon(data=data, aes(ymin=cum_import_ll, ymax=cum_import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") +
# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0,0.25), "cm"))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# # PLOT SPECIFICS
#
# y.size = x.size = 9
# leg.text.size = 12
# leg.title.size = 14
#
# rep_col <- "indianred2"
# est_col <- "blue3"
# est_ribbon_col <- "blue3"
# est_ribbon_alpha <- 0.2
#
# # PLOT TOTAL IMPORTATIONS -------------------------------------------------
#
# p_total <- plot_imports(data=import_results_desttime, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# est_ribbon_col = "blue3",
# est_ribbon_alpha=0.25,
# plot_legend=TRUE)
# #plot(p_total)
#
#
# p_total_barchart <- plot_imports_barchart(data=import_results_desttime, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# plot_legend=TRUE)
# #plot(p_total_barchart)
#
#
#
# p_cum <- plot_cum_imports(data=import_results_desttime_cum, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# est_ribbon_col = "blue3",
# est_ribbon_alpha=0.25,
# plot_legend=TRUE)
#
# # Plot 2 plots together
# #gridExtra::grid.arrange(p_total, p_cum, nrow=2)
#
#
#
# p_stacked_barchart <- plot_imports_stackedsource(data=import_results_sourcetime, t_limits=t_limits,
# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8,
# rep_col = "indianred2",
# est_col = "blue3")
# # plot(p_stacked_barchart)
#
# p_stackeddest_barchart <- plot_imports_stackeddest(data=import_results_desttime, t_limits=t_limits,
# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8,
# rep_col = "indianred2",
# est_col = "blue3")
#
#
#
#
#
# # PLOT ESTIMATED VS REPORTED ----------------------------------------------
#
# # Reported from CDC
# shen_cases <- read_csv("data/shenzhen_data/shenzhen_case_counts.csv")
# shen_cases <- shen_cases %>% mutate(cum_cases = cumsum(count))
# # From Linelists
# ll_data <- read_csv("data/linelist_current.csv")
# shen_rows <- apply(ll_data, 1, FUN=function(x) sum(grepl("shenzhen", x, ignore.case = TRUE)))>0
# ll_data_shenzhen <- ll_data[shen_rows, ]
# shen_data_aggr <- ll_data_shenzhen %>% count(date_confirmation)
# rm(ll_data, ll_data_shenzhen, shen_rows)
#
# shen_counts <- full_join(shen_cases %>% rename(count_CDC = count),
# shen_data_aggr %>% rename(count_ll = n, date=date_confirmation),
# by=c("date"="date"))
# shen_counts[is.na(shen_counts)] <- 0
#
# # Merge with estimates
# shen_counts_all <- full_join(shen_counts,
# import_results_desttime %>% select(date=t, import_mean, import_ll, import_ul) %>% mutate(date = as.Date(date)), by=c("date"))
# shen_counts_all <- full_join(shen_counts_all,
# import_results_desttime_cum %>% select(date=t, cum_import_mean, cum_import_ll, cum_import_ul) %>% mutate(date = as.Date(date)), by=c("date"))
#
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# shen_counts_all <- shen_counts_all %>% rowwise %>% filter(as.Date(date) >= as.Date(t_limits[1]) & as.Date(date) <= as.Date(t_limits[2])) %>% as.data.frame()
# }
#
#
# p_incid_shen_inclest <- ggplot(shen_counts_all %>% mutate(label1 = "CDC counts", label2 = "Linelist counts", label3="Est. detected imports"),
# aes(x=date, y=count_CDC)) +
# geom_bar(stat="identity", aes(fill=label1)) +
# geom_point(aes(x=date,y=count_ll, shape=label2, color=label2), size=2) +
# geom_point(aes(x=date,y=import_mean, shape=label3, color=label3), size=2) +
# scale_color_manual(values=c("maroon","green")) +
# scale_fill_manual(values=c("navy")) +
# ylab("Reported Cases") + ggtitle("Shenzhen Reported nCoV Cases") +
# theme_classic() +
# theme(#legend.background = element_rect(color="grey"),
# legend.position = c(0.05, 1),
# legend.justification = c(0, 1),
# legend.title = element_blank())
# #plot(p_incid_shen_inclest)
#
#
#
# # Plot cumulative cases in Shenzhen
# # Get cumulative case counts in each
# shen_counts_cum <- shen_counts_all %>% arrange(as.character(date)) %>% mutate(cum_CDC = cumsum(count_CDC), cum_ll = cumsum(count_ll))
#
#
# p_cum_shen_inclest <- ggplot(shen_counts_cum %>% mutate(label1 = "CDC cumulative", label2 = "Linelist cumulative", label3="Est. detected imports"),
# aes(x=date, y=cum_CDC)) +
# geom_bar(stat="identity", aes(fill=label1)) +
# geom_point(aes(x=date,y=cum_ll, shape=label2, color=label2), size=2) +
# geom_point(aes(x=date,y=cum_import_mean, shape=label3, color=label3), size=2) +
# scale_color_manual(values=c("maroon","green")) +
# scale_fill_manual(values=c("navy")) +
# ylab("Cumulative Cases") + ggtitle("Shenzhen Cumulative nCoV Cases") +
# coord_cartesian() +
# theme_classic() +
# theme(#legend.background = element_rect(color="grey"),
# legend.position = c(0.05, 1),
# legend.justification = c(0, 1),
# legend.title = element_blank())
# #plot(p_cum_shen_inclest)
#
#
HopkinsIDD/covidImportation documentation built on Sept. 14, 2020, 2:43 p.m.
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##' Plot the estimated and reported number of importations over time
##'
##' Author: Shaun Truelove
##' email: shauntruelove@jhu.edu
##' Updated: 31 Jan 2020
# SETUP -------------------------------------------------------------------
if (!exists("version")){ version <- "1" }
if (!exists("batch")){ batch <- "1" }
if (!exists("project_name")){ project_name <- "california_import" }
import_sim_file <- file.path("output",project_name, sprintf("covid_importation_sim_%s_batch_detect_v%s.RData", batch, version))
options(scipen=999)
if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse)
if(!require('RColorBrewer')) install.packages('RColorBrewer'); library(RColorBrewer)
if(!require('grid')) install.packages('grid'); library(grid)
if(!require('gridExtra')) install.packages('gridExtra'); library(gridExtra)
# LOAD SUMMARIZED SIMULATION RESULTS ---------------------------------------------------------------
# Destination by time
import_results_desttime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_detect_v%s.csv", version)))
import_results_desttime_detect$t <- as.Date(import_results_desttime_detect$t)
t_values <- sort(unique(import_results_desttime_detect$t))
import_results_desttime_detect <- import_results_desttime_detect %>%
mutate(t = factor(as.character(t))) %>%
mutate(t_num = as.integer(t))
# Source by time, single destination
import_results_sourcetime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_sourcetime_detect_v%s.csv", version)))
import_results_sourcetime_detect$t <- as.Date(import_results_sourcetime_detect$t)
t_values <- sort(unique(import_results_sourcetime_detect$t))
import_results_sourcetime_detect <- import_results_sourcetime_detect %>%
mutate(t = factor(as.character(t))) %>%
mutate(t_num = as.integer(t))
#
# # Destination by time, Cumulative
# import_results_desttime_cum <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_cumulative_detect_v%s.csv", version)))
# import_results_desttime_cum$t <- as.Date(import_results_desttime_cum$t)
# t_values <- sort(unique(import_results_desttime_cum$t))
# import_results_desttime_cum <- import_results_desttime_cum %>%
# mutate(t = factor(as.character(t))) %>%
# mutate(t_num = as.integer(t))
# t_limits <- as.Date(c("2020-01-01","2020-01-27"))
if (!exists("t_limits")){ t_limits <- range(t_values) }
#
# # FUNCTIONS ---------------------------------------------------------------
#
# plot_imports <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2]))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean)) +
# #geom_hline(yintercept=0)+
# geom_line(aes(color='Detected', linetype="Detected"), size=1.2) +
# geom_ribbon(aes(ymin=import_ll, ymax=import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") +
# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0,0.25), "cm"))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# plot_imports_barchart <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3",
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2]))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill='Detected')) +
# geom_bar(stat="identity", color="black") +
# geom_errorbar(aes(ymin=import_ll, ymax=import_ul), width=.4) +
# ylab("Detected imported nCoV cases (n)") +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0.25,0.25), "cm")) +
# guides(fill=guide_legend(title = element_blank()))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# # Barchart plot of importations stacked by source
# plot_imports_stackedsource <- function(data=import_results_sourcetime, t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 8, leg.title.size = 10,
# rep_col = "indianred2", est_col = "blue3",
# time_int = 5){ # time interval for x-axis
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# t_values <- as.character(unique(sort(data$t)))
#
# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=source)) +
# geom_bar(position="stack", stat="identity", color="black") +
# ylab("Detected imported nCoV cases (n)") +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20),
# legend.key.size=unit(8, "pt"),
# legend.key = element_blank(),
# legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025),
# plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) +
# guides(fill=guide_legend(title = element_blank(), ncol=1))
# return(p)
# }
#
#
#
#
#
#
# # For plotting importions from multiple regions
# plot_imports_byregion <- function(data=import_results_desttime_byregion, t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# plot_legend=TRUE){
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
#
# p <- ggplot(data=data, aes(x=t_num, color=region, fill=region)) +
# geom_line(data=data, aes(y=import_mean), size=1.2) +
# geom_ribbon(data=data, aes(ymin=import_ll, ymax=import_ul, fill=region), alpha=est_ribbon_alpha) +
# #geom_line(data=data, aes(y=rep_import, color="Reported"), size=1.2) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(name="Imported cases", values=c(Reported=rep_col, Estimated=est_col)) +
# scale_color_manual(values=c("grey50", brewer.pal(3,"Dark2"), "red"), guide=guide_legend(title="Detected imported cases")) +
#
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size), axis.text.x = element_text(size=x.size, angle = 90, hjust = 1),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.1, .90), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.margin = unit(c(.5,1,.25,.25), "cm"))
#
# p + facet_grid(region ~ .)
#
#
# return(p)
# }
#
#
#
#
# plot_cum_imports <- function(data=import_results_desttime_cum, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")),
# y.size = 9, x.size = 9,
# leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25,
# time_int = 5, # time interval for x-axis
# plot_legend=TRUE, x_axis=TRUE){
# # Subset by region if wanted
# if (region_!="All"){
# data <- data %>% filter(region==region_)
# }
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# data <- data %>% mutate(t = as.Date(t)) %>%
# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>%
# mutate(t_num = as.integer(as.factor(t)))
# }
# t_values <- as.character(sort(data$t))
#
# p <- ggplot(data=data, aes(x=t_num, y=cum_import_mean)) +
# geom_line(data=data, aes(color='Detected', linetype="Detected"), size=1.2) +
# geom_ribbon(data=data, aes(ymin=cum_import_ll, ymax=cum_import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) +
# scale_x_continuous(breaks=seq(1,length(t_values),time_int),
# labels=t_values[seq(1,length(t_values),time_int)]) +
# ylab("Detected imported nCoV cases (n)") +
# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") +
# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) +
# scale_colour_manual(values=c(Detected=est_col), guide="none") +
# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) +
# #scale_y_continuous(expand = c(0,0)) +
# theme(axis.line = element_line(colour = "black"),
# panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
# panel.border = element_blank(), panel.background=element_blank(),
# axis.text.y = element_text(size=y.size),
# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)),
# axis.title.x = element_blank(),
# legend.title=element_text(size=leg.title.size),
# legend.text=element_text(size=leg.text.size), # legend text size
# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20),
# legend.key.size=unit(15, "pt"), # Change key size in the legend
# legend.key = element_blank(),
# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(),
# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025),
# plot.margin = unit(c(-.75,.25,0,0.25), "cm"))
#
# if (region_ != "All"){
# p <- p + ggtitle(region_)
# }
# if (plot_legend==FALSE){
# p <- p + theme(legend.position = "none")
# }
# if (x_axis==FALSE){
# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(),
# axis.ticks.x=element_blank(), axis.title.x=element_blank())
# }
# return(p)
# }
#
#
# # PLOT SPECIFICS
#
# y.size = x.size = 9
# leg.text.size = 12
# leg.title.size = 14
#
# rep_col <- "indianred2"
# est_col <- "blue3"
# est_ribbon_col <- "blue3"
# est_ribbon_alpha <- 0.2
#
# # PLOT TOTAL IMPORTATIONS -------------------------------------------------
#
# p_total <- plot_imports(data=import_results_desttime, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# est_ribbon_col = "blue3",
# est_ribbon_alpha=0.25,
# plot_legend=TRUE)
# #plot(p_total)
#
#
# p_total_barchart <- plot_imports_barchart(data=import_results_desttime, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# plot_legend=TRUE)
# #plot(p_total_barchart)
#
#
#
# p_cum <- plot_cum_imports(data=import_results_desttime_cum, region_ = "All", t_limits=t_limits,
# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14,
# rep_col = "indianred2",
# est_col = "blue3",
# est_ribbon_col = "blue3",
# est_ribbon_alpha=0.25,
# plot_legend=TRUE)
#
# # Plot 2 plots together
# #gridExtra::grid.arrange(p_total, p_cum, nrow=2)
#
#
#
# p_stacked_barchart <- plot_imports_stackedsource(data=import_results_sourcetime, t_limits=t_limits,
# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8,
# rep_col = "indianred2",
# est_col = "blue3")
# # plot(p_stacked_barchart)
#
# p_stackeddest_barchart <- plot_imports_stackeddest(data=import_results_desttime, t_limits=t_limits,
# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8,
# rep_col = "indianred2",
# est_col = "blue3")
#
#
#
#
#
# # PLOT ESTIMATED VS REPORTED ----------------------------------------------
#
# # Reported from CDC
# shen_cases <- read_csv("data/shenzhen_data/shenzhen_case_counts.csv")
# shen_cases <- shen_cases %>% mutate(cum_cases = cumsum(count))
# # From Linelists
# ll_data <- read_csv("data/linelist_current.csv")
# shen_rows <- apply(ll_data, 1, FUN=function(x) sum(grepl("shenzhen", x, ignore.case = TRUE)))>0
# ll_data_shenzhen <- ll_data[shen_rows, ]
# shen_data_aggr <- ll_data_shenzhen %>% count(date_confirmation)
# rm(ll_data, ll_data_shenzhen, shen_rows)
#
# shen_counts <- full_join(shen_cases %>% rename(count_CDC = count),
# shen_data_aggr %>% rename(count_ll = n, date=date_confirmation),
# by=c("date"="date"))
# shen_counts[is.na(shen_counts)] <- 0
#
# # Merge with estimates
# shen_counts_all <- full_join(shen_counts,
# import_results_desttime %>% select(date=t, import_mean, import_ll, import_ul) %>% mutate(date = as.Date(date)), by=c("date"))
# shen_counts_all <- full_join(shen_counts_all,
# import_results_desttime_cum %>% select(date=t, cum_import_mean, cum_import_ll, cum_import_ul) %>% mutate(date = as.Date(date)), by=c("date"))
#
#
# # Limit the time of the plots
# if (!is.na(t_limits[1])){
# shen_counts_all <- shen_counts_all %>% rowwise %>% filter(as.Date(date) >= as.Date(t_limits[1]) & as.Date(date) <= as.Date(t_limits[2])) %>% as.data.frame()
# }
#
#
# p_incid_shen_inclest <- ggplot(shen_counts_all %>% mutate(label1 = "CDC counts", label2 = "Linelist counts", label3="Est. detected imports"),
# aes(x=date, y=count_CDC)) +
# geom_bar(stat="identity", aes(fill=label1)) +
# geom_point(aes(x=date,y=count_ll, shape=label2, color=label2), size=2) +
# geom_point(aes(x=date,y=import_mean, shape=label3, color=label3), size=2) +
# scale_color_manual(values=c("maroon","green")) +
# scale_fill_manual(values=c("navy")) +
# ylab("Reported Cases") + ggtitle("Shenzhen Reported nCoV Cases") +
# theme_classic() +
# theme(#legend.background = element_rect(color="grey"),
# legend.position = c(0.05, 1),
# legend.justification = c(0, 1),
# legend.title = element_blank())
# #plot(p_incid_shen_inclest)
#
#
#
# # Plot cumulative cases in Shenzhen
# # Get cumulative case counts in each
# shen_counts_cum <- shen_counts_all %>% arrange(as.character(date)) %>% mutate(cum_CDC = cumsum(count_CDC), cum_ll = cumsum(count_ll))
#
#
# p_cum_shen_inclest <- ggplot(shen_counts_cum %>% mutate(label1 = "CDC cumulative", label2 = "Linelist cumulative", label3="Est. detected imports"),
# aes(x=date, y=cum_CDC)) +
# geom_bar(stat="identity", aes(fill=label1)) +
# geom_point(aes(x=date,y=cum_ll, shape=label2, color=label2), size=2) +
# geom_point(aes(x=date,y=cum_import_mean, shape=label3, color=label3), size=2) +
# scale_color_manual(values=c("maroon","green")) +
# scale_fill_manual(values=c("navy")) +
# ylab("Cumulative Cases") + ggtitle("Shenzhen Cumulative nCoV Cases") +
# coord_cartesian() +
# theme_classic() +
# theme(#legend.background = element_rect(color="grey"),
# legend.position = c(0.05, 1),
# legend.justification = c(0, 1),
# legend.title = element_blank())
# #plot(p_cum_shen_inclest)
#
#
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