plot.default(log(cumsum(mdf[,13])[1:543]),log(cumsum(dmdf[,13])[21:563]))
par()$usr
# > par()$usr
# [1] -0.4845012 12.5970321 -0.3095047 8.0471209
plot.default(log(cumsum(mdf[,13])[1:543]),log(cumsum(dmdf[,13])[21:563]),xlim=c(-0.48,12.59),ylim=c(-0.309,8.0471))
par(new=T)
plot.default(log(cumsum(mdf[,13])[1:543]),log(0.01*cumsum(mdf[,13])[1:543]),xlim=c(-0.48,12.59),ylim=c(-0.309,8.0471),type='l')
par(new=T)
plot.default(log(cumsum(mdf[,13])[1:543]),log(0.02*cumsum(mdf[,13])[1:543]),xlim=c(-0.48,12.59),ylim=c(-0.309,8.0471),type='l')
gap <- 20 # shift between positive and death. as new death only comes out after certain number of days of positive.
start <- 500 # day of start should be less than length(mdf$t) - gap 500 means "2021-05-30"
end <- 0 # day to end. 0 means the end of record.
dmdf$t[start]
if(end == 0){
end <- length(mdf[,13])
}
d <- dmdf[,13][(gap+start):(end)] %>% cumsum()
p <- mdf[,13][start:(end-gap)] %>% cumsum()
df <- data.frame(death=d,positive=p)
# p <- ggplot(df, aes(x = positive, y = death))
# p <- p + geom_point(stat="identity", position="identity")
df <- cbind(df,twopercent=df$positive * 0.02)
df <- cbind(df,onepointfive=df$positive * 0.015)
df <- cbind(df,onepercent=df$positive * 0.01)
df <- cbind(df,halfpercent=df$positive * 0.005)
df <- cbind(df,qpercent=df$positive * 0.0025)
p <- ggplot(df, aes(x = positive, y = death))
p <- p + geom_point(stat="identity", position="identity")
p <- p + geom_path(aes(y=twopercent))
p <- p + geom_path(aes(y=onepointfive))
p <- p + geom_path(aes(y=onepercent))
p <- p + geom_path(aes(y=halfpercent))
p <- p + geom_path(aes(y=qpercent))
plot(p)
