#
# project: LTBI screening
# N Green
# April 2017
#
# plots of number of active tb cases over time
# histograms --------------------------------------------------------------
hist(ceiling(IMPUTED_sample$exituk_tb.years), col = "blue",
breaks = 150, #, xlim = c(0, 50), ylim = c(0,25),
xlab = "Time (year)", main = "")
hist_progression_times(IMPUTED_sample)
hist_progression_times(cohort)
legend('topright', c('Observed', 'EWNI', 'Outside EWNI'), col = c('red', 'green', 'blue'), lty = 1)
##TODO: update
# plot(x = 0:19,
# y = num_uk_tb_year[1:20],
# type = "o", ylim = c(0, 85),
# lty = 1,
# xlab = "Time (year)", ylab = "Frequency",
# main = "Active TB cases")
# curves ------------------------------------------------------------------
# plot(x = 0:19,
# y = num_uk_tb_year[1:20],
# type = "o", ylim = c(0, 85),
# lty = 1,
# xlab = "Time (year)", ylab = "Frequency",
# main = "Active TB cases")
#
# lines(num_exituk_tb_year, type = 'l', xlim = c(0, 20),
# col = "red") #rgb(0, 0, 0, 0.5))
#
# # lines(x = seq_along(obs_uk_tb_year) - 1,
# # y = obs_uk_tb_year,
# # type = "o",
# # col = "red")
#
# lines(x = seq_along(num_exituk_tb_year) - 1,
# y = num_exituk_tb_year,
# col = "green",
# lty = 2,
# type = 'o')
#
# lines(x = seq_along(num_all_tb_year) - 1,
# y = num_all_tb_year,
# col = "blue",
# lty = 3,
# type = 'o')
#
# legend("topright",
# # legend = c("Observed", "Estimated uk", "Estimated exit", "Total"),
# # col = c("red", "black", "green", "blue"), lty = 1)
# legend = c("Estimated uk", "Estimated exit", "Total"),
# col = c("black", "green", "blue"), lty = c(1,2,3))
# multiple samples
# for (i in 1:5) {
#
# exituk_tb.years <- sim_aTB_times(pop = pop_year,
# data = cohort,
# prob = year_prob.activetb_cens_exituk)
#
# x <- hist(exituk_tb.years,
# breaks = 100, xlim = c(0, 20), ylim = c(0,25),
# xlab = "year", main = "", plot = F)
#
# points(x$mids[x$counts > 0] + rnorm(sum(x$counts > 0), 0, 0.5),
# x$counts[x$counts > 0] + rnorm(sum(x$counts > 0), 0, 0.5),
# pch = 16, col = rgb(0, 0, 0, 0.3))
# }
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