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# Load packages
library(epinowcast)
library(data.table)
library(ggplot2)

# Load and filter germany hospitalisations
nat_germany_hosp <- germany_covid19_hosp[location == "DE"][age_group %in% "00+"]
nat_germany_hosp <- enw_filter_report_dates(
  nat_germany_hosp,
  latest_date = "2021-10-01"

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# Load packages
library(brms)
library(cmdstanr)
library(data.table) # here we use the development version of data.table install it with data.table::update_dev_pkg
library(purrr)

# Set up parallel cores
options(mc.cores = 4)

# Simulate some truncated and truncation data

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functions{ 
#include functions/ct_trajectory.stan
#include functions/truncated_normal_rng.stan
#include functions/censor.stan
}

data {
  int P; // number of patients
  int N; // number of tests
  real c_lod; // Ct value at limit of detection 

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library(data.table)
library(snakecase)
library(ggplot2)

# make a convolution matrix
convolution_matrix <- function(vec1, vec2) {
  lvec1 <- length(vec1)
  lvec2 <- length(vec2)
  conv <- matrix(0, nrow = lvec1, ncol = lvec1)
  for (s in 1:lvec1) {

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library(covidregionaldata)

# set up a data cache
start_using_memoise()
#> Using a cache at: /tmp/RtmphiSeWY

# check for supported countries
get_available_datasets()
#> # A tibble: 18 x 8
#>    origin   class level_1_region level_2_region level_3_region type  data_urls  

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# Packages ----------------------------------------------------------------
require(data.table, quietly = TRUE)
require(EpiNow2, quietly = TRUE)
require(purrr)
require(ggplot2)

# Target date -------------------------------------------------------------
creation_date <- Sys.Date()
extraction_date <- creation_date

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# Packages ----------------------------------------------------------------
library(covid19.nhs.data)
library(vroom)
library(dplyr)
library(tidyr)
library(lubridate)
library(gganimate) 
#devtools::install_github("thomasp85/transformr")
library(transformr)
library(gifski)

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# Packages ----------------------------------------------------------------
library(covid19.nhs.data)
library(dplyr)
library(tidyr)
library(lubridate)
library(gganimate) 
#devtools::install_github("thomasp85/transformr")
library(transformr)
library(gifski)
library(ggplot2)

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# Packages ----------------------------------------------------------------
library(covid19.nhs.data)
library(dplyr)
library(tidyr)
library(lubridate)
library(gganimate) 
#devtools::install_github("thomasp85/transformr")
library(transformr)
library(gifski)
library(ggplot2)

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# packages
# install.packages(c("data.table", "remotes", "EpiNow2"))		
# remotes::install_github("epiforecasts/EpiNow2")
# remotes::install_github("epiforecasts/covidregionaldata")
library(data.table)
library(EpiNow2)
library(covidregionaldata)

# target country (must be supported in covidregionaldata)
country <- "uk"   # harder to fit "india"