find_previous_number_of_survivors: Find the previous measurement number of animals alive after...

In konkam/RTTanalyse: Analysis of Rapid Toxicity Tests data using a hierarchical model

Description

The long dataset is obtained using gather_(dataset, "time", "number_alive", time_cols). test_id must by a variable identifying in an unique manner the replicate. The dataset must not contain NAs.

Usage

find_previous_number_of_survivors(long_dataset, tprec, test_id_)

Arguments

long_dataset	A dataset in the long format, with one line for each measurement in time.
tprec	The time for which we want to compute the preceding time.
test_id_	A unique identifier for each replicate.

Value

The previous time found in the dataset.

Examples

dataset = read_csv('data/RTT_dataV2_ImidaclopridCorrected.csv') %>%
 mutate(test_id = seq(nrow(.)))
concentration_col = "Concentration"
species_col = "Identifier"
time_cols = c("0h", "24h", "48", "72", "R96h")
time_stamps = c(0,24,48,72,96)
ordered_time_cols = time_cols[order(time_stamps)]
make_time_col_name_time_stamp_converter = function(time_col_names, time_stamps){
  cv = c(time_col_names, time_stamps) %>% setNames(c(time_stamps, time_col_names) %>% as.character())
  cv_fun = function(ids){
    sapply(ids, function(x) cv[x])
  }
  return(cv_fun)
}
time_col_name_time_stamp_converter = make_time_col_name_time_stamp_converter(time_col_names = time_cols, time_stamps = time_stamps)

long_dataset = gather_(dataset, "time", "number_alive", time_cols) %>%
  mutate(time = time_col_name_time_stamp_converter(time) %>% as.numeric()) %>%
  subset(!is.na(number_alive)) %>%
  subset(time>0)

  find_previous_number_of_survivors(long_dataset = long_dataset, test_id = 5, find_previous_measurement_time(long_dataset = long_dataset, test_id = 5, time = 96))

konkam/RTTanalyse documentation built on May 20, 2019, 12:55 p.m.