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(v0.7.1.9021) CI fix for resistance_predict

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dr. M.S. (Matthijs) Berends
2019-08-04 10:48:41 +02:00
parent 4f3ef53c78
commit d6ab3896a1
16 changed files with 68 additions and 34 deletions
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25
R/resistance_predict.R
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@ -28,8 +28,8 @@
#' @param year_max highest year to use in the prediction model, defaults to 10 years after today
#' @param year_every unit of sequence between lowest year found in the data and \code{year_max}
#' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
#' @param model the statistical model of choice. Defaults to a generalised linear regression model with binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for valid options.
#' @param I_as_S a logical to indicate whether values \code{I} should be treated as \code{S}
#' @param model the statistical model of choice. Defaults to a generalised linear regression model with binomial distribution (i.e. using \code{\link{glm}(..., family = \link{binomial})}), assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for valid options.
#' @param I_as_S a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R})
#' @param preserve_measurements a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.
#' @param main title of the plot
@ -162,18 +162,19 @@ resistance_predict <- function(x,
as.integer(format(as.Date(x), '%Y'))
}
}
df <- x %>%
mutate_at(col_ab, as.rsi) %>%
mutate_at(col_ab, droplevels) %>%
mutate_at(col_ab, ~(
if (I_as_S == TRUE) {
gsub("I", "S", .)
} else {
# then I as R
gsub("I", "R", .)
}
)) %>%
mutate_at(col_ab, droplevels)
if (I_as_S == TRUE) {
df <- df %>%
mutate_at(col_ab, ~gsub("I", "S", .))
} else {
# then I as R
df <- df %>%
mutate_at(col_ab, ~gsub("I", "R", .))
}
df <- df %>%
filter_at(col_ab, all_vars(!is.na(.))) %>%
mutate(year = pull(., col_date) %>% year()) %>%
group_by_at(c('year', col_ab)) %>%