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removed ratio, better rsi_calc, update for freq
This commit is contained in:
parent
0c0e538ef4
commit
a100d07da6
@ -1,5 +1,5 @@
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Package: AMR
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Package: AMR
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Version: 0.3.0.9002
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Version: 0.3.0.9003
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Date: 2018-08-23
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Date: 2018-08-23
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Title: Antimicrobial Resistance Analysis
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Title: Antimicrobial Resistance Analysis
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Authors@R: c(
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Authors@R: c(
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@ -79,7 +79,6 @@ export(portion_R)
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export(portion_S)
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export(portion_S)
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export(portion_SI)
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export(portion_SI)
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export(portion_df)
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export(portion_df)
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export(ratio)
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export(resistance_predict)
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export(resistance_predict)
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export(right_join_microorganisms)
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export(right_join_microorganisms)
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export(rsi)
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export(rsi)
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@ -127,7 +126,6 @@ importFrom(dplyr,arrange)
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importFrom(dplyr,arrange_at)
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importFrom(dplyr,arrange_at)
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importFrom(dplyr,as_tibble)
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importFrom(dplyr,as_tibble)
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importFrom(dplyr,between)
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importFrom(dplyr,between)
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importFrom(dplyr,bind_cols)
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importFrom(dplyr,bind_rows)
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importFrom(dplyr,bind_rows)
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importFrom(dplyr,case_when)
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importFrom(dplyr,case_when)
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importFrom(dplyr,desc)
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importFrom(dplyr,desc)
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16
NEWS.md
16
NEWS.md
@ -2,9 +2,12 @@
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#### New
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#### New
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* Functions `count_R`, `count_IR`, `count_I`, `count_SI` and `count_S` to selectively count resistant or susceptible isolates
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* Functions `count_R`, `count_IR`, `count_I`, `count_SI` and `count_S` to selectively count resistant or susceptible isolates
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* New function `count_df` to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables
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* Function `is.rsi.eligible` to check for columns that have valid antimicrobial results, but do not have the `rsi` class yet. Transform the columns of your raw data with: `data %>% mutate_if(is.rsi.eligible, as.rsi)`
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* Function `is.rsi.eligible` to check for columns that have valid antimicrobial results, but do not have the `rsi` class yet. Transform the columns of your raw data with: `data %>% mutate_if(is.rsi.eligible, as.rsi)`
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#### Changed
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#### Changed
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* Removed function `ratio`
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* Fix in `as.mic` for values ending in zeroes after a real number
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* Added parameters `minimum` and `as_percent` to `portion_df`
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* Added parameters `minimum` and `as_percent` to `portion_df`
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* Support for quasiquotation in the functions series `count_*` and `portions_*`, and `n_rsi`. This allows to check for more than 2 vectors or columns.
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* Support for quasiquotation in the functions series `count_*` and `portions_*`, and `n_rsi`. This allows to check for more than 2 vectors or columns.
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* `septic_patients %>% select(amox, cipr) %>% count_R()`
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* `septic_patients %>% select(amox, cipr) %>% count_R()`
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@ -14,6 +17,19 @@
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* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`.
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* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`.
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* Fix for `ggplot_rsi` when the `ggplot2` package was not loaded
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* Fix for `ggplot_rsi` when the `ggplot2` package was not loaded
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* Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences
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* Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences
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* Support for types list and matrix for `freq`
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```r
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my_matrix = with(septic_patients, matrix(c(age, sex), ncol = 2))
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freq(my_matrix)
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```
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* Subsetting also possible for lists:
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```r
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my_list = list(age = septic_patients$age, sex = septic_patients$sex)
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my_list %>% freq(age)
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```
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#### Other
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* More unit tests to ensure better integrity of functions
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# 0.3.0 (latest stable version)
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# 0.3.0 (latest stable version)
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**Published on CRAN: 2018-08-14**
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**Published on CRAN: 2018-08-14**
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@ -240,10 +240,13 @@ as.mic <- function(x, na.rm = FALSE) {
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# remove all after last digit
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# remove all after last digit
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x <- gsub('[^0-9]+$', '', x)
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x <- gsub('[^0-9]+$', '', x)
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# remove last zeroes
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# remove last zeroes
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x <- gsub('[.]?0+$', '', x)
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x <- gsub('([.].?)0+$', '\\1', x)
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# force to be character
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# force to be character
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x <- as.character(x)
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x <- as.character(x)
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# previously unempty values now empty - should return a warning later on
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x[x.bak != "" & x == ""] <- "invalid"
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# these are alllowed MIC values and will become factor levels
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# these are alllowed MIC values and will become factor levels
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lvls <- c("<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
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lvls <- c("<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
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"<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
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"<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
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@ -275,7 +278,7 @@ as.mic <- function(x, na.rm = FALSE) {
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"<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
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"<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
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"<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
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"<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
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"<0.28", "<=0.28", "0.28", ">=0.28", ">0.28",
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"<0.28", "<=0.28", "0.28", ">=0.28", ">0.28",
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"<0.30", "<=0.30", "0.30", ">=0.30", ">0.30",
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"<0.3", "<=0.3", "0.3", ">=0.3", ">0.3",
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"<0.32", "<=0.32", "0.32", ">=0.32", ">0.32",
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"<0.32", "<=0.32", "0.32", ">=0.32", ">0.32",
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"<0.36", "<=0.36", "0.36", ">=0.36", ">0.36",
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"<0.36", "<=0.36", "0.36", ">=0.36", ">0.36",
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"<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
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"<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
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35
R/freq.R
35
R/freq.R
@ -152,22 +152,39 @@ frequency_tbl <- function(x,
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mult.columns <- 0
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mult.columns <- 0
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x.name <- NULL
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cols <- NULL
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if (any(class(x) == 'list')) {
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cols <- names(x)
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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x.name <- "a list"
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} else if (any(class(x) == 'matrix')) {
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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x.name <- "a matrix"
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cols <- colnames(x)
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if (all(cols %like% 'V[0-9]')) {
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cols <- NULL
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}
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}
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if (any(class(x) == 'data.frame')) {
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if (any(class(x) == 'data.frame')) {
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x.name <- deparse(substitute(x))
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if (is.null(x.name)) {
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x.name <- deparse(substitute(x))
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}
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if (x.name == ".") {
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if (x.name == ".") {
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x.name <- NULL
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x.name <- NULL
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}
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}
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dots <- base::eval(base::substitute(base::alist(...)))
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dots <- base::eval(base::substitute(base::alist(...)))
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ndots <- length(dots)
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ndots <- length(dots)
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if (NROW(x) == 0) {
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if (ndots < 10) {
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x <- NA
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} else if (ndots > 0 & ndots < 10) {
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cols <- as.character(dots)
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cols <- as.character(dots)
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if (!all(cols %in% colnames(x))) {
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if (!all(cols %in% colnames(x))) {
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stop("one or more columns not found: `", paste(cols, collapse = "`, `"), '`', call. = FALSE)
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stop("one or more columns not found: `", paste(cols, collapse = "`, `"), '`', call. = FALSE)
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}
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}
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x <- x[, cols]
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if (length(cols) > 0) {
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x <- x[, cols]
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}
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} else if (ndots >= 10) {
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} else if (ndots >= 10) {
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stop('A maximum of 9 columns can be analysed at the same time.', call. = FALSE)
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stop('A maximum of 9 columns can be analysed at the same time.', call. = FALSE)
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} else {
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} else {
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@ -298,10 +315,6 @@ frequency_tbl <- function(x,
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header <- header %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > "))
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header <- header %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > "))
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}
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}
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if (is.list(x) | is.matrix(x) | is.environment(x) | is.function(x)) {
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stop('frequency tables do not support lists, matrices, environments and functions.', call. = FALSE)
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}
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header <- header %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(),
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header <- header %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(),
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' (of which NA: ', NAs %>% length() %>% format(),
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' (of which NA: ', NAs %>% length() %>% format(),
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' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>% percent(force_zero = TRUE, round = digits) %>% sub('NaN', '0', ., fixed = TRUE), ')')
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' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>% percent(force_zero = TRUE, round = digits) %>% sub('NaN', '0', ., fixed = TRUE), ')')
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@ -485,6 +498,10 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
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opt <- attr(x, 'opt')
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opt <- attr(x, 'opt')
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if (length(opt$vars) == 0) {
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opt$vars <- NULL
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}
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if (!is.null(opt$data) & !is.null(opt$vars)) {
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if (!is.null(opt$data) & !is.null(opt$vars)) {
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title <- paste0("of `", paste0(opt$vars, collapse = "` and `"), "` from ", opt$data)
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title <- paste0("of `", paste0(opt$vars, collapse = "` and `"), "` from ", opt$data)
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} else if (!is.null(opt$data) & is.null(opt$vars)) {
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} else if (!is.null(opt$data) & is.null(opt$vars)) {
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33
R/g.test.R
33
R/g.test.R
@ -79,11 +79,7 @@
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#' # by a single gene with two co-dominant alleles, you would expect a 1:2:1
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#' # by a single gene with two co-dominant alleles, you would expect a 1:2:1
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#' # ratio.
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#' # ratio.
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#'
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#'
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#' x <- c(772, 1611, 737)
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#' x <- c(772, 1611, 737)#'
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#' E <- ratio(x, "1:2:1")
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#' E
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#' # 780 1560 780
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#'
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#' G <- g.test(x, p = c(1, 2, 1) / 4)
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#' G <- g.test(x, p = c(1, 2, 1) / 4)
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#' # G$p.value = 0.12574.
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#' # G$p.value = 0.12574.
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#'
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#'
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@ -228,30 +224,3 @@ g.test <- function(x,
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observed = x, expected = E, residuals = (x - E)/sqrt(E),
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observed = x, expected = E, residuals = (x - E)/sqrt(E),
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stdres = (x - E)/sqrt(V)), class = "htest")
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stdres = (x - E)/sqrt(V)), class = "htest")
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}
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}
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#' Transform vector to ratio
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#' @param x vector of values
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#' @param ratio vector with ratios of \code{x} and with same length (like \code{ratio = c(1, 2, 1)}) or a text with characters \code{":"}, \code{"-"} or \code{","} (like \code{ratio = "1:2:1"} or even \code{ratio = "1:2:1.25"})
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#' @export
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#' @seealso \code{\link{g.test}}
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#' @references McDonald, J.H. 2014. \strong{Handbook of Biological Statistics (3rd ed.)}. Sparky House Publishing, Baltimore, Maryland.
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#' @importFrom dplyr %>%
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#' @inherit g.test examples
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ratio <- function(x, ratio) {
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if (!all(is.numeric(x))) {
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stop('`x` must be a vector of numeric values.')
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}
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if (length(ratio) == 1) {
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if (ratio %like% '^([0-9]+([.][0-9]+)?[-,:])+[0-9]+([.][0-9]+)?$') {
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# support for "1:2:1", "1-2-1", "1,2,1" and even "1.75:2:1.5"
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ratio <- ratio %>% base::strsplit("[-,:]") %>% base::unlist() %>% base::as.double()
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} else {
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stop('Invalid `ratio`: ', ratio, '.')
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}
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}
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if (length(x) != length(ratio)) {
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stop('`x` and `ratio` must be of same size.')
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}
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base::sum(x, na.rm = TRUE) * (ratio / base::sum(ratio, na.rm = TRUE))
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}
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45
R/rsi_calc.R
45
R/rsi_calc.R
@ -16,7 +16,7 @@
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# GNU General Public License for more details. #
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# GNU General Public License for more details. #
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# ==================================================================== #
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# ==================================================================== #
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#' @importFrom dplyr %>% bind_cols pull
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#' @importFrom dplyr %>% pull
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rsi_calc <- function(...,
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rsi_calc <- function(...,
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type,
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type,
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include_I,
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include_I,
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@ -34,33 +34,36 @@ rsi_calc <- function(...,
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stop('`as_percent` must be logical', call. = FALSE)
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stop('`as_percent` must be logical', call. = FALSE)
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}
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}
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dots_length <- ...length()
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dots_df <- ...elt(1) # it needs this evaluation
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dots <- ...elt(1) # it needs this evaluation
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dots <- base::eval(base::substitute(base::alist(...)))
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dots <- rlang::exprs(...) # or this will be a list without actual values
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ndots <- length(dots)
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if ("data.frame" %in% class(dots[[1]]) & dots_length > 1) {
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if ("data.frame" %in% class(dots_df)) {
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# data.frame passed with other columns, like:
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# data.frame passed with other columns, like:
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# septic_patients %>% portion_S(amcl, gent)
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# septic_patients %>% portion_S(amcl, gent)
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df <- dots[[1]]
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dots <- as.character(dots)
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dots_df <- data.frame(col1 = df[,1])
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dots <- dots[dots != "."]
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for (i in 2:dots_length) {
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if (length(dots) == 0 | all(dots == "df")) {
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dots_col <- as.character(dots[[i]])
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# for complete data.frames, like septic_patients %>% select(amcl, gent) %>% portion_S()
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if (!dots_col %in% colnames(df)) {
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# and the old rsi function, that has "df" as name of the first parameter
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stop("variable not found: ", dots_col)
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x <- dots_df
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}
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} else {
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dots_df <- dots_df %>% bind_cols(data.frame(df %>% pull(dots_col)))
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x <- dots_df[, dots]
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}
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}
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x <- dots_df[, -1]
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} else if (ndots == 1) {
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} else if (dots_length == 1) {
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# only 1 variable passed (can also be data.frame), like:
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# only 1 variable passed (count also be data.frame), like:
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# portion_S(septic_patients$amcl)
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# portion_S(septic_patients$amcl)
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# septic_patients$amcl %>% portion_S()
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# septic_patients$amcl %>% portion_S()
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x <- dots[[1]]
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x <- dots_df
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} else {
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} else {
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# multiple variables passed without pipe, like:
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# multiple variables passed without pipe, like:
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# portion_S(septic_patients$amcl, septic_patients$gent)
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# portion_S(septic_patients$amcl, septic_patients$gent)
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# with(septic_patients, portion_S(amcl, gent))
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x <- NULL
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x <- as.data.frame(rlang::list2(...))
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try(x <- as.data.frame(dots), silent = TRUE)
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if (is.null(x)) {
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# support for: with(septic_patients, portion_S(amcl, gent))
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x <- as.data.frame(rlang::list2(...))
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}
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}
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}
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print_warning <- FALSE
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print_warning <- FALSE
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@ -110,11 +110,7 @@ If there are more than two categories and you want to find out which ones are si
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# by a single gene with two co-dominant alleles, you would expect a 1:2:1
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# by a single gene with two co-dominant alleles, you would expect a 1:2:1
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# ratio.
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# ratio.
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x <- c(772, 1611, 737)
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x <- c(772, 1611, 737)#'
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E <- ratio(x, "1:2:1")
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E
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# 780 1560 780
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G <- g.test(x, p = c(1, 2, 1) / 4)
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G <- g.test(x, p = c(1, 2, 1) / 4)
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# G$p.value = 0.12574.
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# G$p.value = 0.12574.
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60
man/ratio.Rd
60
man/ratio.Rd
@ -1,60 +0,0 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/g.test.R
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\name{ratio}
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\alias{ratio}
|
|
||||||
\title{Transform vector to ratio}
|
|
||||||
\usage{
|
|
||||||
ratio(x, ratio)
|
|
||||||
}
|
|
||||||
\arguments{
|
|
||||||
\item{x}{vector of values}
|
|
||||||
|
|
||||||
\item{ratio}{vector with ratios of \code{x} and with same length (like \code{ratio = c(1, 2, 1)}) or a text with characters \code{":"}, \code{"-"} or \code{","} (like \code{ratio = "1:2:1"} or even \code{ratio = "1:2:1.25"})}
|
|
||||||
}
|
|
||||||
\description{
|
|
||||||
Transform vector to ratio
|
|
||||||
}
|
|
||||||
\examples{
|
|
||||||
# = EXAMPLE 1 =
|
|
||||||
# Shivrain et al. (2006) crossed clearfield rice (which are resistant
|
|
||||||
# to the herbicide imazethapyr) with red rice (which are susceptible to
|
|
||||||
# imazethapyr). They then crossed the hybrid offspring and examined the
|
|
||||||
# F2 generation, where they found 772 resistant plants, 1611 moderately
|
|
||||||
# resistant plants, and 737 susceptible plants. If resistance is controlled
|
|
||||||
# by a single gene with two co-dominant alleles, you would expect a 1:2:1
|
|
||||||
# ratio.
|
|
||||||
|
|
||||||
x <- c(772, 1611, 737)
|
|
||||||
E <- ratio(x, "1:2:1")
|
|
||||||
E
|
|
||||||
# 780 1560 780
|
|
||||||
|
|
||||||
G <- g.test(x, p = c(1, 2, 1) / 4)
|
|
||||||
# G$p.value = 0.12574.
|
|
||||||
|
|
||||||
# There is no significant difference from a 1:2:1 ratio.
|
|
||||||
# Meaning: resistance controlled by a single gene with two co-dominant
|
|
||||||
# alleles, is plausible.
|
|
||||||
|
|
||||||
|
|
||||||
# = EXAMPLE 2 =
|
|
||||||
# Red crossbills (Loxia curvirostra) have the tip of the upper bill either
|
|
||||||
# right or left of the lower bill, which helps them extract seeds from pine
|
|
||||||
# cones. Some have hypothesized that frequency-dependent selection would
|
|
||||||
# keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992)
|
|
||||||
# observed 1752 right-billed and 1895 left-billed crossbills.
|
|
||||||
|
|
||||||
x <- c(1752, 1895)
|
|
||||||
g.test(x)
|
|
||||||
# p = 0.01787343
|
|
||||||
|
|
||||||
# There is a significant difference from a 1:1 ratio.
|
|
||||||
# Meaning: there are significantly more left-billed birds.
|
|
||||||
|
|
||||||
}
|
|
||||||
\references{
|
|
||||||
McDonald, J.H. 2014. \strong{Handbook of Biological Statistics (3rd ed.)}. Sparky House Publishing, Baltimore, Maryland.
|
|
||||||
}
|
|
||||||
\seealso{
|
|
||||||
\code{\link{g.test}}
|
|
||||||
}
|
|
@ -28,9 +28,15 @@ test_that("mic works", {
|
|||||||
expect_true(is.mic(as.mic(8)))
|
expect_true(is.mic(as.mic(8)))
|
||||||
|
|
||||||
expect_equal(as.double(as.mic(">=32")), 32)
|
expect_equal(as.double(as.mic(">=32")), 32)
|
||||||
|
expect_equal(as.numeric(as.mic(">=32")), 32)
|
||||||
expect_equal(as.integer(as.mic(">=32")), 32)
|
expect_equal(as.integer(as.mic(">=32")), 32)
|
||||||
expect_equal(suppressWarnings(as.logical(as.mic("INVALID VALUE"))), NA)
|
expect_equal(suppressWarnings(as.logical(as.mic("INVALID VALUE"))), NA)
|
||||||
|
|
||||||
|
# all levels should be valid MICs
|
||||||
|
expect_silent(as.mic(levels(as.mic(1))))
|
||||||
|
|
||||||
|
expect_warning(as.mic("INVALID VALUE"))
|
||||||
|
|
||||||
# print plots, should not raise errors
|
# print plots, should not raise errors
|
||||||
barplot(as.mic(c(1, 2, 4, 8)))
|
barplot(as.mic(c(1, 2, 4, 8)))
|
||||||
plot(as.mic(c(1, 2, 4, 8)))
|
plot(as.mic(c(1, 2, 4, 8)))
|
||||||
|
@ -1,6 +1,8 @@
|
|||||||
context("freq.R")
|
context("freq.R")
|
||||||
|
|
||||||
test_that("frequency table works", {
|
test_that("frequency table works", {
|
||||||
|
library(dplyr)
|
||||||
|
|
||||||
expect_equal(nrow(freq(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)
|
expect_equal(nrow(freq(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)
|
||||||
expect_equal(nrow(frequency_tbl(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)
|
expect_equal(nrow(frequency_tbl(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)
|
||||||
|
|
||||||
@ -9,6 +11,7 @@ test_that("frequency table works", {
|
|||||||
expect_equal(nrow(freq(septic_patients$date)),
|
expect_equal(nrow(freq(septic_patients$date)),
|
||||||
length(unique(septic_patients$date)))
|
length(unique(septic_patients$date)))
|
||||||
|
|
||||||
|
expect_output(print(septic_patients %>% freq(age, nmax = Inf)))
|
||||||
expect_output(print(freq(septic_patients$age, nmax = Inf)))
|
expect_output(print(freq(septic_patients$age, nmax = Inf)))
|
||||||
expect_output(print(freq(septic_patients$age, nmax = NA)))
|
expect_output(print(freq(septic_patients$age, nmax = NA)))
|
||||||
expect_output(print(freq(septic_patients$age, nmax = NULL)))
|
expect_output(print(freq(septic_patients$age, nmax = NULL)))
|
||||||
@ -31,7 +34,13 @@ test_that("frequency table works", {
|
|||||||
# rsi
|
# rsi
|
||||||
expect_output(print(freq(septic_patients$amcl)))
|
expect_output(print(freq(septic_patients$amcl)))
|
||||||
# hms
|
# hms
|
||||||
expect_output(print(freq(hms::as.hms(sample(c(0:86399), 50)))))
|
expect_output(suppressWarnings(print(freq(hms::as.hms(sample(c(0:86399), 50))))))
|
||||||
|
# matrix
|
||||||
|
expect_output(print(freq(as.matrix(septic_patients$age))))
|
||||||
|
expect_output(print(freq(as.matrix(septic_patients[, c("age", "sex")]))))
|
||||||
|
# list
|
||||||
|
expect_output(print(freq(list(age = septic_patients$age))))
|
||||||
|
expect_output(print(freq(list(age = septic_patients$age, sex = septic_patients$sex))))
|
||||||
|
|
||||||
library(dplyr)
|
library(dplyr)
|
||||||
expect_output(septic_patients %>% select(1:2) %>% freq() %>% print())
|
expect_output(septic_patients %>% select(1:2) %>% freq() %>% print())
|
||||||
@ -94,5 +103,11 @@ test_that("frequency table works", {
|
|||||||
class() %>%
|
class() %>%
|
||||||
.[1],
|
.[1],
|
||||||
"tbl_df")
|
"tbl_df")
|
||||||
|
|
||||||
|
expect_error(septic_patients %>% freq(nonexisting))
|
||||||
|
expect_error(septic_patients %>% select(1:10) %>% freq())
|
||||||
|
expect_error(septic_patients %>% freq(peni, oxac, clox, amox, amcl,
|
||||||
|
ampi, pita, czol, cfep, cfur))
|
||||||
|
|
||||||
})
|
})
|
||||||
|
|
||||||
|
@ -6,24 +6,30 @@ test_that("G-test works", {
|
|||||||
|
|
||||||
# example 1: clearfield rice vs. red rice
|
# example 1: clearfield rice vs. red rice
|
||||||
x <- c(772, 1611, 737)
|
x <- c(772, 1611, 737)
|
||||||
x.expected <- ratio(x, ratio = "1:2:1")
|
|
||||||
expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
|
expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
|
||||||
expected = 0.12574,
|
expected = 0.12574,
|
||||||
tolerance = 0.00001)
|
tolerance = 0.00001)
|
||||||
|
|
||||||
# example 2: red crossbills
|
# example 2: red crossbills
|
||||||
x <- c(1752, 1895)
|
x <- c(1752, 1895)
|
||||||
x.expected <- ratio(x, c(1, 1))
|
|
||||||
expect_equal(g.test(x)$p.value,
|
expect_equal(g.test(x)$p.value,
|
||||||
expected = 0.01787343,
|
expected = 0.01787343,
|
||||||
tolerance = 0.00000001)
|
tolerance = 0.00000001)
|
||||||
|
|
||||||
|
expect_error(g.test(0))
|
||||||
|
expect_error(g.test(c(0, 1), 0))
|
||||||
|
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25)))
|
||||||
|
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24)))
|
||||||
|
expect_warning(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24), rescale.p = TRUE))
|
||||||
|
|
||||||
# INDEPENDENCE
|
# INDEPENDENCE
|
||||||
|
|
||||||
x <- matrix(data = round(runif(4) * 100000, 0),
|
x <- as.data.frame(
|
||||||
ncol = 2,
|
matrix(data = round(runif(4) * 100000, 0),
|
||||||
byrow = TRUE)
|
ncol = 2,
|
||||||
|
|
||||||
|
byrow = TRUE)
|
||||||
|
)
|
||||||
expect_lt(g.test(x)$p.value,
|
expect_lt(g.test(x)$p.value,
|
||||||
1)
|
1)
|
||||||
|
|
||||||
@ -31,4 +37,7 @@ test_that("G-test works", {
|
|||||||
y = c(780, 1560, 780),
|
y = c(780, 1560, 780),
|
||||||
rescale.p = TRUE))
|
rescale.p = TRUE))
|
||||||
|
|
||||||
|
expect_error(g.test(matrix(data = c(-1, -2, -3 , -4), ncol = 2, byrow = TRUE)))
|
||||||
|
expect_error(g.test(matrix(data = c(0, 0, 0, 0), ncol = 2, byrow = TRUE)))
|
||||||
|
|
||||||
})
|
})
|
||||||
|
@ -4,11 +4,12 @@ context("mdro.R")
|
|||||||
test_that("MDRO works", {
|
test_that("MDRO works", {
|
||||||
library(dplyr)
|
library(dplyr)
|
||||||
|
|
||||||
outcome <- MDRO(septic_patients, "EUCAST", info = FALSE)
|
outcome <- suppressWarnings(MDRO(septic_patients, "EUCAST", info = TRUE))
|
||||||
|
outcome <- suppressWarnings(EUCAST_exceptional_phenotypes(septic_patients, info = TRUE))
|
||||||
# check class
|
# check class
|
||||||
expect_equal(outcome %>% class(), c('ordered', 'factor'))
|
expect_equal(outcome %>% class(), c('ordered', 'factor'))
|
||||||
|
|
||||||
outcome <- MDRO(septic_patients, "nl", info = FALSE)
|
outcome <- suppressWarnings(MDRO(septic_patients, "nl", info = TRUE))
|
||||||
# check class
|
# check class
|
||||||
expect_equal(outcome %>% class(), c('ordered', 'factor'))
|
expect_equal(outcome %>% class(), c('ordered', 'factor'))
|
||||||
|
|
||||||
@ -18,4 +19,7 @@ test_that("MDRO works", {
|
|||||||
|
|
||||||
expect_equal(BRMO(septic_patients, info = FALSE), MDRO(septic_patients, "nl", info = FALSE))
|
expect_equal(BRMO(septic_patients, info = FALSE), MDRO(septic_patients, "nl", info = FALSE))
|
||||||
|
|
||||||
|
# still working on German guidelines
|
||||||
|
expect_error(suppressWarnings(MRGN(septic_patients, info = TRUE)))
|
||||||
|
|
||||||
})
|
})
|
||||||
|
Loading…
Reference in New Issue
Block a user