change param names for q matrices

DESCRIPTION

@@ -12,7 +12,7 @@ Description: We provide a tidy grammar of population genetics, facilitating
 License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Depends:
     R (>= 3.0.2),
     dplyr,

R/as_q_matrix.R

@@ -26,17 +26,18 @@ as_q_matrix <- function(x){
 #' Takes a `q_matrix` object, which is a matrix, and returns a tidied tibble.
 #'
 #' @param x A Q matrix object (as returned by LEA::Q()).
-#' @param gen_tbl An associated gen_tibble
+#' @param data An associated tibble (e.g. a [`gen_tibble`]), with the individuals in the same order as the data used to
+#' generate the Q matrix
 #' @param ... not currently used
 #' @return A tidied tibble
 #' @export
-tidy.q_matrix <- function(x, gen_tbl, ...){
+tidy.q_matrix <- function(x, data, ...){
   rlang::check_dots_empty()
   q_tbl <- x %>%
     tibble::as_tibble() %>%
-    dplyr::mutate(id = gen_tbl$id,
+    dplyr::mutate(id = data$id,
                   # @TODO we should get this from the grouped tibble, not hardcode it!
-                  group = gen_tbl$population)
+                  group = data$population)
 
   q_tbl <- q_tbl %>% tidyr::pivot_longer(cols = dplyr::starts_with(".Q"),
                                          names_to = "q", values_to = "percentage")
@@ -63,12 +64,13 @@ tidy.q_matrix <- function(x, gen_tbl, ...){
 #' produces a list of tidied tibbles ready to plot.
 #'
 #' @param x the name of a directory containing .Q files
-#' @param gen_tbl  An associated gen_tibble
+#' @param data  An associated tibble (e.g. a [`gen_tibble`]), with the individuals in the same order as the data used to
+#' generate the Q matrix
 #' @returns a list of `q_matrix` objects to plot
 #'
 #' @export
 
-read_q_matrix_list <- function(x, gen_tbl){
+read_q_matrix_list <- function(x, data){
 
   files <- list.files(x, pattern = "\\.Q$", full.names = TRUE)
 
@@ -82,34 +84,35 @@ read_q_matrix_list <- function(x, gen_tbl){
   matrix_list <- matrix_list[order(sapply(matrix_list, ncol))]
 
   # Tidy each
-  matrix_list <- lapply(matrix_list, function(x) tidy(x, gen_tbl = gen_tbl))
+  matrix_list <- lapply(matrix_list, function(x) tidy(x, gen_tbl = data))
 
   matrix_list
 }
 
 
 #' Autoplots for `q_matrix` objects
 #'
-#' @param object A Q matrix object (as returned by `as_q_matrix`).
-#' @param gen_tbl An associated gen_tibble
+#' @param object A Q matrix object (as returned by [as_q_matrix()]).
+#' @param data An associated tibble (e.g. a [`gen_tibble`]), with the individuals in the same order as the data used to
+#' generate the Q matrix
 #' @param annotate_group Boolean determining whether to annotate the plot with the
 #' group information
 #' @param ... not currently used.
 #' @returns a barplot of individuals, coloured by ancestry proportion
 #'
 #' @export
 
-autoplot.q_matrix <- function(object, gen_tbl = NULL, annotate_group = TRUE, ...){
+autoplot.q_matrix <- function(object, data = NULL, annotate_group = TRUE, ...){
 
   rlang::check_dots_empty()
   K <- ncol(object)
-  if (is.null(gen_tbl)) {
+  if (is.null(data)) {
     q_tbl <- as.data.frame(object)
     q_tbl$id <- 1:nrow(q_tbl)
     q_tbl <- q_tbl %>% tidyr::pivot_longer(cols = dplyr::starts_with(".Q"),
                                        names_to = "q", values_to = "percentage")
   } else {
-    q_tbl <- tidy(object, gen_tbl)
+    q_tbl <- tidy(object, data)
   }
     plt <- ggplot2::ggplot(q_tbl,
                            ggplot2::aes(x = .data$id,
@@ -121,7 +124,7 @@ autoplot.q_matrix <- function(object, gen_tbl = NULL, annotate_group = TRUE, ...
       theme_distruct() +
       scale_fill_distruct()
     if (annotate_group){
-      if (is.null(gen_tbl)){
+      if (is.null(data)){
         warning("no annotation possible if 'gen_tbl' is NULL")
       } else {
         plt <- plt + annotate_group_info(q_tbl)

vignettes/a03_example_clustering_and_dapc.Rmd

@@ -341,7 +341,7 @@ head(q_mat)
 
 We can quickly plot it with
 ```{r}
-autoplot(q_mat,gen_tbl = anole_gt)
+autoplot(q_mat, data = anole_gt)
 ```
 
 We can tidy our q matrix, and attach the population and id data from our original gen_tibble, returning it