diff --git a/NAMESPACE b/NAMESPACE index 22cefa9..8c03a6d 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -44,6 +44,7 @@ importFrom(ggplot2,scale_y_reverse) importFrom(ggplot2,stat_qq) importFrom(ggplot2,theme) importFrom(ggplot2,theme_bw) +importFrom(ggplot2,vars) importFrom(grDevices,colorRampPalette) importFrom(grDevices,rainbow) importFrom(graphics,plot) diff --git a/R/heatmap.R b/R/heatmap.R index caab682..897fe71 100644 --- a/R/heatmap.R +++ b/R/heatmap.R @@ -11,7 +11,8 @@ #' @param smooth Logical (default: `TRUE`). If `raster` is `TRUE`, interpolation can be applied across the grid to obtain a smoothed grid. Ignored if `raster` is `FALSE`. #' @param palette Colour palatte to use. By default it will use the `viridis` (colour-blind friendly) palette. Other palettes available can be seen with [grDevices::hcl.pals()]. #' -#' @importFrom ggplot2 ggplot aes geom_tile geom_raster scale_fill_gradientn scale_x_continuous scale_y_continuous facet_wrap +#' @importFrom ggplot2 ggplot aes geom_tile geom_raster scale_fill_gradientn scale_x_continuous scale_y_continuous facet_wrap vars theme_bw +#' @importFrom rlang ensym enquo quo_is_null #' #' @return A `ggplot2` object. #' @export @@ -24,16 +25,16 @@ #' dat$groups <- sample(rep(LETTERS[1:6], times = 5)) #' #' heat_map(dat, value, x, y) +#' heat_map(dat, "value", "x", "y", "groups") heat_map <- function(data, value, x_axis, y_axis, grouping = NULL, raster = TRUE, smooth = FALSE, palette = "default") { # TODO: # - Error and sanity checking - # - What if grouping is NULL? - # - NSE value <- rlang::ensym(value) x_axis <- rlang::ensym(x_axis) y_axis <- rlang::ensym(y_axis) + grouping <- rlang::enquo(grouping) # Set the default palette to viridis if(palette=="default") { @@ -55,9 +56,11 @@ heat_map <- function(data, value, x_axis, y_axis, grouping = NULL, raster = TRUE ggplot2::scale_x_continuous(expand = c(0, 0)) + ggplot2::scale_y_continuous(expand = c(0, 0)) - if(!is.null(grouping)) { + if(!rlang::quo_is_null(grouping)) { grouping <- rlang::ensym(grouping) - plt <- plt + ggplot2::facet_wrap(vars({{ gropuing }})) + plt <- plt + ggplot2::facet_wrap(ggplot2::vars({{ grouping }})) } + + plt <- plt+ggplot2::theme_bw() return(plt) } diff --git a/man/heat_map.Rd b/man/heat_map.Rd index 82b25d8..4887906 100644 --- a/man/heat_map.Rd +++ b/man/heat_map.Rd @@ -46,4 +46,5 @@ dat$value <- rnorm(30) dat$groups <- sample(rep(LETTERS[1:6], times = 5)) heat_map(dat, value, x, y) +heat_map(dat, "value", "x", "y", "groups") }