ggplot2_rsi fix

R/ggplot_rsi.R

@@ -20,7 +20,7 @@
 #'
 #' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}} functions.
 #' @param data a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})
-#' @param position position adjustment of bars, either \code{"stack"} (default when \code{fun} is \code{\link{portion_df}}) or \code{"dodge"} (default when \code{fun} is \code{\link{count_df}})
+#' @param position position adjustment of bars, either \code{"fill"}, \code{"stack"} (default when \code{fun} is \code{\link{portion_df}}) or \code{"dodge"} (default when \code{fun} is \code{\link{count_df}})
 #' @param x variable to show on x axis, either \code{"Antibiotic"} (default) or \code{"Interpretation"} or a grouping variable
 #' @param fill variable to categorise using the plots legend, either \code{"Antibiotic"} (default) or \code{"Interpretation"} or a grouping variable
 #' @param facet variable to split plots by, either \code{"Interpretation"} (default) or \code{"Antibiotic"} or a grouping variable
@@ -56,7 +56,6 @@
 #' df <- septic_patients[, c("amox", "nitr", "fosf", "trim", "cipr")]
 #' ggplot(df) +
 #'   geom_rsi() +
-#'   facet_rsi() +
 #'   scale_y_percent() +
 #'   scale_rsi_colours() +
 #'   theme_rsi()
@@ -87,12 +86,12 @@
 #'   ggplot_rsi() + scale_fill_viridis_d()
 #'
 #'
-#' # it also supports groups (don't forget to use the group on `x` or `facet`):
+#' # it also supports groups (don't forget to use the group var on `x` or `facet`):
 #' septic_patients %>%
 #'   select(hospital_id, amox, nitr, fosf, trim, cipr) %>%
 #'   group_by(hospital_id) %>%
-#'   ggplot_rsi(x = "hospital_id",
+#'   ggplot_rsi(x = hospital_id,
-#'              facet = "Antibiotic",
+#'              facet = Antibiotic,
 #'              nrow = 1) +
 #'   labs(title = "AMR of Anti-UTI Drugs Per Hospital",
 #'        x = "Hospital")
@@ -101,8 +100,8 @@
 #' septic_patients %>%
 #'   # create new bacterial ID's, with all CoNS under the same group (Becker et al.)
 #'   mutate(mo = as.mo(mo, Becker = TRUE)) %>%
-#'   # filter on top 2 bacterial ID's
+#'   # filter on top three bacterial ID's
-#'   filter(mo %in% top_freq(freq(.$mo), 2)) %>%
+#'   filter(mo %in% top_freq(freq(.$mo), 3)) %>%
 #'   # determine first isolates
 #'   mutate(first_isolate = first_isolate(.,
 #'                                        col_date = "date",
@@ -110,17 +109,18 @@
 #'                                        col_mo = "mo")) %>%
 #'   # filter on first isolates
 #'   filter(first_isolate == TRUE) %>%
-#'   # join the `microorganisms` data set
+#'   # get short MO names (like "E. coli")
-#'   left_join_microorganisms() %>%
+#'   mutate(mo = mo_shortname(mo, Becker = TRUE)) %>%
-#'   # select full name and some antiseptic drugs
+#'   # select this short name and some antiseptic drugs
-#'   select(mo = fullname,
+#'   select(mo, cfur, gent, cipr) %>%
-#'          cfur, gent, cipr) %>%
 #'   # group by MO
 #'   group_by(mo) %>%
 #'   # plot the thing, putting MOs on the facet
-#'   ggplot_rsi(x = "Antibiotic",
+#'   ggplot_rsi(x = Antibiotic,
-#'              facet = "mo") +
+#'              facet = mo,
-#'   labs(title = "AMR of Top Two Microorganisms In Blood Culture Isolates",
+#'              translate_ab = FALSE,
+#'              nrow = 1) +
+#'   labs(title = "AMR of Top Three Microorganisms In Blood Culture Isolates",
 #'        subtitle = "Only First Isolates, CoNS grouped according to Becker et al. (2014)",
 #'        x = "Microorganisms")
 #' }
@@ -144,6 +144,28 @@ ggplot_rsi <- function(data,
     stop("`fun` must be portion_df or count_df")
   }
 
+  x <- x[1]
+  facet <- facet[1]
+
+  # we work with aes_string later on
+  x_deparse <- deparse(substitute(x))
+  if (x_deparse != "x") {
+    x <- x_deparse
+  }
+  if (x %like% '".*"') {
+    x <- substr(x, 2, nchar(x) - 1)
+  }
+  facet_deparse <- deparse(substitute(facet))
+  if (facet_deparse != "facet") {
+    facet <- facet_deparse
+  }
+  if (facet %like% '".*"') {
+    facet <- substr(facet, 2, nchar(facet) - 1)
+  }
+  if (facet %in% c("NULL", "")) {
+    facet <- NULL
+  }
+
   p <- ggplot2::ggplot(data = data) +
     geom_rsi(position = position, x = x, fill = fill, translate_ab = translate_ab, fun = fun, ...) +
     theme_rsi()
@@ -190,6 +212,16 @@ geom_rsi <- function(position = NULL,
   }
 
   x <- x[1]
+
+  # we work with aes_string later on
+  x_deparse <- deparse(substitute(x))
+  if (x_deparse != "x") {
+    x <- x_deparse
+  }
+  if (x %like% '".*"') {
+    x <- substr(x, 2, nchar(x) - 1)
+  }
+
   if (tolower(x) %in% tolower(c('ab', 'antibiotic', 'abx', 'antibiotics'))) {
     x <- "Antibiotic"
   } else if (tolower(x) %in% tolower(c('SIR', 'RSI', 'interpretation', 'interpretations', 'result'))) {
@@ -209,6 +241,16 @@ geom_rsi <- function(position = NULL,
 facet_rsi <- function(facet = c("Interpretation", "Antibiotic"), nrow = NULL) {
 
    facet <- facet[1]
+
+  # we work with aes_string later on
+  facet_deparse <- deparse(substitute(facet))
+  if (facet_deparse != "facet") {
+    facet <- facet_deparse
+  }
+  if (facet %like% '".*"') {
+    facet <- substr(facet, 2, nchar(facet) - 1)
+  }
+
   if (tolower(facet) %in% tolower(c('SIR', 'RSI', 'interpretation', 'interpretations', 'result'))) {
     facet <- "Interpretation"
   } else if (tolower(facet) %in% tolower(c('ab', 'antibiotic', 'abx', 'antibiotics'))) {

R/mo_property.R

@@ -142,12 +142,13 @@ mo_shortname <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
     res2_fullname <- mo_fullname(res2)
     res2_fullname[res2_fullname %like% "\\(CoNS\\)"] <- "CoNS"
     res2_fullname[res2_fullname %like% "\\(CoPS\\)"] <- "CoPS"
-    res2_fullname <- gsub("Streptococcus (group|gruppe|Gruppe|groep|grupo) (.)",
+    res2_fullname <- gsub("Streptococcus (group|Gruppe|gruppe|groep|grupo|gruppo|groupe) (.)",
                           "G\\2S",
                           res2_fullname) # turn "Streptococcus group A" and "Streptococcus grupo A" to "GAS"
-    res2_fullname[res2_fullname == mo_fullname(x)] <- paste0(substr(mo_genus(res2_fullname), 1, 1),
+    res2_fullname_vector <- res2_fullname[res2_fullname == mo_fullname(x)]
+    res2_fullname[res2_fullname == mo_fullname(x)] <- paste0(substr(mo_genus(res2_fullname_vector), 1, 1),
                                                              ". ",
-                                                             suppressWarnings(mo_species(res2_fullname)))
+                                                             suppressWarnings(mo_species(res2_fullname_vector)))
     if (sum(res1 == res2, na.rm = TRUE) > 0) {
       res1[res1 == res2] <- paste0(substr(mo_genus(res1[res1 == res2]), 1, 1),
                                    ". ",

man/ggplot_rsi.Rd

@@ -28,7 +28,7 @@ theme_rsi()
 \arguments{
 \item{data}{a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})}
 
-\item{position}{position adjustment of bars, either \code{"stack"} (default when \code{fun} is \code{\link{portion_df}}) or \code{"dodge"} (default when \code{fun} is \code{\link{count_df}})}
+\item{position}{position adjustment of bars, either \code{"fill"}, \code{"stack"} (default when \code{fun} is \code{\link{portion_df}}) or \code{"dodge"} (default when \code{fun} is \code{\link{count_df}})}
 
 \item{x}{variable to show on x axis, either \code{"Antibiotic"} (default) or \code{"Interpretation"} or a grouping variable}
 
@@ -75,7 +75,6 @@ ggplot(septic_patients \%>\% select(amox, nitr, fosf, trim, cipr)) +
 df <- septic_patients[, c("amox", "nitr", "fosf", "trim", "cipr")]
 ggplot(df) +
   geom_rsi() +
-  facet_rsi() +
   scale_y_percent() +
   scale_rsi_colours() +
   theme_rsi()
@@ -106,12 +105,12 @@ septic_patients \%>\%
   ggplot_rsi() + scale_fill_viridis_d()
 
 
-# it also supports groups (don't forget to use the group on `x` or `facet`):
+# it also supports groups (don't forget to use the group var on `x` or `facet`):
 septic_patients \%>\%
   select(hospital_id, amox, nitr, fosf, trim, cipr) \%>\%
   group_by(hospital_id) \%>\%
-  ggplot_rsi(x = "hospital_id",
+  ggplot_rsi(x = hospital_id,
-             facet = "Antibiotic",
+             facet = Antibiotic,
              nrow = 1) +
   labs(title = "AMR of Anti-UTI Drugs Per Hospital",
        x = "Hospital")
@@ -120,8 +119,8 @@ septic_patients \%>\%
 septic_patients \%>\%
   # create new bacterial ID's, with all CoNS under the same group (Becker et al.)
   mutate(mo = as.mo(mo, Becker = TRUE)) \%>\%
-  # filter on top 2 bacterial ID's
+  # filter on top three bacterial ID's
-  filter(mo \%in\% top_freq(freq(.$mo), 2)) \%>\%
+  filter(mo \%in\% top_freq(freq(.$mo), 3)) \%>\%
   # determine first isolates
   mutate(first_isolate = first_isolate(.,
                                        col_date = "date",
@@ -129,17 +128,18 @@ septic_patients \%>\%
                                        col_mo = "mo")) \%>\%
   # filter on first isolates
   filter(first_isolate == TRUE) \%>\%
-  # join the `microorganisms` data set
+  # get short MO names (like "E. coli")
-  left_join_microorganisms() \%>\%
+  mutate(mo = mo_shortname(mo, Becker = TRUE)) \%>\%
-  # select full name and some antiseptic drugs
+  # select this short name and some antiseptic drugs
-  select(mo = fullname,
+  select(mo, cfur, gent, cipr) \%>\%
-         cfur, gent, cipr) \%>\%
   # group by MO
   group_by(mo) \%>\%
   # plot the thing, putting MOs on the facet
-  ggplot_rsi(x = "Antibiotic",
+  ggplot_rsi(x = Antibiotic,
-             facet = "mo") +
+             facet = mo,
-  labs(title = "AMR of Top Two Microorganisms In Blood Culture Isolates",
+             translate_ab = FALSE,
+             nrow = 1) +
+  labs(title = "AMR of Top Three Microorganisms In Blood Culture Isolates",
        subtitle = "Only First Isolates, CoNS grouped according to Becker et al. (2014)",
        x = "Microorganisms")
 }