Merge pull request #288 from ldecicco-USGS/master

Slimming namespace

DESCRIPTION

@@ -2,7 +2,7 @@ Package: toxEval
 Type: Package
 Title: ToxCast Evaluations
 Version: 1.0.0
-Date: 2018-07-11
+Date: 2018-07-31
 Authors@R: c(person("Laura", "DeCicco", 
                      role = c("aut","cre"),
                      email = "[email protected]"),
@@ -30,9 +30,9 @@ Imports:
     DT (>= 0.1.24),
     leaflet  (>= 1.0.0),
     ggplot2 (>= 3.0.0),
+    magrittr,
     shiny,
     shinydashboard,
-    data.table,
     RColorBrewer,
     readxl,
     tools,
@@ -41,11 +41,10 @@ Imports:
 Suggests:
     rmarkdown,
     testthat,
-    knitr,
-    htmltools
+    knitr
 BugReports: https://github.com/USGS-R/toxEval/issues
 VignetteBuilder: knitr
 BuildVignettes: true
 LazyLoad: yes
 LazyData: yes
-RoxygenNote: 6.0.1
+RoxygenNote: 6.1.0

NAMESPACE

@@ -28,45 +28,9 @@ export(rank_sites_DT)
 export(remove_flags)
 export(tox_boxplot_data)
 export(tox_chemicals)
-import(DT)
-import(RColorBrewer)
-import(data.table)
 import(ggplot2)
-import(leaflet)
-import(shinyAce)
-import(shinydashboard)
-importFrom(dplyr,anti_join)
-importFrom(dplyr,arrange)
-importFrom(dplyr,desc)
-importFrom(dplyr,distinct)
-importFrom(dplyr,filter)
-importFrom(dplyr,filter_)
-importFrom(dplyr,full_join)
-importFrom(dplyr,group_by)
-importFrom(dplyr,group_by_)
-importFrom(dplyr,left_join)
-importFrom(dplyr,mutate)
-importFrom(dplyr,mutate_)
-importFrom(dplyr,rename)
-importFrom(dplyr,rename_)
-importFrom(dplyr,right_join)
-importFrom(dplyr,select)
-importFrom(dplyr,select_)
-importFrom(dplyr,summarise)
-importFrom(dplyr,summarize)
 importFrom(grDevices,colorRampPalette)
-importFrom(leaflet,addCircles)
-importFrom(leaflet,addLegend)
-importFrom(leaflet,clearControls)
-importFrom(leaflet,clearShapes)
-importFrom(leaflet,leaflet)
-importFrom(shiny,runApp)
-importFrom(shinycssloaders,withSpinner)
+importFrom(magrittr,"%>%")
 importFrom(stats,median)
 importFrom(stats,quantile)
-importFrom(tidyr,gather)
-importFrom(tidyr,spread)
-importFrom(tidyr,unite)
 importFrom(tools,file_ext)
-importFrom(tools,toTitleCase)
-importFrom(utils,packageVersion)

R/clean_endPoint_info.R

@@ -15,7 +15,6 @@
 #' filtered out and some additional categories in intended_target_family and
 #' intended_target_family_sub. The names in intended_target_family
 #' are revised to look more appealing in graphs and tables.
-#' @importFrom tools toTitleCase
 #' @examples 
 #' end_point_info <- end_point_info
 #' cleaned_ep <- clean_endPoint_info(end_point_info)

R/create_toxEval.R

@@ -213,6 +213,7 @@ rm_em_dash <- function(df){
 #' @param \dots additional parameters
 #'
 #' @export
+#' @importFrom magrittr "%>%"
 #' @examples 
 #' path_to_tox <-  system.file("extdata", package="toxEval")
 #' file_name <- "OWC_data_fromSup.xlsx"

R/endpoint_hits.R

@@ -28,11 +28,8 @@
 #' @export
 #' @return data frame with one row per endpoint that had a hit (based on the
 #' hit_threshold). The columns are based on the category.
-#' @import DT
 #' @rdname endpoint_hits_DT
 #' @importFrom stats median
-#' @importFrom tidyr spread unite
-#' @importFrom dplyr full_join filter mutate select left_join right_join
 #' @examples
 #' # This is the example workflow:
 #' path_to_tox <-  system.file("extdata", package="toxEval")
@@ -72,8 +69,8 @@ endpoint_hits_DT <- function(chemical_summary,
   if(category == "Chemical"){
     orig_names <- names(fullData)
 
-    casKey <- select(chemical_summary, chnm, CAS) %>%
-      distinct()
+    casKey <- dplyr::select(chemical_summary, chnm, CAS) %>%
+      dplyr::distinct()
 
     numeric_hits <- fullData
     hits <- sapply(fullData, function(x) as.character(x))
@@ -100,14 +97,14 @@ endpoint_hits_DT <- function(chemical_summary,
   n <- ncol(fullData)-1
 
   if(n > 20 & n<30){
-    colors <- c(brewer.pal(n = 12, name = "Set3"),
-                brewer.pal(n = 8, name = "Set2"),
-                brewer.pal(n = max(c(3,n-20)), name = "Set1"))
+    colors <- c(RColorBrewer::brewer.pal(n = 12, name = "Set3"),
+                RColorBrewer::brewer.pal(n = 8, name = "Set2"),
+                RColorBrewer::brewer.pal(n = max(c(3,n-20)), name = "Set1"))
   } else if (n <= 20){
-    colors <- c(brewer.pal(n = 12, name = "Set3"),
-                brewer.pal(n =  max(c(3,n-12)), name = "Set2"))     
+    colors <- c(RColorBrewer::brewer.pal(n = 12, name = "Set3"),
+                RColorBrewer::brewer.pal(n =  max(c(3,n-12)), name = "Set2"))     
   } else {
-    colors <- colorRampPalette(brewer.pal(11,"Spectral"))(n)
+    colors <- colorRampPalette(RColorBrewer::brewer.pal(11,"Spectral"))(n)
   }
 
   fullData_dt <- DT::datatable(fullData, extensions = 'Buttons',
@@ -119,13 +116,13 @@ endpoint_hits_DT <- function(chemical_summary,
                                              order=list(list(1,'desc'))))
 
   for(i in 2:ncol(fullData)){
-    fullData_dt <- formatStyle(fullData_dt,
+    fullData_dt <- DT::formatStyle(fullData_dt,
                              names(fullData)[i],
                              backgroundColor = colors[i])
 
     if(category != "Chemical"){
-      fullData_dt <- formatStyle(fullData_dt, names(fullData)[i],
-                                 background = styleColorBar(range(fullData[,names(fullData)[i]],na.rm = TRUE), 'goldenrod'),
+      fullData_dt <- DT::formatStyle(fullData_dt, names(fullData)[i],
+                                 background = DT::styleColorBar(range(fullData[,names(fullData)[i]],na.rm = TRUE), 'goldenrod'),
                                  backgroundSize = '100% 90%',
                                  backgroundRepeat = 'no-repeat',
                                  backgroundPosition = 'center' )      
@@ -152,48 +149,48 @@ endpoint_hits <- function(chemical_summary,
   fullData <- fullData_init
 
   if(category == "Chemical"){
-    chemical_summary <- mutate(chemical_summary, category = chnm)
+    chemical_summary <- dplyr::mutate(chemical_summary, category = chnm)
   } else if (category == "Chemical Class"){
-    chemical_summary <- mutate(chemical_summary, category = Class)
+    chemical_summary <- dplyr::mutate(chemical_summary, category = Class)
   } else {
-    chemical_summary <- mutate(chemical_summary, category = Bio_category)
+    chemical_summary <- dplyr::mutate(chemical_summary, category = Bio_category)
   }
 
   if(length(unique(chemical_summary$site)) > 1){
 
     if(!sum_logic){
       fullData <- chemical_summary %>%
-        group_by(site, category, endPoint, date) %>%
-        summarize(sumEAR = max(EAR)) %>%
-        group_by(site, category, endPoint) %>%
-        summarize(meanEAR = ifelse(mean_logic, mean(sumEAR),max(sumEAR))) %>%
-        group_by(category, endPoint) %>%
-        summarize(nSites = sum(meanEAR > hit_threshold)) %>%
-        spread(category, nSites)       
+        dplyr::group_by(site, category, endPoint, date) %>%
+        dplyr::summarize(sumEAR = max(EAR)) %>%
+        dplyr::group_by(site, category, endPoint) %>%
+        dplyr::summarize(meanEAR = ifelse(mean_logic, mean(sumEAR),max(sumEAR))) %>%
+        dplyr::group_by(category, endPoint) %>%
+        dplyr::summarize(nSites = sum(meanEAR > hit_threshold)) %>%
+        tidyr::spread(category, nSites)       
     } else {
       fullData <- chemical_summary %>%
-        group_by(site, category, endPoint, date) %>%
-        summarize(sumEAR = sum(EAR)) %>%
-        group_by(site, category, endPoint) %>%
-        summarize(meanEAR = ifelse(mean_logic, mean(sumEAR),max(sumEAR))) %>%
-        group_by(category, endPoint) %>%
-        summarize(nSites = sum(meanEAR > hit_threshold)) %>%
-        spread(category, nSites)      
+        dplyr::group_by(site, category, endPoint, date) %>%
+        dplyr::summarize(sumEAR = sum(EAR)) %>%
+        dplyr::group_by(site, category, endPoint) %>%
+        dplyr::summarize(meanEAR = ifelse(mean_logic, mean(sumEAR),max(sumEAR))) %>%
+        dplyr::group_by(category, endPoint) %>%
+        dplyr::summarize(nSites = sum(meanEAR > hit_threshold)) %>%
+        tidyr::spread(category, nSites)      
     }
 
   } else {
     if(!sum_logic){
       fullData <- chemical_summary %>%
-        group_by(category, endPoint) %>%
-        summarise(nSites = sum(EAR > hit_threshold)) %>%
-        spread(category, nSites)        
+        dplyr::group_by(category, endPoint) %>%
+        dplyr::summarise(nSites = sum(EAR > hit_threshold)) %>%
+        tidyr::spread(category, nSites)        
     } else {
       fullData <- chemical_summary %>%
-        group_by(category, endPoint, date) %>%
-        summarize(sumEAR = sum(EAR)) %>%
-        group_by(category, endPoint) %>%
-        summarise(nSites = sum(sumEAR > hit_threshold)) %>%
-        spread(category, nSites)      
+        dplyr::group_by(category, endPoint, date) %>%
+        dplyr::summarize(sumEAR = sum(EAR)) %>%
+        dplyr::group_by(category, endPoint) %>%
+        dplyr::summarise(nSites = sum(sumEAR > hit_threshold)) %>%
+        tidyr::spread(category, nSites)      
     }
   }
 

R/explore_endpoints.R

@@ -9,24 +9,12 @@
 #' 
 #' @param browse Logical. Use browser for running Shiny app.
 #' @export
-#' @importFrom shiny runApp
 #' @importFrom tools file_ext
-#' @importFrom leaflet leaflet
-#' @importFrom leaflet addLegend
-#' @importFrom leaflet addCircles
-#' @importFrom leaflet clearControls
-#' @importFrom leaflet clearShapes
-#' @importFrom shinycssloaders withSpinner
-#' @import DT
 #' @import ggplot2
-#' @import data.table
-#' @import RColorBrewer
-#' @import shinydashboard
-#' @import shinyAce
 #' @examples 
 #' \dontrun{
 #' explore_endpoints()
 #' }
 explore_endpoints <- function(browse=TRUE){
-  runApp(system.file('shiny', package='toxEval'), launch.browser = browse)
+  shiny::runApp(system.file('shiny', package='toxEval'), launch.browser = browse)
 }

R/filter_endPoint_info.R

@@ -23,7 +23,6 @@
 #' "BSK" (BioSeek) assay is removed.
 #' @param remove_groups Vector of groups within the selected 'groupCol' to remove.
 #' @export
-#' @importFrom dplyr rename
 #' @examples 
 #' end_point_info <- end_point_info
 #' cleaned_ep <- clean_endPoint_info(end_point_info)
@@ -43,7 +42,7 @@ filter_groups <- function(ep,
   assay_source_name <- assay_component_endpoint_name <- ".dplyr"
 
   ep <- ep[,c("assay_component_endpoint_name",groupCol,"assay_source_name")] %>%
-    rename(endPoint = assay_component_endpoint_name,
+    dplyr::rename(endPoint = assay_component_endpoint_name,
            assaysFull = assay_source_name)
   names(ep)[names(ep) == groupCol] <- "groupCol"
 

R/get_ACC.R

@@ -12,8 +12,6 @@
 #' @param CAS Vector of CAS. 
 #' @return data frame with columns CAS, chnm, flags, endPoint, ACC, MlWt, and ACC_value
 #' @export
-#' @importFrom tidyr gather
-#' @importFrom dplyr select filter right_join mutate
 #' @examples
 #' CAS <- c("121-00-6","136-85-6","80-05-7","84-65-1","5436-43-1","126-73-8")
 #' ACC <- get_ACC(CAS)
@@ -22,19 +20,19 @@ get_ACC <- function(CAS){
   # Getting rid of NSE warnings:
   Structure_MolWt <- Substance_CASRN <- casn <- chnm <- flags <- MlWt <- ACC_value <- casrn <- endPoint <- ".dplyr"
 
-  chem_list <- select(tox_chemicals,
-                    casrn = Substance_CASRN,
-                    MlWt = Structure_MolWt) %>%
-    filter(casrn %in% CAS) 
+  chem_list <- dplyr::select(tox_chemicals,
+                             casrn = Substance_CASRN,
+                             MlWt = Structure_MolWt) %>%
+    dplyr::filter(casrn %in% CAS) 
 
   ACC <- ToxCast_ACC %>%
-    filter(CAS %in% CAS) %>%
-    right_join(chem_list,
+    dplyr::filter(CAS %in% CAS) %>%
+    dplyr::right_join(chem_list,
                by= c("CAS"="casrn")) %>%
     data.frame() %>%
-    mutate(ACC_value = 10^ACC) %>%
-    mutate(ACC_value = ACC_value * MlWt) %>%
-    filter(!is.na(ACC_value)) 
+    dplyr::mutate(ACC_value = 10^ACC,
+                  ACC_value = ACC_value * MlWt) %>%
+    dplyr::filter(!is.na(ACC_value)) 
 
   if(any(is.na(ACC$MlWt))){
     warning("Some chemicals are missing molecular weights")