Merge branch 'dev'

.Rbuildignore

@@ -1,3 +1,4 @@
+^README\.Rmd$
 ^docs$
 ^_pkgdown\.yml$
 ^.*\.Rproj$

.gitignore

@@ -5,3 +5,9 @@
 .Rprofile
 qntmap.Rproj
 *.sync-conflict*
+
+vignettes/center_add\.csv
+
+vignettes/centers0\.csv
+
+vignettes/\.build\.timestamp

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: qntmap
 Type: Package
-Title: Enhance quantitative analysis of EPMA data
-Version: 0.2.2
+Title: Enhance quantitative analysis of EPMA map
+Version: 0.3.0
 Authors@R: c(
         person(given = 'YASUMOTO Atsushi', role = c('aut', 'cph', 'cre'), email = '[email protected]'),
         person(given = 'YOSHIDA Kenta', role = c('ctb')),
@@ -17,16 +17,17 @@ Description: A main function of this packages is
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 6.1.0
+RoxygenNote: 6.1.1
 Depends: R(>= 3.1.2)
 Imports: curl,
     data.table,
     dplyr,
-    ggplot2,
+    DT,
     easycsv,
-    imager,
+    ggplot2,
+    htmltools,
+    knitr,
     matrixStats,
-    plotly,
     pipeR,
     PoiClaClu,
     png,
@@ -35,6 +36,7 @@ Imports: curl,
     scales,
     stringr,
     shiny,
+    shinyWidgets,
     tibble,
     tidyr,
     utils
@@ -56,15 +58,13 @@ Collate:
     'find_centers_kpp.R'
     'group_cluster.R'
     'mean.R'
+    'plot-shiny.R'
     'plot.R'
-    'plot_shiny.R'
-    'plotly.R'
+    'plot_gg.R'
     'print.R'
     'qntmap.R'
     'quantify.R'
     'read_cnd.R'
-    'read_map_beam.R'
-    'read_map_pos.R'
     'read_qnt.R'
     'read_qnt_elemw.R'
     'read_xmap.R'
@@ -78,6 +78,7 @@ Collate:
 Roxygen: list(markdown = TRUE)
 Suggests: 
     knitr,
+    pkgdown,
     rmarkdown,
     testthat
 VignetteBuilder: knitr

NAMESPACE

@@ -2,6 +2,8 @@
 
 S3method(mean,qntmap)
 S3method(pick,qm_xmap)
+S3method(plot,qm_cluster)
+S3method(plot,qm_raster)
 S3method(plot,qm_xmap)
 S3method(plot,qntmap)
 S3method(print,qntmap)
@@ -30,14 +32,18 @@ export(read_xmap)
 export(save4qm)
 export(segment)
 export(tidy_epma)
-import(shiny)
+importFrom(DT,dataTableOutput)
+importFrom(DT,datatable)
+importFrom(DT,formatRound)
+importFrom(DT,renderDT)
 importFrom(PoiClaClu,Classify)
 importFrom(data.table,fread)
 importFrom(data.table,fwrite)
 importFrom(dplyr,arrange)
 importFrom(dplyr,bind_cols)
 importFrom(dplyr,bind_rows)
 importFrom(dplyr,distinct)
+importFrom(dplyr,everything)
 importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
 importFrom(dplyr,left_join)
@@ -49,55 +55,80 @@ importFrom(dplyr,right_join)
 importFrom(dplyr,select)
 importFrom(dplyr,summarise)
 importFrom(dplyr,summarize)
+importFrom(dplyr,summarize_if)
 importFrom(dplyr,transmute)
 importFrom(dplyr,transmute_at)
 importFrom(dplyr,ungroup)
 importFrom(easycsv,choose_dir)
 importFrom(ggplot2,aes)
-importFrom(ggplot2,aes_string)
+importFrom(ggplot2,coord_cartesian)
 importFrom(ggplot2,coord_fixed)
 importFrom(ggplot2,element_blank)
 importFrom(ggplot2,element_rect)
-importFrom(ggplot2,geom_col)
+importFrom(ggplot2,geom_bar)
+importFrom(ggplot2,geom_histogram)
 importFrom(ggplot2,geom_raster)
 importFrom(ggplot2,ggplot)
-importFrom(ggplot2,ggtitle)
-importFrom(ggplot2,scale_fill_gradientn)
+importFrom(ggplot2,guide_colorbar)
+importFrom(ggplot2,guide_legend)
+importFrom(ggplot2,guides)
+importFrom(ggplot2,scale_fill_gradient)
+importFrom(ggplot2,scale_fill_manual)
 importFrom(ggplot2,scale_fill_viridis_c)
 importFrom(ggplot2,scale_y_reverse)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,theme_classic)
 importFrom(grDevices,col2rgb)
 importFrom(grDevices,dev.copy)
 importFrom(grDevices,dev.off)
+importFrom(grDevices,nclass.FD)
 importFrom(grDevices,png)
 importFrom(grDevices,rgb)
-importFrom(graphics,hist)
 importFrom(graphics,pie)
 importFrom(graphics,plot)
-importFrom(imager,load.image)
+importFrom(grid,unit)
+importFrom(htmltools,br)
+importFrom(htmltools,tags)
+importFrom(knitr,kable)
 importFrom(matrixStats,rowMaxs)
 importFrom(matrixStats,weightedMedian)
 importFrom(pipeR,"%>>%")
 importFrom(pipeR,pipeline)
-importFrom(plotly,event_data)
-importFrom(plotly,ggplotly)
-importFrom(plotly,layout)
-importFrom(plotly,plot_ly)
-importFrom(plotly,plotlyOutput)
-importFrom(plotly,renderPlotly)
+importFrom(png,readPNG)
 importFrom(png,writePNG)
 importFrom(purrr,map)
 importFrom(purrr,map2)
 importFrom(purrr,map2_dbl)
 importFrom(purrr,map_at)
 importFrom(purrr,map_dbl)
+importFrom(purrr,map_if)
 importFrom(purrr,map_int)
 importFrom(purrr,pmap)
 importFrom(purrr,walk2)
-importFrom(scales,gradient_n_pal)
+importFrom(rlang,sym)
 importFrom(scales,squish)
-importFrom(scales,viridis_pal)
+importFrom(shiny,brushOpts)
+importFrom(shiny,checkboxInput)
+importFrom(shiny,fluidPage)
+importFrom(shiny,hoverOpts)
+importFrom(shiny,htmlOutput)
+importFrom(shiny,mainPanel)
+importFrom(shiny,numericInput)
+importFrom(shiny,observeEvent)
+importFrom(shiny,plotOutput)
+importFrom(shiny,reactive)
+importFrom(shiny,reactiveValues)
+importFrom(shiny,renderPlot)
+importFrom(shiny,renderPrint)
+importFrom(shiny,renderUI)
+importFrom(shiny,req)
+importFrom(shiny,selectInput)
+importFrom(shiny,shinyApp)
+importFrom(shiny,sidebarLayout)
+importFrom(shiny,sidebarPanel)
+importFrom(shiny,splitLayout)
+importFrom(shiny,uiOutput)
+importFrom(shinyWidgets,radioGroupButtons)
 importFrom(stats,coef)
 importFrom(stats,lm)
 importFrom(stats,lsfit)

NEWS.md

@@ -1,3 +1,22 @@
+# qntmap 0.3.0
+
+## Major changes
+
+- `plot()`
+    - Interactive plot is a combination of shiny, ggplot2, and more. No more using plotly.
+        - Color control with histogram
+        - Hover information of pixels
+        - Zooming
+        - Moving
+        - Summarizing data in a table below heatmap
+            - Double click to keep pixel data
+            - Box select to keep mean values of data
+    - Grayscale is supported in addition to viridis.
+    - Clustering result is supported.
+- `segment()`
+    - Only allows PNG format as an input. 
+      No more JPG nor BMP allowed.
+
 # qntmap 0.2.2
 
 ## Major changes

R/add_centers.R

@@ -3,8 +3,7 @@
 #' 
 #' Add centroids manually by picking X-ray counts of selected pixels in X-ray maps.
 #' 
-#' @seealso [pick()]
-#' @seealso [find_centers()]
+#' @seealso [pick()], [find_centers()]
 #' 
 #' @examples 
 #' centers <- data.frame(
@@ -25,20 +24,18 @@
 #' @inheritParams pick
 #' 
 #' @importFrom dplyr bind_rows
-#' @importFrom pipeR pipeline
 #' @export
-add_centers <- function(
-  centers,
-  xmap
-) {
-  pipeline({
-    as.data.frame(centers)
+add_centers <- function (centers, xmap) {
+  save4qm(
+    structure(
       bind_rows(
+        as.data.frame(centers),
         pick(xmap, x = x, y = y, phase = phase, i = i)[names(centers)]
-      )
-      `class<-`(class(centers))
-      save4qm(nm = saveas, saving = is.character(saveas))
-  })
+      ),
+      class = class(centers)
+    ),
+    nm = saveas, saving = is.character(saveas)
+  )
 }
 formals(add_centers) <- c(
   formals(add_centers), 

R/cluster.R

@@ -1,20 +1,24 @@
-#' Poisson distribution based custering based on `PoiClaClu:Classify()`
+#' Poisson distribution based custering based on [`PoiClaClu::Classify()`]
 #' 
-#' @param centers c-by-p matrix returned by `find_centers()` or by manually; c clusters and p features. Used to guess initial centers (or centroids) of clusters. A value returned by , typically `data.frame` or `matrix`, indicating initial guess centers (or centroids) or clusters. See `find_centers()`.
+#' @param centers c-by-p matrix returned by [`find_centers()`] or by manually; 
+#' c clusters and p features. 
+#' Used to guess initial centers (or centroids) of clusters. 
+#' A value returned by , typically [`data.frame`] or [`matrix`], 
+#' indicating initial guess centers (or centroids) or clusters. 
+#' See [`find_centers()`].
 #' @inheritParams PoiClaClu::Classify
 #' @inheritDotParams PoiClaClu::Classify -x -y -xte
-#' @inherit PoiClaClu::Classify return
-#' @inherit PoiClaClu::Classify references
-#' @seealso \link[PoiClaClu]{Classify}
+#' @inherit PoiClaClu::Classify return references
+#' @seealso [PoiClaClu::Classify()], [find_centers()]
 #'
 #' @importFrom PoiClaClu Classify
 #' @export
 cluster <- function(x, centers, xte = NULL, ...) {
   x_trans <- t(x)
   y <- pipeline({
     centers
-    apply(1, function(y) colSums((x_trans - y) ^ 2))
-    apply(1, which.min)
+    apply(1L, function(y) colSums((x_trans - y) ^ 2L))
+    apply(1L, which.min)
   })
   rm(x_trans)
   Classify(x, y, `if`(is.null(xte), x, xte), ...)
@@ -25,16 +29,19 @@ cluster <- function(x, centers, xte = NULL, ...) {
 #' Cluster mapping data into mineral species
 #'
 #' @inheritParams cluster
-#' @param xmap a `qm_xmap` class object returned by `read_xmap`
-#' @param elements A character vector indicating which elements to be utilized in cluster analysis. `NULL`, in default, selects as much elements as possible are utilized in cluster analysis.
+#' @param xmap a `qm_xmap` class object returned by [`read_xmap()`]
+#' @param elements 
+#' A character vector to chose elements to be utilized in cluster analysis. 
+#' `NULL` (default) selects as much elements as possible.
 #' @param saving `TRUE` or `FALSE` to save result.
-#' @param group_cluster `TRUE` (default) or `FALSE` to integrate same phase subgrouped using suffix. For example, when there are clusters named as Pl_NaRich and Pl_NaPoor, they are grouped as Pl.
+#' @param group_cluster 
+#' `FALSE` (default) or `TRUE` to integrate same phase subgrouped using suffix.
+#' For example, 
+#' clusters named "Pl_NaRich" and "Pl_NaPoor" are integrated to "Pl" cluster .
 #'
-#' @importFrom dplyr group_by
-#' @importFrom dplyr ungroup
+#' @importFrom dplyr group_by ungroup
 #' @importFrom pipeR pipeline
-#' @importFrom tidyr gather
-#' @importFrom tidyr spread
+#' @importFrom tidyr gather spread
 #' @importFrom matrixStats rowMaxs
 #'
 #' @export
@@ -86,20 +93,20 @@ cluster_xmap <- function(
   if(nrow(centers) == ncol(result$membership)) {
     colnames(result$membership) <- centers$phase
   } else {
-    if(ncol(result$membership) == 1) {
-      colnames(result$membership) <- names(result$ytehat[1])
+    if(ncol(result$membership) == 1L) {
+      colnames(result$membership) <- names(result$ytehat[1L])
     } else {
       TF <- !duplicated(result$cluster)
-      colnames(result$membership)[apply(result$membership[TF, ], 1, which.max)] <-
+      colnames(result$membership)[apply(result$membership[TF, ], 1L, which.max)] <-
         result$cluster[TF]
       rm(TF)
     }
     missings <- setdiff(centers$phase, colnames(result$membership))
     result$membership <- cbind(
         result$membership,
         matrix(
-          0,
-          nrow(result$membership),
+          0L,
+          nrow = nrow(result$membership),
           ncol = length(missings),
           dimnames = list(NULL, missings)
         )
@@ -122,9 +129,10 @@ cluster_xmap <- function(
 
 
 
-#' (Deprecated) Use `cluster_xmap()`
+#' (DEPRECATED) Use `cluster_xmap()`
 #' 
-#' @param centers_initial Equivalent to `centers_initial` parameter of `cluster_xmap`
+#' @param centers_initial 
+#' Equivalent to `centers_initial` parameter of `cluster_xmap`
 #' @param qltmap Equivalent to `xmap` parameter of `cluster_xmap`
 #' @param wd Path to the working directory.
 #' @param integration Equivalent to `group_cluster` parameter of `cluster_xmap`
@@ -153,7 +161,6 @@ qntmap_cls_pois <- function(
   if(is.null(elements)) elements <- 
     intersect(names(qltmap), colnames(centers_initial))
 
-  xmap <- 
   cluster_xmap(
     qltmap,
     centers_initial,