adopt use of highlight_unit() in demos where it makes sense

cpsievert · cpsievert · commit 8d71a24ecd58 · 2018-06-08T14:36:33.000-05:00
diff --git a/R/ggplotly.R b/R/ggplotly.R
@@ -47,8 +47,7 @@
 #' ggplotly(viz, tooltip = c("text", "size"))
 #' 
 #' # linked scatterplot brushing
-#' library(crosstalk)
-#' d <- SharedData$new(mtcars)
+#' d <- highlight_unit(mtcars)
 #' qplot(data = d, x = mpg, y = wt) %>%
 #'   subplot(qplot(data = d, x = mpg, y = vs)) %>% 
 #'   layout(title = "Click and drag to select points") %>%
@@ -59,7 +58,7 @@
 #' demo("crosstalk-highlight-ggplotly", package = "plotly")
 #' 
 #' # client-side linked brushing in a scatterplot matrix
-#' SharedData$new(iris) %>%
+#' highlight_unit(iris) %>%
 #'   GGally::ggpairs(aes(colour = Species), columns = 1:4) %>%
 #'   ggplotly(tooltip = c("x", "y", "colour")) %>%
 #'   highlight("plotly_selected")
diff --git a/data-raw/res-us.R b/data-raw/res-us.R
@@ -9,7 +9,7 @@ res <- sf::st_read("~/Downloads/tl_2017_us_aiannh/tl_2017_us_aiannh.shp")
 # (2) crosstalk highlight should set fillcolor...
 
 res %>%
-  SharedData$new(~NAME) %>%
+  highlight_unit(~NAME) %>%
   plot_ly(text = ~NAME) %>%
   highlight(selectize = TRUE, dynamic = TRUE)
 
diff --git a/demo/animation-tour-USArrests.R b/demo/animation-tour-USArrests.R
@@ -45,7 +45,7 @@ ax <- list(
 # for nicely formatted slider labels
 options(digits = 3)
 
-tour_dat <- crosstalk::SharedData$new(tour_dat, ~state, group = "A")
+tour_dat <- highlight_unit(tour_dat, ~state, group = "A")
 
 tour <- proj_dat %>%
   plot_ly(x = ~x, y = ~y, frame = ~step, color = I("black")) %>%
diff --git a/demo/crosstalk-filter-dynamic-axis.R b/demo/crosstalk-filter-dynamic-axis.R
@@ -3,7 +3,7 @@ library(tidyr)
 library(crosstalk)
 
 m <- gather(mtcars, variable, value, -vs)
-msd <- SharedData$new(m, ~variable)
+msd <- highlight_unit(m, ~variable)
 gg <- ggplot(msd, aes(factor(vs), value)) + 
   geom_jitter(alpha = 0.3)
 
diff --git a/demo/crosstalk-filter-lines.R b/demo/crosstalk-filter-lines.R
@@ -3,7 +3,7 @@ library(ggplot2)
 library(gapminder)
 library(plotly)
 
-sd <- SharedData$new(gapminder)
+sd <- highlight_unit(gapminder)
 
 g <- ggplot(sd, aes(year, lifeExp, color = country, group = country)) +
   geom_line()
diff --git a/demo/crosstalk-highlight-binned-target-a.R b/demo/crosstalk-highlight-binned-target-a.R
@@ -1,8 +1,7 @@
 # These examples demonstrate ways to display binned/aggregated selections
-library(crosstalk)
 library(plotly)
 
-d <- SharedData$new(mpg)
+d <- highlight_unit(mpg)
 dots <- plot_ly(d, colors = "Set1", color = ~class, x = ~displ, y = ~cyl) %>%
   layout(
     xaxis = list(title = "Engine displacement"),
diff --git a/demo/crosstalk-highlight-binned-target-b.R b/demo/crosstalk-highlight-binned-target-b.R
@@ -1,13 +1,11 @@
 # These examples demonstrate ways to display binned/aggregated selections
-library(crosstalk)
 library(plotly)
 
-d <- SharedData$new(mtcars)
+d <- highlight_unit(mtcars)
 sp <- plot_ly(d, x = ~mpg, y = ~disp) %>%
   add_markers(color = I("black"))
 
-# hist/box/violin are all 'statistical trace types' meaning
-# they compute aggregations on the fly
+# 'statistical trace types'
 hist <- plot_ly(d, x = ~factor(cyl)) %>% 
   add_histogram(color = I("black"))
 box <- plot_ly(d, y = ~disp, color = I("black")) %>% 
@@ -22,7 +20,4 @@ subplot(sp, box, violin, shareY = TRUE, titleX = TRUE, titleY = TRUE) %>%
     title = "Click and drag scatterplot",
     showlegend = FALSE
   ) %>%
-  highlight(
-    "plotly_selected",
-    selected = attrs_selected(showlegend = FALSE)
-  )
+  highlight("plotly_selected")
diff --git a/demo/crosstalk-highlight-binned-target-c.R b/demo/crosstalk-highlight-binned-target-c.R
@@ -1,8 +1,7 @@
 # These examples demonstrate ways to display binned/aggregated selections
-library(crosstalk)
 library(plotly)
 
-tx <- SharedData$new(txhousing, ~city)
+tx <- highlight_unit(txhousing, ~city)
 p1 <- ggplot(tx, aes(date, median, group = city)) + geom_line() + xlab(NULL)
 gg1 <- ggplotly(p1, tooltip = c("city", "date", "median"))
 p2 <- plot_ly(tx, x = ~median, color = I("black")) %>% 
diff --git a/demo/crosstalk-highlight-epl-2.R b/demo/crosstalk-highlight-epl-2.R
@@ -2,7 +2,6 @@ library(engsoccerdata)
 library(dplyr)
 library(tidyr)
 library(plotly)
-library(crosstalk)
 
 # shape data into desired format
 dat <- england %>% 
@@ -21,7 +20,7 @@ dat <- england %>%
   mutate(meanP = mean(cumpts)) %>%
   filter(Season > 2006)
 
-sd <- SharedData$new(dat, ~team, "Select a team")
+sd <- highlight_unit(dat, ~team, "Select a team")
 
 # a 'wormchart' like fig 8 here http://www.gradaanwr.net/wp-content/uploads/2016/06/dataApr16.pdf
 p <- ggplot(sd, aes(x = gameno, y = cumpts - meanP)) + 
@@ -33,7 +32,7 @@ p <- ggplot(sd, aes(x = gameno, y = cumpts - meanP)) +
     y = "Cumulative points (above/below) average"
   ) 
 
-gg <- ggplotly(p, width = 1050, height = 600, tooltip = "team")
+gg <- ggplotly(p, tooltip = "team")
 
 highlight(
   gg, 
diff --git a/demo/crosstalk-highlight-epl.R b/demo/crosstalk-highlight-epl.R
@@ -2,7 +2,6 @@ library(engsoccerdata)
 library(dplyr)
 library(tidyr)
 library(plotly)
-library(crosstalk)
 
 # shape data into desired format
 dat <- england %>% 
@@ -17,7 +16,7 @@ dat <- england %>%
   group_by(Season, team) %>% 
   mutate(gameno = row_number(), cumpts = cumsum(pts))
 
-sd <- SharedData$new(dat, ~Season, "Select a season")
+sd <- highlight_unit(dat, ~Season, "Select a season")
 
 p <- ggplot(sd, aes(x = gameno, y = cumpts)) + 
   geom_line(aes(color = Season, group = Season), alpha = 0.5) + 
diff --git a/demo/crosstalk-highlight-ggpairs.R b/demo/crosstalk-highlight-ggpairs.R
@@ -1,4 +1,5 @@
 library(GGally)
-d <- SharedData$new(iris)
-p <- GGally::ggpairs(d, aes(colour = Species), columns = 1:5)
-ggplotly(p) %>% highlight("plotly_selected")
+d <- highlight_unit(iris)
+p <- ggpairs(d, aes(colour = Species), columns = 1:5)
+ggplotly(p) %>% 
+  highlight("plotly_selected")
diff --git a/demo/crosstalk-highlight-ggplotly.R b/demo/crosstalk-highlight-ggplotly.R
@@ -1,8 +1,7 @@
 library(plotly)
-library(crosstalk)
 
 # see https://vimeo.com/202647310
-d <- SharedData$new(txhousing, ~city, "Select a city")
+d <- highlight_unit(txhousing, ~city, "Select a city")
 p <- ggplot(d, aes(date, median, group = city)) + geom_line()
 ggplotly(p, tooltip = "city") %>%
   layout(title = "Click on a line to highlight a year") %>%
@@ -11,16 +10,15 @@ ggplotly(p, tooltip = "city") %>%
 # crosstalk keys are automatically added to the group aesthetic...
 # if you want to avoid adding the key to group for a layer,
 # use the original data
-sd <- SharedData$new(txhousing, ~city)
-p <- ggplot(sd, aes(month, median)) +
+p <- ggplot(d, aes(month, median)) +
   geom_line(aes(group = city)) + 
   geom_smooth(data = txhousing, method = "gam") + 
   facet_wrap(~ year)
 ggplotly(p) %>%
   layout(title = "Click on a line to highlight a year")
 
 # perhaps a more useful example
-sd <- SharedData$new(txhousing, ~year)
+sd <- highlight_unit(txhousing, ~year)
 p <- ggplot(sd, aes(month, median)) +
   geom_line(aes(group = year)) + 
   geom_smooth(data = txhousing, method = "gam") + 
diff --git a/demo/crosstalk-highlight-intro.R b/demo/crosstalk-highlight-intro.R
@@ -1,5 +1,4 @@
 library(plotly)
-library(crosstalk)
 
 nPatients <- 50
 nVisits <- 10
@@ -11,7 +10,7 @@ df <- data.frame(
 )
 
 # delare the patient variable as the "unit of interest"
-sd <- SharedData$new(df, ~patient)
+sd <- highlight_unit(df, ~patient)
 
 p <- plot_ly(sd, x = ~visit, y = ~perc, color = I("black"),
              text = ~paste("Patient:", patient)) %>%
diff --git a/demo/crosstalk-highlight-leaflet.R b/demo/crosstalk-highlight-leaflet.R
@@ -7,7 +7,7 @@ library(htmltools)
 # leaflet should respect these "global" highlight() options
 options(opacityDim = 0.5)
 
-sd <- SharedData$new(quakes)
+sd <- crosstalk_unit(quakes)
 
 p <- plot_ly(sd, x = ~depth, y = ~mag) %>% 
   add_markers(alpha = 0.5) %>%
diff --git a/demo/crosstalk-highlight-pipeline.R b/demo/crosstalk-highlight-pipeline.R
@@ -1,7 +1,6 @@
 library(plotly)
-library(crosstalk)
 
-sd <- SharedData$new(txhousing, ~city, "Select a city")
+sd <- highlight_unit(txhousing, ~city, "Select a city")
 
 base <- plot_ly(sd, color = I("black"), height = 400) %>%
   group_by(city)
diff --git a/demo/crosstalk-highlight-subplot.R b/demo/crosstalk-highlight-subplot.R
@@ -1,7 +1,6 @@
 library(plotly)
-library(crosstalk)
 
-d <- SharedData$new(mtcars)
+d <- highlight_unit(mtcars)
 s <- subplot(
   qplot(data = d, x = mpg, y = wt),
   qplot(data = d, x = mpg, y = vs)
diff --git a/demo/sf-dt.R b/demo/sf-dt.R
@@ -1,8 +1,7 @@
 library(plotly)
-library(crosstalk)
 
 nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
-ncsd <- SharedData$new(nc)
+ncsd <- highlight_unit(nc)
 
 map <- plot_ly(ncsd, split = ~NAME, color = I("gray"), hoveron = "fills") %>%
   highlight(persistent = TRUE, color = "red", opacityDim = 1) %>%
diff --git a/demo/sf-mapbox-data.R b/demo/sf-mapbox-data.R
@@ -10,7 +10,7 @@ plot_mapbox(res_mn, split = ~INDRESNAME, span = I(1))
 plot_mapbox(res_mn, split = ~INDRESNAME, color = ~AREA, stroke = ~PERIMETER, span = I(1))
 
 # linking with DT
-mn <- crosstalk::SharedData$new(res_mn)
+mn <- highlight_unit(res_mn)
 bscols(
   plot_mapbox(mn, split = ~INDRESNAME, text = ~INDRESNAME, hoverinfo = "text", hoveron = "fills") %>%
     layout(title = "Click a reservation", showlegend = FALSE),
@@ -19,7 +19,7 @@ bscols(
 
 # linking with plotly
 nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
-ncsd <- SharedData$new(nc)
+ncsd <- highlight_unit(nc)
 
 # note that brushing counties is currently possible with plot_ly(), but isn't quite working 
 # yet with plot_mapbox() -- https://github.com/plotly/plotly.js/issues/2512
diff --git a/demo/sf-plotly-3D-globe.R b/demo/sf-plotly-3D-globe.R
@@ -1,6 +1,5 @@
 library(plotly)
 library(dplyr)
-library(crosstalk)
 
 # latitude, longitude, and altitiude of tropical storms
 storms <- sf::st_read(system.file("shape/storms_xyz.shp", package = "sf"), quiet = TRUE)
@@ -43,7 +42,7 @@ globe <- plot_ly(height = 500) %>%
     hoverinfo = "none"
   ) %>%
   add_sf(
-    data = SharedData$new(storms, group = "storm paths"),
+    data = highlight_unit(storms, group = "storm paths"),
     name = "storm paths",
     x = ~ 1.001 * cos(degrees2radians(x)) * cos(degrees2radians(y)),
     y = ~ 1.001 * sin(degrees2radians(x)) * cos(degrees2radians(y)),
@@ -98,7 +97,7 @@ distanceByAlt <- storms %>%
   group_by(L1) %>%
   mutate(dist = arc_dist(X, Y)) %>%
   rename(altitude = Z) %>%
-  SharedData$new(~L1, group = "storm paths") %>%
+  highlight_unit(~L1, group = "storm paths") %>%
   plot_ly(x = ~dist, y = ~altitude, height = 400) %>%
   # plotly.js doesn't support color gradient along *2D* lines
   add_lines(color = I("gray")) %>%
diff --git a/demo/sf-plotly-storms.R b/demo/sf-plotly-storms.R
@@ -1,8 +1,7 @@
-library(htmltools)
-library(crosstalk)
+library(plotly)
 
 storms <- sf::st_read(system.file("shape/storms_xyz.shp", package = "sf"), quiet = TRUE)
-stormz <- SharedData$new(storms)
+stormz <- highlight_unit(storms)
 
 xy <- plot_ly(stormz, color = ~z, mode = "markers+lines", line = list(color = "gray"), hoverinfo = "none")
 xz <- add_sf(xy, y = ~z, color = ~y)
@@ -61,5 +60,5 @@ xyz3D <- plot_ly(stormz, color = ~z, z = ~z) %>%
   )
 
 
-
+library(htmltools)
 browsable(tagList(xyz2D, xyz3D))
diff --git a/man/ggplotly.Rd b/man/ggplotly.Rd
