library(plotly) nPatients <- 50 nVisits <- 10 d <- data.frame( perc = rnorm(n = nPatients * nVisits, mean = 50, sd = 10), patient = rep(seq(nPatients), each = nVisits), visit = rep(seq(nVisits), nPatients) ) # Define a 'primary key' variable (patient) for interactive queries hd <- highlight_key(d, ~patient) # Create a "repeated measures" plot p <- plot_ly(hd, x = ~visit, y = ~perc, color = I("black"), text = ~paste("Patient:", patient)) %>% group_by(patient) %>% add_trace(mode = "markers+lines") # Since the data provided (hd) has a primary key definition of 'patient', # **plotly** knows to highlight any lines/markers matching the selected patient(s). # Go ahead and *click* on any marker and watch the entire 'patient' be highlighted layout(p, title = "Click on a marker to highlight that patient") # By default, the "on event" is "plotly_click", but we can change that to # "plotly_selected", which corresponds to click and drag mouse events. p %>% layout(title = "Click and drag to select patient") %>% highlight("plotly_selecting") # Plotly provides two types of drag modes that will trigger a "plotly_selected" # event: "lasso" and "select". You can change the dragmode interactively via # the modebar and/or set the default dragmode via `layout()`. p %>% layout(title = "Click and drag to select patient", dragmode = "lasso") %>% highlight("plotly_selecting") # The first argument of `highlight()`, `on`, sets the interaction type used # trigger a "highlight selection". The second argument, `off`, sets the # interaction required to clear the selection set and return to the original view. # IF you don't provide an `off` event, a sensible one will be choosen based # on the value of `on`. p %>% highlight(on = "plotly_hover", off = "plotly_doubleclick") %>% layout(dragmode = "zoom") # By default, all selections are transient, meaning prior selections are # removed from the selection set before new selections are added. To prevent # prior selections from being removed, hold down the shift key while triggering # the event p %>% layout(title = "Shift the key to accumulate selections") %>% highlight("plotly_hover") # Sometimes its useful to compare two or more different selection sets. # For example, how do patients with a high response on visit 1 compare to those # with a low response? To make this sort of comparison, we can alter the color # in multiple persistent selections. By setting the dynamic argument to `TRUE` # a colourpicker will appear just above the plotly visualization. # At any given time, the value of this widget controls the color of new selection(s). highlight(p, dynamic = TRUE) # By default, the colourpicker widget uses colors from the "Set1" # colour brewer palette (@RColorBrewer), but any set of valid R colors can # be supplied to the color argument. colors <- RColorBrewer::brewer.pal(4, "Dark2") highlight(p, color = colors, dynamic = TRUE)
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