Changing Marker Style in R-Plotly Scatter3D

Introduction

Plotly is a powerful data visualization library that allows users to create interactive, web-based visualizations. One of its features is the ability to add markers to 3D plots, which can be used to highlight specific points or trends in the data. In this article, we will explore how to change the style of clicked markers in R-Plotly’s scatter3D function.

Background

When working with large datasets and multiple visualizations, it can become challenging to identify specific points or trends in the data. Plotly’s 3D scatter plot feature allows users to add interactive markers that can be used to highlight specific points or trends in the data.

To achieve this, we need to use the plotlyProxy function, which creates a proxy object that allows us to manipulate individual elements of the plot. In this case, we want to change the style of clicked markers, so we will use the plotlyProxyInvoke function, which is used to invoke specific functions on the proxy object.

Problem Statement

The problem statement in the question is as follows:

“I’m trying to visualize a lot of data on a 3D plot, and have been using click events to display additional data on the selected marker. It becomes very difficult to see which marker is selected without a color change.”

In this case, the user has already implemented a click event listener that generates a point when a marker is clicked, but it does not work correctly for scatter3D plots.

Solution

To solve this problem, we need to use the plotlyProxy function to create a proxy object that allows us to manipulate individual elements of the plot. We will then use the plotlyProxyInvoke function to invoke specific functions on the proxy object, such as changing the color or size of markers.

Here is an example code snippet that demonstrates how to achieve this:

library(shiny)
library(ggplot2)
library(plotly)

ui <- navbarPage("Page",
  page1 <- fluidPage(
    titlePanel("Panel"),
    plotlyOutput('plot'))
)

server <- function(input, output, session) {
  # Create a proxy object for the plot
  plot_proxy <- reactiveValues(proxy = plotly::plotlyProxy('plot'))

  # Define a function to change the color of markers when clicked
  observeEvent(event_data("plotly_click"), {
    # Get the index of the selected marker
    marker_index <- event_data("plotly_click")$pointNumber[1] + 1
    
    # Change the color of all markers except the selected one
    plot_proxy$proxy %>% 
      plotlyProxyInvoke("restyle", list(marker = list(opacity = 0.5, color = "blue")))
    
    # Highlight the selected marker by changing its color and size
    plot_proxy$proxy %>% 
      plotlyProxyInvoke("restyle", list(marker = list(
        opacity = 1,
        color = "red",
        size = 10 + (marker_index - 1) * 5)))
  })

  # Render the plot
  output$plot <- renderPlotly({
    p <- plot_ly()
    p <- add_trace(p, data = mtcars, x = ~mpg, y = ~cyl, z = ~wt, color = ~hp, type = 'scatter3d', mode = "markers")
  })
}

# Create a shiny app
shinyApp(ui = ui, server = server)

In this code snippet, we first create a proxy object for the plot using plotly::plotlyProxy. We then define an observe event function that changes the color of all markers except the selected one when a click event occurs. Finally, we highlight the selected marker by changing its color and size.

Conclusion

Changing the style of clicked markers in R-Plotly’s scatter3D function can be achieved using the plotlyProxy and plotlyProxyInvoke functions. By creating a proxy object for the plot and invoking specific functions on it, we can manipulate individual elements of the plot to achieve our desired result.

Best Practices

• Use plotlyProxy to create a proxy object for your plot.
• Define an observe event function to detect changes in the plot.
• Use plotlyProxyInvoke to invoke specific functions on the proxy object.
• Manipulate individual elements of the plot as needed.

Common Issues

• Make sure to use the correct syntax when creating a proxy object and invoking functions on it.
• Ensure that you are using the correct data to identify the selected marker.
• Use debugging tools to identify any issues with your code.

Last modified on 2023-05-23