Functionality

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# Create a clipboard button on the rendered HTML page
source(here::here("clipboard.R")); clipboard

# Set seed for reproducibility
#set.seed(1982) 
# Set global options for all code chunks
knitr::opts_chunk$set(
  # Disable messages printed by R code chunks
  message = FALSE,    
  # Disable warnings printed by R code chunks
  warning = FALSE,    
  # Show R code within code chunks in output
  echo = TRUE,        
  # Include both R code and its results in output
  include = TRUE,     
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  eval = TRUE,       
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  cache = FALSE,      
  # Align figures in the center of the output
  fig.align = "center",
  # Enable retina display for high-resolution figures
  retina = 2,
  # Show errors in the output instead of stopping rendering
  error = TRUE,
  # Do not collapse code and output into a single block
  collapse = FALSE
)
# Start the figure counter
fig_count <- 0
# Define the captioner function
captioner <- function(caption) {
  fig_count <<- fig_count + 1
  paste0("Figure ", fig_count, ": ", caption)
}

library(MetricGraph)
library(ggplot2)
library(reshape2)
library(dplyr)
library(viridis)
library(plotly)
library(patchwork)

library(slackr)
source("keys.R")
slackr_setup(token = token) # token comes from keys.R

## [1] "Successfully connected to Slack"

# Color for axis name and axis numbers
colaxnn <- "gray"
# Global font size
gfsize <- 16
# Dark blue color
mydarkblue <- "#0000C8"
# Global size or widht for objects
gsw <- 7

gets.graph.interval <- function(n){
  edge <- rbind(c(0,0),c(1,0))
  edges = list(edge)
  graph <- metric_graph$new(edges = edges)
  graph$build_mesh(n = n)
  return(graph)
}

gets.graph.circle <- function(n){
  r = 1/(pi)
  theta <- seq(from=-pi,to=pi,length.out = 100)
  edge <- cbind(1+r+r*cos(theta),r*sin(theta))
  edges = list(edge)
  graph <- metric_graph$new(edges = edges)
  graph$build_mesh(n = n)
  return(graph)
}

# Function to build a tadpole graph and create a mesh
gets.graph.tadpole <- function(h){
  edge1 <- rbind(c(0,0),c(1,0))
  theta <- seq(from=-pi,to=pi,length.out = 100)
  edge2 <- cbind(1+1/pi+cos(theta)/pi,sin(theta)/pi)
  edges <- list(edge1, edge2)
  graph <- metric_graph$new(edges = edges, verbose = 0)
  graph$set_manual_edge_lengths(edge_lengths = c(1,2))
  graph$build_mesh(h = h)
  return(graph)
}

# Function to order the vertices for plotting
plotting.order <- function(v, graph){
  edge_number <- graph$mesh$VtE[, 1]
  pos <- sum(edge_number == 1)+1
  return(c(v[1], v[3:pos], v[2], v[(pos+1):length(v)], v[2]))
}

# Original camera
eye <- list(x = 5, y = 3, z = 4)
center <- list(x = (1+2/pi)/2, y = 0, z = 0)

# Fraction to move toward center (zoom in)
f <- 0  # 50% closer

new_eye <- list(
  x = eye$x + f * (center$x - eye$x),
  y = eye$y + f * (center$y - eye$y),
  z = eye$z + f * (center$z - eye$z)
)

tadpole.layout <- function(x_range, y_range, z_range){
  return(list(xaxis = list(title = list(text = "x", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = x_range),
              yaxis = list(title = list(text = "y", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = y_range),
              zaxis = list(title = list(text = "z", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = z_range),
              aspectratio = list(x = 2*(1+2/pi), 
                                 y = 2*(2/pi), 
                                 z = 1*(2/pi)),
              camera = list(eye = list(x = 5, y = 3, z = 4),
                            center = list(x = (1+2/pi)/2, y = 0, z = 0))))
}

tadpole.layout.with.zoom <- function(x_range, y_range, z_range){
  return(list(xaxis = list(title = list(text = "x", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = x_range),
              yaxis = list(title = list(text = "y", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = y_range),
              zaxis = list(title = list(text = "z", font = list(color = colaxnn)),  tickfont = list(color = colaxnn), range = z_range),
              aspectratio = list(x = 2*(1+2/pi), 
                                 y = 2*(2/pi), 
                                 z = 1*(2/pi)),
              camera = list(eye = new_eye,
                            center = center)))
}

myggsave <- function(plot, width = 9.22, height = 7.05) {
  
  dir_to_save <- here::here("data_files/tikzpic")
  obj_name <- deparse(substitute(plot))
  tex_name <- file.path(dir_to_save, paste0(obj_name, ".tex"))
  
  # Create directory if it doesn't exist
  if (!dir.exists(dir_to_save)) dir.create(dir_to_save, recursive = TRUE)
  
  # Save TikZ plot
  tikzDevice::tikz(tex_name, standAlone = TRUE, width = width, height = height)
  print(plot)
  dev.off()
  
  # Compile to PDF
  system(paste0("pdflatex -output-directory=", dir_to_save, " ", tex_name))
  
  # Remove auxiliary files
  aux_ext <- c(".aux", ".log", ".tex")
  for (ext in aux_ext) {
    f <- file.path(dir_to_save, paste0(obj_name, ext))
    if (file.exists(f)) file.remove(f)
  }
  
  # Remove any temporary raster images generated by tikzDevice
  ras_files <- list.files(
    dir_to_save,
    pattern = paste0(obj_name, "_ras[0-9]+\\.png$"),
    full.names = TRUE
  )
  if (length(ras_files) > 0) file.remove(ras_files)
  
  message("PDF saved at: ", file.path(dir_to_save, paste0(obj_name, ".pdf")))
}

library(plotly)
library(reticulate)
library(jsonlite)
library(glue)

combine_plotly_grid_pdf <- function(plots, output_pdf = "combined_grid.pdf", 
                                    ncol = 2, width = 1400, height = 1000, scale = 2, 
                                    resolution = 300, spacing = 50) {
  py_config() # Check Python configuration
  if (!is.list(plots) || length(plots) < 2) {
    stop("plots must be a list of at least two plotly objects")
  }
  
  # Temporary PNG files
  tmp_files <- sapply(seq_along(plots), function(i) tempfile(fileext = ".png"))
  
  # Save all plots as PNGs
  for (i in seq_along(plots)) {
    plotly::save_image(plots[[i]], tmp_files[i], width = width, height = height, scale = scale)
  }
  
  # Convert temporary files to JSON array for Python
  py_tmp_files <- toJSON(tmp_files, auto_unbox = TRUE)
  
  # Python code using glue (variables directly substituted)
  py_code <- glue("
from PIL import Image
import math

files = {py_tmp_files}
images = [Image.open(f) for f in files]

ncol = {ncol}
nrow = math.ceil(len(images)/ncol)
spacing = {spacing}

cell_width = max(img.width for img in images)
cell_height = max(img.height for img in images)

combined_width = cell_width * ncol + spacing * (ncol - 1)
combined_height = cell_height * nrow + spacing * (nrow - 1)

combined = Image.new('RGB', (combined_width, combined_height), (255, 255, 255))

for idx, img in enumerate(images):
    row = idx // ncol
    col = idx % ncol
    x = col * (cell_width + spacing)
    y = row * (cell_height + spacing)
    combined.paste(img, (x, y))

combined.save(r'{output_pdf}', 'PDF', resolution={resolution})
  ")
  
  # Run Python code
  py_run_string(py_code)
  
  # Clean up temporary files
  file.remove(tmp_files)
  
  message("Combined PDF saved to: ", output_pdf)
}

# p1 <- plot_ly(z = ~volcano, type = "surface") %>% layout(title = "Plot 1")
# p2 <- plot_ly(z = ~volcano + 5, type = "surface") %>% layout(title = "Plot 2")
# p3 <- plot_ly(z = ~volcano + 10, type = "surface") %>% layout(title = "Plot 3")
# p4 <- plot_ly(z = ~volcano + 15, type = "surface") %>% layout(title = "Plot 4")
# 
# combine_plotly_grid_pdf(list(p1, p2, p3, p4), output_pdf = "plots_2x2.pdf", ncol = 4)

library(plotly)
library(reticulate)


combine_plotly_pdf <- function(p1, p2, output_pdf = "combined_side_by_side.pdf", 
                               width = 1400, height = 1000, scale = 2, resolution = 300,
                               spacing = 50) {
  py_config() # Check Python configuration
  # Temporary PNG paths
  tmp1 <- tempfile(fileext = ".png")
  tmp2 <- tempfile(fileext = ".png")
  
  # Save the plotly plots as PNGs
  plotly::save_image(p1, tmp1, width = width, height = height, scale = scale)
  plotly::save_image(p2, tmp2, width = width, height = height, scale = scale)
  
  # Python code to combine PNGs side by side
  py_run_string(sprintf("
from PIL import Image

img1 = Image.open(r'%s')
img2 = Image.open(r'%s')

# Compute dimensions
combined_width = img1.width + img2.width + %d
combined_height = max(img1.height, img2.height)

combined = Image.new('RGB', (combined_width, combined_height), (255, 255, 255))
combined.paste(img1, (0, 0))
combined.paste(img2, (img1.width + %d, 0))

# Save as PDF
combined.save(r'%s', 'PDF', resolution=%d)
", tmp1, tmp2, spacing, spacing, output_pdf, resolution))
  
  # Remove temporary PNGs
  file.remove(tmp1, tmp2)
  
  message("Combined PDF saved to: ", output_pdf)
}


# # Create example 3D plotly plots
# p1 <- plot_ly(z = ~volcano, type = "surface") %>% layout(title = "Plot 1")
# p2 <- plot_ly(z = ~volcano + 10, type = "surface") %>% layout(title = "Plot 2")
# 
# # Combine into one PDF
# combine_plotly_pdf(p1, p2, output_pdf = "my_plots.pdf")

library(plotly)
library(reticulate)

combine_plotly_pdf_single <- function(p, output_pdf = "single_plot.pdf", 
                                      width = 1400, height = 1000, scale = 2, 
                                      resolution = 300) {
  py_config()  # Check Python configuration
  
  # Temporary PNG path
  tmp_png <- tempfile(fileext = ".png")
  
  # Save the Plotly plot as PNG
  plotly::save_image(p, tmp_png, width = width, height = height, scale = scale)
  
  # Python code: open PNG, convert to RGB, save as PDF
  py_run_string(sprintf("
from PIL import Image

img = Image.open(r'%s')
img_rgb = img.convert('RGB')
img_rgb.save(r'%s', 'PDF', resolution=%d)
", tmp_png, output_pdf, resolution))
  
  # Clean up temporary PNG
  file.remove(tmp_png)
  
  message("PDF saved to: ", normalizePath(output_pdf))
}
# combine_plotly_pdf_single(p3, output_pdf = "single_plot.pdf")
# # Example plot
# p1 <- plot_ly(z = ~volcano, type = "surface") %>% layout(title = "Single Plot")
# 
# # Save as PDF
# combine_plotly_pdf_single(p1, output_pdf = "single_plot.pdf")

1 References

grateful::cite_packages(output = "paragraph", out.dir = ".")

We used R version 4.5.2 (R Core Team 2025a) and the following R packages: cowplot v. 1.2.0 (Wilke 2025), ggmap v. 4.0.2 (Kahle and Wickham 2013), ggpubr v. 0.6.3 (Kassambara 2026), ggtext v. 0.1.2 (Wilke and Wiernik 2022), glue v. 1.8.0 (Hester and Bryan 2024), grid v. 4.5.2 (R Core Team 2025b), here v. 1.0.1 (Müller 2020), htmltools v. 0.5.8.1 (Cheng et al. 2024), INLA v. 25.11.22 (Rue, Martino, and Chopin 2009; Lindgren, Rue, and Lindström 2011; Martins et al. 2013; Lindgren and Rue 2015; De Coninck et al. 2016; Rue et al. 2017; Verbosio et al. 2017; Bakka et al. 2018; Kourounis, Fuchs, and Schenk 2018), inlabru v. 2.13.0 (Yuan et al. 2017; Bachl et al. 2019), knitr v. 1.50 (Xie 2014, 2015, 2025), latex2exp v. 0.9.8 (Meschiari 2026), Matrix v. 1.7.3 (Bates, Maechler, and Jagan 2025), MetricGraph v. 1.5.0.9000 (Bolin, Simas, and Wallin 2023a, 2023b, 2024, 2025; Bolin et al. 2024), OpenStreetMap v. 0.4.1 (Fellows and Stotz 2025), patchwork v. 1.3.1 (Pedersen 2025), plotly v. 4.11.0 (Sievert 2020), plotrix v. 3.8.14 (J 2006), renv v. 1.1.7 (Ushey and Wickham 2026), reshape2 v. 1.4.4 (Wickham 2007), reticulate v. 1.44.1 (Ushey, Allaire, and Tang 2025), rmarkdown v. 2.30 (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020; Allaire et al. 2025), rSPDE v. 2.5.2.9000 (Bolin and Kirchner 2020; Bolin and Simas 2023; Bolin, Simas, and Xiong 2024), scales v. 1.4.0 (Wickham, Pedersen, and Seidel 2025), sf v. 1.1.0 (E. Pebesma 2018; E. Pebesma and Bivand 2023), slackr v. 3.4.0 (Kaye et al. 2025), sp v. 2.2.1 (E. J. Pebesma and Bivand 2005; Bivand, Pebesma, and Gomez-Rubio 2013), tidyverse v. 2.0.0 (Wickham et al. 2019), tikzDevice v. 0.12.6 (Sharpsteen and Bracken 2023), viridis v. 0.6.5 (Garnier et al. 2024), xaringanExtra v. 0.8.0 (Aden-Buie and Warkentin 2024).

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