Unable to zoom or hover map using nested subplot()

My interactive dashboard where multiple Plotly objects including maps are displayed using nested subplot() in R:

library(digest)
library(sf)
library(jsonlite)
library(plotly)
library(ggplot2)
library(tidyr)
library(dplyr)
library(tibble)

sa_final_dataset <- read.csv("state_data.csv")
final_dataset <- read.csv("nation_data.csv")
australia_data <- read_sf("australia_map.shp")
pivot_data <- read.csv("pivot_data.csv")

sa_map_data <- subset(australia_data, STE_NAME21 == "South Australia")

# Interpolate and split into line segments
  interpolate_segments_as_lines <- function(df, steps = 50) {
    df %>%
      rowwise() %>%
      do({
        x_vals <- seq(.$fromX, .$X, length.out = steps)
        y_vals <- seq(.$fromY, .$Y, length.out = steps)
        position <- seq(0, 1, length.out = steps)

        # Construct segments
        data.frame(
          x = head(x_vals, -1),
          y = head(y_vals, -1),
          xend = tail(x_vals, -1),
          yend = tail(y_vals, -1),
          position = head(position, -1),
          FROM_NAME = .$FROM_NAME,
          TO_NAME = .$TO_NAME,
          TOTAL = .$TOTAL,
          AGE_15_34 = .$AGE_15_34,
          AGE_35_49 = .$AGE_35_49,
          AGE_50_65 = .$AGE_50_65,
          AGE_65_PLUS = .$AGE_65_PLUS
        )
      }) %>%
      ungroup()
  }

  # Apply interpolation
  sa_lines_segments <- interpolate_segments_as_lines(sa_final_dataset)

  sa_lines_segments <- sa_lines_segments %>%
    mutate(
      thickness = round(rescale(abs(TOTAL), to = c(3, 10))),
      color = rgb(
        colorRamp(c("#cc0b15ff", "#1cc00dff"))(position),
        maxColorValue = 255
      )
    )

  # Use add_segments with thickness mapped to line width
  sa_plotly <- plot_ly(height = 900, source = "South_Australia_Map") %>%
    add_sf(
    data = sa_map_data,
    fill = "#007499",
    line = list(color = "black"),
    showlegend = FALSE,
    hoverinfo = "skip"
    )

  # Optionally, you can color by direction or other variable if needed
  for (t in sort(unique(sa_lines_segments$thickness))) {
    seg_data <- sa_lines_segments %>% filter(thickness == t )
    for (g in unique(seg_data$color)) {
      seg_data_color <- seg_data %>% filter(color == g)
      if (nrow(seg_data_color) > 0) {
        sa_plotly <- sa_plotly %>%
          add_segments(
            data = seg_data_color,
            x = ~x, y = ~y, xend = ~xend, yend = ~yend,
            line = list(
              color = ~color,
              width = t
            ),
            opacity = 0.8,
            hovertext = paste0(
              "From: ", seg_data_color$FROM_NAME, "<br>",
              "To: ", seg_data_color$TO_NAME, "<br>",
              "Age 15 - 34 Migrations: <b>", seg_data_color$AGE_15_34, "</b><br>",
              "Age 35 - 49 Migrations: <b>", seg_data_color$AGE_35_49, "</b><br>",
              "Age 50 - 65 Migrations: <b>", seg_data_color$AGE_50_65, "</b><br>",
              "Age 66+ Migrations: <b>", seg_data_color$AGE_65_PLUS, "</b><br>",
              "Net Migrations: <b>", seg_data_color$TOTAL, "</b>"
            ),
            hoverinfo = "text",
            showlegend = FALSE,
            inherit = FALSE,
            yaxis="y"
          )
      }
    }
  }

  sa_plotly <- sa_plotly %>%
    layout(
    xaxis = list(title = ""),
    yaxis = list(title = "")
    )

  interpolate_segments_as_lines_inter <- function(df, steps = 50) {
    df %>%
    rowwise() %>%
    do({
      x_vals <- seq(.$fromX, .$X, length.out = steps)
      y_vals <- seq(.$fromY, .$Y, length.out = steps)
      position <- seq(0, 1, length.out = steps)
      data.frame(
      x = head(x_vals, -1),
      y = head(y_vals, -1),
      xend = tail(x_vals, -1),
      yend = tail(y_vals, -1),
      position = head(position, -1),
      group = .$group,
      thickness = .$thickness,
      SA3_NAME21 = .$SA3_NAME21,
      State = .$State,
      FinalValue = .$FinalValue,
      AGE_15_34 = .$AGE_15_34,
      AGE_35_49 = .$AGE_35_49,
      AGE_50_65 = .$AGE_50_65,
      AGE_65_PLUS = .$AGE_65_PLUS
      )
    }) %>%
    ungroup()
  }

  inter_lines_segments <- interpolate_segments_as_lines_inter(final_dataset)

  inter_hovertexts <- paste0(
    "SA3 Name: ", inter_lines_segments$SA3_NAME21, "<br>",
    "Age 15 - 34 Migrations: <b>", inter_lines_segments$AGE_15_34, "</b><br>",
    "Age 35 - 49 Migrations: <b>", inter_lines_segments$AGE_35_49, "</b><br>",
    "Age 50 - 65 Migrations: <b>", inter_lines_segments$AGE_50_65, "</b><br>",
    "Age 66+ Migrations: <b>", inter_lines_segments$AGE_65_PLUS, "</b><br>",
    "State: <b>", inter_lines_segments$State, "</b><br>",
    "Net Value: <b>", inter_lines_segments$FinalValue, "</b>"
  )

  # Build plotly map for inter-state migration
  plotly_gg_map <- plot_ly(height = 900, source = "Australia_Map") %>%
    add_sf(
      data = subset(australia_data, STE_NAME21 != "South Australia"),
      fill = "#007499",
      line = list(color = "black"),
      showlegend = FALSE,
      hoverinfo = "skip"
    ) %>%
    add_sf(
      data = subset(australia_data, STE_NAME21 == "South Australia"),
      fill = "#007499",
      line = list(color = "black"),
      showlegend = FALSE,
      hoverinfo = "skip"
    )

  groups <- c("Outgoing Migration", "Incoming Migration")
  colors <- c("Outgoing Migration" = "#cc0b15ff", "Incoming Migration" = "#1cc00dff")

  # Track if legend has been added for each group
  legend_added <- setNames(rep(FALSE, length(groups)), groups)

  for (g in groups) {
    for (t in sort(unique(inter_lines_segments$thickness))) {
    seg_data <- inter_lines_segments %>%
      filter(group == g, thickness == t)

    if (nrow(seg_data) > 0) {
      seg_hovertexts <- inter_hovertexts[which(inter_lines_segments$group == g & inter_lines_segments$thickness == t)]
      plotly_gg_map <- plotly_gg_map %>%
      add_segments(
        data = seg_data,
        x = ~x, y = ~y, xend = ~xend, yend = ~yend,
        line = list(color = colors[[g]], width = t),
        opacity = 0.7,
        hovertext = seg_hovertexts,
        hoverinfo = "text",
        name = g,
        legendgroup = g,
        showlegend = !legend_added[[g]]
      )
      legend_added[[g]] <- TRUE
    }
    }
  }

  plotly_gg_map <- plotly_gg_map %>%
    layout(
      showlegend = TRUE,
      xaxis = list(title = ""),
      yaxis = list(overlaying="y2"),
      legend = list(title = list(text = ""))
    )

  plotly_combined <- subplot(
    plotly_gg_map,
    sa_plotly,
    nrows = 1
  ) %>%
    layout(
      showlegend = TRUE,
      legend = list(
        orientation = "h",
        x = 0.5,
        y = 0.1,
        xanchor = "center",
        yanchor = "top",
        font = list(size = 12)
      ),
      annotations = list(
        list(
          text = "<b>Inter State Migration Map</b>",
          x = 0.185,
          y = 1.035,
          xref = "paper",
          yref = "paper",
          showarrow = FALSE
        ),
        list(
          text = "<b>Intra State Migration Map</b>",
          x = 0.825,
          y = 1.035,
          xref = "paper",
          yref = "paper",
          showarrow = FALSE
        )
      )
    )

  # Plotly table
  table_plot <- plot_ly(
    source = "Table 1",
    type = "table",
    columnwidth = c(15, 10, 10, 10, 10, 10, 10, 10, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20),
    header = list(
      values = colnames(pivot_data),
      align = "center",
      line = list(color = "#000000ff"),
      font = list(color = list(
        "black",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white"
      ), size = 12),
      fill = list(
        color = list(
          c("#ffffffff"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333")
        )
      ),
      height = 40
    ),
    cells = list(
      values = rbind(t(as.matrix(unname(pivot_data)))
      ),
      align = "center",
      line = list(color = "#000000ff"),
      fill = list(color = "#ffffffff"),
      font = list(color = "#000000ff", size = 12)
    )
  )

  table_plot2 <- plot_ly(
    type = "table",
    source = "Table 2",
    header = list(
        values = list(
            c("<b>Sources:</b> Demo")
        ),
        align = "left",
        font = list(family = "Arial", size = 12),
        height = 40,
        line = list(color = "rgba(0,0,0,0)") # Remove borders
    ),
    cells = list(
        line = list(color = "rgba(0,0,0,0)") # Remove borders
    ),
    domain = list(
        x = c(0, 1),
        y = c(0, 0.03)
    )
  )

  # Ensure hoverinfo is retained for all subplots by explicitly setting hoverinfo for each axis
  final_combined <- subplot(
    table_plot, plotly_combined, table_plot2,
    nrows = 3,
    heights = c(0.25, 0.7, 0.05),
    shareX = FALSE,
    shareY = FALSE,
    titleX = FALSE,
    titleY = FALSE
  ) %>%
  layout(
    annotations = list(
      list(
        text = "<b>Average Monthly Net Migration</b>",
        x = 0.5,
        y = 1.035,
        xref = "paper",
        yref = "paper",
        showarrow = FALSE,
        font = list(size = 16, color = "#000000")
      )
    )
  )

print(final_combined)

When using subplot() with multiple maps from sf objects I cannot zoom or pan into the maps and hover text does not appear. It works when the map is plotted individually. Files to reproduce the issue. The data has been modified to remove confidential information so please ignore inconsistency or logical mismatches. It's part of a larger architecture where R acts only as the backend, hence I am limited to Plotly, Leaflet and MapView.

Is this a bug in nested subplot() when used with sf objects or map traces? How can I retain map interactivity (zoom, pan, hover) when embedded as part of a nested subplot() layout? I've tried using subplot() with add_sf() and add_trace() and modifying layout options (dragmode, uirevision, and geo anchoring). final_combined should be able to convert it into Plotly JSON using:

plotly_json <- plotly_json(final_combined, jsonedit = FALSE)

Commencez par exécuter l’exemple fourni de subplots imbriqués et examinez final_combined, plotly_combined et les traces de carte basées sur sf. Utilisez plotly_json(final_combined, jsonedit = FALSE) pour comparer la mise en page imbriquée avec les cartes rendues individuellement. Le travail est terminé lorsque les cartes intégrées conservent le zoom, le déplacement et le texte au survol sans casser le tableau ni les autres contenus des subplots.