如何注释n维可绘SPLOM的每个子图？

Question

我从下面的示例代码开始，该代码生成一个SPLOM：

library(plotly)

df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/iris-data.csv')
pl_colorscale=list(c(0.0, '#19d3f3'),
                   c(0.333, '#19d3f3'),
                   c(0.333, '#e763fa'),
                   c(0.666, '#e763fa'),
                   c(0.666, '#636efa'),
                   c(1, '#636efa'))

axis = list(showline=FALSE,
            zeroline=FALSE,
            gridcolor='#ffff',
            ticklen=4)

p <- df %>%
    plot_ly() %>%
    add_trace(
        type = 'splom',
        dimensions = list(
            list(label='sepal length', values=~sepal.length),
            list(label='sepal width', values=~sepal.width),
            list(label='petal length', values=~petal.length),
            list(label='petal width', values=~petal.width)
        ),
        text=~class,
        marker = list(
            color = as.integer(df$class),
            colorscale = pl_colorscale,
            size = 7,
            line = list(
                width = 1,
                color = 'rgb(230,230,230)'
            )
        )
    ) %>%
    layout(
        title= 'Iris Data set',
        hovermode='closest',
        dragmode= 'select',
        plot_bgcolor='rgba(240,240,240, 0.95)',
        xaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
        yaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
        xaxis2=axis,
        xaxis3=axis,
        xaxis4=axis,
        yaxis2=axis,
        yaxis3=axis,
        yaxis4=axis
    )
p

我想使用plotly::add_annotations()函数向注解中的每个图添加注释，如下所示：

library(plotly)

df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/iris-data.csv')
pl_colorscale=list(c(0.0, '#19d3f3'),
                   c(0.333, '#19d3f3'),
                   c(0.333, '#e763fa'),
                   c(0.666, '#e763fa'),
                   c(0.666, '#636efa'),
                   c(1, '#636efa'))

axis = list(showline=FALSE,
            zeroline=FALSE,
            gridcolor='#ffff',
            ticklen=4)

p <- df %>%
    plot_ly() %>%
    add_trace(
        type = 'splom',
        dimensions = list(
            list(label='sepal length', values=~sepal.length),
            list(label='sepal width', values=~sepal.width),
            list(label='petal length', values=~petal.length),
            list(label='petal width', values=~petal.width)
        ),
        text=~class,
        marker = list(
            color = as.integer(df$class),
            colorscale = pl_colorscale,
            size = 7,
            line = list(
                width = 1,
                color = 'rgb(230,230,230)'
            )
        )
    ) %>%
    layout(
        title= 'Iris Data set',
        hovermode='closest',
        dragmode= 'select',
        plot_bgcolor='rgba(240,240,240, 0.95)',
        xaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
        yaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
        xaxis2=axis,
        xaxis3=axis,
        xaxis4=axis,
        yaxis2=axis,
        yaxis3=axis,
        yaxis4=axis
    ) %>%
    add_annotations(
        text = "stats::cor(x, y)",
        x = 1.00, 
        y = 1.00, 
        xref        = "paper",
        yref        = "paper",
        xanchor     = "right",
        yanchor     = "top",
        showarrow   = FALSE,
        legendtitle = FALSE
    )
p

但这只会为SPLOM添加注释，而不是为每个子图添加注释。是否有一种方法可以在每个子图上放置一个批注，而不用使用多少维来生成SPLOM？我的目的是为每个子图添加一个相关值。