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是否可以“链接”两个散景/全息对象的悬停，以便同时显示两个对象上的悬停？

这是我想要实现的示例：

在此处输入图像描述

目前我只能在其中一个图像上显示悬停，但不能同时在两个图像上显示： 在此处输入图像描述

请在下面找到我用来生成最后一个数字的可重现代码。

import xarray as xr
import hvplot.xarray  # noqa

import holoviews as hv
from holoviews import opts
hv.extension('bokeh')

import panel as pn
import panel.widgets as pnw
pn.extension()

from bokeh.models import HoverTool

# Load tutorial xarray air dataset
air_ds = xr.tutorial.open_dataset('air_temperature').load()

# Create two different datasets based on the yearly mean and standard deviation of the  air temperature
meanairbyyear = air_ds.air.groupby('time.year').mean()
stdairbyyear = air_ds.air.groupby('time.year').std()
meanair2d = xr.Dataset(
    {
        "y2013": (["lat", "lon"], meanairbyyear[0,:,:]),
        "y2014": (["lat", "lon"], meanairbyyear[1,:,:]),
    },
    coords={
        "lon": ("lon", meanairbyyear.lon),
        "lat": ("lat", meanairbyyear.lat),
    },
)
stdair2d = xr.Dataset(
    {
        "y2013": (["lat", "lon"], stdairbyyear[0,:,:]),
        "y2014": (["lat", "lon"], stdairbyyear[1,:,:]),
    },
    coords={
        "lon": ("lon", stdairbyyear.lon),
        "lat": ("lat", stdairbyyear.lat),
    },
)

# Define panel object
variable_type = ('y2013', 'y2014')

variables  = pnw.RadioButtonGroup(name='Variable', value='y2014', 
                                 options=list(variable_type))

def plot_map_mean(var):
    plt = meanair2d[var].hvplot.contourf(width=400)
    # Hover
    MyHover = HoverTool(
        tooltips=[
            ( 'Lon', ' $x'),
            ( 'Lat', ' $y'),
            ( var + ' Mean', '@' + var),
       ],
        formatters={
            '$x' : 'numeral',
            '$y' : 'numeral',
            '@' + var : 'numeral',            
        },
        point_policy="follow_mouse"
    )
    plt.opts(tools = [MyHover])
    return plt

def plot_map_std(var):
    plt = stdair2d[var].hvplot.contourf(width=400)
    # Hover
    MyHover = HoverTool(
        tooltips=[
            ( 'Lon', ' $x'),
            ( 'Lat', ' $y'),
            ( var + ' Std', '@' + var),
       ],
        formatters={
            '$x' : 'numeral',
            '$y' : 'numeral',
            '@' + var : 'numeral',            
        },
        point_policy="follow_mouse"
    )
    plt.opts(tools = [MyHover])
    return plt

@pn.depends(variables)
def reactive_mean_plot(variables):
    return plot_map_mean(variables)

@pn.depends(variables)
def reactive_std_plot(variables):
    return plot_map_std(variables)

widgets   = pn.Column("<br>\n# Years", variables)
contour_pn = pn.Column(widgets,pn.Column("<br>\n### Mean",reactive_mean_plot),
                               pn.Column("<br>\n### Std",reactive_std_plot)
                      )
contour_pn
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