Python 如何使用bokeh select元素使滑块隐藏或不可见？

此示例与bokeh示例不同，滑块可以控制图中的条。（sliders.py） 在我的情况下，左侧有30多个滑块。它看起来有点凌乱，所以我尝试使用bokeh select元素来连接滑块。目标是当我选择时，滑块区域将只显示一个滑块

我阅读了文档，有两种使用方法： 一个是残疾人。如果为True，则小部件将变灰，并且不会响应UI事件。但它不会隐藏。另一个可见，但我得到一个属性错误： AttributeError（“滑块可见的意外属性，禁用类似属性”）

是否可以使bokeh滑块隐藏或不可见？或者有没有其他方法可以让滑块（超过30个）更清晰地区分

下面是可以在Jupyter笔记本中运行的代码

import bokeh.plotting.figure as bk_figure
from bokeh.io import curdoc, show
from bokeh.layouts import row, widgetbox
from bokeh.models import ColumnDataSource, Select
from bokeh.models.widgets import Slider, TextInput
from bokeh.io import output_notebook # enables plot interface in J notebook
import numpy as np
# init bokeh        
from bokeh.application import Application
from bokeh.application.handlers import FunctionHandler
    
    
output_notebook()
    
# Set up data
    
data = { 
    'line_x' : [1,2,3,4],
    'line_y' : [4,3,2,1],
    'bar_x':[1, 2, 3, 4],
    'bar_bottom':[1,1,1,1],
    'bar_top':[0.2, 2.5, 3.7, 4],
}
   
#bar_color
determine_top = data['bar_top']
determine_bottom = data['bar_bottom']
determine_color = []
for i in range(0,4):
    if (determine_top[i] > determine_bottom[i]): 
        determine_color.append('#B3DE69') #green
    else:
        determine_color.append('firebrick')
    i+=1
data['determine_colors'] = determine_color
    
source = ColumnDataSource(data=data)
    
# Set up plot
plot = bk_figure(plot_height=400, plot_width=400, title="test",
                 tools="crosshair,pan,reset,save,wheel_zoom",
                 x_range=[0, 10], y_range=[-5, 5])
    
    plot.vbar(x='bar_x', width=0.5, top='bar_top',bottom='bar_bottom',
              source=source, color='determine_colors') 

# Set up widgets
select = Select(title="days_select:", 
                options=["d1_select", "d2_select", "d3_select", "d4_select"])

d1 = Slider(title="d1", value=0.0, start=-5.0, end=5.0, step=0.1)
d2 = Slider(title="d2", value=1.0, start=-5.0, end=5.0, step=0.1)
d3 = Slider(title="d3", value=0.0, start=0.0, end=2*np.pi)
d4 = Slider(title="d4", value=1.0, start=0.1, end=5.1, step=0.1)


# Set up callbacks
def update_data(attrname, old, new):
    # Get the current slider values
    d1_value = d1.value
    d2_value = d2.value
    d3_value = d3.value
    d4_value = d4.value

    ##select
    #if select.value == "d2_select":
    #   d3.disabled = True
    #   d4.visible = False
    
    
    # Generate the new curve
    new_data = {
        'line_x' : [1,2,3,4],
        'line_y' : [4,3,2,1],
        'bar_x': [1, 2, 3, 4],
        'bar_bottom':[d1_value, d2_value, d3_value, d4_value],
        'bar_top':[0.2, d1_value, d2_value, d3_value],
    }
    
    #bar_color
    determine_top = new_data['bar_top']
    determine_bottom = new_data['bar_bottom']
    determine_color = []
    for i in range(0,4):
        if (determine_top[i] > determine_bottom[i]): 
            determine_color.append('green') #green
        else:
            determine_color.append('red')
        i+=1
    new_data['determine_colors'] = determine_color

    source.data = new_data
    
for w in [select, d1, d2, d3, d4]:
    w.on_change('value', update_data)

# Set up layouts and add to document
layout = row(widgetbox(select, d1, d2, d3, d4), plot)

def modify_doc(doc):
    doc.add_root(row(layout, width=800))
    doc.title = "Sliders"

handler = FunctionHandler(modify_doc)
app = Application(handler)
show(app)

谢谢你的建议