Bokeh使用选择或滑块更新地图工具提示

Question

我正在尝试使用切片器或下拉选择更新世界地图工具提示。我得到了以下问题，该问题对Bokeh Slider自定义JS回调的大部分内容进行了排序

import pandas as pd
import random
from datetime import timedelta
df = pd.DataFrame({'base' : ["2017-01-01" for t in range(10000)],
'Date' : [random.randint(0, 1035) for t in range(10000)], 
'Sales' : [random.random() for t in range(10000)]})
df['base'] = pd.to_datetime(df['base'])
df["Date2"] = df.apply(lambda x: x["base"] + timedelta(days=x['Date']), axis=1)
df.drop(['base', 'Date'], axis=1, inplace=True)
df.set_index('Date2', inplace=True)
df['month'] = df.index.month
df['year'] = df.index.year
df['day'] = df.index.day
df.head()
from bokeh.models.widgets import Slider,Select
from bokeh.io import output_notebook, show, output_file
from bokeh.layouts import widgetbox, column
from bokeh.models import Slider, ColumnDataSource, CustomJS
from bokeh.plotting import figure, curdoc
from bokeh.core.properties import value
from bokeh.models.ranges import FactorRange
from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh.models import ColumnDataSource, CDSView, IndexFilter, BooleanFilter, HoverTool

source1=df.groupby(['year','month','day'], as_index = False).sum()
source = source1[source1['year']== 2017]
sourcex = source[source['month'] ==1]
Overall=ColumnDataSource(source)
Curr=ColumnDataSource(sourcex)
boolinit = source['month']==1
view = CDSView(source=Overall, filters=[BooleanFilter(boolinit)])
hover3 = HoverTool(tooltips = [('day', '@day'),('Sales','@{Sales}{0,0}')],
formatters = {'day': 'datetime','Sales': 'numeral'})
p =  figure(title='YEARLY SALES',  plot_width=600, plot_height=400, min_border=3,
tools = [hover3,'box_zoom','wheel_zoom', 'pan','reset'],  
toolbar_location="above")
r = p.vbar(x='day', top='Sales', width=0.2, color='#e8bc76', source=Curr)
p.xaxis.axis_label = 'Day'
p.xaxis.axis_label_text_font_style = 'normal'
p.xaxis.axis_label_text_font_size = '12pt'

callback = CustomJS(args=dict(source=Overall, sc=Curr), code="""       
var f = select.value;
sc.data['day'] = [];
sc.data['Sales'] = [];
for (var i = 0; i <= source.get_length(); i++){
if (source.data['month'][i] == f){
sc.data['day'].push(source.data['day'][i])
sc.data['Sales'].push(source.data['Sales'][i])
}
}
sc.change.emit();
""")
select = Select(options=["1","2","3"], title="Month", callback=callback)
callback.args["select"] = select
layout = column(select, p)
#Display plot inline in Jupyter notebook
output_notebook()
output_file("Filterdata.html")
show(layout)

现在，我为世界地图复制了同样的内容，如下所示：

import pandas as pd
import geopandas as gpd
current_week = 4
shapefile = 'data/countries_110m/ne_110m_admin_0_countries.shp'
gdf = gpd.read_file(shapefile)[['ADMIN', 'ADM0_A3', 'geometry']]
gdf.columns = ['country', 'country_code', 'geometry']
gdf = gdf.drop(gdf.index[159])
df = pd.DataFrame({'Country':['India','India'],
'SalesGain':['10%','20%'],
'Week':[4,5],
'Color':[0.2,0.4]
})
import json
from bokeh.models.widgets import Slider,Select
from bokeh.io import output_notebook, show, output_file
from bokeh.layouts import widgetbox, column
from bokeh.models import Slider, ColumnDataSource, CustomJS
from bokeh.plotting import figure, curdoc
from bokeh.core.properties import value
from bokeh.models.ranges import FactorRange
from bokeh.palettes import brewer
from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh.models import ColumnDataSource, CDSView, IndexFilter, BooleanFilter, HoverTool,GeoJSONDataSource, LinearColorMapper, ColorBar
from bokeh.plotting import figure, output_file, show
output_file("worldmap.html")

merged = gdf.merge(df, left_on = 'country', right_on = 'Country', how = 'left')
merged_json = json.loads(merged.to_json())
json_data = json.dumps(merged_json)
geosource_all = GeoJSONDataSource(geojson =  json_data)
df_curr = df[df['Week']==current_week]
merged_curr = gdf.merge(df_curr, left_on = 'country', right_on = 'Country', how = 'left')
merged_json_curr = json.loads(merged_curr.to_json())
json_data_curr = json.dumps(merged_json_curr)
geosource_curr = GeoJSONDataSource(geojson =  json_data_curr)

# boolinit = merged['Week']!=current_week
boolinit = merged['Week']==current_week
view = CDSView(source=geosource_all, filters=[BooleanFilter(boolinit)])
hover3 = HoverTool(tooltips = [('Country', '@Country'),('Sales','@SalesGain')])
#Define a sequential multi-hue color palette.
palette = brewer['YlGnBu'][8]
#Reverse color order so that dark blue is highest value
palette = palette[::-1]
#Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors. Input nan_color.
color_mapper = LinearColorMapper(palette = palette, low = 0, high = 12, nan_color = '#d9d9d9')
#Define custom tick labels for color bar.
tick_labels = {'0': '0', '2':'2%',  '4':'4%',  '6':'6%', '8':'8%','10':'10%','12':'12%'}
#Create color bar. 
color_bar = ColorBar(color_mapper=color_mapper, label_standoff=6,width = 500, height = 20,
border_line_color=None,location = (0,0), orientation = 'horizontal', major_label_overrides = tick_labels)

#Create figure object.
p =  figure(title='Covid-19 Impact',  plot_width=900, plot_height=600, min_border=3,
tools = [hover3,'box_zoom','wheel_zoom', 'pan','reset'],toolbar_location="above")
p.title.text_font_size = '20pt'
p.title.text_color = "darkblue"
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None

#Add patch renderer to figure. 
p.patches('xs','ys', source = geosource_curr,fill_color = {'field' :'Color', 'transform' : color_mapper},
line_color = 'black', line_width = 0.25, fill_alpha = 1)
p.add_layout(color_bar, 'below')

callback = CustomJS(args=dict(source=geosource_all, sc=geosource_curr), code="""       
var f = slider.value;
sc.data['Country'] = [];
sc.data['Week'] = [];
sc.data['SalesGain'] = [];
for (var i = 0; i <= source.get_length(); i++){
if ((source.data['Week'][i] == f ) || (source.data['Country'][i] == null) ){
sc.data['SalesGain'].push(source.data['SalesGain'][i])
sc.data['Week'].push(source.data['Week'][i])
sc.data['Country'].push(source.data['Country'][i])
}
}
sc.change.emit();
""")
# select = Select(options=["201951","201952","201953"], title="Week", callback=callback)
# callback.args["select"] = select
# layout = column(select, p)
slider = Slider(start=1, end=5, value=current_week, step=1, title="Month", callback=callback)
callback.args["slider"] = slider
layout = column(slider, p)
#Display plot inline in Jupyter notebook
output_notebook()
show(layout)

但在这种情况下，只要我单击滑块，工具提示数据就会消失。世界地图输入文件可以在这里找到，以顺利运行代码：https://github.com/CrazyDaffodils/Interactive-Choropleth-Map-Using-Python/tree/master/bokeh-app/data

Answer 1

将鼠标从触发它的字形上移开后，工具提示会在一小段延迟后消失。

现在，Bokeh没有任何内在的方式来改变这种行为。这方面存在一个悬而未决的问题，即您可能能够适应自己的需求的变通方法：https://github.com/bokeh/bokeh/issues/5724