运行任意python代码的散景hovertools

问题描述 投票:1回答:1

我正在使用Bokeh尝试创建一个图形,当用户“悬停”时数据点将在悬停工具中显示另一个图形,显示有关该数据点的其他信息(即,在主图中数据点是平均值在设定的时间间隔内的时间序列,我希望悬停工具显示该时间间隔内的所有数据)。

user guide(下面复制的完整代码)提供了一种解决方案:使用自定义HTML工具提示来引用文件中的图形。但是,这需要我创建文件中的所有数字(可能超过10,000)以供参考。这是一个太大的时间开销,所以我希望有一个更好的解决方案。即:悬浮工具是否可以动态运行python代码,以便它们可以交互显示数据图?

(示例图片,取自用户指南,代码如下)

以下代码于2019年3月19日从bokeh user guide复制而来。

from bokeh.plotting import figure, output_file, show, ColumnDataSource

output_file("toolbar.html")

source = ColumnDataSource(data=dict(
    x=[1, 2, 3, 4, 5],
    y=[2, 5, 8, 2, 7],
    desc=['A', 'b', 'C', 'd', 'E'],
imgs=[
    'https://bokeh.pydata.org/static/snake.jpg',
    'https://bokeh.pydata.org/static/snake2.png',
    'https://bokeh.pydata.org/static/snake3D.png',
    'https://bokeh.pydata.org/static/snake4_TheRevenge.png',
    'https://bokeh.pydata.org/static/snakebite.jpg'
],
fonts=[
    '<i>italics</i>',
    '<pre>pre</pre>',
    '<b>bold</b>',
    '<small>small</small>',
    '<del>del</del>'
]
))

TOOLTIPS = """
<div>
    <div>
        <img
            src="@imgs" height="42" alt="@imgs" width="42"
            style="float: left; margin: 0px 15px 15px 0px;"
            border="2"
        ></img>
    </div>
    <div>
        <span style="font-size: 17px; font-weight: bold;">@desc</span>
        <span style="font-size: 15px; color: #966;">[$index]</span>
    </div>
    <div>
        <span>@fonts{safe}</span>
    </div>
    <div>
        <span style="font-size: 15px;">Location</span>
        <span style="font-size: 10px; color: #696;">($x, $y)</span>
    </div>
</div>
"""

p = figure(plot_width=400, plot_height=400, tooltips=TOOLTIPS,
       title="Mouse over the dots")

p.circle('x', 'y', size=20, source=source)

show(p)

example_hover_tool

python bokeh
1个回答
2
投票

您只能在Bokeh服务器应用程序中使用Python回调。似乎不可能对HoverTool使用Python回调(它必须始终是JS回调,否则会出现此错误:ValueError: expected an instance of type Callback, got <function callback at 0x114fdbb90> of type function)。

以下解决方案使用JS回调,当在主图上悬停圆圈时显示一个小的“工具提示图”(适用于Bokeh v1.0.4,并且仅当Bokeh文档中有2个图时):

from bokeh.plotting import figure, show
from bokeh.layouts import gridplot, Row
from bokeh.models import ColumnDataSource, CDSView, BooleanFilter, CustomJS, BoxSelectTool, HoverTool
import pandas as pd

data = {'x': [1, 2, 3],
        'y':[1, 2, 3],
        'xs':[[9, 8, 7], [6, 5, 4], [3, 2, 1]],
        'ys':[[29, 28, 29], [27, 28, 27], [25, 25, 20]]}
source = ColumnDataSource(data)
plot = figure(title = 'PLOT IN HOVER TOOLTIP', tools = '')
circles = plot.circle('x', 'y', size = 20, source = source)

plot_tooltip = figure(name = 'plot_tooltip', plot_width = 200, plot_height = 200, x_axis_location = None, y_axis_location = None, title = None, tools = 'hover', tooltips = [("x", "@x"), ("y", "@y")], toolbar_location = None)
lines = plot_tooltip.line('x', 'y', source = ColumnDataSource({'x': [], 'y': []}))
circles2 = plot_tooltip.circle('x', 'y', source = ColumnDataSource({'x': [], 'y': []}))

code = """  
var indices = cb_data.index['1d'].indices;
if (indices.length > 0){
    if(plot_tooltip.x_range.bounds == null)
    {
        Bokeh.documents[0].add_root(plot_tooltip)
    }
    const idx = indices[0]
    lines.data_source.data['x'] = source.data['xs'][idx]
    lines.data_source.data['y'] = source.data['ys'][idx]
    lines.data_source.change.emit();

    circles.data_source.data['x'] = source.data['xs'][idx]
    circles.data_source.data['y'] = source.data['ys'][idx]
    circles.data_source.change.emit();  

    div = document.getElementsByClassName('bk-root')[1];
    div.style = "position:absolute; left:" + cb_data.geometry['sx'] + "px; top:" + cb_data.geometry['sy'] + "px;";              
} """

callback = CustomJS(args = dict(source = source, lines = lines, circles = circles2, plot_tooltip = plot_tooltip), code = code)

hover = HoverTool()
hover.callback = callback
hover.tooltips = None
hover.renderers = [circles]
plot.add_tools(hover)

show(plot)

结果:

enter image description here

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