获取散景框选择工具中包含的选定数据 [英] Get selected data contained within box select tool in Bokeh

问题描述

如果我在bokeh中有一个散点图，并且启用了Box Select Tool，则假设我使用Box Select Tool选择了一些点.如何访问所选点的(x，y)位置信息?

If I have a scatter plot in bokeh and I've enabled the Box Select Tool, suppose I select a few points with the Box Select Tool. How can I access the (x,y) position location information of the points that I've selected?

%matplotlib inline
import numpy as np
from random import choice
from string import ascii_lowercase

from bokeh.models.tools import *
from bokeh.plotting import *

output_notebook()


TOOLS="pan,wheel_zoom,reset,hover,poly_select,box_select"
p = figure(title = "My chart", tools=TOOLS)
p.xaxis.axis_label = 'X'
p.yaxis.axis_label = 'Y'

source = ColumnDataSource(
    data=dict(
        xvals=list(range(0, 10)),
        yvals=list(np.random.normal(0, 1, 10)),
        letters = [choice(ascii_lowercase) for _ in range(10)]
    )
)
p.scatter("xvals", "yvals",source=source,fill_alpha=0.2, size=5)

select_tool = p.select(dict(type=BoxSelectTool))[0]

show(p)

# How can I know which points are contained in the Box Select Tool?

我无法调用"callback"属性，而"dimensions"属性仅返回一个列表["width"，"height"].如果我只能获取选定框"的尺寸和位置，则可以从中找出数据集中的点.

I can't call the "callback" attribute and the "dimensions" attribute just returns a list ["width", "height"]. If I can just get the dimensions and the location of the Selected Box, I can figure out which points are in my dataset from there.

推荐答案

您可以在ColumnDataSource上使用callback，以使用所选数据的索引更新Python变量:

You can use a callback on the ColumnDataSource that updates a Python variable with the indices of the selected data:

%matplotlib inline
import numpy as np
from random import choice
from string import ascii_lowercase

from bokeh.models.tools import *
from bokeh.plotting import *
from bokeh.models import CustomJS



output_notebook()


TOOLS="pan,wheel_zoom,reset,hover,poly_select,box_select"
p = figure(title = "My chart", tools=TOOLS)
p.xaxis.axis_label = 'X'
p.yaxis.axis_label = 'Y'

source = ColumnDataSource(
    data=dict(
        xvals=list(range(0, 10)),
        yvals=list(np.random.normal(0, 1, 10)),
        letters = [choice(ascii_lowercase) for _ in range(10)]
    )
)
p.scatter("xvals", "yvals",source=source,fill_alpha=0.2, size=5)

select_tool = p.select(dict(type=BoxSelectTool))[0]

source.callback = CustomJS(args=dict(p=p), code="""
        var inds = cb_obj.get('selected')['1d'].indices;
        var d1 = cb_obj.get('data');
        console.log(d1)
        var kernel = IPython.notebook.kernel;
        IPython.notebook.kernel.execute("inds = " + inds);
        """
)

show(p)

然后，您可以使用类似的方法访问所需的数据属性

Then you can access the desired data attributes using something like

zip([source.data['xvals'][i] for i in inds],
    [source.data['yvals'][i] for i in inds])

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