获取Bokeh中框选择工具中包含的选定数据

如果我在散景中有一个散点图并且我启用了Box Select Tool,假设我使用Box Select Tool选择了几个点.如何访问我选择的点的(x,y)位置信息？

%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?

我不能调用"callback"属性,而"dimensions"属性只返回一个列表["width","height"].如果我可以获得选定框的尺寸和位置,我可以从那里找出我的数据集中的哪些点.

您可以使用callback上ColumnDataSource,更新与所选择的数据的索引的Python变量:

%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式访问所需的数据属性

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