根据 RangeTool 中的日期时间散景过滤 CDSView

Question

我正在尝试根据另一个图中范围工具控制的日期范围过滤散点图 (p1) 的数据。

这将是此处已显示内容的变体：https://docs.bokeh.org/en/latest/docs/gallery/range_tool.html

这里是 MWE（不是真正为 p1 工作）：

import numpy as np

from bokeh.io import show
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, RangeTool
from bokeh.plotting import figure
from bokeh.sampledata.stocks import AAPL



dates = np.array(AAPL['date'], dtype=np.datetime64)


source = ColumnDataSource(data=dict(date=dates, close=AAPL['adj_close'], volume=AAPL['volume']))


####################### p


p = figure(plot_height=300, plot_width=800, tools="xpan", toolbar_location=None,
           x_axis_type="datetime", x_axis_location="above",
           background_fill_color="#efefef", x_range=(dates[1500], dates[2500]))

p.line('date', 'close', source=source)



p.yaxis.axis_label = 'Price'


################ p1

p1 = figure(plot_height=300, plot_width=800, tools="xpan", toolbar_location=None,
           background_fill_color="#efefef")

p1.circle (x='close', y='volume', source=source)



##################### select (rangeslider)

select = figure(title="Drag the middle and edges of the selection box to change the range above",
                plot_height=130, plot_width=800, y_range=p.y_range,
                x_axis_type="datetime", y_axis_type=None,
                tools="", toolbar_location=None, background_fill_color="#efefef")

range_tool = RangeTool(x_range=p.x_range)
range_tool.overlay.fill_color = "navy"
range_tool.overlay.fill_alpha = 0.2

select.line('date', 'close', source=source)
select.ygrid.grid_line_color = None
select.add_tools(range_tool)
select.toolbar.active_multi = range_tool


#####################


show(column(p,p1, select))

plot result

我想使用“RangeTool(x_range=p.x_range)”来控制 p1 源的过滤器。任何帮助将不胜感激

Answer 1

这是一个例子：

import numpy as np

from bokeh.layouts import column
from bokeh.models import ColumnDataSource, RangeTool, CustomJS, CDSView, CustomJSFilter
from bokeh.plotting import figure, show
from bokeh.sampledata.stocks import AAPL

dates = np.array(AAPL['date'], dtype=np.datetime64)
source = ColumnDataSource(data=dict(date=dates, close=AAPL['adj_close'], volume=AAPL['volume']))

p = figure(plot_height=300, x_axis_type="datetime", x_range=(dates[1500], dates[2500]))

p.line('date', 'close', source=source)

range_tool = RangeTool(x_range=p.x_range)

p.x_range.callback = CustomJS(args=dict(source=source), code="source.change.emit();")

date_filter = CustomJSFilter(args=dict(source=source, x_range=p.x_range), code="""
let start=x_range.start;
let end=x_range.end;
let dates = source.data['date'];
let indices = [];
for (var i = 0; i <= dates.length; i++){
    if (dates[i] >= start && dates[i] <= end) indices.push(i);
}
return indices;
""")

view = CDSView(source=source, filters=[date_filter])

p1 = figure(plot_height=300)
p1.circle (x='close', y='volume', source=source, view=view)

select = figure(plot_height=130, x_axis_type="datetime")

select.line('date', 'close', source=source)
select.add_tools(range_tool)

show(column(p, p1, select))