Bokeh filter CDSView according to Datetime in RangeTool

Question

I'm trying to filter the data of a scatterplot (p1) according to a date range controlled by a rangetool in another plot.

This would be a variation of what already showed here: https://docs.bokeh.org/en/latest/docs/gallery/range_tool.html

here a MWE (not really working for p1):

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

I would like to use "RangeTool(x_range=p.x_range)" to control a filter for the source of p1. Any help will be really appreciated

Answer 1

Here is an example:

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))