With Bokeh, how do I get a handle to the Renderer
(or GlyphRenderer
) for an Annotation
? Is this possible?
I would like to be able to toggle a Band
(which is an Annotation
) on and off with an interactive legend, so I need to be able to pass a list of Renderers
to the LegendItem
constructor.
This code:
maxline = fig.line(x='Date', y=stn_max, line_width=0.5, legend=stn_max, name="{}_line".format(stn_max), color=stn_color, alpha=0.75, source=source)
minline = fig.line(x='Date', y=stn_min, line_width=0.5, legend=stn_min, name="{}_line".format(stn_min), color=stn_color, alpha=0.75, source=source)
band = bkm.Band(base='Date', lower=stn_min, upper=stn_max, fill_alpha=0.50, line_width=0.5, fill_color=stn_color, source=source)
bkm.LegendItem(label=stn, renderers=[maxline, minline, band])
Produces this error
...
ValueError: expected an element of List(Instance(GlyphRenderer)), got seq with invalid items [Band(id='1091', ...)]
For LegendItem
only instances of GlyphRenderer
can be passed to its renderers
attribute and Band
is not based on GlyphRenderer
so it gives error. In the code below the Band visibility is being toggled by means of a callback:
from bokeh.plotting import figure, show
from bokeh.models import Band, ColumnDataSource, Legend, LegendItem, CustomJS
import pandas as pd
import numpy as np
x = np.random.random(2500) * 140 - 20
y = np.random.normal(size = 2500) * 2 + 5
df = pd.DataFrame(data = dict(x = x, y = y)).sort_values(by = "x")
sem = lambda x: x.std() / np.sqrt(x.size)
df2 = df.y.rolling(window = 100).agg({"y_mean": np.mean, "y_std": np.std, "y_sem": sem})
df2 = df2.fillna(method = 'bfill')
df = pd.concat([df, df2], axis = 1)
df['lower'] = df.y_mean - df.y_std
df['upper'] = df.y_mean + df.y_std
source = ColumnDataSource(df.reset_index())
p = figure(tools = "pan,wheel_zoom,box_zoom,reset,save")
scatter = p.scatter(x = 'x', y = 'y', line_color = None, fill_alpha = 0.3, size = 5, source = source)
band = Band(base = 'x', lower = 'lower', upper = 'upper', source = source)
p.add_layout(band)
p.title.text = "Rolling Standard Deviation"
p.xaxis.axis_label = 'X'
p.yaxis.axis_label = 'Y'
callback = CustomJS(args = dict(band = band), code = """
if (band.visible == false)
band.visible = true;
else
band.visible = false; """)
legend = Legend(items = [ LegendItem(label = "x", renderers = [scatter, band.source.selection_policy]) ])
legend.click_policy = 'hide'
scatter.js_on_change('visible', callback)
p.add_layout(legend)
show(p)
Result: