Interactive and clickable plots using Panel, Holoviz and Bokeh in Jupyter Notebooks

interactive_audio_plots.py

import numpy as np
import panel as pn
pn.extension()
import holoviews as hv 
hv.notebook_extension("bokeh")
# hv.extension('matplotlib')
from holoviews.streams import Stream, Params
from scipy.io import wavfile
from scipy.signal import spectrogram

rate, data = wavfile.read('/filepath.wav')
width = 1000
audio = pn.pane.Audio(data, sample_rate=rate, name='Audio', throttle=500)
time = np.linspace(0, len(data) / rate, num=len(data))
line_plot = hv.Curve((time, data), ["time (s)","amplitude"]).opts(width=width)
f, t, sxx = spectrogram(data, rate)
spec_gram = hv.Image((t, f, np.log10(sxx)), ["time (s)","frequency (hz)"]).opts(width=width)

def interactive_play(x,y,t):
    if x is None:
        return hv.VLine(t).opts(color='green')
    else:
        audio.time = x
        return hv.VLine(x).opts(color='green')

stream = Params(parameters=[audio.param.time], rename={'time': 't'})
tap = hv.streams.SingleTap(transient=True)
dmap_time = hv.DynamicMap(interactive_play, streams=[stream, tap])

pn.Column( audio, (spec_gram * dmap_time), (line_plot * dmap_time))