I'm trying to animate a Path using the periodic
function on DynamicMap
but my Jupyter Notebook starts complaining with the following error message:
IOPub message rate exceeded.
The notebook server will temporarily stop sending output
to the client in order to avoid crashing it.
To change this limit, set the config variable
`--NotebookApp.iopub_msg_rate_limit`.
Current values:
NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)
NotebookApp.rate_limit_window=3.0 (secs)
This is my code:
def paths3():
N = 50
x = np.linspace(0,10,N)
y = (2 * x + 3)
f = 0.0
g = 0.5
while True:
i = np.clip(int((N-1)*f),0,N-1)
j = np.clip(int((N-1)*(f-g)),0,N-1)
if j < 0:
j = 0
alpha_max = 1 if f <= 1 else ((1.0-(f-g))*N) / N
alpha = np.concatenate((np.zeros(j),np.linspace(0.1,alpha_max,(i-j+1)),np.zeros(N-(i+1))))
data = pd.DataFrame({'x':x,'y':y,'alpha':alpha})
yield hv.Path(data, vdims='alpha').opts(alpha='alpha')
if f > 2:
f = 0
else:
f += 0.01
paths3 = paths3()
dmap = hv.DynamicMap(paths3, streams=[Stream.define('Next')()])
dmap
dmap.periodic(0.1, 100)
I see that people have had similar issue, but that was back in 2017-ish with an older version of Jupyter Notebook.
This is the 'About' section in my Jupyter Notebook:
Server Information:
You are using Jupyter notebook.
The version of the notebook server is: 6.0.1
The server is running on this version of Python:
Python 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019, 14:00:49) [MSC v.1915 64 bit (AMD64)]
Current Kernel Information:
Python 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019, 14:00:49) [MSC v.1915 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.
IPython 5.8.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
Does it help (when starting jupyter notebook) to set the message rate higher to 10,000 or 100,000, like so:
jupyter notebook --NotebookApp.iopub_msg_rate_limit=10000
This SO question refers to a similar problem:
IOPub data rate exceeded in Jupyter notebook (when viewing image)