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我正在尝试使用periodicon 函数为路径设置动画，DynamicMap但我的 Jupyter Notebook 开始抱怨以下错误消息：

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)

这是我的代码：

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)

我看到人们也遇到过类似的问题，但那是在 2017 年的旧版 Jupyter Notebook 上。

这是我的 Jupyter Notebook 中的“关于”部分：

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.
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1 回答 1

0

将消息速率设置为 10,000 或 100,000 是否有帮助（启动 jupyter notebook 时），如下所示：

jupyter notebook --NotebookApp.iopub_msg_rate_limit=10000

这个 SO 问题指的是类似的问题：
IOPub data rate exceeded in Jupyter notebook (when 查看 image)

于 2019-11-06T12:41:02.557 回答