Interactive matplotlib using ipywidgets

Question

I want to implement an interactive plot using Matplotlib and ipywidgets in IPython (python3). So, how I can do this efficiently (change smoothly without delay)?

And another question is why this code works?!

from ipywidgets import *
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

x = np.linspace(0, 2 * np.pi)

def update(w = 1.0):
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.plot(x, np.sin(w * x))

    fig.canvas.draw()

interact(update);

But, this doesn't work?!

from ipywidgets import *
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

x = np.linspace(0, 2 * np.pi)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
line, = ax.plot(x, np.sin(x))

def update(w = 1.0):
    line.set_ydata(np.sin(w * x))
    fig.canvas.draw()

interact(update);

Did you ever find a way to get the second example to work? I have the same problem right now. — mdornfe1
– mdornfe1, Commented Apr 20, 2017 at 23:06

Quant · Accepted Answer · 2017-01-23 03:41:54Z

8

The second approach is the right one for the notebook backend

%matplotlib notebook

Or with ipympl.

However, it won't work with the inline backend which does not update the plot.

answered Jan 23, 2017 at 3:41

Quant

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3 Comments

tfv Over a year ago

For me, the second approach does not work for the notebook backend. No graph is shown at all.

Quant Over a year ago

I recommend using ipympl (aka jupyter-matplotlib), which is the notebook backend split into a separate package. The reason for the split is that release cycles of Jupyter are much faster than matplotlib. ipympl is separated from matplotlib to be able to track this better.

jmborr Over a year ago

Also, fig.show() is necessary in order to show the canvas.

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