6

Every example I've seen of using widgets for interactive matplotlib plots in the notebook do something like this (adapted from here):

%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt
from IPython.html.widgets import interact
from IPython.display import display

def sigmoid_demo(a=5,b=1):
    x = np.linspace(0,10,256)
    s = 1/(1+np.exp(-(x-a)/(b+0.1))) # +0.1 to avoid dividing by 0
    sn = 100.0*(s-min(s))/(max(s)-min(s)) # normalize sigmoid to 0-100

    # Does this have to be in this function?
    fig, ax = plt.subplots(figsize=(24,6))

    ax.set_xticks([])
    ax.set_yticks([])
    plt.plot(x,sn,lw=2,color='black')
    plt.xlim(x.min(), x.max())

w=interact(sigmoid_demo,a=5,b=1)

I suspect that the responsiveness of the plot could be sped up hugely if you didn't have to create a brand new figure with plt.subplots() or plt.figure() each time a widget was adjusted.

I've tried a few things to move figure creation outside of the function being called by interact() but nothing has worked.

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Mr. W.
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1 Answers1

6

Some setup:

%matplotlib notebook
import matplotlib.pyplot as plt
from IPython.html.widgets import interactive
from IPython.display import display
import numpy as np

Create your objects:

fig, ax = plt.subplots()
ax.set_xlim(0, .25)
ax.set_ylim(-2.5, 2.5)
ax.set_title('beat frequencies')
lnA, = ax.plot([], [], color='r', label='A')
lnB, = ax.plot([], [], color='purple', label='B')
lnsum, = ax.plot([], [], color='k', label='signal')
ax.legend()
max_time = 3
rate = 8000
times = np.linspace(0,max_time,rate*max_time)

def beat_freq(f1=220.0, f2=224.0):

    A = np.sin(2*np.pi*f1*times)
    B = np.sin(2*np.pi*f2*times)
    sig = A + B

    lnA.set_data(times, A)
    lnB.set_data(times, B)
    lnsum.set_data(times, sig)

    plt.draw()

beat_freq(0, 0)

and the interactive (which I think needs to go in it's own cell)

interactive(beat_freq, f1=(200.0,300.0), f2=(200.0,300.0))

You can also poke at the objects from a different cell:

ax.set_xlim(0, .05)
ax.set_ylim(-2, 2)
plt.draw()

or 

lnB.set_color('g')
ax.legend()
plt.draw()
tacaswell
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