CODEWITHSUNDEEP
pythonmatplotlibjupyter-notebookjupyter
FLab
FLab

Reputation: 7476

Jupyter Notebook: interactive plot with widgets

I am trying to generate an interactive plot that depends on widgets. The problem I have is that when I change parameters using the slider, a new plot is done after the previous one, instead I would expect only one plot changing according to the parameters.

Example:

from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets

import matplotlib.pyplot as plt
%matplotlib inline

import numpy as np

def plot_func(freq):
    x = np.linspace(0, 2*np.pi)
    y = np.sin(x * freq)
    plt.plot(x, y)

interact(plot_func, freq = widgets.FloatSlider(value=7.5,
                                               min=1,
                                               max=5.0,
                                               step=0.5))

After moving the slider to 4.0, I have:

enter image description here

while I just want one figure to change as I move the slider. How can I achieve this?

(I am using Python 2.7, matplotlib 2.0 and I have just updated notebook and jupyter to the latest version. let me know if further info is needed.)

Upvotes: 67

Views: 178273

Answers (3)

Luis Jose
Luis Jose

Reputation: 754

For completion, here is an answer that makes use of more than one slider bar and sets the default parameters as well as the interval lengths.

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

x = np.linspace(-10, 10,100)

def f(x, A, B, C):
    return A*x**2 + B*x + C

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
line, = ax.plot(x, f(x, A=1, B=1, C=1))

def update(A = 1, B = 0, C = 0):
    line.set_ydata(f(x,A,B,C))
    fig.canvas.draw_idle()
    
interact(update, A = (-4,4,0.1), B = (-4,4,0.1), C = (-4,4,0.1));

enter image description here

Upvotes: 6

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339170

As you want to change the figure, instead of creating a new one, may I suggest the following way:

  1. Use an interactive backend; %matplotlib notebook
  2. Update the line in the plot, instead of drawing new ones.

So the code could look something like this:

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

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_idle()

interact(update);

enter image description here

Alternatively you may use plt.show() as in this answer.

Upvotes: 74

Stelios
Stelios

Reputation: 5521

This is an issue (?) introduced in the last version of jupyter and/or ipywidgets. One workaround I found was to add the line plt.show() at the end of plot_func.

Upvotes: 3

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