updated graphs through iteration, matplotlib

Question

I'm trying to graph features of a data-set one by one by, via iteration. So I want the graph to continuously update as I proceed through the loop.

I refered to this thread,real-time plotting in while loop with matplotlib but the answers are all over the place, and despite incorporating some of their suggestions as shown below, I still can't seem to get the code working. I'm using Jupyter Notebook.

import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
colors = ["darkblue", "darkgreen"]

f, (ax1, ax2) = plt.subplots(1, 2, sharey=True, sharex = True)


for i in range(X.shape[-1]-1):
    idx = np.where(y == 1)[0]
    ax1.scatter(X[idx, i], X[idx, i+1], color=colors[0], label=1)


    idx = np.where(y == 0)[0]
    ax2.scatter(X[idx, i], X[idx, i+1], color=colors[1], label=0)

    plt.draw()
    plt.pause(0.0001)

Any suggestions?

Thank you.

mforpe · Accepted Answer · 2017-04-23 17:03:09Z

2

This is an example for real-time plotting in a Jupyter Notebook

%matplotlib inline
%load_ext autoreload  #Reload all modules every time before executing the Python code typed.
%autoreload 2 
%matplotlib notebook

import matplotlib.pyplot as plt
import numpy as np
import time

colors = ["darkblue", "darkgreen"]

# initialise the graph and settings

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = fig.add_subplot(211)
plt.ion() # interactive mode
fig.show()
fig.canvas.draw() # matplotlib canvas drawing

# plotting loop

for i in range(X.shape[-1]-1):
  ax1.clear()
  ax2.clear()

  idx = np.where(y == 1)[0]
  ax1.scatter(X[idx, i], X[idx, i+1], color=colors[0], label=1)

  idx = np.where(y == 0)[0]
  ax2.scatter(X[idx, i], X[idx, i+1], color=colors[1], label=0)

  fig.canvas.draw() # draw
  time.sleep(0.5)   # sleep

answered Apr 23, 2017 at 17:03

mforpe

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4 Comments

Moondra Over a year ago

Thank you, going to test it out once I have a chance. =)

ImportanceOfBeingErnest Over a year ago

@ManelFornos Did you test that? I think this should not work and only show the final figure after the animation has finished.

Moondra Over a year ago

It seems to be working. I'm testing it right now. I will examine it some more. Thank you.

Moondra Over a year ago

I can't seem to figure out how to share the axes with your new code. I was tryingto revert back to my old code with subplots but it was producing an error.

ImportanceOfBeingErnest · Accepted Answer · 2017-10-22 17:57:06Z

For an animation you need an interactive backend. %matplotlib inline is no interactive backend (it essentially shows a printed version of the figure).

You may decide not to run you code in jupyter but as a script. In this case you would need to put plt.ion() to put interactive mode on.

Another option would be to use a FuncAnimation, as e.g in this example. To run such a FuncAnimation in Jupyter you will still need some interactive backend, either %matplotlib tk or %matplotlib notebook.

From matplotlib 2.1 on, we can also create an animation using JavaScript.

from IPython.display import HTML
HTML(ani.to_jshtml())

Some complete example:

import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np

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

fig, ax = plt.subplots()
ax.axis([0,2*np.pi,-1,1])
l, = ax.plot([],[])

def animate(i):
    l.set_data(t[:i], x[:i])

ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))

from IPython.display import HTML
HTML(ani.to_jshtml())

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