Is there a way to detach matplotlib plots so that the computation can continue?

Question

Use matplotlib's calls that won't block:

Using draw():

from matplotlib.pyplot import plot, draw, show
plot([1,2,3])
draw()
print('continue computation')

# at the end call show to ensure window won't close.
show()

Using interactive mode:

from matplotlib.pyplot import plot, ion, show
ion() # enables interactive mode
plot([1,2,3]) # result shows immediatelly (implicit draw())

print('continue computation')

# at the end call show to ensure window won't close.
show()

Use the keyword 'block' to override the blocking behavior, e.g.

from matplotlib.pyplot import show, plot

plot(1)  
show(block=False)

# your code

to continue your code.

It is better to always check with the library you are using if it supports usage in a non-blocking way.

But if you want a more generic solution, or if there is no other way, you can run anything that blocks in a separated process by using the multprocessing module included in python. Computation will continue:

from multiprocessing import Process
from matplotlib.pyplot import plot, show

def plot_graph(*args):
    for data in args:
        plot(data)
    show()

p = Process(target=plot_graph, args=([1, 2, 3],))
p.start()

print 'yay'
print 'computation continues...'
print 'that rocks.'

print 'Now lets wait for the graph be closed to continue...:'
p.join()

That has the overhead of launching a new process, and is sometimes harder to debug on complex scenarios, so I'd prefer the other solution (using matplotlib's nonblocking API calls)

Try

import matplotlib.pyplot as plt
plt.plot([1,2,3])
plt.show(block=False)
# other code
# [...]

# Put
plt.show()
# at the very end of your script to make sure Python doesn't bail out
# before you finished examining.

The show() documentation says:

In non-interactive mode, display all figures and block until the figures have been closed; in interactive mode it has no effect unless figures were created prior to a change from non-interactive to interactive mode (not recommended). In that case it displays the figures but does not block.

A single experimental keyword argument, block, may be set to True or False to override the blocking behavior described above.

IMPORTANT: Just to make something clear. I assume that the commands are inside a .py script and the script is called using e.g. python script.py from the console.

A simple way that works for me is:

1. Use the block = False inside show : plt.show(block = False)
2. Use another show() at the end of the .py script.

---

Example of script.py file:

plt.imshow(*something*)                                                               
plt.colorbar()                                                                             
plt.xlabel("true ")                                                                   
plt.ylabel("predicted ")                                                              
plt.title(" the matrix")  

# Add block = False                                           
plt.show(block = False)

################################
# OTHER CALCULATIONS AND CODE HERE ! ! !
################################

# the next command is the last line of my script
plt.show()

---

You may want to read this document in matplotlib's documentation, titled:

Using matplotlib in a python shell