While utilizing an IPython notebook with:
ipython notebook --pylab
If I am executing a CPU intensive code, the previous matplotlib figures become unresponsive. Is there a method to run matplotlib on a separate thread? I have experimented with the ion() command but nothing appears to resolve the issue.
I understand this might be considered basic, but I haven't come across a straightforward command to achieve this!
When working with IPython notebooks, I prefer not to utilize pylab for plotting due to the fact that it can "populate the interactive namespace from numpy and matplotlib," potentially causing issues such as overwriting Python functions like sum with NumPy equivalents. A more effective approach, in my opinion, is to use the
%matplotlib inline
magic function and then import pyplot and numpy separately to clearly define which functions you are using.
import numpy as np
from matplotlib import pyplot as plt
By following this method, you can explicitly call functions such as NumPy's sum using
np.sum(my_numpy_array) and sum(my_python_list) (especially useful for performance optimization when dealing with large arrays or lists).
For plotting purposes, you can then proceed with
plt.plot(my_data)
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