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I"m having a hard time wrapping my brain around PEP 380.
- What are the situations where "yield from" is useful?
- What is the classic use case?
- Why is it compared to micro-threads?
[ update ]
Now I understand the cause of my difficulties. I"ve used generators, but never really used coroutines (introduced by PEP-342). Despite some similarities, generators and coroutines are basically two different concepts. Understanding coroutines (not only generators) is the key to understanding the new syntax.
IMHO coroutines are the most obscure Python feature, most books make it look useless and uninteresting.
Thanks for the great answers, but special thanks to agf and his comment linking to David Beazley presentations. David rocks.
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In practice, what are the main uses for the new "yield from" syntax in Python 3.3? around: Questions
Removing white space around a saved image in matplotlib
2 answers
I need to take an image and save it after some process. The figure looks fine when I display it, but after saving the figure, I got some white space around the saved image. I have tried the "tight" option for savefig method, did not work either. The code:
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
fig = plt.figure(1)
img = mpimg.imread(path)
plt.imshow(img)
ax=fig.add_subplot(1,1,1)
extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig("1.png", bbox_inches=extent)
plt.axis("off")
plt.show()
I am trying to draw a basic graph by using NetworkX on a figure and save it. I realized that without a graph it works, but when added a graph I get white space around the saved image;
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import networkx as nx
G = nx.Graph()
G.add_node(1)
G.add_node(2)
G.add_node(3)
G.add_edge(1,3)
G.add_edge(1,2)
pos = {1:[100,120], 2:[200,300], 3:[50,75]}
fig = plt.figure(1)
img = mpimg.imread("image.jpg")
plt.imshow(img)
ax=fig.add_subplot(1,1,1)
nx.draw(G, pos=pos)
extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig("1.png", bbox_inches = extent)
plt.axis("off")
plt.show()
Answer #1
You can remove the white space padding by setting bbox_inches="tight" in savefig:
plt.savefig("test.png",bbox_inches="tight")
You"ll have to put the argument to bbox_inches as a string, perhaps this is why it didn"t work earlier for you.
Possible duplicates:
Matplotlib plots: removing axis, legends and white spaces
Answer #2
I cannot claim I know exactly why or how my “solution” works, but this is what I had to do when I wanted to plot the outline of a couple of aerofoil sections — without white margins — to a PDF file. (Note that I used matplotlib inside an IPython notebook, with the -pylab flag.)
plt.gca().set_axis_off()
plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0,
hspace = 0, wspace = 0)
plt.margins(0,0)
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.savefig("filename.pdf", bbox_inches = "tight",
pad_inches = 0)
I have tried to deactivate different parts of this, but this always lead to a white margin somewhere. You may even have modify this to keep fat lines near the limits of the figure from being shaved by the lack of margins.
