I am trying to save plots I make using matplotlib; however, the images are saving blank.
Here is my code:
plt.subplot(121)
plt.imshow(dataStack, cmap=mpl.cm.bone)
plt.subplot(122)
y = copy.deepcopy(tumorStack)
y = np.ma.masked_where(y == 0, y)
plt.imshow(dataStack, cmap=mpl.cm.bone)
plt.imshow(y, cmap=mpl.cm.jet_r, interpolation='nearest')
if T0 is not None:
plt.subplot(123)
plt.imshow(T0, cmap=mpl.cm.bone)
#plt.subplot(124)
#Autozoom
#else:
#plt.subplot(124)
#Autozoom
plt.show()
plt.draw()
plt.savefig('tessstttyyy.png', dpi=100)
And tessstttyyy.png is blank (also tried with .jpg)
Answers:
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Method 1
First, what happens when T0 is not None? I would test that, then I would adjust the values I pass to plt.subplot(); maybe try values 131, 132, and 133, or values that depend whether or not T0 exists.
Second, after plt.show() is called, a new figure is created. To deal with this, you can
-
Call
plt.savefig('tessstttyyy.png', dpi=100)before you callplt.show() -
Save the figure before you
show()by callingplt.gcf()for “get current figure”, then you can callsavefig()on thisFigureobject at any time.
For example:
fig1 = plt.gcf()
plt.show()
plt.draw()
fig1.savefig('tessstttyyy.png', dpi=100)
In your code, ‘tesssttyyy.png’ is blank because it is saving the new figure, to which nothing has been plotted.
Method 2
plt.show() should come after plt.savefig()
Explanation: plt.show() clears the whole thing, so anything afterwards will happen on a new empty figure
Method 3
change the order of the functions fixed the problem for me:
- first Save the plot
- then Show the plot
as following:
plt.savefig('heatmap.png')
plt.show()
Method 4
Calling savefig before show() worked for me.
fig ,ax = plt.subplots(figsize = (4,4))
sns.barplot(x='sex', y='tip', color='g', ax=ax,data=tips)
sns.barplot(x='sex', y='tip', color='b', ax=ax,data=tips)
ax.legend(['Male','Female'], facecolor='w')
plt.savefig('figure.png')
plt.show()
Method 5
let’s me give a more detail example:
import numpy as np
import matplotlib.pyplot as plt
def draw_result(lst_iter, lst_loss, lst_acc, title):
plt.plot(lst_iter, lst_loss, '-b', label='loss')
plt.plot(lst_iter, lst_acc, '-r', label='accuracy')
plt.xlabel("n iteration")
plt.legend(loc='upper left')
plt.title(title)
plt.savefig(title+".png") # should before plt.show method
plt.show()
def test_draw():
lst_iter = range(100)
lst_loss = [0.01 * i + 0.01 * i ** 2 for i in xrange(100)]
# lst_loss = np.random.randn(1, 100).reshape((100, ))
lst_acc = [0.01 * i - 0.01 * i ** 2 for i in xrange(100)]
# lst_acc = np.random.randn(1, 100).reshape((100, ))
draw_result(lst_iter, lst_loss, lst_acc, "sgd_method")
if __name__ == '__main__':
test_draw()
All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0
