Matplotlib (pyplot) savefig outputs blank image

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)

Solution 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

1. Call plt.savefig('tessstttyyy.png', dpi=100) before you call plt.show()

2. Save the figure before you show() by calling plt.gcf() for "get current figure", then you can call savefig() on this Figure object 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.

Solution 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

Solution 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()

Solution 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()

Solution 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()