Fixes a memory leak where each spines' path was a view of the spine path of the previous run.
The following code (simplified to its essence from an example by Caleb Constantine) leaks memory very slowly -- detectable only using valgrind. It turns out that if the axes are cleared and reused rather than deleted, each spine's path is created as a view based on the spine's path in the previous draw. This creates a long reference chain rather than freeing the previous draw's path view.
This pull request fixes the leak, but @astraw may want to have a look at the fix... I'm not entirely sure why the copy is needed at all -- it hasn't actually been creating a copy all this time any way. Perhaps an alternative solution is just to remove the copy and the assignment (marked with the comment "# replace") altogether?
import numpy
import matplotlib
matplotlib.use("Agg")
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
figure = Figure(dpi=None)
canvas = FigureCanvas(figure)
axes = figure.add_subplot(1,1,1)
def draw(channel, seconds):
axes.clear()
axes.plot(channel, seconds)
canvas.print_figure('test.png')
channel = numpy.sin(numpy.arange(1000))
seconds = numpy.arange(len(channel))
for i in range(10):
draw(channel, seconds)
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Fixes a memory leak where each spines' path was a view of the spine path of the previous run.
The following code (simplified to its essence from an example by Caleb Constantine) leaks memory very slowly -- detectable only using valgrind. It turns out that if the axes are cleared and reused rather than deleted, each spine's path is created as a view based on the spine's path in the previous draw. This creates a long reference chain rather than freeing the previous draw's path view.
This pull request fixes the leak, but @astraw may want to have a look at the fix... I'm not entirely sure why the copy is needed at all -- it hasn't actually been creating a copy all this time any way. Perhaps an alternative solution is just to remove the copy and the assignment (marked with the comment "# replace") altogether?
import numpy import matplotlib matplotlib.use("Agg") from matplotlib.figure import Figure from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas figure = Figure(dpi=None) canvas = FigureCanvas(figure) axes = figure.add_subplot(1,1,1) def draw(channel, seconds): axes.clear() axes.plot(channel, seconds) canvas.print_figure('test.png') channel = numpy.sin(numpy.arange(1000)) seconds = numpy.arange(len(channel)) for i in range(10): draw(channel, seconds)