Description
Bug report
I've noticed that when running a matplotlib as a run-chart/long term plotting tool, memory use by matplotlib increases over the course of about a week, ultimately crashing the program. I'm continually updating my plot, but I am only plotting the most recent 100 data points (so that the data itself isn't contributing to the memory increase). See an overly simplified example below that still shows the issue. As you will see when running the code below, matplotlib\transforms.py just continually increases by around 5-15 kb on each turn of the loop, despite clearing my axes and using the object oriented version of matplotlib. This increase will continue to happen until it fills up the memory of my computer. Is this intentional? My thought was that in the object oriented program version of matplotlib, my code shouldn't increase in memory like this.
Most of the code below is simply just tracemalloc helper functions for keeping track of memory.
Code for reproduction
import matplotlib.pyplot as plt
import numpy as np
import os
import linecache
import sys
import tracemalloc
import time
def display_top(snapshot, key_type='lineno', limit=2):
'''
function for pretty printing tracemalloc output
'''
snapshot = snapshot.filter_traces((
tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
tracemalloc.Filter(False, "<unknown>"),
))
top_stats = snapshot.statistics(key_type)
print("Top %s lines" % limit)
for index, stat in enumerate(top_stats[:limit], 1):
frame = stat.traceback[0]
# replace "/path/to/module/file.py" with "module/file.py"
filename = os.sep.join(frame.filename.split(os.sep)[-2:])
print("#%s: %s:%s: %.1f KiB"
% (index, filename, frame.lineno, stat.size / 1024))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
print(' %s' % line)
other = top_stats[limit:]
if other:
size = sum(stat.size for stat in other)
print("%s other: %.1f KiB" % (len(other), size / 1024))
total = sum(stat.size for stat in top_stats)
print("Total allocated size: %.1f KiB" % (total / 1024))
tracemalloc.start()
y = np.random.rand(100)
x = range(len(y))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x,y,'b-')
plt.show(block=False)
t0 = time.time()
while True:
try:
ax.clear()
ax.plot(x,np.random.rand(100),'b-')
plt.pause(0.0001)
snapshot = tracemalloc.take_snapshot()
print("Run Time:", time.time()-t0)
display_top(snapshot)
time.sleep(0.05)
except KeyboardInterrupt:
breakIf you'd prefer to use your own memory debugger, here's the simplest form of this issue:
import matplotlib.pyplot as plt
import numpy as np
import time
y = np.random.rand(100)
x = range(len(y))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x,y,'b-')
plt.show(block=False)
t0 = time.time()
while True:
try:
ax.clear()
ax.plot(x,np.random.rand(100),'b-')
plt.pause(0.0001)
print("Run Time:", time.time()-t0)
time.sleep(0.05)
except KeyboardInterrupt:
breakIn the console output, you'll see matplotlib\transforms.py quickly become the largest memory holder, and increase continually.
This issue also appears if I use a line object and line.set_xdata, etc., rather than ax.plot().
Using WinPython, Python 3.6.2
Matplotlib version 2.2.2
Windows 7 and Windows 10
Backend TkAgg