Diagnosing Memory Leaks in Matplotlib

test_oo.py

# Object-oriented API
#
# Memory usage (iteration, object count, memory size)
# 100 5637 1562216
# 200 5529 1491528
# 300 5422 1426264
# 400 5758 1587376
# 500 5422 1426288
# 600 5416 1440456
# 700 5610 1515056
# 800 5422 1426032
# 900 5530 1493264
# 
# 241.35 real       239.52 user         1.38 sys

import matplotlib as mpl
mpl.use('Agg')

from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas

import numpy as np

import guppy

heapy = guppy.hpy()

mem = open('memory_oo.txt', 'wb')

heapy.setref()

for i in range(1000):

    if i % 100 == 0:
        h = heapy.heap()
        mem.write('%i %s %s\n' % (i, h.count, h.size))

    fig = Figure()
    canvas = FigureCanvas(fig)
    ax = fig.add_subplot(1, 1, 1)
    ax.scatter(np.random.random(10), np.random.random(10))
    canvas.print_figure('test.png')

mem.close()

test_pyplot.py

# Original
#
# Memory usage (iteration, object count, memory size)
# 100 431941 134768552
# 200 862736 269479552
# 300 1295682 405239168
# 400 1726603 539967136
# 500 2157948 674784872
# 600 2589067 809598080
# 700 3020848 944697920
# 800 3451516 1079398704
# 900 3884074 1214923736
# 
# 2542.85 real      2535.49 user         6.66 sys

import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

import numpy as np

import guppy

heapy = guppy.hpy()

mem = open('memory_pyplot.txt', 'wb')

heapy.setref()

for i in range(1000):

    if i % 100 == 0:
        h = heapy.heap()
        mem.write('%i %s %s\n' % (i, h.count, h.size))

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.scatter(np.random.random(10), np.random.random(10))
    fig.savefig('test.png')

    mem.flush()

mem.close()

test_pyplot_clf.py

# Added fig.clf()
#
# Memory usage (iteration, object count, memory size)
# 100 24523  7963408
# 200 43692  14487880
# 300 63681  21294464
# 400 82909  27825696
# 500 102409 34451408
# 600 121637 40974992
# 700 141545 47740552
# 800 160909 54312208
# 900 180409 60949200
#
# 454.47 real       450.69 user         3.20 sys


import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

import numpy as np

import guppy

heapy = guppy.hpy()

mem = open('memory_pyplot_clf.txt', 'wb')

heapy.setref()

for i in range(1000):

    if i % 100 == 0:
        h = heapy.heap()
        mem.write('%i %s %s\n' % (i, h.count, h.size))

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.scatter(np.random.random(10), np.random.random(10))
    fig.savefig('test.png')

    fig.clf()

mem.close()

test_pyplot_close.py

# Added plt.close()
#
# Memory usage (iteration, object count, memory size)
# 100 5461 1464216
# 200 5683 1569464
# 300 5610 1527120
# 400 5798 1617432
# 500 5320 1366000
# 600 5610 1530224
# 700 5724 1579600
# 800 5610 1527040
# 900 5616 1514112
#
# 271.73 real       270.46 user         0.77 sys


import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

import numpy as np

import guppy

heapy = guppy.hpy()

mem = open('memory_pyplot_close.txt', 'wb')

heapy.setref()

for i in range(1000):

    if i % 100 == 0:
        h = heapy.heap()
        mem.write('%i %s %s\n' % (i, h.count, h.size))

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.scatter(np.random.random(10), np.random.random(10))
    fig.savefig('test.png')

    plt.close()

mem.close()