我在Python中编写的代码不会以应有的方式释放内存。内存由Python占用，但即使在不再使用后也永远不会被释放。即使你用ctrl + c打破正在运行的程序。删除变量并运行它似乎不收集的gc.collect（）。或者与Ipython中相同并运行％reset。内存不会被释放并且运行gc.collect（）无效。我在Windows中对此进行了测试，因为我想看看它是否可能与垃圾收集器库有关。看来情况就是这样。在Linux中运行下面的代码，然后在Windows中运行。然后比较内存使用情况。你需要安装numpy和scipy。对此问题的任何帮助或见解将不胜感激。
导入模型，创建实例，然后运行createSpecific（）。
以下是在Ubuntu 10.04中展示此行为的代码：
from numpy import array, maximum,intersect1d, meshgrid, std, log, log10, zeros, ones, argwhere, abs, arange, size, copy, sqrt, sin, cos, pi, vstack, hstack, zeros, exp, max, mean, savetxt, loadtxt, minimum, linspace, where
from numpy.fft import fft
from scipy.stats import f_oneway, kruskal, sem, scoreatpercentile
#import matplotlib
#matplotlib.use('cairo.pdf')
from matplotlib.pyplot import plot, clf, show, cla, xlim, xscale, imshow, ylabel, xlabel, figure, savefig, close, bar, title, xticks, yticks, axes, axis
from matplotlib.axes import Axes
from mpl_toolkits.mplot3d import Axes3D
#from enthought.mayavi import mlab
from matplotlib import cm
import matplotlib.pyplot as plt
import os
from time import clock
from timeit import Timer
class Model:
#Constructors and default includes
def __init__(self, prevAud = None, debug=False):
if (prevAud == None):
self.fs=16000. #sample rate
self.lowFreq=60.
self.hiFreq=5000.
self.numFilt=300 #number of channel
self.EarQ = 9.26449 #9.26449
self.minBW = 24.7 #24.7
self.integrationWindow=.01
self.sliceAt=.035
self.maxOverallInhibit = 0.1
self.winLen = int(self.fs*self.integrationWindow+.01) #default integration window 10 ms
self.fullWind = 0.300
self.outShortWindow = None
self.siderArray = None
self.maxNormalizeValue = .284 # Optimized at .284
self.outputSemiModel = None
self.semitones = 11
self.activationTrace = None
return
def setErbScale(self, erbScale = None):
if (erbScale ==None):
self.erbScale = arange(100,500,5)
else:
self.erbScale = erbScale
def trainModel(self,soundVec=None, fs=None, lowfreq=None, highfreq=None, numfilt=None, figto=0, savefig = 'N', prompts=False, plotter=False):
self.setErbScale()
templateArray = self.intWindow(self.halfWaveRec(self.creGammatone(soundVec)))
for i in xrange(templateArray[0].size):
self.outerTest(self.innerTest(templateArray[:,i]))
return templateArray
def createSpecific(self, freqArray = None, semitones = 11, timeforHarm = .3, soundVec=None, fs=None, lowfreq=None, highfreq=None, numfilt=None, figto=0, saveData='N', fileDir='TempRunT/', prompts=False, plotter=False):
if (freqArray == None):
self.setErbScale()
freqArray = self.erbScale
if (type(semitones) == int):
semitones = arange(semitones+1)
totalRuns = int(timeforHarm/self.integrationWindow+.001)
inhibitWindowArray = zeros((freqArray.size,(semitones.size),self.numFilt,totalRuns))
for x in xrange(freqArray.size):
tempHarm = self.makeHarmonicAmpMod(freqArray[x],timeforHarm, numHarm=7,modulation=10)
for y in semitones:
tempChord = self.makeSemiChordAmpMod(tempHarm, freqArray[x],timeforHarm,modulation=10,numHarm=7,semi=y)
inhibitWindowArray[x,y] = self.trainModel( tempChord, savefig = 'N', plotter=plotter)
self.inhibitWindowArray = inhibitWindowArray
def creGammatone(self, soundVec):
temp = zeros((300,soundVec.size))
for i in xrange(temp[:,0].size):
temp[i] = -1**i*soundVec
return temp
def halfWaveRec(self, halfWaveFilts):
filtShape = halfWaveFilts.shape
if (filtShape[1] != int(self.fs*self.fullWind)):
halfWaveFilts = hstack((halfWaveFilts,zeros((self.numFilt,int(self.fs*self.fullWind)-filtShape[1]))))
temp = zeros((halfWaveFilts[:,0].size,halfWaveFilts[0].size))
halfWaveFilts = maximum(halfWaveFilts,temp)
del temp
return halfWaveFilts
def intWindow(self, integratedFilts):
winlen = self.winLen
length = integratedFilts[0].size/winlen
mod = integratedFilts[0].size%winlen
outShortWindow = zeros((integratedFilts[:,0].size,length))
meanval = 0
if (mod != 0):
for i in xrange(integratedFilts[:,0].size):
mean(integratedFilts[i,0:-mod].reshape(length,winlen),1,out=outShortWindow[i])
else:
for i in xrange(integratedFilts[:,0].size):
mean(integratedFilts[i].reshape(length,winlen),1,out=outShortWindow[i])
del integratedFilts
return outShortWindow
def innerTest(self, window):
temper = copy(window)
sider = 7
st = .04
sizer = temper.size
inhibVal = 0
for j in xrange(sider):
inhibVal = (temper[0:j+sider+1].sum())*(sider*2+1)/(sider+1+j)
window[j] += - st*(inhibVal)
for j in xrange(sider,sizer - sider):
inhibVal = temper[j-sider:j+sider+1].sum()
window[j] += - st*(inhibVal)
for j in xrange(sizer-sider, sizer):
inhibVal = (temper[j-sider:sizer].sum())*(sider*2+1)/(sider+sizer-j)
window[j] += - st*(inhibVal)
maxsub = max(window) * self.maxOverallInhibit
window += - maxsub
del temper
return window
def outerTest(self, window):
newSatValue = scoreatpercentile(window, (76))
numones = where(window > newSatValue)
window[numones]=1
self.maxSatValue = newSatValue
del numones
return window
def makeHarmonicAmpMod(self, freq = 100, time = 1.,modulation=10, fsamp=None, numHarm=7):
if fsamp == None: fsamp = self.fs
samples = arange(time*fsamp)
signal = 0
for x in xrange(1,(numHarm+1),1):
signal = signal + sin(samples/float(fsamp)*x*freq*2*pi)
signal = (signal)*maximum(zeros(time*fsamp),sin((samples/float(fsamp)*modulation*2*pi)))
return signal
def makeSemiChordAmpMod(self, harmVec = None, freq=100, time = 1., modulation=10, fsamp=None, numHarm=7, semi = 2):
if (harmVec == None): harmVec = self.makeHarmonicAmpMod(freq,time,modulation,fsamp,numHarm)
if (semi == 0): return harmVec
return harmVec + self.makeHarmonicAmpMod(freq*(2**(semi/12.)),time,modulation,fsamp,numHarm)
答案 0 :(得分：2)
虚拟内存不是稀缺资源。由于每个进程都有自己的地址空间，因此无需将其返回给系统。你的实际问题是什么？导致这种情况的问题是什么？
答案 1 :(得分：0)
我安装了最新的nvy svn并且问题已经消失了。我认为它是在一个numpy函数内。我再也没有机会深入挖掘它。