即使在gc.collect（）之后，分配给Python的内存也不会在Linux中释放回来

Question

我已经在Python中编写了不会按应有的方式释放内存的代码。内存由Python占用，但是即使不再使用也不会释放。即使您使用ctrl +
c中断正在运行的程序。删除变量，然后运行似乎没有收集到的gc.collect（）。或与Ipython中相同，并运行％reset。内存将不会被释放，并且运行gc.collect（）无效。我在Windows中进行了测试，因为我想看看它是否可能与垃圾收集器库一起使用。看来是这样。在Linux中然后在Windows中运行以下代码。然后比较内存使用情况。您将需要安装numpy和scipy。在这个问题上的任何帮助或见解将不胜感激。

导入模型，创建一个实例，然后运行createSpecific（）。

这是在Ubuntu 10.04中表现出这种行为的代码：

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)

Answer 1

我安装了最新的numpy svn，问题消失了。我假设它在numpyhtml" target="_blank">函数之一内。我从来没有机会进一步研究它。