对象没有LEN（）错误

Question

我使用蟒并行编程模块我已返回我的阵列，但是当我打印变量包含并行化的函数的值的函数返回我“ pp._Task object at 0x04696510“，而不是矩阵的值。 下面是代码：

from __future__ import print_function 
import scipy, pylab 
from scipy.io.wavfile import read 
import sys 
import peakpicker as pea 
import pp 
import fingerprint as fhash 
import matplotlib 
import numpy as np 
import tdft 
import subprocess 
import time 
if __name__ == '__main__': 
     start=time.time() 
     #Peak picking dimensions 
     f_dim1 = 30 
     t_dim1 = 80 
     f_dim2 = 10 
     t_dim2 = 20 
     percentile = 80 
     base = 100 # lowest frequency bin used (peaks below are too common/not as useful for identification) 
     high_peak_threshold = 75 
     low_peak_threshold = 60 
     #TDFT parameters 
     windowsize = 0.008  #set the window size (0.008s = 64 samples) 
     windowshift = 0.004 #set the window shift (0.004s = 32 samples) 
     fftsize = 1024   #set the fft size (if srate = 8000, 1024 --> 513 freq. bins separated by 7.797 Hz from 0 to 4000Hz) 

     #Hash parameters 
     delay_time = 250  # 250*0.004 = 1 second#200 
     delta_time = 250*3 # 750*0.004 = 3 seconds#300 
     delta_freq = 128  # 128*7.797Hz = approx 1000Hz#80 
     #Time pair parameters 
     TPdelta_freq = 4 
     TPdelta_time = 2 


     #Cargando datos almacenados 
     database=np.loadtxt('database.dat') 
     songnames=np.loadtxt('songnames.dat', dtype=str, delimiter='\t') 
     separator = '.' 
     print('Please enter an audio sample file to identify: ') 
     userinput = raw_input('---> ') 
     subprocess.call(['ffmpeg','-y','-i',userinput, '-ac', '1','-ar', '8k', 'filesample.wav']) 
     sample = read('filesample.wav') 
     userinput = userinput.split(separator,1)[0] 
     print('Analyzing the audio sample: '+str(userinput)) 
     srate = sample[0] #sample rate in samples/second 
     audio = sample[1] #audio data  
     spectrogram = tdft.tdft(audio, srate, windowsize, windowshift, fftsize) 
     mytime = spectrogram.shape[0] 
     freq = spectrogram.shape[1] 

     print('The size of the spectrogram is time: '+str(mytime)+' and freq: '+str(freq)) 

     threshold = pea.find_thres(spectrogram, percentile, base) 

     peaks = pea.peak_pick(spectrogram,f_dim1,t_dim1,f_dim2,t_dim2,threshold,base) 

     print('The initial number of peaks is:'+str(len(peaks))) 
     peaks = pea.reduce_peaks(peaks, fftsize, high_peak_threshold, low_peak_threshold) 
     print('The reduced number of peaks is:'+str(len(peaks))) 

     #Store information for the spectrogram graph 
     samplePeaks = peaks 
     sampleSpectro = spectrogram 

     hashSample = fhash.hashSamplePeaks(peaks,delay_time,delta_time,delta_freq) 
     print('The dimensions of the hash matrix of the sample: '+str(hashSample.shape)) 


     # tuple of all parallel python servers to connect with 
     ppservers =() 
     #ppservers = ("10.0.0.1",) 

     if len(sys.argv) > 1: 
      ncpus = int(sys.argv[1]) 
      # Creates jobserver with ncpus workers 
      job_server = pp.Server(ncpus, ppservers=ppservers) 
     else: 
      # Creates jobserver with automatically detected number of workers 
      job_server = pp.Server(ppservers=ppservers) 

     print ("Starting pp with", job_server.get_ncpus(), "workers") 

     print('Attempting to identify the sample audio clip.') 

这里我称之为指纹的功能，注释行的工作，但是当我尝试并行不起作用：

 timepairs = job_server.submit(fhash.findTimePairs, (database, hashSample, TPdelta_freq, TPdelta_time,)) 
#  timepairs = fhash.findTimePairs(database, hashSample, TPdelta_freq, TPdelta_time) 
     print (timepairs) 


     #Compute number of matches by song id to determine a match 
     numSongs = len(songnames) 
     songbins= np.zeros(numSongs) 
     numOffsets = len(timepairs) 
     offsets = np.zeros(numOffsets) 
     index = 0 
     for i in timepairs: 
       offsets[index]=i[0]-i[1] 
       index = index+1 
       songbins[i[2]] += 1 

     # Identify the song 
     #orderarray=np.column_stack((songbins,songnames)) 
     #orderarray=orderarray[np.lexsort((songnames,songbins))] 
     q3=np.percentile(songbins, 75) 
     q1=np.percentile(songbins, 25) 
     j=0 
     for i in songbins: 
       if i>(q3+(3*(q3-q1))): 
         print("Result-> "+str(i)+":"+songnames[j]) 
       j+=1 
     end=time.time() 
     print('Tiempo: '+str(end-start)+' s') 
     print("Time elapsed: ", +time.time() - start, "s") 
     fig3 = pylab.figure(1003) 
     ax = fig3.add_subplot(111) 
     ind = np.arange(numSongs) 
     width = 0.35 
     rects1 = ax.bar(ind,songbins,width,color='blue',align='center') 
     ax.set_ylabel('Number of Matches') 
     ax.set_xticks(ind) 
     xtickNames = ax.set_xticklabels(songnames) 
     matplotlib.pyplot.setp(xtickNames) 
     pylab.title('Song Identification') 
     fig3.show() 

     pylab.show() 

     print('The sample song is: '+str(songnames[np.argmax(songbins)])) 

指纹的功能，我尝试并行是：

def findTimePairs(hash_database,sample_hash,deltaTime,deltaFreq): 
"Find the matching pairs between sample audio file and the songs in the database" 

timePairs = [] 

for i in sample_hash: 
    for j in hash_database: 
     if(i[0] > (j[0]-deltaFreq) and i[0] < (j[0] + deltaFreq)): 
      if(i[1] > (j[1]-deltaFreq) and i[1] < (j[1] + deltaFreq)): 
       if(i[2] > (j[2]-deltaTime) and i[2] < (j[2] + deltaTime)): 
        timePairs.append((j[3],i[3],j[4])) 
       else: 
        continue 
      else: 
       continue 
     else: 
      continue 

return timePairs 

完整的错误是：

Traceback (most recent call last): 
File "analisisPrueba.py", line 93, in <module> 
numOffsets = len(timepairs) 
TypeError: object of type '_Task' has no len() 

Answer 1

的submit()方法将任务提交到服务器。你得到的是对任务的引用，而不是结果。 （怎么可能之前任何工作已经完成的返回它的结果？submit()回报！）而应该提供一个回调函数接收结果。例如，timepairs.append是将拍摄效果，并将其附加到列表timepairs的功能。

timepairs = [] 
job_server.submit(fhash.findTimePairs, (database, hashSample, TPdelta_freq, TPdelta_time,), callback=timepairs.append) 

（每个findTimePairs调用应计算一个结果是，在并不明显的情况下，你应该提交多个任务。否则，你是在调用并行的Python的所有机器无缘无故。请确保您拨打job_server.wait()等待所有任务完成，然后再尝试对结果做任何事情。简而言之，请阅读文档和一些示例脚本，并确保您了解其工作原理。）