我试着加速这个循环,把数据分成两类。通常我不太关心速度,但我发现现在这个代码的速度在多次迭代之后实际上正在显著地减慢。下面是我如何编写代码:
plane1Data = []
plane2Data = []
plane1Times = []
plane2Times = []
plane1Dets = []
plane2Dets = []
t1 = time.time()
for i in range(0,len(adcBoardVals)):#10000):
tic = time.time()
if adcBoardVals[i] == 5:
if adcChannel[i] == 0:
#detectorVal = detectorVal + [0]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [0]
elif adcChannel[i] == 1:
#detectorVal = detectorVal + [1]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [1]
elif adcChannel[i] == 2:
#detectorVal = detectorVal + [2]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [2]
elif adcChannel[i] == 3:
#detectorVal = detectorVal + [3]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [3]
elif adcChannel[i] == 4:
#detectorVal = detectorVal + [4]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
#plane1Dets = plane1Dets + [4]
elif adcChannel[i] == 5:
#detectorVal = detectorVal + [5]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [5]
elif adcChannel[i] == 6:
#detectorVal = detectorVal + [6]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [6]
elif adcChannel[i] == 7:
#detectorVal = detectorVal + [7]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [7]
elif adcBoardVals[i] == 7:
if adcChannel[i] == 0:
#detectorVal = detectorVal + [16]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [16]
elif adcChannel[i] == 1:
#detectorVal = detectorVal + [17]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [17]
elif adcChannel[i] == 2:
#detectorVal = detectorVal + [18]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [18]
elif adcChannel[i] == 3:
#detectorVal = detectorVal + [19]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [19]
elif adcChannel[i] == 4:
#detectorVal = detectorVal + [20]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [20]
elif adcChannel[i] == 5:
#detectorVal = detectorVal + [21]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [21]
elif adcChannel[i] == 6:
#detectorVal = detectorVal + [22]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [22]
elif adcChannel[i] == 7:
#detectorVal = detectorVal + [23]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [23]
elif adcBoardVals[i] == 6:
if adcChannel[i] == 0:
#detectorVal = detectorVal + [8]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [8]
elif adcChannel[i] == 1:
#detectorVal = detectorVal + [9]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [9]
elif adcChannel[i] == 2:
#detectorVal = detectorVal + [10]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [10]
elif adcChannel[i] == 3:
#detectorVal = detectorVal + [11]
plane1Data = plane1Data + [rawDataMat[i,:]]
plane1Times = plane1Times + [timeVals[i]]
plane1Dets = plane1Dets + [11]
elif adcChannel[i] == 4:
#detectorVal = detectorVal + [12]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [12]
elif adcChannel[i] == 5:
#detectorVal = detectorVal + [13]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [13]
elif adcChannel[i] == 6:
#detectorVal = detectorVal + [14]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [14]
elif adcChannel[i] == 7:
#detectorVal = detectorVal + [15]
plane2Data = plane2Data + [rawDataMat[i,:]]
plane2Times = plane2Times + [timeVals[i]]
plane2Dets = plane2Dets + [15]
if i%100000 == 0:
print('k = ',i)
toc = time.time()
print('tictoc = ',toc-tic)
print('elapsed = ',toc-t1)
elif i>900000:
if i%1000 == 0:
print('k = ',i)
toc = time.time()
print('tictoc = ',toc-tic)
print('elapsed = ',toc-t1)
#detectorVal = np.array(detectorVal,dtype='float')
plane1Data = np.array(plane1Data,dtype='float')
plane2Data = np.array(plane2Data,dtype='float')
plane1Times = np.array(plane1Times,dtype='float')
plane2Times = np.array(plane2Times,dtype='float')
plane1Dets = np.array(plane1Dets,dtype='int')
plane2Dets = np.array(plane2Dets,dtype='int')
我模模糊糊地记得不久前我上的一门c++课程,你可以列出比嵌套的“if”语句运行得更快的列表。这是正确的吗?如果是的话,我可以用python来做这个吗?我现在正在运行python3.5。谢谢你的帮助。在
你的问题,而且是一个主要的浪费时间的问题,是形式的陈述
在每个循环迭代中调用其中三个,例如:
^{pr2}$因为您可能有对
list_variable
所指向的列表的其他引用,所以Python在每次调用时都会构造一个完整的列表副本,只在执行赋值时丢弃原始的列表。将以下表格用于所有列表扩展名,您将看到天翻地覆的改进:这里有证据证明这是真的发生了:
给你。对于这个100000个元素列表,添加到位比复制和分配快三千倍。如果你想衡量你的收益,你可以分析你自己的数据子集。在
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