我有一个用于频谱计算的示例def REE_Group_Plot(dfs, label):
# combine all dataframes into 1
all_dfs = pd.concat(dfs)
# the rest of the code to plot the graph
REE_Group_Plot(dfs=[df, df2, df3, df4], label = “ABC”)
脚本。我将信号分成几个块，并对每个块进行计算。
R此处spect=function(x,samplingfrequency=1,blocksize=2^12)
{
T=length(x)
blocks=trunc(T/blocksize)
localfreq=c() ; localspec=c()
for(i in 1:blocks){localfreq[[i]]=c() ; localspec[[i]]=c() }
for(i in 1:blocks)
{
time=c( (1+(i-1)*blocksize) : (i*blocksize) )
localspectrum=spectrum(x[time],plot=FALSE)
localfreq[[i]]=localspectrum$freq
localspec[[i]]=localspectrum$spec
}
averagespec=rep(0,(blocksize/2))
for(freq in 1:(blocksize/2))
{
for(block in 1:blocks)
{
averagespec[freq]=(averagespec[freq]+localspec[[block]][freq])
}
averagespec[freq]=averagespec[freq]/blocks
}
par(mar=c(5.1,5.1,2.5,1.5))
plot(c(1:(blocksize/2))/(blocksize/2)*samplingfrequency/2,averagespec,log="xy",t="l",xlab="frequency [Hz]",ylab="average spectrum [a.u.]",cex.lab=1.8,cex.axis=1.8)
abline(v=(samplingfrequency/2),col=2)
abline(v=(1/blocksize*samplingfrequency),col=4)
}
是您的时间序列输入。我不直接使用x中的spectrum函数，因为结果太吵了。我想知道我是否可以以某种方式避免脚本中的R循环？