我有一个名为ERRORLOG
的数据,其中我对效率进行了混合样本比较。对于sampleA和sampleB的混合,有七种不同的效率列。我希望看到这七种效率的情节,看看与前几列相比,它们的效率水平会显着下降。
C:\Program Files\Microsoft SQL Server\...\MSSQL\Log
答案 0 :(得分:4)
以下是绘制数据的一种方法:
mydf <- structure(list(sample_A=structure(c(1L,2L,2L,2L,3L,4L),.Label=c('2568','2669','2670','2671','2946','LPH-001-10_AK1','LPH-001-12_AK2','LPH-001-9'),class='factor'),sample_B=structure(c(1L,2L,3L,4L,3L,4L),.Label=c('2568','2669','2670','2671','2946','LPH-001-10_AK1','LPH-001-12_AK2','LPH-001-9'),class='factor'),efficiency=c(1.02,0.964,0.415,0.422,0.98,0.986),efficiency2=c(1,0.944,0.395,0.402,0.96,0.966),efficiency3=c(0.9,0.844,0.295,0.302,0.86,0.866),efficiency4=c(0.32,0.264,-0.285,-0.278,0.28,0.286),efficiency5=c(0.02,-0.0360000000000001,-0.585,-0.578,-0.0200000000000001,-0.0140000000000001),efficiency6=c(0.12,0.0639999999999999,-0.485,-0.478,0.08,0.086),efficiency7=c(0.02,-0.036,-0.585,-0.578,-0.02,-0.014)),.Names=c('sample_A','sample_B','efficiency','efficiency2','efficiency3','efficiency4','efficiency5','efficiency6','efficiency7'),row.names=c(NA,6L),class='data.frame');
effCis <- grep('^efficiency',names(mydf));
xlim <- c(1,length(effCis));
ylim <- range(mydf[,effCis],na.rm=T);
ylim[1L] <- floor(ylim[1L]/0.1)*0.1;
ylim[2L] <- ceiling(ylim[2L]/0.1)*0.1;
xticks <- seq_along(effCis);
yticks <- seq(ylim[1L],ylim[2L],0.1);
plot(NA,xlim=xlim,ylim=ylim,xlab='measurement',ylab='efficiency',xaxs='i',yaxs='i',axes=F);
abline(v=xticks,col='lightgrey');
abline(h=yticks,col='lightgrey');
abline(h=0,lwd=2);
axis(1L,xticks,xticks,font=2L,cex.axis=0.7);
axis(2L,yticks,sprintf('%.1f',yticks),las=1L,font=2L,cex.axis=0.7);
hybrid.col <- data.frame(hybrid=seq_len(nrow(mydf)),col=c('red','green','blue','gold','cyan','magenta'),stringsAsFactors=F);
splineN <- 200L;
for (ri in seq_len(nrow(hybrid.col))) {
hybrid <- hybrid.col$hybrid[ri];
col <- hybrid.col$col[ri];
x <- xticks;
y <- c(as.matrix(mydf[hybrid,effCis]));
points(x,y,pch=16L,col=col,xpd=NA);
with(spline(x,y,splineN),{
lines(x,y,col=col,lwd=2,xpd=NA);
localwin <- which(x>2 & x<3);
tp <- which.min(abs(diff(y[localwin])));
if (length(tp)>0L) points(x[localwin[tp]],y[localwin[tp]],col=col,pch=4L);
localwin <- which(x>2 & x<5);
tp <- which.min(diff(y[localwin]));
if (length(tp)>0L) {
m <- diff(y[localwin[seq(tp,len=2L)]])/diff(x[localwin[seq(tp,len=2L)]]);
if (is.finite(m)) abline(y[localwin[tp]]-m*x[localwin[tp]],m,col=col,lty=2L);
};
});
};
legend(5.5,0.95,paste0(mydf$sample_A,' / ',mydf$sample_B),fill=hybrid.col$col,cex=0.7,title='hybrid');
我不能100%确定你的渐近线是什么意思。我最初想过,也许你想要它们开始下降之前的曲线的局部最大值,这就是我用点(符号X,即pch=4L
)标记局部最大值的原因。但后来我意识到你可能意味着沿着水滴的切线,所以我添加了与最陡斜点相切的线。
这是渐近线的定义:
当曲线方程中的一个变量接近无穷大时,给定曲线逼近的直线。
我认为这不适用于此;绘制这些数据不涉及将任何东西带到无穷大。我想你想要局部最大值或切线。