问题描述
我有一个包含ID,Vg,Device,Die,W,L和其他列的大数据集(与该问题无关).我想以给定的Id值对Vg进行插值,但是必须对按Device and Die列分组的数据执行此操作.
I have a big data set with columns Id, Vg, Device, Die, W ,L and others (not relevant to this question). I want to interpolate Vg at a given value of Id but this operation has to be performed on data grouped by column Device and Die.
我的样本数据如下
Die Device Id Vg W L
1 Device1 1 0 10 1
1 Device1 1.2 0.1 10 1
1 Device1 1.3 0.2 10 1
1 Device2 1 0 10 2
1 Device2 1.2 0.1 10 2
1 Device2 1.3 0.2 10 2
1 Device3 1 0 10 3
1 Device3 1.2 0.1 10 3
1 Device3 1.3 0.2 10 3
每个骰子都有22个独特的器件.有67个管芯,每个管芯上的22个设备名称相同.因此,如果我对Id = 1.25的Vg进行插值,那么我期望对Id = 1.25的Vg取22 * 67的值.
Each die has 22 unique devices. There are 67 dies and 22 Device names on each die are the same. Therefore if I interpolate Vg for Id=1.25, I expect to get 22*67 values of Vg for Id=1.25.
这是我正在尝试的代码
data_tidy%>%
group_by(Die,Device)%>% #Die is numeric, Device is factor
mutate(Vt=approx(x=log10(Id),y=Vg,xout=log10(3e-8*W/L))$y)
这类似于建议的此处,我正在从下方链接
This is similar to what is suggested here and I am copying the suggested code from the link below
df %>%
group_by(variable) %>%
arrange(variable, event.date) %>%
mutate(time=seq(1,n())) %>%
mutate(ip.value=approx(time,value,time)$y) %>%
select(-time)
但是,当我在上面执行代码时,会收到一条错误消息,提示
However, when I execute my code above I get an error message saying
推荐答案
以下是data.table解决方案:
Here's a data.table solution:
library(data.table)
f <- function(x) setDT(df)[,approx(Id,Vg,x), by=list(Device,Die)]
f(1.25)
# Device Die x y
# 1: Device1 1 1.25 0.15
# 2: Device2 1 1.25 0.15
# 3: Device3 1 1.25 0.15
此处 y
列是插值.
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