应用规范化

我正在为一位同事开展一个项目，以标准化 GC 数据并将其从 mol% 转换为 mass%。

编辑：我正在做逐行归一化。即每次物种的总和norm1应该是 100（尽管每个都乘以质量，因此不再总和为 100。在 for 循环中，它相当于一个非常繁重的：

for (time in Nmass[,1]){
   for species in norm1{
      Nmass[time,species] = Fmolwt[species,] = Nmass[time,species] / rowSums(Nmass[time,norm1])
                       }
                       }

我导入了 CSV 文件，它们被排列为物种名称列和注射时间行（处理虚拟数据，因此当前全部为零）。

> Nmass[1:5,c("Time",norm1)]
# A tibble: 5 x 13
  Time                HTFeed_Methane HTFeed_Ethane HTFeed_Ethylene HTFeed_Propane HTFeed_Propylene `HTFeed_iso-butane` `HTFee~ `HTFeed~ `HTFe~ HTFee~ `HTFee~ `HTFee~
  <dttm>                       <dbl>         <dbl>           <dbl>          <dbl>            <dbl>               <dbl>   <dbl>    <dbl>  <dbl>  <dbl>   <dbl>   <dbl>
1 2019-10-06 13:02:00              0             0               0              0                0                   0       0        0      0      0       0       0
2 2019-10-06 13:17:00              0             0               0              0                0                   0       0        0      0      0       0       0
3 2019-10-06 13:32:00              0             0               0              0                0                   0       0        0      0      0       0       0
4 2019-10-06 13:47:00              0             0               0              0                0                   0       0        0      0      0       0       0
5 2019-10-06 14:02:00              0             0               0              0                0                   0       0        0      0      0       0       0

我有一个正常工作的例程：

norm1 = c('HTFeed_Methane','HTFeed_Ethane','HTFeed_Ethylene','HTFeed_Propane','HTFeed_Propylene','HTFeed_iso-butane','HTFeed_n-Butane',
        'HTFeed_trans-2-butene','HTFeed_1-Butene','HTFeed_Isobutylene','HTFeed_cis-2-butene','HTFeed_1,3-Butadiene')

Nmass[,norm1] = as.data.frame(apply(Nmass[,norm1], 2, function(x) x/sum(x)))

但是当我尝试使用按物种预先构建的质量列表来实现质量转换时：

Fmolwt = data.frame(c(16.04,30.07,28.05,44.9,42.08,58.12,58.12,56.11,56.11,56.11,56.11,54.1))
colnames(Fmolwt)[1] = 'weight'
rownames(Fmolwt) = c('HTFeed_Methane','HTFeed_Ethane','HTFeed_Ethylene','HTFeed_Propane','HTFeed_Propylene','HTFeed_iso-butane',
                    'HTFeed_n-Butane','HTFeed_trans-2-butene','HTFeed_1-Butene','HTFeed_Isobutylene','HTFeed_cis-2-butene','HTFeed_1,3-Butadiene')

例程变为（我认为）：

Nmass[,norm1] = as.data.frame(apply(Nmass[,norm1], 2, function(x) x*Fmolwt[x,]/sum(x)))

我收到关于尺寸不同的错误。

Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE,  : 
  arguments imply differing number of rows: 0, 3696
In addition: Warning messages:
1: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
2: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
3: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
4: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
5: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
6: In x * Fmolwt[x, ] :
  longer object length is not a multiple of shorter object length
7: In x * Fmolwt[x, ] :

我预计这是由于 apply 语句试图同时引入所有命名的分子量norm1。

我可以按照我尝试的方式完成这项工作，还是需要写出一个 for 循环？