Truncate dataset after maximum value

I have a dataset with repeated measures over time, in which I am looking for predictors of the maximum tn value. I am not interested in measures which occur after this. The maximum values occur on different days for different patients.

ID  day  tn  hb  sofa  
1    1   7   85   NA  
1    2   NA  NA   NA  
1    3   35  80   13  
1    4   28  79   12  
2    1   500 NA   12  
2    2   280 80   9  
2    3   140 90   8  
2    4   20  90   7  
3    1   60  80   12  
3    2   75  75   10  
3    3   NA  75   NA  
3    4   55  84   7

I can find tn_ max:

    tn_max <- df %>% group_by(record) %>% summarise(tn_max = max(tn,na.rm=TRUE))

How can I truncate the dataset after the maximum tn for each patient? I found this code from a previous similar question, but I can't get it to work Error: unexpected ':' in "N_max = find(df(:"

    mod_df = df; 
    N_max = find(df(:,3) == max(df(:,3)));
    N_max(1);

    for N=1:size(df,3)
    if df(N,1) < N_max
    mod_df (N,:)=0;
    end
    end
    mod_data_1(all(mod_data_1==0,1),:) = []

Many thanks, Annemarie

Solution

First I would create a function able to return, for any vector, a Boolean vector of the same length and whose coefficients are TRUE if the value occurs before the maximum, and FALSE otherwise:

f <- function(x) 1:length(x) <= which.max(x)

Then I would apply this function to each sub-vector of tn defined by the ID :

ind <- as.logical(ave(df$tn, df$ID, FUN=f))

Finally, all I have to do is to take the corresponding subset of the original data-frame:

df[ind, ]