Background

This routine is used in a package that calculates tree (as in Christmas tree) volumes for various species codes (spcd) and geographic regions. The equation forms and coefficients vary by species and region, so I have a dataframe of functions along with their respective species and region that calculate the volume based off of the height (ht) of the tree and diameter (dbh).

Data Setup

Note: In my package, this part is taken care of by other functions, this is just to create a reproducible example (please ignore the sloppyness)

I have a data frame that includes a column of functions, along with some information about “where” to apply those functions in another data frame.

The functions (in reality these are more complex):

func1 <- function(dbh,ht){dbh^2 + ht} func2 <- function(dbh,ht){dbh^2 - ht}    

The data frame (in reality this data frame is much longer):

spcd <- c(122, 122, 141, 141) region <- c('OR_W', 'OR_E', 'OR_W', 'OR_E')  funcs_df <- data.frame(spcd, region, funcs) funcs_df$  funcs <- c("func1", "func2", "func1", "func2") 

Then, I have another frame that has some information, including the spcd and region that should match the values in func_df:

spcd <- c(122, 141, 141, 122, 141, 122) region <- c('OR_W', 'OR_E', 'OR_W', 'OR_E', 'OR_W', 'OR_W') dbh <- c(12, 13, 15, 11, 10, 21) ht <- c(101, 121, 100, 99, 88, 76)  tree_df <- data.frame(spcd, region, dbh, ht) 

Applying the Functions

This is the part I would prefer feedback on.

First, I split the tree_df into distinct groups based on spcd and region so I can apply the functions that correspond to these distinct groups.

tree_split <- split(tree_df, list(tree_df$  region, tree_df$  spcd)) 

Then, I create an empty data frame to append to.

new_tree <- data.frame() 

Next, (and this is where things get messy) I loop through each group, grab the top left cell that acts as a “key” to get the equation from the func_df and use mapply on each group (with some conditionals to handle NA values).

for (group in tree_split) {     # Get the 'group key'     region <- group$  region[1]     spcd <- group$  spcd[1]      # Get the equation from eqs     eq <- funcs_df$  funcs[which((funcs_df$  spcd == spcd & funcs_df$  region ==            region))]      # Convert func string into actual function     eq <- eq[[1]]     eq <- eval(parse(text=eq))      # Apply the equation to each record in the group     group$  cvts <- mapply(eq, group$  dbh, group$  ht)      # Append to new_tree     new_tree <- rbind(new_tree ,group) } 

Discussion

This results in the desired output with the new cvts outputs according to each function defined in the dataframe:

  spcd region dbh  ht cvts 4  122   OR_E  11  99   22 1  122   OR_W  12 101  245 6  122   OR_W  21  76  517 2  141   OR_E  13 121   48 3  141   OR_W  15 100  325 5  141   OR_W  10  88  188 

I have a few concerns with this approach:

1. The old adage “if you write a for-loop you are doing it wrong” seems to apply here. Is there some way I could reduce this for-loop to some sort of apply or mapply type function?

2. Grabbing the key from a cell (see “# Get the ‘group key'” comment above) seems sloppy. Is there a way to get this ‘group key’ in a more formal fashion?

Other advice is, of course, welcome.