Read functions as text and use for plotting - r

Question

I have a set of 500 equations listed in a single column of a .csv file. The equations are written as text like this (for example):
15+6.2*A-4.3*B+3.7*C-7.9*B*C+2*D^2
(this is the "right" side of the equation, which equals "y", but the text "y=" does not appear in the .csv file)
These are general linear models that have been written to a .csv file by someone else. Not all models have the same number of variables.
I would like to read these functions into R and format them in a way that will allow for using them to (iteratively) make simple line plots (one for each n = 500 models) of "y" across a range of values for A (shown on the x-axis), given values of B, C, and D.
Does anyone have any suggestions for how to do this?

Answer 1

I thought of something based on this [post][1], it is not the best solution, but it seems to work.
Equations
Created two equations for an example
models <- c("15+6.2*A-4.3*B+3.7*C-7.9*B*C+2*D^2","50+6.2*A-4.3*B+3.7*C-7.9*B*C+2*D^2")
models_names <- c("model1","model2")
Data
Random data as an example
data <-
tibble(
A = rnorm(100),
B = rnorm(100),
C = rnorm(100),
D = rnorm(100)
)
Function
Then a created a function that uses those text equations and apply as function returning the values
text_model <- function(formula){
eval(parse(text = paste('f <- function(A,B,C,D) { return(' , formula , ')}', sep='')))
out <- f(data$A,data$B,data$C,data$D)
return(out)
}
Applied equations
Finally, I apply each equation for the data, binding both.
data %>%
bind_cols(
map(.x = models,.f = text_model) %>%
set_names(models_names) %>%
bind_rows(.id = "model")
)
# A tibble: 100 x 6
A B C D model1 model2
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 -0.0633 1.18 -0.409 2.01 9.52 54.9
2 -0.00207 1.35 1.28 1.59 9.16 40.3
3 0.798 -0.141 1.58 -0.123 20.6 63.2
4 -0.162 -0.0795 0.408 0.663 14.3 52.0
5 -1.11 0.788 -1.37 1.20 4.71 46.0
6 2.80 1.84 -0.850 0.161 24.4 68.7
7 1.03 0.550 0.907 -1.92 19.0 60.8
8 0.515 -0.179 -0.980 0.0437 19.0 48.9
9 -0.353 0.0643 1.39 1.30 12.5 55.3
10 -0.427 -1.01 -1.11 -0.547 16.7 39.3
# ... with 90 more rows