Dear Ravi,
I have uploaded on GitHub a version which handles also constant values
instead of functions.
Regarding named arguments: this is actually handled automatically as well:
eval.by.formula((x > 5 & x %% 2) ~ (x <= 5) ~ ., FUN, y=2, x)
# [1] 1 4 9 16 25 6 14 8 18 10
eval.by.formula((x > 5 & x %% 2) ~ (x <= 5) ~ ., FUN, x=2, x)
# [1] 4 4 4 4 4 2 14 2 18 2
eval.by.formula((x > 5 & x %% 2) ~ (x <= 5) ~ ., list(FUN[[1]], 0, 1),
y=2, x)
# [1] 0 0 0 0 0 1 14 1 18 1
But it still needs proper testing and maybe optimization: it is possible
to run sapply on the filtered sequence (but I did not want to break
anything now).
Sincerely,
Leonard
On 10/9/2021 9:26 PM, Leonard Mada wrote:
Dear Ravi,
I wrote a small replacement for ifelse() which avoids such unnecessary
evaluations (it bothered me a few times as well - so I decided to try
a small replacement).
### Example:
x = 1:10
FUN = list();
FUN[[1]] = function(x, y) x*y;
FUN[[2]] = function(x, y) x^2;
FUN[[3]] = function(x, y) x;
# lets run multiple conditions
# eval.by.formula(conditions, FUN.list, ... (arguments for FUN) );
eval.by.formula((x > 5 & x %% 2) ~ (x <= 5) ~ ., FUN, x, x-1)
# Example 2
eval.by.formula((x > 5 & x %% 2) ~ (x <= 5) ~ ., FUN, 2, x)
### Disclaimer:
- NOT properly tested;
The code for the function is below. Maybe someone can experiment with
the code and improve it further. There are a few issues / open
questions, like:
1.) Best Name: eval.by.formula, ifelse.formula, ...?
2.) Named arguments: not yet;
3.) Fixed values inside FUN.list
4.) Format of expression for conditions:
expression(cond1, cond2, cond3) vs cond1 ~ cond2 ~ cond3 ???
5.) Code efficiency
- some tests on large data sets & optimizations are warranted;
Sincerely,
Leonard
=======
The latest code is on Github:
https://github.com/discoleo/R/blob/master/Stat/Tools.Formulas.R
[...]
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