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For data.frames with more than 200k lines, there is an important opportunity to improve the speed in the calculation of this function, which is the core of calculate_covariate_fit() function.
Well, after that calculation there is another calculation based on table() that also can be improved significantly by using a data.table calculation. If you accept to add data.tabledependency in shifter I will open a PR with these calculations. with these changes, I was able to pass from some minutes calculations in my comparison data.frame to barely 30 secs.
Thanks,
Carlos.
The text was updated successfully, but these errors were encountered:
Hi Przemek,
For data.frames with more than 200k lines, there is an important opportunity to improve the speed in the calculation of this function, which is the core of
calculate_covariate_fit()
function.Instead of using
rank()
here:It would improve a lot if you use
frank()
fromdata.table
package.Well, after that calculation there is another calculation based on
table()
that also can be improved significantly by using adata.table
calculation. If you accept to adddata.table
dependency inshifter
I will open a PR with these calculations. with these changes, I was able to pass from some minutes calculations in my comparison data.frame to barely 30 secs.Thanks,
Carlos.
The text was updated successfully, but these errors were encountered: