There are two vignettes in this package that guide you through the process of using this software.
Currently, testing covers this proportion of lines of code
Your function can have any name you wish. There are, however, a few criteria you should adhere to:
Your function must return a list as a result. This list needs to contain the following elements if you wish to use the inbuilt diagnostics tools (recognition rate, etc. although these will need be adapted). Should you wish to use the slicer function (i.e. expect more than one pattern per sample) you need to make sure to include point 4) in your output list.
EXT=extrema as passed to your function
RESULT=Logical. TRUE if any pattern is found in the sample, FALSE otherwise. Depending on whether your algorithm looks for more than one type of pattern, this needs to be programmed. If TRUE, slicer counts the result as a find.
The remaining arguments and list entries in the result need not confirm to any standard.
Below is an example of a skeleton recognition function for your own patterns. ITALIC are optional but recommended elements.
custompatrec <- function(extrema, extvals, extpos, arguments){
#room for your code
result <- list(EXT=extrema, EXV=extvals, EXP=extpos, recog, RESULT=logical)
#recog is your own output. I recommend a separate list
#element per type of pattern your function recognises
return(result)
}
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