str_match_all_variable: All matches from one subject, variable argument syntax
In namedCapture: Named Capture Regular Expressions

Description Usage Arguments Value Author(s) Examples

Extract all matches of a named capture regex pattern from one subject string. It is for the common case of extracting all matches of a regex from a single multi-line text file subject; for other subjects, str_match_all_named can be used to find all matches. This function uses variable_args_list to analyze the arguments and str_match_all_named to perform the matching.

1 2	str_match_all_variable(subject.vec, ...)

subject.vec

The subject character vector. We treat elements of subject as separate lines; i.e. we do the regex matching on the single subject string formed by pasting together the subject character vector using newlines as the separator.

...

name1=pattern1, fun1, etc, which creates the regex (?<name1>pattern1) and uses fun1 for conversion. These other arguments specify the regular expression pattern and must be character/function/list. All patterns must be character vectors of length 1. If the pattern is a named argument in R, we will add a named capture group (?P<name>pattern) in the regex. All patterns are pasted together to obtain the final pattern used for matching. Each named pattern may be followed by at most one function which is used to convert the previous named pattern. Lists are parsed recursively for convenience.

matrix or data.frame with one row for each match, and one column for each named group, see str_match_all_named for details.

Toby Dylan Hocking

chr.pos.vec <- c(
  "chr10:213,054,000-213,055,000",
  "chrM:111,000-222,000",
  "this will not match",
  NA, # neither will this.
  "chr1:110-111 chr2:220-222") # two possible matches.
keep.digits <- function(x)as.integer(gsub("[^0-9]", "", x))
## str_match_all_variable treats elements of subject as separate
## lines (and ignores NA elements). Named arguments are used to
## create named capture groups, and conversion functions such as
## keep.digits are used to convert the previously named group.
int.pattern <- list("[0-9,]+", keep.digits)
(match.df <- namedCapture::str_match_all_variable(
  chr.pos.vec,
  name="chr.*?",
  ":",
  chromStart=int.pattern,
  "-",
  chromEnd=int.pattern))
str(match.df)
match.df["chr1", "chromEnd"]