Build a 'types' object

This function builds an object of the class types.

Usage

types(
  x,
  re_drop_line = NULL,
  line_glue = NULL,
  re_cut_area = NULL,
  re_token_splitter = re("[^_\\p{L}\\p{N}\\p{M}'-]+"),
  re_token_extractor = re("[_\\p{L}\\p{N}\\p{M}'-]+"),
  re_drop_token = NULL,
  re_token_transf_in = NULL,
  token_transf_out = NULL,
  token_to_lower = TRUE,
  perl = TRUE,
  blocksize = 300,
  verbose = FALSE,
  show_dots = FALSE,
  dot_blocksize = 10,
  file_encoding = "UTF-8",
  ngram_size = NULL,
  ngram_sep = "_",
  ngram_n_open = 0,
  ngram_open = "[]",
  as_text = FALSE
)

Arguments

x

Either a list of filenames of the corpus files (if as_text is TRUE) or the actual text of the corpus (if as_text is FALSE).

If as_text is TRUE and the length of the vector x is higher than one, then each item in x is treated as a separate line (or a separate series of lines) in the corpus text. Within each item of x, the character "\\n" is also treated as a line separator.

re_drop_line

NULL or character vector. If NULL, it is ignored. Otherwise, a character vector (assumed to be of length 1) containing a regular expression. Lines in x that contain a match for re_drop_line are treated as not belonging to the corpus and are excluded from the results.

line_glue

NULL or character vector. If NULL, it is ignored. Otherwise, all lines in a corpus file (or in x, if as_text is TRUE), are glued together in one character vector of length 1, with the string line_glue pasted in between consecutive lines. The value of line_glue can also be equal to the empty string "". The 'line glue' operation is conducted immediately after the 'drop line' operation.

re_cut_area

NULL or character vector. If NULL, it is ignored. Otherwise, all matches in a corpus file (or in x, if as_text is TRUE), are 'cut out' of the text prior to the identification of the tokens in the text (and are therefore not taken into account when identifying the tokens). The 'cut area' operation is conducted immediately after the 'line glue' operation.

re_token_splitter

Regular expression or NULL. Regular expression that identifies the locations where lines in the corpus files are split into tokens. (See Details.)

The 'token identification' operation is conducted immediately after the 'cut area' operation.

re_token_extractor

Regular expression that identifies the locations of the actual tokens. This argument is only used if re_token_splitter is NULL. (See Details.)

The 'token identification' operation is conducted immediately after the 'cut area' operation.

re_drop_token

Regular expression or NULL. If NULL, it is ignored. Otherwise, it identifies tokens that are to be excluded from the results. Any token that contains a match for re_drop_token is removed from the results. The 'drop token' operation is conducted immediately after the 'token identification' operation.

re_token_transf_in

Regular expression that identifies areas in the tokens that are to be transformed. This argument works together with the argument token_transf_out.

If both re_token_transf_in and token_transf_out differ from NA, then all matches, in the tokens, for the regular expression re_token_transf_in are replaced with the replacement string token_transf_out.

The 'token transformation' operation is conducted immediately after the 'drop token' operation.

token_transf_out

Replacement string. This argument works together with re_token_transf_in and is ignored if re_token_transf_in is NULL or NA.

token_to_lower

Logical. Whether tokens must be converted to lowercase before returning the result. The 'token to lower' operation is conducted immediately after the 'token transformation' operation.

perl

Logical. Whether the PCRE regular expression flavor is being used in the arguments that contain regular expressions.

blocksize

Number that indicates how many corpus files are read to memory at each individual step' during the steps in the procedure; normally the default value of 300` should not be changed, but when one works with exceptionally small corpus files, it may be worthwhile to use a higher number, and when one works with exceptionally large corpus files, it may be worthwhile to use a lower number.

verbose

IfTRUE, messages are printed to the console to indicate progress.

show_dots, dot_blocksize

If TRUE, dots are printed to the console to indicate progress.

file_encoding

File encoding that is assumed in the corpus files.

ngram_size

Argument in support of ngrams/skipgrams (see also max_skip).

If one wants to identify individual tokens, the value of ngram_size should be NULL or 1. If one wants to retrieve token ngrams/skipgrams, ngram_size should be an integer indicating the size of the ngrams/skipgrams. E.g. 2 for bigrams, or 3 for trigrams, etc.

ngram_sep

Character vector of length 1 containing the string that is used to separate/link tokens in the representation of ngrams/skipgrams in the output of this function.

ngram_n_open

If ngram_size is 2 or higher, and moreover ngram_n_open is a number higher than 0, then ngrams with 'open slots' in them are retrieved. These ngrams with 'open slots' are generalizations of fully lexically specific ngrams (with the generalization being that one or more of the items in the ngram are replaced by a notation that stands for 'any arbitrary token').

For instance, if ngram_size is 4 and ngram_n_open is 1, and if moreover the input contains a 4-gram "it_is_widely_accepted", then the output will contain all modifications of "it_is_widely_accepted" in which one (since ngram_n_open is 1) of the items in this n-gram is replaced by an open slot. The first and the last item inside an ngram are never turned into an open slot; only the items in between are candidates for being turned into open slots. Therefore, in the example, the output will contain "it_[]_widely_accepted" and "it_is_[]_accepted".

As a second example, if ngram_size is 5 and ngram_n_open is 2, and if moreover the input contains a 5-gram "it_is_widely_accepted_that", then the output will contain "it_[]_[]_accepted_that", "it_[]_widely_[]_that", and "it_is_[]_[]_that".

ngram_open

Character string used to represent open slots in ngrams in the output of this function.

as_text

Logical. Whether x is to be interpreted as a character vector containing the actual contents of the corpus (if as_text is TRUE) or as a character vector containing the names of the corpus files (if as_text is FALSE). If if as_text is TRUE, then the arguments blocksize, verbose, show_dots, dot_blocksize, and file_encoding are ignored.

Value

An object of the class types, which is based on a character vector. It has additional attributes and methods such as:

base print(), as_data_frame(), sort() and base::summary() (which returns the number of items and of unique items),
tibble::as_tibble(),
the n_types() getter and the explore() method,
subsetting methods such as keep_types(), keep_pos(), etc. including [] subsetting (see brackets).

An object of class types can be merged with another by means of types_merge(), written to file with write_types() and read from file with write_types().

Details

The actual token identification is either based on the re_token_splitter argument, a regular expression that identifies the areas between the tokens, or on re_token_extractor, a regular expression that identifies the area that are the tokens. The first mechanism is the default mechanism: the argument re_token_extractor is only used if re_token_splitter is NULL. Currently the implementation of re_token_extractor is a lot less time-efficient than that of re_token_splitter.

Examples

toy_corpus <- "Once upon a time there was a tiny toy corpus.
It consisted of three sentences. And it lived happily ever after."
(tps <- types(toy_corpus, as_text = TRUE))
#> Type collection of length 19
#>         type
#>    ---------
#>  1         a
#>  2        it
#>  3     after
#>  4       and
#>  5 consisted
#>  6    corpus
#>  7      ever
#>  8   happily
#>  9     lived
#> 10        of
#> 11      once
#> 12 sentences
#> 13     there
#> 14     three
#> 15      time
#> 16      tiny
#> 17       toy
#> 18      upon
#> 19       was
print(tps)
#> Type collection of length 19
#>         type
#>    ---------
#>  1         a
#>  2        it
#>  3     after
#>  4       and
#>  5 consisted
#>  6    corpus
#>  7      ever
#>  8   happily
#>  9     lived
#> 10        of
#> 11      once
#> 12 sentences
#> 13     there
#> 14     three
#> 15      time
#> 16      tiny
#> 17       toy
#> 18      upon
#> 19       was

as.data.frame(tps)
#>         type
#> 1          a
#> 2         it
#> 3      after
#> 4        and
#> 5  consisted
#> 6     corpus
#> 7       ever
#> 8    happily
#> 9      lived
#> 10        of
#> 11      once
#> 12 sentences
#> 13     there
#> 14     three
#> 15      time
#> 16      tiny
#> 17       toy
#> 18      upon
#> 19       was
as_tibble(tps)
#> # A tibble: 19 × 1
#>    type     
#>    <types>  
#>  1 a        
#>  2 it       
#>  3 after    
#>  4 and      
#>  5 consisted
#>  6 corpus   
#>  7 ever     
#>  8 happily  
#>  9 lived    
#> 10 of       
#> 11 once     
#> 12 sentences
#> 13 there    
#> 14 three    
#> 15 time     
#> 16 tiny     
#> 17 toy      
#> 18 upon     
#> 19 was      

sort(tps)
#> Type collection of length 19
#>         type
#>    ---------
#>  1         a
#>  2     after
#>  3       and
#>  4 consisted
#>  5    corpus
#>  6      ever
#>  7   happily
#>  8        it
#>  9     lived
#> 10        of
#> 11      once
#> 12 sentences
#> 13     there
#> 14     three
#> 15      time
#> 16      tiny
#> 17       toy
#> 18      upon
#> 19       was
sort(tps, decreasing = TRUE)
#> Type collection of length 19
#>         type
#>    ---------
#>  1       was
#>  2      upon
#>  3       toy
#>  4      tiny
#>  5      time
#>  6     three
#>  7     there
#>  8 sentences
#>  9      once
#> 10        of
#> 11     lived
#> 12        it
#> 13   happily
#> 14      ever
#> 15    corpus
#> 16 consisted
#> 17       and
#> 18     after
#> 19         a

Usage

Arguments

Value

Details

See also

Examples