Get or set package options for quanteda

Get or set global options affecting functions across quanteda.

quanteda_options(..., reset = FALSE, initialize = FALSE)

Arguments

...	options to be set, as key-value pair, same as options(). This may be a list of valid key-value pairs, useful for setting a group of options at once (see examples).
reset	logical; if TRUE, reset all quanteda options to their default values
initialize	logical; if TRUE, reset only the quanteda options that are not already defined. Used for setting initial values when some have been defined previously, such as in .Rprofile.

Value

When called using a key = value pair (where key can be a label or quoted character name)), the option is set and TRUE is returned invisibly.

When called with no arguments, a named list of the package options is returned.

When called with reset = TRUE as an argument, all arguments are options are reset to their default values, and TRUE is returned invisibly.

Details

Currently available options are:

verbose

logical; if TRUE then use this as the default for all functions with a verbose argument

threads

integer; specifies the number of threads to use in parallelized functions

print_dfm_max_ndoc

integer; specifies the number of documents to display when using the defaults for printing a dfm

print_dfm_max_nfeat

integer; specifies the number of features to display when using the defaults for printing a dfm

base_docname

character; stem name for documents that are unnamed when a corpus, tokens, or dfm are created or when a dfm is converted from another object

base_featname

character; stem name for features that are unnamed when they are added, for whatever reason, to a dfm through an operation that adds features

base_compname

character; stem name for components that are created by matrix factorization

language_stemmer

character; language option for char_wordstem, tokens_wordstem, and dfm_wordstem

pattern_hashtag, pattern_username

character; regex patterns for (social media) hashtags and usernames respectively, used to avoid segmenting these in the default internal "word" tokenizer

tokens_block_size

integer; specifies the number of documents to be tokenized at a time in blocked tokenization. When the number is large, tokenization becomes faster but also memory-intensive.

Examples

(opt <- quanteda_options())
#> $threads
#> [1] 2
#> 
#> $verbose
#> [1] FALSE
#> 
#> $print_dfm_max_ndoc
#> [1] 6
#> 
#> $print_dfm_max_nfeat
#> [1] 10
#> 
#> $print_dfm_summary
#> [1] TRUE
#> 
#> $print_corpus_max_ndoc
#> [1] 6
#> 
#> $print_corpus_max_nchar
#> [1] 60
#> 
#> $print_corpus_summary
#> [1] TRUE
#> 
#> $print_tokens_max_ndoc
#> [1] 6
#> 
#> $print_tokens_max_ntoken
#> [1] 12
#> 
#> $print_tokens_summary
#> [1] TRUE
#> 
#> $print_dictionary_max_nkey
#> [1] 6
#> 
#> $print_dictionary_max_nval
#> [1] 20
#> 
#> $print_dictionary_summary
#> [1] TRUE
#> 
#> $base_docname
#> [1] "text"
#> 
#> $base_featname
#> [1] "feat"
#> 
#> $base_compname
#> [1] "comp"
#> 
#> $language_stemmer
#> [1] "english"
#> 
#> $pattern_hashtag
#> [1] "#\\w+#?"
#> 
#> $pattern_username
#> [1] "@[a-zA-Z0-9_]+"
#> 
#> $tokens_block_size
#> [1] 10000
#> 
# \donttest{
quanteda_options(verbose = TRUE)
quanteda_options("verbose" = FALSE)
quanteda_options("threads")
#> [1] 2
quanteda_options(print_dfm_max_ndoc = 50L)
# reset to defaults
quanteda_options(reset = TRUE)
# reset to saved options
quanteda_options(opt)
# }