PsychWordVec (version 2025.3)

data_transform: Transform plain text of word vectors into wordvec (data.table) or embed (matrix), saved in a compressed ".RData" file.

Description

Transform plain text of word vectors into wordvec (data.table) or embed (matrix), saved in a compressed ".RData" file.

Speed: In total (preprocess + compress + save), it can process about 30000 words/min with the slowest settings (compress="xz", compress.level=9) on a modern computer (HP ProBook 450, Windows 11, Intel i7-1165G7 CPU, 32GB RAM).

Usage

data_transform(
  file.load,
  file.save,
  as = c("wordvec", "embed"),
  sep = " ",
  header = "auto",
  encoding = "auto",
  compress = "bzip2",
  compress.level = 9,
  verbose = TRUE
)

Value

A wordvec (data.table) or embed (matrix).

Arguments

file.load

File name of raw text (must be plain text).

Data must be in this format (values separated by sep):

cat 0.001 0.002 0.003 0.004 0.005 ... 0.300

dog 0.301 0.302 0.303 0.304 0.305 ... 0.600

file.save

File name of to-be-saved R data (must be .RData).

as

Transform the text to which R object? wordvec (data.table) or embed (matrix). Defaults to wordvec.

sep

Column separator. Defaults to " ".

header

Is the 1st row a header (e.g., meta-information such as "2000000 300")? Defaults to "auto", which automatically determines whether there is a header. If TRUE, then the 1st row will be dropped.

encoding

File encoding. Defaults to "auto" (using vroom::vroom_lines() to fast read the file). If specified to any other value (e.g., "UTF-8"), then it uses readLines() to read the file, which is much slower than vroom.

compress

Compression method for the saved file. Defaults to "bzip2".

Options include:

• 1 or "gzip": modest file size (fastest)

• 2 or "bzip2": small file size (fast)

• 3 or "xz": minimized file size (slow)

compress.level

Compression level from 0 (none) to 9 (maximal compression for minimal file size). Defaults to 9.

verbose

Print information to the console? Defaults to TRUE.

Download

Download pre-trained word vectors data (.RData): https://psychbruce.github.io/WordVector_RData.pdf

See Also

as_wordvec / as_embed

load_wordvec / load_embed

normalize

data_wordvec_subset

Examples

if (FALSE) {
# please first manually download plain text data of word vectors
# e.g., from: https://fasttext.cc/docs/en/crawl-vectors.html

# the text file must be on your disk
# the following code cannot run unless you have the file
library(bruceR)
set.wd()
data_transform(file.load="cc.zh.300.vec",   # plain text file
               file.save="cc.zh.300.vec.RData",  # RData file
               header=TRUE, compress="xz")  # of minimal size
}