closure_write: Write CLOSURE results to disk (and read them back in)

In unsum: Reconstruct Raw Data from Summary Statistics

Write CLOSURE results to disk (and read them back in)

Description

You can use closure_write() to save the results of closure_generate() on your computer. A message will show the exact location.

The data are saved in a new folder as four separate files, one for each tibble in closure_generate()'s output. The folder is named after the parameters of closure_generate().

closure_read() is the opposite: it reads those files back into R, recreating the original CLOSURE list. This is useful for later analyses if you don't want to re-run a lengthy closure_generate() call.

Usage

closure_write(data, path)

closure_read(path)

Arguments

data	List returned by closure_generate().
path	String (length 1). File path where closure_write() will create a new folder with the results. Set it to "." to choose the current working directory. For closure_read(), the path to an existing folder with results.

Details

closure_write() saves the first three tibbles as CSVs, but the "results" tibble becomes a Parquet file. This is much faster and takes up far less disk space — roughly 1% of a CSV file with the same data. Speed and disk space can be relevant with large result sets.

Use closure_read() to recreate the CLOSURE list from the folder. One of the reasons why it is convenient is that opening a Parquet file requires a special reader. For a more general tool, see nanoparquet::read_parquet().

Value

closure_write() returns the path to the new folder it created, closure_read() returns a list.

Folder name

The new folder's name should be sufficient to recreate its CLOSURE results. Dashes separate values, underscores replace decimal periods. For example:

CLOSURE-3_5-1_0-90-1-5-up_or_down-5

The order is the same as in closure_generate():

  closure_generate(
    mean = "3.5",
    sd = "1.0",
    n = 90,
    scale_min = 1,
    scale_max = 5,
    rounding = "up_or_down",  # default
    threshold = 5             # default
  )
 

Examples

data <- closure_generate(
  mean = "2.7",
  sd = "0.6",
  n = 45,
  scale_min = 1,
  scale_max = 5
)

# You should write to a real folder instead;
# or just leave `path` unspecified. I use a
# fake folder just for this example.
path_new_folder <- closure_write(data, path = tempdir())

# In a later session, conveniently read the files
# back into R. This returns the original list,
# identical except for floating-point error.
closure_read(path_new_folder)

unsum documentation built on June 20, 2025, 1:08 a.m.