ieegio (version 0.0.4)

low-level-read-write: Low-level file read and write

Description

Interfaces to read from or write to files with common formats.

Usage

io_read_fst(
  con,
  method = c("proxy", "data_table", "data_frame", "header_only"),
  ...,
  old_format = FALSE
)
io_write_fst(x, con, compress = 50, ...)
io_read_ini(con, ...)
io_read_json(con, ...)
io_write_json(
  x,
  con = stdout(),
  ...,
  digits = ceiling(-log10(.Machine$double.eps)),
  pretty = TRUE,
  serialize = TRUE
)
io_read_mat(
  con,
  method = c("auto", "R.matlab", "pymatreader", "mat73"),
  verbose = TRUE,
  on_convert_error = c("warning", "error", "ignore"),
  ...
)
io_write_mat(x, con, method = c("R.matlab", "scipy"), ...)
io_read_yaml(con, ...)
io_write_yaml(x, con, ..., sorted = FALSE)

Value

The reader functions returns the data extracted from files, mostly as R objects, with few exceptions on some 'Matlab' files. When reading a 'Matlab' file requires using 'Python' modules, io_read_mat will try its best effort to convert 'Python' objects to R. However, such conversion might fail. In this case, the result might partially contain 'Python' objects with warnings.

Arguments

con

connection or file

method

method to read table. For 'fst', the choices are

'proxy'

do not read data to memory, query the table when needed;

'data_table'

read as data.table;

'data_frame'

read as data.frame;

'header_only'

read 'fst' table header.

For 'mat', the choices are

'auto'

automatically try the native option, and then 'pymatreader' if fails;

'R.matlab'

use the native method (provided by readMat); only support 'MAT 5.0' format;

'pymatreader'

use 'Python' library 'pymatreader';

'mat73'

use 'Python' library 'mat73'.

...

passed to internal function calls

old_format

see fst

x

data to write to disk

compress

compress level from 0 to 100; default is 50

digits, pretty

for writing numeric values to 'json' format

serialize

set to TRUE to serialize the data to 'json' format (with the data types, default); or FALSE to save the values without types

verbose

whether to print out the process

on_convert_error

for reading 'mat' files with 'Python' modules, the results will be converted to R objects in the end. Not all objects can be converted. This input defines the behavior when the conversion fails; choices are "error", "warning", or "ignore"

sorted

whether to sort the list; default is FALSE

Examples

# ---- fst ----------------------------------------------------------------


f <- tempfile(fileext = ".fst")
x <- data.frame(
  a = 1:10,
  b = rnorm(10),
  c = letters[1:10]
)

io_write_fst(x, con = f)

# default reads in proxy
io_read_fst(f)

# load as data.table
io_read_fst(f, "data_table")

# load as data.frame
io_read_fst(f, "data_frame")

# get header
io_read_fst(f, "header_only")

# clean up
unlink(f)



# ---- json ---------------------------------------------------------------
f <- tempfile(fileext = ".json")

x <- list(a = 1L, b = 2.3, c = "a", d = 1+1i)

# default is serialize
io_write_json(x, f)

io_read_json(f)

cat(readLines(f), sep = "\n")

# just values
io_write_json(x, f, serialize = FALSE, pretty = FALSE)

io_read_json(f)

cat(readLines(f), sep = "\n")

# clean up
unlink(f)



# ---- Matlab .mat --------------------------------------------------------

if (FALSE) {

f <- tempfile(fileext = ".mat")

x <- list(a = 1L, b = 2.3, c = "a", d = 1+1i)

# save as MAT 5.0
io_write_mat(x, f)

io_read_mat(f)

# require setting up Python environment

io_read_mat(f, method = "pymatreader")

# MAT 7.3 example
sample_data <- ieegio_sample_data("mat_v73.mat")
io_read_mat(sample_data)

# clean up
unlink(f)

}



# ---- yaml ---------------------------------------------------------------

f <- tempfile(fileext = ".yaml")

x <- list(a = 1L, b = 2.3, c = "a")
io_write_yaml(x, f)

io_read_yaml(f)

# clean up
unlink(f)