Package 'grumpy'

Convert raw bytes to an R array based on the specified data type information

Description

This is a replacement for readBin() that can handle the various data types and endianness specified in the .npy file header.

Usage

convert_bytes_to_array(bytes, what, shape, size, endian)

Arguments

bytes	A raw vector containing the bytes to convert
what	A character specifying the base type to convert to (e.g., "float", "int", "string", etc.)
shape	A numeric vector with desired shape of the output array
size	A numeric value with the number of bytes per element for the specified type
endian	The endianness of the data ("little", "big", or NA for single-byte types)

Value

An R array containing the converted data, with the specified shape and data type.

Examples

x <- matrix(c(3L, 6L, 2L, 1L, 12L, 0L), nrow = 2, ncol = 3)
x

y <- writeBin(c(x), raw()) |>
  convert_bytes_to_array(
     "int",
     shape = c(2L, 3L),
     size = 4L,
     endian = "little"
  )
y
dim(y)
is.array(y)
storage.mode(y)

---

Parse a NumPy Array-protocol type string

Description

Parse a NumPy Array-protocol type string

Usage

parse_npy_datatype(descr)

Arguments

descr

A NumPy dtype description string, or a list of such strings for structured dtypes

Details

If a list is passed to descr, each element can be of length 1, or of length 2 in which case the first element corresponds to the name of the field and the second to its dtype.

Value

A list containing the parsed data type information, including the base type, the number of bytes, and the endianness

Examples

parse_npy_datatype(">i8")
parse_npy_datatype("|b1")
# A structured datatype where each element has 3 components, all integers,
# named "r", "g" and "b".
parse_npy_datatype(list(c("r", "<i8"), c("g", "<i8"), c("b", "<i8")))

---

Read a .npy file

Description

Read a .npy file

Usage

read_npy(file, lazy = FALSE, ...)

Arguments

file	Path to the .npy file
lazy	If TRUE, and file is a path (not a connection), the data payload is memory-mapped rather than read into memory upfront via readBin(). This limits the number of copies in memory when the npy file contains types native to R. Requires a POSIX platform; ignored (with a warning) otherwise. Defaults to FALSE.
...	Ignored. Reserved for future use.

Value

An array containing the data from the .npy file

Examples

# Array of integers. NumPy "<i4" dtype
read_npy(
  system.file("extdata", "test_int32.npy", package = "grumpy")
)

# Array of logicals. NumPy "|b1" dtype
read_npy(
  system.file("extdata", "test_bool.npy", package = "grumpy")
)

# Array of numerics. NumPy "<f8" dtype
read_npy(
  system.file("extdata", "test_float64.npy", package = "grumpy")
)

# Array of strings. NumPy "<U" dtype
read_npy(
  system.file("extdata", "test_str_unicode.npy", package = "grumpy")
)

# "Array" of lists. Numpy structured dtype
read_npy(
  system.file("extdata", "test_structured.npy", package = "grumpy")
)

---

Read a .npz file

Description

Read a .npz file

Usage

read_npz(file, arrays = NULL)

Arguments

file	Path to the .npz file
arrays	Optional character vector of array names or numeric vector of indices to read from the .npz file. If NULL (the default), all arrays are read.

Value

A named list of arrays containing the data from the .npz file

Examples

read_npz(
  system.file("extdata", "test.npz", package = "grumpy")
)

read_npz(
  system.file("extdata", "test.npz", package = "grumpy"),
  arrays = "x"
)

---