//! Contains the compression attribute definition
//! and methods to compress and decompress data.
// private modules make non-breaking changes easier
mod zip;
mod rle;
mod piz;
mod pxr24;
mod b44;
use std::convert::TryInto;
use std::mem::size_of;
use half::f16;
use crate::meta::attribute::{IntegerBounds, SampleType, ChannelList};
use crate::error::{Result, Error, usize_to_i32};
use crate::meta::header::Header;
/// A byte vector.
pub type ByteVec = Vec<u8>;
/// A byte slice.
pub type Bytes<'s> = &'s [u8];
/// Specifies which compression method to use.
/// Use uncompressed data for fastest loading and writing speeds.
/// Use RLE compression for fast loading and writing with slight memory savings.
/// Use ZIP compression for slow processing with large memory savings.
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum Compression {
/// Store uncompressed values.
/// Produces large files that can be read and written very quickly.
/// Consider using RLE instead, as it provides some compression with almost equivalent speed.
Uncompressed,
/// Produces slightly smaller files
/// that can still be read and written rather quickly.
/// The compressed file size is usually between 60 and 75 percent of the uncompressed size.
/// Works best for images with large flat areas, such as masks and abstract graphics.
/// This compression method is lossless.
RLE,
/// Uses ZIP compression to compress each line. Slowly produces small images
/// which can be read with moderate speed. This compression method is lossless.
/// Might be slightly faster but larger than `ZIP16´.
ZIP1, // TODO ZIP { individual_lines: bool, compression_level: Option<u8> } // TODO specify zip compression level?
/// Uses ZIP compression to compress blocks of 16 lines. Slowly produces small images
/// which can be read with moderate speed. This compression method is lossless.
/// Might be slightly slower but smaller than `ZIP1´.
ZIP16, // TODO collapse with ZIP1
/// PIZ compression works well for noisy and natural images. Works better with larger tiles.
/// Only supported for flat images, but not for deep data.
/// This compression method is lossless.
// A wavelet transform is applied to the pixel data, and the result is Huffman-
// encoded. This scheme tends to provide the best compression ratio for the types of
// images that are typically processed at Industrial Light & Magic. Files are
// compressed and decompressed at roughly the same speed. For photographic
// images with film grain, the files are reduced to between 35 and 55 percent of their
// uncompressed size.
// PIZ compression works well for scan-line based files, and also for tiled files with
// large tiles, but small tiles do not shrink much. (PIZ-compressed data start with a
// relatively long header; if the input to the compressor is short, adding the header
// tends to offset any size reduction of the input.)
PIZ,
/// Like `ZIP1`, but reduces precision of `f32` images to `f24`.
/// Therefore, this is lossless compression for `f16` and `u32` data, lossy compression for `f32` data.
/// This compression method works well for depth
/// buffers and similar images, where the possible range of values is very large, but
/// where full 32-bit floating-point accuracy is not necessary. Rounding improves
/// compression significantly by eliminating the pixels' 8 least significant bits, which
/// tend to be very noisy, and therefore difficult to compress.
/// This produces really small image files. Only supported for flat images, not for deep data.
// After reducing 32-bit floating-point data to 24 bits by rounding (while leaving 16-bit
// floating-point data unchanged), differences between horizontally adjacent pixels
// are compressed with zlib, similar to ZIP. PXR24 compression preserves image
// channels of type HALF and UINT exactly, but the relative error of FLOAT data
// increases to about ???.
PXR24, // TODO specify zip compression level?
/// This is a lossy compression method for f16 images.
/// It's the predecessor of the `B44A` compression,
/// which has improved compression rates for uniformly colored areas.
/// You should probably use `B44A` instead of the plain `B44`.
///
/// Only supported for flat images, not for deep data.
// lossy 4-by-4 pixel block compression,
// flat fields are compressed more
// Channels of type HALF are split into blocks of four by four pixels or 32 bytes. Each
// block is then packed into 14 bytes, reducing the data to 44 percent of their
// uncompressed size. When B44 compression is applied to RGB images in
// combination with luminance/chroma encoding (see below), the size of the
// compressed pixels is about 22 percent of the size of the original RGB data.
// Channels of type UINT or FLOAT are not compressed.
// Decoding is fast enough to allow real-time playback of B44-compressed OpenEXR
// image sequences on commodity hardware.
// The size of a B44-compressed file depends on the number of pixels in the image,
// but not on the data in the pixels. All images with the same resolution and the same
// set of channels have the same size. This can be advantageous for systems that
// support real-time playback of image sequences; the predictable file size makes it
// easier to allocate space on storage media efficiently.
// B44 compression is only supported for flat images.
B44, // TODO B44 { optimize_uniform_areas: bool }
/// This is a lossy compression method for f16 images.
/// All f32 and u32 channels will be stored without compression.
/// All the f16 pixels are divided into 4x4 blocks.
/// Each block is then compressed as a whole.
///
/// The 32 bytes of a block will require only ~14 bytes after compression,
/// independent of the actual pixel contents. With chroma subsampling,
/// a block will be compressed to ~7 bytes.
/// Uniformly colored blocks will be compressed to ~3 bytes.
///
/// The 512 bytes of an f32 block will not be compressed at all.
///
/// Should be fast enough for realtime playback.
/// Only supported for flat images, not for deep data.
B44A, // TODO collapse with B44
/// __This lossy compression is not yet supported by this implementation.__
// lossy DCT based compression, in blocks
// of 32 scanlines. More efficient for partial buffer access.
DWAA(Option<f32>), // TODO does this have a default value? make this non optional? default Compression Level setting is 45.0
/// __This lossy compression is not yet supported by this implementation.__
// lossy DCT based compression, in blocks
// of 256 scanlines. More efficient space
// wise and faster to decode full frames
// than DWAA_COMPRESSION.
DWAB(Option<f32>), // TODO collapse with B44. default Compression Level setting is 45.0
}
impl std::fmt::Display for Compression {
fn fmt(&self, formatter: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
write!(formatter, "{} compression", match self {
Compression::Uncompressed => "no",
Compression::RLE => "rle",
Compression::ZIP1 => "zip line",
Compression::ZIP16 => "zip block",
Compression::B44 => "b44",
Compression::B44A => "b44a",
Compression::DWAA(_) => "dwaa",
Compression::DWAB(_) => "dwab",
Compression::PIZ => "piz",
Compression::PXR24 => "pxr24",
})
}
}
impl Compression {
/// Compress the image section of bytes.
pub fn compress_image_section(self, header: &Header, uncompressed_native_endian: ByteVec, pixel_section: IntegerBounds) -> Result<ByteVec> {
let max_tile_size = header.max_block_pixel_size();
assert!(pixel_section.validate(Some(max_tile_size)).is_ok(), "decompress tile coordinate bug");
if header.deep { assert!(self.supports_deep_data()) }
use self::Compression::*;
let compressed_little_endian = match self {
Uncompressed => {
return Ok(convert_current_to_little_endian(
uncompressed_native_endian, &header.channels, pixel_section
))
},
// we need to clone here, because we might have to fallback to the uncompressed data later (when compressed data is larger than raw data)
ZIP16 => zip::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section),
ZIP1 => zip::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section),
RLE => rle::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section),
PIZ => piz::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section),
PXR24 => pxr24::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section),
B44 => b44::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section, false),
B44A => b44::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section, true),
_ => return Err(Error::unsupported(format!("yet unimplemented compression method: {}", self)))
};
let compressed_little_endian = compressed_little_endian.map_err(|_|
Error::invalid(format!("pixels cannot be compressed ({})", self))
)?;
if self == Uncompressed || compressed_little_endian.len() < uncompressed_native_endian.len() {
// only write compressed if it actually is smaller than raw
Ok(compressed_little_endian)
}
else {
// if we do not use compression, manually convert uncompressed data
Ok(convert_current_to_little_endian(uncompressed_native_endian, &header.channels, pixel_section))
}
}
/// Decompress the image section of bytes.
pub fn decompress_image_section(self, header: &Header, compressed: ByteVec, pixel_section: IntegerBounds, pedantic: bool) -> Result<ByteVec> {
let max_tile_size = header.max_block_pixel_size();
assert!(pixel_section.validate(Some(max_tile_size)).is_ok(), "decompress tile coordinate bug");
if header.deep { assert!(self.supports_deep_data()) }
let expected_byte_size = pixel_section.size.area() * header.channels.bytes_per_pixel; // FIXME this needs to account for subsampling anywhere
// note: always true where self == Uncompressed
if compressed.len() == expected_byte_size {
// the compressed data was larger than the raw data, so the small raw data has been written
Ok(convert_little_endian_to_current(compressed, &header.channels, pixel_section))
}
else {
use self::Compression::*;
let bytes = match self {
Uncompressed => Ok(convert_little_endian_to_current(compressed, &header.channels, pixel_section)),
ZIP16 => zip::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
ZIP1 => zip::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
RLE => rle::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
PIZ => piz::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
PXR24 => pxr24::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
B44 | B44A => b44::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic),
_ => return Err(Error::unsupported(format!("yet unimplemented compression method: {}", self)))
};
// map all errors to compression errors
let bytes = bytes
.map_err(|decompression_error| match decompression_error {
Error::NotSupported(message) =>
Error::unsupported(format!("yet unimplemented compression special case ({})", message)),
error => Error::invalid(format!(
"compressed {:?} data ({})",
self, error.to_string()
)),
})?;
if bytes.len() != expected_byte_size {
Err(Error::invalid("decompressed data"))
}
else { Ok(bytes) }
}
}
/// For scan line images and deep scan line images, one or more scan lines may be
/// stored together as a scan line block. The number of scan lines per block
/// depends on how the pixel data are compressed.
pub fn scan_lines_per_block(self) -> usize {
use self::Compression::*;
match self {
Uncompressed | RLE | ZIP1 => 1,
ZIP16 | PXR24 => 16,
PIZ | B44 | B44A | DWAA(_) => 32,
DWAB(_) => 256,
}
}
/// Deep data can only be compressed using RLE or ZIP compression.
pub fn supports_deep_data(self) -> bool {
use self::Compression::*;
match self {
Uncompressed | RLE | ZIP1 => true,
_ => false,
}
}
/// Most compression methods will reconstruct the exact pixel bytes,
/// but some might throw away unimportant data for specific types of samples.
pub fn is_lossless_for(self, sample_type: SampleType) -> bool {
use self::Compression::*;
match self {
PXR24 => sample_type != SampleType::F32, // pxr reduces f32 to f24
B44 | B44A => sample_type != SampleType::F16, // b44 only compresses f16 values, others are left uncompressed
Uncompressed | RLE | ZIP1 | ZIP16 | PIZ => true,
DWAB(_) | DWAA(_) => false,
}
}
/// Most compression methods will reconstruct the exact pixel bytes,
/// but some might throw away unimportant data in some cases.
pub fn may_loose_data(self) -> bool {
use self::Compression::*;
match self {
Uncompressed | RLE | ZIP1 | ZIP16 | PIZ => false,
PXR24 | B44 | B44A | DWAB(_) | DWAA(_) => true,
}
}
/// Most compression methods will reconstruct the exact pixel bytes,
/// but some might replace NaN with zeroes.
pub fn supports_nan(self) -> bool {
use self::Compression::*;
match self {
B44 | B44A | DWAB(_) | DWAA(_) => false, // TODO dwa might support it?
_ => true
}
}
}
// see https://github.com/AcademySoftwareFoundation/openexr/blob/6a9f8af6e89547bcd370ae3cec2b12849eee0b54/OpenEXR/IlmImf/ImfMisc.cpp#L1456-L1541
#[allow(unused)] // allows the extra parameters to be unused
fn convert_current_to_little_endian(mut bytes: ByteVec, channels: &ChannelList, rectangle: IntegerBounds) -> ByteVec {
#[cfg(target = "big_endian")]
reverse_block_endianness(&mut byte_vec, channels, rectangle);
bytes
}
#[allow(unused)] // allows the extra parameters to be unused
fn convert_little_endian_to_current(mut bytes: ByteVec, channels: &ChannelList, rectangle: IntegerBounds) -> ByteVec {
#[cfg(target = "big_endian")]
reverse_block_endianness(&mut bytes, channels, rectangle);
bytes
}
#[allow(unused)] // unused when on little endian system
fn reverse_block_endianness(bytes: &mut [u8], channels: &ChannelList, rectangle: IntegerBounds){
let mut remaining_bytes: &mut [u8] = bytes;
for y in rectangle.position.y() .. rectangle.end().y() {
for channel in &channels.list {
let line_is_subsampled = mod_p(y, usize_to_i32(channel.sampling.y())) != 0;
if line_is_subsampled { continue; }
let sample_count = rectangle.size.width() / channel.sampling.x();
match channel.sample_type {
SampleType::F16 => remaining_bytes = chomp_convert_n::<f16>(reverse_2_bytes, remaining_bytes, sample_count),
SampleType::F32 => remaining_bytes = chomp_convert_n::<f32>(reverse_4_bytes, remaining_bytes, sample_count),
SampleType::U32 => remaining_bytes = chomp_convert_n::<u32>(reverse_4_bytes, remaining_bytes, sample_count),
}
}
}
#[inline]
fn chomp_convert_n<T>(convert_single_value: fn(&mut[u8]), mut bytes: &mut [u8], count: usize) -> &mut [u8] {
let type_size = size_of::<T>();
let (line_bytes, rest) = bytes.split_at_mut(count * type_size);
let value_byte_chunks = line_bytes.chunks_exact_mut(type_size);
for value_bytes in value_byte_chunks {
convert_single_value(value_bytes);
}
rest
}
debug_assert!(remaining_bytes.is_empty(), "not all bytes were converted to little endian");
}
#[inline]
fn reverse_2_bytes(bytes: &mut [u8]){
// this code seems like it could be optimized easily by the compiler
let two_bytes: [u8; 2] = bytes.try_into().expect("invalid byte count");
bytes.copy_from_slice(&[two_bytes[1], two_bytes[0]]);
}
#[inline]
fn reverse_4_bytes(bytes: &mut [u8]){
let four_bytes: [u8; 4] = bytes.try_into().expect("invalid byte count");
bytes.copy_from_slice(&[four_bytes[3], four_bytes[2], four_bytes[1], four_bytes[0]]);
}
#[inline]
fn div_p (x: i32, y: i32) -> i32 {
if x >= 0 {
if y >= 0 { x / y }
else { -(x / -y) }
}
else {
if y >= 0 { -((y-1-x) / y) }
else { (-y-1-x) / -y }
}
}
#[inline]
fn mod_p(x: i32, y: i32) -> i32 {
x - y * div_p(x, y)
}
/// A collection of functions used to prepare data for compression.
mod optimize_bytes {
/// Integrate over all differences to the previous value in order to reconstruct sample values.
pub fn differences_to_samples(buffer: &mut [u8]) {
// The naive implementation is very simple:
//
// for index in 1..buffer.len() {
// buffer[index] = (buffer[index - 1] as i32 + buffer[index] as i32 - 128) as u8;
// }
//
// But we process elements in pairs to take advantage of instruction-level parallelism.
// When computations within a pair do not depend on each other, they can be processed in parallel.
// Since this function is responsible for a very large chunk of execution time,
// this tweak alone improves decoding performance of RLE images by 20%.
if let Some(first) = buffer.get(0) {
let mut previous = *first as i16;
for chunk in &mut buffer[1..].chunks_exact_mut(2) {
// no bounds checks here due to indices and chunk size being constant
let diff0 = chunk[0] as i16;
let diff1 = chunk[1] as i16;
// these two computations do not depend on each other, unlike in the naive version,
// so they can be executed by the CPU in parallel via instruction-level parallelism
let sample0 = (previous + diff0 - 128) as u8;
let sample1 = (previous + diff0 + diff1 - 128 * 2) as u8;
chunk[0] = sample0;
chunk[1] = sample1;
previous = sample1 as i16;
}
// handle the remaining element at the end not processed by the loop over pairs, if present
for elem in &mut buffer[1..].chunks_exact_mut(2).into_remainder().iter_mut() {
let sample = (previous + *elem as i16 - 128) as u8;
*elem = sample;
previous = sample as i16;
}
}
}
/// Derive over all values in order to produce differences to the previous value.
pub fn samples_to_differences(buffer: &mut [u8]){
// naive version:
// for index in (1..buffer.len()).rev() {
// buffer[index] = (buffer[index] as i32 - buffer[index - 1] as i32 + 128) as u8;
// }
//
// But we process elements in batches to take advantage of autovectorization.
// If the target platform has no vector instructions (e.g. 32-bit ARM without `-C target-cpu=native`)
// this will instead take advantage of instruction-level parallelism.
if let Some(first) = buffer.get(0) {
let mut previous = *first as i16;
// Chunk size is 16 because we process bytes (8 bits),
// and 8*16 = 128 bits is the size of a typical SIMD register.
// Even WASM has 128-bit SIMD registers.
for chunk in &mut buffer[1..].chunks_exact_mut(16) {
// no bounds checks here due to indices and chunk size being constant
let sample0 = chunk[0] as i16;
let sample1 = chunk[1] as i16;
let sample2 = chunk[2] as i16;
let sample3 = chunk[3] as i16;
let sample4 = chunk[4] as i16;
let sample5 = chunk[5] as i16;
let sample6 = chunk[6] as i16;
let sample7 = chunk[7] as i16;
let sample8 = chunk[8] as i16;
let sample9 = chunk[9] as i16;
let sample10 = chunk[10] as i16;
let sample11 = chunk[11] as i16;
let sample12 = chunk[12] as i16;
let sample13 = chunk[13] as i16;
let sample14 = chunk[14] as i16;
let sample15 = chunk[15] as i16;
// Unlike in decoding, computations in here are truly independent from each other,
// which enables the compiler to vectorize this loop.
// Even if the target platform has no vector instructions,
// so using more parallelism doesn't imply doing more work,
// and we're not really limited in how wide we can go.
chunk[0] = (sample0 - previous + 128) as u8;
chunk[1] = (sample1 - sample0 + 128) as u8;
chunk[2] = (sample2 - sample1 + 128) as u8;
chunk[3] = (sample3 - sample2 + 128) as u8;
chunk[4] = (sample4 - sample3 + 128) as u8;
chunk[5] = (sample5 - sample4 + 128) as u8;
chunk[6] = (sample6 - sample5 + 128) as u8;
chunk[7] = (sample7 - sample6 + 128) as u8;
chunk[8] = (sample8 - sample7 + 128) as u8;
chunk[9] = (sample9 - sample8 + 128) as u8;
chunk[10] = (sample10 - sample9 + 128) as u8;
chunk[11] = (sample11 - sample10 + 128) as u8;
chunk[12] = (sample12 - sample11 + 128) as u8;
chunk[13] = (sample13 - sample12 + 128) as u8;
chunk[14] = (sample14 - sample13 + 128) as u8;
chunk[15] = (sample15 - sample14 + 128) as u8;
previous = sample15;
}
// Handle the remaining element at the end not processed by the loop over batches, if present
// This is what the iterator-based version of this function would look like without vectorization
for elem in &mut buffer[1..].chunks_exact_mut(16).into_remainder().iter_mut() {
let diff = (*elem as i16 - previous + 128) as u8;
previous = *elem as i16;
*elem = diff;
}
}
}
use std::cell::Cell;
thread_local! {
// A buffer for reusing between invocations of interleaving and deinterleaving.
// Allocating memory is cheap, but zeroing or otherwise initializing it is not.
// Doing it hundreds of times (once per block) would be expensive.
// This optimization brings down the time spent in interleaving from 15% to 5%.
static SCRATCH_SPACE: Cell<Vec<u8>> = Cell::new(Vec::new());
}
fn with_reused_buffer<F>(length: usize, mut func: F) where F: FnMut(&mut [u8]) {
SCRATCH_SPACE.with(|scratch_space| {
// reuse a buffer if we've already initialized one
let mut buffer = scratch_space.take();
if buffer.len() < length {
// Efficiently create a zeroed Vec by requesting zeroed memory from the OS.
// This is slightly faster than a `memcpy()` plus `memset()` that would happen otherwise,
// but is not a big deal either way since it's not a hot codepath.
buffer = vec![0u8; length];
}
// call the function
func(&mut buffer[..length]);
// save the internal buffer for reuse
scratch_space.set(buffer);
});
}
/// Interleave the bytes such that the second half of the array is every other byte.
pub fn interleave_byte_blocks(separated: &mut [u8]) {
with_reused_buffer(separated.len(), |interleaved| {
// Split the two halves that we are going to interleave.
let (first_half, second_half) = separated.split_at((separated.len() + 1) / 2);
// The first half can be 1 byte longer than the second if the length of the input is odd,
// but the loop below only processes numbers in pairs.
// To handle it, preserve the last element of the first slice, to be handled after the loop.
let first_half_last = first_half.last();
// Truncate the first half to match the lenght of the second one; more optimizer-friendly
let first_half_iter = &first_half[..second_half.len()];
// Main loop that performs the interleaving
for ((first, second), interleaved) in first_half_iter.iter().zip(second_half.iter())
.zip(interleaved.chunks_exact_mut(2)) {
// The length of each chunk is known to be 2 at compile time,
// and each index is also a constant.
// This allows the compiler to remove the bounds checks.
interleaved[0] = *first;
interleaved[1] = *second;
}
// If the length of the slice was odd, restore the last element of the first half that we saved
if interleaved.len() % 2 == 1 {
if let Some(value) = first_half_last {
// we can unwrap() here because we just checked that the lenght is non-zero:
// `% 2 == 1` will fail for zero
*interleaved.last_mut().unwrap() = *value;
}
}
// write out the results
separated.copy_from_slice(&interleaved);
});
}
/// Separate the bytes such that the second half contains every other byte.
/// This performs deinterleaving - the inverse of interleaving.
pub fn separate_bytes_fragments(source: &mut [u8]) {
with_reused_buffer(source.len(), |separated| {
// Split the two halves that we are going to interleave.
let (first_half, second_half) = separated.split_at_mut((source.len() + 1) / 2);
// The first half can be 1 byte longer than the second if the length of the input is odd,
// but the loop below only processes numbers in pairs.
// To handle it, preserve the last element of the input, to be handled after the loop.
let last = source.last();
let first_half_iter = &mut first_half[..second_half.len()];
// Main loop that performs the deinterleaving
for ((first, second), interleaved) in first_half_iter.iter_mut().zip(second_half.iter_mut())
.zip(source.chunks_exact(2)) {
// The length of each chunk is known to be 2 at compile time,
// and each index is also a constant.
// This allows the compiler to remove the bounds checks.
*first = interleaved[0];
*second = interleaved[1];
}
// If the length of the slice was odd, restore the last element of the input that we saved
if source.len() % 2 == 1 {
if let Some(value) = last {
// we can unwrap() here because we just checked that the lenght is non-zero:
// `% 2 == 1` will fail for zero
*first_half.last_mut().unwrap() = *value;
}
}
// write out the results
source.copy_from_slice(&separated);
});
}
#[cfg(test)]
pub mod test {
#[test]
fn roundtrip_interleave(){
let source = vec![ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ];
let mut modified = source.clone();
super::separate_bytes_fragments(&mut modified);
super::interleave_byte_blocks(&mut modified);
assert_eq!(source, modified);
}
#[test]
fn roundtrip_derive(){
let source = vec![ 0, 1, 2, 7, 4, 5, 6, 7, 13, 9, 10 ];
let mut modified = source.clone();
super::samples_to_differences(&mut modified);
super::differences_to_samples(&mut modified);
assert_eq!(source, modified);
}
}
}
#[cfg(test)]
pub mod test {
use super::*;
use crate::meta::attribute::ChannelDescription;
use crate::block::samples::IntoNativeSample;
#[test]
fn roundtrip_endianness_mixed_channels(){
let a32 = ChannelDescription::new("A", SampleType::F32, true);
let y16 = ChannelDescription::new("Y", SampleType::F16, true);
let channels = ChannelList::new(smallvec![ a32, y16 ]);
let data = vec![
23582740683_f32.to_ne_bytes().as_slice(),
35827420683_f32.to_ne_bytes().as_slice(),
27406832358_f32.to_f16().to_ne_bytes().as_slice(),
74062358283_f32.to_f16().to_ne_bytes().as_slice(),
52582740683_f32.to_ne_bytes().as_slice(),
45827420683_f32.to_ne_bytes().as_slice(),
15406832358_f32.to_f16().to_ne_bytes().as_slice(),
65062358283_f32.to_f16().to_ne_bytes().as_slice(),
].into_iter().flatten().map(|x| *x).collect();
roundtrip_convert_endianness(
data, &channels,
IntegerBounds::from_dimensions((2, 2))
);
}
fn roundtrip_convert_endianness(
current_endian: ByteVec, channels: &ChannelList, rectangle: IntegerBounds
){
let little_endian = convert_current_to_little_endian(
current_endian.clone(), channels, rectangle
);
let current_endian_decoded = convert_little_endian_to_current(
little_endian.clone(), channels, rectangle
);
assert_eq!(current_endian, current_endian_decoded, "endianness conversion failed");
}
}