numquant

Crates.ionumquant
lib.rsnumquant
version0.2.0
sourcesrc
created_at2022-04-11 09:38:23.522984
updated_at2022-04-11 21:25:34.053924
descriptionQuantize numbers to a smaller range to save bandwidth or memory data types and back again.
homepage
repositoryhttps://github.com/vilcans/numquant
max_upload_size
id565550
size27,548
Martin Vilcans (vilcans)

documentation

https://docs.rs/numquant

README

numquant

Quantize numbers to a smaller range to save bandwidth or memory.

The input floating point value is expected within a given range. Values outside this range will be clamped. The input value will then be quantized into a given integer range.

For example, given the allowed range -1000.0 to 1000.0, and the quantized range 0 to 255 (to fit in a byte), the value -1000.0 would be quantized to 0, and 1000.0 would be quantized to 255, and values in-between are linearly interpolated between 0 and 255.

Example

This example uses the type Quantized<U8<0, 1000>> that converts any floating point number between 0.0 and 1000.0 to a byte (which has the range 0 to 255). Some precision is lost, but an approximate value can be brought back.

let original = 500.0;
// Quantize the value into a byte.
// Quantization supports inputs between 0 and 1000.
let quantized = Quantized::<U8<0, 1000>>::from_f64(original);
// Convert it back to an f64
let dequantized = quantized.to_f64();
// The conversion isn't lossless, but the dequantized value is close to the original:
approx::assert_abs_diff_eq!(original, dequantized, epsilon = U8::<0, 1000>::max_error());

Links

Commit count: 21

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