nd-image-codecs

Composable Zarr v3 codecs for ND scientific images — Python binding.

A family of Zarr v3 codecs that capture correlation along z, time, and channel axes explicitly — as ordinary, independently specified array-to-array and array-to-bytes codecs — then store the result with a fast entropy backend, High-Throughput JPEG 2000 (ISO/IEC 15444-15) coefficient planes, or ZFP blocks. Built for OME-Zarr / OME-NGFF.

No JPEG 2000 Part 2 (MCT) syntax anywhere — cross-axis decorrelation is an explicit Zarr codec, sidestepping Part 2 IP entirely.

The three codec families

codec_series assembles a series (pipeline) of Zarr v3 codecs from an array's axis metadata:

Install

pip install nd-image-codecs

Usage

from nd_image_codecs import codec_series

codecs = codec_series(["t", "c", "z", "y", "x"], [8, 1, 32, 256, 256],
                      "uint16", "nd-lift-ht")

The three codec classes (NdLift, Htj2k, NdZfp) register with zarr-python v3 through the zarr.codecs entry-point group, so pipelines produced by codec_series resolve by name.

Status

Pre-alpha. The codec_series builder is fully implemented and is cross-checked against the Rust and TypeScript implementations in CI. The codec encode/decode paths are scaffolds — they land across the six roadmap phases.

Links

• Repository
• Python usage guide
• Architecture

License

MIT — Copyright (c) Fideus Labs LLC.