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From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 10 Nov 2025 20:01:40 +0000
Subject: [PATCH 1/2] Initial plan


From a06745128ba6fbd1423738ab2e432e4cd0c03326 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 10 Nov 2025 20:04:10 +0000
Subject: [PATCH 2/2] =?UTF-8?q?Fix=20spelling=20error:=20develpoments=20?=
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Co-authored-by: dimitri-yatsenko <1096169+dimitri-yatsenko@users.noreply.github.com>
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 README.md | 2 +-
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 This codec is designed for compressing image recordings with Poisson noise such as in microscopy, radiography, and astronomy.
 
 **Status:** This is the official and actively maintained Anscombe transform codec for Zarr/Numcodecs, maintained by DataJoint.
-It originated as a fork of [AllenNeuralDynamics/poisson-numcodecs](https://github.com/AllenNeuralDynamics/poisson-numcodecs) and earlier develpoments at https://github.com/datajoint/compress-multiphoton. It has since diverged significantly. New users should rely on this repository as the canonical source.
+It originated as a fork of [AllenNeuralDynamics/poisson-numcodecs](https://github.com/AllenNeuralDynamics/poisson-numcodecs) and earlier developments at https://github.com/datajoint/compress-multiphoton. It has since diverged significantly. New users should rely on this repository as the canonical source.
 
 The codec assumes that the video is linearly encoded with a potential offset (`zero_level`) and that the `conversion_gain` (also called `photon_sensitivity`)—the average increase in intensity per photon—is either already known or can be accurately estimated from the data.