Skip to main content

Tools for neuroglancer scenes.

Project description

NGSidekick

Documentation

Tools for working with neuroglancer. See docs.

Feature Highlights

  • Segment properties: read and write neuroglancer's precomputed segment properties format from a pandas DataFrame.

  • Annotations:

    • Local annotations: construct local annotations directly in viewer state. (API subject to change.)

    • Precomputed annotations: export annotations in neuroglancer's precomputed annotations format from a pandas DataFrame.

      • Supports all five annotation types:
        • point
        • line
        • axis_aligned_bounding_box
        • ellipsoid
        • polyline
      • Per-annotation properties (numeric, enum/categorical, and rgb/rgba color).
      • Per-annotation relationships (lists of related segment IDs, used by neuroglancer to filter annotations by segment).
      • Written to all "index" types (annotation id, related segment, and multi-level spatial grid)
      • Sharded output, written in parallel via tensorstore.
      • Note: writing directly to cloud storage is not yet supported; outputs must be written to a local filesystem (you must upload to cloud storage afterwards).

Installation

Packages are available from both PyPI and conda-forge.

Using pixi:

pixi add ngsidekick

Using conda:

conda install -c conda-forge ngsidekick

Using pip:

pip install ngsidekick

Using uv:

uv add ngsidekick

# or in an existing environment
uv pip install ngsidekick

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ngsidekick-0.0.15.tar.gz (17.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ngsidekick-0.0.15-py3-none-any.whl (69.8 kB view details)

Uploaded Python 3

File details

Details for the file ngsidekick-0.0.15.tar.gz.

File metadata

  • Download URL: ngsidekick-0.0.15.tar.gz
  • Upload date:
  • Size: 17.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for ngsidekick-0.0.15.tar.gz
Algorithm Hash digest
SHA256 585b16b88a2701fdf228f90a7fc26c0bc7028ff0e54b0762bc3c3fb3a4c0757f
MD5 535f83a2c69a2d339a4b1a0aff7712c0
BLAKE2b-256 c1e6512a669812747909421ddac9de317f0a92c366d7c8c44606179107bf2c5d

See more details on using hashes here.

File details

Details for the file ngsidekick-0.0.15-py3-none-any.whl.

File metadata

  • Download URL: ngsidekick-0.0.15-py3-none-any.whl
  • Upload date:
  • Size: 69.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for ngsidekick-0.0.15-py3-none-any.whl
Algorithm Hash digest
SHA256 e87df0ca9d1adb56fe6ad15ca62bebe5ac70c26ffbf82b6e43945844440e88ec
MD5 5c2f27046654e77f2d35def344e7b4be
BLAKE2b-256 23f89c694cd4aa78838fb5350d11fd6f89ea79895f32b1978a7eaf99003748cc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page