Skip to main content

A tool for creating and visualizing n-dimensional microscopy images.

Project description

nViz

Build Status Ruff uv Coverage Status

This project focuses on ingesting a set of TIFF images as OME-Zarr or OME-TIFF. Each input image set1 are organized by channel and z-slices which form four dimensional (4D) microscopy data. These 4D microscopy data contain information for biological objects (such as organoids).

We read the output with Napari, which provides a way to analyze and understand the 3D image data.

1. Image set is loosely defined and changes depending on the context of the data. Here it represents a set of images in multiple dimensions that contain information regarding the same sample. Each image in an imageset is paired data and must be related as such.

Installation

Install nViz from PyPI or from source:

# install from pypi
pip install nviz

# install directly from source
pip install git+https://github.com/WayScience/nViz.git

Installation notes for Linux

nViz leverages Napari to help render visuals. Napari leverages PyQT to help build graphical components. PyQT has specific requirements based on the operating system which sometimes can cause errors within Napari, and as a result, also nViz.

Below are some steps to try if you find that nViz visualizations through Napari are resulting in QT-related errors.

  • Attempt to install python3-pyqt5 through your system package manager (e.g. apt install python3-pyqt5).
  • When using nViz within GitHub Actions Linux environments, consider using pyvista/setup-headless-display-action with qt: true in order to run without general exceptions.

Contributing, Development, and Testing

Please see our contributing documentation for more details on contributions, development, and testing.

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

nviz-0.0.3.tar.gz (6.3 MB view details)

Uploaded Source

Built Distribution

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

nviz-0.0.3-py3-none-any.whl (13.1 kB view details)

Uploaded Python 3

File details

Details for the file nviz-0.0.3.tar.gz.

File metadata

  • Download URL: nviz-0.0.3.tar.gz
  • Upload date:
  • Size: 6.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for nviz-0.0.3.tar.gz
Algorithm Hash digest
SHA256 5ec6212103a953a53180cef7f821b84ab473e0ca33ab3a180fc440fe04e83106
MD5 acbbda4b873aff1c40cc81b349b0a55f
BLAKE2b-256 7610899e3627f35dfa3abab73968cd882444ba265d839ec5619a6b731a4f6a94

See more details on using hashes here.

Provenance

The following attestation bundles were made for nviz-0.0.3.tar.gz:

Publisher: publish-pypi.yml on WayScience/nViz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file nviz-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: nviz-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 13.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for nviz-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8d33a19b827541a46e799eb61547e8f6229220e800abded4841467fb86da96f7
MD5 e2cf4f2e14a82a93dfbf83d8aeefa57a
BLAKE2b-256 341691afb58a14d351db8304419167e0b7bfc89b024546c64e922ebd1aff0e80

See more details on using hashes here.

Provenance

The following attestation bundles were made for nviz-0.0.3-py3-none-any.whl:

Publisher: publish-pypi.yml on WayScience/nViz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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