Skip to main content

A plugin for making animations in napari

Project description

napari-animation

License PyPI Python Version tests codecov

napari-animation is a plugin for making animations in napari.


Merlin Lange used napari-animation to create one of Nature's best science images for September 2022


This plugin is built on naparimovie from @guiwitz. naparimovie was submitted to napari in PR#851 before napari plugin infrastructure existed.


Overview

napari-animation provides a framework for the creation of animations in napari. The plugin contains:

  • an easy to use GUI for creating animations interactively;
  • a Python package for the programmatic creation of animations.

This plugin remains under development and contributions are very welcome, please open an issue to discuss potential improvements.

You can read the documentation at https://napari.org/napari-animation

Installation

PyPI

napari-animation is available through the Python package index and can be installed using pip.

pip install napari-animation
`napari-animation` uses `ffmpeg` to export animations. If you are using a macOS arm64 computer (Apple Silicon e.g. M1, M2 processor)
the PyPI package does not include the needed binary for your platform. You will need to install `ffmpeg` using
`conda` from the [conda-forge channel](https://conda-forge.org/docs/#what-is-conda-forge) (`conda install -c conda-forge ffmpeg`)
or using [`homebrew`](https://brew.sh) (`brew install ffmpeg`).

Conda

napari-animation is also available for install using conda through the conda-forge channel.

conda install -c conda-forge napari-animation

Local

You can clone this repository and install locally with

pip install -e .

Interactive use

napari-animation can be used interactively.

An animation is created by capturing keyframes containing the current viewer state.

To activate the GUI, select napari-animation: wizard from the plugins menu

Scripting

napari-animation can also be run programatically, allowing for reproducible, scripted creation of animations.

from napari_animation import Animation

animation = Animation(viewer)

viewer.dims.ndisplay = 3
viewer.camera.angles = (0.0, 0.0, 90.0)
animation.capture_keyframe()
viewer.camera.zoom = 2.4
animation.capture_keyframe()
viewer.camera.angles = (-7.0, 15.7, 62.4)
animation.capture_keyframe(steps=60)
viewer.camera.angles = (2.0, -24.4, -36.7)
animation.capture_keyframe(steps=60)
viewer.reset_view()
viewer.camera.angles = (0.0, 0.0, 90.0)
animation.capture_keyframe()
animation.animate('demo.mov', canvas_only=False)

Examples

Examples can be found in our Examples gallery, generated from our example scripts. Simple examples for both interactive and headless use of the plugin follow.

Contributing

Contributions are very welcome and a detailed contributing guide is coming soon. In the meantime, clone this repository and install it in editable mode using pip:

pip install -e .

We recommend using a virtual environment, for example conda.

Ensure you have a suitable Qt backend for napari! We recommend `PyQt5`.
For more information, see the napari [Qt backend installation guide](https://napari.org/stable/tutorials/fundamentals/installation.html#choosing-a-different-qt-backend)

To set up your development installation, clone this repository, navigate to the clone folder, and install napari-animation in editable mode using pip.

conda create -n nap-anim python=3.10
conda activate nap-anim
pip install -e ".[dev]" PyQt5

Tests are run with pytest. You can make sure your [dev] installation is working properly by running pytest . from within the repository.

We use [`pre-commit`](https://pre-commit.com) to sort imports and lint with
[`ruff`](https://github.com/astral-sh/ruff) and format code with
[`black`](https://github.com/psf/black) automatically prior to each commit.
To minmize test errors when submitting pull requests, please install `pre-commit`
in your environment as follows:

`pre-commit install`

Documentation

The documentation is available at https://napari.org/napari-animation

The documentation for napari-animation is built with Sphinx and the napari Sphinx Theme.

Building docs locally

After installing the documentation dependencies with

pip install ".[doc]"

you can see a local version of the documentation by running

make docs

Open up the docs/_build/index.html file in your browser, and you'll see the home page of the docs being displayed.

Deploying docs

The napari-animation documentation is automatically built and deployed to the website whenever the main branch is updated, or a new release is tagged. This is controlled by the deploy_docs.yml github actions script.

You can also manually trigger a documenation re-build and deployment from the github actions tab.

License

Distributed under the terms of the BSD-3 license, napari-animation is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

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

napari_animation-0.0.8.tar.gz (819.2 kB view details)

Uploaded Source

Built Distribution

napari_animation-0.0.8-py3-none-any.whl (33.8 kB view details)

Uploaded Python 3

File details

Details for the file napari_animation-0.0.8.tar.gz.

File metadata

  • Download URL: napari_animation-0.0.8.tar.gz
  • Upload date:
  • Size: 819.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for napari_animation-0.0.8.tar.gz
Algorithm Hash digest
SHA256 82f0888cc56bb164d7d3d129b7fb6482dca268ff15f4fc0fb49a1996b3864bcc
MD5 dbbdefd5371319fa181b8ca8df1330b5
BLAKE2b-256 815c6a68fc184711f6b0fe0e9cb9a4946329bb8f41e0cb9a6ea589c35e27d0fc

See more details on using hashes here.

File details

Details for the file napari_animation-0.0.8-py3-none-any.whl.

File metadata

File hashes

Hashes for napari_animation-0.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 09afe0b7b637a3f5cbc6a1d6d0f7a0ad66a19a3e380a77d6bb3f5f2602d1c660
MD5 c935265a19f57dd597939ff66326dadc
BLAKE2b-256 a95e2f337dc8329ed6d7bb5821553e33fa70a8642c2a0e5e36a6ab408f4ba72d

See more details on using hashes here.

Supported by

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