Python tool for visualising and interacting with cryo-ET and subtomogram averaging data.
blik is a tool for visualising and interacting with cryo-ET and subtomogram averaging data. It leverages the fast, multi-dimensional napari viewer and the scientific python stack.
DISCLAIMER: this package is in development phase. Expect bugs and crashes. Please, report them on the issue tracker and ask if anything is unclear!
You can either install
blik through the napari plugin system, through pip, or get both napari and blik directly with:
pip install "blik[all]"
[all] qualifier also installs
pyqt5 as the napari GUI backend, and a few additional napari plugins that you might find useful in your workflow:
From the command line:
napari -w blik -- /path/to.star /path/to/mrc/files/*
-w blik is important for proper initialization of all the layers. Keep the main widget open to ensure nothing goes wrong!
blik is just
napari. Particles and images are exposed as simple napari layers, which can be analysed and manipulated with simple python, and most importantly other napari plugins.
The main widget has a few functions:
experiment: quickly switch to a different experiment id (typically, everything related to an individual tomogram such as volume, particles and segmentations)
new: generate a new
segmentation, a new manually-picked set of
particles, or a new
surface pickingfor segmentation or particle generation
add to exp: add a layer to the currently selected
experiment(just a shorthand for
layer.metadata['experiment_id'] = current_exp_id)
surface: process a previously picked
surface pickinglayer to generate a surface mesh or distribute particles on it for subtomogram averaging.
- 20 September 2023
- 15 June 2021
- Information not submitted
- Stars: 17
- Forks: 4
- Issues + PRs: 4