blik

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!

Installation¶

You can either install blik through the napari plugin system, through pip, or get both napari and blik directly with:

pip install "blik[all]"

The [all] qualifier also installs pyqt5 as the napari GUI backend, and a few additional napari plugins that you might find useful in your workflow:

• napari-properties-plotter
• napari-properties-viewer
• napari-label-interpolator

Basic Usage¶

From the command line:

napari -w blik -- /path/to.star /path/to/mrc/files/*

The -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.

Widget¶

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 picking for 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 picking layer to generate a surface mesh or distribute particles on it for subtomogram averaging.