Skip to main content

Plugin to use TomoTwin within the Scipion framework

Project description

This plugin provides a wrapper for TomoTwin software: Particle picking in Tomograms using triplet networks and metric learning

PyPI release License Supported Python versions SonarCloud quality gate Downloads

Installation

You will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:

  1. Stable version

scipion installp -p scipion-em-tomotwin
  1. Developer’s version

    • download repository

    git clone -b devel https://github.com/scipion-em/scipion-em-tomotwin.git
    • install

    scipion installp -p /path/to/scipion-em-tomotwin --devel

TomoTwin software will be installed automatically with the plugin but you can also use an existing installation by providing TOMOTWIN_ENV_ACTIVATION (see below).

Important: you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.

Configuration variables

CONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the PATH (not recommended), which can lead to execution problems mixing scipion python with conda ones. One example of this could can be seen below but depending on your conda version and shell you will need something different: CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”

TOMOTWIN_ENV_ACTIVATION (default = conda activate tomotwin-0.2.1.6): Command to activate the TomoTwin environment.

TOMOTWIN_MODEL (default = software/em/tomotwin_model-052022/tomotwin_model_p120_052022_loss.pth): Path to the pre-trained model.

NAPARI_ENV_ACTIVATION (default = conda activate napari): Command to activate the Napari viewer (boxmanager) environment.

Verifying

To check the installation, simply run the following Scipion test:

scipion test tomotwin.tests.test_protocols_tomotwin.TestTomoTwinRefPicking

Supported versions

0.1.2, 0.2.1.6

Protocols

  • reference-based picking

References

  1. TomoTwin: Generalized 3D Localization of Macromolecules in Cryo-electron Tomograms with Structural Data Mining. Gavin Rice, Thorsten Wagner, Markus Stabrin, Stefan Raunser. https://www.biorxiv.org/content/10.1101/2022.06.24.497279v1

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

scipion-em-tomotwin-3.0b4.tar.gz (156.4 kB view details)

Uploaded Source

Built Distribution

scipion_em_tomotwin-3.0b4-py3-none-any.whl (160.9 kB view details)

Uploaded Python 3

File details

Details for the file scipion-em-tomotwin-3.0b4.tar.gz.

File metadata

  • Download URL: scipion-em-tomotwin-3.0b4.tar.gz
  • Upload date:
  • Size: 156.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.14

File hashes

Hashes for scipion-em-tomotwin-3.0b4.tar.gz
Algorithm Hash digest
SHA256 b6c9a278f29d8814bace238baf4fdfe745706a30cf25f68a01c30dda142541b4
MD5 75ffa60558d4ca14ac55ea99f53a2e4d
BLAKE2b-256 7afda0ecc88b89af8224cbeb654ed94f1497c2a958c8f118681154905aba1268

See more details on using hashes here.

File details

Details for the file scipion_em_tomotwin-3.0b4-py3-none-any.whl.

File metadata

File hashes

Hashes for scipion_em_tomotwin-3.0b4-py3-none-any.whl
Algorithm Hash digest
SHA256 127f383bfbb10ac701d753d882b0a9a22f0047daac10344ee03ae8bea0926d2f
MD5 0309cd283ea34d6f77ff9c9bea2ae437
BLAKE2b-256 b3f0961e89d2f90e7250419410008a0d9ba49a28bb28d871fcd90aa38b273b65

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