Installation and Download
Installation
We recommend to use the conda client mamba for installation. You should use the latest miniforge for installation of mamba. Alternatively you can replace mamba with conda in the commands below, but the installation will be much slower.
There are three main steps to install TomoTwin:
1. Install TomoTwin
In case you have on old TomoTwin version installed, please remove the old one first with:
mamba env remove -n tomotwin
Next you can create the TomoTwin environment:
mamba env create -n tomotwin -f https://raw.githubusercontent.com/MPI-Dortmund/tomotwin-cryoet/main/conda_env_tomotwin.yml
pip install tomotwin-cryoet
2. Install Napari
Here we assume that you don’t have napari installed. Please do:
mamba env create -n napari-tomotwin -f https://raw.githubusercontent.com/MPI-Dortmund/napari-tomotwin/main/conda_env.yml
pip install napari-tomotwin
3. Link Napari
This is an optional step, but for convenience reasons we link an adapted napari call into the tomotwin environment. With that you don’t need to switch environments when working with tomotwin. While this is optional, I assume during the tutorials that you did this step. Here is what you need to do:
conda activate tomotwin
tomotwin_dir=$(realpath $(dirname $(which tomotwin_embed.py)))
napari_link_file=${tomotwin_dir}/napari_boxmanager
conda activate napari-tomotwin
echo -e "#\!/usr/bin/bash\nexport NAPARI_EXE=$(which napari)\nnapari_exe='$(which napari_boxmanager)'\n\${napari_exe} \"\${@}\""> ${napari_link_file}
ln -rs $(which napari) ${tomotwin_dir}
chmod +x ${napari_link_file}
conda activate tomotwin
Update TomoTwin & Napari
To update an existing TomoTwin installation just do:
mamba env update -n tomotwin -f https://raw.githubusercontent.com/MPI-Dortmund/tomotwin-cryoet/main/conda_env_tomotwin.yml --prune
conda activate tomotwin
pip install tomotwin-cryoet
mamba env update -n napari-tomotwin -f https://raw.githubusercontent.com/MPI-Dortmund/tomotwin-cryoet/main/conda_env_napari.yml --prune
Download latest model
- Last update:
09.2023
- Number of proteins:
120
- Link:
System requirements
So far we run it on Ubuntu 20.04 and the following GPUs:
NVIDIA V100
NVIDIA RTX 2080
NVIDIA A100