Twk Lausanne Download Verified · Genuine

# ------------------------------------------------- # 3. Fit a GLM (event‑related design) # ------------------------------------------------- design = tio.load_events(bids_root, task='nback') glm = tstat.GLM() glm.fit(func_clean, design)

git clone https://github.com/epfl-twk/twk-lausanne.git cd twk-lausanne # Optionally check out the latest tag, e.g., v2.0.3 git checkout tags/v2.0.3 # Install in editable mode python -m pip install -e . The repository includes ; you can run the test suite with: twk lausanne download

from twk.distributed import RayExecutor

singularity pull docker://epfl/twk-lausanne:2.0 singularity exec twk-lausanne_2.0.sif twk-dashboard These containers embed all optional dependencies (CUDA, neuroimaging libraries, JupyterLab) and are . 4.4. Source Code (Git) If you prefer to develop on the bleeding edge: # ------------------------------------------------- # 3

dti = DTI(gpu=True) dti.fit(dataset.dwi, bvals=dataset.bval, bvecs=dataset.bvec) fa_map = dti.fa() tvis.plot_volume(fa_map, cmap='viridis') TWK Lausanne ships a Ray‑based distributed executor . Example for scaling across a Kubernetes cluster: task='nback') glm = tstat.GLM() glm.fit(func_clean

docker pull epfl/twk-lausanne:2.0 docker run -it --rm -v $PWD:/data epfl/twk-lausanne:2.0 bash For HPC clusters that rely on Singularity: