TaxVAMB #204
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TaxVAMB #204
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jakobnissen
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Nov 6, 2023
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| """ | ||
| The following code is a modification of a k-means based reclustering algorithm first published at https://github.com/BigDataBiology/SemiBin | ||
| The original code is distributed under MIT License. | ||
| """ | ||
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| import os | ||
| import subprocess | ||
| import tempfile | ||
| import sys | ||
| import contextlib | ||
| from typing import IO | ||
| from sklearn.cluster import KMeans | ||
| import numpy as np | ||
| from collections import defaultdict | ||
| import pandas as pd | ||
| from sklearn.cluster import DBSCAN | ||
| from sklearn.metrics import pairwise_distances | ||
| import gzip |
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Re this file: Let's discuss the plan for removing it when I'm back in the office. I.e. if we manage to implement SCG in the latent space, how can we excise this module, and all the related functionality in a clean way?
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| #!/usr/bin/bash | ||
| module load tools computerome_utils/2.0 | ||
| module load anaconda3/2023.03 | ||
| module unload gcc | ||
| module load gcc/11.1.0 | ||
| module load minimap2/2.17r941 samtools/1.10 | ||
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| source ~/.bashrc | ||
| conda init bash | ||
| conda activate /home/projects/cpr_10006/people/svekut/.conda/vamb | ||
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Should all these Computerome scripts be part of the repo? They're very dev-specific for our group. Perhaps have them in their own folder?
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nah, they will be deleted
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Implementation of the predictor, VAEVAE and hierarchical loss, all in one commit
The squashed version of PR#184. Keeping the old PR to not lose the comments.