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remove print as this seems to cause macos testing to hang
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dbdimitrov committed Apr 12, 2024
1 parent 9839d6a commit 0213b7f
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26 changes: 13 additions & 13 deletions docs/source/notebooks/bivariate.ipynb
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"text": [
"Using `.X`!\n",
"Using resource `consensus`.\n",
"100%|██████████| 100/100 [01:17<00:00, 1.29it/s]\n",
"100%|██████████| 100/100 [01:07<00:00, 1.48it/s]\n"
"100%|██████████| 100/100 [01:56<00:00, 1.17s/it]\n",
"100%|██████████| 100/100 [01:01<00:00, 1.64it/s]\n"
]
}
],
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"output_type": "stream",
"text": [
" 0%| | 0/10 [00:00<?, ?it/s]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 10%|█ | 1/10 [00:02<00:25, 2.85s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 20%|██ | 2/10 [00:10<00:45, 5.71s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 30%|███ | 3/10 [00:15<00:38, 5.52s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 40%|████ | 4/10 [00:21<00:34, 5.70s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 50%|█████ | 5/10 [00:30<00:34, 6.84s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 60%|██████ | 6/10 [00:40<00:30, 7.71s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 70%|███████ | 7/10 [00:51<00:26, 8.83s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 80%|████████ | 8/10 [01:01<00:18, 9.34s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 90%|█████████ | 9/10 [01:13<00:10, 10.14s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
"100%|██████████| 10/10 [01:24<00:00, 8.47s/it]\n",
" 10%|█ | 1/10 [00:02<00:25, 2.86s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 20%|██ | 2/10 [00:08<00:34, 4.33s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 30%|███ | 3/10 [00:14<00:36, 5.20s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 40%|████ | 4/10 [00:21<00:35, 5.91s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 50%|█████ | 5/10 [00:29<00:32, 6.56s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 60%|██████ | 6/10 [00:37<00:28, 7.21s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 70%|███████ | 7/10 [00:47<00:23, 7.94s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 80%|████████ | 8/10 [00:56<00:16, 8.35s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
" 90%|█████████ | 9/10 [01:06<00:08, 8.88s/it]/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n",
"100%|██████████| 10/10 [01:17<00:00, 7.79s/it]\n",
"Estimated rank: 3\n",
"/home/dbdimitrov/anaconda3/envs/spiana/lib/python3.10/site-packages/sklearn/decomposition/_nmf.py:1710: ConvergenceWarning: Maximum number of iterations 200 reached. Increase it to improve convergence.\n"
]
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"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1/1 [00:02<00:00, 2.05s/it]\n"
"100%|██████████| 1/1 [00:01<00:00, 1.36s/it]\n"
]
}
],
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2 changes: 1 addition & 1 deletion liana/multi/_nmf.py
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Expand Up @@ -125,4 +125,4 @@ def _plot_elbow(errors, n_components, x='k', y='error'):
p9.labs(x='Component number (k)', y='Reconstruction error') +
p9.geom_vline(xintercept=n_components, linetype='dashed', color='red')
)
print(p)
p.draw()
2 changes: 1 addition & 1 deletion liana/multi/to_mudata.py
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Expand Up @@ -122,7 +122,7 @@ def adata_to_views(adata: AnnData,
def lrs_to_views(adata: AnnData,
score_key: (str or None) = None,
inverse_fun: callable = V.inverse_fun,
obs_keys: (list or None) =None,
obs_keys: (list or None) = None,
lr_prop: float = 0.5,
lr_fill: np.nan = np.nan,
lrs_per_view:int = 20,
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