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Adding tests and interface improvements #47

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merged 9 commits into from
Apr 30, 2024
Merged

Adding tests and interface improvements #47

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515c6e8
make the modules public
selmanozleyen Apr 29, 2024
04de112
refactor adj matrix
selmanozleyen Apr 30, 2024
8b752e6
edge index update and add test
selmanozleyen Apr 30, 2024
7460088
update the tests and function
selmanozleyen Apr 30, 2024
f773a35
add_edge_index updates
selmanozleyen Apr 30, 2024
bf82e39
formatting
selmanozleyen Apr 30, 2024
2309d24
add test and remove __call__ docstrings because class docstring shoul…
selmanozleyen Apr 30, 2024
d44166c
add tests check notebooks again refactor
selmanozleyen Apr 30, 2024
574fd97
update readme
selmanozleyen Apr 30, 2024
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2 changes: 1 addition & 1 deletion .gitignore
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Expand Up @@ -27,4 +27,4 @@ __pycache__/
/.idea/
/.vscode/

**/lightning_logs/**
**/lightning_logs/**
4 changes: 4 additions & 0 deletions README.md
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Expand Up @@ -33,6 +33,10 @@ pip install geome
1. Install the latest development version:

```bash
mamba create -n geome python=3.11
mamba activate geome
mamba install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia
pip install torch-scatter torch-sparse torch-cluster -f https://data.pyg.org/whl/torch-2.1.0+cu121.html
pip install git+https://github.com/theislab/geome.git@main
```

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5 changes: 4 additions & 1 deletion docs/conf.py
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Expand Up @@ -19,7 +19,8 @@


# -- Project information -----------------------------------------------------

# NOTE: If you installed your project in editable mode, this might be stale.
# If this is the case, reinstall it to refresh the metadata
# info = metadata("geome")
# project_name = info["Name"]
project_name = "geome"
Expand Down Expand Up @@ -114,12 +115,14 @@
#
html_theme = "furo"
html_static_path = ["_static"]
html_css_files = ["css/custom.css"]
html_title = project_name

html_theme_options = {
"repository_url": repository_url,
"use_repository_button": True,
"path_to_docs": "docs/",
"navigation_with_keys": False,
}

pygments_style = "default"
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34 changes: 0 additions & 34 deletions docs/conf.py.rej
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8 changes: 0 additions & 8 deletions docs/index.md.rej
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15 changes: 9 additions & 6 deletions docs/notebooks/1_iterables_and_iterators.ipynb
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Expand Up @@ -51,10 +51,9 @@
"metadata": {},
"outputs": [],
"source": [
"from geome import iterables, transforms, ann2data\n",
"from geome import iterables, ann2data\n",
"import squidpy as sq\n",
"import numpy as np\n",
"from anndata import AnnData"
"import numpy as np"
]
},
{
Expand Down Expand Up @@ -162,7 +161,7 @@
],
"source": [
"split_adatas = list(to_iterable(adata)) # split by cluster\n",
"assert len(split_adatas) == len(adata.obs[\"Cluster\"].cat.categories) # ensure all clusters have their own adata\n",
"assert len(split_adatas) == len(adata.obs[\"Cluster\"].cat.categories) # ensure all clusters have their own adata\n",
"split_adatas[:3] # show first 3"
]
},
Expand All @@ -183,7 +182,9 @@
"metadata": {},
"outputs": [],
"source": [
"assert all(len(ad.obs[\"Cluster\"].cat.categories) == len(adata.obs[\"Cluster\"].cat.categories) for ad in split_adatas) # ensure all splits have the same category"
"assert all(\n",
" len(ad.obs[\"Cluster\"].cat.categories) == len(adata.obs[\"Cluster\"].cat.categories) for ad in split_adatas\n",
") # ensure all splits have the same category"
]
},
{
Expand Down Expand Up @@ -297,7 +298,9 @@
"metadata": {},
"outputs": [],
"source": [
"assert all(np.allclose(r1.x, r2.x) for r1, r2 in zip(result1, result2)) and all(np.allclose(r1.x, r3.x) for r1, r3 in zip(result1, result3))"
"assert all(np.allclose(r1.x, r2.x) for r1, r2 in zip(result1, result2)) and all(\n",
" np.allclose(r1.x, r3.x) for r1, r3 in zip(result1, result3)\n",
")"
]
}
],
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83 changes: 35 additions & 48 deletions docs/notebooks/2_transforms_and_preprocessing.ipynb
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Expand Up @@ -37,32 +37,22 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from geome import iterables, transforms, ann2data\n",
"from geome import transforms\n",
"import squidpy as sq\n",
"import numpy as np\n",
"from anndata import AnnData"
]
},
Expand All @@ -76,19 +66,12 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Load some simple adata sample\n",
"def create_adata():\n",
" adata = sq.datasets.mibitof()\n",
" simple_adata = AnnData(adata.X)\n",
" simple_adata.obs[\"Cluster\"] = adata.obs[\"Cluster\"]\n",
" simple_adata.obsp[\"connectivities\"] = adata.obsp[\"connectivities\"]\n",
" return simple_adata\n",
"\n",
"adata = create_adata()"
"adata = sq.datasets.mibitof()"
]
},
{
Expand All @@ -102,18 +85,21 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 3309 × 36\n",
" obs: 'Cluster'\n",
" obsp: 'connectivities'"
" obs: 'row_num', 'point', 'cell_id', 'X1', 'center_rowcoord', 'center_colcoord', 'cell_size', 'category', 'donor', 'Cluster', 'batch', 'library_id'\n",
" var: 'mean-0', 'std-0', 'mean-1', 'std-1', 'mean-2', 'std-2'\n",
" uns: 'Cluster_colors', 'batch_colors', 'neighbors', 'spatial', 'umap'\n",
" obsm: 'X_scanorama', 'X_umap', 'spatial'\n",
" obsp: 'connectivities', 'distances'"
]
},
"execution_count": 12,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -124,13 +110,12 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"adds_edge_index = transforms.AddEdgeIndex(\n",
" adj_matrix_loc=\"obsp/connectivities\", edge_index_key=\"edge_index\", overwrite=True\n",
")"
"sq_neighbors_args = {\"radius\": 4.0, \"coord_type\": \"generic\"}\n",
"adds_edge_index = transforms.AddEdgeIndex(edge_index_key=\"edge_index\", edge_weight_key=\"edge_weight\", func_args=sq_neighbors_args, spatial_key=\"spatial\", key_added=\"added\")"
]
},
{
Expand All @@ -142,19 +127,21 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 3309 × 36\n",
" obs: 'Cluster'\n",
" uns: 'edge_index'\n",
" obsp: 'connectivities'"
" obs: 'row_num', 'point', 'cell_id', 'X1', 'center_rowcoord', 'center_colcoord', 'cell_size', 'category', 'donor', 'Cluster', 'batch', 'library_id'\n",
" var: 'mean-0', 'std-0', 'mean-1', 'std-1', 'mean-2', 'std-2'\n",
" uns: 'Cluster_colors', 'batch_colors', 'neighbors', 'spatial', 'umap', 'added_neighbors', 'edge_index', 'edge_weight'\n",
" obsm: 'X_scanorama', 'X_umap', 'spatial'\n",
" obsp: 'connectivities', 'distances', 'added_connectivities', 'added_distances'"
]
},
"execution_count": 14,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -165,42 +152,42 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"multiple_transforms = transforms.Compose( # you can get creative with this\n",
" [\n",
" transforms.AddEdgeIndex(adj_matrix_loc=\"obsp/connectivities\", edge_index_key=\"edge_index\", overwrite=True),\n",
" transforms.AddEdgeWeight(\n",
" weight_matrix_loc=\"obsp/connectivities\",\n",
" edge_index_key=\"edge_index\",\n",
" edge_weight_key=\"edge_weight\",\n",
" overwrite=True,\n",
" ),\n",
" transforms.AddAdjMatrix(func_args=sq_neighbors_args, key_added=\"added2\", spatial_key=\"spatial\"),\n",
" transforms.AddEdgeIndexFromAdj(adj_matrix_loc=\"obsp/added2_connectivities\", edge_index_key=\"edge_index2\", edge_weight_key=\"edge_weight2\"),\n",
" ]\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([71500])"
"AnnData object with n_obs × n_vars = 3309 × 36\n",
" obs: 'row_num', 'point', 'cell_id', 'X1', 'center_rowcoord', 'center_colcoord', 'cell_size', 'category', 'donor', 'Cluster', 'batch', 'library_id'\n",
" var: 'mean-0', 'std-0', 'mean-1', 'std-1', 'mean-2', 'std-2'\n",
" uns: 'Cluster_colors', 'batch_colors', 'neighbors', 'spatial', 'umap', 'added_neighbors', 'edge_index', 'edge_weight', 'added2_neighbors', 'edge_index2', 'edge_weight2'\n",
" obsm: 'X_scanorama', 'X_umap', 'spatial'\n",
" obsp: 'connectivities', 'distances', 'added_connectivities', 'added_distances', 'added2_connectivities', 'added2_distances'"
]
},
"execution_count": 16,
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res = multiple_transforms(adata)\n",
"res.uns[\"edge_weight\"].shape"
"res"
]
}
],
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