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romankouzromankouz
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final results
1 parent 880e4f5 commit 90f6e75

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-3035
lines changed

‎config/model/MonetDenseXenium.yaml‎

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Original file line numberDiff line numberDiff line change
@@ -2,25 +2,25 @@ name: MonetDense
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_includes_celltypes: ${datasets.dataset.include_celltypes}
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kwargs:
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observables_dimension: 100
5-
hidden_dimensions: [512, 512, 512, 512, 512, 512]
5+
hidden_dimensions: [256, 256, 256]
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output_dimension: 148
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loss_type: "mse"
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other_logged_losses: ["mse"]
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dim: 2
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other_logged_losses: []
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dim: 4
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kernel_size: 10
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radius: ${radius}
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mask_random_prop: 0.0
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mask_cells_prop: 0.0
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mask_genes_prop: 1.0
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response_genes: # empty by default this is none so we can use the responses from the data
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celltypes:
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batchnorm: True
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final_relu: False
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batchnorm: False
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final_relu: True
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attach_mask: False
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dropout: 0
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responses: True
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hide_responses: True
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include_skip_connections: True
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aggr: "sum"
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pseudo_mode: "polar"
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aggr: "mean"
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pseudo_mode: "polar_and_degree"
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num_gpus: ${gpus}

‎config/optimizer/adam.yaml‎

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@@ -3,5 +3,5 @@ params:
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lr: 0.001
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betas: [0.9, 0.999]
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eps: 1e-8
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weight_decay: 1e-5
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weight_decay: 0.0
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amsgrad: False

‎config/optimizer/sgd.yaml‎

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@@ -1,5 +1,5 @@
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name: SGD
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params:
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lr: 0.01
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weight_decay: 1e-6
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momentum: 0
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lr: 0.001
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eps: 1e-8
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weight_decay: 1e-4

‎config/training/default.yaml‎

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@@ -1,27 +1,27 @@
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plotting: True
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n_epochs: 1200
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logger_name: XENIUM
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logger_name: WIDEBOI
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save_model_summary: False
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batch_size: 1
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folds: 1
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dropout: True
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early_stopping:
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monitor: "val_loss"
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min_delta: 0.00
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min_delta: 0.00005
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patience: 10
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verbose: False
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mode: "min"
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log_transform: True # why is this not in the data section....
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seed: False
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seed: 888
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trainer:
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profiler: simple
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logger: True
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enable_checkpointing: True
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devices: ${gpus}
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accelerator: "gpu"
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strategy: "ddp"
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strategy: "fsdp"
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max_epochs: ${training.n_epochs}
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min_epochs: 0
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min_epochs: 150
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limit_train_batches: 1.0
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limit_val_batches: 1.0
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check_val_every_n_epoch: 1

‎examples/0v60_w_celltypes.ipynb‎

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‎examples/MAE.ipynb‎

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@@ -11,7 +11,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 3,
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"id": "going-danish",
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"metadata": {},
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"outputs": [],
@@ -39,197 +39,29 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 4,
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"id": "96bacff8",
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"metadata": {
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"scrolled": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[ 1.0e+00 -2.9e-01]\n",
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"ename": "KeyError",
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"evalue": "\"Unable to synchronously open object (object 'Animal_ID' doesn't exist)\"",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m train \u001b[38;5;241m=\u001b[39m \u001b[43mMerfishDataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m../data\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/spatial/spatial/merfish_dataset.py:43\u001b[0m, in \u001b[0;36mMerfishDataset.__init__\u001b[0;34m(self, root, pre_transform, n_neighbors, train, log_transform, include_celltypes, radius, non_response_genes_file, splits)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;66;03m# response genes (columns in MERFISH)\u001b[39;00m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mresponse_genes \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mset\u001b[39m(\u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m155\u001b[39m)) \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mset\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfeatures))\n\u001b[0;32m---> 43\u001b[0m data_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconstruct_graphs\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 44\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_neighbors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlog_transform\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minclude_celltypes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mradius\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplits\u001b[49m\n\u001b[1;32m 45\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 47\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m h5py\u001b[38;5;241m.\u001b[39mFile(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmerfish_hdf5, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m h5f:\n\u001b[1;32m 48\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgene_names \u001b[38;5;241m=\u001b[39m h5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgene_names\u001b[39m\u001b[38;5;124m\"\u001b[39m][:][\u001b[38;5;241m~\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbad_genes]\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mU\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
57+
"File \u001b[0;32m~/spatial/spatial/merfish_dataset.py:283\u001b[0m, in \u001b[0;36mMerfishDataset.construct_graphs\u001b[0;34m(self, n_neighbors, train, log_transform, include_celltypes, radius, splits)\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconstruct_graphs\u001b[39m(\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 271\u001b[0m n_neighbors,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 277\u001b[0m ):\n\u001b[1;32m 278\u001b[0m \u001b[38;5;66;03m# load hdf5\u001b[39;00m\n\u001b[1;32m 279\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m h5py\u001b[38;5;241m.\u001b[39mFile(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmerfish_hdf5, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m h5f:\n\u001b[1;32m 280\u001b[0m \u001b[38;5;66;03m# pylint: disable=no-member\u001b[39;00m\n\u001b[1;32m 282\u001b[0m data \u001b[38;5;241m=\u001b[39m types\u001b[38;5;241m.\u001b[39mSimpleNamespace(\n\u001b[0;32m--> 283\u001b[0m anids\u001b[38;5;241m=\u001b[39m\u001b[43mh5f\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mAnimal_ID\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m[:],\n\u001b[1;32m 284\u001b[0m bregs\u001b[38;5;241m=\u001b[39mh5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBregma\u001b[39m\u001b[38;5;124m\"\u001b[39m][:],\n\u001b[1;32m 285\u001b[0m expression\u001b[38;5;241m=\u001b[39mh5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mexpression\u001b[39m\u001b[38;5;124m\"\u001b[39m][:],\n\u001b[1;32m 286\u001b[0m locations\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mc_[h5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCentroid_X\u001b[39m\u001b[38;5;124m\"\u001b[39m][:], h5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCentroid_Y\u001b[39m\u001b[38;5;124m\"\u001b[39m][:]],\n\u001b[1;32m 287\u001b[0m behavior\u001b[38;5;241m=\u001b[39mh5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBehavior\u001b[39m\u001b[38;5;124m\"\u001b[39m][:]\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mU\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 288\u001b[0m celltypes\u001b[38;5;241m=\u001b[39mh5f[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCell_class\u001b[39m\u001b[38;5;124m\"\u001b[39m][:]\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mU\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 289\u001b[0m )\n\u001b[1;32m 291\u001b[0m \u001b[38;5;66;03m# see if you can update data locations AFTER data was created\u001b[39;00m\n\u001b[1;32m 292\u001b[0m \u001b[38;5;66;03m# create a deepcopy and then split the locations\u001b[39;00m\n\u001b[1;32m 293\u001b[0m \n\u001b[1;32m 294\u001b[0m \u001b[38;5;66;03m# get the (animal_id,bregma) pairs that define a unique slice\u001b[39;00m\n\u001b[1;32m 295\u001b[0m unique_slices \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39munique(np\u001b[38;5;241m.\u001b[39mc_[data\u001b[38;5;241m.\u001b[39manids, data\u001b[38;5;241m.\u001b[39mbregs], axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n",
58+
"File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
59+
"File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
60+
"File \u001b[0;32m~/.cache/pypoetry/virtualenvs/spatial-G_n0JvVf-py3.10/lib/python3.10/site-packages/h5py/_hl/group.py:357\u001b[0m, in \u001b[0;36mGroup.__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 355\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid HDF5 object reference\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 356\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(name, (\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m)):\n\u001b[0;32m--> 357\u001b[0m oid \u001b[38;5;241m=\u001b[39m \u001b[43mh5o\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_lapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 358\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAccessing a group is done with bytes or str, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 360\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnot \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mtype\u001b[39m(name)))\n",
61+
"File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
62+
"File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
63+
"File \u001b[0;32mh5py/h5o.pyx:189\u001b[0m, in \u001b[0;36mh5py.h5o.open\u001b[0;34m()\u001b[0m\n",
64+
"\u001b[0;31mKeyError\u001b[0m: \"Unable to synchronously open object (object 'Animal_ID' doesn't exist)\""
23365
]
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}
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],
@@ -5318,7 +5150,7 @@
53185150
],
53195151
"metadata": {
53205152
"kernelspec": {
5321-
"display_name": "Python 3 (ipykernel)",
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"display_name": "spatial-G_n0JvVf-py3.10",
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"language": "python",
53235155
"name": "python3"
53245156
},
@@ -5332,7 +5164,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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"version": "3.10.12"
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}
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},
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"nbformat": 4,

‎examples/recent_result.json‎

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{"result": 0.32090893387794495}
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{"result": 0.17702952027320862}

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