style code

Author: rcannood

src/methods/scprint/script.py

@@ -9,16 +9,12 @@
 import os
 
 ## VIASH START
-# Note: this section is auto-generated by viash at runtime. To edit it, make changes
-# in config.vsh.yaml and then run `viash config inject config.vsh.yaml`.
 par = {
-  'input': 'resources_test/.../input.h5ad',
-  'output': 'output.h5ad',
-  "model": "large",
-}
-meta = {
-  'name': 'scprint'
+    "input": "resources_test/.../input.h5ad",
+    "output": "output.h5ad",
+    "model": "large",
 }
+meta = {"name": "scprint"}
 ## VIASH END
 
 sys.path.append(meta["resources_dir"])
@@ -33,35 +29,36 @@
 elif input.uns["dataset_organism"] == "mus_musculus":
     input.obs["organism_ontology_term_id"] = "NCBITaxon:10090"
 else:
-    raise ValueError(f"scPRINT requires human or mouse data, not '{input.uns['dataset_organism']}'")
+    raise ValueError(
+        f"scPRINT requires human or mouse data, not '{input.uns['dataset_organism']}'"
+    )
 adata = input.copy()
 
-print('\n>>> Preprocessing data...', flush=True)
+print("\n>>> Preprocessing data...", flush=True)
 preprocessor = Preprocessor(
     # Lower this threshold for test datasets
-    min_valid_genes_id = 1000 if input.n_vars < 2000 else 10000,
+    min_valid_genes_id=1000 if input.n_vars < 2000 else 10000,
     # Turn off cell filtering to return results for all cells
-    filter_cell_by_counts = False,
-    min_nnz_genes = False,
+    filter_cell_by_counts=False,
+    min_nnz_genes=False,
     do_postp=False,
     # Skip ontology checks
-    skip_validate=True
+    skip_validate=True,
 )
 adata = preprocessor(adata)
 
 print(f"\n>>> Downloading '{par['model']}' model...", flush=True)
 model_checkpoint_file = hf_hub_download(
-    repo_id="jkobject/scPRINT",
-    filename=f"{par['model']}.ckpt"
+    repo_id="jkobject/scPRINT", filename=f"{par['model']}.ckpt"
 )
 print(f"Model checkpoint file: '{model_checkpoint_file}'", flush=True)
 model = scPrint.load_from_checkpoint(
     model_checkpoint_file,
-    transformer = "normal", # Don't use this for GPUs with flashattention
-    precpt_gene_emb = None
+    transformer="normal",  # Don't use this for GPUs with flashattention
+    precpt_gene_emb=None,
 )
 
-print('\n>>> Embedding data...', flush=True)
+print("\n>>> Embedding data...", flush=True)
 if torch.cuda.is_available():
     print("CUDA is available, using GPU", flush=True)
     precision = "16"
@@ -77,10 +74,10 @@
     max_len=4000,
     add_zero_genes=0,
     num_workers=n_cores_available,
-    doclass = False,
-    doplot = False,
-    precision = precision,
-    dtype = dtype,
+    doclass=False,
+    doplot=False,
+    precision=precision,
+    dtype=dtype,
 )
 embedded, _ = embedder(model, adata, cache=False)