From 6542acbceb0d04c229c9c0fbec81479f8d91c528 Mon Sep 17 00:00:00 2001
From: Luke Zappia <luke@data-intuitive.com>
Date: Fri, 8 Nov 2024 11:56:07 +0100
Subject: [PATCH] Style hvg overlap script

---
 src/metrics/hvg_overlap/script.py | 59 ++++++++++++++-----------------
 1 file changed, 26 insertions(+), 33 deletions(-)

diff --git a/src/metrics/hvg_overlap/script.py b/src/metrics/hvg_overlap/script.py
index 61e980c..2db0f9b 100644
--- a/src/metrics/hvg_overlap/script.py
+++ b/src/metrics/hvg_overlap/script.py
@@ -1,4 +1,5 @@
 import sys
+
 import anndata as ad
 import numpy as np
 import scanpy as sc
@@ -7,37 +8,30 @@
 
 ## VIASH START
 par = {
-    'input_integrated': 'resources_test/task_batch_integration/cxg_immune_cell_atlas/integrated_full.h5ad',
-    'input_solution': 'resources_test/task_batch_integration/cxg_immune_cell_atlas/solution.h5ad',
-    'output': 'output.h5ad',
-}
-meta = {
-    'name': 'foo',
-    "resources_dir": "src/utils"
+    "input_integrated": "resources_test/task_batch_integration/cxg_immune_cell_atlas/integrated_full.h5ad",
+    "input_solution": "resources_test/task_batch_integration/cxg_immune_cell_atlas/solution.h5ad",
+    "output": "output.h5ad",
 }
+meta = {"name": "foo", "resources_dir": "src/utils"}
 ## VIASH END
 
 sys.path.append(meta["resources_dir"])
 from read_anndata_partial import read_anndata
 
-print('Read input', flush=True)
+print("Read input", flush=True)
 adata_solution = read_anndata(
-    par['input_solution'],
-    X='layers/normalized',
-    obs='obs',
-    var='var',
-    uns='uns'
+    par["input_solution"], X="layers/normalized", obs="obs", var="var", uns="uns"
 )
 adata_integrated = read_anndata(
-    par['input_integrated'],
-    X='layers/corrected_counts',
-    obs='obs',
-    var='var',
-    uns='uns'
+    par["input_integrated"],
+    X="layers/corrected_counts",
+    obs="obs",
+    var="var",
+    uns="uns",
 )
 
 print("Copy batch information", flush=True)
-adata_integrated.obs['batch'] = adata_solution.obs['batch']
+adata_integrated.obs["batch"] = adata_solution.obs["batch"]
 
 print("Remove batches with insufficient genes", flush=True)
 adata_list = split_batches(adata_solution, "batch", hvg=adata_integrated.var_names)
@@ -47,27 +41,26 @@
     n_hvg_tmp = np.minimum(500, int(0.5 * adata_batch.n_vars))
     if n_hvg_tmp < 500:
         batch = adata_batch.obs["batch"][0]
-        print(f"Batch '{batch}' has insufficient genes (0.5 * {adata_batch.n_vars} < 500) and will be skipped", flush=True)
+        print(
+            f"Batch '{batch}' has insufficient genes (0.5 * {adata_batch.n_vars} < 500) and will be skipped",
+            flush=True,
+        )
         skip_batches.append(batch)
 
-adata_solution = adata_solution[~adata_solution.obs['batch'].isin(skip_batches)]
-adata_integrated = adata_integrated[~adata_integrated.obs['batch'].isin(skip_batches)]
+adata_solution = adata_solution[~adata_solution.obs["batch"].isin(skip_batches)]
+adata_integrated = adata_integrated[~adata_integrated.obs["batch"].isin(skip_batches)]
 
-print('Compute score', flush=True)
-score = hvg_overlap(
-    adata_solution,
-    adata_integrated,
-    batch_key="batch"
-)
+print("Compute score", flush=True)
+score = hvg_overlap(adata_solution, adata_integrated, batch_key="batch")
 
 print("Create output AnnData object", flush=True)
 output = ad.AnnData(
     uns={
-        "dataset_id": adata_solution.uns['dataset_id'],
-        'normalization_id': adata_solution.uns['normalization_id'],
-        "method_id": adata_integrated.uns['method_id'],
-        "metric_ids": [meta['name']],
-        "metric_values": [score]
+        "dataset_id": adata_solution.uns["dataset_id"],
+        "normalization_id": adata_solution.uns["normalization_id"],
+        "method_id": adata_integrated.uns["method_id"],
+        "metric_ids": [meta["name"]],
+        "metric_values": [score],
     }
 )