Increase test coverage

sccellfie/expression/tests/test_aggregation.py

@@ -27,12 +27,27 @@ def test_agg_expression_cells_specific_gene_present():
     adata.obs[groupby] = ['group1' if i < adata.n_obs // 2 else 'group2' for i in range(adata.n_obs)]
     gene_symbols = ['gene1', 'gene10']
 
+    # Test aggregation with one gene
+    agg_result = agg_expression_cells(adata, groupby, gene_symbols=gene_symbols[0], agg_func='mean')
+    assert agg_result.shape == (len(adata.obs[groupby].unique()), 1), "Shape mismatch"
+    assert gene_symbols[0] in agg_result.columns, "Missing gene in result"
+
     # Test aggregation with specific genes
     agg_result = agg_expression_cells(adata, groupby, gene_symbols=gene_symbols, agg_func='mean')
     assert agg_result.shape == (len(adata.obs[groupby].unique()), len(gene_symbols)), "Shape mismatch"
     assert all(gene in agg_result.columns for gene in gene_symbols), "Missing genes in result"
 
 
+def test_agg_expression_cells_layer():
+    adata = create_random_adata(layers='gene_scores')
+    groupby = 'group'
+    adata.obs[groupby] = ['group1' if i < adata.n_obs // 2 else 'group2' for i in range(adata.n_obs)]
+
+    # Test aggregation with one gene
+    agg_result = agg_expression_cells(adata, groupby, layer='gene_scores', agg_func='mean')
+    assert agg_result.shape == (len(adata.obs[groupby].unique()), adata.shape[1]), "Shape mismatch"
+
+
 def test_agg_expression_cells_invalid_agg_func():
     adata = create_random_adata()
     groupby = 'group'

sccellfie/tests/toy_inputs.py

@@ -12,6 +12,8 @@ def create_random_adata(n_obs=100, n_vars=50, layers=None):
     adata = sc.AnnData(X=X, obs=obs, var=var)
 
     if layers:
+        if isinstance(layers, str):
+            layers = [layers]
         for layer in layers:
             adata.layers[layer] = np.random.rand(n_obs, n_vars)
     return adata