Run black formatting on python test scripts.

Run black formatting on python test scripts.

Author: ghuls

tests/test_aucell.py

@@ -8,18 +8,24 @@
 from pyscenic.aucell import aucell, create_rankings, derive_auc_threshold
 
 NOMENCLATURE = "HGNC"
-TEST_EXPRESSION_MTX_FNAME = resource_filename('resources.tests', "GSE103322.em.hgnc.sample.cxg.csv")
-TEST_SIGNATURE_FNAME = resource_filename('resources.tests', "c6.all.v6.1.symbols.gmt")
+TEST_EXPRESSION_MTX_FNAME = resource_filename(
+    "resources.tests", "GSE103322.em.hgnc.sample.cxg.csv"
+)
+TEST_SIGNATURE_FNAME = resource_filename("resources.tests", "c6.all.v6.1.symbols.gmt")
 
 
 @pytest.fixture
 def exp_matrix():
-    return pd.read_csv(TEST_EXPRESSION_MTX_FNAME, sep=',', header=0, index_col=0)
+    return pd.read_csv(TEST_EXPRESSION_MTX_FNAME, sep=",", header=0, index_col=0)
 
 
 @pytest.fixture
 def gs():
-    return GeneSignature.from_gmt(TEST_SIGNATURE_FNAME, gene_separator="\t", field_separator="\t", )
+    return GeneSignature.from_gmt(
+        TEST_SIGNATURE_FNAME,
+        gene_separator="\t",
+        field_separator="\t",
+    )
 
 
 def test_create_rankings(exp_matrix):
@@ -41,6 +47,8 @@ def test_aucell_w2(exp_matrix, gs):
 
 def test_aucell_mismatch(exp_matrix, gs):
     percentiles = derive_auc_threshold(exp_matrix)
-    gss = [GeneSignature(name="test", gene2weight=list(map("FAKE{}".format, range(100))))] + gs
+    gss = [
+        GeneSignature(name="test", gene2weight=list(map("FAKE{}".format, range(100))))
+    ] + gs
     aucs_mtx = aucell(exp_matrix, gss, auc_threshold=percentiles[0.01], num_workers=1)
     print(aucs_mtx.head())

tests/test_featureseq.py

@@ -5,29 +5,29 @@
 
 
 def test_feature_overlap():
-    f1 = Feature.from_string('chr1 12 50 feature1 10.0 +')
-    f2 = Feature.from_string('chr1 40 60 feature2 10.0 -')
-    f3 = Feature.from_string('chr1 60 80 feature2 10.0 -')
-    f4 = Feature.from_string('chr2 60 80 feature2 10.0 -')
+    f1 = Feature.from_string("chr1 12 50 feature1 10.0 +")
+    f2 = Feature.from_string("chr1 40 60 feature2 10.0 -")
+    f3 = Feature.from_string("chr1 60 80 feature2 10.0 -")
+    f4 = Feature.from_string("chr2 60 80 feature2 10.0 -")
     assert f1.has_overlap_with(f2)
     assert not f1.has_overlap_with(f3)
     assert not f3.has_overlap_with(f4)
     assert not f2.has_overlap_with(f3)
 
 
 def test_feature_contains():
-    f1 = Feature.from_string('chr1 50 60 feature1 10.0 +')
-    f2 = Feature.from_string('chr1 40 60 feature2 10.0 -')
-    f3 = Feature.from_string('chr2 40 80 feature2 10.0 -')
+    f1 = Feature.from_string("chr1 50 60 feature1 10.0 +")
+    f2 = Feature.from_string("chr1 40 60 feature2 10.0 -")
+    f3 = Feature.from_string("chr2 40 80 feature2 10.0 -")
     assert f1 in f2
     assert not f1 in f3
 
 
 def test_feature_bp_overlap():
-    f1 = Feature.from_string('chr1 12 50 feature1 10.0 +')
-    f2 = Feature.from_string('chr1 40 60 feature2 10.0 -')
-    f3 = Feature.from_string('chr1 60 80 feature2 10.0 -')
-    f4 = Feature.from_string('chr2 60 80 feature2 10.0 -')
+    f1 = Feature.from_string("chr1 12 50 feature1 10.0 +")
+    f2 = Feature.from_string("chr1 40 60 feature2 10.0 -")
+    f3 = Feature.from_string("chr1 60 80 feature2 10.0 -")
+    f4 = Feature.from_string("chr2 60 80 feature2 10.0 -")
     assert f1.get_overlap_in_bp_with(f2) == 10
     assert f1.get_overlap_in_bp_with(f3) == 0
     assert f2.get_overlap_in_bp_with(f3) == 0

tests/test_math.py

@@ -9,5 +9,7 @@
 def test_masked_rho():
     x = np.array([1, 2, -1, 0.0, 4], dtype=float)
     y = np.array([1, 2, 0.0, -8, 4], dtype=float)
-    assert pytest.approx(masked_rho(x, y, 0.0), 0.00001) == \
-           np.corrcoef(np.array([1.0, 2.0, 4.0]), np.array([1.0, 2.0, 4.0]))[0, 1]
+    assert (
+        pytest.approx(masked_rho(x, y, 0.0), 0.00001)
+        == np.corrcoef(np.array([1.0, 2.0, 4.0]), np.array([1.0, 2.0, 4.0]))[0, 1]
+    )