ruff fix

chainladder/core/base.py

@@ -601,7 +601,7 @@ def _drop_subtriangles(self):
             del self.sigma_
         if "std_err_" in sub_tris:
             del self.std_err_
-        #w_ is currently stored as an ndarray
+        # w_ is currently stored as an ndarray
         if hasattr(self, "w_"):
             del self.w_
 

chainladder/utils/data/_manifest.py

@@ -268,7 +268,16 @@
         "origin": "Accident Year",
         "development": "Calendar Year",
         "index": None,
-        "columns": ["Paid Claims", "Reported Claims", "Closed Claim Counts", "Reported Claim Counts", "Case Outstanding", "Reported Severities", "Earned Premium","Incremental Paid Severity"],
+        "columns": [
+            "Paid Claims",
+            "Reported Claims",
+            "Closed Claim Counts",
+            "Reported Claim Counts",
+            "Case Outstanding",
+            "Reported Severities",
+            "Earned Premium",
+            "Incremental Paid Severity"
+        ],
         "cumulative": True,
     },
     "genins": {

chainladder/utils/tests/test_utilities.py

@@ -12,7 +12,6 @@
 from chainladder import (
     __dt64_unit__
 )
-from chainladder.utils.utility_functions import date_delta_adjustment
 from chainladder.utils.data._manifest import SAMPLES
 from chainladder.utils.utility_functions import (
     date_delta_adjustment,
@@ -59,7 +58,6 @@
 
 
 def test_triangle_json_io(clrd):
-    xp = clrd.get_array_module()
     clrd2 = cl.read_json(clrd.to_json(), array_backend=clrd.array_backend)
     assert clrd == clrd2
     assert np.all(clrd.kdims == clrd2.kdims)
@@ -153,7 +151,7 @@
     )
 
 
-def test_model_diagnostics_erorr(raa,atol):
+def test_model_diagnostics_erorr(raa, atol):
     with pytest.raises(ValueError):
         cl.model_diagnostics(raa)
     dev = cl.Development().fit_transform(raa)
@@ -162,7 +160,7 @@
     md = cl.model_diagnostics(est)
     assert np.allclose(
         md['Run Off 1'].values,
-        emerg[emerg.valuation.year==1991].latest_diagonal.values,
+        emerg[emerg.valuation.year == 1991].latest_diagonal.values,
         atol=atol,
         equal_nan=True
     )
@@ -186,18 +184,18 @@
     )
 
 
-def test_model_diagnostics_groupby(prism,atol):
+def test_model_diagnostics_groupby(prism, atol):
     dev = cl.Development().fit(prism["Incurred"].sum())
     est = cl.Chainladder().fit(dev.transform(prism["Incurred"]))
-    lhs = cl.model_diagnostics(est,groupby=['Line'])
+    lhs = cl.model_diagnostics(est, groupby=['Line'])
     rhs = cl.model_diagnostics(cl.Chainladder().fit(dev.transform(prism["Incurred"].groupby('Line').sum())))
-    assert np.allclose(lhs['Ultimate'].values,rhs['Ultimate'].values,atol=atol,equal_nan=True)
-    assert np.allclose(np.nan_to_num(lhs['IBNR'].values),np.nan_to_num(rhs['IBNR'].values),atol=atol,equal_nan=True)
+    assert np.allclose(lhs['Ultimate'].values,rhs['Ultimate'].values,atol=atol, equal_nan=True)
+    assert np.allclose(np.nan_to_num(lhs['IBNR'].values),np.nan_to_num(rhs['IBNR'].values),atol=atol, equal_nan=True)
 
 
 def test_concat_immutability(raa):
     u = cl.Chainladder().fit(raa).ultimate_
     l = raa.latest_diagonal
     u.columns = l.columns
     u_new = copy.deepcopy(u)
     cl.concat((l, u), axis=3)
@@ -682,7 +680,7 @@
     """
     options = cl.Options()
     assert options.ARRAY_BACKEND == "numpy"
     assert options.AUTO_SPARSE == True
     assert options.ARRAY_PRIORITY == ["dask", "sparse", "cupy", "numpy"]
     assert isinstance(options.ULT_VAL, str)
 
@@ -1273,5 +1271,5 @@
     Testing new path that allows weights on full triangles
     '''
     ult = cl.Chainladder().fit(raa)
     tw = cl.TriangleWeight(n_periods = 4).fit(raa)
     tw_full = cl.TriangleWeight(n_periods = 4).fit(ult.full_triangle_)