Fixed some tests so that they are easier to read

chainladder/adjustments/tests/test_trend.py

@@ -1,13 +1,40 @@
 import chainladder as cl
+import numpy as np
+
 
 def test_trend1(clrd):
-    tri = clrd[['CumPaidLoss', 'EarnedPremDIR']].sum()
-    assert (
-        cl.CapeCod(.05).fit(tri['CumPaidLoss'], sample_weight=tri['EarnedPremDIR'].latest_diagonal).ibnr_ ==
-        cl.CapeCod().fit(cl.Trend(.05).fit_transform(tri['CumPaidLoss']), sample_weight=tri['EarnedPremDIR'].latest_diagonal).ibnr_)
+    tri = clrd[["CumPaidLoss", "EarnedPremDIR"]].sum()
+    lhs = (
+        cl.CapeCod(0.05)
+        .fit(tri["CumPaidLoss"], sample_weight=tri["EarnedPremDIR"].latest_diagonal)
+        .ibnr_
+    )
+    rhs = (
+        cl.CapeCod()
+        .fit(
+            cl.Trend(0.05).fit_transform(tri["CumPaidLoss"]),
+            sample_weight=tri["EarnedPremDIR"].latest_diagonal,
+        )
+        .ibnr_
+    )
+    assert np.round(lhs, 0) == np.round(rhs, 0)
+
 
 def test_trend2(raa):
     tri = raa
-    assert abs(
-        cl.Trend(trends=[.05, .05], dates=[(None, '1985'), ('1985', None)], axis='origin').fit(tri).trend_*tri -
-        tri.trend(.05, axis='origin')).sum().sum() < 1e-6
+    assert (
+        abs(
+            cl.Trend(
+                trends=[0.05, 0.05],
+                dates=[(None, "1985"), ("1985", None)],
+                axis="origin",
+            )
+            .fit(tri)
+            .trend_
+            * tri
+            - tri.trend(0.05, axis="origin")
+        )
+        .sum()
+        .sum()
+        < 1e-6
+    )