reverted formatting

Deltares-research · Oct 8, 2024 · 177a7bb · 177a7bb
1 parent 017d4d7
commit 177a7bb
Showing 1 changed file with 20 additions and 24 deletions.
diff --git a/tests/test_slotgemiddelden.py b/tests/test_slotgemiddelden.py
@@ -69,18 +69,16 @@ def test_calc_slotgemiddelden(df_meas_2010_2014, df_ext_12_2010_2014):
     assert set(slotgemiddelden_dict_noext.keys()) == set(expected_keys_noext)
 
     # assertion of values
-    wl_mean_peryear_expected = np.array(
-        [0.07960731, 0.08612119, 0.0853051, 0.07010864, 0.10051922]
-    )
-    hw_mean_peryear_expected = np.array(
-        [1.13968839, 1.12875177, 1.13988685, 1.1415461, 1.18998584]
-    )
-    lw_mean_peryear_expected = np.array(
-        [-0.60561702, -0.59089362, -0.59342291, -0.61334278, -0.58024113]
-    )
-    range_mean_peryear_expected = np.array(
-        [1.74530541, 1.71964539, 1.73330976, 1.75488888, 1.77022697]
-    )
+    # fmt: off
+    wl_mean_peryear_expected = np.array([0.07960731, 0.08612119, 0.0853051,
+                                         0.07010864, 0.10051922])
+    hw_mean_peryear_expected = np.array([1.13968839, 1.12875177, 1.13988685,
+                                         1.1415461, 1.18998584])
+    lw_mean_peryear_expected = np.array([-0.60561702, -0.59089362, -0.59342291,
+                                         -0.61334278, -0.58024113])
+    range_mean_peryear_expected = np.array([1.74530541, 1.71964539, 1.73330976,
+                                            1.75488888, 1.77022697])
+    # fmt: on
     assert np.allclose(
         slotgemiddelden_dict_inclext["wl_mean_peryear"].values, wl_mean_peryear_expected
     )
@@ -95,18 +93,16 @@ def test_calc_slotgemiddelden(df_meas_2010_2014, df_ext_12_2010_2014):
         range_mean_peryear_expected,
     )
 
-    wl_model_fit_expected = np.array(
-        [0.0141927, 0.08612119, 0.0853051, 0.07010864, 0.10051922, 0.23137634]
-    )
-    hw_model_fit_expected = np.array(
-        [1.05295416, 1.12875177, 1.13988685, 1.1415461, 1.18998584, 1.336182]
-    )
-    lw_model_fit_expected = np.array(
-        [-0.67420399, -0.59089362, -0.59342291, -0.61334278, -0.58024113, -0.42969074]
-    )
-    range_model_fit_expected = np.array(
-        [1.72715816, 1.71964539, 1.73330976, 1.75488888, 1.77022697, 1.76587273]
-    )
+    # fmt: off
+    wl_model_fit_expected = np.array([0.0141927, 0.08612119, 0.0853051,
+                                      0.07010864, 0.10051922, 0.23137634])
+    hw_model_fit_expected = np.array([1.05295416, 1.12875177, 1.13988685,
+                                      1.1415461, 1.18998584, 1.336182])
+    lw_model_fit_expected = np.array([-0.67420399, -0.59089362, -0.59342291,
+                                      -0.61334278, -0.58024113, -0.42969074])
+    range_model_fit_expected = np.array([1.72715816, 1.71964539, 1.73330976,
+                                         1.75488888, 1.77022697, 1.76587273])
+    # fmt: on
     assert np.allclose(
         slotgemiddelden_dict_inclext["wl_model_fit"].values, wl_model_fit_expected
     )