updated tests

Deltares-research · Oct 8, 2024 · b974eed · b974eed
1 parent a6fffd2
commit b974eed
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Showing 5 changed files with 303 additions and 104 deletions.
diff --git a/tests/test_data_retrieve.py b/tests/test_data_retrieve.py
@@ -33,10 +33,10 @@ def test_drop_duplicate_times(df_meas_2010, caplog):
 
     assert len(meas_duplicated) == 105120
     assert len(meas_clean) == 52560
-    
+
     # assert logging messages
-    assert '52530 rows with duplicated time-value-combinations dropped' in caplog.text
-    assert '30 rows with duplicated times dropped' in caplog.text
+    assert "52530 rows with duplicated time-value-combinations dropped" in caplog.text
+    assert "30 rows with duplicated times dropped" in caplog.text
 
 
 @pytest.mark.unittest
@@ -45,7 +45,7 @@ def test_drop_duplicate_times_noaction(df_meas_2010, caplog):
 
     assert len(df_meas_2010) == 52560
     assert len(meas_clean) == 52560
-    
+
     # assert that there is no logging messages
     assert caplog.text == ""
 

diff --git a/tests/test_overschrijding.py b/tests/test_overschrijding.py
@@ -68,15 +68,15 @@ def test_calc_overschrijding(df_ext_12_2010_2014):
     expected_values = np.array(
         [
             1.93,
-            2.09327434,
-            2.26311592,
-            2.44480348,
-            2.70434509,
-            2.91627091,
-            3.14247786,
-            3.46480369,
-            3.72735283,
-            4.00701551,
+            2.09356726,
+            2.2637632,
+            2.44533302,
+            2.70383299,
+            2.91416492,
+            3.13795447,
+            3.45560027,
+            3.71330277,
+            3.98682045,
         ]
     )
     assert np.allclose(dist["geinterpoleerd"].values, expected_values)
@@ -96,11 +96,24 @@ def test_calc_overschrijding_with_hydra(df_ext_12_2010_2014):
         1 / 100,
         1 / 200,
     ]
-    hydra_values = np.array([2.473, 3.18 , 4.043, 4.164, 4.358, 4.696, 5.056, 5.468, 5.865,
-           6.328, 7.207])
-    hydra_index = np.array([1.00000000e+00, 1.00000000e-01, 2.00000000e-02, 1.00000000e-02,
-           3.33333333e-03, 1.00000000e-03, 3.33333333e-04, 1.00000000e-04,
-           3.33333333e-05, 1.00000000e-05, 1.00000000e-06])
+    hydra_values = np.array(
+        [2.473, 3.18, 4.043, 4.164, 4.358, 4.696, 5.056, 5.468, 5.865, 6.328, 7.207]
+    )
+    hydra_index = np.array(
+        [
+            1.00000000e00,
+            1.00000000e-01,
+            2.00000000e-02,
+            1.00000000e-02,
+            3.33333333e-03,
+            1.00000000e-03,
+            3.33333333e-04,
+            1.00000000e-04,
+            3.33333333e-05,
+            1.00000000e-05,
+            1.00000000e-06,
+        ]
+    )
     ser_hydra = pd.Series(hydra_values, index=hydra_index)
     ser_hydra.attrs = df_ext_12_2010_2014.attrs
     dist_hydra = {"Hydra-NL": ser_hydra}
@@ -121,12 +134,12 @@ def test_calc_overschrijding_with_hydra(df_ext_12_2010_2014):
     expected_values = np.array(
         [
             1.93,
-            2.09327434,
-            2.26311587,
-            2.46299612,
-            2.79965222,
-            3.08436295,
-            3.4987347,
+            2.09356726,
+            2.26376316,
+            2.46348569,
+            2.79932582,
+            3.08359924,
+            3.49814949,
             4.043,
             4.164,
             4.3095,
@@ -227,20 +240,18 @@ def test_calc_overschrijding_clip_physical_break(df_ext_12_2010_2014):
     expected_values_normal = np.array(
         [
             1.93,
-            2.09327434,
-            2.26311592,
-            2.44480348,
-            2.70434509,
-            2.91627091,
-            3.14247786,
-            3.46480369,
-            3.72735283,
-            4.00701551,
+            2.09356726,
+            2.2637632,
+            2.44533302,
+            2.70383299,
+            2.91416492,
+            3.13795447,
+            3.45560027,
+            3.71330277,
+            3.98682045,
         ]
     )
-    assert np.allclose(
-        dist_normal["geinterpoleerd"].values, expected_values_normal
-    )
+    assert np.allclose(dist_normal["geinterpoleerd"].values, expected_values_normal)
     expected_values_clip = np.array(
         [
             1.93,
@@ -255,9 +266,7 @@ def test_calc_overschrijding_clip_physical_break(df_ext_12_2010_2014):
             3.90683996,
         ]
     )
-    assert np.allclose(
-        dist_clip["geinterpoleerd"].values, expected_values_clip
-    )
+    assert np.allclose(dist_clip["geinterpoleerd"].values, expected_values_clip)
 
 
 @pytest.mark.unittest

diff --git a/tests/test_slotgemiddelden.py b/tests/test_slotgemiddelden.py
@@ -69,14 +69,18 @@ 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])
+    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]
+    )
     assert np.allclose(
         slotgemiddelden_dict_inclext["wl_mean_peryear"].values, wl_mean_peryear_expected
     )
@@ -88,17 +92,21 @@ def test_calc_slotgemiddelden(df_meas_2010_2014, df_ext_12_2010_2014):
     )
     assert np.allclose(
         slotgemiddelden_dict_inclext["tidalrange_mean_peryear"].values,
-        range_mean_peryear_expected
+        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])
+    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]
+    )
     assert np.allclose(
         slotgemiddelden_dict_inclext["wl_model_fit"].values, wl_model_fit_expected
     )
@@ -109,8 +117,8 @@ def test_calc_slotgemiddelden(df_meas_2010_2014, df_ext_12_2010_2014):
         slotgemiddelden_dict_inclext["LW_model_fit"].values, lw_model_fit_expected
     )
     assert np.allclose(
-        slotgemiddelden_dict_inclext["tidalrange_model_fit"].values, 
-        range_model_fit_expected
+        slotgemiddelden_dict_inclext["tidalrange_model_fit"].values,
+        range_model_fit_expected,
     )