Fixed the current tests.

tests/create_sample_data_and_reference_results.py

@@ -135,14 +135,15 @@ def create_sample_data(sample_data_dir):
     values[np.random.default_rng().choice(values.size,
                                           size=int(0.085*values.size),
                                           replace=False)] = np.nan
-    pd.Series(values, datetime_index).to_csv(
+    pd.Series(values, datetime_index).dropna().to_csv(
         Path(sample_data_dir, "sample_data.csv"), header=False
     )
     Path(sample_data_dir, "sample_metadata.cfg").write_text(
         "[METADATA]\n"
         "station_lat: 50.906389\n"
         "station_lon: 6.403889\n"
-        "station_climatic_zone: 3\n"
+        "station_climatic_zone: 3\n",
+        encoding="utf-8"
     )
 
 

tests/test_toarstats.py

@@ -23,7 +23,7 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from toarstats import toarstats
+from toarstats.interface import calculate_statistics
 
 
 def get_all_statistics():
@@ -82,7 +82,8 @@ def sample_metadata():
     """
     parser = ConfigParser()
     with open(Path(Path(__file__).resolve().parent,
-                   "sample_data/sample_metadata.cfg")) as file:
+                   "sample_data/sample_metadata.cfg"),
+              encoding="utf-8") as file:
         parser.read_file(file)
     Metadata = namedtuple("Metadata", ["station_lat", "station_lon",
                                        "station_climatic_zone"])
@@ -110,19 +111,22 @@ def test_results_match_reference_results(statistic, sampling, sample_data,
                                          sample_metadata):
     """Test if the results match old package versions."""
     if statistic == "drmdmax1h" and sampling == "monthly":
-        with pytest.raises(ValueError, match="Invalid mtype"):
-            result = toarstats(sampling, [statistic], sample_data,
-                               sample_metadata)
+        with pytest.raises(ValueError, match="The drmdmax1h statistic cannot"
+                                             " be evaluated with monthly"
+                                             " sampling"):
+            result = calculate_statistics(sampling, statistic, sample_data,
+                                          sample_metadata)
     else:
-        result = toarstats(sampling, [statistic], sample_data, sample_metadata)
+        result = calculate_statistics(sampling, statistic, sample_data,
+                                      sample_metadata)
         for file in Path(
-                Path(__file__).resolve().parent, "reference_results"
+            Path(__file__).resolve().parent, "reference_results"
         ).rglob(f"{statistic}-{sampling}.csv"):
             expected_result = pd.read_csv(file, header=None, index_col=0,
                                           parse_dates=True)
             pd.testing.assert_index_equal(result.index, expected_result.index,
                                           check_names=False)
-            if statistic == "w90":
+            if statistic == "w90" and sampling == "seasonal":
                 with pytest.raises(AssertionError):
                     np.testing.assert_allclose(result.values,
                                                expected_result.values,