add testdata for elevation with third station, and test for both min …

…and max elevation

src/pyaro/timeseries/Filter.py

@@ -830,11 +830,10 @@ class AltitudeFilter(StationReductionFilter):
 
     def __init__(self, min_altitude: float | None = None, max_altitude: float | None = None):
         """
-        :param min_altitude : float of minimum altitude in meters required to keep the station.
-        :param max_altitude : float of maximum altitude in meters required to keep the station.
+        :param min_altitude : float of minimum altitude in meters required to keep the station (inclusive).
+        :param max_altitude : float of maximum altitude in meters required to keep the station (inclusive).
 
-        Stations will be kept if min_altitude ≤ x ≤ max_altitude where x is the elevation of the
-        station. If station elevation is nan, it is always excluded.
+        If station elevation is nan, it is always excluded.
         """
         if min_altitude is not None and max_altitude is not None:
             if min_altitude > max_altitude:

tests/test_CSVTimeSeriesReader.py

@@ -32,6 +32,12 @@ class TestCSVTimeSeriesReader(unittest.TestCase):
         "datadir",
         "csvReader_testdata.csv",
     )
+    elevation_file = os.path.join(
+        os.path.dirname(os.path.realpath(__file__)),
+        "testdata",
+        "datadir_elevation",
+        "csvReader_testdata_elevation.csv",
+    )
     multifile = "glob:" + os.path.join(
         os.path.dirname(os.path.realpath(__file__)), "testdata", "datadir", "**/*.csv"
     )
@@ -417,7 +423,7 @@ def test_country_lookup(self):
     def test_altitude_filter_1(self):
         engines = pyaro.list_timeseries_engines()
         with engines["csv_timeseries"].open(
-            filename=self.file,
+            filename=self.elevation_file,
             filters=[pyaro.timeseries.filters.get("altitude", max_altitude=150)],
             columns={
                 "variable": 0,
@@ -439,8 +445,30 @@ def test_altitude_filter_1(self):
     def test_altitude_filter_2(self):
         engines = pyaro.list_timeseries_engines()
         with engines["csv_timeseries"].open(
-            filename=self.file,
-            filters=[pyaro.timeseries.filters.get("altitude", min_altitude=150)],
+            filename=self.elevation_file,
+            filters=[pyaro.timeseries.filters.get("altitude", min_altitude=250)],
+            columns={
+                "variable": 0,
+                "station": 1,
+                "longitude": 2,
+                "latitude": 3,
+                "value": 4,
+                "units": 5,
+                "start_time": 6,
+                "end_time": 7,
+                "altitude": 9,
+                "country": "NO",
+                "standard_deviation": "NaN",
+                "flag": "0",
+            }
+        ) as ts:
+            self.assertEqual(len(ts.stations()), 1)
+
+    def test_altitude_filter_3(self):
+        engines = pyaro.list_timeseries_engines()
+        with engines["csv_timeseries"].open(
+            filename=self.elevation_file,
+            filters=[pyaro.timeseries.filters.get("altitude", min_altitude=150, max_altitude=250)],
             columns={
                 "variable": 0,
                 "station": 1,