fix: lint

pyposeidon/telemac.py

@@ -194,13 +194,19 @@ def write_netcdf(ds, outpath):
 
 
 def extract_t_elev_2D(
-    ds: xr.Dataset, x: float, y: float, var: str = "elev", xstr: str = "longitude", ystr: str = "latitude", max_dist: float = 1000,
+    ds: xr.Dataset,
+    x: float,
+    y: float,
+    var: str = "elev",
+    xstr: str = "longitude",
+    ystr: str = "latitude",
+    max_dist: float = 1000,
 ):
     lons, lats = ds[xstr].values, ds[ystr].values
-    mesh = pd.DataFrame(np.vstack([x, y]).T, columns = ["lon", "lat"])
-    points = pd.DataFrame(np.vstack([lons, lats]).T, columns = ["lon", "lat"])
+    mesh = pd.DataFrame(np.vstack([x, y]).T, columns=["lon", "lat"])
+    points = pd.DataFrame(np.vstack([lons, lats]).T, columns=["lon", "lat"])
     df = find_nearest_nodes(mesh, points, 1)
-    df  = df[df.distance < max_dist]
+    df = df[df.distance < max_dist]
     indx = df["mesh_index"]
     ds_ = ds.isel(node=indx.values[0])
     out_ = ds_[var].values
@@ -1102,7 +1108,7 @@ def run(self, api=True, **kwargs):
             return
 
         if self.fortran:
-            user_fortran = 'user_fortran'
+            user_fortran = "user_fortran"
         else:
             user_fortran = None
 
@@ -1430,16 +1436,10 @@ def set_obs(self, **kwargs):
             return
 
         mesh = pd.DataFrame(
-            np.array(
-                [
-                    self.mesh.Dataset.SCHISM_hgrid_node_x.values,
-                    self.mesh.Dataset.SCHISM_hgrid_node_y.values
-                ]
-            ).T,
-            columns = ["lon", "lat"])
-        points = pd.DataFrame(
-            np.array([tgn.longitude.values, tgn.latitude.values]).T,
-            columns = ["lon", "lat"])
+            np.array([self.mesh.Dataset.SCHISM_hgrid_node_x.values, self.mesh.Dataset.SCHISM_hgrid_node_y.values]).T,
+            columns=["lon", "lat"],
+        )
+        points = pd.DataFrame(np.array([tgn.longitude.values, tgn.latitude.values]).T, columns=["lon", "lat"])
         df = find_nearest_nodes(mesh, points, 1)
         df = df[df.distance < max_dist]
 
@@ -1453,7 +1453,7 @@ def set_obs(self, **kwargs):
 
         # convert to MERCATOR coordinates
         # dirty fix (this needs to be fixed in TELEMAC directly)
-        x, y = longlat2spherical(df["lon"], df["lat"],0,0)
+        x, y = longlat2spherical(df["lon"], df["lat"], 0, 0)
         df["x"] = x
         df["y"] = y
 

pyposeidon/utils/cfl.py

@@ -103,9 +103,7 @@ def parse_hgrid(path: os.PathLike[str] | str) -> dict[str, T.Any]:
         no_closed_boundaries = int(fd.readline().split(b"=")[0].strip())
         total_closed_boundary_nodes = int(fd.readline().split(b"=")[0].strip())
         for i in range(no_closed_boundaries):
-            no_nodes_in_boundary, boundary_type = map(
-                int, (fd.readline().split(b"=")[0].strip().split(b" "))
-            )
+            no_nodes_in_boundary, boundary_type = map(int, (fd.readline().split(b"=")[0].strip().split(b" ")))
             boundary_nodes = np.fromiter(
                 fd,
                 count=no_nodes_in_boundary,

pyposeidon/utils/cpoint.py

@@ -101,6 +101,4 @@ def find_nearest_nodes(
         .assign(distance=(distances.flatten() * earth_radius))
         .reset_index(names=["mesh_index"])
     )
-    return pd.concat(
-        (points.loc[points.index.repeat(k)].reset_index(drop=True), closest_nodes), axis="columns"
-    )
+    return pd.concat((points.loc[points.index.repeat(k)].reset_index(drop=True), closest_nodes), axis="columns")

pyposeidon/utils/obs.py

@@ -1,4 +1,5 @@
 """ Observational Data retrieval """
+
 from __future__ import annotations
 
 import itertools
@@ -152,14 +153,27 @@ def serialize_stations(
         msg = f"stations must have these columns too: {mandatory_cols.difference(df_cols)}"
         raise ValueError(msg)
     #
-    basic_cols = ["mesh_lon", "mesh_lat", "z", "separator", "unique_id", "mesh_index", "lon", "lat", "depth", "distance"]
+    basic_cols = [
+        "mesh_lon",
+        "mesh_lat",
+        "z",
+        "separator",
+        "unique_id",
+        "mesh_index",
+        "lon",
+        "lat",
+        "depth",
+        "distance",
+    ]
     station_in = stations.assign(
         z=0,
         separator="\t!\t",
     )
-    station_in = station_in.set_index(station_in.index +1)
+    station_in = station_in.set_index(station_in.index + 1)
     station_in = station_in[basic_cols]
     with open(f"{path}", "w") as fd:
-        fd.write(f"{schism_station_flag.strip()}\t ! https://schism-dev.github.io/schism/master/input-output/optional-inputs.html#stationin-bp-format\n")
+        fd.write(
+            f"{schism_station_flag.strip()}\t ! https://schism-dev.github.io/schism/master/input-output/optional-inputs.html#stationin-bp-format\n"
+        )
         fd.write(f"{len(station_in)}\t ! number of stations\n")
         station_in.to_csv(fd, header=None, sep=" ", float_format="%.10f")

pyposeidon/utils/pplot.py

@@ -23,6 +23,7 @@
 
 import sys
 import os
+
 # from pyposeidon.tools import to_geodataframe
 
 ffmpeg = sys.exec_prefix + "/bin/ffmpeg"

tests/test_telemac.py

@@ -79,7 +79,7 @@
     },
 }
 
-case4 = { # test does not work with telemac3d: mesh quality is too bad
+case4 = {  # test does not work with telemac3d: mesh quality is too bad
     "solver_name": "telemac",
     "mesh_file": MESH_FILE,
     "module": "telemac3d",

tests/utils/test_cpoint.py

@@ -11,19 +11,23 @@
 
 @pytest.fixture(scope="session")
 def mesh_nodes():
-    return pd.DataFrame({
-        "lon": [0, 10, 20],
-        "lat": [0, 5, 0],
-    })
+    return pd.DataFrame(
+        {
+            "lon": [0, 10, 20],
+            "lat": [0, 5, 0],
+        }
+    )
 
 
 @pytest.fixture(scope="session")
 def points():
-    return pd.DataFrame({
-        "lon": [1, 11, 21, 2],
-        "lat": [1, 4, 1, 2],
-        "id": ["a", "b", "c", "d"],
-    })
+    return pd.DataFrame(
+        {
+            "lon": [1, 11, 21, 2],
+            "lat": [1, 4, 1, 2],
+            "id": ["a", "b", "c", "d"],
+        }
+    )
 
 
 @pytest.fixture(scope="session")
@@ -41,7 +45,7 @@ def test_find_nearest_nodes(mesh_nodes, points):
     assert nearest_nodes.distance.max() < 320_000
 
 
-@pytest.mark.parametrize("k", [pytest.param(2, id='2 points'), pytest.param(3, id='3 points')])
+@pytest.mark.parametrize("k", [pytest.param(2, id="2 points"), pytest.param(3, id="3 points")])
 def test_find_nearest_nodes_multiple_points_and_pass_tree_as_argument(mesh_nodes, points, k, ball_tree):
     nearest_nodes = find_nearest_nodes(mesh_nodes, points, k=k, tree=ball_tree)
     assert isinstance(nearest_nodes, pd.DataFrame)

tests/utils/test_obs.py

@@ -17,17 +17,19 @@ def test_serialize_stations(tmp_path):
         3 20.0000000000 0.0000000000 0 	!	 c 2 21.0000000000 1.0000000000 1 157249.3812719441
         """
     )
-    stations = pd.DataFrame({
-        'lon': [1., 11., 21.],
-        'lat': [1., 4., 1.],
-        'unique_id': ["a", "b", "c"],
-        'extra_col': ["AA", "BB", "CC"],
-        'mesh_index': [0, 1, 2],
-        'mesh_lon': [0., 10., 20.],
-        'mesh_lat': [0., 5., 0.],
-        'distance': [157249.38127194397, 157010.16264060183, 157249.38127194406],
-        'depth': [3, 5, 1],
-    })
+    stations = pd.DataFrame(
+        {
+            "lon": [1.0, 11.0, 21.0],
+            "lat": [1.0, 4.0, 1.0],
+            "unique_id": ["a", "b", "c"],
+            "extra_col": ["AA", "BB", "CC"],
+            "mesh_index": [0, 1, 2],
+            "mesh_lon": [0.0, 10.0, 20.0],
+            "mesh_lat": [0.0, 5.0, 0.0],
+            "distance": [157249.38127194397, 157010.16264060183, 157249.38127194406],
+            "depth": [3, 5, 1],
+        }
+    )
     path = tmp_path / "station.in"
     serialize_stations(stations, path)
     contents = path.read_text()