Area plot clean up

oceannavigator/dataset_config.py

@@ -39,19 +39,15 @@ def _get_dataset_config() -> dict:
                 f"Loaded dataset config file from: {settings.dataset_config_file}"
             )
 
-        for name in config: 
+        for name in config:
             stub_file = f"{settings.dataset_config_stub_path}{name}.json"
 
-            with open(stub_file, "r") as f: 
+            with open(stub_file, "r") as f:
                 config[name] = json.load(f)[name]
-                log().debug(
-                    f"Loaded stub dataset config file from: {stub_file}"
-                )
+                log().debug(f"Loaded stub dataset config file from: {stub_file}")
 
         return config
 
-
-
     def _get_attribute(self, key: str) -> Union[str, dict]:
         return self._config.get(key) if not None else ""
 
@@ -369,14 +365,14 @@ def scale(self) -> list:
             return [self._variable.valid_min, self._variable.valid_max]
         else:
             return [0, 100]
-        
+
     @property
     def data_categories(self) -> list | None:
         """
         Returns ordered category labels for discrete/categorical variables.
         """
         try:
-            return self.__get_attribute('data_categories')
+            return self.__get_attribute("data_categories")
         except KeyError:
             return None
 

oceannavigator/frontend/src/components/data-selectors/TimeSlider.jsx

@@ -409,8 +409,6 @@ function TimeSlider({ id, dataset, timestamps, selected, onChange }) {
     />
   ));
 
-  console.log(dataset.id, timestamps.length, thumbLeft, selectedIndex);
-
   return (
     <div
       className="time-slider"

plotting/map.py

@@ -6,7 +6,6 @@
 import threading
 import tempfile
 from textwrap import wrap
-from typing import Union
 
 import cartopy.crs as ccrs
 import cartopy.feature as cfeature
@@ -17,7 +16,7 @@
 from matplotlib.patches import Patch, PathPatch, Polygon
 from matplotlib.path import Path
 from osgeo import gdal, osr
-from shapely.geometry import box, LinearRing, MultiPolygon, Point, Polygon as Poly
+from shapely.geometry import LinearRing, MultiPolygon, Point, Polygon as Poly
 from shapely.ops import unary_union
 
 import plotting.colormap as colormap
@@ -31,7 +30,6 @@
 
 from oceannavigator.settings import get_settings
 
-
 settings = get_settings()
 
 
@@ -47,10 +45,8 @@ def parse_query(self, query):
         super().parse_query(query)
 
         if len(self.variables) > 1:
-            raise ClientError(
-                f"MapPlotter only supports 1 variable. \
-                    Received multiple: {self.variables}"
-            )
+            raise ClientError(f"MapPlotter only supports 1 variable. \
+                    Received multiple: {self.variables}")
 
         self.projection = query.get("projection")
 
@@ -143,28 +139,21 @@ def __apply_poly_mask(self, data: np.ma.MaskedArray) -> np.ma.MaskedArray:
     def get_land_geoms(self, extent: tuple) -> list:
         # Returns a list of land shape geometries that intersect the plot extent
         scaler = cfeature.AdaptiveScaler("110m", (("50m", 50), ("10m", 15)))
-        land_shp = cfeature.NaturalEarthFeature(
-            "physical", "land", scale=scaler.scale_from_extent(extent)
-        )
+        scale = scaler.scale_from_extent(extent)
 
-        lon_min, lon_max, lat_min, lat_max = extent
+        land_feats = cfeature.NaturalEarthFeature("physical", "land", scale=scale)
+
+        land_geoms = land_feats.intersecting_geometries(extent)
+        land_geoms = unary_union(list(land_geoms))
 
         geometries = []
-        if lon_min <= lon_max:
-            bbox = box(lon_min, lat_min, lon_max, lat_max)
-            for geom in land_shp.geometries():
-                inter = geom.intersection(bbox)
-                if not inter.is_empty:
-                    geometries.append(inter)
-        else:
-            # plot wraps longitudes
-            west_box = box(lon_min, lat_min, 180, lat_max)
-            east_box = box(-180, lat_min, lon_max, lat_max)
-            for geom in land_shp.geometries():
-                for bb in (west_box, east_box):
-                    inter = geom.intersection(bb)
-                    if not inter.is_empty:
-                        geometries.append(inter)
+        if not land_geoms.is_empty:
+            lake_feats = cfeature.NaturalEarthFeature("physical", "lakes", scale=scale)
+
+            lake_geoms = lake_feats.intersecting_geometries(extent)
+            lake_geoms = unary_union(list(lake_geoms))
+
+            geometries.append(land_geoms.difference(lake_geoms))
 
         return geometries
 
@@ -173,7 +162,7 @@ def load_map(
         extent: list,
         figuresize: list,
         dpi: int,
-    ) -> Union[plt.figure, plt.axes]:
+    ) -> tuple:
 
         CACHE_DIR = settings.cache_dir
         filename = self._get_filename(self.plot_projection.proj4_params["proj"], extent)
@@ -286,18 +275,10 @@ def load_data(self):
                 ]
             )
 
-        elif abs(self.centroid[1] - self.bounds[1]) > 90:
-
-            if abs(self.bounds[3] - self.bounds[1]) > 360:
-                raise ClientError(
-                    (  # gettext(
-                        "You have requested an area that exceeds the width \
-                        of the world. Thinking big is good but plots need to \
-                        be less than 360 deg wide."
-                    )
-                )
-            self.plot_projection = ccrs.Mercator(central_longitude=self.centroid[1])
-
+        elif abs(self.bounds[3] - self.bounds[1]) > 360:
+            raise ClientError(("You have requested an area that exceeds the width \
+                of the world. Thinking big is good but plots need to \
+                be less than 360 deg wide."))  # gettext()
         else:
             self.plot_projection = ccrs.Mercator(
                 central_longitude=self.centroid[1],
@@ -816,7 +797,9 @@ def plot(self):
                 self.data, self.dataset_config.variable[f"{self.variables[0]}"]
             )
 
-        data_categories = self.dataset_config.variable[self.variables[0]].data_categories
+        data_categories = self.dataset_config.variable[
+            self.variables[0]
+        ].data_categories
         c = ax.imshow(
             self.data,
             vmin=vmin,
@@ -914,6 +897,7 @@ def plot(self):
                 self.longitude,
                 self.latitude,
                 self.bathymetry,
+                transform_first=True,
                 linewidths=0.5,
                 norm=FuncNorm(
                     (lambda x: np.log10(x), lambda x: 10**x), vmin=1, vmax=6000