Revert "Added new selection based on proximity to a boundary"

This reverts commit c8c277d.
wavespectra · Dec 5, 2023 · b313f68 · b313f68
1 parent c8c277d
commit b313f68
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Showing 3 changed files with 36 additions and 115 deletions.
diff --git a/tests/core/test_sel.py b/tests/core/test_sel.py
@@ -1,11 +1,10 @@
 """Unit testing for SpecDataset wrapper around DataArray."""
 import os
-
-import numpy as np
 import pytest
+import numpy as np
 
-from wavespectra import read_era5, read_ww3
 from wavespectra.core.attributes import attrs
+from wavespectra import read_ww3, read_era5
 from wavespectra.core.select import Coordinates
 
 FILES_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "../sample_files")
@@ -49,16 +48,6 @@ def test_dset_sel_bbox(self):
         )
         dset[attrs.SITENAME].size == self.dset[attrs.SITENAME].size
 
-    def test_dset_sel_boundary(self):
-        """Assert that sel/bbox method runs."""
-        dset = self.dset.spec.sel(
-            lons=self.dset.lon.values,
-            lats=self.dset.lat.values,
-            method="boundary",
-            tolerance=0.0,
-        )
-        dset[attrs.SITENAME].size == self.dset[attrs.SITENAME].size
-
     def test_dset_sel_bbox_outside(self):
         """Assert that sel/bbox method raises for bbox outside dataset."""
         with pytest.raises(ValueError):
@@ -134,7 +123,6 @@ def test_weighting(self):
             upper = np.array([max(s1, s2) for s1, s2 in zip(site0, site1)])
             assert (upper - idw > 0).all() and (idw - lower > 0).all()
 
-
 class TestSelCoordinatesConventions:
     """Test Sel methods with different coordinates conventions."""
 
@@ -164,15 +152,25 @@ def test_nearest_both_180(self):
         dset = self.dset.copy(deep=True)
         dset["lon"].values = [-10, 10]
         dset["lat"].values = [30, 30]
-        ds = dset.spec.sel(method="nearest", lons=[-9], lats=[31], tolerance=5.0)
+        ds = dset.spec.sel(
+            method="nearest",
+            lons=[-9],
+            lats=[31],
+            tolerance=5.0
+        )
         assert ds.lon == -10
 
     def test_nearest_dset_360_slice_180(self):
         """Test nearest with Dataset in [0 <--> 360] and slice in [-180 <--> 180]."""
         dset = self.dset.copy(deep=True)
         dset["lon"].values = [0, 350]
         dset["lat"].values = [30, 30]
-        ds = dset.spec.sel(method="nearest", lons=[-9], lats=[31], tolerance=5.0)
+        ds = dset.spec.sel(
+            method="nearest",
+            lons=[-9],
+            lats=[31],
+            tolerance=5.0
+        )
         assert ds.lon == -10
 
     def test_nearest_dset_180_slice_360(self):
@@ -187,7 +185,7 @@ def test_nearest_dset_180_slice_360(self):
             lats=[31],
             tolerance=5.0,
             dset_lons=dset.lon.values,
-            dset_lats=dset.lat.values,
+            dset_lats=dset.lat.values
         )
         assert ds.lon == 350
 
@@ -249,24 +247,7 @@ def test_bbox_both_180(self):
             lats=[-35, 35],
             tolerance=0.0,
             dset_lons=dset.lon.values,
-            dset_lats=dset.lat.values,
-        )
-        assert np.array_equal(ds.lon.values, dset.lon.values)
-
-    def test_bbox_both_180(self):
-        """Test bbox with both dataset and slice in [-180 <--> 180]."""
-        dset = self.dset.copy(deep=True)
-        dset["lon"].values = [-10, 10]
-        dset["lat"].values = [30, 30]
-        lon = -9
-
-        ds = dset.spec.sel(
-            method="boundary",
-            lons=[-10, 10],
-            lats=[-35, 35],
-            tolerance=50,
-            dset_lons=dset.lon.values,
-            dset_lats=dset.lat.values,
+            dset_lats=dset.lat.values
         )
         assert np.array_equal(ds.lon.values, dset.lon.values)
 
@@ -281,11 +262,9 @@ def test_bbox_dset_360_slice_180(self):
             lats=[-35, 35],
             tolerance=0.0,
             dset_lons=dset.lon.values,
-            dset_lats=dset.lat.values,
-        )
-        assert np.array_equal(
-            sorted(ds.lon.values % 360), sorted(dset.lon.values % 360)
+            dset_lats=dset.lat.values
         )
+        assert np.array_equal(sorted(ds.lon.values % 360), sorted(dset.lon.values % 360))
 
     def test_bbox_dset_180_slice_360(self):
         """Test bbox with Dataset in [-180 <--> 180] and slice in [0 <--> 360]."""
@@ -298,6 +277,6 @@ def test_bbox_dset_180_slice_360(self):
             lats=[-35, 35],
             tolerance=0.0,
             dset_lons=dset.lon.values,
-            dset_lats=dset.lat.values,
+            dset_lats=dset.lat.values
         )
-        assert int(ds.lon) == 350
+        assert int(ds.lon) == 350
diff --git a/wavespectra/core/select.py b/wavespectra/core/select.py
@@ -1,12 +1,11 @@
 """Interpolate stations."""
-import logging
-
 import numpy as np
 import xarray as xr
-from scipy.spatial import cKDTree
+import logging
 
 from wavespectra.core.attributes import attrs, set_spec_attributes
 
+
 logger = logging.getLogger(__name__)
 
 
@@ -92,10 +91,7 @@ def distance(self, lon, lat):
             List of distances between each station and site.
 
         """
-        dist = np.sqrt(
-            (self.dset_lons % 360 - np.array(lon) % 360) ** 2
-            + (self.dset_lats - np.array(lat)) ** 2
-        )
+        dist = np.sqrt((self.dset_lons % 360 - np.array(lon) % 360) ** 2 + (self.dset_lats - np.array(lat)) ** 2)
         if isinstance(dist, xr.DataArray):
             dist = dist.values
         return np.abs(dist)
@@ -123,12 +119,12 @@ def nearer(self, lon, lat, tolerance=np.inf, max_sites=None):
     def nearest(self, lon, lat):
         """Nearest station in (dset_lons, dset_lats) to site (lon, lat).
 
-        Args:
-            lon (float): Longitude to locate from lons.
-            lat (float): Latitude to locate from lats.
+            Args:
+                lon (float): Longitude to locate from lons.
+                lat (float): Latitude to locate from lats.
 
-        Returns:
-            Index and distance of closest station.
+            Returns:
+                Index and distance of closest station.
 
         """
         dist = self.distance(lon, lat)
@@ -168,9 +164,7 @@ def sel_nearest(
             improve precision if projected coordinates are provided at high latitudes.
 
     """
-    coords = Coordinates(
-        dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats
-    )
+    coords = Coordinates(dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats)
 
     station_ids = []
     for lon, lat in zip(coords.lons, coords.lats):
@@ -223,9 +217,7 @@ def sel_idw(
             improve precision if projected coordinates are provided at high latitudes.
 
     """
-    coords = Coordinates(
-        dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats
-    )
+    coords = Coordinates(dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats)
 
     mask = dset.isel(site=0, drop=True) * np.nan
     dsout = []
@@ -302,9 +294,7 @@ def sel_bbox(dset, lons, lats, tolerance=0.0, dset_lons=None, dset_lats=None):
             improve precision if projected coordinates are provided at high latitudes.
 
     """
-    coords = Coordinates(
-        dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats
-    )
+    coords = Coordinates(dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats)
 
     minlon = min(coords.lons) - tolerance
     minlat = min(coords.lats) - tolerance
@@ -331,7 +321,7 @@ def sel_bbox(dset, lons, lats, tolerance=0.0, dset_lons=None, dset_lats=None):
                 & (coords.dset_lats >= minlat)
                 & (coords.dset_lons <= minlon)
                 & (coords.dset_lats <= maxlat)
-            )[0],
+            )[0]
         )
 
     if station_ids.size == 0:
@@ -350,49 +340,3 @@ def sel_bbox(dset, lons, lats, tolerance=0.0, dset_lons=None, dset_lats=None):
     dsout = dsout.assign_coords({attrs.SITENAME: np.arange(len(station_ids))})
 
     return dsout
-
-
-def sel_boundary(dset, lons, lats, tolerance=0.1, dset_lons=None, dset_lats=None):
-    """Select sites from wthin the given dset that are within a given distance of any of the passed points
-    Primary use case is to extract spectral points from a parent spectral forcing dataset that
-    are within a certain distance of nest boundary.
-
-    Args:
-        dset (Dataset): Stations SpecDataset to select from.
-        lons (array): Longitude of sites
-        lats (array): Latitude of sites
-        tolerance (float): Minimum distance from any site (degrees)
-        dset_lons (array): Longitude of stations in dset.
-        dset_lats (array): Latitude of stations in dset.
-
-    Returns:
-        Selected SpecDataset point within the miniumum_disance any site passed
-
-    Note:
-        Args `dset_lons`, `dset_lats` are not required but can improve performance when
-            `dset` is chunked with site=1 (expensive to access station coordinates) and
-            improve precision if projected coordinates are provided at high latitudes.
-
-    """
-    coords = Coordinates(
-        dset, lons=lons, lats=lats, dset_lons=dset_lons, dset_lats=dset_lats
-    )
-
-    # Create kdtree of boundary
-    input_points = list(zip(coords.dset_lons, coords.dset_lats))
-    boundary = list(zip(coords.lons, coords.lats))
-    tree = cKDTree(np.array(boundary))
-
-    # Find the indices of points in forcing dataset within the distance_threshold from any point in the boundary
-    within_distance_indices = tree.query_ball_point(np.array(input_points), tolerance)
-    result_list = [i for i, indices in enumerate(within_distance_indices) if indices]
-
-    dsout = dset.isel(**{attrs.SITENAME: result_list})
-
-    # Return longitudes in the convention provided
-    if coords.consistent is False:
-        dsout.lon.values = coords._swap_longitude_convention(dsout.lon.values)
-
-    dsout = dsout.assign_coords({attrs.SITENAME: np.arange(len(result_list))})
-
-    return dsout
diff --git a/wavespectra/specdataset.py b/wavespectra/specdataset.py
@@ -1,13 +1,12 @@
 """Wrapper around the xarray dataset."""
+import types
 import os
 import re
 import sys
-import types
-
 import xarray as xr
 
 from wavespectra.core.attributes import attrs
-from wavespectra.core.select import sel_bbox, sel_boundary, sel_idw, sel_nearest
+from wavespectra.core.select import sel_idw, sel_nearest, sel_bbox
 from wavespectra.specarray import SpecArray
 
 here = os.path.dirname(os.path.abspath(__file__))
@@ -112,7 +111,7 @@ def sel(
         tolerance=2.0,
         dset_lons=None,
         dset_lats=None,
-        **kwargs,
+        **kwargs
     ):
         """Select stations near or at locations defined by (lons, lats) vector.
 
@@ -149,7 +148,6 @@ def sel(
             "idw": sel_idw,
             "bbox": sel_bbox,
             "nearest": sel_nearest,
-            "boundary": sel_boundary,
             None: sel_nearest,
         }
         try:
@@ -172,6 +170,6 @@ def sel(
             tolerance=tolerance,
             dset_lons=dset_lons,
             dset_lats=dset_lats,
-            **kwargs,
+            **kwargs
         )
         return dsout