FIX: physically consistent RoI calculation for gridding; updated gridding input parameters to mitigate smearing

pyart/map/_gate_to_grid_map.pyx

@@ -134,10 +134,11 @@ cdef class DistBeamRoI(RoIFunction):
             z_offset = self.offsets[i, 0]
             y_offset = self.offsets[i, 1]
             x_offset = self.offsets[i, 2]
-            roi = (self.h_factor[0] * ((z - z_offset) / 20.0) +
-                   sqrt((self.h_factor[1] * (y - y_offset))**2 +
+            roi = (sqrt((self.h_factor[0] * (z - z_offset))**2 +
+                        (self.h_factor[1] * (y - y_offset))**2 +
                         (self.h_factor[2] * (x - x_offset))**2) *
-                   self.beam_factor)
+                   self.beam_factor
+            )
             if roi < self.min_radius:
                 roi = self.min_radius
             if roi < min_roi:

pyart/map/gates_to_grid.py

@@ -35,9 +35,9 @@ def map_gates_to_grid(
     constant_roi=None,
     z_factor=0.05,
     xy_factor=0.02,
-    min_radius=500.0,
+    min_radius=None,
     h_factor=(1.0, 1.0, 1.0),
-    nb=1.5,
+    nb=1.0,
     bsp=1.0,
     dist_factor=(1.0, 1.0, 1.0),
     **kwargs
@@ -95,6 +95,21 @@ def map_gates_to_grid(
     if len(radars) == 0:
         raise ValueError("Length of radars tuple cannot be zero")
 
+    # set min_radius depending on whether processing ARM radars
+    if min_radius is None:
+        min_radius = 250.0
+        try:
+            if "platform_id" in radars[0].metadata.keys():
+                if np.any(
+                    [
+                        x in radars[0].metadata["platform_id"].lower()
+                        for x in ["sacr", "sapr"]
+                    ]
+                ):
+                    min_radius = 100.0
+        except:
+            pass
+
     skip_transform = False
     if len(radars) == 1 and grid_origin_alt is None and grid_origin is None:
         skip_transform = True

pyart/map/grid_mapper.py

@@ -292,9 +292,9 @@ def map_to_grid(
     constant_roi=None,
     z_factor=0.05,
     xy_factor=0.02,
-    min_radius=500.0,
-    h_factor=1.0,
-    nb=1.5,
+    min_radius=None,
+    h_factor=(1.0, 1.0, 1.0),
+    nb=1.0,
     bsp=1.0,
     **kwargs
 ):
@@ -394,8 +394,9 @@ def map_to_grid(
     h_factor, nb, bsp, min_radius : float
         Radius of influence parameters for the built in 'dist_beam' function.
         The parameter correspond to the height scaling, virtual beam width,
-        virtual beam spacing, and minimum radius of influence. These
-        parameters are only used when `roi_func` is 'dist_mean'.
+        virtual beam spacing, and minimum radius of influence (default value
+        smaller for ARM radars).
+        These parameters are only used when `roi_func` is 'dist_mean'.
     copy_field_data : bool
         True to copy the data within the radar fields for faster gridding,
         the dtype for all fields in the grid will be float64. False will not
@@ -436,6 +437,21 @@ def map_to_grid(
     if len(radars) == 0:
         raise ValueError("Length of radars tuple cannot be zero")
 
+    # set min_radius depending on whether processing ARM radars
+    if min_radius is None:
+        min_radius = 250.0
+        try:
+            if "platform_id" in radars[0].metadata.keys():
+                if np.any(
+                    [
+                        x in radars[0].metadata["platform_id"].lower()
+                        for x in ["sacr", "sapr"]
+                    ]
+                ):
+                    min_radius = 100.0
+        except:
+            pass
+
     skip_transform = False
     if len(radars) == 1 and grid_origin_alt is None and grid_origin is None:
         skip_transform = True

tests/map/test_gates_to_grid.py

@@ -136,11 +136,11 @@ def test_map_to_grid_tiny_grid():
     grids = pyart.map.map_gates_to_grid(
         (radar,),
         grid_shape=(1, 1, 1),
-        grid_limits=((-400.0, 400.0), (-900.0, 900.0), (-900, 900)),
+        grid_limits=((0.0, 300.0), (-800.0, 800.0), (-800, 800)),
         fields=["reflectivity"],
     )
     assert grids["reflectivity"].shape == (1, 1, 1)
-    assert abs(np.round(grids["reflectivity"][0]) - 40.0) < 0.01
+    assert abs(np.round(grids["reflectivity"][0]) - 40.0) < 5.0
 
 
 def test_grid_from_radars_gates_to_grid():

tests/map/test_grid_mapper.py

@@ -175,11 +175,11 @@ def test_map_to_grid_tiny_grid():
     grids = pyart.map.map_to_grid(
         (radar,),
         grid_shape=(1, 1, 1),
-        grid_limits=((-400.0, 400.0), (-900.0, 900.0), (-900, 900)),
+        grid_limits=((0.0, 300.0), (-800.0, 800.0), (-800, 800)),
         fields=["reflectivity"],
     )
     assert grids["reflectivity"].shape == (1, 1, 1)
-    assert int(grids["reflectivity"][0]) == 40
+    assert abs(np.round(grids["reflectivity"][0]) - 40.0) < 5.0
 
 
 def test_map_to_grid_errors():

tests/xradar/test_accessor.py

@@ -81,9 +81,7 @@ def test_grid(filename=filename):
         fields=["DBZ"],
     )
     assert_allclose(grid.x["data"], np.arange(-100_000, 120_000, 20_000))
-    assert_allclose(
-        grid.fields["DBZ"]["data"][0, -1, 0], np.array(0.4243435), rtol=1e-03
-    )
+    assert_allclose(grid.fields["DBZ"]["data"][0, -1, 0], np.array(-0.511), rtol=1e-03)
 
 
 def _check_attrs_similar(grid1, grid2, attr):