Merge branch 'ARM-DOE:main' into hidx

.github/workflows/ci.yml

@@ -63,7 +63,7 @@ jobs:
           python -m pytest -v --cov=./ --cov-report=xml
 
       - name: Upload code coverage to Codecov
-        uses: codecov/codecov-action@v4.3.1
+        uses: codecov/codecov-action@v4.4.1
         with:
           file: ./coverage.xml
           flags: unittests

.github/workflows/wheels.yml

@@ -44,7 +44,7 @@ jobs:
            git fetch --prune --unshallow
 
       - name: Build wheels for CPython
-        uses: pypa/cibuildwheel@v2.17.0
+        uses: pypa/cibuildwheel@v2.18.1
         with:
           output-dir: dist
         env:

pyart/core/grid.py

@@ -170,26 +170,33 @@ def __setstate__(self, state):
     def projection_proj(self):
         # Proj instance as specified by the projection attribute.
         # Raises a ValueError if the pyart_aeqd projection is specified.
-        projparams = self.get_projparams()
-        if projparams["proj"] == "pyart_aeqd":
-            raise ValueError(
-                "Proj instance can not be made for the pyart_aeqd projection"
-            )
         if not _PYPROJ_AVAILABLE:
             raise MissingOptionalDependency(
                 "PyProj is required to create a Proj instance but it "
                 + "is not installed"
             )
+        projparams = self.get_projparams()
+
+        # Check if projparams is dictionary and check for pyart_aeqd
+        if isinstance(projparams, dict):
+            if projparams["proj"] == "pyart_aeqd":
+                raise ValueError(
+                    "Proj instance can not be made for the pyart_aeqd projection"
+                )
+        # Get proj instance from a proj str or dict
         proj = pyproj.Proj(projparams)
         return proj
 
     def get_projparams(self):
-        """Return a projparam dict from the projection attribute."""
-        projparams = self.projection.copy()
-        if projparams.pop("_include_lon_0_lat_0", False):
-            projparams["lon_0"] = self.origin_longitude["data"][0]
-            projparams["lat_0"] = self.origin_latitude["data"][0]
-        return projparams
+        """Return a projparam dict or str from the projection attribute."""
+        if isinstance(self.projection, dict):
+            projparams = self.projection.copy()
+            if projparams.pop("_include_lon_0_lat_0", False):
+                projparams["lon_0"] = self.origin_longitude["data"][0]
+                projparams["lat_0"] = self.origin_latitude["data"][0]
+            return projparams
+        else:
+            return self.projection
 
     def _find_and_check_nradar(self):
         """
@@ -366,6 +373,14 @@ def to_xarray(self):
             ds.z.encoding["_FillValue"] = None
             ds.lat.encoding["_FillValue"] = None
             ds.lon.encoding["_FillValue"] = None
+
+            # Grab original radar(s) name and number of radars used to make grid
+            ds.attrs["nradar"] = self.nradar
+            ds.attrs["radar_name"] = self.radar_name
+
+            # Grab all metadata
+            ds.attrs.update(self.metadata)
+
             ds.close()
         return ds
 

pyart/correct/attenuation.py

@@ -48,6 +48,9 @@ def calculate_attenuation_zphi(
     or up to where temperatures in a temperature field are positive.
     The coefficients are either user-defined or radar frequency dependent.
 
+    NOTE: The base 10 forumulation that uses attenuated radar reflectivity and
+    differential phase that is used in this function can be found in Gu et al (2011).
+
     Parameters
     ----------
     radar : Radar

pyart/default_config.py

@@ -1072,6 +1072,9 @@
     134: None,  # High Resolution VIL
     135: None,  # Enhanced Echo Tops
     138: radar_estimated_rain_rate,  # Digital Storm Total Precipitation
+    153: reflectivity,  # Super Resolution Base Reflectivity Data Array
+    154: velocity,  # Super Resolution Base Velocity Data Array
+    155: spectrum_width,  # Super Resolution Base Spectrum Width Data Array
     159: differential_reflectivity,  # Digital Differential Reflectivity
     161: cross_correlation_ratio,  # Digital Correlation Coefficient
     163: specific_differential_phase,  # Digital Specific Differential Phase

pyart/filters/gatefilter.py

@@ -695,6 +695,15 @@ def exclude_invalid(self, field, exclude_masked=True, op="or"):
         marked = ~np.isfinite(self._get_fdata(field))
         return self._merge(marked, op, exclude_masked)
 
+    def exclude_last_gates(self, field, n_gates=10, exclude_masked=True, op="or"):
+        """
+        Excludes a number of gates at the end of each ray. This is useful
+        for when trying to exclude "ring artifacts" in some datasets.
+        """
+        marked = np.full(self._get_fdata(field).shape, False)
+        marked[:, -n_gates:] = True
+        return self._merge(marked, op, exclude_masked)
+
     def exclude_gates(self, mask, exclude_masked=True, op="or"):
         """
         Exclude gates where a given mask is equal True.

pyart/io/cfradial.py

@@ -56,6 +56,7 @@ def read_cfradial(
     exclude_fields=None,
     include_fields=None,
     delay_field_loading=False,
+    use_arm_scan_name=False,
     **kwargs,
 ):
     """
@@ -92,6 +93,10 @@ def read_cfradial(
         LazyLoadDict objects not dict objects. Delayed field loading will not
         provide any speedup in file where the number of gates vary between
         rays (ngates_vary=True) and is not recommended.
+    use_arm_scan_name : bool
+        Whether or not to get the sweep_mode information from the ARM scan_name
+        attribute. Default is False and will use the sweep_mode information as
+        defined in the cfradial standards.
 
     Returns
     -------
@@ -126,7 +131,7 @@ def read_cfradial(
     if "volume_number" in ncvars:
         if np.ma.isMaskedArray(ncvars["volume_number"][:]):
             metadata["volume_number"] = int(
-                np.ma.getdata(ncvars["volume_number"][:].flatten())
+                np.ma.getdata(ncvars["volume_number"][:].flatten())[0]
             )
         else:
             metadata["volume_number"] = int(ncvars["volume_number"][:])
@@ -191,20 +196,27 @@ def read_cfradial(
     else:
         ray_angle_res = None
 
-    # Uses ARM scan name if present.
-    if not hasattr(ncobj, "scan_name"):
-        scan_name = ""
-    else:
-        scan_name = ncobj.scan_name
-    if len(scan_name) > 0:
-        mode = scan_name
-    else:
-        # first sweep mode determines scan_type
-        try:
-            mode = netCDF4.chartostring(sweep_mode["data"][0])[()].decode("utf-8")
-        except AttributeError:
-            # Python 3, all strings are already unicode.
+    # Use ARM scan_name if chosen by the user
+    if use_arm_scan_name:
+        # Check if attribute actually exists
+        if not hasattr(ncobj, "scan_name"):
+            warnings.warn(
+                UserWarning,
+                "No scan_name attribute present in dataset, using sweep_mode instead.",
+            )
             mode = netCDF4.chartostring(sweep_mode["data"][0])[()]
+        # Check if attribute is invalid of length 0
+        elif len(ncobj.scan_name) < 0 or ncobj.scan_name is None:
+            warnings.warn(
+                UserWarning,
+                "Scan name contains no sweep information, using sweep_mode instead.",
+            )
+            mode = netCDF4.chartostring(sweep_mode["data"][0])[()]
+        else:
+            mode = ncobj.scan_name
+    else:
+        # Use sweep_mode if arm_scan_name isn't used. This is default
+        mode = netCDF4.chartostring(sweep_mode["data"][0])[()]
 
     mode = mode.strip()
 

pyart/io/nexrad_level3.py

@@ -280,7 +280,7 @@ def get_data(self):
         elif msg_code in [134]:
             mdata = self._get_data_msg_134()
 
-        elif msg_code in [94, 99, 182, 186]:
+        elif msg_code in [94, 99, 153, 154, 155, 182, 186]:
             hw31, hw32 = np.frombuffer(threshold_data[:4], ">i2")
             data = (self.raw_data - 2) * (hw32 / 10.0) + hw31 / 10.0
             mdata = np.ma.array(data, mask=self.raw_data < 2)
@@ -598,7 +598,24 @@ def _int16_to_float16(val):
 
 # List of product numbers for which Halfword 30 corresponds to sweep elev angle
 # Per Table V of the ICD
-ELEVATION_ANGLE = [19, 20, 25, 27, 28, 30, 56, 94, 99, 159, 161, 163, 165]
+ELEVATION_ANGLE = [
+    19,
+    20,
+    25,
+    27,
+    28,
+    30,
+    56,
+    94,
+    99,
+    153,
+    154,
+    155,
+    159,
+    161,
+    163,
+    165,
+]
 
 PRODUCT_RANGE_RESOLUTION = {
     19: 1.0,  # 124 nm
@@ -618,6 +635,9 @@ def _int16_to_float16(val):
     134: 1000.0,
     135: 1000.0,
     138: 1.0,
+    153: 0.25,
+    154: 0.25,
+    155: 0.25,
     159: 0.25,
     161: 0.25,
     163: 0.25,
@@ -655,6 +675,9 @@ def _int16_to_float16(val):
     134: 1,
     135: 0,
     138: 2,
+    153: 0,
+    154: 0,
+    155: 0,
     159: 0,
     161: 0,
     163: 0,
@@ -803,6 +826,10 @@ def _int16_to_float16(val):
     134,  # High Resolution VIL
     135,  # Enhanced Echo Tops
     138,  # Digital Storm Total
+    # Super Resolution
+    153,  # Super Resolution Base Reflectivity Data Array
+    154,  # Super Resolution Base Velocity Data Array
+    155,  # Super Resolution Base Spectrum Width Data Array
     # Precipitation
     159,  # Digital Differential
     # Reflectivity
@@ -861,9 +888,6 @@ def _int16_to_float16(val):
 #    147,    # Storm Total Snow Depth
 #    150,    # User Selectable Snow Water Equivalent
 #    151,    # User Selectable Snow Depth
-#    153,    # Super Resolution Reflectivity Data Array
-#    154,    # Super Resolution Velocity Data Array
-#    155,    # Super Resolution Spectrum Width Data Array
 #    158,    # Differential Reflectivity
 #    160,    # Correlation Coefficient
 #    162,    # Specific Differential Phase

pyart/util/columnsect.py

@@ -69,7 +69,7 @@ def column_vertical_profile(
     total_moment.update({"height": [], "time_offset": []})
 
     # Define the start of the radar volume
-    base_time = pd.to_datetime(radar.time["units"][14:]).to_numpy()
+    base_time = np.datetime64(datetime_from_radar(radar).isoformat(), "ns")
 
     # call the sphere_distance function
     dis = sphere_distance(

tests/core/test_grid.py

@@ -101,6 +101,9 @@ def test_grid_to_xarray():
     assert_equal(ds.lat.data, lat)
     assert_equal(ds.time.data, time)
 
+    assert ds.attrs["nradar"] == 1
+    assert ds.attrs["radar_name"]["data"][0] == "ExampleRadar"
+
 
 def _check_dicts_similar(dic1, dic2):
     for k, v in dic1.items():
@@ -304,6 +307,13 @@ def test_projection_proj():
     assert isinstance(grid.projection_proj, pyproj.Proj)
 
 
+@pytest.mark.skipif(not _PYPROJ_AVAILABLE, reason="PyProj is not installed.")
+def test_projection_proj_str():
+    grid = pyart.testing.make_target_grid()
+    grid.projection = "+proj=aeqd"
+    assert isinstance(grid.projection_proj, pyproj.Proj)
+
+
 def test_projection_proj_raised():
     grid = pyart.testing.make_target_grid()
 

tests/filters/test_gatefilter.py

@@ -239,6 +239,20 @@ def test_gatefilter_ops():
     assert gfilter.gate_excluded[0, 9] is np.True_
 
 
+def test_gatefilter_exclude_last_gates():
+    gfilter = pyart.correct.GateFilter(radar)
+    gfilter.exclude_last_gates("test_field", n_gates=2)
+    assert gfilter.gate_excluded[0, 0] is np.False_
+    assert gfilter.gate_excluded[0, 8] is np.True_
+    assert gfilter.gate_excluded[0, 9] is np.True_
+
+    gfilter = pyart.correct.GateFilter(radar)
+    gfilter.exclude_last_gates("test_field", n_gates=1)
+    assert gfilter.gate_excluded[0, 0] is np.False_
+    assert gfilter.gate_excluded[0, 8] is np.False_
+    assert gfilter.gate_excluded[0, 9] is np.True_
+
+
 def test_gatefilter_raises():
     gfilter = pyart.correct.GateFilter(radar)
     pytest.raises(ValueError, gfilter.exclude_below, "test_field", 0.5, op="fuzz")