adding option for the penny et al (2023) rmw regression fill without …

…the moving mean smoother

stormevents/nhc/const.py

@@ -8,6 +8,7 @@ class RMWFillMethod(Enum):
     none = None
     persistent = auto()
     regression_penny_2023 = auto()
+    regression_penny_2023_no_smoothing = auto()
 
 
 # Bias correction values for the Rmax forecast

stormevents/nhc/track.py

@@ -1377,7 +1377,10 @@ def movingmean(dff):
                 "radius_of_maximum_winds"
             ]
 
-        elif rmw_fill == RMWFillMethod.regression_penny_2023:
+        elif (
+            rmw_fill == RMWFillMethod.regression_penny_2023
+            or rmw_fill == RMWFillMethod.regression_penny_2023_no_smoothing
+        ):
             # fill OFCL maximum wind radius based on regression method from
             # Penny et al. (2023). https://doi.org/10.1175/WAF-D-22-0209.1
             isotach_radii = forecast[

tests/test_nhc.py

@@ -482,7 +482,24 @@ def test_rmw_fill_method_regression_penny_2023():
     rmw = data.loc[data.track_start_time == data.track_start_time.unique()[i_uq_row]][
         "radius_of_maximum_winds"
     ]
-    assert len(rmw.unique()) > 1
+    assert len(rmw.unique()) == 11
+
+
+def test_rmw_fill_method_regression_penny_2023_no_smoothing():
+    tr_florence2018 = VortexTrack.from_storm_name(
+        "Florence",
+        2018,
+        file_deck="a",
+        advisories=["OFCL"],
+        rmw_fill=RMWFillMethod.regression_penny_2023_no_smoothing,
+    )
+    assert tr_florence2018.rmw_fill == RMWFillMethod.regression_penny_2023_no_smoothing
+    data = tr_florence2018.data
+    i_uq_row = 40
+    rmw = data.loc[data.track_start_time == data.track_start_time.unique()[i_uq_row]][
+        "radius_of_maximum_winds"
+    ]
+    assert len(rmw.unique()) == 10
 
 
 def test_rmw_fill_method_setvalue_invalid():