add .forecasts property that retrieves forecasts (#32)

* add `.forecasts` property that returns a dictionary of forecasts starting at each initial time for all forecast advisories in the track

* add test for forecasts

* make forecasts a mapping of strings to dataframes

Co-authored-by: zacharyburnett <zachary.r.burnett@gmail.com>

stormevents/nhc/track.py

@@ -922,6 +922,29 @@ def wind_swaths(self, wind_speed: int, segments: int = 91) -> Dict[str, Polygon]
 
         return wind_swaths
 
+    @property
+    def forecasts(self) -> Dict[str, Dict[str, DataFrame]]:
+        data = self.data
+
+        forecast_advisories = (
+            advisory for advisory in pandas.unique(data['advisory']) if advisory != 'BEST'
+        )
+
+        forecasts = {}
+        for advisory in forecast_advisories:
+            advisory_data = data[data['advisory'] == advisory]
+
+            initial_times = pandas.unique(advisory_data['datetime'])
+
+            forecasts[advisory] = {}
+            for initial_time in initial_times:
+                forecast_data = advisory_data[advisory_data['datetime'] == initial_time]
+                forecasts[advisory][
+                    f'{pandas.to_datetime(initial_time):%Y%m%dT%H%M%S}'
+                ] = forecast_data.sort_values('forecast_hours')
+
+        return forecasts
+
     @property
     def duration(self) -> pandas.Timedelta:
         """

tests/test_nhc.py

@@ -97,6 +97,16 @@ def test_vortex_track_properties():
     assert len(track) == 175
 
 
+def test_vortex_track_forecasts():
+    track = VortexTrack.from_storm_name('florence', 2018, file_deck='a')
+
+    forecasts = track.forecasts
+
+    assert len(forecasts) == 4
+    assert len(forecasts['OFCL']) == 77
+    assert len(forecasts['OFCL']['20180830T120000']) == 13
+
+
 @pytest.mark.disable_socket
 def test_vortex_track_from_file():
     input_directory = INPUT_DIRECTORY / 'test_vortex_track_from_file'