Remove some missed accesses to dataset attrs

climada/hazard/tc_tracks.py

@@ -242,7 +242,7 @@ def get_track(self, track_name=None):
             return self.data
 
         for track in self.data:
-            if track.name == track_name:
+            if track.attrs['name'] == track_name:
                 return track
             if hasattr(track, 'sid') and track.sid == track_name:
                 return track
@@ -932,7 +932,7 @@ def from_simulations_chaz(cls, file_names, year_range=None, ensemble_nums=None):
                     'orig_event_flag': True,
                     'data_provider': "CHAZ",
                     'id_no': track_ds['id_no'].item(),
-                    'category': track_ds.category.item(),
+                    'category': track_ds['category'].item(),
                 }))
             if last_perc != 100:
                 LOGGER.info("Progress: 100%")
@@ -1556,7 +1556,7 @@ def _one_interp_data(track, time_step_h, land_geom=None):
                                                .interpolate(method)
             track_int.attrs['category'] = set_category(
                 track_int['max_sustained_wind'].values,
-                track_int.max_sustained_wind_unit)
+                track_int.attrs['max_sustained_wind_unit'])
             # restrict to time steps within original bounds
             track_int = track_int.sel(
                 time=(track['time'][0] <= track_int['time']) &

climada/hazard/tc_tracks_synth.py

@@ -332,7 +332,7 @@ def _one_rnd_walk(track, nb_synth_tracks, max_shift_ini, max_dspeed_rel, max_ddi
                 # end the track here
                 max_wind_end = i_track['max_sustained_wind'].values[last_idx]
                 ss_scale_end = climada.hazard.tc_tracks.set_category(max_wind_end,
-                        i_track.max_sustained_wind_unit)
+                        i_track.attrs['max_sustained_wind_unit'])
                 # TC category at ending point should not be higher than 1
                 cutoff_txt = (f"{i_track.attrs['name']}_gen{i_ens + 1}"
                               f" ({climada.hazard.tc_tracks.CAT_NAMES[ss_scale_end]})")
@@ -698,7 +698,7 @@ def _decay_values(track, land_geom, s_rel):
         for sea_land, land_sea in zip(sea_land_idx, land_sea_idx):
             v_landfall = track['max_sustained_wind'][sea_land - 1].values
             ss_scale = climada.hazard.tc_tracks.set_category(v_landfall,
-                                                             track.max_sustained_wind_unit)
+                                                             track.attrs['max_sustained_wind_unit'])
 
             v_land = track['max_sustained_wind'][sea_land - 1:land_sea].values
             if v_land[0] > 0:
@@ -873,7 +873,7 @@ def _apply_decay_coeffs(track, v_rel, p_rel, land_geom, s_rel):
         v_landfall = track['max_sustained_wind'][sea_land - 1].values
         p_landfall = float(track['central_pressure'][sea_land - 1].values)
         ss_scale = climada.hazard.tc_tracks.set_category(v_landfall,
-                                                         track.max_sustained_wind_unit)
+                                                         track.attrs['max_sustained_wind_unit'])
         if land_sea - sea_land == 1:
             continue
         S = _calc_decay_ps_value(track, p_landfall, land_sea - 1, s_rel)
@@ -909,7 +909,7 @@ def _apply_decay_coeffs(track, v_rel, p_rel, land_geom, s_rel):
                         track['sid'])
             v_decay[v_decay > 1] = (track['max_sustained_wind'][sea_land:land_sea][v_decay > 1]
                                     / v_landfall)
-        track.max_sustained_wind[sea_land:land_sea] = v_landfall * v_decay
+        track['max_sustained_wind'][sea_land:land_sea] = v_landfall * v_decay
 
         # correct values of sea after a landfall (until next landfall, if any)
         if land_sea < track['time'].size:
@@ -920,7 +920,7 @@ def _apply_decay_coeffs(track, v_rel, p_rel, land_geom, s_rel):
             else:
                 # if there is no further landfall, correct until the end of
                 # the track
-                end_cor = track.time.size
+                end_cor = track['time'].size
             rndn = 0.1 * float(np.abs(np.random.normal(size=1) * 5) + 6)
             r_diff = track['central_pressure'][land_sea].values - \
                      track['central_pressure'][land_sea - 1].values + rndn
@@ -938,7 +938,7 @@ def _apply_decay_coeffs(track, v_rel, p_rel, land_geom, s_rel):
         track['max_sustained_wind'][track['max_sustained_wind'] < 0] = 0
 
     track.attrs['category'] = climada.hazard.tc_tracks.set_category(
-        track['max_sustained_wind'].values, track.max_sustained_wind_unit)
+        track['max_sustained_wind'].values, track.attrs['max_sustained_wind_unit'])
     return track
 
 

climada/hazard/trop_cyclone/trop_cyclone.py

@@ -483,9 +483,9 @@ def video_intensity(
 
             tc_tmp = cls.from_tracks(tr_sel, centroids=centroids)
             tc_tmp.event_name = [
-                track.name + ' ' + time.strftime(
+                track['name'] + ' ' + time.strftime(
                     "%d %h %Y %H:%M",
-                    time.gmtime(tr_sel.data[0].time[1].values.astype(int)
+                    time.gmtime(tr_sel.data[0]['time'][1].values.astype(int)
                                 / 1000000000)
                 )
             ]
@@ -610,16 +610,16 @@ def from_single_track(
         new_haz.centroids = centroids
         new_haz.event_id = np.array([1])
         new_haz.frequency = np.array([1])
-        new_haz.event_name = [track.sid]
+        new_haz.event_name = [track.attrs['sid']]
         new_haz.fraction = sparse.csr_matrix(new_haz.intensity.shape)
         # store first day of track as date
         new_haz.date = np.array([
             dt.datetime(track['time'].dt.year.values[0],
                         track['time'].dt.month.values[0],
                         track['time'].dt.day.values[0]).toordinal()
         ])
-        new_haz.orig = np.array([track.orig_event_flag])
-        new_haz.category = np.array([track.category])
+        new_haz.orig = np.array([track.attrs['orig_event_flag']])
+        new_haz.category = np.array([track.attrs['category']])
         # users that pickle TCTracks objects might still have data with the legacy basin attribute,
         # so we have to deal with it here
         new_haz.basin = [track['basin'] if isinstance(track['basin'], str)