snapshot...

modules/icing/pirep_goes.py

@@ -1110,12 +1110,13 @@ def tile_extract(trnfile='/home/rink/tiles_l1b_train.h5', tstfile='/home/rink/ti
     trn_icing_lats = icing_lats[trn_idxs,]
 
     #  Data augmentation -------------------------------------------------------------
-    trn_data_dct_aug = {ds_name : [] for ds_name in train_params}
-    trn_icing_intesity_aug = []
-    trn_icing_times_aug = []
-    trn_icing_lons_aug = []
-    trn_icing_lats_aug = []
     if augment:
+        trn_data_dct_aug = {ds_name: [] for ds_name in train_params}
+        trn_icing_intesity_aug = []
+        trn_icing_times_aug = []
+        trn_icing_lons_aug = []
+        trn_icing_lats_aug = []
+
         for k in range(trn_icing_intesity.shape[0]):
             iceint = trn_icing_intesity[k]
             icetime = trn_icing_times[k]
@@ -1144,19 +1145,19 @@ def tile_extract(trnfile='/home/rink/tiles_l1b_train.h5', tstfile='/home/rink/ti
                 trn_icing_lats_aug.append(icelat)
                 trn_icing_lats_aug.append(icelat)
 
-    for ds_name in train_params:
-        trn_data_dct_aug[ds_name] = np.stack(trn_data_dct_aug[ds_name])
-    trn_icing_intesity_aug = np.stack(trn_icing_intesity_aug)
-    trn_icing_times_aug = np.stack(trn_icing_intesity_aug)
-    trn_icing_lons_aug = np.stack(trn_icing_lons_aug)
-    trn_icing_lats_aug = np.stack(trn_icing_lats_aug)
+        for ds_name in train_params:
+            trn_data_dct_aug[ds_name] = np.stack(trn_data_dct_aug[ds_name])
+        trn_icing_intesity_aug = np.stack(trn_icing_intesity_aug)
+        trn_icing_times_aug = np.stack(trn_icing_intesity_aug)
+        trn_icing_lons_aug = np.stack(trn_icing_lons_aug)
+        trn_icing_lats_aug = np.stack(trn_icing_lats_aug)
 
-    for ds_name in train_params:
-        trn_data_dct[ds_name] = np.concatenate([trn_data_dct[ds_name], trn_data_dct_aug[ds_name]])
-    trn_icing_intensity = np.concatenate([trn_icing_intesity, trn_icing_intesity_aug])
-    trn_icing_times = np.concatenate([trn_icing_times, trn_icing_times_aug])
-    trn_icing_lons = np.concatenate([trn_icing_lons, trn_icing_lons_aug])
-    trn_icing_lats = np.concatenate([trn_icing_lats, trn_icing_lats_aug])
+        for ds_name in train_params:
+            trn_data_dct[ds_name] = np.concatenate([trn_data_dct[ds_name], trn_data_dct_aug[ds_name]])
+        trn_icing_intensity = np.concatenate([trn_icing_intesity, trn_icing_intesity_aug])
+        trn_icing_times = np.concatenate([trn_icing_times, trn_icing_times_aug])
+        trn_icing_lons = np.concatenate([trn_icing_lons, trn_icing_lons_aug])
+        trn_icing_lats = np.concatenate([trn_icing_lats, trn_icing_lats_aug])
 
     # do sort
     ds_indexes = np.argsort(trn_icing_times)
@@ -1199,45 +1200,6 @@ def tile_extract(trnfile='/home/rink/tiles_l1b_train.h5', tstfile='/home/rink/ti
 
     write_file(tstfile, train_params, tst_data_dct, tst_icing_intensity, tst_icing_times, tst_icing_lons, tst_icing_lats)
 
-    # h5f_expl = h5py.File(a_clvr_file, 'r')
-    # h5f_out = h5py.File(outfile, 'w')
-    #
-    # for idx, ds_name in enumerate(train_params):
-    #     dt = ds_types[idx]
-    #     data = data_dct[ds_name]
-    #     h5f_out.create_dataset(ds_name, data=data, dtype=dt)
-    #
-    # icing_int_ds = h5f_out.create_dataset('icing_intensity', data=icing_intensity, dtype='i4')
-    # icing_int_ds.attrs.create('long_name', data='From PIREP. -1:No Icing, 1:Trace, 2:Light, 3:Light Moderate, 4:Moderate, 5:Moderate Severe, 6:Severe')
-    #
-    # time_ds = h5f_out.create_dataset('time', data=icing_times, dtype='f4')
-    # time_ds.attrs.create('units', data='seconds since 1970-1-1 00:00:00')
-    # time_ds.attrs.create('long_name', data='PIREP time')
-    #
-    # lon_ds = h5f_out.create_dataset('longitude', data=icing_lons, dtype='f4')
-    # lon_ds.attrs.create('units', data='degrees_east')
-    # lon_ds.attrs.create('long_name', data='PIREP longitude')
-    #
-    # lat_ds = h5f_out.create_dataset('latitude', data=icing_lats, dtype='f4')
-    # lat_ds.attrs.create('units', data='degrees_north')
-    # lat_ds.attrs.create('long_name', data='PIREP latitude')
-    #
-    # # copy relevant attributes
-    # for ds_name in train_params:
-    #     h5f_ds = h5f_out[ds_name]
-    #     h5f_ds.attrs.create('standard_name', data=h5f_expl[ds_name].attrs.get('standard_name'))
-    #     h5f_ds.attrs.create('long_name', data=h5f_expl[ds_name].attrs.get('long_name'))
-    #     h5f_ds.attrs.create('units', data=h5f_expl[ds_name].attrs.get('units'))
-    #     attr = h5f_expl[ds_name].attrs.get('actual_range')
-    #     if attr is not None:
-    #         h5f_ds.attrs.create('actual_range', data=attr)
-    #     attr = h5f_expl[ds_name].attrs.get('flag_values')
-    #     if attr is not None:
-    #         h5f_ds.attrs.create('flag_values', data=attr)
-    #
-    # h5f_out.close()
-    # h5f_expl.close()
-
     # --- close files
     for h5f in h5_s_icing:
         h5f.close()