diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index 7b3c9b5547dac929b6e496a269cf765891acbe04..b8852348a05443af939d52272fb909f1650f0288 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -2323,7 +2323,7 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
h5f.close()
-def run_icing_predict_new(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=homedir,
+def run_icing_predict_fcn(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=homedir,
day_model_path=model_path_day, night_model_path=model_path_night,
prob_thresh=0.5, satellite='GOES16', domain='CONUS', day_night='AUTO',
l1b_andor_l2='both', use_flight_altitude=False, res_fac=1, use_nan=False):
@@ -2586,3 +2586,137 @@ def run_icing_predict_image(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output
print('Done: ', clvrx_str_time)
h5f.close()
+
+
+def run_icing_predict_image_fcn(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=homedir,
+ day_model_path=model_path_day, night_model_path=model_path_night,
+ prob_thresh=0.5, satellite='GOES16', domain='CONUS', day_night='AUTO',
+ l1b_andor_l2='BOTH', use_flight_altitude=True, res_fac=1,
+ extent=[-105, -70, 15, 50],
+ pirep_file='/Users/tomrink/data/pirep/pireps_202109200000_202109232359.csv',
+ obs_lons=None, obs_lats=None, obs_times=None, obs_alt=None, flight_level=None):
+
+ if use_flight_altitude is True:
+ flight_levels = [0, 1, 2, 3, 4]
+ else:
+ flight_levels = [0]
+
+ if pirep_file is not None:
+ ice_dict, no_ice_dict, neg_ice_dict = setup(pirep_file)
+
+ alt_lo, alt_hi = 0.0, 15000.0
+ if flight_level is not None:
+ alt_lo, alt_hi = flt_level_ranges[flight_level]
+
+ day_train_params = get_training_parameters(day_night='DAY', l1b_andor_l2=l1b_andor_l2)
+ nght_train_params = get_training_parameters(day_night='NIGHT', l1b_andor_l2=l1b_andor_l2)
+
+ if day_night == 'AUTO':
+ train_params = list(set(day_train_params + nght_train_params))
+ elif day_night == 'DAY':
+ train_params = day_train_params
+ elif day_night == 'NIGHT':
+ train_params = nght_train_params
+
+ if satellite == 'H08':
+ clvrx_ds = CLAVRx_H08(clvrx_dir)
+ else:
+ clvrx_ds = CLAVRx(clvrx_dir)
+ clvrx_files = clvrx_ds.flist
+
+ for fidx, fname in enumerate(clvrx_files):
+ h5f = h5py.File(fname, 'r')
+ dto = clvrx_ds.get_datetime(fname)
+ ts = dto.timestamp()
+ clvrx_str_time = dto.strftime('%Y-%m-%d_%H:%M')
+
+ dto, _ = get_time_tuple_utc(ts)
+ dto_0 = dto - datetime.timedelta(minutes=30)
+ dto_1 = dto + datetime.timedelta(minutes=30)
+ ts_0 = dto_0.timestamp()
+ ts_1 = dto_1.timestamp()
+
+ if pirep_file is not None:
+ _, keep_lons, keep_lats, _ = time_filter_3(ice_dict, ts_0, ts_1, alt_lo, alt_hi)
+ elif obs_times is not None:
+ keep = np.logical_and(obs_times >= ts_0, obs_times < ts_1)
+ keep = np.where(keep, np.logical_and(obs_alt >= alt_lo, obs_alt < alt_hi), False)
+ keep_lons = obs_lons[keep]
+ keep_lats = obs_lats[keep]
+ else:
+ keep_lons = None
+ keep_lats = None
+
+ data_dct, solzen, satzen, ll, cc = prepare_evaluate(h5f, name_list=train_params, satellite=satellite, domain=domain, offset=8)
+ num_elems = len(cc)
+ num_lines = len(ll)
+
+ if fidx == 0:
+ nav = get_navigation(satellite, domain)
+ lons_2d, lats_2d, x_rad, y_rad = get_lon_lat_2d_mesh(nav, ll, cc)
+
+ day_idxs = solzen < 80.0
+ num_day_tiles = np.sum(day_idxs)
+
+ nght_idxs = solzen > 100.0
+ num_nght_tiles = np.sum(nght_idxs)
+
+ # initialize output arrays
+ probs_2d_dct = {flvl: None for flvl in flight_levels}
+ preds_2d_dct = {flvl: None for flvl in flight_levels}
+ for flvl in flight_levels:
+ fd_preds = np.zeros(num_lines * num_elems, dtype=np.int8)
+ fd_preds[:] = -1
+ fd_probs = np.zeros(num_lines * num_elems, dtype=np.float32)
+ fd_probs[:] = -1.0
+ preds_2d_dct[flvl] = fd_preds
+ probs_2d_dct[flvl] = fd_probs
+
+ if (day_night == 'AUTO' or day_night == 'DAY') and num_day_tiles > 0:
+
+ preds_day_dct, probs_day_dct = run_evaluate_static_fcn(data_dct, day_model_path,
+ day_night='DAY', l1b_or_l2=l1b_andor_l2,
+ prob_thresh=prob_thresh,
+ use_flight_altitude=use_flight_altitude,
+ flight_levels=flight_levels)
+ for flvl in flight_levels:
+ preds = preds_day_dct[flvl]
+ probs = probs_day_dct[flvl]
+ fd_preds = preds_2d_dct[flvl]
+ fd_probs = probs_2d_dct[flvl]
+ fd_preds[day_idxs] = preds[day_idxs]
+ fd_probs[day_idxs] = probs[day_idxs]
+
+ if (day_night == 'AUTO' or day_night == 'NIGHT') and num_nght_tiles > 0:
+ preds_nght_dct, probs_nght_dct = run_evaluate_static_fcn(data_dct, night_model_path,
+ day_night='NIGHT', l1b_or_l2=l1b_andor_l2,
+ prob_thresh=prob_thresh,
+ use_flight_altitude=use_flight_altitude,
+ flight_levels=flight_levels)
+ for flvl in flight_levels:
+ preds = preds_nght_dct[flvl]
+ probs = probs_nght_dct[flvl]
+ fd_preds = preds_2d_dct[flvl]
+ fd_probs = probs_2d_dct[flvl]
+ fd_preds[nght_idxs] = preds[nght_idxs]
+ fd_probs[nght_idxs] = probs[nght_idxs]
+
+ for flvl in flight_levels:
+ fd_preds = preds_2d_dct[flvl]
+ fd_probs = probs_2d_dct[flvl]
+ preds_2d_dct[flvl] = fd_preds.reshape((num_lines, num_elems))
+ probs_2d_dct[flvl] = fd_probs.reshape((num_lines, num_elems))
+
+ prob_s = []
+ for flvl in flight_levels:
+ probs = probs_2d_dct[flvl]
+ prob_s.append(probs)
+ prob_s = np.stack(prob_s, axis=-1)
+ max_prob = np.max(prob_s, axis=2)
+ max_prob = np.where(max_prob < 0.5, np.nan, max_prob)
+
+ make_icing_image(h5f, max_prob, None, None, clvrx_str_time, satellite, domain,
+ ice_lons_vld=keep_lons, ice_lats_vld=keep_lats, extent=extent)
+
+ print('Done: ', clvrx_str_time)
+ h5f.close()
\ No newline at end of file