diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index 037f88f862264874608c4094c7c8834388e3c31b..9fc45feb00aa5657261c9b4530fe2ba0aa66aa96 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -2165,601 +2165,3 @@ flt_level_ranges[1] = [2000.0, 4000.0]
flt_level_ranges[2] = [4000.0, 6000.0]
flt_level_ranges[3] = [6000.0, 8000.0]
flt_level_ranges[4] = [8000.0, 15000.0]
-
-
-def run_make_images(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', ckpt_dir_s_path='/Users/tomrink/tf_model/', prob_thresh=0.5, satellite='GOES16', domain='CONUS',
- 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,
- use_flight_altitude=False, day_night='DAY', l1b_andor_l2='l2'):
-
- if pirep_file is not None:
- ice_dict, no_ice_dict, neg_ice_dict = setup(pirep_file)
-
- if satellite == 'H08':
- clvrx_ds = CLAVRx_H08(clvrx_dir)
- else:
- clvrx_ds = CLAVRx(clvrx_dir)
- clvrx_files = clvrx_ds.flist
-
- alt_lo, alt_hi = 0.0, 15000.0
- if flight_level is not None:
- alt_lo, alt_hi = flt_level_ranges[flight_level]
-
- train_params = get_training_parameters(day_night=day_night, l1b_andor_l2=l1b_andor_l2)
-
- 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')
-
- data_dct, ll, cc = make_for_full_domain_predict(h5f, name_list=train_params, satellite=satellite, domain=domain)
- num_elems, num_lines = len(cc), len(ll)
-
- 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
-
- ice_lons, ice_lats, preds_2d = icing_cnn.run_evaluate_static_avg(data_dct, ll, cc, ckpt_dir_s_path=ckpt_dir_s_path,
- flight_level=flight_level, prob_thresh=prob_thresh,
- satellite=satellite, domain=domain,
- use_flight_altitude=use_flight_altitude)
-
- make_icing_image(h5f, None, ice_lons, ice_lats, clvrx_str_time, satellite, domain,
- ice_lons_vld=keep_lons, ice_lats_vld=keep_lats, extent=extent)
-
- # preds_2d_dct, probs_2d_dct = run_evaluate_static(data_dct, num_lines, num_elems, day_night=day_night,
- # ckpt_dir_s_path=ckpt_dir_s_path, prob_thresh=prob_thresh,
- # flight_levels=[0],
- # use_flight_altitude=use_flight_altitude)
- #
- # make_icing_image(None, probs_2d_dct[0], None, None, clvrx_str_time, satellite, domain,
- # ice_lons_vld=keep_lons, ice_lats_vld=keep_lats, extent=extent)
-
- h5f.close()
- print('Done: ', clvrx_str_time)
-
-
-def run_icing_predict(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, use_nan=False):
- if use_flight_altitude is True:
- flight_levels = [0, 1, 2, 3, 4]
- else:
- flight_levels = [0]
-
- 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')
-
- data_dct, ll, cc = make_for_full_domain_predict(h5f, name_list=train_params, satellite=satellite, domain=domain, res_fac=res_fac)
-
- if fidx == 0:
- num_elems = len(cc)
- num_lines = len(ll)
- nav = get_navigation(satellite, domain)
- lons_2d, lats_2d, x_rad, y_rad = get_lon_lat_2d_mesh(nav, ll, cc, offset=int(8 / res_fac))
-
- ancil_data_dct, _, _ = make_for_full_domain_predict(h5f, name_list=
- ['solar_zenith_angle', 'sensor_zenith_angle', 'cld_height_acha', 'cld_geo_thick'],
- satellite=satellite, domain=domain, res_fac=res_fac)
-
- satzen = ancil_data_dct['sensor_zenith_angle']
- solzen = ancil_data_dct['solar_zenith_angle']
- day_idxs = []
- nght_idxs = []
- for j in range(num_lines):
- for i in range(num_elems):
- k = i + j*num_elems
- if not check_oblique(satzen[k]):
- continue
- if is_day(solzen[k]):
- day_idxs.append(k)
- else:
- nght_idxs.append(k)
-
- num_tiles = num_lines * num_elems
- num_day_tiles = len(day_idxs)
- num_nght_tiles = len(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:
-
- day_data_dct = {name: [] for name in day_train_params}
- for name in day_train_params:
- for k in day_idxs:
- day_data_dct[name].append(data_dct[name][k])
- day_grd_dct = {name: None for name in day_train_params}
- for ds_name in day_train_params:
- day_grd_dct[ds_name] = np.stack(day_data_dct[ds_name])
-
- preds_day_dct, probs_day_dct = icing_cnn.run_evaluate_static(day_grd_dct, num_day_tiles, 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)
- day_idxs = np.array(day_idxs)
- for flvl in flight_levels:
- day_preds = preds_day_dct[flvl]
- day_probs = probs_day_dct[flvl]
- fd_preds = preds_2d_dct[flvl]
- fd_probs = probs_2d_dct[flvl]
- fd_preds[day_idxs] = day_preds[:]
- fd_probs[day_idxs] = day_probs[:]
-
- if (day_night == 'AUTO' or day_night == 'NIGHT') and num_nght_tiles > 0:
-
- nght_data_dct = {name: [] for name in nght_train_params}
- for name in nght_train_params:
- for k in nght_idxs:
- nght_data_dct[name].append(data_dct[name][k])
- nght_grd_dct = {name: None for name in nght_train_params}
- for ds_name in nght_train_params:
- nght_grd_dct[ds_name] = np.stack(nght_data_dct[ds_name])
-
- preds_nght_dct, probs_nght_dct = icing_cnn.run_evaluate_static(nght_grd_dct, num_nght_tiles, 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)
- nght_idxs = np.array(nght_idxs)
- for flvl in flight_levels:
- nght_preds = preds_nght_dct[flvl]
- nght_probs = probs_nght_dct[flvl]
- fd_preds = preds_2d_dct[flvl]
- fd_probs = probs_2d_dct[flvl]
- fd_preds[nght_idxs] = nght_preds[:]
- fd_probs[nght_idxs] = nght_probs[:]
-
- 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))
-
- write_icing_file_nc4(clvrx_str_time, output_dir, preds_2d_dct, probs_2d_dct,
- x_rad, y_rad, lons_2d, lats_2d, cc, ll,
- satellite=satellite, domain=domain, use_nan=use_nan, prob_thresh=prob_thresh)
-
- print('Done: ', clvrx_str_time)
- h5f.close()
-
-
-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):
- if use_flight_altitude is True:
- flight_levels = [0, 1, 2, 3, 4]
- else:
- flight_levels = [0]
-
- 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')
-
- 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 = icing_fcn.run_evaluate_static(data_dct, 1, 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 = icing_fcn.run_evaluate_static_fcn(data_dct, 1, 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))
-
- write_icing_file_nc4(clvrx_str_time, output_dir, preds_2d_dct, probs_2d_dct,
- x_rad, y_rad, lons_2d, lats_2d, cc, ll,
- satellite=satellite, domain=domain, use_nan=use_nan, prob_thresh=prob_thresh)
-
- print('Done: ', clvrx_str_time)
- h5f.close()
-
-
-def run_icing_predict_image(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')
-
- data_dct, ll, cc = make_for_full_domain_predict(h5f, name_list=train_params, satellite=satellite, domain=domain, res_fac=res_fac)
-
- if fidx == 0:
- num_elems = len(cc)
- num_lines = len(ll)
- nav = get_navigation(satellite, domain)
-
- ancil_data_dct, _, _ = make_for_full_domain_predict(h5f, name_list=
- ['solar_zenith_angle', 'sensor_zenith_angle', 'cld_height_acha', 'cld_geo_thick'],
- satellite=satellite, domain=domain, res_fac=res_fac)
-
- satzen = ancil_data_dct['sensor_zenith_angle']
- solzen = ancil_data_dct['solar_zenith_angle']
- day_idxs = []
- nght_idxs = []
- for j in range(num_lines):
- for i in range(num_elems):
- k = i + j*num_elems
- if not check_oblique(satzen[k]):
- continue
- if is_day(solzen[k]):
- day_idxs.append(k)
- else:
- nght_idxs.append(k)
-
- num_tiles = num_lines * num_elems
- num_day_tiles = len(day_idxs)
- num_nght_tiles = len(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:
-
- day_data_dct = {name: [] for name in day_train_params}
- for name in day_train_params:
- for k in day_idxs:
- day_data_dct[name].append(data_dct[name][k])
- day_grd_dct = {name: None for name in day_train_params}
- for ds_name in day_train_params:
- day_grd_dct[ds_name] = np.stack(day_data_dct[ds_name])
-
- preds_day_dct, probs_day_dct = icing_cnn.run_evaluate_static(day_grd_dct, num_day_tiles, 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)
- day_idxs = np.array(day_idxs)
- for flvl in flight_levels:
- day_preds = preds_day_dct[flvl]
- day_probs = probs_day_dct[flvl]
- fd_preds = preds_2d_dct[flvl]
- fd_probs = probs_2d_dct[flvl]
- fd_preds[day_idxs] = day_preds[:]
- fd_probs[day_idxs] = day_probs[:]
-
- if (day_night == 'AUTO' or day_night == 'NIGHT') and num_nght_tiles > 0:
-
- nght_data_dct = {name: [] for name in nght_train_params}
- for name in nght_train_params:
- for k in nght_idxs:
- nght_data_dct[name].append(data_dct[name][k])
- nght_grd_dct = {name: None for name in nght_train_params}
- for ds_name in nght_train_params:
- nght_grd_dct[ds_name] = np.stack(nght_data_dct[ds_name])
-
- preds_nght_dct, probs_nght_dct = icing_cnn.run_evaluate_static(nght_grd_dct, num_nght_tiles, 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)
- nght_idxs = np.array(nght_idxs)
- for flvl in flight_levels:
- nght_preds = preds_nght_dct[flvl]
- nght_probs = probs_nght_dct[flvl]
- fd_preds = preds_2d_dct[flvl]
- fd_probs = probs_2d_dct[flvl]
- fd_preds[nght_idxs] = nght_preds[:]
- fd_probs[nght_idxs] = nght_probs[:]
-
- 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))
-
- 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
-
- 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()
-
-
-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 = icing_fcn.run_evaluate_static(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 = icing_fcn.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