diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index 8a63918997c15af5e4e9d6d380d67a94487955d1..c7d836f8468e504e76113cae906ac15bdebcab62 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -1,3 +1,4 @@
+from deeplearning.icing_fcn import run_evaluate_static_fcn
from icing.pireps import pirep_icing
import numpy as np
import pickle
@@ -5,7 +6,7 @@ import matplotlib.pyplot as plt
import os
from util.util import get_time_tuple_utc, GenericException, add_time_range_to_filename, is_night, is_day, \
check_oblique, get_timestamp, homedir, write_icing_file_nc4, make_for_full_domain_predict, \
- get_indexes_within_threshold
+ get_indexes_within_threshold, prepare_evaluate
from util.plot import make_icing_image
from util.geos_nav import get_navigation, get_lon_lat_2d_mesh
from util.setup import model_path_day, model_path_night
@@ -2307,6 +2308,143 @@ 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,
+ 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)
+ num_elems = len(cc)
+ num_lines = len(ll)
+
+ # Don't need these yet
+ # 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)
+ num_day_tiles = 1
+
+ # 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 = 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)
+ 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 = 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_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',