From 44bb526e08c1fad812724b4eace953b979ce4d39 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 26 Jan 2022 12:44:09 -0600
Subject: [PATCH] snapshot...
---
modules/icing/pirep_goes.py | 121 ++++++++++++++++++++++++++++--------
1 file changed, 94 insertions(+), 27 deletions(-)
diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index bab1b3f0..34a7e674 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -4,8 +4,8 @@ import pickle
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, write_icing_file_nc4, make_for_full_domain_predict, \
- make_for_full_domain_predict2, get_indexes_within_threshold
+ check_oblique, get_timestamp, homedir, write_icing_file_nc4, make_for_full_domain_predict, \
+ get_indexes_within_threshold
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
@@ -2175,18 +2175,21 @@ def run_make_images(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', ckpt_dir_s_pat
print('Done: ', clvrx_str_time)
-def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=homedir, model_path=None,
- prob_thresh=0.5, satellite='GOES16', domain='CONUS', day_night='DAY',
+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):
+ flight_levels = [0, 1, 2, 3, 4]
- if day_night == 'DAY':
- if model_path is None:
- model_path = model_path_day
- else:
- if model_path is None:
- model_path = model_path_night
+ 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)
- train_params = get_training_parameters(day_night=day_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)
@@ -2200,7 +2203,6 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
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)
- # ancil_data_dct, _, _ = make_for_full_domain_predict(h5f, name_list=['cld_height_acha', 'cld_geo_thick'])
if fidx == 0:
num_elems = len(cc)
@@ -2208,21 +2210,86 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
nav = get_navigation(satellite, domain)
lons_2d, lats_2d, x_rad, y_rad = get_lon_lat_2d_mesh(nav, ll, cc)
- solzen, satzen = make_for_full_domain_predict2(h5f, satellite=satellite, domain=domain)
- keep = np.logical_or(lats_2d > -63.0, lats_2d < 63.0)
- keep = np.where(keep, satzen < 70, False)
- if day_night == 'DAY':
- keep = np.where(keep, solzen < 80, False)
-
- preds_2d_dct, probs_2d_dct = run_evaluate_static(data_dct, num_lines, num_elems, day_night=day_night,
- ckpt_dir_s_path=model_path, prob_thresh=prob_thresh,
- use_flight_altitude=use_flight_altitude)
- flt_lvls = list(preds_2d_dct.keys())
- for flvl in flt_lvls:
- probs = probs_2d_dct[flvl]
- preds = preds_2d_dct[flvl]
- np.where(keep, preds, -1)
- np.where(keep, probs, -1.0)
+ 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)
+
+ 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 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 = run_evaluate_static(day_grd_dct, num_day_tiles, day_night='DAY',
+ ckpt_dir_s_path=day_model_path, prob_thresh=prob_thresh,
+ use_flight_altitude=use_flight_altitude)
+ day_preds = preds_day_dct[flvl]
+ day_probs = probs_day_dct[flvl]
+ day_idxs = np.array(day_idxs)
+ 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, day_night='NIGHT',
+ ckpt_dir_s_path=night_model_path, prob_thresh=prob_thresh,
+ use_flight_altitude=use_flight_altitude)
+ nght_preds = preds_nght_dct[flvl]
+ nght_probs = probs_nght_dct[flvl]
+ nght_idxs = np.array(nght_idxs)
+ fd_preds[nght_idxs] = nght_preds[:]
+ fd_probs[nght_idxs] = nght_probs[:]
+
+ # solzen, satzen = make_for_full_domain_predict2(h5f, satellite=satellite, domain=domain)
+ # keep = np.logical_or(lats_2d > -63.0, lats_2d < 63.0)
+ # keep = np.where(keep, satzen < 70, False)
+ # if day_night == 'DAY':
+ # keep = np.where(keep, solzen < 80, False)
+
+ 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)
--
GitLab