diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index 260f36637f41cd884420403a3bb691f174f6bdf8..6b32892a988720d5e52ca81503ff90af392b11ef 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -1013,16 +1013,20 @@ def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path):
def run_evaluate_static(h5f, ckpt_dir_s_path, prob_thresh=0.5, satellite='GOES16', domain='FD'):
data_dct, ll, cc = make_for_full_domain_predict(h5f, name_list=train_params, domain=domain)
+ num_elems = len(cc)
+ num_lines = len(ll)
ckpt_dir_s = os.listdir(ckpt_dir_s_path)
+ nav = get_navigation(satellite, domain)
+
prob_s = []
for ckpt in ckpt_dir_s:
ckpt_dir = ckpt_dir_s_path + ckpt
if not os.path.isdir(ckpt_dir):
continue
nn = IcingIntensityNN()
- nn.setup_eval_pipeline(data_dct, len(ll) * len(cc))
+ nn.setup_eval_pipeline(data_dct, num_lines * num_elems)
nn.build_model()
nn.build_training()
nn.build_evaluation()
@@ -1040,23 +1044,26 @@ def run_evaluate_static(h5f, ckpt_dir_s_path, prob_thresh=0.5, satellite='GOES16
preds = np.where(probs > prob_thresh, 1, 0)
else:
preds = np.argmax(probs, axis=1)
+ preds_2d = preds.reshape((len(ll), len(cc)))
+ cc = np.array(cc)
+ ll = np.array(ll)
+ x_rad = cc * nav.CFAC + nav.COFF
+ y_rad = ll * nav.LFAC + nav.LOFF
ll, cc = np.meshgrid(ll, cc, indexing='ij')
cc = cc.flatten()
ll = ll.flatten()
+ lon_s, lat_s = nav.lc_to_earth(cc, ll)
+ lons_2d = lon_s.reshape((num_lines, num_elems))
+ lats_2d = lat_s.reshape((num_lines, num_elems))
+
ice_mask = preds == 1
ice_cc = cc[ice_mask]
ice_ll = ll[ice_mask]
- nav = get_navigation(satellite, domain)
- ice_lons = []
- ice_lats = []
- for k in range(ice_cc.shape[0]):
- lon, lat = nav.lc_to_earth(ice_cc[k], ice_ll[k])
- ice_lons.append(lon)
- ice_lats.append(lat)
-
- return ice_lons, ice_lats
+ ice_lons, ice_lats = nav.lc_to_earth(ice_cc, ice_ll)
+
+ return ice_lons, ice_lats, preds_2d, lons_2d, lats_2d, x_rad, y_rad
if __name__ == "__main__":
diff --git a/modules/icing/pirep_goes.py b/modules/icing/pirep_goes.py
index f781fec0dc229d5d4c763947ae3169a658ba8ec5..af2f4e4cfc839644945fedbc1090ad58b7f92713 100644
--- a/modules/icing/pirep_goes.py
+++ b/modules/icing/pirep_goes.py
@@ -4,7 +4,7 @@ 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, make_times, find_bin_index, get_timestamp, homedir
+ check_oblique, make_times, find_bin_index, get_timestamp, homedir, write_icing_file
from util.plot import make_icing_image
from aeolus.datasource import CLAVRx, CLAVRx_VIIRS, GOESL1B, CLAVRx_H08
import h5py
@@ -1883,7 +1883,9 @@ def run_make_images(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', ckpt_dir_s_pat
else:
keep_lons = None
keep_lats = None
- ice_lons, ice_lats = run_evaluate_static(h5f, ckpt_dir_s_path=ckpt_dir_s_path, prob_thresh=prob_thresh, satellite=satellite, domain=domain)
+
+ ice_lons, ice_lats, preds_2d, lons_2d, lats_2d, x_rad, y_rad = run_evaluate_static(h5f, ckpt_dir_s_path=ckpt_dir_s_path, prob_thresh=prob_thresh, satellite=satellite, domain=domain)
make_icing_image(h5f, ice_lons, ice_lats, clvrx_str_time, satellite, domain, ice_lons_vld=keep_lons, ice_lats_vld=keep_lats, extent=extent)
+ write_icing_file(clvrx_str_time, preds_2d, x_rad, y_rad, lons_2d, lats_2d)
print('Done: ', clvrx_str_time)
h5f.close()
diff --git a/modules/util/util.py b/modules/util/util.py
index 9953dfcc255dd7899c7722e30cbd03db80645ac6..e474ad8d440c424aee2fc004859eabd4e4fe2c38 100644
--- a/modules/util/util.py
+++ b/modules/util/util.py
@@ -557,4 +557,57 @@ def make_for_full_domain_predict(h5f, name_list=None, satellite='GOES16', domain
grd_dct[ds_name] = np.stack(grd_dct_n[ds_name])
return grd_dct, ll, cc
-# -------------------------------------------------------------------------------------------
\ No newline at end of file
+# -------------------------------------------------------------------------------------------
+
+
+def write_icing_file(clvrx_str_time, preds, x, y, lons, lats):
+ outfile_name = homedir + 'icing_prediction_'+clvrx_str_time+'.h5'
+ h5f_out = h5py.File(outfile_name, 'w')
+
+ icing_pred_ds = h5f_out.create_dataset('icing_prediction', data=preds, dtype='i2')
+ icing_pred_ds.attrs.create('coordinates', data='y x')
+ icing_pred_ds.attrs.create('grid_mapping', data='Projection')
+
+ lon_ds = h5f_out.create_dataset('longitude', data=lons, dtype='f4')
+ lon_ds.attrs.create('units', data='degrees_east')
+ lon_ds.attrs.create('long_name', data='icing prediction longitude')
+
+ lat_ds = h5f_out.create_dataset('latitude', data=lats, dtype='f4')
+ lat_ds.attrs.create('units', data='degrees_north')
+ lat_ds.attrs.create('long_name', data='icing prediction latitude')
+
+ proj_ds = h5f_out.create_dataset('Projection', data=0, dtype='b')
+ proj_ds.attrs.create('long_name', data='Himawari Imagery Projection')
+ proj_ds.attrs.create('sweep_angle_axis', data='y')
+ proj_ds.attrs.create('units', data='radians')
+ proj_ds.attrs.create('semi_major_axis', data=6378.137)
+ proj_ds.attrs.create('semi_minor_axis', data=6356.7523)
+ proj_ds.attrs.create('inverse_flattening', data=298.257)
+ proj_ds.attrs.create('perspective_point_height', data=35785.863)
+ proj_ds.attrs.create('latitude_of_projection_origin', data=0.0)
+ proj_ds.attrs.create('longitude_of_projection_origin', data=140.7)
+ proj_ds.attrs.create('CFAC', data=20466275)
+ proj_ds.attrs.create('LFAC', data=20466275)
+ proj_ds.attrs.create('COFF', data=2750.5)
+ proj_ds.attrs.create('LOFF', data=2750.5)
+
+ if x is not None:
+ x_ds = h5f_out.create_dataset('x', data=x, dtype='f8')
+ x_ds.attrs.create('units', data='radians')
+ x_ds.attrs.create('standard_name', data='projection_x_coordinate')
+ x_ds.attrs.create('long_name', data='GOES PUG W-E fixed grid viewing angle')
+ x_ds.attrs.create('scale_factor', data=5.58879902955962e-05)
+ x_ds.attrs.create('add_offset', data=-0.153719917308037)
+ x_ds.attrs.create('CFAC', data=20466275)
+ x_ds.attrs.create('COFF', data=2750.5)
+
+ y_ds = h5f_out.create_dataset('y', data=y, dtype='f8')
+ y_ds.attrs.create('units', data='radians')
+ y_ds.attrs.create('standard_name', data='projection_y_coordinate')
+ y_ds.attrs.create('long_name', data='GOES PUG S-N fixed grid viewing angle')
+ y_ds.attrs.create('scale_factor', data=-5.58879902955962e-05)
+ y_ds.attrs.create('add_offset', data=0.153719917308037)
+ y_ds.attrs.create('LFAC', data=20466275)
+ y_ds.attrs.create('LOFF', data=2750.5)
+
+ h5f_out.close()