diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py index f5b4076d3369a8ea0143271ce61958df324d4e1e..2c579ed46a2d37c86ca89ccc8262294e363fcf6e 100644 --- a/modules/deeplearning/icing_cnn.py +++ b/modules/deeplearning/icing_cnn.py @@ -48,8 +48,8 @@ f.close() # 'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_acha', 'cld_opd_acha'] # -- DAY L2 ------------- train_params = ['cld_height_acha', 'cld_geo_thick', 'cld_temp_acha', 'cld_press_acha', 'supercooled_cloud_fraction', - 'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'cld_cwp_dcomp', 'iwc_dcomp', 'lwc_dcomp'] -# 'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'iwc_dcomp', 'lwc_dcomp'] +# 'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'cld_cwp_dcomp', 'iwc_dcomp', 'lwc_dcomp'] + 'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'iwc_dcomp', 'lwc_dcomp'] # -- DAY L1B -------------------------------- # train_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom', # 'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom', @@ -886,8 +886,8 @@ def run_restore_static(filename_tst, ckpt_dir_s_path): return cm_avg -def run_evaluate_static(filename, ckpt_dir_s_path, prob_thresh=0.5): - data_dct, ll, cc = make_for_full_domain_predict(filename, name_list=train_params) +def run_evaluate_static(filename, ckpt_dir_s_path, prob_thresh=0.5, domain='FD'): + data_dct, ll, cc = make_for_full_domain_predict(filename, name_list=train_params, doamin=domain) ckpt_dir_s = os.listdir(ckpt_dir_s_path) prob_s = [] for ckpt in ckpt_dir_s: @@ -920,9 +920,10 @@ def run_evaluate_static(filename, ckpt_dir_s_path, prob_thresh=0.5): ice_cc = cc[ice_mask] ice_ll = ll[ice_mask] - nav = GEOSNavigation(sub_lon=-75.0, CFAC=5.6E-05, COFF=-0.101332, LFAC=-5.6E-05, LOFF=0.128212, num_elems=2500, - num_lines=1500) - + if domain == 'CONUS': + nav = GEOSNavigation(sub_lon=-75.0, CFAC=5.6E-05, COFF=-0.101332, LFAC=-5.6E-05, LOFF=0.128212, num_elems=2500, num_lines=1500) + elif domain == 'FD': + nav = GEOSNavigation(sub_lon=-75.0, CFAC=5.6E-05, COFF=-0.151844, LFAC=-5.6E-05, LOFF=0.151844, num_elems=5424, num_lines=5424) ice_lons = [] ice_lats = [] for k in range(ice_cc.shape[0]):