From f18e4d498c452b0950d2935b359e4194e189f6e2 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 19 Apr 2023 16:14:14 -0500
Subject: [PATCH] snapshot...
---
.../deeplearning/cloud_fraction_fcn_abi.py | 41 +++++++++++--------
1 file changed, 25 insertions(+), 16 deletions(-)
diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py
index a13737c7..e2161efa 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi.py
@@ -60,6 +60,7 @@ label_param = 'cloud_probability'
params = ['temp_11_0um_nom', 'refl_0_65um_nom', 'refl_submin_ch01', 'refl_submax_ch01', 'refl_substddev_ch01', label_param]
params_i = ['temp_11_0um_nom', 'refl_0_65um_nom', label_param]
data_params_half = ['temp_11_0um_nom']
+sub_fields = ['refl_submin_ch01', 'refl_submax_ch01', 'refl_substddev_ch01']
data_params_full = ['refl_0_65um_nom']
label_idx_i = params_i.index(label_param)
@@ -313,27 +314,35 @@ class SRCNN:
data_norm = []
for param in data_params_half:
# If next 2 uncommented, take out get_grid_cell_mean
- # idx = params.index(param)
- # tmp = input_data[:, idx, :, :]
- idx = params_i.index(param)
- tmp = input_label[:, idx, :, :]
- tmp = get_grid_cell_mean(tmp)
+ idx = params.index(param)
+ tmp = input_data[:, idx, :, :]
+ # idx = params_i.index(param)
+ # tmp = input_label[:, idx, :, :]
+ # tmp = get_grid_cell_mean(tmp)
tmp = tmp[:, slc_y, slc_x]
tmp = normalize(tmp, param, mean_std_dct)
data_norm.append(tmp)
- for param in data_params_full:
- idx = params_i.index(param)
- tmp = input_label[:, idx, :, :]
-
- lo, hi, std, avg = get_min_max_std(tmp)
- lo = normalize(lo, param, mean_std_dct)
- hi = normalize(hi, param, mean_std_dct)
- avg = normalize(avg, param, mean_std_dct)
+ for param in sub_fields:
+ idx = params.index(param)
+ tmp = input_data[:, idx, :, :]
+ tmp = tmp[:, slc_y, slc_x]
+ if param != 'refl_substddev_ch01':
+ tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
+ data_norm.append(tmp)
- data_norm.append(lo[:, slc_y, slc_x])
- data_norm.append(hi[:, slc_y, slc_x])
- data_norm.append(std[:, slc_y, slc_x])
+ # for param in data_params_full:
+ # idx = params_i.index(param)
+ # tmp = input_label[:, idx, :, :]
+ #
+ # lo, hi, std, avg = get_min_max_std(tmp)
+ # lo = normalize(lo, param, mean_std_dct)
+ # hi = normalize(hi, param, mean_std_dct)
+ # # avg = normalize(avg, param, mean_std_dct)
+ #
+ # data_norm.append(lo[:, slc_y, slc_x])
+ # data_norm.append(hi[:, slc_y, slc_x])
+ # data_norm.append(std[:, slc_y, slc_x])
# ---------------------------------------------------
# If next uncommented, take out get_grid_cell_mean
# tmp = input_data[:, label_idx, :, :]
--
GitLab