From e336db62b092ed68e29a3528fe9abe0032ee78e1 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 13 Jul 2023 14:20:31 -0500
Subject: [PATCH] `snapshot...`
---
modules/deeplearning/cloud_opd_srcnn_abi.py | 52 ++++++++++-----------
1 file changed, 26 insertions(+), 26 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_abi.py b/modules/deeplearning/cloud_opd_srcnn_abi.py
index d1447321..5c08ee46 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi.py
@@ -59,8 +59,7 @@ params_i = ['temp_11_0um_nom', 'refl_0_65um_nom', 'temp_stddev3x3_ch31', 'refl_s
# data_params_half = ['temp_11_0um_nom', 'refl_0_65um_nom']
data_params_half = ['temp_11_0um_nom']
data_params_full = ['refl_0_65um_nom']
-# sub_fields = ['refl_submin_ch01', 'refl_submax_ch01', 'refl_substddev_ch01']
-sub_fields = ['refl_substddev_ch01']
+sub_fields = ['refl_submin_ch01', 'refl_submax_ch01', 'refl_substddev_ch01']
# sub_fields = ['refl_stddev3x3_ch01']
label_idx_i = params_i.index(label_param)
@@ -211,7 +210,7 @@ class SRCNN:
self.test_label_files = None
# self.n_chans = len(data_params_half) + len(data_params_full) + 1
- self.n_chans = 4
+ self.n_chans = 3
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
@@ -274,21 +273,22 @@ class SRCNN:
data_norm.append(tmp)
# High res refectance ----------
- # idx = params_i.index('refl_0_65um_nom')
- # tmp = input_label[:, idx, :, :]
- # tmp = np.where(np.isnan(tmp), 0, tmp)
- # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
- # data_norm.append(tmp[:, self.slc_y, self.slc_x])
-
idx = params_i.index('refl_0_65um_nom')
tmp = input_label[:, idx, :, :]
- tmp = tmp.copy()
- tmp = np.where(np.isnan(tmp), 0.0, tmp)
- tmp = tmp[:, self.slc_y_2, self.slc_x_2]
- tmp = self.upsample(tmp)
- tmp = smooth_2d(tmp)
- tmp = normalize(tmp, label_param, mean_std_dct)
- data_norm.append(tmp)
+ tmp = np.where(np.isnan(tmp), 0, tmp)
+ tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
+ data_norm.append(tmp[:, self.slc_y, self.slc_x])
+
+ # High res reflectance down 2 ---------
+ # idx = params_i.index('refl_0_65um_nom')
+ # tmp = input_label[:, idx, :, :]
+ # tmp = tmp.copy()
+ # tmp = np.where(np.isnan(tmp), 0.0, tmp)
+ # tmp = tmp[:, self.slc_y_2, self.slc_x_2]
+ # tmp = self.upsample(tmp)
+ # tmp = smooth_2d(tmp)
+ # tmp = normalize(tmp, label_param, mean_std_dct)
+ # data_norm.append(tmp)
tmp = input_label[:, label_idx_i, :, :]
tmp = tmp.copy()
@@ -312,16 +312,16 @@ class SRCNN:
# tmp = np.where(np.isnan(tmp), 0.0, tmp)
# data_norm.append(tmp)
- for param in sub_fields:
- idx = params.index(param)
- tmp = input_data[:, idx, :, :]
- tmp = upsample_nearest(tmp)
- tmp = tmp[:, self.slc_y, self.slc_x]
- if param != 'refl_substddev_ch01':
- tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
- else:
- tmp = np.where(np.isnan(tmp), 0, tmp)
- data_norm.append(tmp)
+ # for param in sub_fields:
+ # idx = params.index(param)
+ # tmp = input_data[:, idx, :, :]
+ # tmp = upsample_nearest(tmp)
+ # tmp = tmp[:, self.slc_y, self.slc_x]
+ # if param != 'refl_substddev_ch01':
+ # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
+ # else:
+ # tmp = np.where(np.isnan(tmp), 0, tmp)
+ # data_norm.append(tmp)
# ---------------------------------------------------
data = np.stack(data_norm, axis=3)
--
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