From 294475b0501a3e7911c68abc44c11e2e396ae7ae Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 15 Jun 2023 13:45:56 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_srcnn_viirs.py | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_viirs.py b/modules/deeplearning/cloud_opd_srcnn_viirs.py
index 55344d85..220f09a9 100644
--- a/modules/deeplearning/cloud_opd_srcnn_viirs.py
+++ b/modules/deeplearning/cloud_opd_srcnn_viirs.py
@@ -291,8 +291,8 @@ class SRCNN:
# -----------------------------------------------------
# -----------------------------------------------------
label = input_label[:, label_idx_i, :, :]
- # label = normalize(label, label_param, mean_std_dct)
- label = scale(label, label_param, mean_std_dct)
+ label = normalize(label, label_param, mean_std_dct)
+ # label = scale(label, label_param, mean_std_dct)
label = label[:, self.y_128, self.x_128]
label = np.where(np.isnan(label), 0, label)
@@ -620,10 +620,10 @@ class SRCNN:
preds = np.concatenate(self.test_preds)
print(labels.shape, preds.shape)
- # labels_denorm = denormalize(labels, label_param, mean_std_dct)
- # preds_denorm = denormalize(preds, label_param, mean_std_dct)
- labels_denorm = descale(labels, label_param, mean_std_dct)
- preds_denorm = descale(preds, label_param, mean_std_dct)
+ labels_denorm = denormalize(labels, label_param, mean_std_dct)
+ preds_denorm = denormalize(preds, label_param, mean_std_dct)
+ # labels_denorm = descale(labels, label_param, mean_std_dct)
+ # preds_denorm = descale(preds, label_param, mean_std_dct)
print(preds_denorm.min(), preds_denorm.max())
return labels_denorm, preds_denorm
@@ -736,8 +736,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
h5f.close()
cld_opd_sres = nn.run_evaluate(data, ckpt_dir)
- # cld_opd_sres = denormalize(cld_opd_sres, label_param, mean_std_dct)
- cld_opd_sres = descale(cld_opd_sres, label_param, mean_std_dct)
+ cld_opd_sres = denormalize(cld_opd_sres, label_param, mean_std_dct)
+ # cld_opd_sres = descale(cld_opd_sres, label_param, mean_std_dct)
_, ylen, xlen, _ = cld_opd_sres.shape
cld_opd_sres_out = np.zeros((LEN_Y, LEN_X), dtype=np.float32)
--
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