From 97c48b52a2ca38a3044f8f5c867b392ffe765fd7 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 13 Feb 2023 15:22:19 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/cnn_cld_frac.py | 9 ++-------
1 file changed, 2 insertions(+), 7 deletions(-)
diff --git a/modules/deeplearning/cnn_cld_frac.py b/modules/deeplearning/cnn_cld_frac.py
index 7a3271bb..d51c45ae 100644
--- a/modules/deeplearning/cnn_cld_frac.py
+++ b/modules/deeplearning/cnn_cld_frac.py
@@ -381,13 +381,12 @@ class SRCNN:
tmp = input_data[:, label_idx, :, :]
tmp = tmp.copy()
tmp = np.where(np.isnan(tmp), 0, tmp)
- if DO_SMOOTH:
- tmp = smooth_2d(tmp, sigma=SIGMA)
- # tmp = median_filter_2d(tmp)
if DO_ESPCN:
tmp = tmp[:, slc_y_2, slc_x_2]
else: # Half res upsampled to full res:
tmp = upsample(tmp)
+ # tmp = upsample_mean(tmp)
+ # tmp = tmp[:, slc_y, slc_x]
if label_param != 'cloud_probability':
tmp = normalize(tmp, label_param, mean_std_dct)
if DO_ADD_NOISE:
@@ -405,10 +404,6 @@ class SRCNN:
# -----------------------------------------------------
label = input_data[:, label_idx, :, :]
label = label.copy()
- # if DO_SMOOTH:
- # label = np.where(np.isnan(label), 0, label)
- # label = smooth_2d(label, sigma=SIGMA)
- # # label = median_filter_2d(label)
label = label[:, y_128, x_128]
label = get_label_data(label)
--
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