From 4bfbe59adb880c16a1133fdad628a276992ee530 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Sat, 5 Nov 2022 13:12:41 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cnn_cld_frac.py | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/modules/deeplearning/cnn_cld_frac.py b/modules/deeplearning/cnn_cld_frac.py
index b8f84f39..1a5c8b98 100644
--- a/modules/deeplearning/cnn_cld_frac.py
+++ b/modules/deeplearning/cnn_cld_frac.py
@@ -280,12 +280,8 @@ class CNN:
tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
data_norm.append(tmp)
# --------
- tmp = input_data[:, label_idx, y_128_2, x_128_2]
- if label_param != 'cloud_fraction':
- tmp = normalize(tmp, label_param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
- else:
- tmp = np.where(np.isnan(tmp), 0, tmp)
- tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
+ tmp = input_data[:, label_idx, y_128, x_128]
+ tmp = np.where(np.isnan(tmp), 0, tmp) # shouldn't need this
data_norm.append(tmp)
# ---------
data = np.stack(data_norm, axis=3)
@@ -464,6 +460,10 @@ class CNN:
conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_3')
+ conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_4')
+
+ conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_5')
+
# conv = conv + conv_b
print(conv.shape)
--
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