From 4c29a2613e67791ba02a615d541cc4b753ab06d3 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Fri, 23 Dec 2022 09:40:29 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index fd10b532..6895b8b9 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -755,6 +755,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
hr_grd_a = grd_a.copy()
hr_grd_a = hr_grd_a[y_128, x_128]
grd_a = grd_a[slc_y_2, slc_x_2]
+ grd_a = resample_2d_linear_one(x_2, y_2, grd_a, t, s)
+ grd_a = grd_a[:, y_k, x_k]
grd_a = normalize(grd_a, 'temp_11_0um_nom', mean_std_dct)
#
# grd_b = get_grid_values_all(h5f, 'refl_0_65um_nom')
@@ -769,10 +771,10 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
hr_grd_c = grd_c.copy()
hr_grd_c = hr_grd_c[y_128, x_128]
grd_c = grd_c[slc_y_2, slc_x_2]
- if label_param != 'cloud_probability':
- grd_c = normalize(grd_c, label_param, mean_std_dct)
grd_c = resample_2d_linear_one(x_2, y_2, grd_c, t, s)
grd_c = grd_c[y_k, x_k]
+ if label_param != 'cloud_probability':
+ grd_c = normalize(grd_c, label_param, mean_std_dct)
# data = np.stack([grd_a, grd_b, grd_c], axis=2)
data = np.stack([grd_a, grd_c], axis=2)
--
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