From 6d7b2a097cfba775ee7c3d1b6f543f902f83d841 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 21 Mar 2023 15:15:05 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_fraction_fcn.py | 20 ++++++++++++--------
1 file changed, 12 insertions(+), 8 deletions(-)
diff --git a/modules/deeplearning/cloud_fraction_fcn.py b/modules/deeplearning/cloud_fraction_fcn.py
index 98b7d892..1693c6f5 100644
--- a/modules/deeplearning/cloud_fraction_fcn.py
+++ b/modules/deeplearning/cloud_fraction_fcn.py
@@ -783,26 +783,30 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
grd_a = get_grid_values_all(h5f, 'orig/temp_11_0um')
grd_a = np.where(np.isnan(grd_a), 0, grd_a)
- grd_a = grd_a[y_0:y_0+sub_y, x_0:x_0+sub_x]
+ # grd_a = grd_a[y_0:y_0+sub_y, x_0:x_0+sub_x]
grd_a = normalize(grd_a, 'temp_11_0um_nom', mean_std_dct)
- grd_a = grd_a[slc_y, slc_x]
+ #grd_a = grd_a[slc_y, slc_x]
+ grd_a = grd_a[2:3230, 2:1098]
grd_b = get_grid_values_all(h5f, 'super/refl_0_65um')
grd_b = np.where(np.isnan(grd_b), 0, grd_b)
- grd_b = grd_b[y_0:y_0+sub_y, x_0:x_0+sub_x]
+ #grd_b = grd_b[y_0:y_0+sub_y, x_0:x_0+sub_x]
grd_b = np.expand_dims(grd_b, axis=0)
lo, hi, std, avg = get_min_max_std(grd_b)
lo = normalize(lo, 'refl_0_65um_nom', mean_std_dct)
hi = normalize(hi, 'refl_0_65um_nom', mean_std_dct)
avg = normalize(avg, 'refl_0_65um_nom', mean_std_dct)
- lo = lo[0, slc_y, slc_x]
- hi = hi[0, slc_y, slc_x]
- avg = avg[0, slc_y, slc_x]
+ #lo = lo[0, slc_y, slc_x]
+ #hi = hi[0, slc_y, slc_x]
+ #avg = avg[0, slc_y, slc_x]
+ lo = lo[0, 2:3230, 2:1098]
+ hi = hi[0, 2:3230, 2:1098]
+ avg = avg[0, 2:3230, 2:1098]
grd_c = get_grid_values_all(h5f, 'orig/'+label_param)
grd_c = np.where(np.isnan(grd_c), 0, grd_c)
- grd_c = grd_c[y_0:y_0+sub_y, x_0:x_0+sub_x]
- grd_c = grd_c[slc_y, slc_x]
+ #grd_c = grd_c[y_0:y_0+sub_y, x_0:x_0+sub_x]
+ grd_c = grd_c[2:3230, 2:1098]
data = np.stack([grd_a, lo, hi, avg, grd_c], axis=2)
data = np.expand_dims(data, axis=0)
--
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