From cfad92c9f7fdb3f9ade02c648ad8375839698d3a Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 13 Sep 2022 12:29:09 -0500
Subject: [PATCH] snaphot...
---
modules/deeplearning/srcnn.py | 30 ++++++++++++++++++++++++------
1 file changed, 24 insertions(+), 6 deletions(-)
diff --git a/modules/deeplearning/srcnn.py b/modules/deeplearning/srcnn.py
index 2c040602..f5391cd5 100644
--- a/modules/deeplearning/srcnn.py
+++ b/modules/deeplearning/srcnn.py
@@ -1,7 +1,7 @@
import glob
import tensorflow as tf
from util.setup import logdir, modeldir, cachepath, now, ancillary_path
-from util.util import EarlyStop, normalize, denormalize, resample
+from util.util import EarlyStop, normalize, denormalize, resample, get_grid_values_all
import os, datetime
import numpy as np
import pickle
@@ -49,13 +49,13 @@ mean_std_dct.update(mean_std_dct_l2)
# emis_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom',
# 'temp_6_7um_nom', 'temp_6_2um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom']
-data_params = ['refl_0_65um_nom', 'temp_11_0um_nom', 'cld_temp_acha', 'cld_press_acha', 'cloud_fraction']
-label_params = ['refl_0_65um_nom', 'temp_11_0um_nom', 'cld_temp_acha', 'cld_press_acha', 'cloud_fraction']
+data_params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'cld_temp_acha', 'cld_press_acha']
+label_params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'cld_temp_acha', 'cld_press_acha']
DO_ZERO_OUT = False
-data_idx, label_idx = 4, 4
+data_idx, label_idx = 0, 0
data_param = data_params[data_idx]
label_param = label_params[label_idx]
print(data_param+', '+label_param)
@@ -603,8 +603,8 @@ class SRCNN:
ckpt.restore(ckpt_manager.latest_checkpoint)
data = normalize(nda_lr, param, mean_std_dct)
- #data = np.expand_dims(data, axis=0)
- #data = np.expand_dims(data, axis=3)
+ data = np.expand_dims(data, axis=0)
+ data = np.expand_dims(data, axis=3)
self.reset_test_metrics()
@@ -668,6 +668,24 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
return out_sr
+def run_evaluate_static_new(in_file, out_file, ckpt_dir):
+ nda = np.load(in_file)
+
+ nda = nda[:, data_idx, 3:131:2, 3:131:2]
+ nda = resample(x_64, y_64, nda, t, s)
+ nda = np.expand_dims(nda, axis=3)
+
+ h5f = h5py.File(in_file, 'r')
+ grd = get_grid_values_all(h5f, data_param)
+
+ nn = SRCNN()
+ out_sr = nn.run_evaluate(grd, data_param, ckpt_dir)
+ if out_file is not None:
+ np.save(out_file, out_sr)
+ else:
+ return out_sr
+
+
if __name__ == "__main__":
nn = SRCNN()
nn.run('matchup_filename')
--
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