From 9b3db84964092cfc6d6068413d681ab62395a677 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 2 Jan 2023 13:02:08 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/icing_fcn.py | 28 ++++++++++++++--------------
1 file changed, 14 insertions(+), 14 deletions(-)
diff --git a/modules/deeplearning/icing_fcn.py b/modules/deeplearning/icing_fcn.py
index 1803fc46..576e3de0 100644
--- a/modules/deeplearning/icing_fcn.py
+++ b/modules/deeplearning/icing_fcn.py
@@ -19,6 +19,7 @@ if NumClasses == 2:
NumLogits = 1
else:
NumLogits = NumClasses
+NumFlightLevels = 3
BATCH_SIZE = 128
NUM_EPOCHS = 60
@@ -241,8 +242,7 @@ class IcingIntensityFCN:
self.X_img = tf.keras.Input(shape=(None, None, n_chans))
self.inputs.append(self.X_img)
- #self.inputs.append(tf.keras.Input(shape=(None, None, 5)))
- self.inputs.append(tf.keras.Input(shape=(None, None, 3)))
+ self.inputs.append(tf.keras.Input(shape=(None, None, NumFlightLevels)))
self.flight_level = 0
@@ -362,18 +362,18 @@ class IcingIntensityFCN:
nda = h5f[param][nd_idxs,]
- # nda[np.logical_and(nda >= 0, nda < 2000)] = 0
- # nda[np.logical_and(nda >= 2000, nda < 4000)] = 1
- # nda[np.logical_and(nda >= 4000, nda < 6000)] = 2
- # nda[np.logical_and(nda >= 6000, nda < 8000)] = 3
- # nda[np.logical_and(nda >= 8000, nda < 15000)] = 4
-
- nda[np.logical_and(nda >= 0, nda < 3000)] = 0
- nda[np.logical_and(nda >= 3000, nda < 6000)] = 1
- nda[np.logical_and(nda >= 6000, nda < 15000)] = 2
-
- # nda = tf.one_hot(nda, 5).numpy()
- nda = tf.one_hot(nda, 3).numpy()
+ if NumFlightLevels == 5:
+ nda[np.logical_and(nda >= 0, nda < 2000)] = 0
+ nda[np.logical_and(nda >= 2000, nda < 4000)] = 1
+ nda[np.logical_and(nda >= 4000, nda < 6000)] = 2
+ nda[np.logical_and(nda >= 6000, nda < 8000)] = 3
+ nda[np.logical_and(nda >= 8000, nda < 15000)] = 4
+ elif NumFlightLevels == 3:
+ nda[np.logical_and(nda >= 0, nda < 3000)] = 0
+ nda[np.logical_and(nda >= 3000, nda < 6000)] = 1
+ nda[np.logical_and(nda >= 6000, nda < 15000)] = 2
+
+ nda = tf.one_hot(nda, NumFlightLevels).numpy()
nda = np.expand_dims(nda, axis=1)
nda = np.expand_dims(nda, axis=1)
--
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