From e0a5ae8674d982a2b8ed1009db32a9bad49f9277 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 19 May 2021 11:00:56 -0500
Subject: [PATCH] minor...
---
modules/deeplearning/icing_cnn.py | 46 +++++++++++++++++--------------
1 file changed, 25 insertions(+), 21 deletions(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index aee3e3b5..8f33d0c3 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -150,6 +150,8 @@ class IcingIntensityNN:
self.test_recall = None
self.test_precision = None
self.test_confusion_matrix = None
+ self.test_f1score = None
+ self.test_mcc = None
self.test_true_pos = None
self.test_true_neg = None
self.test_false_pos = None
@@ -483,6 +485,8 @@ class IcingIntensityNN:
self.test_auc = tf.keras.metrics.AUC(name='test_auc')
self.test_recall = tf.keras.metrics.Recall(name='test_recall')
self.test_precision = tf.keras.metrics.Precision(name='test_precision')
+ self.test_f1score = tfa.metrics.F1Score(2, threshold=0.5, name='test_f1score')
+ self.test_mcc = tfa.metrics.MatthewsCorrelationCoefficient(2, name='test_mcc')
self.test_true_neg = tf.keras.metrics.TrueNegatives(name='test_true_neg')
self.test_true_pos = tf.keras.metrics.TruePositives(name='test_true_pos')
self.test_false_neg = tf.keras.metrics.FalseNegatives(name='test_false_neg')
@@ -542,6 +546,8 @@ class IcingIntensityNN:
self.test_true_pos(labels, pred)
self.test_false_neg(labels, pred)
self.test_false_pos(labels, pred)
+ self.test_f1score(labels, pred)
+ self.test_mcc(labels, pred)
def predict(self, mini_batch):
inputs = [mini_batch[0]]
@@ -562,6 +568,22 @@ class IcingIntensityNN:
self.test_false_neg(labels, pred)
self.test_false_pos(labels, pred)
+ def reset_test_metrics(self):
+ self.test_loss.reset_states()
+ self.test_accuracy.reset_states()
+ self.test_auc.reset_states()
+ self.test_recall.reset_states()
+ self.test_precision.reset_states()
+ self.test_f1score.reset_states()
+ self.test_mcc.reset_states()
+ self.test_true_neg.reset_states()
+ self.test_true_pos.reset_states()
+ self.test_false_neg.reset_states()
+ self.test_false_pos.reset_states()
+
+ def do_metrics(self):
+ pass
+
def do_training(self, ckpt_dir=None):
if ckpt_dir is None:
@@ -602,16 +624,7 @@ class IcingIntensityNN:
tf.summary.scalar('num_train_steps', step, step=step)
tf.summary.scalar('num_epochs', epoch, step=step)
- self.test_loss.reset_states()
- self.test_accuracy.reset_states()
- self.test_auc.reset_states()
- self.test_recall.reset_states()
- self.test_precision.reset_states()
- self.test_true_neg.reset_states()
- self.test_true_pos.reset_states()
- self.test_false_neg.reset_states()
- self.test_false_pos.reset_states()
-
+ self.reset_test_metrics()
for data0_tst, label_tst in self.test_dataset:
tst_ds = tf.data.Dataset.from_tensor_slices((data0_tst, label_tst))
tst_ds = tst_ds.batch(BATCH_SIZE)
@@ -653,16 +666,7 @@ class IcingIntensityNN:
print('End of Epoch: ', epoch+1, 'elapsed time: ', (t1-t0))
total_time += (t1-t0)
- self.test_loss.reset_states()
- self.test_accuracy.reset_states()
- self.test_auc.reset_states()
- self.test_recall.reset_states()
- self.test_precision.reset_states()
- self.test_true_neg.reset_states()
- self.test_true_pos.reset_states()
- self.test_false_neg.reset_states()
- self.test_false_pos.reset_states()
-
+ self.reset_test_metrics()
for data0, label in self.test_dataset:
ds = tf.data.Dataset.from_tensor_slices((data0, label))
ds = ds.batch(BATCH_SIZE)
@@ -681,7 +685,7 @@ class IcingIntensityNN:
mcc = ((tp*tn) - (fp*fn))/np.sqrt((tp+fp)*(tp+fn)*(tn+fp)*(tn+fn))
print('loss, acc, recall, precision, auc, f1, mcc: ', self.test_loss.result().numpy(), self.test_accuracy.result().numpy(),
- recall, precsn, self.test_auc.result().numpy(), f1, mcc)
+ recall, precsn, self.test_auc.result().numpy(), f1, self.test_f1score.result().numpy(), mcc, self.test_mcc.result().numpy())
print('--------------------------------------------------')
ckpt_manager.save()
--
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