From 0c4523fdba427ba84d4d43890f64ecd3ce8fbfb5 Mon Sep 17 00:00:00 2001
From: Mohamed Haseeb <mohamedaziz52@gmail.com>
Date: Sun, 23 Dec 2018 18:36:21 +0100
Subject: [PATCH] printouts update

---
 example.py                                      | 4 ++--
 shapelets_lts/classification/shapelet_models.py | 6 ++++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/example.py b/example.py
index 93b41ee..282c287 100644
--- a/example.py
+++ b/example.py
@@ -29,7 +29,7 @@ def main():
     print('\nLoading data...')
     x_train, y_train, x_test, y_test = _load_train_test_datasets()
 
-    # create a classifier. (200 epochs yielded a 0.99 accuracy)
+    # create a classifier
     Q = x_train.shape[1]
     K = int(0.15 * Q)
     L_min = int(0.2 * Q)
@@ -37,7 +37,7 @@ def main():
         K=K,
         R=3,
         L_min=L_min,
-        epocs=200,
+        epocs=30,  # (200 epochs yielded a 0.99 accuracy)
         lamda=0.01,
         eta=0.01,
         shapelet_initialization='segments_centroids',
diff --git a/shapelets_lts/classification/shapelet_models.py b/shapelets_lts/classification/shapelet_models.py
index bf895ab..e160f99 100644
--- a/shapelets_lts/classification/shapelet_models.py
+++ b/shapelets_lts/classification/shapelet_models.py
@@ -178,8 +178,10 @@ def _train_network(self):
 
             valid_accur[0, epoc] = valid_epoc_accur
             # print current loss info
-            print("epoc=" + str(epoc) + "/" + str(self.epocs - 1) + " (iteration=" + str(iteration) + ") loss=" + str(l)
-                  + " validation accuracy=" + str(valid_epoc_accur))
+            print(
+                'epoch={}/{} (iteration={}) loss={} validation accuracy={}'
+                ''.format(epoc + 1, self.epocs, iteration, l, valid_epoc_accur)
+            )
             # plot if needed
             if self.plot_loss:
                 self._plot_loss(loss, valid_accur, epoc)