diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index b724b92..1025693 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -225,7 +225,7 @@
   <component name="PropertiesComponent">
     <property name="WebServerToolWindowFactoryState" value="false" />
     <property name="aspect.path.notification.shown" value="true" />
-    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588386264613" />
+    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588386307951" />
     <property name="go.gopath.indexing.explicitly.defined" value="true" />
     <property name="nodejs_interpreter_path.stuck_in_default_project" value="undefined stuck path" />
     <property name="nodejs_npm_path_reset_for_default_project" value="true" />
diff --git a/train.py b/train.py
index a05c6e4..7696112 100644
--- a/train.py
+++ b/train.py
@@ -100,12 +100,10 @@ def experiment(repeats, series, seed):
 	for r in range(repeats):
 		# fit the model
 		batch_size = 4
-		t = train.shape[0] % batch_size
-		train = train[train.shape[0] - t * batch_size:]
-		t = test.shape[0] % batch_size
-		test = test[test.shape[0] - t * batch_size:]
+		t1 = train.shape[0] % batch_size
+		t2 = test.shape[0] % batch_size
 
-		train_trimmed = train_scaled[2:, :]
+		train_trimmed = train_scaled[train_scaled.shape[0] - t1 * batch_size:, :]
 		lstm_model = fit_lstm(train_trimmed, batch_size, 30, 4)
 		# forecast the entire training dataset to build up state for forecasting
 		if seed: