Use correct label for colour

1 files changed, 2 insertions, 2 deletions

diff --git a/lenet.py b/lenet.py
index 3d9ed20..273053d 100644
--- a/lenet.py
+++ b/lenet.py
@@ -161,7 +161,7 @@ def test_classifier(model, x_test, y_true, conf_mat=False, pca=False, tsne=False
     set_pca = PCA(n_components=2)
     pca_rep = set_pca.fit_transform(logits)
     pca_rep, y_tmp = shuffle(pca_rep, y_true, random_state=0)
-    plt.scatter(pca_rep[:1000, 0], pca_rep[:1000, 1], c=y_true[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
+    plt.scatter(pca_rep[:1000, 0], pca_rep[:1000, 1], c=y_tmp[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
     plt.xlabel('component 1')
     plt.ylabel('component 2')
     plt.colorbar();
@@ -171,7 +171,7 @@ def test_classifier(model, x_test, y_true, conf_mat=False, pca=False, tsne=False
     components = tsne.fit_transform(logits)
     print(components.shape)
     components, y_tmp = shuffle(components, y_true, random_state=0)
-    plt.scatter(components[:1000, 0], components[:1000, 1], c=y_true[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
+    plt.scatter(components[:1000, 0], components[:1000, 1], c=y_tmp[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
     plt.xlabel('component 1')
     plt.ylabel('component 2')
     plt.colorbar();