Slightly improve graphs

1 files changed, 6 insertions, 6 deletions

diff --git a/lenet.py b/lenet.py
index 273053d..9b4bb2e 100644
--- a/lenet.py
+++ b/lenet.py
@@ -161,9 +161,9 @@ 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_tmp[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
-    plt.xlabel('component 1')
-    plt.ylabel('component 2')
+    plt.scatter(pca_rep[:5000, 0], pca_rep[:5000, 1], c=y_tmp[:5000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
+    plt.xlabel('Feature 1')
+    plt.ylabel('Feature 2')
     plt.colorbar();
     plt.show()
   if tsne:
@@ -171,9 +171,9 @@ 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_tmp[:1000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
-    plt.xlabel('component 1')
-    plt.ylabel('component 2')
+    plt.scatter(components[:5000, 0], components[:5000, 1], c=y_tmp[:5000], edgecolor='none', alpha=0.5, cmap=plt.cm.get_cmap('Paired', 10))
+    plt.xlabel('Feature 1')
+    plt.ylabel('Feature 2')
     plt.colorbar();
     plt.show()