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-rw-r--r--lenet.py4
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();