ENH more readable iris dots in example
@@ -40,7 +40,7 @@ plt.figure(2, figsize=(8, 6))
plt.clf()
# Plot the training points
-plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Paired,
+plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Set1,
edgecolor='k')
plt.xlabel('Sepal length')
plt.ylabel('Sepal width')
@@ -56,7 +56,7 @@ fig = plt.figure(1, figsize=(8, 6))
ax = Axes3D(fig, elev=-150, azim=110)
X_reduced = PCA(n_components=3).fit_transform(iris.data)
ax.scatter(X_reduced[:, 0], X_reduced[:, 1], X_reduced[:, 2], c=y,
- cmap=plt.cm.Paired, edgecolor='k')
+ cmap=plt.cm.Set1, edgecolor='k', s=40)
ax.set_title("First three PCA directions")
ax.set_xlabel("1st eigenvector")
ax.w_xaxis.set_ticklabels([])
