[MRG] Modify Svm examples for matplotlibv2 comp (scikit-learn#8456)

* Modify plot_custom_kernel for matplotlib v2 comp Add `edgecolors` attribute in scatter plot for better visualization in matplotlib version 2 Issue: scikit-learn#8364 * Modify plot_oneclass.py for matplotlib v2 comp Add `edgecolors` attribute to scatter plot for better visualization in matplotlib version 2 Issue: scikit-learn#8364 * Modify plot_rbf_parameters for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_separating_hyperplane_unbalanced for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plo_svm_kernels for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_svm_margin for matplotlib v2 comp Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_svm_nonlinear for matplotlib v2 Add `edgecolors` attribute to scatter plot for matplotlib version 2 compatibility Issue: scikit-learn#8364 * Modify file for remove flake8 error Remove extra white space. Issue: scikit-learn#8364
lrcusack · Mar 4, 2017 · cdd693b · cdd693b
1 parent 75c892c
commit cdd693b
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Showing 7 changed files with 17 additions and 11 deletions.
diff --git a/examples/svm/plot_custom_kernel.py b/examples/svm/plot_custom_kernel.py
@@ -50,7 +50,7 @@ def my_kernel(X, Y):
 plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired)
 
 # Plot also 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.Paired, edgecolors='k')
 plt.title('3-Class classification using Support Vector Machine with custom'
           ' kernel')
 plt.axis('tight')

diff --git a/examples/svm/plot_oneclass.py b/examples/svm/plot_oneclass.py
@@ -46,9 +46,11 @@
 plt.contourf(xx, yy, Z, levels=[0, Z.max()], colors='palevioletred')
 
 s = 40
-b1 = plt.scatter(X_train[:, 0], X_train[:, 1], c='white', s=s)
-b2 = plt.scatter(X_test[:, 0], X_test[:, 1], c='blueviolet', s=s)
-c = plt.scatter(X_outliers[:, 0], X_outliers[:, 1], c='gold', s=s)
+b1 = plt.scatter(X_train[:, 0], X_train[:, 1], c='white', s=s, edgecolors='k')
+b2 = plt.scatter(X_test[:, 0], X_test[:, 1], c='blueviolet', s=s,
+                 edgecolors='k')
+c = plt.scatter(X_outliers[:, 0], X_outliers[:, 1], c='gold', s=s,
+                edgecolors='k')
 plt.axis('tight')
 plt.xlim((-5, 5))
 plt.ylim((-5, 5))

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
@@ -166,7 +166,8 @@ def __call__(self, value, clip=None):
 
     # visualize parameter's effect on decision function
     plt.pcolormesh(xx, yy, -Z, cmap=plt.cm.RdBu)
-    plt.scatter(X_2d[:, 0], X_2d[:, 1], c=y_2d, cmap=plt.cm.RdBu_r)
+    plt.scatter(X_2d[:, 0], X_2d[:, 1], c=y_2d, cmap=plt.cm.RdBu_r,
+                edgecolors='k')
     plt.xticks(())
     plt.yticks(())
     plt.axis('tight')

diff --git a/examples/svm/plot_separating_hyperplane_unbalanced.py b/examples/svm/plot_separating_hyperplane_unbalanced.py
@@ -60,7 +60,7 @@
 # plot separating hyperplanes and samples
 h0 = plt.plot(xx, yy, 'k-', label='no weights')
 h1 = plt.plot(xx, wyy, 'k--', label='with weights')
-plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Paired)
+plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Paired, edgecolors='k')
 plt.legend()
 
 plt.axis('tight')

diff --git a/examples/svm/plot_svm_kernels.py b/examples/svm/plot_svm_kernels.py
@@ -56,8 +56,9 @@
     plt.clf()
 
     plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1], s=80,
-                facecolors='none', zorder=10)
-    plt.scatter(X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.cm.Paired)
+                facecolors='none', zorder=10, edgecolors='k')
+    plt.scatter(X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.cm.Paired,
+                edgecolors='k')
 
     plt.axis('tight')
     x_min = -3

diff --git a/examples/svm/plot_svm_margin.py b/examples/svm/plot_svm_margin.py
@@ -62,8 +62,9 @@
     plt.plot(xx, yy_up, 'k--')
 
     plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1], s=80,
-                facecolors='none', zorder=10)
-    plt.scatter(X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.cm.Paired)
+                facecolors='none', zorder=10, edgecolors='k')
+    plt.scatter(X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.cm.Paired,
+                edgecolors='k')
 
     plt.axis('tight')
     x_min = -4.8

diff --git a/examples/svm/plot_svm_nonlinear.py b/examples/svm/plot_svm_nonlinear.py
@@ -34,7 +34,8 @@
            origin='lower', cmap=plt.cm.PuOr_r)
 contours = plt.contour(xx, yy, Z, levels=[0], linewidths=2,
                        linetypes='--')
-plt.scatter(X[:, 0], X[:, 1], s=30, c=Y, cmap=plt.cm.Paired)
+plt.scatter(X[:, 0], X[:, 1], s=30, c=Y, cmap=plt.cm.Paired,
+            edgecolors='k')
 plt.xticks(())
 plt.yticks(())
 plt.axis([-3, 3, -3, 3])