BUG: example plot compatibility with older matplotlib versions

aaa952 · Dec 20, 2011 · 0c38141 · 0c38141
1 parent a2bb3ff
commit 0c38141
Show file tree

Hide file tree

Showing 2 changed files with 19 additions and 8 deletions.
diff --git a/examples/covariance/plot_covariance_estimation.py b/examples/covariance/plot_covariance_estimation.py
@@ -68,15 +68,20 @@
 
 ###############################################################################
 # Plot results
-pl.figure(-1)
+pl.figure()
 pl.title("Regularized covariance: likelihood and shrinkage coefficient")
 pl.xlabel('Shrinkage')
 pl.ylabel('Negative log-likelihood')
 # range shrinkage curve
 pl.loglog(shrinkages, negative_logliks)
+
 # real likelihood reference
-pl.hlines(loglik_real, pl.xlim()[0], pl.xlim()[1], color='red',
-          label="real covariance likelihood", linestyle='--')
+# BUG: hlines(..., linestyle='--') breaks on some older versions of matplotlib
+#pl.hlines(loglik_real, pl.xlim()[0], pl.xlim()[1], color='red',
+#          label="real covariance likelihood", linestyle='--')
+pl.plot(pl.xlim(), 2*[loglik_real], '--r',
+        label="real covariance likelihood")
+
 # adjust view
 lik_max = np.amax(negative_logliks)
 lik_min = np.amin(negative_logliks)

diff --git a/examples/plot_permutation_test_for_classification.py b/examples/plot_permutation_test_for_classification.py
@@ -52,11 +52,17 @@
 # View histogram of permutation scores
 pl.hist(permutation_scores, 20, label='Permutation scores')
 ylim = pl.ylim()
-pl.vlines(score, ylim[0], ylim[1], linestyle='--',
-          color='g', linewidth=3, label='Classification Score'
-          ' (pvalue %s)' % pvalue)
-pl.vlines(1.0 / n_classes, ylim[0], ylim[1], linestyle='--',
-          color='k', linewidth=3, label='Luck')
+# BUG: vlines(..., linestyle='--') fails on older versions of matplotlib
+#pl.vlines(score, ylim[0], ylim[1], linestyle='--',
+#          color='g', linewidth=3, label='Classification Score'
+#          ' (pvalue %s)' % pvalue)
+#pl.vlines(1.0 / n_classes, ylim[0], ylim[1], linestyle='--',
+#          color='k', linewidth=3, label='Luck')
+pl.plot(2 * [score], ylim, '--g', linewidth=3,
+        label='Classification Score'
+        ' (pvalue %s)' % pvalue)
+pl.plot(2 * [1. / n_classes], ylim, '--k', linewidth=3, label='Luck')
+
 pl.ylim(ylim)
 pl.legend()
 pl.xlabel('Score')