Examples cleanup: remove pl.close, it is now handled by gen_rst.

examples/plot_covariance_estimation.py

@@ -40,7 +40,6 @@ negative_logliks = [-cov.fit(X_train, shrinkage=s).score(X_test) \
 
 ###############################################################################
 # Plot results
-pl.close('all')
 pl.loglog(shrinkages, negative_logliks)
 pl.xlabel('Shrinkage')
 pl.ylabel('Negative log-likelihood')

examples/plot_ica_vs_pca.py

@@ -77,7 +77,6 @@ def plot_samples(S, axis_list=None):
     pl.xlabel('$x$')
     pl.ylabel('$y$')
 
-pl.close('all')
 pl.subplot(2, 2, 1)
 plot_samples(S / S.std())
 pl.title('True Independant Sources')

examples/plot_permutation_test_for_classification.py

@@ -17,6 +17,7 @@ obtained in the first place.
 print __doc__
 
 import numpy as np
+import pylab as pl
 
 from scikits.learn.svm import SVC
 from scikits.learn.cross_val import StratifiedKFold, permutation_test_score
@@ -49,8 +50,6 @@ print "Classification score %s (pvalue : %s)" % (score, pvalue)
 
 ###############################################################################
 # View histogram of permutation scores
-import pylab as pl
-pl.close('all')
 pl.hist(permutation_scores, label='Permutation scores')
 ylim = pl.ylim()
 pl.vlines(score, ylim[0], ylim[1], linestyle='--',