Merge branch 'simplify-fselection'

Fixes #3131.
MAINT make export_graphviz more exception-safe
Improved formatting of unsupported sparse matrices in swapping
Merge pull request #3140 from MechCoder/small_fixes

TST Improved handling of unsupported sparse matrices in swapping
Revert "COSMIT skip some repeated computations in k-means"

This reverts commit e3583daa2f196b5822f784c7e53f081668ecef6d,
except for a typo fix.

Fixes #3039.
DOC grid_search_digits.py does no do nested CV

Fixes #3136.
MAINT: ignore coveralls failures
Merge pull request #3145 from ogrisel/travis-coveralls

[MRG] MAINT: ignore coveralls failures
TST MiniBatchKMeans with many reassignments

Regression test for #3039.
DOC L1 distance works for sparse matrices

This was implemented in 3bc3d9f5ea773f6a2e9c207e9243102651785aac.
Updated examples to use pyplot for plotting instead of pylab

Some examples not updated because scripts throw error (probably not
because of the change)
Fixed pep8 violations. Some 'line too long' errors still remain.
Fixed some PEP8 violations even present in master branch, in examples/

This fixes some of the violations that were not caused by the change to pyplot
from pylab.
MAINT remove default values from private funcs in GMM

Removed default values for 'mean' and 'covars' arguments.
They did not have the excepted format causing the functions
to fail when called with default arguments.
ENH faster sampling in GMMs

A few optimizations for sampling with full covariance matrix:
1) use eigh instead of svd, which are equivalent (up to numerical precision),
2) use broadcasting instead of matrix multiplication for the product U s^(1/2),
3) simpler construction of the random vectors.
Merge branch 'pr/3120'

Fixes #3120, "Bad default arguments in gmm.py".
FIX numerical stability in GMM with eigh sampling
Merge pull request #3151 from rajatkhanduja/fixing_examples

Updated examples to use pyplot for plotting instead of pylab
adding conditional import to lfw.py for python3 support
Some more examples updated to use matplotlib.pyplot