NF: 1st-level HRF-modeling for eventrelated_dataset() (fixes gh-188)

Quite simplistic, based in NiPy. So far without contrasts, but should be
easy to add.
Enable NiPy for travis
ENH: Custom regressors for HRF modeling (from dataset or external sources)
DOC: update and extend eventrelated_dataset() documentation.
BF: Guard against missing externals
DOC: minor typos/wording for glm/hrf new functionality docs
RF: Move NiPy's GLM into its on mapper (draft)

docs pending.
ENH: More flexible GLM.

Eat regressors form datasets, the mapper itself, auto-add constants.
BF: Do not modified input values.
RF: GLMMapper

To abstract away from NiPyGLMMapper.
NF+RF: GLM Mapper with statsmodels + plus convergence test.
BF: Missed argument rename
BF: SplitClassifier -- do not pre-populate the list of clfs. Closes #156

Then ChainNode, which might not adhere to Partitioner interface (ie
without get_partition_specs) could be used as well, and classifiers get
cloned/populated as new splits arrive
ENH: move lightbox __main__ sample code into a smoke test + allow it swallow 1st volume of 4d

lightbox had no unittests per se (used in examples though), thus official coverage was absent
NF: Support for convenience constraint specs.

Not comprehensive -- more like a place holder.
Merge pull request #199 from hanke/simple_constraints

NF: Support for convenience constraint specs.
ENH: RSA implementation with tests.

This is the RSA essence of PR #121.
DissimilarityMatrixMeasure returns multi-samples, one feature

unless squareform.

TODO: make the return dataset more sexy, e.g. record pairs...
BF: DissimilarityConsistencyMeasure: one feature/multiple samples in return

Now the tests should pass.
DOC+RM: Make RSA docs more similar to the rest; kill DissimilarityMultiRegressMeasure

The removed class had no tests. Can be reintroduced later on.