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
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.
RF: Kill all broken, half-baked and duplicate RSA implementations.

Also killed the searchlight_dsm example -- long broken and not very
meaningful anyway. Needs replacement.
BF: Guard for missing scipy
ENH: Add sample attributes to DSM results
OPT: Avoid repated vstack'ing and associated copying.