Added apply_roi and unapply_roi

Started implementation of ROI functions.
Added normalize_regions option to apply_roi()

This option has been added to get roi-timeseries with proper
normalisation. This is different from normalizing for variance.
See docstring for details.
Added conversion function for ROI data structures

Handling of ROI can be made using different kinds of data structures,
namely a 4D array, a list of 3D arrays, and a 3D array of labels.
Conversion functions between these formats have been written (six
functions).
Merge remote branch 'nisl/master' into roi
Merge branch 'master' into roi

Conflicts:
	nisl/tests/__init__.py
Added overlap parameter to signal generator

Coding-style fixes in test_roi.py
Added masking functions for regions.

These functions are very similar to mask/unmask functions, they
just handle labeled regions properly.
Downloaders for Yeo and Craddock parcellations

Two downloaders have been added.
Merge branch 'master' into roi
Merge branch 'master' into roi
Fixed some Sphinx compilation errors
Renamed roi.py in region.py

Renamed apply_mask_regions() to apply_mask_to_regions() and similarly
for unapply_mask_regions().
Renamed tests/test_roi.py to tests/tests_region.py
Fixed tests of region.py functions.
Added regions_to_mask() and NislImage class

Tests for regions_to_mask() have been written too.
Option background_label to regions_labels_to_list()

This option is used to give the label that should be considered as
background during the conversion (nothing is output for this label)
Added plot_regions_covariance.py (example file)

This script demonstrates usage of the regions API.
Style fixes in plot_regions_covariance.py
Detrending in high_variance_confounds()

Added "detrend" parameter in high_variance_confounds(), to detrend
data before computing confounds.
Created nisl.datasets.load_harvard_oxford()

This function loads Harvard-Oxford atlas, provided it is already
on the disk. It can also split every region in two symmetric parts.

plot_regions_covariance.py has been heavily adapted.