Merge branch 'master' of github.com:PyMVPA/PyMVPA

* 'master' of github.com:PyMVPA/PyMVPA:
  BF: Fix doc reference.
  RF; Adjust hyperalignment example for new tutorial data setup
  BF: File location

doc/examples/hyperalignment.py

@@ -46,8 +46,7 @@
 """
 
 verbose(1, "Loading data...")
-filepath = os.path.join(pymvpa_datadbroot,
-                        'hyperalignment_tutorial_data',
+filepath = os.path.join(cfg.get('location', 'tutorial data'),
                         'hyperalignment_tutorial_data.hdf5.gz')
 ds_all = h5load(filepath)
 # zscore all datasets individually

doc/examples/rsa_fmri.py

@@ -41,7 +41,7 @@
 
 # load dataset -- ventral and occipital ROIs
 from mvpa2.datasets.sources.native import load_tutorial_data
-datapath = pjoin(cfg.get('location', 'tutorial data'))
+datapath = pjoin(cfg.get('location', 'tutorial data'), 'haxby2001')
 ds = load_tutorial_data(roi=(15, 16, 23, 24, 36, 38, 39, 40, 48))
 
 """

mvpa2/misc/stats.py

@@ -229,7 +229,7 @@ def binomial_proportion_ci(n, X, alpha=.05, meth='jeffreys'):
     Anderson Winkler and Tom Nichols.
 
     Parameters
-    ==========
+    ----------
     n : int
       Number of trials
     X : int or array
@@ -241,17 +241,16 @@ def binomial_proportion_ci(n, X, alpha=.05, meth='jeffreys'):
       Interval estimation method.
 
     Returns
-    =======
+    -------
     2-item array or 2D array
       With the lower and upper bound for the confidence interval. If X was given
       as a vector with p items a 2xp array is returned.
 
-    See also
-    ========
-    Brown LD, Cai TT, DasGupta AA. Interval estimation for a
-    binomial proportion. Statistical Science. 2001 16(2):101-133.
-
-    http://brainder.org/2012/04/21/confidence-intervals-for-bernoulli-trials/
+    References
+    ----------
+    .. [1] Brown LD, Cai TT, DasGupta AA. Interval estimation for a
+       binomial proportion. Statistical Science. 2001 16(2):101-133.
+       http://brainder.org/2012/04/21/confidence-intervals-for-bernoulli-trials
     """
 
     from scipy import stats