fix

Author: mrahim

README.rst

@@ -58,10 +58,10 @@ First, install neurodebian-travis::
 
 Second, install the python packages pip, scipy, nose, nibabel, sklearn, nipype, pandas, matplotlib, nilearn and configobj.  If you have a python virtual environment, just run::
 
-     $ pip install scipy nose nibabel scikit-learn nipype pandas matplotlib nilearn configobj 
+     $ pip install scipy nose nibabel scikit-learn nipype pandas matplotlib nilearn configobj
 
 If not, make sure to install pip (run: 'sudo apt-get install python-pip'). If you want to install these locally, use the --user option::
-        
+
      $ pip install scipy nose nibabel scikit-learn nipype pandas matplotlib nilearn configobj --user
 
 If you want to install these for all users, use sudo::
@@ -74,21 +74,21 @@ Finally, install pypreprocess itself by running the following in the pypreproces
 
 or simply 'python setup.py install' in a virtual environment.
 
-       
+
 
 After Installation: Few steps to configure SPM on your own device
 =================================================================
 There are three cases:
 
-* If you have used the pypreprocess/continuous_integration/setup_spm.sh or install_spm script, you have nothing to do. 
+* If you have used the pypreprocess/continuous_integration/setup_spm.sh or install_spm script, you have nothing to do.
 
 * If you have matlab and spm installed, then specify the location of your
-  SPM installation directory and export this location as SPM_DIR:: 
+  SPM installation directory and export this location as SPM_DIR::
 
        $ export SPM_DIR=/path/to/spm/installation/dir
 
 * If you have installed a pre-compiled version of SPM then, specify the
-  location of the SPM executable and export as SPM_MCR:: 
+  location of the SPM executable and export as SPM_MCR::
 
        $ export SPM_MCR=/path/to/spm_mcr_script (script implies spm8.sh)
 
@@ -97,9 +97,9 @@ Getting started: pypreprocess 101
 =================================
 Simply ``cd`` to the ``examples/easy_start/`` sub-directory and run the following command::
 
-       $ python nipype_preproc_spm_auditory.py 
+       $ python nipype_preproc_spm_auditory.py
 
-If you find nipype errors like "could not configure SPM", this is most likely that the export of SPM_DIR and SPM_MCR (see above) have not been done in this shell. 
+If you find nipype errors like "could not configure SPM", this is most likely that the export of SPM_DIR and SPM_MCR (see above) have not been done in this shell.
 
 Layout of examples
 ==================
@@ -134,7 +134,7 @@ Using .ini configuration files to specify pipeline
 It is possible (and recommended) to configure the preprocessing pipeline just by copying any of the `.ini` configuration files under the `examples` sub-directory and modifying it (usually, you only need to modify the `dataset_dir` parameter), and then run::
 
       $ python pypreprocess.py your.ini
-      
+
 For example,::
 
       $ python pypreprocess.py examples/easy_start/spm_auditory_preproc.ini
@@ -181,7 +181,7 @@ You can check the latest version of the code with the command::
 or if you have write privileges::
 
        $ git clone [email protected]:neurospin/pypreprocess.git
-       
+
 Common problems and fixes
 =========================
 * libXp.so.6 missing (in ubuntu >= 15.10, for example)
@@ -191,4 +191,4 @@ This is a known is http://askubuntu.com/questions/719839/libxp-so-6-missing-15-1
 
 * when using an 'ini' file, say 'mytest.ini', with ''python preprocessing.py mytest.ini'', there can be a conflict between  pypreprocess.py and the pypreprocess module (solution: rename pypreprocess.py into something like pypreprocini.py)
 
-* the cache is not relocatable (because joblib encode the absolute paths): if you are forced to move the cache -- e.g. because of lack of space on a filesystem -- use a symbolic link to let the system believe that the cache is still at the original location.  
+* the cache is not relocatable (because joblib encode the absolute paths): if you are forced to move the cache -- e.g. because of lack of space on a filesystem -- use a symbolic link to let the system believe that the cache is still at the original location.