DOC: update documentation

unit_tests/fdt/dtifit/feedsRun

 #!/usr/bin/env fslpython
 """
-Generates data following the diffusion tensor model
+Generates data following the diffusion tensor and/or kurtosis model and then fit with dtifit
+
+No noise is added, so we expect (near-)perfect fits
 """
 import sys
 import os
@@ -14,9 +16,13 @@ OUTDIR = sys.argv[0]
 
 def gen_data():
     """
-    Populates given directory with diffusion data
+    Populates given directory with diffusion data following DTI or DKI models
+
+    :yield: tuple with
 
-    :yield: directories containing reference noiseless data with the eigen-vectors and eigen-values used to generate the data
+        - directory containing reference noiseless data with the eigen-vectors and eigen-values used to generate the data
+        - Boolean flag indicating whether data is multi-shell
+        - integer encoding diffusion model used (0: DTI, 1: single kurtosis value, 2: directional kurtosis)
     """
     directory = [''] * 10
     directory[0] = 'dti'
@@ -124,6 +130,21 @@ def gen_data():
 
 
 def fit_data(directory):
+    """
+    Runs dtifit on the diffusion data multiple times with different flags
+
+    Tests with and without the following flags:
+
+    - --wls
+    - --kurt
+    - --kurtdir
+
+    :yield: tuple with
+
+        - base name of the output files
+        - boolean indicating whether the --kurt flag was set
+        - boolean indicating whether the --kudtdir flag was set
+    """
     for kurtdir in (False, True):
         for main_kurt in (False, True):
             for wls in (False, True):  # in this noise-free data the --wls flag should not matter
@@ -154,6 +175,7 @@ def fit_data(directory):
                 yield base_output, main_kurt, kurtdir
 
 
+# Loops through multiple ways to generate and fit the data and check the output
 for directory, multi_shell, kurt in gen_data():
     for base_output, fkurt, fkurtdir in fit_data(directory):
         print('testing', base_output)