Rebased and addressed some comments

Author: MarcCote

nibabel/streamlines/tractogram.py

@@ -245,10 +245,11 @@ def __init__(self, streamlines=None,
             of ndarrays of shape ($N_t$, $M_i$) where $N_t$ is the number of
             points for a particular streamline $t$ and $M_i$ is the number
             scalar values to store for that particular information $i$.
-        affine_to_rasmm : ndarray of shape (4, 4)
+        affine_to_rasmm : ndarray of shape (4, 4), optional
             Transformation matrix that brings the streamlines contained in
             this tractogram to *RAS+* and *mm* space where coordinate (0,0,0)
-            refers to the center of the voxel.
+            refers to the center of the voxel. By default, the streamlines
+            are assumed to be already in *RAS+* and *mm* space.
         """
         self.streamlines = streamlines
         self.data_per_streamline = data_per_streamline
@@ -608,12 +609,13 @@ def __getitem__(self, idx):
         raise NotImplementedError('`LazyTractogram` does not support indexing.')
 
     def __iter__(self):
-        i = 0
-        for i, tractogram_item in enumerate(self.data, start=1):
+        count = 0
+        for tractogram_item in self.data:
             yield tractogram_item
+            count += 1
 
         # Keep how many streamlines there are in this tractogram.
-        self._nb_streamlines = i
+        self._nb_streamlines = count
 
     def __len__(self):
         # Check if we know how many streamlines there are.
@@ -642,13 +644,13 @@ def copy(self):
     def apply_affine(self, affine):
         """ Applies an affine transformation to the streamlines.
 
-        The transformation will be applied just before returning the
-        streamlines.
+        The transformation given by the `affine` matrix is applied after any
+        other pending transformations to the streamline points.
 
         Parameters
         ----------
         affine : 2D array (4,4)
-            Transformation that will be applied on each streamline.
+            Transformation matrix that will be applied on each streamline.
 
         Returns
         -------

nibabel/streamlines/tractogram_file.py

@@ -5,19 +5,19 @@
 
 
 class ExtensionWarning(Warning):
-    pass
+    """ Base class for warnings about tractogram file extension. """
 
 
 class HeaderWarning(Warning):
-    pass
+    """ Base class for warnings about tractogram file header. """
 
 
 class HeaderError(Exception):
-    pass
+    """ Raised when a tractogram file header contains invalid information. """
 
 
 class DataError(Exception):
-    pass
+    """ Raised when data is missing or inconsistent in a tractogram file. """
 
 
 class abstractclassmethod(classmethod):
@@ -71,12 +71,12 @@ def get_magic_number(cls):
 
     @abstractclassmethod
     def support_data_per_point(cls):
-        """ Tells if this tractogram format supports saving data per point. """
+        """ Tells if this format supports saving data per point. """
         raise NotImplementedError()
 
     @abstractclassmethod
     def support_data_per_streamline(cls):
-        """ Tells if this tractogram format supports saving data per streamline. """
+        """ Tells if this format supports saving data per streamline. """
         raise NotImplementedError()
 
     @abstractclassmethod

nibabel/streamlines/trk.py

@@ -450,7 +450,7 @@ class TrkFile(TractogramFile):
     back on save.
     """
 
-    # Contants
+    # Constants
     MAGIC_NUMBER = b"TRACK"
     HEADER_SIZE = 1000
     READ_BUFFER_SIZE = 87382 * 4  # About 4 Mb when no scalars nor properties.
@@ -514,8 +514,6 @@ def is_correct_format(cls, fileobj):
             f.seek(-5, os.SEEK_CUR)
             return magic_number == cls.MAGIC_NUMBER
 
-        return False
-
     @classmethod
     def _create_arraysequence_from_generator(cls, gen):
         """ Creates a ArraySequence object from a generator yielding tuples of