Support numpy 1.5 and make code PEP8 compliant.

Author: MarcCote

nibabel/streamlines/array_sequence.py

@@ -22,7 +22,7 @@ class ArraySequence(object):
     same for every ndarray.
     """
 
-    BUFFER_SIZE = 87382*4  # About 4 Mb if item shape is 3 (e.g. 3D points).
+    BUFFER_SIZE = 87382 * 4  # About 4 Mb if item shape is 3 (e.g. 3D points).
 
     def __init__(self, iterable=None):
         """
@@ -72,7 +72,7 @@ def __init__(self, iterable=None):
 
             offsets.append(offset)
             lengths.append(len(e))
-            self._data[offset:offset+len(e)] = e
+            self._data[offset:offset + len(e)] = e
             offset += len(e)
 
         self._offsets = np.asarray(offsets)
@@ -148,14 +148,14 @@ def extend(self, elements):
         next_offset = self._data.shape[0]
 
         if is_array_sequence(elements):
-            self._data.resize((self._data.shape[0]+sum(elements._lengths),
+            self._data.resize((self._data.shape[0] + sum(elements._lengths),
                                self._data.shape[1]))
 
             offsets = []
             for offset, length in zip(elements._offsets, elements._lengths):
                 offsets.append(next_offset)
-                chunk = elements._data[offset:offset+length]
-                self._data[next_offset:next_offset+length] = chunk
+                chunk = elements._data[offset:offset + length]
+                self._data[next_offset:next_offset + length] = chunk
                 next_offset += length
 
             self._lengths = np.r_[self._lengths, elements._lengths]
@@ -182,8 +182,8 @@ def copy(self):
         offsets = []
         for offset, length in zip(self._offsets, self._lengths):
             offsets.append(next_offset)
-            chunk = self._data[offset:offset+length]
-            seq._data[next_offset:next_offset+length] = chunk
+            chunk = self._data[offset:offset + length]
+            seq._data[next_offset:next_offset + length] = chunk
             next_offset += length
 
         seq._offsets = np.asarray(offsets)
@@ -212,7 +212,7 @@ def __getitem__(self, idx):
         """
         if isinstance(idx, (int, np.integer)):
             start = self._offsets[idx]
-            return self._data[start:start+self._lengths[idx]]
+            return self._data[start:start + self._lengths[idx]]
 
         elif isinstance(idx, (slice, list)):
             seq = ArraySequence()
@@ -241,7 +241,7 @@ def __iter__(self):
                              " len(self._lengths) != len(self._offsets)")
 
         for offset, lengths in zip(self._offsets, self._lengths):
-            yield self._data[offset: offset+lengths]
+            yield self._data[offset: offset + lengths]
 
     def __len__(self):
         return len(self._offsets)

nibabel/streamlines/tests/test_array_sequence.py

@@ -18,12 +18,12 @@ def setup():
     global SEQ_DATA
     rng = np.random.RandomState(42)
     SEQ_DATA['rng'] = rng
-    SEQ_DATA['data'] = generate_data(nb_arrays=10, common_shape=(3,), rng=rng)
+    SEQ_DATA['data'] = generate_data(nb_arrays=5, common_shape=(3,), rng=rng)
     SEQ_DATA['seq'] = ArraySequence(SEQ_DATA['data'])
 
 
 def generate_data(nb_arrays, common_shape, rng):
-    data = [rng.rand(*(rng.randint(10, 50),) + common_shape)
+    data = [rng.rand(*(rng.randint(3, 20),) + common_shape)
             for _ in range(nb_arrays)]
     return data
 
@@ -79,7 +79,7 @@ def test_creating_arraysequence_from_list(self):
         for ndim in range(0, N+1):
             common_shape = tuple([SEQ_DATA['rng'].randint(1, 10)
                                  for _ in range(ndim-1)])
-            data = generate_data(nb_arrays=10, common_shape=common_shape,
+            data = generate_data(nb_arrays=5, common_shape=common_shape,
                                  rng=SEQ_DATA['rng'])
             check_arr_seq(ArraySequence(data), data)
 
@@ -213,7 +213,7 @@ def test_arraysequence_getitem(self):
         SEQ_DATA['rng'].shuffle(indices)
         seq_view = SEQ_DATA['seq'][indices]
         check_arr_seq_view(seq_view, SEQ_DATA['seq'])
-        check_arr_seq(seq_view, np.asarray(SEQ_DATA['data'])[indices])
+        check_arr_seq(seq_view, [SEQ_DATA['data'][i] for i in indices])
 
         # Get slice (this will create a view).
         seq_view = SEQ_DATA['seq'][::2]
@@ -224,7 +224,9 @@ def test_arraysequence_getitem(self):
         selection = np.array([False, True, True, False, True])
         seq_view = SEQ_DATA['seq'][selection]
         check_arr_seq_view(seq_view, SEQ_DATA['seq'])
-        check_arr_seq(seq_view, np.asarray(SEQ_DATA['data'])[selection])
+        check_arr_seq(seq_view,
+                      [SEQ_DATA['data'][i]
+                       for i, keep in enumerate(selection) if keep])
 
         # Test invalid indexing
         assert_raises(TypeError, SEQ_DATA['seq'].__getitem__, 'abc')

nibabel/streamlines/tractogram.py

@@ -295,9 +295,10 @@ def apply_affine(self, affine, lazy=False):
             return self
 
         BUFFER_SIZE = 10000000  # About 128 Mb since pts shape is 3.
-        for i in range(0, len(self.streamlines._data), BUFFER_SIZE):
-            pts = self.streamlines._data[i:i+BUFFER_SIZE]
-            self.streamlines._data[i:i+BUFFER_SIZE] = apply_affine(affine, pts)
+        for start in range(0, len(self.streamlines._data), BUFFER_SIZE):
+            end = start + BUFFER_SIZE
+            pts = self.streamlines._data[start:end]
+            self.streamlines._data[start:end] = apply_affine(affine, pts)
 
         # Update the affine that brings back the streamlines to RASmm.
         self._affine_to_rasmm = np.dot(self._affine_to_rasmm,