BF: #596 First point of LazyTractogram is not saved

nibabel/streamlines/tck.py

@@ -19,6 +19,7 @@
 from .tractogram_file import HeaderError, DataError
 from .tractogram import TractogramItem, Tractogram, LazyTractogram
 from .header import Field
+from .utils import peek_next
 
 MEGABYTE = 1024 * 1024
 
@@ -191,8 +192,16 @@ def save(self, fileobj):
             # Write temporary header that we will update at the end
             self._write_header(f, header)
 
+            # Make sure streamlines are in rasmm.
+            tractogram = self.tractogram.to_world(lazy=True)
+            # Assume looping over the streamlines can be done only once.
+            tractogram = iter(tractogram)
+
             try:
-                first_item = next(iter(self.tractogram))
+                # Use the first element to check
+                #  1) the tractogram is not empty;
+                #  2) quantity of information saved along each streamline.
+                first_item, tractogram = peek_next(tractogram)
             except StopIteration:
                 # Empty tractogram
                 header[Field.NB_STREAMLINES] = 0
@@ -216,9 +225,6 @@ def save(self, fileobj):
                        " alongside points. Dropping: {}".format(keys))
                 warnings.warn(msg, DataWarning)
 
-            # Make sure streamlines are in rasmm.
-            tractogram = self.tractogram.to_world(lazy=True)
-
             for t in tractogram:
                 data = np.r_[t.streamline, self.FIBER_DELIMITER]
                 f.write(data.astype(dtype).tostring())

nibabel/streamlines/tests/test_array_sequence.py

@@ -152,6 +152,11 @@ def test_arraysequence_append(self):
         seq.append(element)
         check_arr_seq(seq, [element])
 
+        # Append an empty array.
+        seq = SEQ_DATA['seq'].copy()  # Copy because of in-place modification.
+        seq.append([])
+        check_arr_seq(seq, SEQ_DATA['seq'])
+
         # Append an element with different shape.
         element = generate_data(nb_arrays=1,
                                 common_shape=SEQ_DATA['seq'].common_shape*2,

nibabel/streamlines/tests/test_streamlines.py

@@ -272,3 +272,19 @@ def test_load_unknown_format(self):
 
     def test_save_unknown_format(self):
         assert_raises(ValueError, nib.streamlines.save, Tractogram(), "")
+
+    def test_save_from_generator(self):
+        tractogram = Tractogram(DATA['streamlines'],
+                                affine_to_rasmm=np.eye(4))
+
+        # Just to create a generator
+        for ext, _ in FORMATS.items():
+            filtered = (s for s in tractogram.streamlines if True)
+            lazy_tractogram = LazyTractogram(lambda: filtered,
+                                             affine_to_rasmm=np.eye(4))
+
+            with InTemporaryDirectory():
+                filename = 'streamlines' + ext
+                nib.streamlines.save(lazy_tractogram, filename)
+                tfile = nib.streamlines.load(filename, lazy_load=False)
+                assert_tractogram_equal(tfile.tractogram, tractogram)

nibabel/streamlines/tests/test_tractogram.py

@@ -13,6 +13,7 @@
 from six.moves import zip
 
 from .. import tractogram as module_tractogram
+from ..tractogram import is_data_dict, is_lazy_dict
 from ..tractogram import TractogramItem, Tractogram, LazyTractogram
 from ..tractogram import PerArrayDict, PerArraySequenceDict, LazyDict
 
@@ -406,14 +407,21 @@ def test_extend(self):
 class TestLazyDict(unittest.TestCase):
 
     def test_lazydict_creation(self):
-        data_dict = LazyDict(DATA['data_per_streamline_func'])
-        assert_equal(data_dict.keys(), DATA['data_per_streamline_func'].keys())
-        for k in data_dict.keys():
-            assert_array_equal(list(data_dict[k]),
-                               list(DATA['data_per_streamline'][k]))
+        # Different ways of creating LazyDict
+        lazy_dicts = []
+        lazy_dicts += [LazyDict(DATA['data_per_streamline_func'])]
+        lazy_dicts += [LazyDict(**DATA['data_per_streamline_func'])]
 
-        assert_equal(len(data_dict),
-                     len(DATA['data_per_streamline_func']))
+        expected_keys = DATA['data_per_streamline_func'].keys()
+        for data_dict in lazy_dicts:
+            assert_true(is_lazy_dict(data_dict))
+            assert_equal(data_dict.keys(), expected_keys)
+            for k in data_dict.keys():
+                assert_array_equal(list(data_dict[k]),
+                                   list(DATA['data_per_streamline'][k]))
+
+            assert_equal(len(data_dict),
+                         len(DATA['data_per_streamline_func']))
 
 
 class TestTractogramItem(unittest.TestCase):
@@ -470,6 +478,9 @@ def test_tractogram_creation(self):
                          DATA['data_per_streamline'],
                          DATA['data_per_point'])
 
+        assert_true(is_data_dict(tractogram.data_per_streamline))
+        assert_true(is_data_dict(tractogram.data_per_point))
+
         # Create a tractogram from another tractogram attributes.
         tractogram2 = Tractogram(tractogram.streamlines,
                                  tractogram.data_per_streamline,
@@ -795,6 +806,9 @@ def test_lazy_tractogram_creation(self):
                                     DATA['data_per_streamline_func'],
                                     DATA['data_per_point_func'])
 
+        assert_true(is_lazy_dict(tractogram.data_per_streamline))
+        assert_true(is_lazy_dict(tractogram.data_per_point))
+
         [t for t in tractogram]  # Force iteration through tractogram.
         assert_equal(len(tractogram), len(DATA['streamlines']))
 
@@ -910,6 +924,22 @@ def test_lazy_tractogram_apply_affine(self):
         tractogram.affine_to_rasmm = None
         assert_raises(ValueError, tractogram.to_world)
 
+        # But calling apply_affine when affine_to_rasmm is None should work.
+        tractogram = DATA['lazy_tractogram'].copy()
+        tractogram.affine_to_rasmm = None
+        transformed_tractogram = tractogram.apply_affine(affine)
+        assert_array_equal(transformed_tractogram._affine_to_apply, affine)
+        assert_true(transformed_tractogram.affine_to_rasmm is None)
+        check_tractogram(transformed_tractogram,
+                         streamlines=[s*scaling for s in DATA['streamlines']],
+                         data_per_streamline=DATA['data_per_streamline'],
+                         data_per_point=DATA['data_per_point'])
+
+        # Calling apply_affine with lazy=False should fail for LazyTractogram.
+        tractogram = DATA['lazy_tractogram'].copy()
+        assert_raises(ValueError, tractogram.apply_affine,
+                      affine=np.eye(4), lazy=False)
+
     def test_tractogram_to_world(self):
         tractogram = DATA['lazy_tractogram'].copy()
         affine = np.random.RandomState(1234).randn(4, 4)

nibabel/streamlines/tractogram.py

@@ -16,7 +16,7 @@ def is_data_dict(obj):
 
 def is_lazy_dict(obj):
     """ True if `obj` seems to implement the :class:`LazyDict` API """
-    return is_data_dict(obj) and callable(obj.store.values()[0])
+    return is_data_dict(obj) and callable(list(obj.store.values())[0])
 
 
 class SliceableDataDict(collections.MutableMapping):
@@ -77,7 +77,7 @@ class PerArrayDict(SliceableDataDict):
 
     This container behaves like a standard dictionary but extends key access to
     allow keys for key access to be indices slicing into the contained ndarray
-    values.  The elements must also be ndarrays.
+    values. The elements must also be ndarrays.
 
     In addition, it makes sure the amount of data contained in those ndarrays
     matches the number of streamlines given at the instantiation of this
@@ -200,9 +200,6 @@ def __init__(self, *args, **kwargs):
                 self.update(**args[0].store)  # Copy the generator functions.
                 return
 
-            if isinstance(args[0], SliceableDataDict):
-                self.update(**args[0])
-
         self.update(dict(*args, **kwargs))
 
     def __getitem__(self, key):

nibabel/streamlines/trk.py

@@ -5,8 +5,8 @@
 
 import os
 import struct
-import warnings
 import string
+import warnings
 
 import numpy as np
 import nibabel as nib
@@ -21,6 +21,7 @@
 from .tractogram_file import DataError, HeaderError, HeaderWarning
 from .tractogram import TractogramItem, Tractogram, LazyTractogram
 from .header import Field
+from .utils import peek_next
 
 
 MAX_NB_NAMED_SCALARS_PER_POINT = 10
@@ -423,8 +424,23 @@ def save(self, fileobj):
             i4_dtype = np.dtype("<i4")  # Always save in little-endian.
             f4_dtype = np.dtype("<f4")  # Always save in little-endian.
 
+            # Since the TRK format requires the streamlines to be saved in
+            # voxmm, we first transform them accordingly. The transformation
+            # is performed lazily since `self.tractogram` might be a
+            # LazyTractogram object, which means we might be able to loop
+            # over the streamlines only once.
+            tractogram = self.tractogram.to_world(lazy=True)
+            affine_to_trackvis = get_affine_rasmm_to_trackvis(header)
+            tractogram = tractogram.apply_affine(affine_to_trackvis, lazy=True)
+
+            # Create the iterator we'll be using for the rest of the funciton.
+            tractogram = iter(tractogram)
+
             try:
-                first_item = next(iter(self.tractogram))
+                # Use the first element to check
+                #  1) the tractogram is not empty;
+                #  2) quantity of information saved along each streamline.
+                first_item, tractogram = peek_next(tractogram)
             except StopIteration:
                 # Empty tractogram
                 header[Field.NB_STREAMLINES] = 0
@@ -470,11 +486,6 @@ def save(self, fileobj):
                 scalar_name[i] = encode_value_in_name(nb_values, name)
             header['scalar_name'][:] = scalar_name
 
-            # Make sure streamlines are in rasmm then send them to voxmm.
-            tractogram = self.tractogram.to_world(lazy=True)
-            affine_to_trackvis = get_affine_rasmm_to_trackvis(header)
-            tractogram = tractogram.apply_affine(affine_to_trackvis, lazy=True)
-
             for t in tractogram:
                 if any((len(d) != len(t.streamline)
                         for d in t.data_for_points.values())):

nibabel/streamlines/utils.py

@@ -1,3 +1,5 @@
+import itertools
+
 import nibabel
 
 
@@ -29,3 +31,22 @@ def get_affine_from_reference(ref):
 
     # Assume `ref` is the name of a neuroimaging file.
     return nibabel.load(ref).affine
+
+
+def peek_next(iterable):
+    """ Peek next element of iterable.
+
+    Parameters
+    ----------
+    iterable
+        Iterable to peek the next element from.
+
+    Returns
+    -------
+    next_item
+        Element peeked from `iterable`.
+    new_iterable
+        Iterable behaving like if the original `iterable` was untouched.
+    """
+    next_item = next(iterable)
+    return next_item, itertools.chain([next_item], iterable)