Merge remote-tracking branch 'upstream/master' into add_fsaverage

.travis.yml

@@ -29,7 +29,7 @@ matrix:
            SCIKIT_LEARN_VERSION="0.15"
     # Fake Ubuntu Xenial (Travis doesn't support Xenial yet)
     - env: DISTRIB="conda" PYTHON_VERSION="2.7"
-           NUMPY_VERSION="1.11" SCIPY_VERSION="0.17"
+           NUMPY_VERSION="1.11.2" SCIPY_VERSION="0.17"
            SCIKIT_LEARN_VERSION="0.17"
            NIBABEL_VERSION="2.0.2"
     # Python 3.4 with intermediary versions

nilearn/_utils/exceptions.py

@@ -1,3 +1,10 @@
+try:
+    from numpy import VisibleDeprecationWarning
+except ImportError:
+    class VisibleDeprecationWarning(UserWarning):
+        pass
+
+
 AuthorizedException = (
         BufferError,
         ArithmeticError,

nilearn/datasets/func.py

@@ -17,6 +17,7 @@
 from .._utils import check_niimg
 from .._utils.compat import BytesIO, _basestring, _urllib
 from .._utils.numpy_conversions import csv_to_array
+from .._utils.exceptions import VisibleDeprecationWarning
 
 
 @deprecated("fetch_haxby_simple will be removed in future releases. "
@@ -151,7 +152,7 @@ def fetch_haxby(data_dir=None, n_subjects=None, subjects=(2,),
         warn_str = ("The parameter 'n_subjects' is deprecated from 0.2.6 and "
                     "will be removed in nilearn next release. Use parameter "
                     "'subjects' instead.")
-        warnings.warn(warn_str, np.VisibleDeprecationWarning, stacklevel=2)
+        warnings.warn(warn_str, VisibleDeprecationWarning, stacklevel=2)
         subjects = n_subjects
 
     if isinstance(subjects, numbers.Number) and subjects > 6:

nilearn/plotting/find_cuts.py

@@ -17,7 +17,7 @@
 from .._utils.numpy_conversions import as_ndarray
 from .._utils import check_niimg_3d
 from .._utils.niimg import _safe_get_data
-from ..image.resampling import get_mask_bounds, coord_transform
+from ..image.resampling import get_mask_bounds, coord_transform, reorder_img
 from ..image.image import _smooth_array
 
 ################################################################################
@@ -216,6 +216,12 @@ def find_cut_slices(img, direction='z', n_cuts=7, spacing='auto'):
     separated by a distance of at least 'spacing'. If n_cuts is very
     large and all the activated regions are covered, cuts with a spacing
     less than 'spacing' will be returned.
+
+    Warning
+    -------
+    If a non-diagonal img is given. This function automatically reorders
+    img to get it back to diagonal. This is to avoid finding same cuts in
+    the slices.
     """
 
     # misc
@@ -226,6 +232,14 @@ def find_cut_slices(img, direction='z', n_cuts=7, spacing='auto'):
     axis = 'xyz'.index(direction)
     img = check_niimg_3d(img)
     affine = img.affine
+    if not np.alltrue(np.diag(affine)[:3]):
+        warnings.warn('A non-diagonal affine is found in the given '
+                      'image. Reordering the image to get diagonal affine '
+                      'for finding cuts in the slices.', stacklevel=2)
+        # resample is set to avoid issues with an image having a non-diagonal
+        # affine and rotation.
+        img = reorder_img(img, resample='nearest')
+        affine = img.affine
     orig_data = np.abs(_safe_get_data(img))
     this_shape = orig_data.shape[axis]
 

nilearn/plotting/img_plotting.py

@@ -34,6 +34,7 @@
 from .._utils.fixes.matplotlib_backports import (cbar_outline_get_xy,
                                                  cbar_outline_set_xy)
 from .._utils.ndimage import get_border_data
+from .._utils.exceptions import VisibleDeprecationWarning
 from ..datasets import load_mni152_template
 from ..image import iter_img
 from .displays import get_slicer, get_projector
@@ -807,7 +808,7 @@ def plot_prob_atlas(maps_img, bg_img=MNI152TEMPLATE, view_type='auto',
         bg_img = anat_img
         warn_str = ("anat_img is deprecated and will be removed in 0.5. "
                     "Use `bg_img` instead.")
-        warnings.warn(warn_str, np.VisibleDeprecationWarning, stacklevel=2)
+        warnings.warn(warn_str, VisibleDeprecationWarning, stacklevel=2)
 
     display = plot_anat(bg_img, cut_coords=cut_coords,
                         display_mode=display_mode,

nilearn/plotting/tests/test_find_cuts.py

@@ -1,5 +1,5 @@
 import numpy as np
-from nose.tools import assert_equal, assert_true
+from nose.tools import assert_equal, assert_true, assert_not_equal
 import nibabel
 from nilearn.plotting.find_cuts import (find_xyz_cut_coords, find_cut_slices,
                                         _transform_cut_coords)
@@ -88,6 +88,30 @@ def test_find_cut_slices():
         cuts = find_cut_slices(img, direction=direction,
                                n_cuts=n_cuts, spacing=2)
 
+    # non-diagonal affines
+    affine = np.array([[-1., 0., 0., 123.46980286],
+                       [0., 0., 1., -94.11079407],
+                       [0., -1., 0., 160.694],
+                       [0., 0., 0., 1.]])
+    img = nibabel.Nifti1Image(data, affine)
+    cuts = find_cut_slices(img, direction='z')
+    assert_not_equal(np.diff(cuts).min(), 0.)
+    affine = np.array([[-2., 0., 0., 123.46980286],
+                       [0., 0., 2., -94.11079407],
+                       [0., -2., 0., 160.694],
+                       [0., 0., 0., 1.]])
+    img = nibabel.Nifti1Image(data, affine)
+    cuts = find_cut_slices(img, direction='z')
+    assert_not_equal(np.diff(cuts).min(), 0.)
+    # Rotate it slightly
+    angle = np.pi / 180 * 15
+    rotation_matrix = np.array([[np.cos(angle), -np.sin(angle)],
+                                [np.sin(angle), np.cos(angle)]])
+    affine[:2, :2] = rotation_matrix * 2.0
+    img = nibabel.Nifti1Image(data, affine)
+    cuts = find_cut_slices(img, direction='z')
+    assert_not_equal(np.diff(cuts).min(), 0.)
+
 
 def test_validity_of_ncuts_error_in_find_cut_slices():
     data = np.zeros((50, 50, 50))