Merge pull request #774 from MichielCottaar/check_cifti_shape

ENH: Check CIFTI-2 data shape matches shape described by header

Author: effigies

nibabel/batteryrunners.py

@@ -141,7 +141,7 @@ def check_only(self, obj):
         -------
         reports : sequence
            sequence of report objects reporting on result of running
-           checks (withou fixes) on `obj`
+           checks (without fixes) on `obj`
         '''
         reports = []
         for check in self._checks:

nibabel/cifti2/cifti2.py

@@ -30,6 +30,7 @@
 from ..nifti2 import Nifti2Image, Nifti2Header
 from ..arrayproxy import reshape_dataobj
 from ..keywordonly import kw_only_meth
+from warnings import warn
 
 
 def _float_01(val):
@@ -1209,6 +1210,38 @@ def _to_xml_element(self):
             mat.append(mim._to_xml_element())
         return mat
 
+    def get_axis(self, index):
+        '''
+        Generates the Cifti2 axis for a given dimension
+
+        Parameters
+        ----------
+        index : int
+            Dimension for which we want to obtain the mapping.
+
+        Returns
+        -------
+        axis : :class:`.cifti2_axes.Axis`
+        '''
+        from . import cifti2_axes
+        return cifti2_axes.from_index_mapping(self.get_index_map(index))
+
+    def get_data_shape(self):
+        """
+        Returns data shape expected based on the CIFTI-2 header
+
+        Any dimensions omitted in the CIFTI-2 header will be given a default size of None.
+        """
+        from . import cifti2_axes
+        if len(self.mapped_indices) == 0:
+            return ()
+        base_shape = [None] * (max(self.mapped_indices) + 1)
+        for mim in self:
+            size = len(cifti2_axes.from_index_mapping(mim))
+            for idx in mim.applies_to_matrix_dimension:
+                base_shape[idx] = size
+        return tuple(base_shape)
+
 
 class Cifti2Header(FileBasedHeader, xml.XmlSerializable):
     ''' Class for CIFTI-2 header extension '''
@@ -1279,8 +1312,7 @@ def get_axis(self, index):
         -------
         axis : :class:`.cifti2_axes.Axis`
         '''
-        from . import cifti2_axes
-        return cifti2_axes.from_index_mapping(self.matrix.get_index_map(index))
+        return self.matrix.get_axis(index)
 
     @classmethod
     def from_axes(cls, axes):
@@ -1345,12 +1377,18 @@ def __init__(self,
         super(Cifti2Image, self).__init__(dataobj, header=header,
                                           extra=extra, file_map=file_map)
         self._nifti_header = Nifti2Header.from_header(nifti_header)
+
         # if NIfTI header not specified, get data type from input array
         if nifti_header is None:
             if hasattr(dataobj, 'dtype'):
                 self._nifti_header.set_data_dtype(dataobj.dtype)
         self.update_headers()
 
+        if self._dataobj.shape != self.header.matrix.get_data_shape():
+            warn("Dataobj shape {} does not match shape expected from CIFTI-2 header {}".format(
+                self._dataobj.shape, self.header.matrix.get_data_shape()
+            ))
+
     @property
     def nifti_header(self):
         return self._nifti_header
@@ -1426,6 +1464,11 @@ def to_file_map(self, file_map=None):
         header = self._nifti_header
         extension = Cifti2Extension(content=self.header.to_xml())
         header.extensions.append(extension)
+        if self._dataobj.shape != self.header.matrix.get_data_shape():
+            raise ValueError(
+                "Dataobj shape {} does not match shape expected from CIFTI-2 header {}".format(
+                    self._dataobj.shape, self.header.matrix.get_data_shape()
+                ))
         # if intent code is not set, default to unknown CIFTI
         if header.get_intent()[0] == 'none':
             header.set_intent('NIFTI_INTENT_CONNECTIVITY_UNKNOWN')
@@ -1438,7 +1481,7 @@ def to_file_map(self, file_map=None):
         img.to_file_map(file_map or self.file_map)
 
     def update_headers(self):
-        ''' Harmonize CIFTI-2 and NIfTI headers with image data
+        ''' Harmonize NIfTI headers with image data
 
         >>> import numpy as np
         >>> data = np.zeros((2,3,4))

nibabel/cifti2/tests/test_cifti2.py

@@ -358,4 +358,10 @@ class TestCifti2ImageAPI(_TDA):
     standard_extension = '.nii'
 
     def make_imaker(self, arr, header=None, ni_header=None):
+        for idx, sz in enumerate(arr.shape):
+            maps = [ci.Cifti2NamedMap(str(value)) for value in range(sz)]
+            mim = ci.Cifti2MatrixIndicesMap(
+                (idx, ), 'CIFTI_INDEX_TYPE_SCALARS', maps=maps
+            )
+            header.matrix.append(mim)
         return lambda: self.image_maker(arr.copy(), header, ni_header)

nibabel/cifti2/tests/test_new_cifti2.py

@@ -12,11 +12,13 @@
 from nibabel import cifti2 as ci
 from nibabel.tmpdirs import InTemporaryDirectory
 
-from nose.tools import assert_true, assert_equal
+from nose.tools import assert_true, assert_equal, assert_raises
+from nibabel.testing import clear_and_catch_warnings, error_warnings, suppress_warnings
 
 affine = [[-1.5, 0, 0, 90],
           [0, 1.5, 0, -85],
-          [0, 0, 1.5, -71]]
+          [0, 0, 1.5, -71],
+          [0, 0, 0, 1.]]
 
 dimensions = (120, 83, 78)
 
@@ -234,7 +236,7 @@ def test_dtseries():
     matrix.append(series_map)
     matrix.append(geometry_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(13, 9)
+    data = np.random.randn(13, 10)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_DENSE_SERIES')
 
@@ -257,7 +259,7 @@ def test_dscalar():
     matrix.append(scalar_map)
     matrix.append(geometry_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 9)
+    data = np.random.randn(2, 10)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_DENSE_SCALARS')
 
@@ -279,7 +281,7 @@ def test_dlabel():
     matrix.append(label_map)
     matrix.append(geometry_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 9)
+    data = np.random.randn(2, 10)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_DENSE_LABELS')
 
@@ -299,7 +301,7 @@ def test_dconn():
     matrix = ci.Cifti2Matrix()
     matrix.append(mapping)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(9, 9)
+    data = np.random.randn(10, 10)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_DENSE')
 
@@ -322,7 +324,7 @@ def test_ptseries():
     matrix.append(series_map)
     matrix.append(parcel_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(13, 3)
+    data = np.random.randn(13, 4)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED_SERIES')
 
@@ -344,7 +346,7 @@ def test_pscalar():
     matrix.append(scalar_map)
     matrix.append(parcel_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 3)
+    data = np.random.randn(2, 4)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED_SCALAR')
 
@@ -366,7 +368,7 @@ def test_pdconn():
     matrix.append(geometry_map)
     matrix.append(parcel_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 3)
+    data = np.random.randn(10, 4)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED_DENSE')
 
@@ -388,7 +390,7 @@ def test_dpconn():
     matrix.append(parcel_map)
     matrix.append(geometry_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 3)
+    data = np.random.randn(4, 10)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_DENSE_PARCELLATED')
 
@@ -410,7 +412,7 @@ def test_plabel():
     matrix.append(label_map)
     matrix.append(parcel_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(2, 3)
+    data = np.random.randn(2, 4)
     img = ci.Cifti2Image(data, hdr)
 
     with InTemporaryDirectory():
@@ -429,7 +431,7 @@ def test_pconn():
     matrix = ci.Cifti2Matrix()
     matrix.append(mapping)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(3, 3)
+    data = np.random.randn(4, 4)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED')
 
@@ -453,7 +455,7 @@ def test_pconnseries():
     matrix.append(parcel_map)
     matrix.append(series_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(3, 3, 13)
+    data = np.random.randn(4, 4, 13)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED_'
                                 'PARCELLATED_SERIES')
@@ -479,7 +481,7 @@ def test_pconnscalar():
     matrix.append(parcel_map)
     matrix.append(scalar_map)
     hdr = ci.Cifti2Header(matrix)
-    data = np.random.randn(3, 3, 13)
+    data = np.random.randn(4, 4, 2)
     img = ci.Cifti2Image(data, hdr)
     img.nifti_header.set_intent('NIFTI_INTENT_CONNECTIVITY_PARCELLATED_'
                                 'PARCELLATED_SCALAR')
@@ -496,3 +498,29 @@ def test_pconnscalar():
         check_parcel_map(img2.header.matrix.get_index_map(0))
         check_scalar_map(img2.header.matrix.get_index_map(2))
         del img2
+
+
+def test_wrong_shape():
+    scalar_map = create_scalar_map((0, ))
+    brain_model_map = create_geometry_map((1, ))
+
+    matrix = ci.Cifti2Matrix()
+    matrix.append(scalar_map)
+    matrix.append(brain_model_map)
+    hdr = ci.Cifti2Header(matrix)
+
+    # correct shape is (2, 10)
+    for data in (
+        np.random.randn(1, 11),
+        np.random.randn(2, 10, 1),
+        np.random.randn(1, 2, 10),
+        np.random.randn(3, 10),
+        np.random.randn(2, 9),
+    ):
+        with clear_and_catch_warnings():
+            with error_warnings():
+                assert_raises(UserWarning, ci.Cifti2Image, data, hdr)
+        with suppress_warnings():
+            img = ci.Cifti2Image(data, hdr)
+        assert_raises(ValueError, img.to_file_map)
+