Add facility to align acorss all FIDs in higher dimensions of nifti-mrs.

fsl_mrs/core/nifti_mrs.py

@@ -428,6 +428,21 @@ class NIFTI_MRS(Image):
         else:
             raise TypeError('dim should be int or a string matching one of the dim tags.')
 
+    def iterate_over_spatial(self):
+        """Iterate over spatial voxels yeilding a data array the shape of the FID and any higher dimensions + index.
+
+        :yield: Complex FID data with any higher dimensions. Index to data.
+        :rtype: tuple
+        """
+        data = self.data
+
+        def calc_slice_idx(idx):
+            slice_obj = list(idx[:3]) + [slice(None), ] * (self.data.ndim - 3)
+            return tuple(slice_obj)
+
+        for idx in np.ndindex(data.shape[:3]):
+            yield self.data[idx], calc_slice_idx(idx)
+
     def generate_mrs(self, dim=None, basis_file=None, basis=None, ref_data=None):
         """Generator for MRS or MRSI objects from the data, optionally returning a whole dimension as a list.
 

fsl_mrs/tests/test_core_nifti_mrs.py

@@ -91,6 +91,18 @@ def test_nifti_mrs_generator():
         break
 
 
+def test_nifti_mrs_spatial_generator():
+    obj = NIFTI_MRS(data['unprocessed'])
+
+    for gen_data, slice_idx in obj.iterate_over_spatial():
+        assert gen_data.shape == (4096, 32, 64)
+        assert slice_idx == (0, 0, 0,
+                             slice(None, None, None),
+                             slice(None, None, None),
+                             slice(None, None, None))
+        break
+
+
 def test_nifti_mrs_gen_mrs():
     obj = NIFTI_MRS(data['unprocessed'])
 

fsl_mrs/tests/test_utils_nifti_mrs_proc.py

@@ -75,6 +75,14 @@ def test_align():
         == 'fsl_mrs.utils.preproc.nifti_mrs_proc.align, dim=DIM_DYN, '\
            'target=None, ppmlim=(1.0, 4.0), niter=1, apodize=5.'
 
+    # Align across all spectra
+    aligned3 = nproc.align(with_coils, 'all', ppmlim=(1.0, 4.0), niter=1, apodize=5)
+
+    assert aligned3.hdr_ext['ProcessingApplied'][0]['Method'] == 'Frequency and phase correction'
+    assert aligned3.hdr_ext['ProcessingApplied'][0]['Details']\
+        == 'fsl_mrs.utils.preproc.nifti_mrs_proc.align, dim=all, '\
+           'target=None, ppmlim=(1.0, 4.0), niter=1, apodize=5.'
+
 
 def test_aligndiff():
     # For want of data this is a bizzare way of using this function.

fsl_mrs/utils/preproc/nifti_mrs_proc.py

@@ -161,11 +161,11 @@ def average(data, dim, figure=False, report=None, report_all=False):
 
 
 def align(data, dim, target=None, ppmlim=None, niter=2, apodize=10, figure=False, report=None, report_all=False):
-    '''Align frequencies of spectra across a dimension
-    specified by a tag.
+    '''Align frequency and phase of spectra. Can be run across a dimension (specified by a tag), or all spectra
+    stored in higher dimensions.
 
     :param NIFTI_MRS data: Data to align
-    :param str dim: NIFTI-MRS dimension tag
+    :param str dim: NIFTI-MRS dimension tag, or 'all'
     :param target: Optional target FID
     :param ppmlim: ppm search limits.
     :param int niter: Number of total iterations
@@ -178,9 +178,19 @@ def align(data, dim, target=None, ppmlim=None, niter=2, apodize=10, figure=False
     '''
 
     aligned_obj = data.copy()
-    for dd, idx in data.iterate_over_dims(dim=dim,
+
+    if dim == 'all':
+        generator = data.iterate_over_spatial()
+    else:
+        generator = data.iterate_over_dims(dim=dim,
                                            iterate_over_space=True,
-                                          reduce_dim_index=False):
+                                           reduce_dim_index=False)
+    for dd, idx in generator:
+
+        if dim == 'all':
+            # flatten
+            original_shape = dd.shape
+            dd = dd.reshape(original_shape[0], -1)
 
         out = preproc.phase_freq_align(
             dd.T,
@@ -193,12 +203,15 @@ def align(data, dim, target=None, ppmlim=None, niter=2, apodize=10, figure=False
             verbose=False,
             target=target)
 
+        if dim == 'all':
+            aligned_obj[idx], phi, eps = out[0].T.reshape(original_shape), out[1], out[2]
+        else:
             aligned_obj[idx], phi, eps = out[0].T, out[1], out[2]
 
         if (figure or report) and (report_all or first_index(idx)):
             from fsl_mrs.utils.preproc.align import phase_freq_align_report
             fig = phase_freq_align_report(dd.T,
-                                          aligned_obj[idx].T,
+                                          out[0],
                                           phi,
                                           eps,
                                           data.bandwidth,
@@ -333,8 +346,10 @@ def ecc(data, reference, figure=False, report=None, report_all=False):
     for dd, idx in data.iterate_over_dims(iterate_over_space=True):
 
         if data.shape == reference.shape:
+            # Reference is the same shape as data, voxel-wise and spectrum-wise iteration
             ref = reference[idx]
         else:
+            # Only one reference FID, only iterate over spatial voxels.
             ref = reference[idx[0], idx[1], idx[2], :]
 
         corrected_obj[idx] = preproc.eddy_correct(dd, ref)