Add all option to command line.

CHANGELOG.rst

 This document contains the FSL-MRS release history in reverse chronological order.
 
+1.1.5 (WIP)
+-------------------------------
+- fsl_mrs_proc align can now align across all higher dimension FIDs. Pass 'all' as dimension tag.
+
 1.1.4 (Tuesday 3rd August 2021)
 -------------------------------
 - Fixed bug in calculation of molality concentration. Tissue mole fractions had been swapped for tissue volume fractions. Molar concentrations unaffected.

fsl_mrs/scripts/fsl_mrs_proc

@@ -85,6 +85,7 @@ def main():
                              help='List of files to align')
     align_group.add_argument('--dim', type=str, default='DIM_DYN',
                              help='NIFTI-MRS dimension tag to align across.'
+                                  'Or "all" to align over all spectra in higer dimensions.'
                                   'Default = DIM_DYN')
     align_group.add_argument('--ppm', type=float, nargs=2,
                              metavar='<lower-limit upper-limit>',
@@ -473,7 +474,9 @@ def average(dataobj, args):
 
 
 def align(dataobj, args):
-    if args['dim'] not in dataobj.data.dim_tags:
+    if args['dim'].lower() == 'all':
+        pass
+    elif args['dim'] not in dataobj.data.dim_tags:
         raise InappropriateDataError(f'Data ({dataobj.datafilename}) has no {args["dim"]} dimension.'
                                      f' Dimensions are is {dataobj.data.dim_tags}.')
 

fsl_mrs/tests/test_scripts_proc.py

@@ -195,11 +195,42 @@ def mrsi_data_diff(tmp_path):
     return testfile, nmrs
 
 
+@pytest.fixture
+def svs_data_uncomb_reps(tmp_path):
+    coils = 2
+    noiseconv = 0.1 * np.eye(coils)
+    coilamps = np.random.randn(coils)
+    coilphs = np.random.random(coils) * 2 * np.pi
+    FID, hdr = syntheticFID(noisecovariance=noiseconv,
+                            coilamps=coilamps,
+                            coilphase=coilphs,
+                            points=512)
+
+    FID2, hdr = syntheticFID(noisecovariance=noiseconv,
+                             coilamps=coilamps,
+                             coilphase=coilphs,
+                             points=512)
+
+    FID = np.stack((np.asarray(FID).T, np.asarray(FID2).T), axis=2)
+    FID = FID.reshape((1, 1, 1) + FID.shape)
+
+    nmrs = gen_new_nifti_mrs(FID,
+                             hdr['dwelltime'],
+                             hdr['centralFrequency'],
+                             dim_tags=['DIM_COIL', 'DIM_DYN', None])
+
+    testname = 'svsdata_uncomb_reps.nii'
+    testfile = op.join(tmp_path, testname)
+    nmrs.save(testfile)
+
+    return testfile, nmrs
+
+
 def splitdata(svs, mrsi):
     return svs[0], mrsi[0], svs[1], mrsi[1]
 
 
-def test_filecreation(svs_data, mrsi_data, svs_data_uncomb, mrsi_data_uncomb):
+def test_filecreation(svs_data, mrsi_data, svs_data_uncomb, mrsi_data_uncomb, svs_data_uncomb_reps):
     svsfile, mrsifile, svsdata, mrsidata = splitdata(svs_data, mrsi_data)
 
     data = read_FID(svsfile)
@@ -221,6 +252,11 @@ def test_filecreation(svs_data, mrsi_data, svs_data_uncomb, mrsi_data_uncomb):
     assert data.shape == (2, 2, 2, 512, 4)
     assert np.allclose(data.data, mrsidata.data)
 
+    # Uncombined and reps
+    data = read_FID(svs_data_uncomb_reps[0])
+    assert data.shape == (1, 1, 1, 512, 2, 2)
+    assert np.allclose(data.data, svs_data_uncomb_reps[1].data)
+
 
 def test_coilcombine(svs_data_uncomb, mrsi_data_uncomb, tmp_path):
     svsfile, mrsifile, svsdata, mrsidata = splitdata(svs_data_uncomb,
@@ -313,7 +349,6 @@ def test_align(svs_data, mrsi_data, tmp_path):
 
     assert np.allclose(data.data, directRun.data)
 
-    # Run coil combination on both sets of data using the command line
     subprocess.check_call(['fsl_mrs_proc',
                            'align',
                            '--dim', 'DIM_DYN',
@@ -331,6 +366,27 @@ def test_align(svs_data, mrsi_data, tmp_path):
     assert np.allclose(data.data, directRun.data, atol=1E-1, rtol=1E-1)
 
 
+def test_align_all(svs_data_uncomb_reps, tmp_path):
+    svsfile, svsdata = svs_data_uncomb_reps[0], svs_data_uncomb_reps[1]
+
+    # Run align on both sets of data using the command line
+    subprocess.check_call(['fsl_mrs_proc',
+                           'align',
+                           '--dim', 'all',
+                           '--file', svsfile,
+                           '--ppm', '-10', '10',
+                           '--output', tmp_path,
+                           '--filename', 'tmp'])
+
+    # Load result for comparison
+    data = read_FID(op.join(tmp_path, 'tmp.nii.gz'))
+
+    # Run directly
+    directRun = preproc.align(svsdata, 'all', ppmlim=(-10, 10))
+
+    assert np.allclose(data.data, directRun.data)
+
+
 def test_ecc(svs_data, mrsi_data, tmp_path):
     svsfile, mrsifile, svsdata, mrsidata = splitdata(svs_data, mrsi_data)
 

fsl_mrs/utils/preproc/nifti_mrs_proc.py

@@ -179,7 +179,7 @@ def align(data, dim, target=None, ppmlim=None, niter=2, apodize=10, figure=False
 
     aligned_obj = data.copy()
 
-    if dim == 'all':
+    if dim.lower() == 'all':
         generator = data.iterate_over_spatial()
     else:
         generator = data.iterate_over_dims(dim=dim,