BabyAFQ : tractometry for infant dMRI data

[bertram0611]

Dear experts,

When trying the infant example using the link (https://tractometry.org/pyAFQ/howto/howto_examples/baby_afq.html#sphx-glr-howto-howto-examples-baby-afq-py), I got an error message as follows. It seems that it could not identify the posterior arcuate tract. The version of pyFAQ is 1.3.6 which was installed under python 3.9. Could you please tell how to fix this issue?

INFO:AFQ:Finding Streamlines for Left Posterior Arcuate INFO:AFQ:Preparing ROIs for Left Posterior Arcuate INFO:AFQ:Time to prep ROIs: 0.5421712398529053s INFO:AFQ:Filtering by Cross Mid. INFO:AFQ:After filtering by Cross Mid. (time: 0.010852813720703125s), 1929218 streamlines remain. INFO:AFQ:Filtering by Startpoint INFO:AFQ:After filtering by Startpoint (time: 5.258361101150513s), 106990 streamlines remain. INFO:AFQ:Filtering by endpoint INFO:AFQ:After filtering by endpoint (time: 0.17697930335998535s), 21294 streamlines remain. INFO:AFQ:Filtering by orientation Traceback (most recent call last): File "/home/lin/data/rel3_derivatives/afqtest.py", line 36, in viz = myafq.export("all_bundles_figure") File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/api/group.py", line 525, in export results[subject][session] = wf_dict[attr_name] File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem self._run_node(self.plan.efferents[k]) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node if not found: res = node(self) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 91, in call result = self.function(*args) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/viz.py", line 80, in viz_bundles profiles_file = segmentation_imap["profiles"] File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem self._run_node(self.plan.efferents[k]) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node if not found: res = node(self) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 90, in call args.append(opts[name]) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 888, in getitem return self._examine_val(k, ps.PMap.getitem(self, k)) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 884, in _examine_val val = val() File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1163, in def curry_choice(k, args): return lambda:choose_fn(k, args) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1132, in _choose_last return vs[-1][k] File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem self._run_node(self.plan.efferents[k]) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node if not found: res = node(self) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 91, in call result = self.function(*args) File "", line 2, in wrapper_has_args_func File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/decorators.py", line 149, in wrapper_as_file gen, meta = func(*args[:og_arg_count], **kwargs) File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/segmentation.py", line 87, in segment bundles, bundle_meta = recognize( File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/recognition/recognize.py", line 181, in recognize run_bundle_rec_plan( File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/recognition/criteria.py", line 380, in run_bundle_rec_plan inputs[criterion] = globals()criterion File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/recognition/criteria.py", line 111, in primary_axis accept_idx = abc.clean_by_orientation( File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/recognition/cleaning.py", line 33, in clean_by_orientation raise ValueError( ValueError: Primary axis must be one of ['L/R', 'P/A', 'I/S'], got 2

[36000]

It looks like babyAFQ is broken for this version! I would switch to pyAFQ 2.0 or above. It looks like pyAFQ 1.3.5 would also fix this. You can also stay in pyAFQ 1.3.6 and fix it by doing this:

    ......

    import AFQ.data.fetch as afd
    from AFQ.api.bundle_dict import BundleDict

    templates = afd.read_pediatric_templates()

    # pediatric probability maps
    prob_map_order = [
        "ATR_L", "ATR_R", "CST_L", "CST_R", "CGC_L", "CGC_R",
        "MdLF_L", "MdLF_R", "FP", "FA", "IFO_L", "IFO_R", "ILF_L",
        "ILF_R", "SLF_L", "SLF_R", "UNC_L", "UNC_R",
        "ARC_L", "ARC_R"]

    prob_maps = templates[
        'UNCNeo_JHU_tracts_prob-for-babyAFQ']
    prob_map_data = prob_maps.get_fdata()

    for bundle_name in prob_map_order:
        templates[bundle_name + "_prob_map"] = nib.Nifti1Image(
            prob_map_data[
                ...,
                prob_map_order.index(bundle_name)], prob_maps.affine)

    # reuse probability map from ILF
    templates["MdLF_L_prob_map"] = templates["ILF_L_prob_map"]
    templates["MdLF_R_prob_map"] = templates["ILF_R_prob_map"]
    bundle_dict = BundleDict({
        'Left Anterior Thalamic': {
            'cross_midline': False,
            'include': [
                templates['ATR_roi3_L'],
                templates['ATR_roi2_L'],
                templates['ATR_roi1_L']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['ATR_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Anterior Thalamic': {'cross_midline': False,
                                    'include': [
                                        templates['ATR_roi3_R'],
                                        templates['ATR_roi2_R'],
                                        templates['ATR_roi1_R']],
                                    'exclude': [],
                                    'space': 'template',
                                    'prob_map': templates['ATR_R_prob_map'],
                                    'mahal': {'distance_threshold': 4}},
        'Left Cingulum Cingulate': {
            'cross_midline': False,
            'include': [templates['CGC_roi3_L'],
                        templates['CGC_roi2_L'],
                        templates['CGC_roi1_L']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['CGC_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Cingulum Cingulate': {
            'cross_midline': False,
            'include': [templates['CGC_roi3_R'],
                        templates['CGC_roi2_R'],
                        templates['CGC_roi1_R']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['CGC_R_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Left Corticospinal': {'cross_midline': False,
                               'include': [templates['CST_roi2_L'],
                                           templates['CST_roi1_L']],
                               'exclude': [],
                               'space': 'template',
                               'prob_map': templates['CST_L_prob_map'],
                               'mahal': {'distance_threshold': 4}},
        'Right Corticospinal': {'cross_midline': False,
                                'include': [templates['CST_roi2_R'],
                                            templates['CST_roi1_R']],
                                'exclude': [],
                                'space': 'template',
                                'prob_map': templates['CST_R_prob_map'],
                                'mahal': {'distance_threshold': 4}},
        'Left Inferior Fronto-occipital': {
            'cross_midline': False,
            'include': [templates['IFO_roi3_L'],
                        templates['IFO_roi2_L'],
                        templates['IFO_roi1_L']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['IFO_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Inferior Fronto-occipital': {
            'cross_midline': False,
            'include': [templates['IFO_roi3_R'],
                        templates['IFO_roi2_R'],
                        templates['IFO_roi1_R']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['IFO_R_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Left Inferior Longitudinal': {
            'cross_midline': False,
            'include': [templates['ILF_roi2_L'],
                        templates['ILF_roi1_L']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['ILF_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Inferior Longitudinal': {
            'cross_midline': False,
            'include': [templates['ILF_roi2_R'],
                        templates['ILF_roi1_R']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['ILF_R_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Left Middle Longitudinal': {
            'cross_midline': False,
            'include': [templates['MdLF_roi2_L'],
                        templates['MdLF_roi1_L']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['MdLF_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Middle Longitudinal': {
            'cross_midline': False,
            'include': [templates['MdLF_roi2_R'],
                        templates['MdLF_roi1_R']],
            'exclude': [],
            'space': 'template',
            'prob_map': templates['MdLF_R_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Left Superior Longitudinal': {
            'cross_midline': False,
            'include': [templates['SLF_roi1_L'],
                        templates['SLF_roi2_L']],
            'exclude': [templates['SLFt_roi2_L']],
            'space': 'template',
            'prob_map': templates['SLF_L_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Right Superior Longitudinal': {
            'cross_midline': False,
            'include': [templates['SLF_roi1_R'],
                        templates['SLF_roi2_R']],
            'exclude': [templates['SLFt_roi2_R']],
            'space': 'template',
            'prob_map': templates['SLF_R_prob_map'],
            'mahal': {'distance_threshold': 4}},
        'Left Arcuate': {'cross_midline': False,
                         'include': [templates['ARC_roi1_L'],
                                     templates['ARC_roi2_L'],
                                     templates['ARC_roi3_L']],
                         'exclude': [],
                         'space': 'template',
                         'prob_map': templates['ARC_L_prob_map'],
                         'mahal': {'distance_threshold': 4}},
        'Right Arcuate': {'cross_midline': False,
                          'include': [templates['ARC_roi1_R'],
                                      templates['ARC_roi2_R'],
                                      templates['ARC_roi3_R']],
                          'exclude': [],
                          'space': 'template',
                          'prob_map': templates['ARC_R_prob_map'],
                          'mahal': {'distance_threshold': 4}},
        'Left Uncinate': {'cross_midline': False,
                          'include': [templates['UNC_roi3_L'],
                                      templates['UNC_roi2_L'],
                                      templates['UNC_roi1_L']],
                          'exclude': [],
                          'space': 'template',
                          'prob_map': templates['UNC_L_prob_map'],
                          'mahal': {'distance_threshold': 4}},
        'Right Uncinate': {'cross_midline': False,
                           'include': [templates['UNC_roi3_R'],
                                       templates['UNC_roi2_R'],
                                       templates['UNC_roi1_R']],
                           'exclude': [],
                           'space': 'template',
                           'prob_map': templates['UNC_R_prob_map'],
                           'mahal': {'distance_threshold': 4}},
        'Forceps Minor': {'cross_midline': True,
                          'include': [templates['FA_R'],
                                      templates['mid-saggital'],
                                      templates['FA_L']],
                          'exclude': [],
                          'space': 'template',
                          'prob_map': templates['FA_prob_map'],
                          'mahal': {'distance_threshold': 4}},
        'Forceps Major': {'cross_midline': True,
                          'include': [templates['FP_R'],
                                      templates['mid-saggital'],
                                      templates['FP_L']],
                          'exclude': [],
                          'space': 'template',
                          'prob_map': templates['FP_prob_map'],
                          'mahal': {'distance_threshold': 4}},
        'Left Optic Radiation': {
            "include": [templates["OR_left_roi3"]],
            "start": templates["OR_leftThal"],
            "end": templates["OR_leftV1"],
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}},
        'Right Optic Radiation': {
            "include": [templates["OR_right_roi3"]],
            "start": templates["OR_rightThal"],
            "end": templates["OR_rightV1"],
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}},
        'Left Posterior Arcuate': {
            "include": [templates["SLFt_roi2_L"]],
            "exclude": [templates["SLF_roi1_L"]],
            "start": templates["pARC_L_start"],
            "end": templates["VOF_box_small_L"],
            "primary_axis": 'I/S',
            "primary_axis_percentage": 40,
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}},
        'Right Posterior Arcuate': {
            "include": [templates["SLFt_roi2_R"]],
            "exclude": [templates["SLF_roi1_R"]],
            "start": templates["pARC_R_start"],
            "end": templates["VOF_box_small_R"],
            "primary_axis": 'I/S',
            "primary_axis_percentage": 40,
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}},
        'Left Vertical Occipital': {
            "start": templates["VOF_L_start"],
            "end": templates["VOF_box_small_L"],
            "primary_axis": 'I/S',
            "primary_axis_percentage": 40,
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}},
        'Right Vertical Occipital': {
            "start": templates["VOF_R_start"],
            "end": templates["VOF_box_small_R"],
            "primary_axis": 'I/S',
            "primary_axis_percentage": 40,
            "cross_midline": False,
            "mahal": {"distance_threshold": 4}}},
        resample_to=afd.read_pediatric_templates()[
            'UNCNeo-withCerebellum-for-babyAFQ'])

    .....

    myafq = GroupAFQ(
        ....,
        bundle_info=bundle_dict,
        ....)
    

[36000]

Let me know if this fix works

[bertram0611]

Hi,
Thank you very much for your quick answer.
I am still using the pyAFQ 1.3.6 by integrating code you provided. The issue has been fixed.
Then I tested my own infant data using the following settings.

# --------------------------------------------------
# Initialize pyAFQ (PNAS-style, updated)
# --------------------------------------------------
myafq = ParticipantAFQ(
    # ---- Required DWI inputs ----
    dwi_nifti,
    bval,
    bvec,
    afq_outdir,

    # ---- Registration ----
    reg_template_spec=afd.read_pediatric_templates()[
        "UNCNeo-withCerebellum-for-babyAFQ"
    ],
    reg_subject_spec="b0",
    mapping_definition=AffMap(),
    brain_mask=brainmask,

    **# ---- Scalars ----
    scalars=[
        "dti_fa",
        "dti_md",
        "dki_fa",
        "dki_md",
        "dki_mk",
    ],**

    # ---- Bundles (NEW: 26 bundles) ----
    #bundle_info=abd.baby_bd(),
    bundle_info=bundle_dict,

    # ---- Tractography (import MRtrix result) ----
    import_tract=tractogram,

    # ---- Segmentation / cleaning ----
    segmentation_params={
        "filter_by_endpoints": False,
        "parallel_segmentation": {"engine": "serial"},
        "dist_to_waypoint": 0.5,
    },
    clean_params={
        "distance_threshold": 3,
    },
)

# --------------------------------------------------
# Run pyAFQ
# --------------------------------------------------
print("Running pyAFQ bundle recognition...")

myafq.export("template_xform")
myafq.clobber(dependent_on="recog")
myafq.export_all()

print("pyAFQ finished successfully.")

However, once I set the scalars argument, the error message would be as follows. I am wondering how can I set parameters if I want to get specific metrics, such as fwdti_fwf etc.

INFO:AFQ:Saving output/afq/sub-CC00063AN06/ses-15102/sub-CC00063AN06_ses-15102_coordsys-RASMM_trkmethod-probCSD_recogmethod-AFQ_desc-medianBundleLengths_dwi.csv
Traceback (most recent call last):
File "", line 1, in
File "/home/lin/data/rel3_derivatives/dhcp_pyafq_pipeline.py", line 339, in dhcp_pyafq_pipeline_local

File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/api/participant.py", line 201, in export_all
export_all_helper(self, xforms, indiv, viz)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/api/utils.py", line 128, in export_all_helper
api_afq_object.export("profiles")
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/api/participant.py", line 155, in export
return self.wf_dict[section][attr_name]
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem
self._run_node(self.plan.efferents[k])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node
if not found: res = node(self)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 90, in call
args.append(opts[name])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 888, in getitem
return self._examine_val(k, ps.PMap.getitem(self, k))
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 884, in _examine_val
val = val()
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1163, in
def curry_choice(k, args): return lambda:choose_fn(k, args)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1132, in _choose_last
return vs[-1][k]
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem
self._run_node(self.plan.efferents[k])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node
if not found: res = node(self)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 91, in call
result = self.function(*args)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/segmentation.py", line 380, in get_scalar_dict
scalar_dict[sc] = data_imap[f"{sc}"]
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem
self._run_node(self.plan.efferents[k])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node
if not found: res = node(self)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 90, in call
args.append(opts[name])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 888, in getitem
return self._examine_val(k, ps.PMap.getitem(self, k))
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 884, in _examine_val
val = val()
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1163, in
def curry_choice(k, args): return lambda:choose_fn(k, args)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1132, in _choose_last
return vs[-1][k]
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem
self._run_node(self.plan.efferents[k])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node
if not found: res = node(self)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 90, in call
args.append(opts[name])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 888, in getitem
return self._examine_val(k, ps.PMap.getitem(self, k))
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 884, in _examine_val
val = val()
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1163, in
def curry_choice(k, args): return lambda:choose_fn(k, args)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/util.py", line 1132, in _choose_last
return vs[-1][k]
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 470, in getitem
self._run_node(self.plan.efferents[k])
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 534, in _run_node
if not found: res = node(self)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/pimms/calculation.py", line 91, in call
result = self.function(*args)
File "", line 2, in wrapper_has_args_func
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/decorators.py", line 149, in wrapper_as_file
gen, meta = func(*args[:og_arg_count], **kwargs)
File "", line 2, in wrapper_has_args_func
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/decorators.py", line 220, in wrapper_as_img
data, meta = func(*args[:og_arg_count], **kwargs)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/tasks/data.py", line 165, in dti_params
dtf = dti_fit_model(
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/AFQ/models/dti.py", line 82, in _fit
return dtimodel.fit(data, mask=mask)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/dipy/reconst/dti.py", line 826, in fit
params_in_mask, extra = self.fit_method(
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/dipy/reconst/dti.py", line 1350, in wrapped_fit_tensor
= fit_tensor(design_matrix,
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/dipy/reconst/dti.py", line 1454, in wls_fit_tensor
np.linalg.pinv(design_matrix * w[..., None]),
File "<array_function internals>", line 180, in pinv
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/numpy/linalg/linalg.py", line 1998, in pinv
u, s, vt = svd(a, full_matrices=False, hermitian=hermitian)
File "<array_function internals>", line 180, in svd
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/numpy/linalg/linalg.py", line 1657, in svd
u, s, vh = gufunc(a, signature=signature, extobj=extobj)
File "/home/lin/anaconda3/envs/pyafq39/lib/python3.9/site-packages/numpy/linalg/linalg.py", line 98, in _raise_linalgerror_svd_nonconvergence
raise LinAlgError("SVD did not converge")
numpy.linalg.LinAlgError: SVD did not converge

Besides, I also noticed a warning message as follows. Could you please help me to check if it is safe when I get such messages.
WARNING:AFQ:Conflicts in bundle assignment detected. 551 conflicts detected in total out of 2000000 total streamlines.Defaulting to whichever bundle appears firstin the bundle_dict.
INFO:AFQ:Re-orienting streamlines to consistent directions

I am looking forward to your insightful comments.

[36000]

The warning is normal, we should change that to say info. I will make that change to the codebase.

---

You can ask for more tissue properties using this syntax:

ParticipantAFQ(
....,
scalars = ["dti_fa", "dti_md", "fwdti_fwf"],
....)

The tissue properties available for that version using single shell data are:
["csd_pmap", "csd_ai", "gq_iso", "gq_aso", "gq_pmap", "gq_ai", "opdt_gfa", "opdt_pmap", "opdt_ai", "csa_gfa", "csa_pmap", "csa_ai", "fwdti_fa", "fwdti_md", "fwdti_fwf", "dti_cfa", "dti_pdd", "dti_ga", "dti_rd", "dti_ad"]

However, many of these models are highly correlated, so we tend to stick to DTI and free water DTI.

---

For the error, I am not sure. I am not an expert on this data. DTI not fitting is concerning, and suggests something wrong with the data. I might check:

1. Are there NaNs in the data?
2. Is the brain mask roughly correct?

To get better advice, could you provide:

1. Details about the scan (resolution, number of volumes, etc.)
2. Perhaps more importantly, details about the preprocessing pipeline

Finally, there is an option you can set in pyafq by passing robust_tensor_fitting=True to ParticipantAFQ which can help with noisy data. If you do this, delete your current output folders using .clobber() to force AFQ to recalculate derivatives with this option on.