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merged 5 commits into from
Mar 12, 2021
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NF: AFNI 3dNetCorr as afni.NetCorr #3263

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a8ee022
ENH: added afni NetCorr
aghayoor Oct 21, 2020
6da8ee8
ENH: modified afni NetCorr development
aghayoor Mar 1, 2021
380d798
ENH: AFNI NetCorr sorted commandline
aghayoor Mar 2, 2021
bfcfa94
ENH: added the correlation maps to the output afni NetCorr
aghayoor Mar 4, 2021
c00dd2f
ENH: added test_auto_NetCorr
aghayoor Mar 4, 2021
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ENH: added afni NetCorr 
Afni 3dNetCorr is added to nipype. For more details, please see: https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dNetCorr.html
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@aghayoor
aghayoor committed Mar 2, 2021
commit a8ee022d6c3d0217aae9837147d16fad110f18db
1 change: 1 addition & 0 deletions nipype/interfaces/afni/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@
LFCD,
Maskave,
Means,
NetCorr,
OutlierCount,
QualityIndex,
ROIStats,
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73 changes: 73 additions & 0 deletions nipype/interfaces/afni/preprocess.py
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Expand Up @@ -2556,6 +2556,79 @@ def _format_arg(self, name, trait_spec, value):
return super(TCorrMap, self)._format_arg(name, trait_spec, value)


class NetCorrInputSpec(AFNICommandInputSpec):
in_file = File(exists=True, argstr="-inset %s", mandatory=True)
in_rois = File(exists=True, argstr="-in_rois %s", mandatory=True)
mask = File(exists=True, argstr="-mask %s")
weight_ts = File(exists=True, argstr="-weight_ts %s")
fish_z = traits.Bool(argstr="-fish_z")
part_corr = traits.Bool(argstr="-part_corr")
ts_out = traits.Bool(argstr="-ts_out")
ts_label = traits.Bool(argstr="-ts_label")
ts_indiv = traits.Bool(argstr="-ts_indiv")
ts_wb_corr = traits.Bool(argstr="-ts_wb_corr")
ts_wb_Z = traits.Bool(argstr="-ts_wb_Z")
ts_wb_strlabel = traits.Bool(argstr="-ts_wb_strlabel")
nifti = traits.Bool(argstr="-nifti")
output_mask_nonnull = traits.Bool(argstr="-output_mask_nonnull")
push_thru_many_zeros = traits.Bool(argstr="-push_thru_many_zeros")
ignore_LT = traits.Bool(argstr="-ignore_LT")
out_file = File(
name_template="%s_netcorr",
desc="output file name part",
argstr="-prefix %s",
position=1,
name_source="in_file",
)

class NetCorrOutputSpec(TraitedSpec):
out_matrix = File(desc="output text file for correlation stats")

class NetCorr(AFNICommand):
"""Calculate correlation matrix of a set of ROIs (using mean time series of
each). Several networks may be analyzed simultaneously, one per brick.

For complete details, see the `3dTcorrMap Documentation.
<https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dNetCorr.html>`_

Examples
--------
>>> from nipype.interfaces import afni
>>> ncorr = afni.NetCorr()
>>> ncorr.inputs.in_file = 'functional.nii'
>>> ncorr.inputs.mask = 'mask.nii'
>>> ncorr.inputs.in_rois = 'rois.nii'
>>> ncorr.inputs.ts_wb_corr = True
>>> ncorr.inputs.ts_wb_Z = True
>>> ncorr.inputs.fish_z = True
>>> ncorr.inputs.prefix = 'sub0.tp1.ncorr'
>>> ncorr.cmdline # doctest: +SKIP
'3dNetCorr -prefix sub0.tp1.ncorr -inset functional.nii -mask mask.nii -in_rois rois.nii -ts_wb_corr -ts_wb_Z -fish_z'
>>> res = ncorr.run() # doctest: +SKIP

"""

_cmd = "3dNetCorr"
input_spec = NetCorrInputSpec
output_spec = NetCorrOutputSpec

def _list_outputs(self):
outputs = self.output_spec().get()

if not isdefined(self.inputs.out_file):
prefix = self._gen_fname(self.inputs.in_file, suffix="_netcorr")
else:
prefix = self.inputs.out_file

# All outputs should be in the same directory as the prefix
out_dir = os.path.dirname(os.path.abspath(prefix))

outputs["out_matrix"] = (
fname_presuffix(prefix, suffix="_000", use_ext=False, newpath=out_dir) + ".netcc"
)
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What is the output file called? I would expect, if I set netcorr.inputs.out_file, the output file is called exactly that.
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@effigies : the netcorr.inputs.out_file defines the prefix for the output.
Afni 3dNetCorr doesn't have actual output options, but it uses the prefix to write out the correlation matrix and correlation maps to the output directory.
This added function finds and returns the convention filename for the output correlation matrix.

I am also interested to return the correlation maps return to a subdirectory in the output directory. The number of these correlation maps depends on the number of regions in the input ROI label map. Do you have any idea how I can those to the output as well?
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@effigies : Thanks for the approval.
also, do you have any idea on this?
Please let me know if my question needs more clarification
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Ah, sorry, missed this. Assuming these files exist, you can use glob to get them. See an example here:

nipype/nipype/interfaces/fsl/model.py

Lines 459 to 490 in e9217c2

class FEAT(FSLCommand):
"""Uses FSL feat to calculate first level stats
"""
_cmd = "feat"
input_spec = FEATInputSpec
output_spec = FEATOutputSpec
def _list_outputs(self):
outputs = self._outputs().get()
is_ica = False
outputs["feat_dir"] = None
with open(self.inputs.fsf_file, "rt") as fp:
text = fp.read()
if "set fmri(inmelodic) 1" in text:
is_ica = True
for line in text.split("\n"):
if line.find("set fmri(outputdir)") > -1:
try:
outputdir_spec = line.split('"')[-2]
if os.path.exists(outputdir_spec):
outputs["feat_dir"] = outputdir_spec
except:
pass
if not outputs["feat_dir"]:
if is_ica:
outputs["feat_dir"] = glob(os.path.join(os.getcwd(), "*ica"))[0]
else:
outputs["feat_dir"] = glob(os.path.join(os.getcwd(), "*feat"))[0]
print("Outputs from FEATmodel:", outputs)
return outputs

Also, can you run make specs and commit the new file?
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Thanks! That was very helpful.
return outputs


class TCorrelateInputSpec(AFNICommandInputSpec):
xset = File(
desc="input xset",
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