doit_spm.py

from nipype.interfaces.spm.base import SPMCommand, SPMCommandInputSpec
from nipype.interfaces.base import (BaseInterface, TraitedSpec, traits, File,
                                    OutputMultiPath, BaseInterfaceInputSpec,
                                    isdefined, InputMultiPath)
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from nipype.interfaces.utility import IdentityInterface
import os
#from utils import doit_workflow


class DoitInputSpec(SPMCommandInputSpec):
    data_ref = traits.List(File(exists=True), field="doit.data_ref")
    bin_thresh = traits.Any(0.5, field="doit.bin_thresh", usedefault=True) #default is 0.5


class DoitOutputSpec(TraitedSpec):
    csv_file = OutputMultiPath(File(exists=True))


class Doit(SPMCommand):
    input_spec = DoitInputSpec
    output_spec = DoitOutputSpec
    _jobtype = 'tools'
    _jobname = 'LST'

    def _make_matlab_command(self, contents, postscript=None):
        len_ref = len(self.inputs.data_ref)

        contents = """
        %% Generated by nipype.interfaces.spm
        if isempty(which('spm')),
             throw(MException('SPMCheck:NotFound', 'SPM not in matlab path'));
        end
        [name, version] = spm('ver');
        fprintf('SPM version: %s Release: %s',name, version);
        fprintf('SPM path: %s', which('spm'));
        spm('Defaults','fMRI');

        if strcmp(name, 'SPM8') || strcmp(name(1:5), 'SPM12'),
           spm_jobman('initcfg');
           spm_get_defaults('cmdline', 1);
        end
        """

        contents += """
        jobs{1}.spm.tools.LST.doit.bin_thresh = %f;
        """ % self.inputs.bin_thresh

        for i, ref in enumerate(self.inputs.data_ref):
            contents += """
            jobs{1}.spm.tools.LST.doit.data_ref{%d, 1} = '%s';
        """ % (i+1,
               ref)

        contents += """
                    spm_jobman('run', jobs);
                    """
        return contents

    def _format_arg(self, opt, spec, val):
        """Convert input to appropriate format for spm
        """
        # import numpy as np
        # from nipype.utils.filemanip import copyfiles

        # if opt in ['t1_files', 'flair_files']:
        #    val2 = copyfiles(val, os.path.abspath("."))
        #    return np.array(val2, dtype=object)
        print("_format_arg opt is: ", opt)
        print("_format_arg opt is: ", spec)
        print("_format_arg opt is: ", val)

        # TODO change the format of data_ref

        return super(Doit, self)._format_arg(opt, spec, val)


    def _list_outputs(self):
        #from nipype.utils.filemanip import fname_presuffix
        from glob import glob
        from os.path import join
        outputs = self._outputs().get()
        print("Listing outputs!")
        print(os.path.abspath('.'))

        outputs["csv_file"] = glob(join(os.path.abspath('.'), "LST_doit_*.csv"))
        print(outputs)
        return outputs


if __name__ == '__main__':
    from glob import glob

    foo = Doit()
    print("The default value is: ", foo.inputs.bin_thresh)
    foo.inputs.data_ref = glob("/data/henry1/tristan/LST/FLAIR-MPRAGE/*/*_bin_lesion_map.nii")
    print("data_ref: ", foo.inputs.data_ref)

    foo.inputs.bin_thresh = 0.5
    print("The threshold is: ", foo.inputs.bin_thresh)
    foo.run()
    ## Make a workflow