How to use the clinica.utils.inputs.clinica_file_reader function in clinica

def build_input_node(self):
        """Build and connect an input node to the pipelines.
        """
        import nipype.interfaces.utility as nutil
        import nipype.pipeline.engine as npe
        from clinica.utils.inputs import clinica_file_reader
        from clinica.utils.stream import cprint
        from clinica.utils.dwi import check_dwi_volume
        from clinica.utils.exceptions import ClinicaBIDSError, ClinicaException
        import clinica.utils.input_files as input_files

        all_errors = []
        try:
            t1w_files = clinica_file_reader(self.subjects,
                                            self.sessions,
                                            self.bids_directory,
                                            input_files.T1W_NII)
        except ClinicaException as e:
            all_errors.append(e)
        try:
            dwi_files = clinica_file_reader(self.subjects,
                                            self.sessions,
                                            self.bids_directory,
                                            input_files.DWI_NII)
        except ClinicaException as e:
            all_errors.append(e)

        # bval files
        try:
            bval_files = clinica_file_reader(self.subjects,

+ self._group_id + '_template.nii*',
                                                   'description': 'T1w template file of group ' + self._group_id,
                                                   'needed_pipeline': 't1-volume or t1-volume-create-dartel'})
        except ClinicaException as e:
            all_errors.append(e)

        iterables_fwhm = self._fwhm
        if not self._apply_pvc:
            iterables_fwhm = [[]] * len(self.subjects)

        if self._apply_pvc:
            # pvc tissues input
            pvc_tissues_input = []
            for tissue_number in self.parameters['pvc_mask_tissues']:
                try:
                    current_file = clinica_file_reader(self.subjects,
                                                       self.sessions,
                                                       self.caps_directory,
                                                       {'pattern': 't1/spm/segmentation/native_space/*_*_T1w_segm-'
                                                                   + tissue_names[tissue_number]
                                                                   + '_probability.nii*',
                                                        'description': 'SPM based probability of ' + tissue_names[tissue_number]
                                                                       + ' based on T1w-MRI in native space',
                                                        'needed_pipeline': 't1-volume'})
                    pvc_tissues_input.append(current_file)
                except ClinicaException as e:
                    all_errors.append(e)

            if len(all_errors) == 0:
                pvc_tissues_input_final = []
                for subject_tissue_list in zip(*pvc_tissues_input):
                    pvc_tissues_input_final.append(subject_tissue_list)

from clinica.utils.stream import cprint

        all_errors = []

        # DWI
        try:
            dwi_bids = clinica_file_reader(self.subjects,
                                           self.sessions,
                                           self.bids_directory,
                                           input_files.DWI_NII)
        except ClinicaException as e:
            all_errors.append(e)

        # DWI json
        try:
            dwi_json = clinica_file_reader(self.subjects,
                                           self.sessions,
                                           self.bids_directory,
                                           input_files.DWI_JSON)

            # Create list_eff_echo_spacings and list_enc_directions
            list_eff_echo_spacings = []
            list_enc_directions = []
            for json in dwi_json:
                [eff_echo_spacing, enc_direction] = utils.parameters_from_dwi_metadata(json)
                list_eff_echo_spacings.append(eff_echo_spacing)
                list_enc_directions.append(enc_direction)

        except ClinicaException as e:
            all_errors.append(e)

        # bval files

input_files.DWI_PREPROC_NII)
        except ClinicaException as e:
            all_errors.append(e)

        # B0 brainmask
        try:
            dwi_brainmask_files = clinica_file_reader(self.subjects,
                                                      self.sessions,
                                                      self.caps_directory,
                                                      input_files.DWI_PREPROC_BRAINMASK)
        except ClinicaException as e:
            all_errors.append(e)

        # Preprocessed bvec
        try:
            bvec_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVEC)
        except ClinicaException as e:
            all_errors.append(e)

        # Preprocessed bval
        try:
            bval_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVAL)
        except ClinicaException as e:
            all_errors.append(e)

        if len(all_errors) > 0:

self.sessions,
                                                                             self.caps_directory,
                                                                             input_files.T1_FS_DESTRIEUX_PARC_L)
        except ClinicaException as e:
            all_errors.append(e)

        try:
            read_parameters_node.inputs.destrieux_right = clinica_file_reader(self.subjects,
                                                                              self.sessions,
                                                                              self.caps_directory,
                                                                              input_files.T1_FS_DESTRIEUX_PARC_R)
        except ClinicaException as e:
            all_errors.append(e)

        try:
            read_parameters_node.inputs.desikan_left = clinica_file_reader(self.subjects,
                                                                           self.sessions,
                                                                           self.caps_directory,
                                                                           input_files.T1_FS_DESIKAN_PARC_L)
        except ClinicaException as e:
            all_errors.append(e)

        try:
            read_parameters_node.inputs.desikan_right = clinica_file_reader(self.subjects,
                                                                            self.sessions,
                                                                            self.caps_directory,
                                                                            input_files.T1_FS_DESIKAN_PARC_R)
        except ClinicaException as e:
            all_errors.append(e)

        if len(all_errors) > 0:
            error_message = 'Clinica faced errors while trying to read files in your BIDS or CAPS directories.\n'

5: 'softtissue',
                        6: 'background'
                        }

        all_errors = []
        read_input_node = npe.Node(name="LoadingCLIArguments",
                                   interface=nutil.IdentityInterface(
                                       fields=self.get_input_fields(),
                                       mandatory_inputs=True))

        # Segmented Tissues
        # =================
        tissues_input = []
        for tissue_number in self.parameters['tissues']:
            try:
                current_file = clinica_file_reader(self.subjects,
                                                   self.sessions,
                                                   self.caps_directory,
                                                   {'pattern': 't1/spm/segmentation/native_space/*_*_T1w_segm-'
                                                               + tissue_names[tissue_number] + '_probability.nii*',
                                                    'description': 'SPM based probability of ' + tissue_names[tissue_number]
                                                                   + ' based on T1w-MRI in native space',
                                                    'needed_pipeline': 't1-volume-tissue-segmentation'})
                tissues_input.append(current_file)
            except ClinicaException as e:
                all_errors.append(e)
        # Tissues_input has a length of len(self.parameters['mask_tissues']). Each of these elements has a size of
        # len(self.subjects). We want the opposite : a list of size len(self.subjects) whose elements have a size of
        # len(self.parameters['mask_tissues']. The trick is to iter on elements with zip(*mylist)
        tissues_input_rearranged = []
        for subject_tissue_list in zip(*tissues_input):
            tissues_input_rearranged.append(subject_tissue_list)

from clinica.utils.inputs import clinica_file_reader
        from clinica.utils.stream import cprint
        from clinica.utils.dwi import check_dwi_volume
        from clinica.utils.exceptions import ClinicaBIDSError, ClinicaException
        import clinica.utils.input_files as input_files

        all_errors = []
        try:
            t1w_files = clinica_file_reader(self.subjects,
                                            self.sessions,
                                            self.bids_directory,
                                            input_files.T1W_NII)
        except ClinicaException as e:
            all_errors.append(e)
        try:
            dwi_files = clinica_file_reader(self.subjects,
                                            self.sessions,
                                            self.bids_directory,
                                            input_files.DWI_NII)
        except ClinicaException as e:
            all_errors.append(e)

        # bval files
        try:
            bval_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.bids_directory,
                                             input_files.DWI_BVAL)
        except ClinicaException as e:
            all_errors.append(e)

        # bvec files

input_files.DWI_PREPROC_BRAINMASK)
        except ClinicaException as e:
            all_errors.append(e)

        # Preprocessed bvec
        try:
            bvec_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVEC)
        except ClinicaException as e:
            all_errors.append(e)

        # Preprocessed bval
        try:
            bval_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVAL)
        except ClinicaException as e:
            all_errors.append(e)

        if len(all_errors) > 0:
            error_message = 'Clinica faced errors while trying to read files in your BIDS or CAPS directories.\n'
            for msg in all_errors:
                error_message += str(msg)
            raise ClinicaCAPSError(error_message)

        # Check space of DWI dataset
        dwi_file_spaces = [re.search('.*_space-(.*)_preproc.nii.*', file, re.IGNORECASE).group(1) for file in dwi_files]

        # Return an error if all the DWI files are not in the same space

input_files.DWI_PREPROC_BRAINMASK)
        except ClinicaException as e:
            all_errors.append(e)

        # DWI preprocessing NIfTI
        try:
            dwi_caps = clinica_file_reader(self.subjects,
                                           self.sessions,
                                           self.caps_directory,
                                           input_files.DWI_PREPROC_NII)
        except ClinicaException as e:
            all_errors.append(e)

        # bval files
        try:
            bval_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVAL)
        except ClinicaException as e:
            all_errors.append(e)

        # bvec files
        try:
            bvec_files = clinica_file_reader(self.subjects,
                                             self.sessions,
                                             self.caps_directory,
                                             input_files.DWI_PREPROC_BVEC)
        except ClinicaException as e:
            all_errors.append(e)

        if len(all_errors) > 0: