示例#1
0
    def convert_clinical_data(self, clinical_data_dir, bids_dir):
        """
        Convert the clinical data defined inside the clinical_specifications.xlx into BIDS

        Args:
            clinical_data_dir: path to the folder with the original clinical data
            bids_dir: path to the bids directory

        """
        import clinica.iotools.bids_utils as bids
        from os import path
        import os
        import numpy as np
        print('Converting clinical data...')
        bids_ids = bids.get_bids_subjs_list(bids_dir)

        iotools_folder = os.path.dirname(
            os.path.dirname(os.path.dirname(__file__)))
        clinic_specs_path = path.join(iotools_folder, 'data',
                                      'clinical_specifications.xlsx')

        # --Create participants.tsv--
        participants_df = bids.create_participants_df('OASIS',
                                                      clinic_specs_path,
                                                      clinical_data_dir,
                                                      bids_ids)

        # Replace the values of the diagnosis_bl column
        participants_df['diagnosis_bl'].replace([0.0, np.nan],
                                                'CN',
                                                inplace=True)
        participants_df['diagnosis_bl'].replace([0.5, 1.0, 1.5, 2.0],
                                                'AD',
                                                inplace=True)
        # Following line has no sense
        # participants_df['diagnosis_bl'].replace(participants_df['diagnosis_bl']>0.0, 'AD', inplace=True)
        participants_df.to_csv(path.join(bids_dir, 'participants.tsv'),
                               sep='\t',
                               index=False,
                               encoding='utf-8')

        # --Create sessions files--
        sessions_dict = bids.create_sessions_dict(clinical_data_dir, 'OASIS',
                                                  clinic_specs_path, bids_ids,
                                                  'ID')
        for y in bids_ids:
            if sessions_dict[y]['M00']['diagnosis'] > 0:
                sessions_dict[y]['M00']['diagnosis'] = 'AD'
            else:
                sessions_dict[y]['M00']['diagnosis'] = 'CN'

        bids.write_sessions_tsv(bids_dir, sessions_dict)

        # --Create scans files--
        # Note: We have no scans information for OASIS
        scans_dict = bids.create_scans_dict(clinical_data_dir, 'OASIS',
                                            clinic_specs_path, bids_ids, 'ID')
        bids.write_scans_tsv(bids_dir, bids_ids, scans_dict)
示例#2
0
    def convert_clinical_data(self,  clinical_data_dir, out_path):
        """
        Convert the clinical data of ADNI specified into the file clinical_specifications_adni.xlsx

        Args:
            clinical_data_dir:  path to the clinical data directory
            out_path: path to the BIDS directory

        """
        from os import path
        import os
        import pandas as pd
        import clinica.iotools.bids_utils as bids
        from clinica.utils.stream import cprint
        import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils

        clinic_specs_path = path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), 'data',
                                      'clinical_specifications_adni.xlsx')
        try:
            os.path.exists(out_path)
        except IOError:
            print('BIDS folder not found.')
            raise

        bids_ids = bids.get_bids_subjs_list(out_path)
        bids_subjs_paths = bids.get_bids_subjs_paths(out_path)

        if not bids_ids:
            adni_merge_path = path.join(clinical_data_dir, 'ADNIMERGE.csv')
            adni_merge = pd.io.parsers.read_csv(adni_merge_path, sep=',')
            bids_ids = ['sub-ADNI' + subj.replace('_', '') for subj in list(adni_merge.PTID.unique())]
            bids_subjs_paths = [path.join(out_path, subj) for subj in bids_ids]

        # -- Creation of participant.tsv --
        cprint("Creating participants.tsv...")
        participants_df = bids.create_participants_df('ADNI', clinic_specs_path, clinical_data_dir, bids_ids)

        # Replace the original values with the standard defined by the AramisTeam
        participants_df['sex'] = participants_df['sex'].replace('Male', 'M')
        participants_df['sex'] = participants_df['sex'].replace('Female', 'F')

        participants_df.to_csv(path.join(out_path, 'participants.tsv'), sep='\t', index=False, encoding='utf-8')

        # -- Creation of sessions.tsv --
        cprint("Creating sessions files...")
        adni_utils.create_adni_sessions_dict(bids_ids, clinic_specs_path, clinical_data_dir, bids_subjs_paths)

        # -- Creation of scans files --
        cprint('Creating scans files...')
        adni_utils.create_adni_scans_files(clinic_specs_path, bids_subjs_paths, bids_ids)
示例#3
0
    def convert_clinical_data(self, clinical_data_dir, bids_dir):
        """Convert the clinical data defined inside the clinical_specifications.xlx into BIDS.

        Args:
            clinical_data_dir: path to the folder with the original clinical data
            bids_dir: path to the BIDS directory
        """
        import os
        from os import path

        import numpy as np

        import clinica.iotools.bids_utils as bids
        from clinica.utils.stream import cprint

        cprint("Converting clinical data...")
        bids_ids = bids.get_bids_subjs_list(bids_dir)

        iotools_folder = os.path.dirname(
            os.path.dirname(os.path.dirname(__file__)))
        clinic_specs_path = path.join(iotools_folder, "data",
                                      "clinical_specifications")

        # -- Creation of modality agnostic files --
        bids.write_modality_agnostic_files("OASIS-1", bids_dir)

        # --Create participants.tsv--
        participants_df = bids.create_participants_df("OASIS",
                                                      clinic_specs_path,
                                                      clinical_data_dir,
                                                      bids_ids)

        # Replace the values of the diagnosis_bl column
        participants_df["diagnosis_bl"].replace([0.0, np.nan],
                                                "CN",
                                                inplace=True)
        participants_df["diagnosis_bl"].replace([0.5, 1.0, 1.5, 2.0],
                                                "AD",
                                                inplace=True)
        # Following line has no sense
        # participants_df['diagnosis_bl'].replace(participants_df['diagnosis_bl']>0.0, 'AD', inplace=True)
        participants_df = participants_df.fillna("n/a")
        participants_df.to_csv(
            path.join(bids_dir, "participants.tsv"),
            sep="\t",
            index=False,
            encoding="utf-8",
        )

        # --Create sessions files--
        sessions_dict = bids.create_sessions_dict_OASIS(
            clinical_data_dir, bids_dir, "OASIS", clinic_specs_path, bids_ids,
            "ID")
        for y in bids_ids:
            if sessions_dict[y]["M00"]["diagnosis"] > 0:
                sessions_dict[y]["M00"]["diagnosis"] = "AD"
            else:
                sessions_dict[y]["M00"]["diagnosis"] = "CN"

        bids.write_sessions_tsv(bids_dir, sessions_dict)

        # --Create scans files--
        # Note: We have no scans information for OASIS
        scans_dict = bids.create_scans_dict(
            clinical_data_dir,
            "OASIS",
            clinic_specs_path,
            bids_ids,
            "ID",
            "",
            sessions_dict,
        )
        bids.write_scans_tsv(bids_dir, bids_ids, scans_dict)
示例#4
0
    def convert_clinical_data(
        self,
        clinical_data_dir: str,
        out_path: str,
        clinical_data_only: bool = False,
        subjects_list_path: Optional[str] = None,
    ):
        """Convert the clinical data of ADNI specified into the file clinical_specifications_adni.xlsx.

        Args:
            clinical_data_dir:  path to the clinical data directory
            out_path: path to the BIDS directory
        """
        import os
        from os import path

        import clinica.iotools.bids_utils as bids
        import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
        from clinica.utils.stream import cprint

        clinic_specs_path = path.join(
            os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
            "data",
            "clinical_specifications_adni",
        )
        try:
            os.path.exists(out_path)
        except IOError:
            print("BIDS folder not found.")
            raise

        conversion_path = path.join(out_path, "conversion_info")

        if clinical_data_only:
            bids_ids, bids_subjs_paths = get_bids_subjs_info(
                clinical_data_dir=clinical_data_dir,
                out_path=out_path,
                subjects_list_path=subjects_list_path,
            )
        else:
            bids_ids = bids.get_bids_subjs_list(out_path)
            bids_subjs_paths = bids.get_bids_subjs_paths(out_path)

        # -- Creation of modality agnostic files --
        cprint("Creating modality agnostic files...")
        bids.write_modality_agnostic_files("ADNI", out_path)

        # -- Creation of participant.tsv --
        cprint("Creating participants.tsv...")
        participants_df = bids.create_participants_df(
            "ADNI", clinic_specs_path, clinical_data_dir, bids_ids
        )

        # Replace the original values with the standard defined by the AramisTeam
        participants_df["sex"] = participants_df["sex"].replace("Male", "M")
        participants_df["sex"] = participants_df["sex"].replace("Female", "F")

        # Correction of diagnosis_sc for ADNI3 participants
        participants_df = adni_utils.correct_diagnosis_sc_adni3(
            clinical_data_dir, participants_df
        )

        participants_df.to_csv(
            path.join(out_path, "participants.tsv"),
            sep="\t",
            index=False,
            encoding="utf-8",
        )

        # -- Creation of sessions.tsv --
        cprint("Creating sessions files...")
        adni_utils.create_adni_sessions_dict(
            bids_ids, clinic_specs_path, clinical_data_dir, bids_subjs_paths
        )

        # -- Creation of scans files --
        if os.path.exists(conversion_path):
            cprint("Creating scans files...")
            adni_utils.create_adni_scans_files(conversion_path, bids_subjs_paths)
示例#5
0
    def convert_clinical_data(self, clinical_data_dir, out_path):
        """Convert the clinical data of ADNI specified into the file clinical_specifications_adni.xlsx.

        Args:
            clinical_data_dir:  path to the clinical data directory
            out_path: path to the BIDS directory
        """
        import os
        from os import path

        import pandas as pd

        import clinica.iotools.bids_utils as bids
        import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
        from clinica.utils.stream import cprint

        clinic_specs_path = path.join(
            os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
            "data",
            "clinical_specifications_adni.xlsx",
        )
        try:
            os.path.exists(out_path)
        except IOError:
            print("BIDS folder not found.")
            raise

        bids_ids = bids.get_bids_subjs_list(out_path)
        bids_subjs_paths = bids.get_bids_subjs_paths(out_path)
        conversion_path = path.join(out_path, "conversion_info")

        if not bids_ids:
            adni_merge_path = path.join(clinical_data_dir, "ADNIMERGE.csv")
            adni_merge = pd.io.parsers.read_csv(adni_merge_path, sep=",")
            bids_ids = [
                "sub-ADNI" + subj.replace("_", "")
                for subj in list(adni_merge.PTID.unique())
            ]
            bids_subjs_paths = [path.join(out_path, subj) for subj in bids_ids]

        # -- Creation of modality agnostic files --
        cprint("Creating modality agnostic files...")
        bids.write_modality_agnostic_files("ADNI", out_path)

        # -- Creation of participant.tsv --
        cprint("Creating participants.tsv...")
        participants_df = bids.create_participants_df("ADNI",
                                                      clinic_specs_path,
                                                      clinical_data_dir,
                                                      bids_ids)

        # Replace the original values with the standard defined by the AramisTeam
        participants_df["sex"] = participants_df["sex"].replace("Male", "M")
        participants_df["sex"] = participants_df["sex"].replace("Female", "F")

        # Correction of diagnosis_sc for ADNI3 participants
        participants_df = adni_utils.correct_diagnosis_sc_adni3(
            clinical_data_dir, participants_df)

        participants_df.to_csv(
            path.join(out_path, "participants.tsv"),
            sep="\t",
            index=False,
            encoding="utf-8",
        )

        # -- Creation of sessions.tsv --
        cprint("Creating sessions files...")
        adni_utils.create_adni_sessions_dict(bids_ids, clinic_specs_path,
                                             clinical_data_dir,
                                             bids_subjs_paths)

        # -- Creation of scans files --
        cprint("Creating scans files...")
        adni_utils.create_adni_scans_files(
            conversion_path,
            bids_subjs_paths,
        )