more

Author: sappelhoff

examples/convert_eeg_to_bids.py

@@ -26,8 +26,8 @@
 
 # %%
 # We are importing everything we need for this example:
-import os.path as op
 import shutil
+from pathlib import Path
 
 import mne
 from mne.datasets import eegbci
@@ -66,8 +66,8 @@
 # of the directory tree.
 
 # get MNE directory with example data
-mne_data_dir = mne.get_config("MNE_DATASETS_EEGBCI_PATH")
-data_dir = op.join(mne_data_dir, "MNE-eegbci-data")
+mne_data_dir = Path(mne.get_config("MNE_DATASETS_EEGBCI_PATH"))
+data_dir = mne_data_dir / "MNE-eegbci-data"
 
 print_dir_tree(data_dir)
 
@@ -156,7 +156,7 @@
 
 # define a task name and a directory where to save the data to
 task = "RestEyesClosed"
-bids_root = op.join(mne_data_dir, "eegmmidb_bids_eeg_example")
+bids_root = mne_data_dir / "eegmmidb_bids_eeg_example"
 
 # %%
 # To ensure the output path doesn't contain any leftover files from previous
@@ -218,7 +218,7 @@
 #
 # If you are preparing a manuscript, please make sure to also cite MNE-BIDS
 # there.
-readme = op.join(bids_root, "README")
+readme = bids_root / "README"
 with open(readme, encoding="utf-8-sig") as fid:
     text = fid.read()
 print(text)

examples/convert_group_studies.py

@@ -17,8 +17,8 @@
 # %%
 # Let us import ``mne_bids``
 
-import os.path as op
 import shutil
+from pathlib import Path
 
 import mne
 from mne.datasets import eegbci
@@ -53,14 +53,15 @@
     eegbci.load_data(subjects=subject_id, runs=runs, update_path=True)
 
 # get path to MNE directory with the downloaded example data
-mne_data_dir = mne.get_config("MNE_DATASETS_EEGBCI_PATH")
-data_dir = op.join(mne_data_dir, "MNE-eegbci-data")
+data_dir = eegbci.data_path
+mne_data_dir = Path(mne.get_config("MNE_DATASETS_EEGBCI_PATH"))
+data_dir = mne_data_dir / "MNE-eegbci-data"
 
 # %%
 # Let us loop over the subjects and create BIDS-compatible folder
 
 # Make a path where we can save the data to
-bids_root = op.join(mne_data_dir, "eegmmidb_bids_group_conversion")
+bids_root = mne_data_dir / "eegmmidb_bids_group_conversion"
 
 # %%
 # To ensure the output path doesn't contain any leftover files from previous

examples/convert_nirs_to_bids.py

@@ -22,8 +22,6 @@
 
 # %%
 # We are importing everything we need for this example:
-import os.path as op
-import pathlib
 import shutil
 
 import mne
@@ -42,7 +40,7 @@
 # We will use the MNE-NIRS package which includes convenient functions to
 # download openly available datasets.
 
-data_dir = pathlib.Path(datasets.fnirs_motor_group.data_path())
+data_dir = datasets.fnirs_motor_group.data_path()
 
 # Let's see whether the data has been downloaded using a quick visualization
 # of the directory tree.
@@ -169,7 +167,7 @@
 #
 # If you are preparing a manuscript, please make sure to also cite MNE-BIDS
 # there.
-readme = op.join(bids_root, "README")
+readme = bids_root / "README"
 with open(readme, encoding="utf-8-sig") as fid:
     text = fid.read()
 print(text)

examples/mark_bad_channels.py

@@ -25,7 +25,6 @@
 # Let's start by importing the required modules and functions, reading the
 # "sample" data, and writing it in the BIDS format.
 
-import os.path as op
 import shutil
 
 import mne
@@ -39,8 +38,8 @@
 )
 
 data_path = mne.datasets.sample.data_path()
-raw_fname = op.join(data_path, "MEG", "sample", "sample_audvis_raw.fif")
-events_fname = op.join(data_path, "MEG", "sample", "sample_audvis_raw-eve.fif")
+raw_fname = data_path / "MEG" / "sample" / "sample_audvis_raw.fif"
+events_fname = data_path / "MEG" / "sample" / "sample_audvis_raw-eve.fif"
 event_id = {
     "Auditory/Left": 1,
     "Auditory/Right": 2,
@@ -49,7 +48,7 @@
     "Smiley": 5,
     "Button": 32,
 }
-bids_root = op.join(data_path, "..", "MNE-sample-data-bids")
+bids_root = data_path.parent / "MNE-sample-data-bids"
 bids_path = BIDSPath(
     subject="01", session="01", task="audiovisual", run="01", root=bids_root
 )

examples/read_bids_datasets.py

@@ -31,8 +31,6 @@
 # Imports
 # -------
 # We are importing everything we need for this example:
-import os
-import os.path as op
 
 import openneuro
 from mne.datasets import sample
@@ -65,9 +63,8 @@
 subject = "pd6"
 
 # Download one subject's data from each dataset
-bids_root = op.join(op.dirname(sample.data_path()), dataset)
-if not op.isdir(bids_root):
-    os.makedirs(bids_root)
+bids_root = sample.data_path().parent / dataset
+bids_root.mkdir(parents=True, exist_ok=True)
 
 openneuro.download(dataset=dataset, target_dir=bids_root, include=[f"sub-{subject}"])
 

examples/rename_brainvision_files.py

@@ -34,8 +34,6 @@
 
 # %%
 # We are importing everything we need for this example:
-import os.path as op
-
 import mne
 
 from mne_bids.copyfiles import copyfile_brainvision
@@ -50,7 +48,7 @@
 # .. warning:: This will download 1.6 GB of data!
 
 data_path = mne.datasets.testing.data_path()
-examples_dir = op.join(data_path, "Brainvision")
+examples_dir = data_path / "Brainvision"
 
 # %%
 # Rename the recording
@@ -72,8 +70,8 @@
 # Here, we rename a test file name:
 
 # Rename the file
-vhdr_file = op.join(examples_dir, "Analyzer_nV_Export.vhdr")
-vhdr_file_renamed = op.join(examples_dir, "test_renamed.vhdr")
+vhdr_file = examples_dir / "Analyzer_nV_Export.vhdr"
+vhdr_file_renamed = examples_dir / "test_renamed.vhdr"
 copyfile_brainvision(vhdr_file, vhdr_file_renamed, verbose=True)
 
 # Check that MNE-Python can read in both, the original as well as the renamed

mne_bids/dig.py

@@ -4,7 +4,6 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 import json
-import os.path as op
 import re
 import warnings
 from collections import OrderedDict
@@ -722,8 +721,8 @@ def convert_montage_to_ras(montage, subject, subjects_dir=None, verbose=None):
     nib = _import_nibabel("converting a montage to RAS")
 
     subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
-    T1_fname = op.join(subjects_dir, subject, "mri", "T1.mgz")
-    if not op.isfile(T1_fname):
+    T1_fname = subjects_dir / subject / "mri" / "T1.mgz"
+    if not T1_fname.is_file():
         raise RuntimeError(
             f"Freesurfer subject ({subject}) and/or "
             f"subjects_dir ({subjects_dir}, incorrectly "
@@ -767,8 +766,8 @@ def convert_montage_to_mri(montage, subject, subjects_dir=None, verbose=None):
     nib = _import_nibabel("converting a montage to MRI")
 
     subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
-    T1_fname = op.join(subjects_dir, subject, "mri", "T1.mgz")
-    if not op.isfile(T1_fname):
+    T1_fname = subjects_dir / subject / "mri" / "T1.mgz"
+    if not T1_fname.is_file():
         raise RuntimeError(
             f"Freesurfer subject ({subject}) and/or "
             f"subjects_dir ({subjects_dir}, incorrectly "

mne_bids/read.py

@@ -5,7 +5,6 @@
 
 import json
 import os
-import os.path as op
 import re
 from datetime import datetime, timedelta, timezone
 from difflib import get_close_matches
@@ -985,7 +984,7 @@ def read_raw_bids(
     # read in associated subject info from participants.tsv
     participants_tsv_path = bids_root / "participants.tsv"
     subject = f"sub-{bids_path.subject}"
-    if op.exists(participants_tsv_path):
+    if participants_tsv_path.exists():
         raw = _handle_participants_reading(
             participants_fname=participants_tsv_path, raw=raw, subject=subject
         )
@@ -1180,7 +1179,7 @@ def get_head_mri_trans(
         fs_subject = f"sub-{meg_bids_path.subject}"
 
     fs_subjects_dir = get_subjects_dir(fs_subjects_dir, raise_error=False)
-    fs_t1_path = Path(fs_subjects_dir) / fs_subject / "mri" / "T1.mgz"
+    fs_t1_path = fs_subjects_dir / fs_subject / "mri" / "T1.mgz"
     if not fs_t1_path.exists():
         raise ValueError(
             f"Could not find {fs_t1_path}. Consider running FreeSurfer's "

mne_bids/report/_report.py

@@ -4,7 +4,6 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 import json
-import os.path as op
 import textwrap
 from pathlib import Path
 
@@ -151,8 +150,8 @@ def _summarize_dataset(root):
     template_dict : dict
         A dictionary of values for various template strings.
     """
-    dataset_descrip_fpath = op.join(root, "dataset_description.json")
-    if not op.exists(dataset_descrip_fpath):
+    dataset_descrip_fpath = root / "dataset_description.json"
+    if not dataset_descrip_fpath.exists():
         return dict()
 
     # read file and 'REQUIRED' components of it
@@ -186,8 +185,8 @@ def _summarize_participants_tsv(root):
     template_dict : dict
         A dictionary of values for various template strings.
     """
-    participants_tsv_fpath = op.join(root, "participants.tsv")
-    if not op.exists(participants_tsv_fpath):
+    participants_tsv_fpath = root / "participants.tsv"
+    if not participants_tsv_fpath.exists():
         return dict()
 
     participants_tsv = _from_tsv(str(participants_tsv_fpath))
@@ -312,7 +311,7 @@ def _summarize_sidecar_json(root, scans_fpaths):
         for scan in scans:
             # summarize metadata of recordings
             bids_path, ext = _parse_ext(scan)
-            datatype = op.dirname(scan)
+            datatype = scan.parent
             if datatype not in ALLOWED_DATATYPES:
                 continue
 
@@ -400,7 +399,7 @@ def _summarize_channels_tsv(root, scans_fpaths):
         for scan in scans:
             # summarize metadata of recordings
             bids_path, _ = _parse_ext(scan)
-            datatype = op.dirname(scan)
+            datatype = scan.parent
             if datatype not in ["meg", "eeg", "ieeg"]:
                 continue
 
@@ -465,6 +464,8 @@ def make_report(root, session=None, verbose=None):
         The paragraph wrapped with 80 characters per line
         describing the summary of the subjects.
     """
+    root = Path(root)
+
     # high level summary
     subjects = get_entity_vals(root, entity_key="subject")
     sessions = get_entity_vals(root, entity_key="session")

mne_bids/tests/test_inspect.py

@@ -3,8 +3,6 @@
 # Authors: The MNE-BIDS developers
 # SPDX-License-Identifier: BSD-3-Clause
 
-import os.path as op
-
 import mne
 import numpy as np
 import pytest
@@ -32,7 +30,7 @@
 
 def setup_bids_test_dir(bids_root):
     """Return path to a written test BIDS dir."""
-    raw_fname = op.join(data_path, "MEG", "sample", "sample_audvis_trunc_raw.fif")
+    raw_fname = data_path / "MEG" / "sample" / "sample_audvis_trunc_raw.fif"
 
     event_id = {
         "Auditory/Left": 1,
@@ -42,11 +40,9 @@ def setup_bids_test_dir(bids_root):
         "Smiley": 5,
         "Button": 32,
     }
-    events_fname = op.join(
-        data_path, "MEG", "sample", "sample_audvis_trunc_raw-eve.fif"
-    )
-    cal_fname = op.join(data_path, "SSS", "sss_cal_mgh.dat")
-    crosstalk_fname = op.join(data_path, "SSS", "ct_sparse.fif")
+    events_fname = data_path / "MEG" / "sample" / "sample_audvis_trunc_raw-eve.fif"
+    cal_fname = data_path / "SSS" / "sss_cal_mgh.dat"
+    crosstalk_fname = data_path / "SSS" / "ct_sparse.fif"
 
     raw = mne.io.read_raw_fif(raw_fname)
     raw.info["line_freq"] = 60