path handling intro folder (#10893)

Author: ashdrew

tutorials/intro/10_overview.py

@@ -17,7 +17,6 @@
 """
 # %%
 
-import os
 import numpy as np
 import mne
 
@@ -45,8 +44,8 @@
 # could be substituted here when running the tutorial locally.
 
 sample_data_folder = mne.datasets.sample.data_path()
-sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
-                                    'sample_audvis_filt-0-40_raw.fif')
+sample_data_raw_file = (sample_data_folder / 'MEG' / 'sample' /
+                        'sample_audvis_filt-0-40_raw.fif')
 raw = mne.io.read_raw_fif(sample_data_raw_file)
 
 # %%
@@ -339,8 +338,8 @@
 # baseline activity level across all of cortex).
 
 # load inverse operator
-inverse_operator_file = os.path.join(sample_data_folder, 'MEG', 'sample',
-                                     'sample_audvis-meg-oct-6-meg-inv.fif')
+inverse_operator_file = (sample_data_folder / 'MEG' / 'sample' /
+                         'sample_audvis-meg-oct-6-meg-inv.fif')
 inv_operator = mne.minimum_norm.read_inverse_operator(inverse_operator_file)
 # set signal-to-noise ratio (SNR) to compute regularization parameter (λ²)
 snr = 3.
@@ -356,7 +355,7 @@
 # (the ``subjects_dir``):
 
 # path to subjects' MRI files
-subjects_dir = os.path.join(sample_data_folder, 'subjects')
+subjects_dir = sample_data_folder / 'subjects'
 # plot the STC
 stc.plot(initial_time=0.1, hemi='split', views=['lat', 'med'],
          subjects_dir=subjects_dir)

tutorials/intro/15_inplace.py

@@ -20,12 +20,11 @@
 
 # %%
 
-import os
 import mne
 
 sample_data_folder = mne.datasets.sample.data_path()
-sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
-                                    'sample_audvis_raw.fif')
+sample_data_raw_file = (sample_data_folder / 'MEG' / 'sample' /
+                        'sample_audvis_raw.fif')
 # the preload flag loads the data into memory now
 raw = mne.io.read_raw_fif(sample_data_raw_file, preload=True)
 raw.crop(tmax=10.)  # raw.crop() always happens in-place

tutorials/intro/20_events_from_raw.py

@@ -29,13 +29,12 @@
 
 # %%
 
-import os
 import numpy as np
 import mne
 
 sample_data_folder = mne.datasets.sample.data_path()
-sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
-                                    'sample_audvis_raw.fif')
+sample_data_raw_file = (sample_data_folder / 'MEG' / 'sample' /
+                        'sample_audvis_raw.fif')
 raw = mne.io.read_raw_fif(sample_data_raw_file)
 raw.crop(tmax=60).load_data()
 
@@ -162,7 +161,7 @@
 # :attr:`~mne.io.Raw.annotations` attribute of the `~mne.io.Raw` object:
 
 testing_data_folder = mne.datasets.testing.data_path()
-eeglab_raw_file = os.path.join(testing_data_folder, 'EEGLAB', 'test_raw.set')
+eeglab_raw_file = testing_data_folder / 'EEGLAB' / 'test_raw.set'
 eeglab_raw = mne.io.read_raw_eeglab(eeglab_raw_file)
 print(eeglab_raw.annotations)
 

tutorials/intro/30_info.py

@@ -17,12 +17,11 @@
 
 # %%
 
-import os
 import mne
 
 sample_data_folder = mne.datasets.sample.data_path()
-sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
-                                    'sample_audvis_filt-0-40_raw.fif')
+sample_data_raw_file = (sample_data_folder / 'MEG' / 'sample' /
+                        'sample_audvis_filt-0-40_raw.fif')
 raw = mne.io.read_raw_fif(sample_data_raw_file)
 
 # %%