doc updates [skip ci]

dev/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: cdc81cce15090a1726205caf1398f763
+config: a45f11a6cfb1de791052d41fb2dfb979
 tags: 645f666f9bcd5a90fca523b33c5a78b7

dev/_downloads/07841a9269d1816a3add41f32d8a5ed2/read_bids_datasets.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os\nimport os.path as op\nimport openneuro\n\nfrom mne.datasets import sample\nfrom mne_bids import (\n    BIDSPath,\n    read_raw_bids,\n    print_dir_tree,\n    make_report,\n    find_matching_paths,\n    get_entity_vals,\n)"
+        "import os\nimport os.path as op\n\nimport openneuro\nfrom mne.datasets import sample\n\nfrom mne_bids import (\n    BIDSPath,\n    find_matching_paths,\n    get_entity_vals,\n    make_report,\n    print_dir_tree,\n    read_raw_bids,\n)"
       ]
     },
     {

dev/_downloads/0bc5481d861907f3ba86dd37d953b980/convert_eeg_to_bids.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os.path as op\nimport shutil\n\nimport mne\nfrom mne.datasets import eegbci\n\nfrom mne_bids import write_raw_bids, BIDSPath, print_dir_tree\nfrom mne_bids.stats import count_events"
+        "import os.path as op\nimport shutil\n\nimport mne\nfrom mne.datasets import eegbci\n\nfrom mne_bids import BIDSPath, print_dir_tree, write_raw_bids\nfrom mne_bids.stats import count_events"
       ]
     },
     {
@@ -256,7 +256,7 @@
       },
       "outputs": [],
       "source": [
-        "readme = op.join(bids_root, \"README\")\nwith open(readme, \"r\", encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
+        "readme = op.join(bids_root, \"README\")\nwith open(readme, encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
       ]
     },
     {

dev/_downloads/1eed244ec75de0e6a9392a728e24219b/convert_group_studies.py

@@ -26,11 +26,11 @@
 from mne.datasets import eegbci
 
 from mne_bids import (
-    write_raw_bids,
     BIDSPath,
     get_anonymization_daysback,
     make_report,
     print_dir_tree,
+    write_raw_bids,
 )
 from mne_bids.stats import count_events
 

dev/_downloads/241c30601b8e062b34a8b85829a39a45/convert_group_studies.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os.path as op\nimport shutil\n\nimport mne\nfrom mne.datasets import eegbci\n\nfrom mne_bids import (\n    write_raw_bids,\n    BIDSPath,\n    get_anonymization_daysback,\n    make_report,\n    print_dir_tree,\n)\nfrom mne_bids.stats import count_events"
+        "import os.path as op\nimport shutil\n\nimport mne\nfrom mne.datasets import eegbci\n\nfrom mne_bids import (\n    BIDSPath,\n    get_anonymization_daysback,\n    make_report,\n    print_dir_tree,\n    write_raw_bids,\n)\nfrom mne_bids.stats import count_events"
       ]
     },
     {

dev/_downloads/3556547a51e51e9556bdd40badb8d4c8/mark_bad_channels.py

@@ -30,12 +30,13 @@
 import shutil
 
 import mne
+
 from mne_bids import (
     BIDSPath,
-    write_raw_bids,
-    read_raw_bids,
     inspect_dataset,
     mark_channels,
+    read_raw_bids,
+    write_raw_bids,
 )
 
 data_path = mne.datasets.sample.data_path()

dev/_downloads/529f3230e5683b7676557bd33b2ea01b/convert_mne_sample.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import json\nimport os.path as op\nfrom pprint import pprint\nimport shutil\n\nimport mne\nfrom mne.datasets import sample\n\nfrom mne_bids import (\n    write_raw_bids,\n    read_raw_bids,\n    write_meg_calibration,\n    write_meg_crosstalk,\n    BIDSPath,\n    print_dir_tree,\n    make_dataset_description,\n)\nfrom mne_bids.stats import count_events"
+        "import json\nimport os.path as op\nimport shutil\nfrom pprint import pprint\n\nimport mne\nfrom mne.datasets import sample\n\nfrom mne_bids import (\n    BIDSPath,\n    make_dataset_description,\n    print_dir_tree,\n    read_raw_bids,\n    write_meg_calibration,\n    write_meg_crosstalk,\n    write_raw_bids,\n)\nfrom mne_bids.stats import count_events"
       ]
     },
     {
@@ -249,7 +249,7 @@
       },
       "outputs": [],
       "source": [
-        "readme = op.join(output_path, \"README\")\nwith open(readme, \"r\", encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
+        "readme = op.join(output_path, \"README\")\nwith open(readme, encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
       ]
     },
     {
@@ -267,7 +267,7 @@
       },
       "outputs": [],
       "source": [
-        "how_to_acknowledge = \"\"\"\\\nIf you reference this dataset in a publication, please acknowledge its \\\nauthors and cite MNE papers: A. Gramfort, M. Luessi, E. Larson, D. Engemann, \\\nD. Strohmeier, C. Brodbeck, L. Parkkonen, M. H\u00e4m\u00e4l\u00e4inen, \\\nMNE software for processing MEG and EEG data, NeuroImage, Volume 86, \\\n1 February 2014, Pages 446-460, ISSN 1053-8119 \\\nand \\\nA. Gramfort, M. Luessi, E. Larson, D. Engemann, D. Strohmeier, C. Brodbeck, \\\nR. Goj, M. Jas, T. Brooks, L. Parkkonen, M. H\u00e4m\u00e4l\u00e4inen, MEG and EEG data \\\nanalysis with MNE-Python, Frontiers in Neuroscience, Volume 7, 2013, \\\nISSN 1662-453X\"\"\"\n\nmake_dataset_description(\n    path=bids_path.root,\n    name=task,\n    authors=[\"Alexandre Gramfort\", \"Matti H\u00e4m\u00e4l\u00e4inen\"],\n    how_to_acknowledge=how_to_acknowledge,\n    acknowledgements=\"\"\"\\\nAlexandre Gramfort, Mainak Jas, and Stefan Appelhoff prepared and updated the \\\ndata in BIDS format.\"\"\",\n    data_license=\"CC0\",\n    ethics_approvals=[\n        \"Human Subjects Division at the University of Washington\"\n    ],  # noqa: E501\n    funding=[\n        \"NIH 5R01EB009048\",\n        \"NIH 1R01EB009048\",\n        \"NIH R01EB006385\",\n        \"NIH 1R01HD40712\",\n        \"NIH 1R01NS44319\",\n        \"NIH 2R01NS37462\",\n        \"NIH P41EB015896\",\n        \"ANR-11-IDEX-0003-02\",\n        \"ERC-StG-263584\",\n        \"ERC-StG-676943\",\n        \"ANR-14-NEUC-0002-01\",\n    ],\n    references_and_links=[\n        \"https://doi.org/10.1016/j.neuroimage.2014.02.017\",\n        \"https://doi.org/10.3389/fnins.2013.00267\",\n        \"https://mne.tools/stable/documentation/datasets.html#sample\",\n    ],\n    doi=\"doi:10.18112/openneuro.ds000248.v1.2.4\",\n    overwrite=True,\n)\ndesc_json_path = bids_path.root / \"dataset_description.json\"\nwith open(desc_json_path, \"r\", encoding=\"utf-8-sig\") as fid:\n    pprint(json.loads(fid.read()))"
+        "how_to_acknowledge = \"\"\"\\\nIf you reference this dataset in a publication, please acknowledge its \\\nauthors and cite MNE papers: A. Gramfort, M. Luessi, E. Larson, D. Engemann, \\\nD. Strohmeier, C. Brodbeck, L. Parkkonen, M. H\u00e4m\u00e4l\u00e4inen, \\\nMNE software for processing MEG and EEG data, NeuroImage, Volume 86, \\\n1 February 2014, Pages 446-460, ISSN 1053-8119 \\\nand \\\nA. Gramfort, M. Luessi, E. Larson, D. Engemann, D. Strohmeier, C. Brodbeck, \\\nR. Goj, M. Jas, T. Brooks, L. Parkkonen, M. H\u00e4m\u00e4l\u00e4inen, MEG and EEG data \\\nanalysis with MNE-Python, Frontiers in Neuroscience, Volume 7, 2013, \\\nISSN 1662-453X\"\"\"\n\nmake_dataset_description(\n    path=bids_path.root,\n    name=task,\n    authors=[\"Alexandre Gramfort\", \"Matti H\u00e4m\u00e4l\u00e4inen\"],\n    how_to_acknowledge=how_to_acknowledge,\n    acknowledgements=\"\"\"\\\nAlexandre Gramfort, Mainak Jas, and Stefan Appelhoff prepared and updated the \\\ndata in BIDS format.\"\"\",\n    data_license=\"CC0\",\n    ethics_approvals=[\"Human Subjects Division at the University of Washington\"],\n    funding=[\n        \"NIH 5R01EB009048\",\n        \"NIH 1R01EB009048\",\n        \"NIH R01EB006385\",\n        \"NIH 1R01HD40712\",\n        \"NIH 1R01NS44319\",\n        \"NIH 2R01NS37462\",\n        \"NIH P41EB015896\",\n        \"ANR-11-IDEX-0003-02\",\n        \"ERC-StG-263584\",\n        \"ERC-StG-676943\",\n        \"ANR-14-NEUC-0002-01\",\n    ],\n    references_and_links=[\n        \"https://doi.org/10.1016/j.neuroimage.2014.02.017\",\n        \"https://doi.org/10.3389/fnins.2013.00267\",\n        \"https://mne.tools/stable/documentation/datasets.html#sample\",\n    ],\n    doi=\"doi:10.18112/openneuro.ds000248.v1.2.4\",\n    overwrite=True,\n)\ndesc_json_path = bids_path.root / \"dataset_description.json\"\nwith open(desc_json_path, encoding=\"utf-8-sig\") as fid:\n    pprint(json.loads(fid.read()))"
       ]
     },
     {

dev/_downloads/58cece9c8037ffebaaad2703d5ce7839/convert_empty_room.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os.path as op\nimport shutil\n\nfrom datetime import datetime, timezone\n\nimport mne\nfrom mne.datasets import sample\n\nfrom mne_bids import write_raw_bids, read_raw_bids, BIDSPath, print_dir_tree"
+        "import os.path as op\nimport shutil\nfrom datetime import datetime, timezone\n\nimport mne\nfrom mne.datasets import sample\n\nfrom mne_bids import BIDSPath, print_dir_tree, read_raw_bids, write_raw_bids"
       ]
     },
     {

dev/_downloads/5eebd75ee4f8ffd30e34a83e87d0e28b/read_bids_datasets.py

@@ -36,16 +36,17 @@
 # We are importing everything we need for this example:
 import os
 import os.path as op
-import openneuro
 
+import openneuro
 from mne.datasets import sample
+
 from mne_bids import (
     BIDSPath,
-    read_raw_bids,
-    print_dir_tree,
-    make_report,
     find_matching_paths,
     get_entity_vals,
+    make_report,
+    print_dir_tree,
+    read_raw_bids,
 )
 
 # %%

dev/_downloads/6a10915cde9ea548655ec1feef4a85d1/update_bids_datasets.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "from mne.datasets import somato\n\nfrom mne_bids import (\n    read_raw_bids,\n    find_matching_paths,\n    print_dir_tree,\n    make_report,\n    update_sidecar_json,\n)"
+        "from mne.datasets import somato\n\nfrom mne_bids import (\n    find_matching_paths,\n    make_report,\n    print_dir_tree,\n    read_raw_bids,\n    update_sidecar_json,\n)"
       ]
     },
     {

dev/_downloads/6a8efa177441ca0b84ef1b16e3806949/anonymize_dataset.ipynb

@@ -26,7 +26,7 @@
       },
       "outputs": [],
       "source": [
-        "import shutil\nfrom pathlib import Path\nimport mne\nfrom mne_bids import (\n    BIDSPath,\n    write_raw_bids,\n    write_anat,\n    write_meg_calibration,\n    write_meg_crosstalk,\n    anonymize_dataset,\n    print_dir_tree,\n)\n\ndata_path = Path(mne.datasets.sample.data_path())\nevent_id = {\n    \"Auditory/Left\": 1,\n    \"Auditory/Right\": 2,\n    \"Visual/Left\": 3,\n    \"Visual/Right\": 4,\n    \"Smiley\": 5,\n    \"Button\": 32,\n}\n\nraw_path = data_path / \"MEG\" / \"sample\" / \"sample_audvis_raw.fif\"\nraw_er_path = data_path / \"MEG\" / \"sample\" / \"ernoise_raw.fif\"  # empty-room\nevents_path = data_path / \"MEG\" / \"sample\" / \"sample_audvis_raw-eve.fif\"\ncal_path = data_path / \"SSS\" / \"sss_cal_mgh.dat\"\nct_path = data_path / \"SSS\" / \"ct_sparse_mgh.fif\"\nt1w_path = data_path / \"subjects\" / \"sample\" / \"mri\" / \"T1.mgz\"\n\nbids_root = data_path.parent / \"MNE-sample-data-bids\"\nbids_root_anon = data_path.parent / \"MNE-sample-data-bids-anon\""
+        "import shutil\nfrom pathlib import Path\n\nimport mne\n\nfrom mne_bids import (\n    BIDSPath,\n    anonymize_dataset,\n    print_dir_tree,\n    write_anat,\n    write_meg_calibration,\n    write_meg_crosstalk,\n    write_raw_bids,\n)\n\ndata_path = Path(mne.datasets.sample.data_path())\nevent_id = {\n    \"Auditory/Left\": 1,\n    \"Auditory/Right\": 2,\n    \"Visual/Left\": 3,\n    \"Visual/Right\": 4,\n    \"Smiley\": 5,\n    \"Button\": 32,\n}\n\nraw_path = data_path / \"MEG\" / \"sample\" / \"sample_audvis_raw.fif\"\nraw_er_path = data_path / \"MEG\" / \"sample\" / \"ernoise_raw.fif\"  # empty-room\nevents_path = data_path / \"MEG\" / \"sample\" / \"sample_audvis_raw-eve.fif\"\ncal_path = data_path / \"SSS\" / \"sss_cal_mgh.dat\"\nct_path = data_path / \"SSS\" / \"ct_sparse_mgh.fif\"\nt1w_path = data_path / \"subjects\" / \"sample\" / \"mri\" / \"T1.mgz\"\n\nbids_root = data_path.parent / \"MNE-sample-data-bids\"\nbids_root_anon = data_path.parent / \"MNE-sample-data-bids-anon\""
       ]
     },
     {

dev/_downloads/86851480108d4b249520df3993b0222b/convert_mne_sample.py

@@ -29,20 +29,20 @@
 
 import json
 import os.path as op
-from pprint import pprint
 import shutil
+from pprint import pprint
 
 import mne
 from mne.datasets import sample
 
 from mne_bids import (
-    write_raw_bids,
+    BIDSPath,
+    make_dataset_description,
+    print_dir_tree,
     read_raw_bids,
     write_meg_calibration,
     write_meg_crosstalk,
-    BIDSPath,
-    print_dir_tree,
-    make_dataset_description,
+    write_raw_bids,
 )
 from mne_bids.stats import count_events
 
@@ -180,7 +180,7 @@
 # for mne-bids. If you are preparing a manuscript, please make sure to also
 # cite MNE-BIDS there.
 readme = op.join(output_path, "README")
-with open(readme, "r", encoding="utf-8-sig") as fid:
+with open(readme, encoding="utf-8-sig") as fid:
     text = fid.read()
 print(text)
 
@@ -209,9 +209,7 @@
 Alexandre Gramfort, Mainak Jas, and Stefan Appelhoff prepared and updated the \
 data in BIDS format.""",
     data_license="CC0",
-    ethics_approvals=[
-        "Human Subjects Division at the University of Washington"
-    ],  # noqa: E501
+    ethics_approvals=["Human Subjects Division at the University of Washington"],
     funding=[
         "NIH 5R01EB009048",
         "NIH 1R01EB009048",
@@ -234,7 +232,7 @@
     overwrite=True,
 )
 desc_json_path = bids_path.root / "dataset_description.json"
-with open(desc_json_path, "r", encoding="utf-8-sig") as fid:
+with open(desc_json_path, encoding="utf-8-sig") as fid:
     pprint(json.loads(fid.read()))
 
 # %%

dev/_downloads/8a652dc37d1d38cf986f15eab46d0f7d/update_bids_datasets.py

@@ -22,10 +22,10 @@
 from mne.datasets import somato
 
 from mne_bids import (
-    read_raw_bids,
     find_matching_paths,
-    print_dir_tree,
     make_report,
+    print_dir_tree,
+    read_raw_bids,
     update_sidecar_json,
 )
 

dev/_downloads/9160181635ad137cb4a8a5779295596c/convert_mri_and_trans.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os.path as op\nimport shutil\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom nilearn.plotting import plot_anat\n\nimport mne\nfrom mne.datasets import sample\nfrom mne import head_to_mri\n\nfrom mne_bids import (\n    write_raw_bids,\n    BIDSPath,\n    write_anat,\n    get_anat_landmarks,\n    get_head_mri_trans,\n    print_dir_tree,\n)"
+        "import os.path as op\nimport shutil\n\nimport matplotlib.pyplot as plt\nimport mne\nimport numpy as np\nfrom mne import head_to_mri\nfrom mne.datasets import sample\nfrom nilearn.plotting import plot_anat\n\nfrom mne_bids import (\n    BIDSPath,\n    get_anat_landmarks,\n    get_head_mri_trans,\n    print_dir_tree,\n    write_anat,\n    write_raw_bids,\n)"
       ]
     },
     {

dev/_downloads/9e546b1b08e67ca7572c8e76f5992643/convert_nirs_to_bids.py

@@ -31,7 +31,7 @@
 import mne
 from mne_nirs import datasets  # For convenient downloading of example data
 
-from mne_bids import write_raw_bids, BIDSPath, print_dir_tree
+from mne_bids import BIDSPath, print_dir_tree, write_raw_bids
 from mne_bids.stats import count_events
 
 # %%
@@ -172,7 +172,7 @@
 # If you are preparing a manuscript, please make sure to also cite MNE-BIDS
 # there.
 readme = op.join(bids_root, "README")
-with open(readme, "r", encoding="utf-8-sig") as fid:
+with open(readme, encoding="utf-8-sig") as fid:
     text = fid.read()
 print(text)
 

dev/_downloads/a577037ece7a732b0607a269316e55b8/convert_ieeg_to_bids.py

@@ -50,24 +50,24 @@
 # %%
 
 import os.path as op
-import numpy as np
 import shutil
 
+import mne
 import nibabel as nib
+import numpy as np
 from nilearn.plotting import plot_anat
 
-import mne
 from mne_bids import (
     BIDSPath,
-    write_raw_bids,
-    write_anat,
+    convert_montage_to_mri,
+    convert_montage_to_ras,
     get_anat_landmarks,
+    print_dir_tree,
     read_raw_bids,
     search_folder_for_text,
-    print_dir_tree,
     template_to_head,
-    convert_montage_to_ras,
-    convert_montage_to_mri,
+    write_anat,
+    write_raw_bids,
 )
 
 # %%
@@ -289,11 +289,8 @@
 
 # compare with standard
 print(
-    "Recovered coordinate: {recovered}\n"
-    "Saved coordinate:     {saved}".format(
-        recovered=montage2.get_positions()["ch_pos"]["LENT 1"],
-        saved=montage.get_positions()["ch_pos"]["LENT 1"],
-    )
+    f"Recovered coordinate: {montage2.get_positions()['ch_pos']['LENT 1']}\n"
+    f"Saved coordinate: {montage.get_positions()['ch_pos']['LENT 1']}"
 )
 
 # %%
@@ -303,7 +300,7 @@
 # If you are preparing a manuscript, please make sure to also cite MNE-BIDS
 # there.
 readme = op.join(bids_root, "README")
-with open(readme, "r", encoding="utf-8-sig") as fid:
+with open(readme, encoding="utf-8-sig") as fid:
     text = fid.read()
 print(text)
 
@@ -397,25 +394,20 @@
 
 # check difference in trans
 print(
-    "Recovered trans:\n{recovered}\n"
-    "Original trans:\n{original}".format(
-        recovered=trans2["trans"].round(3),
-        # combine head->mri with mri->mni to get head->mni
-        # and then invert to get mni->head
-        original=np.linalg.inv(np.dot(trans["trans"], mri_mni_t["trans"])).round(3),
-    )
+    f"Recovered trans:\n{trans2['trans'].round(3)}\n"
+    # combine head->mri with mri->mni to get head->mni
+    # and then invert to get mni->head
+    "Original trans:\n"
+    f"{np.linalg.inv(np.dot(trans['trans'], mri_mni_t['trans'])).round(3)}"
 )
 
 # ensure that the data in MNI coordinates is exactly the same
 # (within computer precision)
 montage2 = raw2.get_montage()  # get montage after transformed back to head
 montage2.apply_trans(trans2)
 print(
-    "Recovered coordinate: {recovered}\n"
-    "Original coordinate:  {original}".format(
-        recovered=montage2.get_positions()["ch_pos"]["LENT 1"],
-        original=montage.get_positions()["ch_pos"]["LENT 1"],
-    )
+    f"Recovered coordinate: {montage2.get_positions()['ch_pos']['LENT 1']}\n"
+    f"Original coordinate: {montage.get_positions()['ch_pos']['LENT 1']}"
 )
 
 # %%
@@ -521,11 +513,8 @@
 montage2 = raw2.get_montage()  # get montage after transformed back to head
 montage2.apply_trans(trans2)  # apply trans to go back to 'mri'
 print(
-    "Recovered coordinate: {recovered}\n"
-    "Original coordinate:  {original}".format(
-        recovered=montage2.get_positions()["ch_pos"]["LENT 1"],
-        original=montage.get_positions()["ch_pos"]["LENT 1"],
-    )
+    f"Recovered coordinate: {montage2.get_positions()['ch_pos']['LENT 1']}\n"
+    f"Original coordinate: {montage.get_positions()['ch_pos']['LENT 1']}"
 )
 
 # %%

dev/_downloads/b143d969421db5e73a9339985e158e7a/convert_mri_and_trans.py

@@ -40,22 +40,20 @@
 import os.path as op
 import shutil
 
-import numpy as np
 import matplotlib.pyplot as plt
-
-from nilearn.plotting import plot_anat
-
 import mne
-from mne.datasets import sample
+import numpy as np
 from mne import head_to_mri
+from mne.datasets import sample
+from nilearn.plotting import plot_anat
 
 from mne_bids import (
-    write_raw_bids,
     BIDSPath,
-    write_anat,
     get_anat_landmarks,
     get_head_mri_trans,
     print_dir_tree,
+    write_anat,
+    write_raw_bids,
 )
 
 # %%

dev/_downloads/b666106ea850b55fb6bc69db6fdda679/convert_nirs_to_bids.ipynb

@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "import os.path as op\nimport pathlib\nimport shutil\n\nimport mne\nfrom mne_nirs import datasets  # For convenient downloading of example data\n\nfrom mne_bids import write_raw_bids, BIDSPath, print_dir_tree\nfrom mne_bids.stats import count_events"
+        "import os.path as op\nimport pathlib\nimport shutil\n\nimport mne\nfrom mne_nirs import datasets  # For convenient downloading of example data\n\nfrom mne_bids import BIDSPath, print_dir_tree, write_raw_bids\nfrom mne_bids.stats import count_events"
       ]
     },
     {
@@ -231,7 +231,7 @@
       },
       "outputs": [],
       "source": [
-        "readme = op.join(bids_root, \"README\")\nwith open(readme, \"r\", encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
+        "readme = op.join(bids_root, \"README\")\nwith open(readme, encoding=\"utf-8-sig\") as fid:\n    text = fid.read()\nprint(text)"
       ]
     },
     {