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Merge pull request #472 from bids-standard/bids_website
[MAINT] update dataset listing
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‎README.md‎

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@@ -136,6 +136,19 @@ DO NOT EDIT DIRECTLY.
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| [asl004](https://github.com/bids-standard/bids-examples/tree/master/asl004) | T1w, asl (Siemens, PCASL, multiPLD with pepolar), m0scan separate scans with pepolar approach | anat, fmap, perf | T1w, asl, aslcontext, asllabeling, m0scan | [link](https://osf.io/yru2q/) | [@patsycle](https://github.com/patsycle) |
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| [asl005](https://github.com/bids-standard/bids-examples/tree/master/asl005) | T1w, asl (Siemens, PCASL, singleTI, 3D_GRASE), m0scan as separate scan | anat, perf | T1w, asl, aslcontext, asllabeling, m0scan | [link](https://osf.io/yru2q/) | [@patsycle](https://github.com/patsycle) |
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### Behavioral
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<!--
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TABLE BELOW IS GENERATED AUTOMATICALLY.
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DO NOT EDIT DIRECTLY.
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-->
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------|:-------------------------------------------------|:-------------------------------------------|
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| [ds000117](https://github.com/bids-standard/bids-examples/tree/master/ds000117) | A multi-subject, multi-modal human neuroimaging dataset of 19 subjects on a MEG visual task | anat, beh, dwi, fmap, func, meg | FLASH, T1w, bold, channels, coordsystem, dwi, events, headshape, magnitude1, magnitude2, meg, phasediff, scans | [link](https://openneuro.org/datasets/ds000117/) | [@RikHenson](https://github.com/RikHenson) |
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| [eeg_ds003645s_hed_demo](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_demo) | Shows usage of Hierarchical Event Descriptor (HED) in .tsv files | anat, beh, eeg, micr, motion | KSSSleep, SPIM, beh, channels, coordsystem, defacemask, eeg, electrodes, events, motion, photo, samples, scans | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [synthetic](https://github.com/bids-standard/bids-examples/tree/master/synthetic) | A synthetic dataset | anat, beh, func | T1w, beh, bold, events, physio, scans, sessions, stim | n/a | [@effigies](https://github.com/effigies) |
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### EEG
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<!--
@@ -151,6 +164,21 @@ DO NOT EDIT DIRECTLY.
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| [eeg_matchingpennies](https://github.com/bids-standard/bids-examples/tree/master/eeg_matchingpennies) | Offline data of BCI experiment decoding left vs. right hand movement. BrainVision data format (.eeg, .vhdr, .vmrk) | eeg | channels, eeg, events | [link](https://doi.org/10.17605/OSF.IO/CJ2DR) | [@sappelhoff](https://github.com/sappelhoff) |
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| [eeg_rishikesh](https://github.com/bids-standard/bids-examples/tree/master/eeg_rishikesh) | Mind wandering experiment. EEG data in Biosemi (.bdf) format | eeg | channels, eeg, events | [link](https://openneuro.org/datasets/ds001787) | [@arnodelorme](https://github.com/arnodelorme) |
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### DWI
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<!--
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TABLE BELOW IS GENERATED AUTOMATICALLY.
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DO NOT EDIT DIRECTLY.
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-->
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------|:-------------------------------------------|
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| [ds000117](https://github.com/bids-standard/bids-examples/tree/master/ds000117) | A multi-subject, multi-modal human neuroimaging dataset of 19 subjects on a MEG visual task | anat, beh, dwi, fmap, func, meg | FLASH, T1w, bold, channels, coordsystem, dwi, events, headshape, magnitude1, magnitude2, meg, phasediff, scans | [link](https://openneuro.org/datasets/ds000117/) | [@RikHenson](https://github.com/RikHenson) |
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| [ds114](https://github.com/bids-standard/bids-examples/tree/master/ds114) | multiple tasks, multiple runs | anat, dwi, func | T1w, bold, dwi, events | [link](https://openneuro.org/datasets/ds000114/versions/1.0.1) | n/a |
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| [dwi_deriv](https://github.com/bids-standard/bids-examples/tree/master/dwi_deriv) | exemplifies the storage of diffusion MRI derivates that may be generated on the Siemens XA platform. | dwi | dwi | n/a | n/a |
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| [eeg_rest_fmri](https://github.com/bids-standard/bids-examples/tree/master/eeg_rest_fmri) | Resting state with simultaneous fMRI. BrainVision data format (.eeg, .vhdr, .vmrk) | anat, dwi, eeg, func | T1w, bold, dwi, eeg | n/a | [@cpernet](https://github.com/cpernet) |
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| [genetics_ukbb](https://github.com/bids-standard/bids-examples/tree/master/genetics_ukbb) | multiple tasks, T1w, DTI, BOLD, genetic info | anat, dwi, func | FLAIR, T1w, bold, dwi, events, info | n/a | [@cpernet](https://github.com/cpernet) |
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### iEEG
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<!--
@@ -167,6 +195,20 @@ DO NOT EDIT DIRECTLY.
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| [ieeg_motorMiller2007](https://github.com/bids-standard/bids-examples/tree/master/ieeg_motorMiller2007) | Cue-based hand & tongue movement data | ieeg | channels, coordsystem, electrodes, events, ieeg | n/a | [@dorahermes](https://github.com/dorahermes) |
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| [ieeg_visual](https://github.com/bids-standard/bids-examples/tree/master/ieeg_visual) | Stimulus dependence of gamma oscillations in human visual cortex | anat, ieeg | T1w, channels, coordsystem, electrodes, events, ieeg | n/a | [@dorahermes](https://github.com/dorahermes) |
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| [ieeg_visual_multimodal](https://github.com/bids-standard/bids-examples/tree/master/ieeg_visual_multimodal) | n/a | anat, fmap, func, ieeg | T1w, bold, channels, coordsystem, electrodes, epi, events, ieeg, sbref | n/a | [@irisgroen](https://github.com/irisgroen) |
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| [xeeg_hed_score](https://github.com/bids-standard/bids-examples/tree/master/xeeg_hed_score) | EEG and iEEG data with annotations of artifacts, seizures and modulators using HED-SCORE | anat, eeg, ieeg | T1w, channels, coordsystem, eeg, electrodes, events, ieeg | n/a | [@dorahermes](https://github.com/dorahermes) |
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### HED
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<!--
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TABLE BELOW IS GENERATED AUTOMATICALLY.
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DO NOT EDIT DIRECTLY.
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-->
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------|:-----------------------------|:---------------------------------------------------------------------------------------------------------------|:------------------------------------------------|:---------------------------------------------|
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| [eeg_ds003645s_hed_demo](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_demo) | Shows usage of Hierarchical Event Descriptor (HED) in .tsv files | anat, beh, eeg, micr, motion | KSSSleep, SPIM, beh, channels, coordsystem, defacemask, eeg, electrodes, events, motion, photo, samples, scans | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [eeg_ds003645s_hed_library](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_library) | HED annotation using HED library vocabularies (schema). | eeg | channels, eeg, events | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [xeeg_hed_score](https://github.com/bids-standard/bids-examples/tree/master/xeeg_hed_score) | EEG and iEEG data with annotations of artifacts, seizures and modulators using HED-SCORE | anat, eeg, ieeg | T1w, channels, coordsystem, eeg, electrodes, events, ieeg | n/a | [@dorahermes](https://github.com/dorahermes) |
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### MEG
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@@ -309,16 +351,3 @@ DO NOT EDIT DIRECTLY.
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| [qmri_sa2rage](https://github.com/bids-standard/bids-examples/tree/master/qmri_sa2rage) | Fast B1+ mapping using SA2RAGE | fmap | TB1SRGE | `not publicly available` | [@agahkarakuzu](https://github.com/agahkarakuzu) |
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| [qmri_tb1tfl](https://github.com/bids-standard/bids-examples/tree/master/qmri_tb1tfl) | B1+ mapping with TurboFLASH readout. | fmap | TB1TFL | `not publicly available` | [@agahkarakuzu](https://github.com/agahkarakuzu) |
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| [qmri_vfa](https://github.com/bids-standard/bids-examples/tree/master/qmri_vfa) | Variable Flip Angle T1 mapping. Includes an Actual Flip Angle (AFI) B1+ mapping example. | anat, fmap | TB1AFI, VFA | [link](https://osf.io/k4bs5/) | [@agahkarakuzu](https://github.com/agahkarakuzu) |
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### Behavioral
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<!--
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TABLE BELOW IS GENERATED AUTOMATICALLY.
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DO NOT EDIT DIRECTLY.
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-->
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------|:-------------------------------------------------|:-------------------------------------------|
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| [ds000117](https://github.com/bids-standard/bids-examples/tree/master/ds000117) | A multi-subject, multi-modal human neuroimaging dataset of 19 subjects on a MEG visual task | anat, beh, dwi, fmap, func, meg | FLASH, T1w, bold, channels, coordsystem, dwi, events, headshape, magnitude1, magnitude2, meg, phasediff, scans | [link](https://openneuro.org/datasets/ds000117/) | [@RikHenson](https://github.com/RikHenson) |
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| [eeg_ds003645s_hed_demo](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_demo) | Shows usage of Hierarchical Event Descriptor (HED) in .tsv files | anat, beh, eeg, micr, motion | KSSSleep, SPIM, beh, channels, coordsystem, defacemask, eeg, electrodes, events, motion, photo, samples, scans | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [synthetic](https://github.com/bids-standard/bids-examples/tree/master/synthetic) | A synthetic dataset | anat, beh, func | T1w, beh, bold, events, physio, scans, sessions, stim | n/a | [@effigies](https://github.com/effigies) |

‎dataset_listing.tsv‎

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@@ -80,4 +80,5 @@ mrs_2dmrsi 2D sLASER MRSI data from 8 subjects [link](https://zenodo.org/records
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mrs_biggaba MEGA-PRESS and PRESS MRS data from 12 subjects from one site from the Big GABA project [link](https://www.nitrc.org/projects/biggaba) [@markmikkelsen](https://github.com/markmikkelsen) anat, mrs T1w, mrsref, svs
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mrs_fmrs Functional MRS data involving a pain stimulus task from 15 subjects [link](https://www.nitrc.org/projects/fmrs_2020) [@markmikkelsen](https://github.com/markmikkelsen) anat, mrs T1w, events, mrsref, svs
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2d_mb_pcasl Siemens 2D MultiBand Multi-delay PCASL (m0 and noRF included within timeseries) [link](https://osf.io/xrkc4/) [@aptinis](https://github.com/aptinis) anat, fmap, perf T1w, asl, aslcontext, epi
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xeeg_hed_score EEG and iEEG data with annotations of artifacts, seizures and modulators using HED-SCORE [@dorahermes](https://github.com/dorahermes) eeg, anat, ieeg channels, coordsystem, electrodes, events, ieeg, eeg, T1w
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xeeg_hed_score EEG and iEEG data with annotations of artifacts, seizures and modulators using HED-SCORE [@dorahermes](https://github.com/dorahermes) anat, eeg, ieeg T1w, channels, coordsystem, eeg, electrodes, events, ieeg
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dwi_deriv exemplifies the storage of diffusion MRI derivates that may be generated on the Siemens XA platform. dwi dwi

‎tools/print_dataset_listing.py‎

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You can pass an argument to insert the content in another file.
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Otherwise the content will be added to the README of this repository.
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"""
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import sys
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from pathlib import Path
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import pandas as pd
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from bids import BIDSLayout
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from rich import print
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folders_to_skip = ["docs", ".git", ".github", "tools", "env", "site", ".vscode"]
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suffixes_to_remove = ["README", "description", "participants", "CITATION"]
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UPSTREAM_REPO = "https://github.com/bids-standard/bids-examples/tree/master/"
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# set to True to update the listing of datasets with the datatypes and suffixes
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update_content = True
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update_content = False
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root = Path(__file__).resolve().parent.parent
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input_file = root / "dataset_listing.tsv"
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tables_order = {
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"ASL": "perf",
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"Behavioral": "beh",
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"EEG": "^eeg$",
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"DWI": "dwi",
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"iEEG": "ieeg",
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"HED": "",
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"MEG": "meg",
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"Microscopy": "micr",
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"Motion": "motion",
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"NIRS": "nirs",
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"PET": "pet",
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"qMRI": "",
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"Behavioral": "beh",
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}
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DELIMITER = "<!-- ADD EXAMPLE LISTING HERE -->"
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def main(output_file=None):
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if len(sys.argv) > 1:
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df = pd.read_csv(input_file, sep="\t")
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names = df["name"].copy()
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check_missing_folders(df, root)
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if update_content:
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df = add_links(df)
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print(df)
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clean_previous_run(output_file)
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df = df[column_order]
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add_tables(df, output_file)
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add_tables(df, output_file, names)
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def check_missing_folders(df, root):
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layout = BIDSLayout(root / row[1]["name"])
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tmp = sorted(layout.get_datatypes()) or ["n/a"]
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print(f" {tmp}")
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datatypes.append(stringify_list(tmp))
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tmp = layout.get_suffixes()
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tmp = sorted([s for s in tmp if s not in suffixes_to_remove]) or ["n/a"]
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print(f" {tmp}")
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suffixes.append(stringify_list(tmp))
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if not datatypes:
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return df
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def clean_previous_run(output_file: Path) -> None:
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print("Cleaning output files from previous run...")
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lines = output_file.read_text().split("\n")
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break
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f.write(line + "\n")
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def add_warning(f):
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f.write("""<!--
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f.write(
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"""<!--
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Table below is generated automatically.
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Do not edit directly.
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-->
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""".upper())
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""".upper()
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)
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def add_tables(df: pd.DataFrame, output_file: Path) -> None:
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def add_tables(df: pd.DataFrame, output_file: Path, names) -> None:
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print("Writing markdown tables...")
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df.fillna("n/a", inplace=True)
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for table_name, table_datatypes in tables_order.items():
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with output_file.open("a") as f:
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f.write(f"\n### {table_name}\n\n")
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add_warning(f)
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if table_name == "qMRI":
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sub_df = df[df["name"].str.contains("qmri_")]
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mask = names.str.contains("qmri_")
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elif table_name == "HED":
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mask = names.str.contains("_hed_")
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else:
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sub_df = df[df["datatypes"].str.contains(table_datatypes, regex=True)]
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mask = df["datatypes"].str.contains(table_datatypes, regex=True)
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sub_df = df[mask].copy()
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sub_df.sort_values(by=["name"], inplace=True)
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# sub_df["name"] = df["name"].apply(lambda x: f'[{x}](https://github.com/bids-standard/bids-examples/tree/master/{x})')
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print(sub_df)
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sub_df.to_markdown(output_file, index=False, mode="a")
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with output_file.open("a") as f:
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f.write("\n")

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