diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 8422f351c..797c20a87 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -1,14 +1,18 @@ name: Docs - concurrency: group: ${{ github.workflow }}-${{ github.event.number }}-${{ github.event.ref }} cancel-in-progress: true + on: push: - branches: [master, develop] + branches: [ master, develop ] pull_request: - branches: [master, develop] + branches: [ master, develop ] +permissions: + contents: write + pages: write + id-token: write jobs: build_docs: @@ -16,8 +20,8 @@ jobs: strategy: fail-fast: true matrix: - os: [ubuntu-latest] - python-version: ["3.9"] + os: [ ubuntu-latest ] + python-version: [ "3.9" ] steps: - uses: actions/checkout@v4 @@ -27,7 +31,7 @@ jobs: mkdir ~/mne_data - name: Setup Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} @@ -37,63 +41,79 @@ jobs: virtualenvs-create: true virtualenvs-in-project: true - - name: Cache datasets and docs - id: cached-dataset-docs + - name: Create/Restore MNE Data Cache + id: cache-mne_data + uses: actions/cache@v3 + with: + path: ~/mne_data + key: ${{ runner.os }}-mne_data + + - name: Cache docs build + id: cache-docs uses: actions/cache@v3 with: - key: doc-${{ github.head_ref }}-${{ hashFiles('moabb/datasets/**') }} - path: | - ~/mne_data - docs/build + key: docs-build-${{ github.run_id }}-${{ github.run_attempt }} + path: docs/build + + - name: Load cached venv + id: cached-poetry-dependencies + uses: actions/cache@v3 + with: + path: .venv + key: + docsvenv-${{ matrix.os }}-py${{matrix.python-version}}-${{ + hashFiles('**/pyproject.toml') }} - name: Install dependencies - if: steps.cached-dataset-docs.outputs.cache-hit != 'true' - run: poetry install --no-interaction --no-root --with docs --extras deeplearning + if: (steps.cached-poetry-dependencies.outputs.cache-hit != 'true') + run: poetry install --no-interaction --no-root --with docs --extras deeplearning --extras optuna - name: Install library - run: poetry install --no-interaction --with docs --extras deeplearning + run: poetry install --no-interaction --with docs --extras deeplearning --extras optuna - name: Build docs run: | cd docs && poetry run make html # Create an artifact of the html output. - - uses: actions/upload-artifact@v2 + - uses: actions/upload-artifact@v4 with: name: DocumentationHTML path: docs/build/html/ - deploy_docs: - if: ${{ github.ref == 'refs/heads/master' }} + deploy_neurotechx: + if: ${{ github.ref == 'refs/heads/develop' }} needs: build_docs runs-on: ${{ matrix.os }} strategy: fail-fast: false matrix: - os: [ubuntu-latest] + os: [ ubuntu-latest ] steps: - uses: actions/checkout@v4 - - name: Create local data folder - run: | - mkdir ~/mne_data - - - name: Cache datasets and docs - id: cached-dataset-docs - uses: actions/cache@v3 + - name: Restore cached docs build + id: cache-docs + uses: actions/cache/restore@v3 with: - key: doc-${{ github.head_ref }}-${{ hashFiles('moabb/datasets/**') }} - path: | - ~/mne_data - docs/build + key: docs-build-${{ github.run_id }}-${{ github.run_attempt }} + path: docs/build - - name: Checkout moabb.github.io - uses: actions/checkout@v4 + - name: Check cache hit + if: steps.cache-docs.outputs.cache-hit != 'true' + run: exit 1 + + - name: Deploy Neurotechx Subpage + uses: peaceiris/actions-gh-pages@v4 with: - repository: "NeuroTechX/moabb.github.io" - path: moabb-ghio - token: ${{ secrets.MOABB_GHIO }} + github_token: ${{ secrets.GITHUB_TOKEN }} + deploy_key: ${{ secrets.ACTIONS_DEPLOY_KEY }} + external_repository: NeuroTechX/moabb.github.io + destination_dir: docs/ + publish_branch: master + publish_dir: ./docs/build/html + cname: moabb.neurotechx.com/ deploy_gh_pages: if: ${{ github.ref == 'refs/heads/develop' }} @@ -102,47 +122,28 @@ jobs: strategy: fail-fast: false matrix: - os: [ubuntu-latest] + os: [ ubuntu-latest ] steps: - uses: actions/checkout@v4 - - name: Create local data folder - run: | - mkdir ~/mne_data - - - name: Cache datasets and docs - id: cached-dataset-docs - uses: actions/cache@v3 + - name: Restore cached docs build + id: cache-docs + uses: actions/cache/restore@v3 with: - key: doc-${{ github.head_ref }}-${{ hashFiles('moabb/datasets/**') }} - path: | - ~/mne_data - docs/build + key: docs-build-${{ github.run_id }}-${{ github.run_attempt }} + path: docs/build - - name: Checkout gh pages - uses: actions/checkout@v4 - with: - ref: gh-pages - path: moabb-ghpages + - name: Check cache hit + if: steps.cache-docs.outputs.cache-hit != 'true' + run: exit 1 - - name: Deploy Neurotechx Subpage - uses: peaceiris/actions-gh-pages@v3 + - name: Deploy gh-pages + uses: peaceiris/actions-gh-pages@v4 with: - deploy_key: ${{ secrets.ACTIONS_DEPLOY_KEY }} - external_repository: NeuroTechX/moabb.github.io + github_token: ${{ secrets.GITHUB_TOKEN }} + deploy_key: ${{ secrets.MOABB_DEPLOY_KEY_NEW }} destination_dir: docs/ - publish_branch: master + publish_branch: gh-pages publish_dir: ./docs/build/html - cname: moabb.neurotechx.com/ - - - name: Deploy on gh-pages - run: | - git config --global user.email "ci@neurotechx.com" - git config --global user.name "Github Actions" - cd ~/work/moabb/moabb/moabb-ghpages - rm -Rf docs - cp -a ~/work/moabb/moabb/docs/build/html ./docs - git add -A - git commit -m "GH Actions update of GH pages ($GITHUB_RUN_ID - $GITHUB_RUN_NUMBER)" - git push origin gh-pages + cname: neurotechx.github.io/moabb/ diff --git a/.github/workflows/test-braindecode.yml b/.github/workflows/test-braindecode.yml index b9a175391..481d6dbd0 100644 --- a/.github/workflows/test-braindecode.yml +++ b/.github/workflows/test-braindecode.yml @@ -1,15 +1,13 @@ name: Test-braindecode - concurrency: group: ${{ github.workflow }}-${{ github.event.number }}-${{ github.event.ref }} cancel-in-progress: true - on: push: - branches: [develop] + branches: [ develop ] pull_request: - branches: [develop] + branches: [ develop ] jobs: test: @@ -18,8 +16,8 @@ jobs: strategy: fail-fast: true matrix: - os: [ubuntu-latest] - python-version: ["3.8"] + os: [ ubuntu-latest ] + python-version: [ "3.8" ] defaults: run: shell: bash @@ -33,8 +31,21 @@ jobs: repository: braindecode/braindecode path: braindecode + - name: Create local data folder + if: runner.os != 'Windows' + run: | + mkdir ~/mne_data + + - name: Create/Restore MNE Data Cache + if: runner.os != 'Windows' + id: cache-mne_data + uses: actions/cache@v3 + with: + path: ~/mne_data + key: ${{ runner.os }}-mne_data + - name: Setup Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} @@ -44,13 +55,6 @@ jobs: virtualenvs-create: true virtualenvs-in-project: true - - name: Create/Restore MNE Data Cache - id: cache-mne_data - uses: actions/cache@v3 - with: - path: ~/mne_data - key: ${{ runner.os }}-mne - - name: Load cached venv if: runner.os != 'Windows' id: cached-poetry-dependencies @@ -58,8 +62,8 @@ jobs: with: path: .venv key: - testvenv-${{ matrix.os }}-py${{matrix.python-version}}-${{ - hashFiles('**/poetry.lock') }} + testvenv-braindecode-${{ matrix.os }}-py${{matrix.python-version}}-${{ + hashFiles('**/pyproject.toml') }} - name: Install dependencies if: | diff --git a/.github/workflows/test-devel.yml b/.github/workflows/test-devel.yml index 3d1651933..92160916a 100644 --- a/.github/workflows/test-devel.yml +++ b/.github/workflows/test-devel.yml @@ -1,15 +1,13 @@ name: Test-devel - concurrency: group: ${{ github.workflow }}-${{ github.event.number }}-${{ github.event.ref }} cancel-in-progress: true - on: push: - branches: [develop] + branches: [ develop ] pull_request: - branches: [develop] + branches: [ develop ] jobs: test: @@ -18,16 +16,29 @@ jobs: strategy: fail-fast: true matrix: - os: [ubuntu-latest, windows-latest, macOS-latest] - python-version: ["3.9", "3.10"] + os: [ ubuntu-latest, windows-latest, macOS-latest ] + python-version: [ "3.9", "3.10" ] defaults: run: shell: bash steps: - uses: actions/checkout@v4 + - name: Create local data folder + if: runner.os != 'Windows' + run: | + mkdir ~/mne_data + + - name: Create/Restore MNE Data Cache + if: runner.os != 'Windows' + id: cache-mne_data + uses: actions/cache@v3 + with: + path: ~/mne_data + key: ${{ runner.os }}-mne_data + - name: Setup Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} @@ -45,21 +56,21 @@ jobs: path: .venv key: testvenv-${{ matrix.os }}-py${{matrix.python-version}}-${{ - hashFiles('**/poetry.lock') }} + hashFiles('**/pyproject.toml') }} - name: Install dependencies if: | (runner.os != 'Windows') && (steps.cached-poetry-dependencies.outputs.cache-hit != 'true') - run: poetry install --no-interaction --no-root --extras deeplearning + run: poetry install --no-interaction --no-root --extras deeplearning --extras optuna - name: Install library (Linux/OSX) if: ${{ runner.os != 'Windows' }} - run: poetry install --no-interaction --extras deeplearning + run: poetry install --no-interaction --extras deeplearning --extras optuna - name: Install library (Windows) if: ${{ runner.os == 'Windows' }} - run: poetry install --no-interaction + run: poetry install --no-interaction --extras optuna - name: Run tests run: | diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 32ea5ad83..5755f4c56 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -1,15 +1,13 @@ name: Test - concurrency: group: ${{ github.workflow }}-${{ github.event.number }}-${{ github.event.ref }} cancel-in-progress: true - on: push: - branches: [master] + branches: [ master ] pull_request: - branches: [master] + branches: [ master ] jobs: test: @@ -18,16 +16,29 @@ jobs: strategy: fail-fast: true matrix: - os: [ubuntu-latest, windows-latest, macOS-latest] - python-version: ["3.9"] + os: [ ubuntu-latest, windows-latest, macOS-latest ] + python-version: [ "3.9", "3.10" ] defaults: run: shell: bash steps: - uses: actions/checkout@v4 + - name: Create local data folder + if: runner.os != 'Windows' + run: | + mkdir ~/mne_data + + - name: Create/Restore MNE Data Cache + if: runner.os != 'Windows' + id: cache-mne_data + uses: actions/cache@v3 + with: + path: ~/mne_data + key: ${{ runner.os }}-mne_data + - name: Setup Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} @@ -44,22 +55,22 @@ jobs: with: path: .venv key: - venv-${{ matrix.os }}-py${{matrix.python-version}}-${{ - hashFiles('**/poetry.lock') }} + testvenv-${{ matrix.os }}-py${{matrix.python-version}}-${{ + hashFiles('**/pyproject.toml') }} - name: Install dependencies if: | (runner.os != 'Windows') && (steps.cached-poetry-dependencies.outputs.cache-hit != 'true') - run: poetry install --no-interaction --no-root --extras deeplearning + run: poetry install --no-interaction --no-root --extras deeplearning --extras optuna - name: Install library (Linux/OSX) if: ${{ runner.os != 'Windows' }} - run: poetry install --no-interaction --extras deeplearning + run: poetry install --no-interaction --extras deeplearning --extras optuna - name: Install library (Windows) if: ${{ runner.os == 'Windows' }} - run: poetry install --no-interaction + run: poetry install --no-interaction --extras optuna - name: Run tests run: | diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 4fe4dbf4e..c59f216a6 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -15,7 +15,7 @@ exclude: ".*svg" repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.5.0 + rev: v4.6.0 hooks: - id: check-yaml - id: check-json @@ -35,14 +35,14 @@ repos: - repo: https://github.com/psf/black - rev: 24.3.0 + rev: 24.4.2 hooks: - id: black - language_version: python3.8 + language_version: python3 args: [ --line-length=90, --target-version=py38 ] - repo: https://github.com/asottile/blacken-docs - rev: 1.16.0 + rev: 1.18.0 hooks: - id: blacken-docs additional_dependencies: [black==23.3.0] @@ -54,7 +54,7 @@ repos: - id: isort - repo: https://github.com/PyCQA/flake8 - rev: 7.0.0 + rev: 7.1.0 hooks: - id: flake8 additional_dependencies: [ @@ -69,17 +69,17 @@ repos: exclude: ^docs/ | ^setup\.py$ | - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.3.5 + rev: v0.5.0 hooks: - id: ruff args: [ --fix, --exit-non-zero-on-fix, --ignore, E501 ] - repo: https://github.com/codespell-project/codespell - rev: v2.2.6 + rev: v2.3.0 hooks: - id: codespell args: - - --ignore-words-list=additionals,alle,alot,bund,currenty,datas,farenheit,falsy,fo,haa,hass,iif,incomfort,ines,ist,nam,nd,pres,pullrequests,resset,rime,ser,serie,te,technik,ue,unsecure,withing,zar,crate + - --ignore-words-list=assertIn,additionals,alle,alot,bund,currenty,datas,farenheit,falsy,fo,haa,hass,iif,incomfort,ines,ist,nam,nd,pres,pullrequests,resset,rime,ser,serie,te,technik,ue,unsecure,withing,zar,crate - --skip="./.*,*.csv,*.json,*.ambr" - --quiet-level=2 exclude_types: [ csv, json, svg ] diff --git a/CITATION.cff b/CITATION.cff index 31d38de8d..4aa2d08af 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -24,8 +24,8 @@ authors: - family-names: "Bjareholt" given-names: "Erik" orcid: "https://orcid.org/0000-0003-1350-9677" -- family-names: "Quentin" - given-names: "Barthelemy" +- family-names: "Barthelemy" + given-names: "Quentin" orcid: "https://orcid.org/0000-0002-7059-6028" - family-names: "Schirrmeister" given-names: "Robin Tibor" @@ -70,7 +70,7 @@ authors: given-names: "Sylvain" orcid: "https://orcid.org/0000-0003-3027-8241" title: "Mother of all BCI Benchmarks" -version: 1.1.0 +version: 1.1.1 doi: 10.5281/zenodo.10034223 -date-released: 2024-05-30 +date-released: 2024-09-16 url: "https://github.com/NeuroTechX/moabb" diff --git a/README.md b/README.md index a94edc692..b319ef9cd 100644 --- a/README.md +++ b/README.md @@ -291,18 +291,18 @@ If you use MOABB in your experiments, please cite this library when publishing a paper to increase the visibility of open science initiatives: ``` -Aristimunha, B., Carrara, I., Guetschel, P., Sedlar, S., Rodrigues, P., Sosulski, J., Narayanan, D., Bjareholt, E., Quentin, B., Schirrmeister, R. T.,Kalunga, E., Darmet, L., Gregoire, C., Abdul Hussain, A., Gatti, R., Goncharenko, V., Thielen, J., Moreau, T., Roy, Y., Jayaram, V., Barachant,A., & Chevallier, S. +Aristimunha, B., Carrara, I., Guetschel, P., Sedlar, S., Rodrigues, P., Sosulski, J., Narayanan, D., Bjareholt, E., Barthelemy, Q., Reinmar, K., Schirrmeister, R. T.,Kalunga, E., Darmet, L., Gregoire, C., Abdul Hussain, A., Gatti, R., Goncharenko, V., Thielen, J., Moreau, T., Roy, Y., Jayaram, V., Barachant,A., & Chevallier, S. Mother of all BCI Benchmarks (MOABB), 2023. DOI: 10.5281/zenodo.10034223. ``` and here is the Bibtex version: ```bibtex -@software{Aristimunha_Mother_of_all_2023, - author = {Aristimunha, Bruno and Carrara, Igor and Guetschel, Pierre and Sedlar, Sara and Rodrigues, Pedro and Sosulski, Jan and Narayanan, Divyesh and Bjareholt, Erik and Quentin, Barthelemy and Schirrmeister, Robin Tibor and Kalunga, Emmanuel and Darmet, Ludovic and Gregoire, Cattan and Abdul Hussain, Ali and Gatti, Ramiro and Goncharenko, Vladislav and Thielen, Jordy and Moreau, Thomas and Roy, Yannick and Jayaram, Vinay and Barachant, Alexandre and Chevallier, Sylvain}, +@software{Aristimunha_Mother_of_all, + author = {Aristimunha, Bruno and Carrara, Igor and Guetschel, Pierre and Sedlar, Sara and Rodrigues, Pedro and Sosulski, Jan and Narayanan, Divyesh and Bjareholt, Erik and Barthelemy, Quentin and Kobler, Reinmar and Schirrmeister, Robin Tibor and Kalunga, Emmanuel and Darmet, Ludovic and Gregoire, Cattan and Abdul Hussain, Ali and Gatti, Ramiro and Goncharenko, Vladislav and Thielen, Jordy and Moreau, Thomas and Roy, Yannick and Jayaram, Vinay and Barachant, Alexandre and Chevallier, Sylvain}, doi = {10.5281/zenodo.10034223}, title = {{Mother of all BCI Benchmarks}}, url = {https://github.com/NeuroTechX/moabb}, version = {1.1.0}, - year = {2023} + year = {2024} } ``` If you want to cite the scientific contributions of MOABB, you could use the following paper: diff --git a/docs/Makefile b/docs/Makefile index 64fc30c07..78ff1405a 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -17,6 +17,7 @@ help: # Catch-all target: route all unknown targets to Sphinx using the new # "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). %: Makefile + @python prepare_summary_tables.py ../moabb/datasets $(BUILDDIR) @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) apidoc: diff --git a/docs/prepare_summary_tables.py b/docs/prepare_summary_tables.py new file mode 100644 index 000000000..8bc9ffba6 --- /dev/null +++ b/docs/prepare_summary_tables.py @@ -0,0 +1,34 @@ +import glob +from argparse import ArgumentParser +from pathlib import Path + +import pandas as pd + + +def prepare_table(df: pd.DataFrame): + no_pwc = df["PapersWithCode leaderboard"].isna() + df.loc[no_pwc, "PapersWithCode leaderboard"] = "No" + df.loc[~no_pwc, "PapersWithCode leaderboard"] = df.loc[ + ~no_pwc, "PapersWithCode leaderboard" + ].apply(lambda x: f"`Yes <{x}>`_") + df["Dataset"] = df["Dataset"].apply(lambda x: f":class:`{x}`") + + +def main(source_dir: str, target_dir: str): + target_dir = Path(target_dir) + target_dir.mkdir(parents=True, exist_ok=True) + files = glob.glob(str(Path(source_dir) / "*.csv")) + for f in files: + target_file = target_dir / Path(f).name + print(f"Processing {f} -> {target_file}") + df = pd.read_csv(f, index_col=False, header=0, skipinitialspace=True) + prepare_table(df) + df.to_csv(target_file, index=False) + + +if __name__ == "__main__": + parser = ArgumentParser() + parser.add_argument("source_dir", type=str) + parser.add_argument("target_dir", type=str) + args = parser.parse_args() + main(args.source_dir, args.target_dir) diff --git a/docs/source/README.md b/docs/source/README.md index 25a16bb1f..5e205b8da 100644 --- a/docs/source/README.md +++ b/docs/source/README.md @@ -82,7 +82,6 @@ The project is currently maintained by: Bruno Aristimunha Igor Carrara Pierre Guetschel - Sara Sedlar @@ -91,7 +90,6 @@ The project is currently maintained by: Bruno Aristimunha Igor Carrara Pierre Guetschel - Sara Sedlar @@ -230,7 +228,6 @@ the link on the gitter channel. We are also on NeuroTechX Slack channel [link_bruno]: https://www.linkedin.com/in/bruaristimunha/ [link_igor]: https://www.linkedin.com/in/carraraig/ [link_pierre]: https://www.linkedin.com/in/pierreguetschel/ -[link_sara]: https://www.linkedin.com/in/sara-sedlar-28709893/ [link_neurotechx_signup]: https://neurotechx.com/ [link_gitter]: https://app.gitter.im/#/room/#moabb_dev_community:gitter.im [link_moabb_docs]: https://neurotechx.github.io/moabb/ diff --git a/docs/source/dataset_summary.rst b/docs/source/dataset_summary.rst index 24a3ca229..8b2908573 100644 --- a/docs/source/dataset_summary.rst +++ b/docs/source/dataset_summary.rst @@ -22,66 +22,28 @@ Motor Imagery ====================== .. csv-table:: - :header: Dataset, #Subj, #Chan, #Classes, #Trials, Trial length, Freq, #Session, #Runs, Total_trials + :file: ../build/summary_imagery.csv + :header-rows: 1 :class: sortable - :class:`AlexMI`,8,16,3,20,3s,512Hz,1,1,480 - :class:`BNCI2014_001`,9,22,4,144,4s,250Hz,2,6,62208 - :class:`BNCI2014_002`,14,15,2,80,5s,512Hz,1,8,17920 - :class:`BNCI2014_004`,9,3,2,360,4.5s,250Hz,5,1,32400 - :class:`BNCI2015_001`,12,13,2,200,5s,512Hz,3,1,14400 - :class:`BNCI2015_004`,9,30,5,80,7s,256Hz,2,1,7200 - :class:`Cho2017`,52,64,2,100,3s,512Hz,1,1,9800 - :class:`Lee2019_MI`,54,62,2,100,4s,1000Hz,2,1,11000 - :class:`GrosseWentrup2009`,10,128,2,150,7s,500Hz,1,1,3000 - :class:`Schirrmeister2017`,14,128,4,120,4s,500Hz,1,2,13440 - :class:`Ofner2017`,15,61,7,60,3s,512Hz,1,10,63000 - :class:`PhysionetMI`,109,64,4,23,3s,160Hz,1,1,69760 - :class:`Shin2017A`,29,30,2,30,10s,200Hz,3,1,5220 - :class:`Shin2017B`,29,30,2,30,10s,200Hz,3,1,5220 - :class:`Weibo2014`,10,60,7,80,4s,200Hz,1,1,5600 - :class:`Zhou2016`,4,14,3,160,5s,250Hz,3,2,11496 - :class:`Stieger2021`,62,64,4,450,3s,1000Hz,7 or 11,1,250000 P300/ERP ====================== .. csv-table:: - :header: Dataset, #Subj, #Chan, #Trials / class, Trials length, Sampling rate, #Sessions + :file: ../build/summary_p300.csv + :header-rows: 1 :class: sortable - :class:`BNCI2014_008`, 8, 8, 3500 NT / 700 T, 1s, 256Hz, 1 - :class:`BNCI2014_009`, 10, 16, 1440 NT / 288 T, 0.8s, 256Hz, 3 - :class:`BNCI2015_003`, 10, 8, 1500 NT / 300 T, 0.8s, 256Hz, 1 - :class:`BI2012`, 25, 16, 640 NT / 128 T, 1s, 128Hz, 2 - :class:`BI2013a`, 24, 16, 3200 NT / 640 T, 1s, 512Hz, 8 for subjects 1-7 else 1 - :class:`BI2014a`, 64, 16, 990 NT / 198 T, 1s, 512Hz, up to 3 - :class:`BI2014b`, 38, 32, 200 NT / 40 T, 1s, 512Hz, 3 - :class:`BI2015a`, 43, 32, 4131 NT / 825 T, 1s, 512Hz, 3 - :class:`BI2015b`, 44, 32, 2160 NT / 480 T, 1s, 512Hz, 1 - :class:`Cattan2019_VR`, 21, 16, 600 NT / 120 T, 1s, 512Hz, 2 - :class:`Huebner2017`, 13, 31, 364 NT / 112 T, 0.9s, 1000Hz, 3 - :class:`Huebner2018`, 12, 31, 364 NT / 112 T, 0.9s, 1000Hz, 3 - :class:`Sosulski2019`, 13, 31, 7500 NT / 1500 T, 1.2s, 1000Hz, 1 - :class:`EPFLP300`, 8, 32, 2753 NT / 551 T, 1s, 2048Hz, 4 - :class:`Lee2019_ERP`, 54, 62, 6900 NT / 1380 T, 1s, 1000Hz, 2 - SSVEP ====================== - .. csv-table:: - :header: Dataset, #Subj, #Chan, #Classes, #Trials / class, Trials length, Sampling rate, #Sessions + :file: ../build/summary_ssvep.csv + :header-rows: 1 :class: sortable - :class:`Lee2019_SSVEP`,54,62,4,50,4s,1000Hz,2 - :class:`Kalunga2016`,12,8,4,16,2s,256Hz,1 - :class:`MAMEM1`,10,256,5,12-15,3s,250Hz,1 - :class:`MAMEM2`,10,256,5,20-30,3s,250Hz,1 - :class:`MAMEM3`,10,14,4,20-30,3s,128Hz,1 - :class:`Nakanishi2015`,9,8,12,15,4.15s,256Hz,1 - :class:`Wang2016`,34,62,40,6,5s,250Hz,1 c-VEP ====================== @@ -97,17 +59,10 @@ potentials (c-VEP): A literature review. Journal of Neural Engineering, 18(6), 0 DOI: https://doi.org/10.1088/1741-2552/ac38cf .. csv-table:: - :header: Dataset, #Subj, #Sessions, Sampling rate, #Chan, Trials length, #Trial classes, #Trials / class, #Epochs classes, #Epochs / class, Codes, Presentation rate + :file: ../build/summary_cvep.csv + :header-rows: 1 :class: sortable - :class:`Thielen2015`,12,1,2048Hz,64,4.2s,36,3,2,27216 NT / 27216 T,Gold codes,120Hz - :class:`Thielen2021`,30,1,512Hz,8,31.5s,20,5,2,18900 NT / 18900 T,Gold codes,60Hz - :class:`CastillosCVEP100`, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,3525 NT / 3495 T,m-sequence,60Hz - :class:`CastillosCVEP40`, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,3525 NT / 3495 T,m-sequence,60Hz - :class:`CastillosBurstVEP40`, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,5820 NT / 1200 T,Burst-CVEP,60Hz - :class:`CastillosBurstVEP100`,12,1,500Hz,32,2.2s,4,15/15/15/15,2,5820 NT / 1200 T,Burst-CVEP,60Hz - - Resting States ====================== @@ -116,12 +71,9 @@ For example, recoding the EEG of a subject while s/he is having the eye closed o is a resting state experiment. .. csv-table:: - :header: Dataset, #Subj, #Chan, #Classes, #Blocks / class, Trials length, Sampling rate, #Sessions - :class: sortable - - :class:`Cattan2019_PHMD`,12,16,2,10,60s,512Hz,1 - :class:`Hinss2021`,15,62,4,1,2s,250Hz,1 - :class:`Rodrigues2017`,20,16,2,5,10s,512Hz,1 + :file: ../build/summary_rstate.csv + :header-rows: 1 + :class: sortable Compound Datasets ====================== diff --git a/docs/source/datasets.rst b/docs/source/datasets.rst index b13fc7dfc..2d3596ba6 100644 --- a/docs/source/datasets.rst +++ b/docs/source/datasets.rst @@ -31,7 +31,7 @@ Motor Imagery Datasets Weibo2014 Zhou2016 Stieger2021 - + Liu2024 ------------ ERP Datasets diff --git a/docs/source/whats_new.rst b/docs/source/whats_new.rst index 0209c752d..d56bfdb0a 100644 --- a/docs/source/whats_new.rst +++ b/docs/source/whats_new.rst @@ -17,19 +17,40 @@ Develop branch Enhancements ~~~~~~~~~~~~ -- None Bugs ~~~~ -- None + +- Fix Stieger2021 dataset bugs (:gh:`651` by `Martin Wimpff`_) +- Unpinning major version Scikit-learn and numpy (:gh:`652` by `Bruno Aristimunha`_) API changes ~~~~~~~~~~~ -- None -Version - 1.1.0 (Stable - PyPi) +Version - 1.1.1 (Stable - PyPi) --------------------------------- +Enhancements +~~~~~~~~~~~~ +- Add possibility to use OptunaGridSearch (:gh:`630` by `Igor Carrara`_) +- Add scripts to upload results on PapersWithCode (:gh:`561` by `Pierre Guetschel`_) +- Centralize dataset summary tables in CSV files (:gh:`635` by `Pierre Guetschel`_) +- Add new dataset :class:`moabb.datasets.Liu2024` dataset (:gh:`619` by `Taha Habib`_) + + +Bugs +~~~~ +- Fix caching in the workflows (:gh:`632` by `Pierre Guetschel`_) + +API changes +~~~~~~~~~~~ +- Include optuna as soft-dependency in the benchmark function and in the base of evaluation (:gh:`630` by `Igor Carrara`_) + + + +Version - 1.1.0 +---------------- + Enhancements ~~~~~~~~~~~~ @@ -444,6 +465,7 @@ Bugs API changes ~~~~~~~~~~~ - None +.. _Martin Wimpff: https://github.com/martinwimpff .. _Reinmar Kobler: https://github.com/rkobler .. _Gabriel Schwartz: https://github.com/Kaos9001 .. _Sara Sedlar: https://github.com/Sara04 @@ -474,3 +496,4 @@ API changes .. _Brian Irvine: https://github.com/brianjohannes .. _Bruna Lopes: https://github.com/brunaafl .. _Yash Chauhan: https://github.com/jiggychauhi +.. _Taha Habib: https://github.com/tahatt13 diff --git a/examples/plot_Hinss2021_classification.py b/examples/plot_Hinss2021_classification.py index 76c15d730..a8d8d4506 100644 --- a/examples/plot_Hinss2021_classification.py +++ b/examples/plot_Hinss2021_classification.py @@ -43,6 +43,7 @@ set_log_level("info") + ############################################################################## # Create util transformer # ---------------------- @@ -103,12 +104,11 @@ def transform(self, X): # To reduce the computation time in the example, we will only use the # first two subjects. -start_subject = 1 -stop_subject = 2 +n__subjects = 2 title = "Datasets: " for dataset in datasets: title = title + " " + dataset.code - dataset.subject_list = dataset.subject_list[start_subject:stop_subject] + dataset.subject_list = dataset.subject_list[:n__subjects] ############################################################################## # Create Pipelines diff --git a/moabb/__init__.py b/moabb/__init__.py index ffbd9c309..0a84ce77c 100644 --- a/moabb/__init__.py +++ b/moabb/__init__.py @@ -1,5 +1,5 @@ # flake8: noqa -__version__ = "1.1.0" +__version__ = "1.1.1" from .benchmark import benchmark from .utils import make_process_pipelines, set_download_dir, set_log_level, setup_seed diff --git a/moabb/benchmark.py b/moabb/benchmark.py index f2493cfa3..312223f6f 100644 --- a/moabb/benchmark.py +++ b/moabb/benchmark.py @@ -45,6 +45,7 @@ def benchmark( # noqa: C901 exclude_datasets=None, n_splits=None, cache_config=None, + optuna=False, ): """Run benchmarks for selected pipelines and datasets. @@ -102,6 +103,7 @@ def benchmark( # noqa: C901 and exclude_datasets are specified, raise an error. exclude_datasets: list of str or Dataset object Datasets to exclude from the benchmark run + optuna: Enable Optuna for the hyperparameter search Returns ------- @@ -110,7 +112,11 @@ def benchmark( # noqa: C901 Notes ----- + .. versionadded:: 1.1.1 + Includes the possibility to use Optuna for hyperparameter search. + .. versionadded:: 0.5.0 + Create the function to run the benchmark """ # set logs if evaluations is None: @@ -182,6 +188,7 @@ def benchmark( # noqa: C901 return_epochs=True, n_splits=n_splits, cache_config=cache_config, + optuna=optuna, ) paradigm_results = context.process( pipelines=ppl_with_epochs, param_grid=param_grid @@ -202,6 +209,7 @@ def benchmark( # noqa: C901 overwrite=overwrite, n_splits=n_splits, cache_config=cache_config, + optuna=optuna, ) paradigm_results = context.process( pipelines=ppl_with_array, param_grid=param_grid diff --git a/moabb/datasets/Lee2019.py b/moabb/datasets/Lee2019.py index 5666a8a67..7edf9b931 100644 --- a/moabb/datasets/Lee2019.py +++ b/moabb/datasets/Lee2019.py @@ -220,15 +220,6 @@ def data_path( class Lee2019_MI(Lee2019): """BMI/OpenBMI dataset for MI. - .. admonition:: Dataset summary - - - ========== ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ========== ======= ======= ========== ================= ============ =============== =========== - Lee2019_MI 54 62 2 100 4s 1000Hz 2 - ========== ======= ======= ========== ================= ============ =============== =========== - Dataset from Lee et al 2019 [1]_. **Dataset Description** @@ -290,15 +281,6 @@ class Lee2019_MI(Lee2019): class Lee2019_ERP(Lee2019): """BMI/OpenBMI dataset for P300. - .. admonition:: Dataset summary - - - =========== ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - =========== ======= ======= ================= =============== =============== =========== - Lee2019_ERP 54 62 6900 NT / 1380 T 1s 1000Hz 2 - =========== ======= ======= ================= =============== =============== =========== - Dataset from Lee et al 2019 [1]_. **Dataset Description** @@ -380,15 +362,6 @@ class Lee2019_ERP(Lee2019): class Lee2019_SSVEP(Lee2019): """BMI/OpenBMI dataset for SSVEP. - .. admonition:: Dataset summary - - - ============= ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ============= ======= ======= ========== ================= =============== =============== =========== - Lee2019_SSVEP 54 62 4 50 4s 1000Hz 2 - ============= ======= ======= ========== ================= =============== =============== =========== - Dataset from Lee et al 2019 [1]_. **Dataset Description** diff --git a/moabb/datasets/Weibo2014.py b/moabb/datasets/Weibo2014.py index 8fedd0e35..14fa047b9 100644 --- a/moabb/datasets/Weibo2014.py +++ b/moabb/datasets/Weibo2014.py @@ -64,15 +64,6 @@ def get_subjects(sub_inds, sub_names, ind): class Weibo2014(BaseDataset): """Motor Imagery dataset from Weibo et al 2014. - .. admonition:: Dataset summary - - - ========= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ========= ======= ======= ========== ================= ============ =============== =========== - Weibo2014 10 60 7 80 4s 200Hz 1 - ========= ======= ======= ========== ================= ============ =============== =========== - Dataset from the article *Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery* [1]_. diff --git a/moabb/datasets/Zhou2016.py b/moabb/datasets/Zhou2016.py index 17ef79bfb..c4037cea9 100644 --- a/moabb/datasets/Zhou2016.py +++ b/moabb/datasets/Zhou2016.py @@ -50,15 +50,6 @@ def local_data_path(base_path, subject): class Zhou2016(BaseDataset): """Motor Imagery dataset from Zhou et al 2016. - .. admonition:: Dataset summary - - - ======== ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ======== ======= ======= ========== ================= ============ =============== =========== - Zhou2016 4 14 3 160 5s 250Hz 3 - ======== ======= ======= ========== ================= ============ =============== =========== - Dataset from the article *A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface* [1]_. This dataset contains data recorded on 4 subjects performing 3 type of diff --git a/moabb/datasets/__init__.py b/moabb/datasets/__init__.py index b8cf8a116..5b3a41fae 100644 --- a/moabb/datasets/__init__.py +++ b/moabb/datasets/__init__.py @@ -61,6 +61,7 @@ from .hinss2021 import Hinss2021 from .huebner_llp import Huebner2017, Huebner2018 from .Lee2019 import Lee2019_ERP, Lee2019_MI, Lee2019_SSVEP +from .liu2024 import Liu2024 from .mpi_mi import MunichMI # noqa: F401 from .mpi_mi import GrosseWentrup2009 from .neiry import DemonsP300 diff --git a/moabb/datasets/alex_mi.py b/moabb/datasets/alex_mi.py index 2f8f5279e..6e2ef7d75 100644 --- a/moabb/datasets/alex_mi.py +++ b/moabb/datasets/alex_mi.py @@ -12,15 +12,6 @@ class AlexMI(BaseDataset): """Alex Motor Imagery dataset. - .. admonition:: Dataset summary - - - ====== ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ====== ======= ======= ========== ================= ============ =============== =========== - AlexMI 8 16 3 20 3s 512Hz 1 - ====== ======= ======= ========== ================= ============ =============== =========== - Motor imagery dataset from the PhD dissertation of A. Barachant [1]_. This Dataset contains EEG recordings from 8 subjects, performing 2 task of diff --git a/moabb/datasets/alphawaves.py b/moabb/datasets/alphawaves.py index aa7f8fe39..f55b270e8 100644 --- a/moabb/datasets/alphawaves.py +++ b/moabb/datasets/alphawaves.py @@ -17,16 +17,6 @@ class Rodrigues2017(BaseDataset): """Alphawaves dataset - .. admonition:: Dataset summary - - - =============== ======= ======= ========== =============== ============ =============== =========== - Name #Subj #Chan #Classes #Blocks/class Trials len Sampling rate #Sessions - =============== ======= ======= ========== =============== ============ =============== =========== - Rodrigues2017 20 16 2 5 10s 512Hz 1 - =============== ======= ======= ========== =============== ============ =============== =========== - - Dataset containing EEG recordings of subjects in a simple resting-state eyes open/closed experimental protocol. Data were recorded during a pilot experiment taking place in the GIPSA-lab, Grenoble, @@ -139,7 +129,6 @@ def _get_single_subject_data(self, subject): def data_path( self, subject, path=None, force_update=False, update_path=None, verbose=None ): - if subject not in self.subject_list: raise (ValueError("Invalid subject number")) diff --git a/moabb/datasets/base.py b/moabb/datasets/base.py index 1fcfb0b5c..0d4672482 100644 --- a/moabb/datasets/base.py +++ b/moabb/datasets/base.py @@ -1,5 +1,7 @@ """Base class for a dataset.""" +from __future__ import annotations + import abc import logging import re @@ -9,6 +11,7 @@ from pathlib import Path from typing import Dict, Union +import pandas as pd from sklearn.pipeline import Pipeline from moabb.datasets.bids_interface import StepType, _interface_map @@ -18,6 +21,36 @@ log = logging.getLogger(__name__) +def get_summary_table(paradigm: str, dir_name: str | None = None): + if dir_name is None: + dir_name = Path(__file__).parent + path = Path(dir_name) / f"summary_{paradigm}.csv" + df = pd.read_csv( + path, + header=0, + index_col="Dataset", + skipinitialspace=True, + dtype={"PapersWithCode leaderboard": str}, + ) + return df + + +_summary_table_imagery = get_summary_table("imagery") +_summary_table_p300 = get_summary_table("p300") +_summary_table_ssvep = get_summary_table("ssvep") +_summary_table_cvep = get_summary_table("cvep") +_summary_table_rstate = get_summary_table("rstate") +_summary_table = pd.concat( + [ + _summary_table_imagery, + _summary_table_p300, + _summary_table_ssvep, + _summary_table_cvep, + _summary_table_rstate, + ], +) + + @dataclass class CacheConfig: """ @@ -178,7 +211,64 @@ def check_run_names(data): ) -class BaseDataset(metaclass=abc.ABCMeta): +def format_row(row: pd.Series): + pwc_key = "PapersWithCode leaderboard" + tab_prefix = " " * 8 + tab_sep = "=" + row = row[~row.isna()] + pwc_link = row.get(pwc_key, None) + if pwc_link is not None: + row = row.drop(pwc_key) + col_names = [str(col) for col in row.index] + + def to_int(x): + try: + i = int(x) + if i == x: + return i + return x + except ValueError: + return x + + values = [str(to_int(val)) for val in row.values] + widths = [max(len(col), len(val)) for col, val in zip(col_names, values)] + row_sep = " ".join([tab_sep * width for width in widths]) + cols_row = " ".join([col.rjust(width) for col, width in zip(col_names, widths)]) + values_row = " ".join([val.rjust(width) for val, width in zip(values, widths)]) + out = ( + " .. admonition:: Dataset summary\n\n" + f"{tab_prefix}{row_sep}\n" + f"{tab_prefix}{cols_row}\n" + f"{tab_prefix}{row_sep}\n" + f"{tab_prefix}{values_row}\n" + f"{tab_prefix}{row_sep}" + ) + if pwc_link is not None: + out = f" **{pwc_key}:** {pwc_link}\n\n" + out + return out + + +class MetaclassDataset(abc.ABCMeta): + def __new__(cls, name, bases, attrs): + doc = attrs.get("__doc__", "") + try: + row = _summary_table.loc[name] + row_str = format_row(row) + doc_list = doc.split("\n\n") + if len(doc_list) >= 2: + doc_list = [doc_list[0], row_str] + doc_list[1:] + else: + doc_list.append(row_str) + attrs["__doc__"] = "\n\n".join(doc_list) + except KeyError: + log.debug( + f"No description found for dataset {name}. " + f"Complete the appropriate moabb/datasets/summary_*.csv file" + ) + return super().__new__(cls, name, bases, attrs) + + +class BaseDataset(metaclass=MetaclassDataset): """Abstract Moabb BaseDataset. Parameters required for all datasets diff --git a/moabb/datasets/bbci_eeg_fnirs.py b/moabb/datasets/bbci_eeg_fnirs.py index ff86ab74a..32fd7f1cf 100644 --- a/moabb/datasets/bbci_eeg_fnirs.py +++ b/moabb/datasets/bbci_eeg_fnirs.py @@ -192,15 +192,6 @@ def data_path( class Shin2017A(BaseShin2017): """Motor Imagey Dataset from Shin et al 2017. - .. admonition:: Dataset summary - - - ========= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ========= ======= ======= ========== ================= ============ =============== =========== - Shin2017A 29 30 2 30 10s 200Hz 3 - ========= ======= ======= ========== ================= ============ =============== =========== - Dataset from [1]_. @@ -315,15 +306,6 @@ def __init__(self, accept=False): class Shin2017B(BaseShin2017): """Mental Arithmetic Dataset from Shin et al 2017. - .. admonition:: Dataset summary - - - ========= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ========= ======= ======= ========== ================= ============ =============== =========== - Shin2017B 29 30 2 30 10s 200Hz 3 - ========= ======= ======= ========== ================= ============ =============== =========== - Dataset from [1]_. .. caution:: diff --git a/moabb/datasets/bnci.py b/moabb/datasets/bnci.py index 1f42197d2..0cef42910 100644 --- a/moabb/datasets/bnci.py +++ b/moabb/datasets/bnci.py @@ -756,15 +756,6 @@ def data_path( class BNCI2014_001(MNEBNCI): """BNCI 2014-001 Motor Imagery dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============ ======= ======= ========== ================= ============ =============== =========== - BNCI2014_001 9 22 4 144 4s 250Hz 2 - ============ ======= ======= ========== ================= ============ =============== =========== - Dataset IIa from BCI Competition 4 [1]_. **Dataset Description** @@ -820,15 +811,6 @@ def __init__(self): class BNCI2014_002(MNEBNCI): """BNCI 2014-002 Motor Imagery dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============ ======= ======= ========== ================= ============ =============== =========== - BNCI2014_002 14 15 2 80 5s 512Hz 1 - ============ ======= ======= ========== ================= ============ =============== =========== - Motor Imagery Dataset from [1]_. **Dataset description** @@ -882,15 +864,6 @@ def __init__(self): class BNCI2014_004(MNEBNCI): """BNCI 2014-004 Motor Imagery dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============ ======= ======= ========== ================= ============ =============== =========== - BNCI2014_004 9 3 2 360 4.5s 250Hz 5 - ============ ======= ======= ========== ================= ============ =============== =========== - Dataset B from BCI Competition 2008. **Dataset description** @@ -965,15 +938,6 @@ def __init__(self): class BNCI2014_008(MNEBNCI): """BNCI 2014-008 P300 dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ============ ======= ======= ================= =============== =============== =========== - BNCI2014_008 8 8 3500 NT / 700 T 1s 256Hz 1 - ============ ======= ======= ================= =============== =============== =========== - Dataset from [1]_. **Dataset description** @@ -1036,15 +1000,6 @@ def __init__(self): class BNCI2014_009(MNEBNCI): """BNCI 2014-009 P300 dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ============ ======= ======= ================= =============== =============== =========== - BNCI2014_009 10 16 1440 NT / 288 T 0.8s 256Hz 3 - ============ ======= ======= ================= =============== =============== =========== - Dataset from [1]_. **Dataset description** @@ -1098,15 +1053,6 @@ def __init__(self): class BNCI2015_001(MNEBNCI): """BNCI 2015-001 Motor Imagery dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============ ======= ======= ========== ================= ============ =============== =========== - BNCI2015_001 12 13 2 200 5s 512Hz 2 - ============ ======= ======= ========== ================= ============ =============== =========== - Dataset from [1]_. **Dataset description** @@ -1154,14 +1100,6 @@ def __init__(self): class BNCI2015_003(MNEBNCI): """BNCI 2015-003 P300 dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ============ ======= ======= ================= =============== =============== =========== - BNCI2015_003 10 8 1500 NT / 300 T 0.8s 256Hz 1 - ============ ======= ======= ================= =============== =============== =========== Dataset from [1]_. @@ -1197,15 +1135,6 @@ def __init__(self): class BNCI2015_004(MNEBNCI): """BNCI 2015-004 Motor Imagery dataset. - .. admonition:: Dataset summary - - - ============ ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============ ======= ======= ========== ================= ============ =============== =========== - BNCI2015_004 9 30 5 80 7s 256Hz 2 - ============ ======= ======= ========== ================= ============ =============== =========== - Dataset from [1]_. **Dataset description** diff --git a/moabb/datasets/braininvaders.py b/moabb/datasets/braininvaders.py index f5b5ffb9f..7d851f215 100644 --- a/moabb/datasets/braininvaders.py +++ b/moabb/datasets/braininvaders.py @@ -416,13 +416,6 @@ def _bi_data_path( # noqa: C901 class BI2012(BaseDataset): """P300 dataset BI2012 from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - ================ ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ================ ======= ======= ================ =============== =============== =========== - BI2012 25 16 640 NT / 128 T 1s 128Hz 2 - ================ ======= ======= ================ =============== =============== =========== - Dataset following the setup from [1]_ carried-out at University of Grenoble Alpes. @@ -483,15 +476,6 @@ def data_path( class BI2013a(BaseDataset): """P300 dataset BI2013a from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - - - ======= ======= ======= ================= =============== =============== ================= - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ======= ======= ======= ================= =============== =============== ================= - BI2013a 24 16 3200 NT / 640 T 1s 512Hz (1-7)8 s|(8-24)1s - ======= ======= ======= ================= =============== =============== ================= - Dataset following the setup from [1]_ carried-out at University of Grenoble Alpes. @@ -586,13 +570,6 @@ def data_path( class BI2014a(BaseDataset): """P300 dataset BI2014a from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - ================ ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ================ ======= ======= ================ =============== =============== =========== - BI2014a 64 16 5 NT x 1 T 1s 512Hz up to 3 - ================ ======= ======= ================ =============== =============== =========== - This dataset contains electroencephalographic (EEG) recordings of 71 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named Brain Invaders. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) @@ -645,13 +622,6 @@ def data_path( class BI2014b(BaseDataset): """P300 dataset BI2014b from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - ================ ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ================ ======= ======= ================ =============== =============== =========== - BI2014b 38 32 5 NT x 1 T 1s 512Hz 3 - ================ ======= ======= ================ =============== =============== =========== - This dataset contains electroencephalographic (EEG) recordings of 38 subjects playing in pair (19 pairs) to the multi-user version of a visual P300-based Brain-Computer Interface (BCI) named Brain Invaders. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, @@ -705,13 +675,6 @@ def data_path( class BI2015a(BaseDataset): """P300 dataset BI2015a from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - ================ ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ================ ======= ======= ================ =============== =============== =========== - BI2015a 43 32 5 NT x 1 T 1s 512Hz 3 - ================ ======= ======= ================ =============== =============== =========== - This dataset contains electroencephalographic (EEG) recordings of 43 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named Brain Invaders. The interface uses the oddball paradigm @@ -766,13 +729,6 @@ def data_path( class BI2015b(BaseDataset): """P300 dataset BI2015b from a "Brain Invaders" experiment. - .. admonition:: Dataset summary - ================ ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ================ ======= ======= ================ =============== =============== =========== - BI2015b 44 32 5 NT x 1 T 1s 512Hz 1 - ================ ======= ======= ================ =============== =============== =========== - This dataset contains electroencephalographic (EEG) recordings of 44 subjects playing in pair to the multi-user version of a visual P300 Brain-Computer Interface (BCI) named Brain Invaders. The interface @@ -830,13 +786,6 @@ def data_path( class Cattan2019_VR(BaseDataset): """Dataset of an EEG-based BCI experiment in Virtual Reality using P300. - .. admonition:: Dataset summary - ============== ======= ======= ================ =============== =============== =========== - Name #Subj #Chan #Trials/class Trials length Sampling Rate #Sessions - ============== ======= ======= ================ =============== =============== =========== - Cattan2019_VR 21 16 600 NT / 120 T 1s 512Hz 2 - ============== ======= ======= ================ =============== =============== =========== - We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.2605204 in mat (Mathworks, Natick, USA) and csv formats [1]_. This dataset contains electroencephalographic recordings on 21 diff --git a/moabb/datasets/castillos2023.py b/moabb/datasets/castillos2023.py index 2f077c4e2..9e2108ab4 100644 --- a/moabb/datasets/castillos2023.py +++ b/moabb/datasets/castillos2023.py @@ -293,14 +293,6 @@ class CastillosBurstVEP100(BaseCastillos2023): Dataset [1]_ from the study on burst-VEP [2]_. - .. admonition:: Dataset summary - - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - CastillosBurstVEP100 12 1 500Hz 32 2.2s 4 15/15/15/15 2 5820NT/1200T Burst-CVEP 60Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - **Dataset description** Participants were comfortably seated and instructed to read and sign the informed consent. EEG data were recorded @@ -355,14 +347,6 @@ class CastillosBurstVEP40(BaseCastillos2023): Dataset [1]_ from the study on burst-VEP [2]_. - .. admonition:: Dataset summary - - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - CastillosBurstVEP40 12 1 500Hz 32 2.2s 4 15/15/15/15 2 5820NT/1200T Burst-CVEP 60Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - **Dataset description** Participants were comfortably seated and instructed to read and sign the informed consent. EEG data were recorded @@ -417,15 +401,6 @@ class CastillosCVEP100(BaseCastillos2023): Dataset [1]_ from the study on burst-VEP [2]_. - .. admonition:: Dataset summary - - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - CastillosCVEP100 12 1 500Hz 32 2.2s 4 15/15/15/15 2 3525NT/3495T m-sequence 60Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - - **Dataset description** Participants were comfortably seated and instructed to read and sign the informed consent. EEG data were recorded @@ -480,13 +455,6 @@ class CastillosCVEP40(BaseCastillos2023): Dataset [1]_ from the study on burst-VEP [2]_. - .. admonition:: Dataset summary - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - CastillosCVEP40 12 1 500Hz 32 2.2s 4 15/15/15/15 2 3525NT/3495T m-sequence 60Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== =============== ========== ================= - **Dataset description** Participants were comfortably seated and instructed to read and sign the informed consent. EEG data were recorded diff --git a/moabb/datasets/epfl.py b/moabb/datasets/epfl.py index 2f190ba9d..68d6d726f 100644 --- a/moabb/datasets/epfl.py +++ b/moabb/datasets/epfl.py @@ -18,15 +18,6 @@ class EPFLP300(BaseDataset): """P300 dataset from Hoffmann et al 2008. - .. admonition:: Dataset summary - - - ======== ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ======== ======= ======= ================= =============== =============== =========== - EPFLP300 8 32 2753 NT / 551 T 1s 2048Hz 4 - ======== ======= ======= ================= =============== =============== =========== - Dataset from the paper [1]_. **Dataset Description** diff --git a/moabb/datasets/gigadb.py b/moabb/datasets/gigadb.py index dada960da..e3624f21c 100644 --- a/moabb/datasets/gigadb.py +++ b/moabb/datasets/gigadb.py @@ -19,15 +19,6 @@ class Cho2017(BaseDataset): """Motor Imagery dataset from Cho et al 2017. - .. admonition:: Dataset summary - - - ======= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ======= ======= ======= ========== ================= ============ =============== =========== - Cho2017 52 64 2 100 3s 512Hz 1 - ======= ======= ======= ========== ================= ============ =============== =========== - Dataset from the paper [1]_. **Dataset Description** diff --git a/moabb/datasets/hinss2021.py b/moabb/datasets/hinss2021.py index a21608e63..f5c97e202 100644 --- a/moabb/datasets/hinss2021.py +++ b/moabb/datasets/hinss2021.py @@ -17,14 +17,6 @@ class Hinss2021(BaseDataset): """Neuroergonomic 2021 dataset. - .. admonition:: Dataset summary - - =========== ======= ======= ========== =============== ============ =============== =========== - Name #Subj #Chan #Classes #Blocks/class Trials len Sampling rate #Sessions - =========== ======= ======= ========== =============== ============ =============== =========== - Hinss2021 15 62 4 1 2s 250Hz 2 - =========== ======= ======= ========== =============== ============ =============== =========== - We describe the experimental procedures for a dataset that is publicly available at https://zenodo.org/records/5055046. This dataset contains electroencephalographic recordings of 15 subjects (6 female, with an diff --git a/moabb/datasets/huebner_llp.py b/moabb/datasets/huebner_llp.py index a75d51e86..1e00abd43 100644 --- a/moabb/datasets/huebner_llp.py +++ b/moabb/datasets/huebner_llp.py @@ -117,15 +117,6 @@ class Huebner2017(_BaseVisualMatrixSpellerDataset): """Learning from label proportions for a visual matrix speller (ERP) dataset from Hübner et al 2017 [1]_. - .. admonition:: Dataset summary - - - =========== ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - =========== ======= ======= ================= =============== =============== =========== - Huebner2017 13 31 364 NT / 112 T 0.9s 1000Hz 3 - =========== ======= ======= ================= =============== =============== =========== - **Dataset description** The subjects were asked to spell the sentence: “Franzy jagt im komplett verwahrlosten Taxi quer durch Freiburg”. @@ -184,15 +175,6 @@ class Huebner2018(_BaseVisualMatrixSpellerDataset): """Mixture of LLP and EM for a visual matrix speller (ERP) dataset from Hübner et al 2018 [1]_. - .. admonition:: Dataset summary - - - =========== ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - =========== ======= ======= ================= =============== =============== =========== - Huebner2018 12 31 364 NT / 112 T 0.9s 1000Hz 3 - =========== ======= ======= ================= =============== =============== =========== - **Dataset description** Within a single session, a subject was asked to spell the beginning of a sentence in each of three blocks.The text diff --git a/moabb/datasets/liu2024.py b/moabb/datasets/liu2024.py new file mode 100644 index 000000000..82dbf4af6 --- /dev/null +++ b/moabb/datasets/liu2024.py @@ -0,0 +1,340 @@ +"""Liu2024 Motor imagery dataset.""" + +import os +import shutil +import warnings +import zipfile as z +from pathlib import Path +from typing import Any, Dict, Tuple + +import mne +import numpy as np +import pandas as pd +from mne.channels import read_custom_montage + +from moabb.datasets import download as dl +from moabb.datasets.base import BaseDataset + + +# Link to the raw data +LIU2024_URL = "https://figshare.com/ndownloader/files/38516654" + +# Links to the electrodes and events information files +LIU2024_ELECTRODES = "https://figshare.com/ndownloader/files/38516078" +LIU2024_EVENTS = "https://figshare.com/ndownloader/files/38516084" + + +class Liu2024(BaseDataset): + """ + + Dataset [1]_ from the study on motor imagery [2]_. + + **Dataset description** + This dataset includes data from 50 acute stroke patients (the time after stroke ranges from 1 day to 30 days) + admitted to the stroke unit of Xuanwu Hospital of Capital Medical University. The patients included 39 males (78%) + and 11 females (22%), aged between 31 and 77 years, with an average age of 56.70 years (SD = 10.57) + Before the start of the experiment, the subject sat in a chair in a position as comfortable as possible with an + EEG cap placed on their head; subjects were positioned approximately 80 cm away from a computer screen in front of them. + The computer played audio instructions to the patient about the procedure. Each experiment lasted approximately 20 minutes, + including preparation time and approximately 10 minutes of signal recording. Before the start of the MI experiment, + the patients opened their eyes and closed their eyes for 1 minute each. The MI experiment was divided into 40 trials, and + each trial took 8 seconds, which consisted of three stages (instruction, MI and break). In the instruction stage, patients + were prompted to imagine grasping a spherical object with the left- or right-hand. In the MI stage, participants imagined + performing this action, a video of gripping motion is played on the computer, which leads the patient imagine grabbing the + ball. This video stays playing for 4 s. Patients only imagine one hand movement.In the break stage, participants were allowed + to relax and rest. The MI experiments alternated between the left- and right-hand, and the patients moved onto the next stage + of the experiment according to the instructions. + + The EEG data were collected through a wireless multichannel EEG acquisition system (ZhenTec NT1, Xi’an ZhenTec Intelligence + Technology Co., Ltd., China). The system includes an EEG cap, an EEG acquisition amplifier, a data receiver and host computer + software. The EEG cap had electrodes placed according to the international 10-10 system, including 29 EEG recording electrodes + and 2 electrooculography (EOG) electrodes. The reference electrode located at CPz position and the grounding electrode located + at FPz position. All the EEG electrodes and grounding electrode are Ag/AgCl semi-dry EEG electrodes based on highly absorbable + porous sponges that are dampened with 3% NaCl solution. The EOG electrodes are composed by Ag/AgCl electrodes and conductive + adhesive hydrogel. The common-mode rejection ratio was 120 dB, the input impedance was 1 GΩ, the input noise was less than + 0.4 μVrms, and the resolution was 24 bits. The acquisition impedance was less than or equal to 20 kΩ. The sampling frequency + was 500 Hz. + + References + ---------- + + .. [1] Liu, Haijie; Lv, Xiaodong (2022). EEG datasets of stroke patients. + figshare. Dataset. DOI: https://doi.org/10.6084/m9.figshare.21679035.v5 + + .. [2] Liu, Haijie, Wei, P., Wang, H. et al. An EEG motor imagery dataset + for brain computer interface in acute stroke patients. Sci Data 11, 131 + (2024). DOI: https://doi.org/10.1038/s41597-023-02787-8 + + Notes + ----- + To add the break and instruction events, set the `break_events` and + `instr_events` parameters to True while instantiating the class. + + .. versionadded:: 1.1.1 + + """ + + def __init__(self, break_events=False, instr_events=False): + self.break_events = break_events + self.instr_events = instr_events + events = {"left_hand": 1, "right_hand": 2} + if break_events: + events["instr"] = 3 + if instr_events: + events["break"] = 4 + super().__init__( + subjects=list(range(1, 50 + 1)), + sessions_per_subject=1, + events=events, + code="Liu2024", + interval=(2, 6), + paradigm="imagery", + doi="10.1038/s41597-023-02787-8", + ) + + def data_path( + self, subject, path=None, force_update=False, update_path=None, verbose=None + ): + """Return the data paths of a single subject. + + Parameters + ---------- + subject : int + The subject number to fetch data for. + path : None | str + Location of where to look for the data storing location. If None, + the environment variable or config parameter MNE_(dataset) is used. + If it doesn’t exist, the “~/mne_data” directory is used. If the + dataset is not found under the given path, the data + will be automatically downloaded to the specified folder. + force_update : bool + Force update of the dataset even if a local copy exists. + update_path : bool | None + If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config + to the given path. + If None, the user is prompted. + verbose : bool, str, int, or None + If not None, override default verbose level (see mne.verbose()). + + Returns + ------- + list + A list containing the path to the subject's data file. + """ + if subject not in self.subject_list: + raise ValueError("Invalid subject number") + + # Download the zip file containing the data + path_zip = dl.data_dl(LIU2024_URL, self.code) + path_zip = Path(path_zip) + path_folder = path_zip.parent + + # Extract the zip file if it hasn't been extracted yet + if not (path_folder / "edffile").is_dir(): + zip_ref = z.ZipFile(path_zip, "r") + zip_ref.extractall(path_folder) + + subject_paths = [] + sub = f"sub-{subject:02d}" + + # Construct the path to the subject's data file + subject_path = ( + path_folder / "edffile" / sub / "eeg" / f"{sub}_task-motor-imagery_eeg.edf" + ) + subject_paths.append(str(subject_path)) + + return subject_paths + + def encoding(self, events_df: pd.DataFrame) -> Tuple[np.array, Dict[int, str]]: + """Encode the columns 'value' and 'trial_type' into a single event type. + + Parameters + ---------- + events_df : pd.DataFrame + DataFrame containing the events information. + + Returns + ------- + np.ndarray + Array of encoded event types. + + Notes + ----- + The 'trial_type' variable can take the following values: + - 1 : Left hand + - 2 : Right hand + + The 'value' variable can take the following values: + - 1 : instructions + - 2 : MI + - 3 : break + + """ + # Define the mapping dictionary + encoding_mapping = { + (2, 2): 1, # Left hand, MI + (1, 2): 2, # Right hand, MI + } + + mapping = { + 1: "left_hand", + 2: "right_hand", + } + + if self.instr_events: + encoding_mapping.update( + { + (1, 1): 3, # Right hand, instructions + (2, 1): 3, # Left hand, instructions + } + ) + mapping[3] = "instr" + + if self.break_events: + encoding_mapping.update( + { + (1, 3): 4, # Right hand, break + (2, 3): 4, # Left hand, break + } + ) + mapping[4] = "break" + + # Filter out rows that won't be encoded + valid_tuples = encoding_mapping.keys() + events_df = events_df[ + events_df.apply( + lambda row: (row["trial_type"], row["value"]) in valid_tuples, axis=1 + ) + ] + + # Apply the mapping to the DataFrame + event_category = events_df.apply( + lambda row: encoding_mapping[(row["trial_type"], row["value"])], axis=1 + ) + + return event_category, mapping + + def _get_single_subject_data(self, subject): + """Return the data of a single subject. + + Parameters + ---------- + subject : int + The subject number to fetch data for. + + Returns + ------- + dict + A dictionary containing the raw data for the subject. + """ + + file_path_list = self.data_path(subject)[0] + path_electrodes, path_events = self.data_infos() + + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + # Read the subject's raw data + raw = mne.io.read_raw_edf( + file_path_list, verbose=False, infer_types=True, stim_channel="" + ) + + # Dropping reference channels with constant values + raw = raw.drop_channels(["CPz"]) + + # Renaming channels accurately + raw.rename_channels({"HEOR": "VEOR", "": "STI"}) + + # Create a dictionary with the channel names and their new types + mapping = {"STI": "stim", "VEOR": "eog", "HEOL": "eog"} + + # Set the new channel types + raw.set_channel_types(mapping) + + # Normalize and Read the montage + path_electrodes = self._normalize_extension(path_electrodes) + # Read and set the montage + montage = read_custom_montage(path_electrodes) + + events_df = pd.read_csv(path_events, sep="\t") + + # Encode the events + event_category, mapping = self.encoding(events_df=events_df) + + events = self.create_event_array(raw=raw, event_category=event_category) + + # Creating and setting annotations from the events + annotations = mne.annotations_from_events( + events, sfreq=raw.info["sfreq"], event_desc=mapping + ) + + raw = raw.set_annotations(annotations) + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + # Removing the stimulus channels + raw = raw.pick(["eeg", "eog"]) + # Setting the montage + raw = raw.set_montage(montage, verbose=False) + # Loading dataset + raw = raw.load_data(verbose=False) + # There is only one session + sessions = {"0": {"0": raw}} + + return sessions + + def data_infos(self): + """Returns the data paths of the electrodes and events information + + This function downloads the necessary data files for electrodes + and events from their respective URLs and returns their local file paths. + + Returns + ------- + tuple + A tuple containing the local file paths to the channels, electrodes, + and events information files. + """ + + path_electrodes = dl.data_dl(LIU2024_ELECTRODES, self.code) + + path_events = dl.data_dl(LIU2024_EVENTS, self.code) + + return path_electrodes, path_events + + @staticmethod + def _normalize_extension(file_name: str) -> str: + # Renaming the .tsv file to make sure it's recognized as .tsv + # Check if the file already has the ".tsv" extension + + file_electrodes_tsv = file_name + ".tsv" + + if not os.path.exists(file_electrodes_tsv): + # Perform the rename operation only if the target file + # doesn't exist + shutil.copy(file_name, file_electrodes_tsv) + + return file_electrodes_tsv + + @staticmethod + def create_event_array(raw: Any, event_category: np.ndarray) -> np.ndarray: + """ + This method creates an event array based on the stimulus channel. + + Parameters + ---------- + raw : mne.io.Raw + The raw data. + event_category : np.ndarray + The event categories. + + Returns + ------- + events : np.ndarray + The created events array. + """ + _, idx_trigger = np.nonzero(raw.copy().pick("STI").get_data()) + n_label_stim = len(event_category) + # Create the events array based on the stimulus channel + events = np.column_stack( + (idx_trigger[:n_label_stim], np.zeros_like(event_category), event_category) + ) + return events diff --git a/moabb/datasets/mpi_mi.py b/moabb/datasets/mpi_mi.py index 5a89fb635..06e8bd366 100644 --- a/moabb/datasets/mpi_mi.py +++ b/moabb/datasets/mpi_mi.py @@ -15,15 +15,6 @@ class GrosseWentrup2009(BaseDataset): """Munich Motor Imagery dataset. - .. admonition:: Dataset summary - - - ================= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ================= ======= ======= ========== ================= ============ =============== =========== - GrosseWentrup2009 10 128 2 150 7s 500Hz 1 - ================= ======= ======= ========== ================= ============ =============== =========== - Motor imagery dataset from Grosse-Wentrup et al. 2009 [1]_. A trial started with the central display of a white fixation cross. After 3 diff --git a/moabb/datasets/neiry.py b/moabb/datasets/neiry.py index 79640c2c9..edc96cbc8 100644 --- a/moabb/datasets/neiry.py +++ b/moabb/datasets/neiry.py @@ -15,15 +15,6 @@ class DemonsP300(BaseDataset): """Visual P300 dataset recorded in Virtual Reality (VR) game Raccoons versus Demons. - .. admonition:: Dataset summary - - - ========== ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ========== ======= ======= ================= =============== =============== =========== - DemonsP300 60 8 935 NT / 50 T 1s 500Hz 1 - ========== ======= ======= ================= =============== =============== =========== - .. danger:: This dataset contains major unresolved issues and could removed in the near futur. Use it in a benchmark diff --git a/moabb/datasets/phmd_ml.py b/moabb/datasets/phmd_ml.py index 8076f94e8..e066965af 100644 --- a/moabb/datasets/phmd_ml.py +++ b/moabb/datasets/phmd_ml.py @@ -17,15 +17,6 @@ class Cattan2019_PHMD(BaseDataset): """Passive Head Mounted Display with Music Listening dataset. - .. admonition:: Dataset summary - - - ============== ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Blocks/class Trials len Sampling rate #Sessions - =============== ======= ======= ========== ================= ============ =============== =========== - Cattan2019_PHMD 12 16 2 10 60s 512Hz 1 - =============== ======= ======= ========== ================= ============ =============== =========== - We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.2617084 in mat (Mathworks, Natick, USA) and csv formats. This dataset contains electroencephalographic recordings of 12 subjects listening to music diff --git a/moabb/datasets/physionet_mi.py b/moabb/datasets/physionet_mi.py index 1f2f977a3..3367c9cf3 100644 --- a/moabb/datasets/physionet_mi.py +++ b/moabb/datasets/physionet_mi.py @@ -14,15 +14,6 @@ class PhysionetMI(BaseDataset): """Physionet Motor Imagery dataset. - .. admonition:: Dataset summary - - - =========== ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - =========== ======= ======= ========== ================= ============ =============== =========== - PhysionetMI 109 64 4 23 3s 160Hz 1 - =========== ======= ======= ========== ================= ============ =============== =========== - Physionet MI dataset: https://physionet.org/pn4/eegmmidb/ This data set consists of over 1500 one- and two-minute EEG recordings, diff --git a/moabb/datasets/schirrmeister2017.py b/moabb/datasets/schirrmeister2017.py index 6a652e4fa..2f5ceff88 100644 --- a/moabb/datasets/schirrmeister2017.py +++ b/moabb/datasets/schirrmeister2017.py @@ -17,15 +17,6 @@ class Schirrmeister2017(BaseDataset): """High-gamma dataset described in Schirrmeister et al. 2017. - .. admonition:: Dataset summary - - - ================= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ================= ======= ======= ========== ================= ============ =============== =========== - Schirrmeister2017 14 128 4 120 4s 500Hz 1 - ================= ======= ======= ========== ================= ============ =============== =========== - Dataset from [1]_ Our “High-Gamma Dataset” is a 128-electrode dataset (of which we later only use diff --git a/moabb/datasets/sosulski2019.py b/moabb/datasets/sosulski2019.py index 75666561a..ade789445 100644 --- a/moabb/datasets/sosulski2019.py +++ b/moabb/datasets/sosulski2019.py @@ -19,15 +19,6 @@ class Sosulski2019(BaseDataset): Dataset [1]_, study on spatial transfer between SOAs [2]_, actual paradigm / online optimization [3]_. - .. admonition:: Dataset summary - - - ============= ======= ======= ================= =============== =============== =========== - Name #Subj #Chan #Trials / class Trials length Sampling rate #Sessions - ============= ======= ======= ================= =============== =============== =========== - Sosulski2019 13 31 7500 NT / 1500 T 1.2s 1000Hz 1 - ============= ======= ======= ================= =============== =============== =========== - **Dataset description** This dataset contains multiple small trials of an auditory oddball paradigm. The paradigm presented two different sinusoidal tones. A low-pitched (500 Hz, 40 ms duration) non-target tone and a high-pitched (1000 Hz, diff --git a/moabb/datasets/ssvep_exo.py b/moabb/datasets/ssvep_exo.py index a63718bde..7df04fc1e 100644 --- a/moabb/datasets/ssvep_exo.py +++ b/moabb/datasets/ssvep_exo.py @@ -15,15 +15,6 @@ class Kalunga2016(BaseDataset): """SSVEP Exo dataset. - .. admonition:: Dataset summary - - - =========== ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - =========== ======= ======= ========== ================= =============== =============== =========== - Kalunga2016 12 8 4 16 2s 256Hz 1 - =========== ======= ======= ========== ================= =============== =============== =========== - SSVEP dataset from E. Kalunga PhD in University of Versailles [1]_. The datasets contains recording from 12 male and female subjects aged diff --git a/moabb/datasets/ssvep_mamem.py b/moabb/datasets/ssvep_mamem.py index 5c8412412..7a7cec0a5 100644 --- a/moabb/datasets/ssvep_mamem.py +++ b/moabb/datasets/ssvep_mamem.py @@ -170,15 +170,6 @@ def data_path( class MAMEM1(BaseMAMEM): """SSVEP MAMEM 1 dataset. - .. admonition:: Dataset summary - - - ====== ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ====== ======= ======= ========== ================= =============== =============== =========== - MAMEM1 10 256 5 12-15 3s 250Hz 1 - ====== ======= ======= ========== ================= =============== =============== =========== - Dataset from [1]_. EEG signals with 256 channels captured from 11 subjects executing a @@ -290,15 +281,6 @@ def __init__(self): class MAMEM2(BaseMAMEM): """SSVEP MAMEM 2 dataset. - .. admonition:: Dataset summary - - - ====== ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ====== ======= ======= ========== ================= =============== =============== =========== - MAMEM2 10 256 5 20-30 3s 250Hz 1 - ====== ======= ======= ========== ================= =============== =============== =========== - Dataset from [1]_. EEG signals with 256 channels captured from 11 subjects executing a @@ -383,15 +365,6 @@ def __init__(self): class MAMEM3(BaseMAMEM): """SSVEP MAMEM 3 dataset. - .. admonition:: Dataset summary - - - ====== ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ====== ======= ======= ========== ================= =============== =============== =========== - MAMEM3 10 14 4 20-30 3s 128Hz 1 - ====== ======= ======= ========== ================= =============== =============== =========== - Dataset from [1]_. EEG signals with 14 channels captured from 11 subjects executing a diff --git a/moabb/datasets/ssvep_nakanishi.py b/moabb/datasets/ssvep_nakanishi.py index 415368d3a..89d8d0dbc 100644 --- a/moabb/datasets/ssvep_nakanishi.py +++ b/moabb/datasets/ssvep_nakanishi.py @@ -20,15 +20,6 @@ class Nakanishi2015(BaseDataset): """SSVEP Nakanishi 2015 dataset. - .. admonition:: Dataset summary - - - ============= ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ============= ======= ======= ========== ================= =============== =============== =========== - Nakanishi2015 9 8 12 15 4.15s 256Hz 1 - ============= ======= ======= ========== ================= =============== =============== =========== - This dataset contains 12-class joint frequency-phase modulated steady-state visual evoked potentials (SSVEPs) acquired from 10 subjects used to estimate an online performance of brain-computer interface (BCI) in the diff --git a/moabb/datasets/ssvep_wang.py b/moabb/datasets/ssvep_wang.py index ea7af02a5..e1b7111ba 100644 --- a/moabb/datasets/ssvep_wang.py +++ b/moabb/datasets/ssvep_wang.py @@ -24,15 +24,6 @@ class Wang2016(BaseDataset): """SSVEP Wang 2016 dataset. - .. admonition:: Dataset summary - - - ======== ======= ======= ========== ================= =============== =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials length Sampling rate #Sessions - ======== ======= ======= ========== ================= =============== =============== =========== - Wang2016 34 62 40 6 5s 250Hz 1 - ======== ======= ======= ========== ================= =============== =============== =========== - Dataset from [1]_. This dataset gathered SSVEP-BCI recordings of 35 healthy subjects (17 diff --git a/moabb/datasets/stieger2021.py b/moabb/datasets/stieger2021.py index 3d11e29c7..808e4ccb3 100644 --- a/moabb/datasets/stieger2021.py +++ b/moabb/datasets/stieger2021.py @@ -24,15 +24,6 @@ class Stieger2021(BaseDataset): """Motor Imagery dataset from Stieger et al. 2021. - .. admonition:: Dataset summary - - - ============= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ============= ======= ======= ========== ================= ============ =============== =========== - Stieger2021 62 64 4 450 3s 1000Hz 10 - ============= ======= ======= ========== ================= ============ =============== =========== - The main goals of our original study were to characterize how individuals learn to control SMR-BCIs and to test whether this learning can be improved through behavioral interventions such as mindfulness training. Participants @@ -236,8 +227,9 @@ def _get_single_subject_data(self, subject): and (container.TrialData[i].triallength + 2) > self.interval[1] ): # this should be the cue time-point - if container.time[i][2 * srate] == 0: - raise ValueError("This should be the cue time-point,") + assert ( + container.time[i][2 * srate] == 0 + ), "This should be the cue time-point" stim[2 * srate] = y X_flat.append(x) stim_flat.append(stim[None, :]) @@ -272,7 +264,11 @@ def _get_single_subject_data(self, subject): badchanidxs = [] for idx in badchanidxs: - used_channels = ch_names if self.channels is None else self.channels + used_channels = ( + ch_names + if (not hasattr(self, "channels") or self.channels is None) + else self.channels + ) if eeg_ch_names[idx - 1] in used_channels: raw.info["bads"].append(eeg_ch_names[idx - 1]) @@ -285,5 +281,5 @@ def _get_single_subject_data(self, subject): bad_info=raw.info["bads"], ) - subject_data[session] = {"run_0": raw} + subject_data[str(session)] = {"0": raw} return subject_data diff --git a/moabb/datasets/summary_cvep.csv b/moabb/datasets/summary_cvep.csv new file mode 100644 index 000000000..18d8bee4b --- /dev/null +++ b/moabb/datasets/summary_cvep.csv @@ -0,0 +1,7 @@ +Dataset, #Subj, #Sessions, Sampling rate, #Chan, Trials length, #Trial classes, #Trials / class, #Epochs classes, #Epochs / class, Codes, Presentation rate, PapersWithCode leaderboard +Thielen2015,12,1,2048Hz,64,4.2s,36,3,2,27216 NT / 27216 T,Gold codes,120Hz, +Thielen2021,30,1,512Hz,8,31.5s,20,5,2,18900 NT / 18900 T,Gold codes,60Hz, +CastillosCVEP100, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,3525 NT / 3495 T,m-sequence,60Hz, +CastillosCVEP40, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,3525 NT / 3495 T,m-sequence,60Hz, +CastillosBurstVEP40, 12,1,500Hz,32,2.2s,4,15/15/15/15,2,5820 NT / 1200 T,Burst-CVEP,60Hz, +CastillosBurstVEP100,12,1,500Hz,32,2.2s,4,15/15/15/15,2,5820 NT / 1200 T,Burst-CVEP,60Hz, diff --git a/moabb/datasets/summary_imagery.csv b/moabb/datasets/summary_imagery.csv new file mode 100644 index 000000000..389615cc4 --- /dev/null +++ b/moabb/datasets/summary_imagery.csv @@ -0,0 +1,19 @@ +Dataset, #Subj, #Chan, #Classes, #Trials, Trial length, Freq, #Session, #Runs, Total_trials, PapersWithCode leaderboard +AlexMI,8,16,3,20,3s,512Hz,1,1,480,https://paperswithcode.com/dataset/alexandremotorimagery-moabb +BNCI2014_001,9,22,4,144,4s,250Hz,2,6,62208,https://paperswithcode.com/dataset/bnci2014-001-moabb-1 +BNCI2014_002,14,15,2,80,5s,512Hz,1,8,17920,https://paperswithcode.com/dataset/bnci2014-002-moabb-1 +BNCI2014_004,9,3,2,360,4.5s,250Hz,5,1,32400,https://paperswithcode.com/dataset/bnci2014-004-moabb-1 +BNCI2015_001,12,13,2,200,5s,512Hz,3,1,14400,https://paperswithcode.com/dataset/bnci2015-001-moabb-1 +BNCI2015_004,9,30,5,80,7s,256Hz,2,1,7200,https://paperswithcode.com/dataset/bnci2015-004-moabb-1 +Cho2017,52,64,2,100,3s,512Hz,1,1,9800,https://paperswithcode.com/dataset/cho2017-moabb +Lee2019_MI,54,62,2,100,4s,1000Hz,2,1,11000,https://paperswithcode.com/dataset/lee2019-mi-moabb-1 +GrosseWentrup2009,10,128,2,150,7s,500Hz,1,1,3000,https://paperswithcode.com/dataset/grossewentrup2009-moabb +Schirrmeister2017,14,128,4,120,4s,500Hz,1,2,13440,https://paperswithcode.com/dataset/schirrmeister2017-moabb +Ofner2017,15,61,7,60,3s,512Hz,1,10,63000, +PhysionetMI,109,64,4,23,3s,160Hz,1,1,69760,https://paperswithcode.com/dataset/physionetmotorimagery-moabb +Shin2017A,29,30,2,30,10s,200Hz,3,1,5220,https://paperswithcode.com/dataset/shin2017a-moabb +Shin2017B,29,30,2,30,10s,200Hz,3,1,5220, +Weibo2014,10,60,7,80,4s,200Hz,1,1,5600,https://paperswithcode.com/dataset/weibo2014-moabb +Zhou2016,4,14,3,160,5s,250Hz,3,2,11496,https://paperswithcode.com/dataset/zhou2016-moabb +Stieger2021,62,64,4,450,3s,1000Hz,7 or 11,1,250000, +Liu2024,50,29,2,20,4s,500Hz,1,1,2000, diff --git a/moabb/datasets/summary_p300.csv b/moabb/datasets/summary_p300.csv new file mode 100644 index 000000000..d3248fe3a --- /dev/null +++ b/moabb/datasets/summary_p300.csv @@ -0,0 +1,17 @@ +Dataset, #Subj, #Chan, #Trials / class, Trials length, Sampling rate, #Sessions, PapersWithCode leaderboard +BNCI2014_008, 8, 8, 3500 NT / 700 T, 1s, 256Hz, 1,https://paperswithcode.com/dataset/bnci2014-008-moabb-1 +BNCI2014_009, 10, 16, 1440 NT / 288 T, 0.8s, 256Hz, 3,https://paperswithcode.com/dataset/bnci2014-009-moabb-1 +BNCI2015_003, 10, 8, 1500 NT / 300 T, 0.8s, 256Hz, 1,https://paperswithcode.com/dataset/bnci2015-003-moabb-1 +BI2012, 25, 16, 640 NT / 128 T, 1s, 128Hz, 2,https://paperswithcode.com/dataset/braininvaders2012-moabb +BI2013a, 24, 16, 3200 NT / 640 T, 1s, 512Hz, 8 for subjects 1-7 else 1,https://paperswithcode.com/dataset/braininvaders2013a-moabb +BI2014a, 64, 16, 990 NT / 198 T, 1s, 512Hz, up to 3,https://paperswithcode.com/dataset/braininvaders2014a-moabb +BI2014b, 38, 32, 200 NT / 40 T, 1s, 512Hz, 3,https://paperswithcode.com/dataset/braininvaders2014b-moabb +BI2015a, 43, 32, 4131 NT / 825 T, 1s, 512Hz, 3,https://paperswithcode.com/dataset/braininvaders2015a-moabb +BI2015b, 44, 32, 2160 NT / 480 T, 1s, 512Hz, 1,https://paperswithcode.com/dataset/braininvaders2015b-moabb +Cattan2019_VR, 21, 16, 600 NT / 120 T, 1s, 512Hz, 2,https://paperswithcode.com/dataset/cattan2019-vr-moabb-1 +Huebner2017, 13, 31, 364 NT / 112 T, 0.9s, 1000Hz, 3,https://paperswithcode.com/dataset/huebner2017-moabb +Huebner2018, 12, 31, 364 NT / 112 T, 0.9s, 1000Hz, 3,https://paperswithcode.com/dataset/huebner2018-moabb +Sosulski2019, 13, 31, 7500 NT / 1500 T, 1.2s, 1000Hz, 1,https://paperswithcode.com/dataset/sosulski2019-moabb +EPFLP300, 8, 32, 2753 NT / 551 T, 1s, 2048Hz, 4,https://paperswithcode.com/dataset/epflp300-moabb +Lee2019_ERP, 54, 62, 6900 NT / 1380 T, 1s, 1000Hz, 2,https://paperswithcode.com/dataset/lee2019-erp-moabb-1 +DemonsP300, 60, 8, 935 NT / 50 T, 1s, 500Hz, 1, diff --git a/moabb/datasets/summary_rstate.csv b/moabb/datasets/summary_rstate.csv new file mode 100644 index 000000000..7c371fa0e --- /dev/null +++ b/moabb/datasets/summary_rstate.csv @@ -0,0 +1,4 @@ +Dataset, #Subj, #Chan, #Classes, #Blocks / class, Trials length, Sampling rate, #Sessions, PapersWithCode leaderboard +Cattan2019_PHMD,12,16,2,10,60s,512Hz,1, +Hinss2021,15,62,4,1,2s,250Hz,1, +Rodrigues2017,20,16,2,5,10s,512Hz,1, diff --git a/moabb/datasets/summary_ssvep.csv b/moabb/datasets/summary_ssvep.csv new file mode 100644 index 000000000..5e5d9ef5c --- /dev/null +++ b/moabb/datasets/summary_ssvep.csv @@ -0,0 +1,8 @@ +Dataset, #Subj, #Chan, #Classes, #Trials / class, Trials length, Sampling rate, #Sessions, PapersWithCode leaderboard +Lee2019_SSVEP,54,62,4,50,4s,1000Hz,2,https://paperswithcode.com/dataset/lee2019-ssvep-moabb-1 +Kalunga2016,12,8,4,16,2s,256Hz,1,https://paperswithcode.com/dataset/kalunga2016-moabb +MAMEM1,10,256,5,12-15,3s,250Hz,1,https://paperswithcode.com/dataset/mamem1-moabb +MAMEM2,10,256,5,20-30,3s,250Hz,1,https://paperswithcode.com/dataset/mamem2-moabb +MAMEM3,10,14,4,20-30,3s,128Hz,1,https://paperswithcode.com/dataset/mamem3-moabb +Nakanishi2015,9,8,12,15,4.15s,256Hz,1,https://paperswithcode.com/dataset/nakanishi2015-moabb +Wang2016,34,62,40,6,5s,250Hz,1,https://paperswithcode.com/dataset/wang2016-moabb diff --git a/moabb/datasets/thielen2015.py b/moabb/datasets/thielen2015.py index b5e051f45..151fee6ef 100644 --- a/moabb/datasets/thielen2015.py +++ b/moabb/datasets/thielen2015.py @@ -24,15 +24,6 @@ class Thielen2015(BaseDataset): Dataset [1]_ from the study on reconvolution for c-VEP [2]_. - .. admonition:: Dataset summary - - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - Thielen2015 12 1 2048Hz 64 4.2s 36 3 2 27216 NT / 27216 T Gold codes 120Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - - **Dataset description** EEG recordings were obtained with a sampling rate of 2048 Hz, using a setup comprising 64 Ag/AgCl electrodes, and diff --git a/moabb/datasets/thielen2021.py b/moabb/datasets/thielen2021.py index c46ea1aa7..f8c5c01d0 100644 --- a/moabb/datasets/thielen2021.py +++ b/moabb/datasets/thielen2021.py @@ -74,14 +74,6 @@ class Thielen2021(BaseDataset): Dataset [1]_ from the study on zero-training c-VEP [2]_. - .. admonition:: Dataset summary - - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - Name #Subj #Sessions Sampling rate #Chan Trials length #Trial classes #Trials / class #Epoch classes #Epochs / class Codes Presentation rate - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - Thielen2021 30 1 512Hz 8 31.5s 20 5 2 94500 NT / 94500 T Gold codes 60Hz - ==================== ======= ========= ============= ===== ============= ============== =============== ============== ================== ========== ================= - **Dataset description** EEG recordings were acquired at a sampling rate of 512 Hz, employing 8 Ag/AgCl electrodes. The Biosemi ActiveTwo EEG diff --git a/moabb/datasets/upper_limb.py b/moabb/datasets/upper_limb.py index 68286c198..f10db8ccd 100644 --- a/moabb/datasets/upper_limb.py +++ b/moabb/datasets/upper_limb.py @@ -13,15 +13,6 @@ class Ofner2017(BaseDataset): """Motor Imagery ataset from Ofner et al 2017. - .. admonition:: Dataset summary - - - ========= ======= ======= ========== ================= ============ =============== =========== - Name #Subj #Chan #Classes #Trials / class Trials len Sampling rate #Sessions - ========= ======= ======= ========== ================= ============ =============== =========== - Ofner2017 15 61 7 60 3s 512Hz 1 - ========= ======= ======= ========== ================= ============ =============== =========== - Upper limb Motor imagery dataset from the paper [1]_. **Dataset description** diff --git a/moabb/evaluations/base.py b/moabb/evaluations/base.py index a16e23226..c15c2699d 100644 --- a/moabb/evaluations/base.py +++ b/moabb/evaluations/base.py @@ -1,5 +1,6 @@ import logging from abc import ABC, abstractmethod +from warnings import warn import pandas as pd from sklearn.base import BaseEstimator @@ -7,11 +8,25 @@ from moabb.analysis import Results from moabb.datasets.base import BaseDataset +from moabb.evaluations.utils import _convert_sklearn_params_to_optuna from moabb.paradigms.base import BaseParadigm log = logging.getLogger(__name__) +# Making the optuna soft dependency +try: + from optuna.integration import OptunaSearchCV + + optuna_available = True +except ImportError: + optuna_available = False + +if optuna_available: + search_methods = {"grid": GridSearchCV, "optuna": OptunaSearchCV} +else: + search_methods = {"grid": GridSearchCV} + class BaseEvaluation(ABC): """Base class that defines necessary operations for an evaluation. @@ -53,11 +68,19 @@ class BaseEvaluation(ABC): Save model after training, for each fold of cross-validation if needed cache_config: bool, default=None Configuration for caching of datasets. See :class:`moabb.datasets.base.CacheConfig` for details. + optuna:bool, default=False + If optuna is enable it will change the GridSearch to a RandomizedGridSearch with 15 minutes of cut off time. + This option is compatible with list of entries of type None, bool, int, float and string + time_out: default=60*15 + Cut off time for the optuna search expressed in seconds, the default value is 15 minutes. + Only used with optuna equal to True. Notes ----- .. versionadded:: 1.1.0 n_splits, save_model, cache_config parameters. + .. versionadded:: 1.1.1 + optuna, time_out parameters. """ def __init__( @@ -77,6 +100,8 @@ def __init__( n_splits=None, save_model=False, cache_config=None, + optuna=False, + time_out=60 * 15, ): self.random_state = random_state self.n_jobs = n_jobs @@ -88,6 +113,16 @@ def __init__( self.n_splits = n_splits self.save_model = save_model self.cache_config = cache_config + self.optuna = optuna + self.time_out = time_out + + if self.optuna and not optuna_available: + raise ImportError("Optuna is not available. Please install it first.") + if (self.time_out != 60 * 15) and not self.optuna: + warn( + "time_out parameter is only used when optuna is enabled. " + "Ignoring time_out parameter." + ) # check paradigm if not isinstance(paradigm, BaseParadigm): raise (ValueError("paradigm must be an Paradigm instance")) @@ -261,9 +296,17 @@ def is_valid(self, dataset): """ def _grid_search(self, param_grid, name, grid_clf, inner_cv): + extra_params = {} if param_grid is not None: if name in param_grid: - search = GridSearchCV( + if self.optuna: + search = search_methods["optuna"] + param_grid[name] = _convert_sklearn_params_to_optuna(param_grid[name]) + extra_params["timeout"] = self.time_out + else: + search = search_methods["grid"] + + search = search( grid_clf, param_grid[name], refit=True, @@ -271,9 +314,9 @@ def _grid_search(self, param_grid, name, grid_clf, inner_cv): n_jobs=self.n_jobs, scoring=self.paradigm.scoring, return_train_score=True, + **extra_params, ) return search - else: return grid_clf diff --git a/moabb/evaluations/utils.py b/moabb/evaluations/utils.py index 0542fa160..79996c293 100644 --- a/moabb/evaluations/utils.py +++ b/moabb/evaluations/utils.py @@ -10,6 +10,14 @@ from sklearn.pipeline import Pipeline +try: + from optuna.distributions import CategoricalDistribution + + optuna_available = True +except ImportError: + optuna_available = False + + def _check_if_is_keras_model(model): """Check if the model is a Keras model. @@ -214,7 +222,7 @@ def create_save_path( return str(path_save) else: print("No hdf5_path provided, models will not be saved.") - + def sort_group(groups): runs_sort = [] @@ -225,3 +233,36 @@ def sort_group(groups): runs_sort.append(index) sorted_ix = np.argsort(runs_sort) return groups[sorted_ix] + + +def _convert_sklearn_params_to_optuna(param_grid: dict) -> dict: + """ + Function to convert the parameter in Optuna format. This function will + create a categorical distribution of values from the list of values + provided in the parameter grid. + + Parameters + ---------- + param_grid: + Dictionary with the parameters to be converted. + + Returns + ------- + optuna_params: dict + Dictionary with the parameters converted to Optuna format. + """ + if not optuna_available: + raise ImportError( + "Optuna is not available. Please install it optuna " "and optuna-integration." + ) + else: + optuna_params = {} + for key, value in param_grid.items(): + try: + if isinstance(value, list): + optuna_params[key] = CategoricalDistribution(value) + else: + optuna_params[key] = value + except Exception as e: + raise ValueError(f"Conversion failed for parameter {key}: {e}") + return optuna_params diff --git a/moabb/tests/benchmark.py b/moabb/tests/benchmark.py index e6147fd7d..f7ea26f60 100644 --- a/moabb/tests/benchmark.py +++ b/moabb/tests/benchmark.py @@ -72,6 +72,16 @@ def test_include_exclude(self): overwrite=True, ) + def test_optuna(self): + res = benchmark( + pipelines=str(self.pp_dir), + evaluations=["WithinSession"], + paradigms=["FakeImageryParadigm"], + overwrite=True, + optuna=True, + ) + self.assertEqual(len(res), 40) + if __name__ == "__main__": unittest.main() diff --git a/moabb/tests/datasets.py b/moabb/tests/datasets.py index 5699c16f8..0c59d16d7 100644 --- a/moabb/tests/datasets.py +++ b/moabb/tests/datasets.py @@ -11,7 +11,12 @@ import moabb.datasets as db import moabb.datasets.compound_dataset as db_compound from moabb.datasets import BNCI2014_001, Cattan2019_VR, Shin2017A, Shin2017B -from moabb.datasets.base import BaseDataset, is_abbrev, is_camel_kebab_case +from moabb.datasets.base import ( + BaseDataset, + _summary_table, + is_abbrev, + is_camel_kebab_case, +) from moabb.datasets.compound_dataset import CompoundDataset from moabb.datasets.compound_dataset.utils import compound_dataset_list from moabb.datasets.fake import FakeDataset, FakeVirtualRealityDataset @@ -251,6 +256,28 @@ def test_depreciated_datasets_init(self): self.assertIsNotNone(obj) self.assertIn(ds.__name__, depreciated_names) + def test_dataset_docstring_table(self): + # The dataset summary table will be automatically added to the docstring of + # all the datasets listed in the moabb/datasets/summary_*.csv files. + depreciated_names, _, _ = zip(*aliases_list) + for ds in dataset_list: + if "Fake" in ds.__name__: + continue + if ds.__name__ in depreciated_names: + continue + self.assertIn(".. admonition:: Dataset summary", ds.__doc__) + + def test_completeness_summary_table(self): + # The dataset summary table will be automatically added to the docstring of + # all the datasets listed in the moabb/datasets/summary_*.csv files. + depreciated_names, _, _ = zip(*aliases_list) + for ds in dataset_list: + if "Fake" in ds.__name__: + continue + if ds.__name__ in depreciated_names: + continue + self.assertIn(ds.__name__, _summary_table.index) + def test_dataset_list(self): if aliases_list: depreciated_list, _, _ = zip(*aliases_list) diff --git a/moabb/tests/evaluations.py b/moabb/tests/evaluations.py index 81069e50b..d6aee6045 100644 --- a/moabb/tests/evaluations.py +++ b/moabb/tests/evaluations.py @@ -58,6 +58,7 @@ def setUp(self): datasets=[dataset], hdf5_path="res_test", save_model=True, + optuna=False, ) def test_mne_labels(self): @@ -138,6 +139,30 @@ def test_eval_grid_search(self): # We should have 9 columns in the results data frame self.assertEqual(len(results[0].keys()), 9 if _carbonfootprint else 8) + def test_eval_grid_search_optuna(self): + # Test grid search + param_grid = {"C": {"csp__metric": ["euclid", "riemann"]}} + process_pipeline = self.eval.paradigm.make_process_pipelines(dataset)[0] + + self.eval.optuna = True + + results = [ + r + for r in self.eval.evaluate( + dataset, + pipelines, + param_grid=param_grid, + process_pipeline=process_pipeline, + ) + ] + + self.eval.optuna = False + + # We should get 4 results, 2 sessions 2 subjects + self.assertEqual(len(results), 4) + # We should have 9 columns in the results data frame + self.assertEqual(len(results[0].keys()), 9 if _carbonfootprint else 8) + def test_within_session_evaluation_save_model(self): res_test_path = "./res_test" diff --git a/poetry.lock b/poetry.lock deleted file mode 100644 index f50b654c6..000000000 --- a/poetry.lock +++ /dev/null @@ -1,3162 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. - 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Benchmarks" authors = ["Alexandre Barachant", "Vinay Jayaram"] maintainers = ["Sylvain Chevallier "] @@ -13,10 +13,10 @@ license = "BSD-3-Clause" [tool.poetry.dependencies] python = ">=3.9,<3.13" -numpy = "^1.22" +numpy = ">=1.22" scipy = "^1.9.3" mne = "^1.7.0" -pandas = "^1.5.2" +pandas = ">=1.5.2" h5py = "^3.10.0" scikit-learn = ">=1.4.2" matplotlib = "^3.6.2" @@ -34,6 +34,7 @@ edfio = "^0.4.2" pytest = "^7.4.0" mne-bids = "^0.14" + # Optional dependencies for carbon emission codecarbon = { version = "^2.1.4", optional = true } @@ -45,12 +46,13 @@ braindecode = {version = "^0.8", optional = true} torch = { version = "^1.13.1", optional = true } libclang = { version = "^15.0", optional = true } docstring_inheritance = { version = "^2.2.0", optional = true} - +optuna = { version = "^3.6.1", optional = true } +optuna-integration = { version = "^3.6.0", optional = true } [tool.poetry.extras] carbonemission = ["codecarbon"] deeplearning = ["tensorflow", "keras", "scikeras", "braindecode", "docstring_inheritance", "torch", "libclang"] - +optuna = ["optuna", "optuna-integration"] [tool.poetry.group.docs] optional = true diff --git a/scripts/paperswithcode/create_datasets_and_tasks.py b/scripts/paperswithcode/create_datasets_and_tasks.py new file mode 100644 index 000000000..935a93ad2 --- /dev/null +++ b/scripts/paperswithcode/create_datasets_and_tasks.py @@ -0,0 +1,155 @@ +import pickle +import re +from argparse import ArgumentParser +from dataclasses import dataclass + +from paperswithcode import PapersWithCodeClient +from paperswithcode.models import DatasetCreateRequest + + +def dataset_name(dataset): + return f"{dataset.code} MOABB" + + +def dataset_full_name(dataset): + s = dataset.__doc__.split("\n\n")[0] + s = re.sub(r" \[\d+\]_", "", s) + s = re.sub(r"\s+", " ", s) + return s + + +def dataset_url(dataset): + return f"http://moabb.neurotechx.com/docs/generated/moabb.datasets.{dataset.__class__.__name__}.html" + + +def valid_datasets(): + from moabb.datasets.utils import dataset_list + from moabb.utils import aliases_list + + deprecated_names = [n[0] for n in aliases_list] + return [ + d() + for d in dataset_list + if (d.__name__ not in deprecated_names) and ("Fake" not in d.__name__) + ] + + +_paradigms = { + "MotorImagery": ( + "Motor Imagery", + ["all classes", "left hand vs. right hand", "right hand vs. feet"], + "Motor Imagery", + ), + "P300": ("ERP", None, "Event-Related Potential (ERP)"), + "SSVEP": ("SSVEP", None, "Steady-State Visually Evoked Potential (SSVEP)"), + "CVEP": ("c-VEP", None, "Code-Modulated Visual Evoked Potential (c-VEP)"), +} +_evaluations = { + "WithinSession": "Within-Session", + "CrossSession": "Cross-Session", + "CrossSubject": "Cross-Subject", +} + + +@dataclass +class Task: + id: str + name: str + description: str + area: str + parent_task: str + + @classmethod + def make(cls, name, description, area, parent_task): + # to snake case + task_id = ( + name.lower().replace(" ", "-").replace("(", "").replace(")", "").split(".")[0] + ) + return cls(task_id, name, description, area, parent_task) + + +def create_tasks(client: PapersWithCodeClient): + tasks = {} + for paradigm_class, ( + paradigm_name, + subparadigms, + paradigm_fullname, + ) in _paradigms.items(): + description = f"Classification of examples recorded under the {paradigm_fullname} paradigm, as part of Brain-Computer Interfaces (BCI)." + d = dict( + name=paradigm_name, + description=description, + area="Medical", + parent_task="Brain Computer Interface", + ) + # task = client.task_add(TaskCreateRequest(**d)) + task = Task.make(**d) + tasks[paradigm_class] = task + for evaluation_class, evaluation in _evaluations.items(): + eval_url = f'http://moabb.neurotechx.com/docs/generated/moabb.evaluations.{evaluation.replace("-", "")}Evaluation.html' + d = dict( + name=f"{evaluation} {paradigm_name}", + description=f"""MOABB's {evaluation} evaluation for the {paradigm_name} paradigm. + +Evaluation details: [{eval_url}]({eval_url})""", + area="medical", + parent_task=task.id, + ) + # subtask = client.task_add(TaskCreateRequest(**d)) + subtask = Task.make(**d) + tasks[(paradigm_class, evaluation_class)] = subtask + if subparadigms is not None: + for subparadigm in subparadigms: + d = dict( + name=f"{evaluation} {paradigm_name} ({subparadigm})", + description=f"""MOABB's {evaluation} evaluation for the {paradigm_name} paradigm ({subparadigm}). + +Evaluation details: [{eval_url}]({eval_url})""", + area="medical", + parent_task=subtask.id, + ) + # subsubtask = client.task_add(TaskCreateRequest(**d)) + subsubtask = Task.make(**d) + tasks[(paradigm_class, evaluation_class, subparadigm)] = subsubtask + return tasks + + +def create_datasets(client): + datasets = valid_datasets() + pwc_datasets = {} + for dataset in datasets: + pwc_dataset = client.dataset_add( + DatasetCreateRequest( + name=dataset_name(dataset), + full_name=dataset_full_name(dataset), + url=dataset_url(dataset), + ) + ) + pwc_datasets[dataset.code] = pwc_dataset + return pwc_datasets + + +if __name__ == "__main__": + parser = ArgumentParser() + parser.add_argument("token", type=str, help="PapersWithCode API token") + parser.add_argument( + "-o", + "--output", + type=str, + help="Pickle output file", + default="paperswithcode_datasets_and_tasks.pickle", + ) + args = parser.parse_args() + + client = PapersWithCodeClient(token=args.token) + + # create tasks + tasks = create_tasks(client) + + # create datasets + datasets = create_datasets(client) + obj = {"datasets": datasets, "tasks": tasks} + + with open(args.output, "wb") as f: + pickle.dump(obj, f) + print(f"Datasets and tasks saved to {args.output}") diff --git a/scripts/paperswithcode/upload_results.py b/scripts/paperswithcode/upload_results.py new file mode 100644 index 000000000..c344b3d17 --- /dev/null +++ b/scripts/paperswithcode/upload_results.py @@ -0,0 +1,182 @@ +import pickle +from argparse import ArgumentParser +from dataclasses import dataclass +from math import isnan + +import pandas as pd +from paperswithcode import PapersWithCodeClient +from paperswithcode.models import ( + EvaluationTableSyncRequest, + MetricSyncRequest, + ResultSyncRequest, +) + + +@dataclass +class Task: + id: str + name: str + description: str + area: str + parent_task: str + + +_metrics = { + "time": "training time (s)", + "carbon_emission": "CO2 Emission (g)", +} + + +def make_table(results_csv_list: list[str], metric: str): + df_list = [] + for results_csv in results_csv_list: + df = pd.read_csv(results_csv) + columns = ["score"] + if "time" in df.columns: + columns.append("time") + if "carbon_emission" in df.columns: + columns.append("carbon_emission") + df = ( + df.groupby( + ["dataset", "paradigm", "evaluation", "pipeline"], + )[columns] + .mean() + .reset_index() + ) + df.score = df.score * 100 + columns = dict(**_metrics, score=metric) + df.rename(columns=columns, inplace=True) + df.paradigm = df.paradigm.replace( + {"FilterBankMotorImagery": "MotorImagery", "LeftRightImagery": "MotorImagery"} + ) + print(df.head()) + df_list.append(df) + return pd.concat(df_list) + + +def upload_subtable(client, df, dataset, task, paper, evaluated_on): + kwargs = dict( + task=task.id, + dataset=dataset.id, + description=task.description, + external_id=f"{dataset.id}-{task.id}", + mirror_url="http://moabb.neurotechx.com/docs/benchmark_summary.html", + ) + print(f"Uploading {kwargs=}") + # client.evaluation_create(EvaluationTableCreateRequest(**kwargs)) + + r = EvaluationTableSyncRequest( + **kwargs, + metrics=[ + MetricSyncRequest(name=metric, is_loss=metric in _metrics.values()) + for metric in df.columns + ], + results=[ + ResultSyncRequest( + metrics={k: str(v) for k, v in row.to_dict().items() if not isnan(v)}, + paper=paper, + methodology=pipeline, + external_id=f"{dataset.id}-{task.id}-{pipeline}", + evaluated_on=evaluated_on, + # external_source_url="http://moabb.neurotechx.com/docs/benchmark_summary.html", + # TODO: maybe update url with the exact row of the result + ) + for pipeline, row in df.iterrows() + ], + ) + print(r) + leaderboard_id = client.evaluation_synchronize(r) + print(f"{leaderboard_id=}") + return leaderboard_id + + +def upload_table(client, df, datasets, tasks, paper, evaluated_on, subsubtask): + gp_cols = ["dataset", "paradigm", "evaluation"] + df_gp = df.groupby(gp_cols) + ids = [] + for (dataset_name, paradigm_name, evaluation_name), sub_df in df_gp: + dataset = datasets[dataset_name] + task_key = (paradigm_name, evaluation_name) + if subsubtask is not None: + task_key += (subsubtask,) + task = tasks[task_key] + id = upload_subtable( + client, + sub_df.set_index("pipeline").drop( + columns=gp_cols + ), # + list(_metrics.values())), + dataset, + task, + paper, + evaluated_on, + ) + ids.append(id) + return ids + + +if __name__ == "__main__": + parser = ArgumentParser() + parser.add_argument("token", type=str, help="PapersWithCode API token") + parser.add_argument( + "metric", + type=str, + help="Metric used in the results CSV (see PapersWithCode metrics)", + ) + parser.add_argument( + "results_csv", type=str, help="CSV file with results to upload", nargs="+" + ) + + parser.add_argument( + "-s", + "--subsubtask", + type=str, + default=None, + help="If relevant, the type of motor imagery task (see create_datasets_and_tasks.py)", + ) + parser.add_argument( + "-d", + "--datasets", + type=str, + help="Pickle file created by create_datasets_and_tasks.py", + default="paperswithcode_datasets_and_tasks.pickle", + ) + parser.add_argument( + "-o", + "--output", + type=str, + help="Pickle output file", + default="paperswithcode_results.pickle", + ) + parser.add_argument("-p", "--paper", type=str, help="Paper URL", default="") + parser.add_argument( + "-e", + "--evaluated_on", + type=str, + help="Results date YYYY-MM-DD", + default="2024-04-09", + ) + args = parser.parse_args() + + with open(args.datasets, "rb") as f: + datasets = pickle.load(f) + summary_table = make_table(args.results_csv, metric=args.metric) + + client = PapersWithCodeClient(token=args.token) + + upload_table( + client, + summary_table, + datasets["datasets"], + datasets["tasks"], + args.paper, + args.evaluated_on, + args.subsubtask, + ) + +# Commands used to upload the results of the benchmark paper: +# (generate a new API token, this one is expired) +# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_rf_Optuna.csv -s="right hand vs. feet" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03 +# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_lhrh_Optuna.csv -s="left hand vs. right hand" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03 +# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b Accuracy ../moabb_paper_plots/DATA/results_All_Optuna.csv -s="all classes" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03 +# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b Accuracy ../moabb_paper_plots/DATA/results_SSVEP.csv ../moabb_paper_plots/DATA/results_SSVEP_DL.csv -d paperswithcode_datasets_and_tasks2.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03 +# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_P300.csv ../moabb_paper_plots/DATA/results_P300_DL.csv -d paperswithcode_datasets_and_tasks2.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03