requirements-dev.lock

# generated by rye
# use `rye lock` or `rye sync` to update this lockfile
#
# last locked with the following flags:
#   pre: false
#   features: []
#   all-features: true
#   with-sources: false

-e file:.
anyio==4.3.0
    # via httpx
astor==0.8.1
    # via formulaic
bayesian-optimization==1.4.3
    # via pte-decode
bids-validator==1.14.1
    # via pybids
black==24.2.0
    # via pte-decode
cachetools==5.3.3
    # via tox
catboost==1.2.3
    # via pte-decode
certifi==2024.2.2
    # via httpcore
    # via httpx
    # via requests
cfgv==3.4.0
    # via pre-commit
chardet==5.2.0
    # via tox
charset-normalizer==3.3.2
    # via requests
click==8.1.7
    # via black
    # via hatch
    # via pybids
    # via userpath
colorama==0.4.6
    # via bayesian-optimization
    # via click
    # via pytest
    # via tox
    # via tqdm
colorspacious==1.1.2
    # via mne-qt-browser
contourpy==1.2.0
    # via matplotlib
coverage==7.4.3
    # via pytest-cov
cycler==0.12.1
    # via matplotlib
darkdetect==0.8.0
    # via mne-qt-browser
decorator==5.1.1
    # via mne
distlib==0.3.8
    # via virtualenv
docopt==0.6.2
    # via num2words
editables==0.5
    # via hatchling
filelock==3.13.1
    # via tox
    # via virtualenv
fonttools==4.49.0
    # via matplotlib
formulaic==0.5.2
    # via pybids
graphviz==0.20.1
    # via catboost
greenlet==3.0.3
    # via sqlalchemy
h11==0.14.0
    # via httpcore
h5io==0.2.2
    # via mne
h5py==3.10.0
    # via h5io
    # via pymatreader
hatch==1.9.3
    # via pte-decode
hatchling==1.21.1
    # via hatch
httpcore==1.0.4
    # via httpx
httpx==0.27.0
    # via hatch
hyperlink==21.0.0
    # via hatch
identify==2.5.35
    # via pre-commit
idna==3.6
    # via anyio
    # via httpx
    # via hyperlink
    # via requests
imageio==2.34.0
    # via scikit-image
imbalanced-learn==0.12.0
    # via pte-decode
iniconfig==2.0.0
    # via pytest
interface-meta==1.3.0
    # via formulaic
jaraco-classes==3.3.1
    # via keyring
jinja2==3.1.3
    # via mne
joblib==1.3.2
    # via imbalanced-learn
    # via pte
    # via pte-decode
    # via pte-stats
    # via scikit-learn
keyring==24.3.0
    # via hatch
kiwisolver==1.4.5
    # via matplotlib
lazy-loader==0.3
    # via mne
    # via scikit-image
llvmlite==0.42.0
    # via numba
markdown-it-py==3.0.0
    # via rich
markupsafe==2.1.5
    # via jinja2
matplotlib==3.8.3
    # via catboost
    # via mne
    # via mne-qt-browser
    # via pte
    # via pte-decode
    # via py-neuromodulation
    # via seaborn
    # via statannotations
mdurl==0.1.2
    # via markdown-it-py
mne==1.6.1
    # via mne-bids
    # via mne-qt-browser
    # via pte
    # via pte-decode
    # via py-neuromodulation
mne-bids==0.14
    # via pte
    # via pte-decode
    # via py-neuromodulation
mne-qt-browser==0.6.1
    # via pte
more-itertools==10.2.0
    # via jaraco-classes
mypy==1.8.0
    # via pte-decode
mypy-extensions==1.0.0
    # via black
    # via mypy
networkx==3.2.1
    # via scikit-image
nibabel==5.2.1
    # via pybids
nodeenv==1.8.0
    # via pre-commit
num2words==0.5.13
    # via pybids
numba==0.59.0
    # via pte
    # via pte-decode
    # via pte-stats
numpy==1.26.4
    # via bayesian-optimization
    # via catboost
    # via colorspacious
    # via contourpy
    # via formulaic
    # via h5io
    # via h5py
    # via imageio
    # via imbalanced-learn
    # via matplotlib
    # via mne
    # via mne-bids
    # via mne-qt-browser
    # via nibabel
    # via numba
    # via pandas
    # via patsy
    # via pte
    # via pte-decode
    # via pte-stats
    # via py-neuromodulation
    # via pybids
    # via pybv
    # via pymatreader
    # via pyqtgraph
    # via scikit-image
    # via scikit-learn
    # via scipy
    # via seaborn
    # via statannotations
    # via statsmodels
    # via tifffile
    # via xgboost
packaging==23.2
    # via black
    # via hatch
    # via hatchling
    # via matplotlib
    # via mne
    # via mne-qt-browser
    # via nibabel
    # via plotly
    # via pooch
    # via pte-decode
    # via pyproject-api
    # via pytest
    # via qtpy
    # via scikit-image
    # via statsmodels
    # via tox
pandas==2.2.1
    # via catboost
    # via formulaic
    # via pte
    # via pte-decode
    # via py-neuromodulation
    # via pybids
    # via seaborn
    # via statannotations
    # via statsmodels
pathspec==0.12.1
    # via black
    # via hatchling
patsy==0.5.6
    # via statsmodels
pexpect==4.9.0
    # via hatch
pillow==10.2.0
    # via imageio
    # via matplotlib
    # via scikit-image
pip==24.0
    # via pte-decode
    # via py-neuromodulation
platformdirs==4.2.0
    # via black
    # via hatch
    # via pooch
    # via tox
    # via virtualenv
plotly==5.19.0
    # via catboost
    # via pte
pluggy==1.4.0
    # via hatchling
    # via pytest
    # via tox
pooch==1.8.1
    # via mne
pre-commit==3.6.2
    # via pte-decode
pte==0.2.0
    # via pte-decode
pte-stats==0.3.0
    # via pte
    # via pte-decode
ptyprocess==0.7.0
    # via pexpect
py-neuromodulation @ git+https://github.com/richardkoehler/py_neuromodulation.git@563ee46d66937ac25ddcb9e6d6350bfa5fbb397d
    # via pte-decode
pybids==0.16.4
    # via py-neuromodulation
pybv==0.7.5
    # via pte
pygments==2.17.2
    # via rich
pymatreader==0.0.32
    # via mne
pyparsing==3.1.1
    # via matplotlib
pyproject-api==1.6.1
    # via tox
pyqt5==5.15.10
    # via pte
pyqt5-qt5==5.15.2
    # via pyqt5
pyqt5-sip==12.13.0
    # via pyqt5
pyqtgraph==0.13.3
    # via mne-qt-browser
pytest==8.0.2
    # via pte-decode
    # via pytest-cov
pytest-cov==4.1.0
    # via pte-decode
python-dateutil==2.8.2
    # via matplotlib
    # via pandas
pytz==2024.1
    # via pandas
pywin32-ctypes==0.2.2
    # via keyring
pyyaml==6.0.1
    # via pre-commit
qdarkstyle==3.2.3
    # via mne-qt-browser
qtpy==2.4.1
    # via mne-qt-browser
    # via qdarkstyle
requests==2.31.0
    # via pooch
rich==13.7.0
    # via hatch
ruff==0.2.2
    # via pte-decode
scikit-image==0.22.0
    # via pte
    # via pte-stats
scikit-learn==1.4.1.post1
    # via bayesian-optimization
    # via imbalanced-learn
    # via pte-decode
    # via py-neuromodulation
scipy==1.12.0
    # via bayesian-optimization
    # via catboost
    # via formulaic
    # via imbalanced-learn
    # via mne
    # via mne-bids
    # via mne-qt-browser
    # via pte
    # via pte-decode
    # via py-neuromodulation
    # via pybids
    # via pymatreader
    # via scikit-image
    # via scikit-learn
    # via seaborn
    # via statannotations
    # via statsmodels
    # via xgboost
scooby==0.9.2
    # via mne-qt-browser
seaborn==0.11.2
    # via pte-decode
    # via statannotations
setuptools==69.1.1
    # via mne-qt-browser
    # via nodeenv
shellingham==1.5.4
    # via hatch
six==1.16.0
    # via catboost
    # via patsy
    # via python-dateutil
sniffio==1.3.1
    # via anyio
    # via httpx
sqlalchemy==2.0.27
    # via pybids
statannotations==0.5.0
    # via pte-decode
statsmodels==0.14.1
    # via pte-stats
tenacity==8.2.3
    # via plotly
threadpoolctl==3.3.0
    # via imbalanced-learn
    # via scikit-learn
tifffile==2024.2.12
    # via scikit-image
tomli-w==1.0.0
    # via hatch
tomlkit==0.12.4
    # via hatch
tox==4.13.0
    # via pte-decode
tqdm==4.66.2
    # via mne
trove-classifiers==2024.2.23
    # via hatchling
typing-extensions==4.10.0
    # via formulaic
    # via mypy
    # via sqlalchemy
tzdata==2024.1
    # via pandas
urllib3==2.2.1
    # via requests
userpath==1.9.1
    # via hatch
virtualenv==20.25.1
    # via hatch
    # via pre-commit
    # via tox
wrapt==1.16.0
    # via formulaic
xgboost==2.0.3
    # via pte-decode
xmltodict==0.13.0
    # via pymatreader
zstandard==0.22.0
    # via hatch