requirements.txt

#
# This file is autogenerated by pip-compile with Python 3.11
# by the following command:
#
#    pip-compile --output-file=requirements.txt requirements.in
#
absl-py==2.1.0
    # via
    #   chex
    #   keras
    #   optax
    #   tensorboard
    #   tensorflow
    #   tensorflow-probability
arviz==0.20.0
    # via
    #   -r requirements.in
    #   pymc
astunparse==1.6.3
    # via tensorflow
autograd==1.7.0
    # via -r requirements.in
bcrypt==4.2.0
    # via paramiko
black==24.10.0
    # via -r requirements.in
bokeh==3.6.1
    # via -r requirements.in
cachetools==5.5.0
    # via pymc
certifi==2024.8.30
    # via requests
cffi==1.17.1
    # via
    #   cryptography
    #   pynacl
chaospy==4.3.17
    # via -r requirements.in
charset-normalizer==3.4.0
    # via requests
check-shapes==1.1.1
    # via gpflow
chex==0.1.87
    # via optax
click==8.1.7
    # via
    #   black
    #   dask
    #   distributed
cloudpickle==3.1.0
    # via
    #   dask
    #   distributed
    #   pymc
    #   tensorflow-probability
cons==0.4.6
    # via
    #   etuples
    #   minikanren
    #   pytensor
contourpy==1.3.0
    # via
    #   bokeh
    #   matplotlib
coverage[toml]==7.6.4
    # via pytest-cov
cryptography==43.0.3
    # via paramiko
cycler==0.12.1
    # via matplotlib
cython==3.0.11
    # via -r requirements.in
dask==2024.10.0
    # via
    #   -r requirements.in
    #   dask-jobqueue
    #   distributed
dask-jobqueue==0.9.0
    # via -r requirements.in
decorator==5.1.1
    # via
    #   fabric
    #   tensorflow-probability
deprecated==1.2.14
    # via
    #   fabric
    #   gpflow
dill==0.3.9
    # via
    #   multiprocess
    #   pathos
distributed==2024.10.0
    # via
    #   -r requirements.in
    #   dask-jobqueue
diversipy==0.9
    # via -r requirements.in
dm-tree==0.1.8
    # via tensorflow-probability
dropstackframe==0.1.1
    # via check-shapes
etils[epy]==1.10.0
    # via optax
etuples==0.3.9
    # via
    #   minikanren
    #   pytensor
execnet==2.1.1
    # via pytest-xdist
fabric==3.2.2
    # via -r requirements.in
filelock==3.16.1
    # via pytensor
flatbuffers==24.3.25
    # via tensorflow
fonttools==4.54.1
    # via matplotlib
fsspec==2024.10.0
    # via dask
gast==0.6.0
    # via
    #   tensorflow
    #   tensorflow-probability
gnuplotlib==0.42
    # via -r requirements.in
google-pasta==0.2.0
    # via tensorflow
gpflow==2.9.2
    # via -r requirements.in
grpcio==1.67.1
    # via
    #   tensorboard
    #   tensorflow
h5netcdf==1.4.0
    # via arviz
h5py==3.12.1
    # via
    #   h5netcdf
    #   keras
    #   tensorflow
idna==3.10
    # via requests
importlib-metadata==6.11.0
    # via
    #   -r requirements.in
    #   chaospy
    #   dask
    #   numpoly
iniconfig==2.0.0
    # via pytest
invoke==2.2.0
    # via fabric
iteration-utilities==0.13.0
    # via scikit-activeml
jax==0.4.35
    # via
    #   -r requirements.in
    #   chex
    #   optax
jaxlib==0.4.35
    # via
    #   chex
    #   jax
    #   optax
jinja2==3.1.4
    # via
    #   -r requirements.in
    #   bokeh
    #   distributed
joblib==1.4.2
    # via
    #   particles
    #   scikit-activeml
    #   scikit-learn
keras==3.6.0
    # via tensorflow
kiwisolver==1.4.7
    # via matplotlib
lark==1.2.2
    # via check-shapes
libclang==18.1.1
    # via tensorflow
llvmlite==0.43.0
    # via numba
locket==1.0.0
    # via
    #   distributed
    #   partd
logical-unification==0.4.6
    # via
    #   cons
    #   minikanren
    #   pytensor
makefun==1.15.6
    # via scikit-activeml
markdown==3.7
    # via tensorboard
markdown-it-py==3.0.0
    # via rich
markupsafe==3.0.2
    # via
    #   jinja2
    #   werkzeug
matplotlib==3.9.2
    # via
    #   -r requirements.in
    #   arviz
    #   pyvista
    #   salib
    #   scikit-activeml
    #   seaborn
    #   vtk
mdurl==0.1.2
    # via markdown-it-py
minikanren==1.0.3
    # via pytensor
ml-dtypes==0.4.1
    # via
    #   jax
    #   jaxlib
    #   keras
    #   tensorflow
mock==5.1.0
    # via -r requirements.in
msgpack==1.1.0
    # via distributed
multipledispatch==1.0.0
    # via
    #   etuples
    #   gpflow
    #   logical-unification
    #   minikanren
multiprocess==0.70.17
    # via
    #   pathos
    #   salib
mypy-extensions==1.0.0
    # via black
namex==0.0.8
    # via keras
numba==0.60.0
    # via
    #   -r requirements.in
    #   particles
numpoly==1.2.14
    # via chaospy
numpy==1.26.4
    # via
    #   -r requirements.in
    #   arviz
    #   autograd
    #   bokeh
    #   chaospy
    #   chex
    #   contourpy
    #   diversipy
    #   gnuplotlib
    #   gpflow
    #   h5py
    #   jax
    #   jaxlib
    #   keras
    #   matplotlib
    #   ml-dtypes
    #   numba
    #   numpoly
    #   numpysane
    #   optax
    #   pandas
    #   particles
    #   pydoe
    #   pymc
    #   pytensor
    #   pyvista
    #   salib
    #   scikit-activeml
    #   scikit-learn
    #   scipy
    #   seaborn
    #   tensorboard
    #   tensorflow
    #   tensorflow-probability
    #   xarray
    #   xarray-einstats
numpysane==0.40
    # via gnuplotlib
opt-einsum==3.4.0
    # via
    #   jax
    #   tensorflow
optax==0.2.3
    # via -r requirements.in
optree==0.13.0
    # via keras
packaging==24.1
    # via
    #   arviz
    #   black
    #   bokeh
    #   dask
    #   distributed
    #   gpflow
    #   h5netcdf
    #   keras
    #   matplotlib
    #   plotly
    #   pooch
    #   pytest
    #   tensorboard
    #   tensorflow
    #   xarray
pandas==2.2.3
    # via
    #   -r requirements.in
    #   arviz
    #   bokeh
    #   pymc
    #   salib
    #   seaborn
    #   xarray
paramiko==3.5.0
    # via fabric
partd==1.4.2
    # via dask
particles==0.4
    # via -r requirements.in
pathos==0.3.3
    # via -r requirements.in
pathspec==0.12.1
    # via black
pillow==11.0.0
    # via
    #   bokeh
    #   matplotlib
    #   pyvista
platformdirs==4.3.6
    # via
    #   black
    #   pooch
plotly==5.24.1
    # via -r requirements.in
pluggy==1.5.0
    # via pytest
pooch==1.8.2
    # via pyvista
pox==0.3.5
    # via pathos
ppft==1.7.6.9
    # via pathos
protobuf==5.28.3
    # via
    #   tensorboard
    #   tensorflow
psutil==6.1.0
    # via distributed
py==1.11.0
    # via -r requirements.in
pycodestyle==2.12.1
    # via pytest-codestyle
pycparser==2.22
    # via cffi
pydoe==0.3.8
    # via -r requirements.in
pyfiglet==1.0.2
    # via -r requirements.in
pygments==2.18.0
    # via rich
pymc==5.17.0
    # via -r requirements.in
pynacl==1.5.0
    # via paramiko
pyparsing==3.2.0
    # via matplotlib
pytensor==2.25.5
    # via pymc
pytest==8.3.3
    # via
    #   -r requirements.in
    #   pytest-codestyle
    #   pytest-cov
    #   pytest-mock
    #   pytest-xdist
pytest-codestyle==2.0.1
    # via -r requirements.in
pytest-cov==5.0.0
    # via -r requirements.in
pytest-mock==3.14.0
    # via -r requirements.in
pytest-xdist==3.6.1
    # via -r requirements.in
python-dateutil==2.9.0.post0
    # via
    #   matplotlib
    #   pandas
pytz==2024.2
    # via pandas
pyvista==0.44.1
    # via -r requirements.in
pyyaml==6.0.2
    # via
    #   -r requirements.in
    #   bokeh
    #   dask
    #   distributed
requests==2.32.3
    # via
    #   pooch
    #   tensorflow
rich==13.9.3
    # via
    #   keras
    #   pymc
salib==1.5.1
    # via -r requirements.in
scikit-activeml==0.5.2
    # via -r requirements.in
scikit-learn==1.5.2
    # via
    #   -r requirements.in
    #   particles
    #   scikit-activeml
scipy==1.14.1
    # via
    #   -r requirements.in
    #   arviz
    #   chaospy
    #   diversipy
    #   gpflow
    #   jax
    #   jaxlib
    #   particles
    #   pydoe
    #   pymc
    #   pytensor
    #   salib
    #   scikit-activeml
    #   scikit-learn
    #   xarray-einstats
scooby==0.10.0
    # via pyvista
seaborn==0.13.2
    # via -r requirements.in
six==1.16.0
    # via
    #   astunparse
    #   google-pasta
    #   python-dateutil
    #   tensorboard
    #   tensorflow
    #   tensorflow-probability
sortedcontainers==2.4.0
    # via distributed
tabulate==0.9.0
    # via gpflow
tblib==3.0.0
    # via distributed
tenacity==9.0.0
    # via plotly
tensorboard==2.18.0
    # via tensorflow
tensorboard-data-server==0.7.2
    # via tensorboard
tensorflow==2.18.0
    # via
    #   -r requirements.in
    #   gpflow
    #   tensorflow-probability
    #   tf-keras
tensorflow-io-gcs-filesystem==0.37.1
    # via tensorflow
tensorflow-probability[tf]==0.24.0
    # via
    #   -r requirements.in
    #   gpflow
termcolor==2.5.0
    # via tensorflow
tf-keras==2.18.0
    # via tensorflow-probability
threadpoolctl==3.5.0
    # via
    #   pymc
    #   scikit-learn
tomli==2.0.2
    # via -r requirements.in
toolz==1.0.0
    # via
    #   chex
    #   dask
    #   distributed
    #   logical-unification
    #   minikanren
    #   partd
tornado==6.4.1
    # via
    #   bokeh
    #   distributed
tqdm==4.66.6
    # via -r requirements.in
typing-extensions==4.12.2
    # via
    #   arviz
    #   chex
    #   etils
    #   gpflow
    #   optree
    #   pymc
    #   pyvista
    #   tensorflow
tzdata==2024.2
    # via pandas
urllib3==2.2.3
    # via
    #   distributed
    #   requests
vtk==9.3.1
    # via
    #   -r requirements.in
    #   pyvista
werkzeug==3.0.6
    # via tensorboard
wheel==0.44.0
    # via astunparse
wrapt==1.16.0
    # via
    #   deprecated
    #   tensorflow
xarray==2024.10.0
    # via
    #   -r requirements.in
    #   arviz
    #   xarray-einstats
xarray-einstats==0.8.0
    # via arviz
xyzservices==2024.9.0
    # via bokeh
zict==3.0.0
    # via distributed
zipp==3.20.2
    # via importlib-metadata

# The following packages are considered to be unsafe in a requirements file:
# setuptools