environment.yml

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: win-64
asttokens=2.4.1=pyhd8ed1ab_0
blas=1.0=mkl
blosc=1.21.3=h6c2663c_0
bottleneck=1.4.2=py312h4b0e54e_0
brotli=1.0.9=h2bbff1b_8
brotli-bin=1.0.9=h2bbff1b_8
bzip2=1.0.8=h2bbff1b_6
c-blosc2=2.12.0=h2f4ed9d_0
ca-certificates=2024.11.26=haa95532_0
colorama=0.4.6=py312haa95532_0
comm=0.2.2=pyhd8ed1ab_0
contourpy=1.2.0=py312h59b6b97_0
cycler=0.11.0=pyhd3eb1b0_0
debugpy=1.6.7=py312hd77b12b_0
decorator=5.1.1=pyhd8ed1ab_0
exceptiongroup=1.2.2=pyhd8ed1ab_0
executing=2.1.0=pyhd8ed1ab_0
expat=2.6.3=h5da7b33_0
filelock=3.13.1=py312haa95532_0
fonttools=4.51.0=py312h2bbff1b_0
freetype=2.12.1=ha860e81_0
fsspec=2024.6.1=py312haa95532_0
h5py=3.12.1=py312h3b2c811_0
hdf5=1.12.1=h51c971a_3
hdf5storage=0.1.19=pyhd8ed1ab_0
icc_rt=2022.1.0=h6049295_2
icu=73.1=h6c2663c_0
importlib-metadata=8.5.0=pyha770c72_0
intel-openmp=2023.1.0=h59b6b97_46320
ipykernel=6.29.5=pyh4bbf305_0
ipython=8.29.0=pyh7428d3b_0
jedi=0.19.2=pyhff2d567_0
jinja2=3.1.4=py312haa95532_1
joblib=1.4.2=py312haa95532_0
jpeg=9e=h827c3e9_3
jupyter_client=8.6.3=pyhd8ed1ab_0
jupyter_core=5.7.2=py312haa95532_0
kiwisolver=1.4.4=py312hd77b12b_0
krb5=1.20.1=h5b6d351_0
lcms2=2.12=h83e58a3_0
lerc=3.0=hd77b12b_0
libbrotlicommon=1.0.9=h2bbff1b_8
libbrotlidec=1.0.9=h2bbff1b_8
libbrotlienc=1.0.9=h2bbff1b_8
libclang=14.0.6=default_hb5a9fac_1
libclang13=14.0.6=default_h8e68704_1
libdeflate=1.17=h2bbff1b_1
libffi=3.4.4=hd77b12b_1
libpng=1.6.39=h8cc25b3_0
libpq=17.0=h70ee33d_0
libsodium=1.0.18=h8d14728_1
libtiff=4.5.1=hd77b12b_0
libuv=1.48.0=h827c3e9_0
libwebp-base=1.3.2=h3d04722_1
lz4-c=1.9.4=h2bbff1b_1
lzo=2.10=he774522_2
markupsafe=2.1.3=py312h2bbff1b_0
matplotlib=3.9.2=py312haa95532_0
matplotlib-base=3.9.2=py312hbdc63d0_0
matplotlib-inline=0.1.7=pyhd8ed1ab_0
mkl=2023.1.0=h6b88ed4_46358
mkl-service=2.4.0=py312h2bbff1b_1
mkl_fft=1.3.11=py312h827c3e9_0
mkl_random=1.2.8=py312h0158946_0
mpmath=1.3.0=py312haa95532_0
nest-asyncio=1.6.0=pyhd8ed1ab_0
networkx=3.3=py312haa95532_0
numexpr=2.10.1=py312h4cd664f_0
numpy=1.26.4=py312hfd52020_0
numpy-base=1.26.4=py312h4dde369_0
openjpeg=2.5.2=hae555c5_0
openssl=3.0.15=h827c3e9_0
packaging=24.1=py312haa95532_0
pandas=2.2.2=py312h0158946_0
parso=0.8.4=pyhd8ed1ab_0
patsy=0.5.6=py312haa95532_0
pickleshare=0.7.5=py_1003
pillow=11.0.0=py312hb5480e2_0
pip=24.2=py312haa95532_0
platformdirs=4.3.6=pyhd8ed1ab_0
ply=3.11=py312haa95532_1
prompt-toolkit=3.0.48=pyha770c72_0
psutil=5.9.0=py312h2bbff1b_0
pure_eval=0.2.3=pyhd8ed1ab_0
py-cpuinfo=9.0.0=py312haa95532_0
pygments=2.18.0=pyhd8ed1ab_0
pyparsing=3.2.0=py312haa95532_0
pyqt=5.15.10=py312hd77b12b_0
pyqt5-sip=12.13.0=py312h2bbff1b_0
pytables=3.9.2=py312h2314d3b_0
python=3.12.7=h14ffc60_0
python-dateutil=2.9.0post0=py312haa95532_2
python-tzdata=2023.3=pyhd3eb1b0_0
pytorch=2.3.1=cpu_py312h0ce1571_0
pytz=2024.1=py312haa95532_0
pywin32=305=py312h2bbff1b_0
pyzmq=25.1.2=py312hd77b12b_0
qt-main=5.15.2=h19c9488_11
scikit-learn=1.5.1=py312h0158946_0
scipy=1.14.1=py312h9d85e7c_0
seaborn=0.13.2=py312haa95532_0
setuptools=75.1.0=py312haa95532_0
sip=6.7.12=py312hd77b12b_0
six=1.16.0=pyhd3eb1b0_1
sqlite=3.45.3=h2bbff1b_0
stack_data=0.6.2=pyhd8ed1ab_0
statsmodels=0.14.2=py312h4b0e54e_0
sympy=1.13.2=py312haa95532_0
tbb=2021.8.0=h59b6b97_0
threadpoolctl=3.5.0=py312hfc267ef_0
tk=8.6.14=h0416ee5_0
tornado=6.4.1=py312h827c3e9_0
tqdm=4.66.5=py312hfc267ef_0
traitlets=5.14.3=pyhd8ed1ab_0
typing_extensions=4.12.2=pyha770c72_0
tzdata=2024b=h04d1e81_0
unicodedata2=15.1.0=py312h2bbff1b_0
vc=14.40=h2eaa2aa_1
vs2015_runtime=14.40.33807=h98bb1dd_1
wcwidth=0.2.13=pyhd8ed1ab_0
wheel=0.44.0=py312haa95532_0
xz=5.4.6=h8cc25b3_1
zeromq=4.3.5=hd77b12b_0
zipp=3.21.0=pyhd8ed1ab_0
zlib=1.2.13=h8cc25b3_1
zlib-ng=2.0.7=h2bbff1b_0
zstd=1.5.6=h8880b57_0