baysplinepy dependencies are probably obsolete for a conda install #10
Description
@brews I have tried to install baysplinepy from your special channel, for one of our PhD students who wanted to experiment with it.
Unfortunately, you must have hard-coded some out-of-date dependencies that seem to want my conda to install a wayland X server or something into my fairly complete existing environment
>conda install baysplinepy -c sbma lev
Retrieving notices: done
Channels:
- sbmalev
- conda-forge
- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: /home/share/unix_files/cdat/miniconda3_2024-03/envs/my_very_complete_env
added / updated specs:
- baysplinepy
The following packages will be downloaded:
package | build
---------------------------|-----------------
alsa-lib-1.2.14 | hb9d3cd8_0 553 KB conda-forge
baysplinepy-0.0.2 | pyh39e3cac_0 93 KB sbmalev
cyrus-sasl-2.1.28 | hd9c7081_0 205 KB conda-forge
dbus-1.13.6 | h5008d03_3 604 KB conda-forge
double-conversion-3.3.1 | h5888daf_0 68 KB conda-forge
libclang-cpp20.1-20.1.8 |default_hddf928d_0 20.3 MB conda-forge
libclang13-20.1.8 |default_ha444ac7_0 11.8 MB conda-forge
libcups-2.3.3 | hb8b1518_5 4.3 MB conda-forge
libdrm-2.4.125 | hb9d3cd8_0 240 KB conda-forge
libegl-1.7.0 | ha4b6fd6_2 44 KB conda-forge
libgl-1.7.0 | ha4b6fd6_2 132 KB conda-forge
libglx-1.7.0 | ha4b6fd6_2 74 KB conda-forge
libllvm20-20.1.8 | hecd9e04_0 41.9 MB conda-forge
libpciaccess-0.18 | hb9d3cd8_0 28 KB conda-forge
libxkbcommon-1.10.0 | h65c71a3_0 691 KB conda-forge
libxslt-1.1.43 | h7a3aeb2_0 239 KB conda-forge
matplotlib-3.10.3 | py312h7900ff3_0 17 KB conda-forge
pyside6-6.9.0 | py312h91f0f75_0 9.7 MB conda-forge
qt6-main-6.9.0 | h8d00660_2 49.3 MB conda-forge
wayland-1.24.0 | h3e06ad9_0 323 KB conda-forge
xcb-util-0.4.1 | h4f16b4b_2 20 KB conda-forge
xcb-util-cursor-0.1.5 | hb9d3cd8_0 20 KB conda-forge
xcb-util-image-0.4.0 | hb711507_2 24 KB conda-forge
xcb-util-keysyms-0.4.1 | hb711507_0 14 KB conda-forge
xcb-util-renderutil-0.3.10 | hb711507_0 17 KB conda-forge
xcb-util-wm-0.4.2 | hb711507_0 50 KB conda-forge
xkeyboard-config-2.45 | hb9d3cd8_0 383 KB conda-forge
xorg-libxcomposite-0.4.6 | hb9d3cd8_2 13 KB conda-forge
xorg-libxcursor-1.2.3 | hb9d3cd8_0 32 KB conda-forge
xorg-libxdamage-1.1.6 | hb9d3cd8_0 13 KB conda-forge
xorg-libxrandr-1.5.4 | hb9d3cd8_0 29 KB conda-forge
xorg-libxtst-1.2.5 | hb9d3cd8_3 32 KB conda-forge
xorg-libxxf86vm-1.1.6 | hb9d3cd8_0 17 KB conda-forge
------------------------------------------------------------
Total: 141.2 MB
The following NEW packages will be INSTALLED:
alsa-lib conda-forge/linux-64::alsa-lib-1.2.14-hb9d3cd8_0
baysplinepy sbmalev/noarch::baysplinepy-0.0.2-pyh39e3cac_0
cyrus-sasl conda-forge/linux-64::cyrus-sasl-2.1.28-hd9c7081_0
dbus conda-forge/linux-64::dbus-1.13.6-h5008d03_3
double-conversion conda-forge/linux-64::double-conversion-3.3.1-h5888daf_0
libclang-cpp20.1 conda-forge/linux-64::libclang-cpp20.1-20.1.8-default_hddf9 28d_0
libclang13 conda-forge/linux-64::libclang13-20.1.8-default_ha444ac7_0
libcups conda-forge/linux-64::libcups-2.3.3-hb8b1518_5
libdrm conda-forge/linux-64::libdrm-2.4.125-hb9d3cd8_0
libegl conda-forge/linux-64::libegl-1.7.0-ha4b6fd6_2
libgl conda-forge/linux-64::libgl-1.7.0-ha4b6fd6_2
libglx conda-forge/linux-64::libglx-1.7.0-ha4b6fd6_2
libllvm20 conda-forge/linux-64::libllvm20-20.1.8-hecd9e04_0
libntlm conda-forge/linux-64::libntlm-1.8-hb9d3cd8_0
libpciaccess conda-forge/linux-64::libpciaccess-0.18-hb9d3cd8_0
libpq conda-forge/linux-64::libpq-17.5-h27ae623_0
libxkbcommon conda-forge/linux-64::libxkbcommon-1.10.0-h65c71a3_0
libxslt conda-forge/linux-64::libxslt-1.1.43-h7a3aeb2_0
matplotlib conda-forge/linux-64::matplotlib-3.10.3-py312h7900ff3_0
openldap conda-forge/linux-64::openldap-2.6.10-he970967_0
pyside6 conda-forge/linux-64::pyside6-6.9.0-py312h91f0f75_0
qt6-main conda-forge/linux-64::qt6-main-6.9.0-h8d00660_2
wayland conda-forge/linux-64::wayland-1.24.0-h3e06ad9_0
xcb-util conda-forge/linux-64::xcb-util-0.4.1-h4f16b4b_2
xcb-util-cursor conda-forge/linux-64::xcb-util-cursor-0.1.5-hb9d3cd8_0
xcb-util-image conda-forge/linux-64::xcb-util-image-0.4.0-hb711507_2
xcb-util-keysyms conda-forge/linux-64::xcb-util-keysyms-0.4.1-hb711507_0
xcb-util-renderut~ conda-forge/linux-64::xcb-util-renderutil-0.3.10-hb711507_0
xcb-util-wm conda-forge/linux-64::xcb-util-wm-0.4.2-hb711507_0
xkeyboard-config conda-forge/linux-64::xkeyboard-config-2.45-hb9d3cd8_0
xorg-libxcomposite conda-forge/linux-64::xorg-libxcomposite-0.4.6-hb9d3cd8_2
xorg-libxcursor conda-forge/linux-64::xorg-libxcursor-1.2.3-hb9d3cd8_0
xorg-libxdamage conda-forge/linux-64::xorg-libxdamage-1.1.6-hb9d3cd8_0
xorg-libxrandr conda-forge/linux-64::xorg-libxrandr-1.5.4-hb9d3cd8_0
xorg-libxtst conda-forge/linux-64::xorg-libxtst-1.2.5-hb9d3cd8_3
xorg-libxxf86vm conda-forge/linux-64::xorg-libxxf86vm-1.1.6-hb9d3cd8_0
Proceed ([y]/n)? n
CondaSystemExit: Exiting.
Fortunately, it seems to work out of the box if I just download the source and run your example. I don't know about the results, but at least it's not throwing any exception
>wget https://github.com/brews/baysplinepy/archive/refs/tags/v0.0.2.tar.gz
--2025-07-31 15:25:04-- https://github.com/brews/baysplinepy/archive/refs/tags/v0.0.2.tar.gz
Resolving github.com (github.com)... 140.82.121.4
Connecting to github.com (github.com)|140.82.121.4|:443... connected.
HTTP request sent, awaiting response... 302 Found
Location: https://codeload.github.com/brews/baysplinepy/tar.gz/refs/tags/v0.0.2 [following]
--2025-07-31 15:25:05-- https://codeload.github.com/brews/baysplinepy/tar.gz/refs/tags/v0.0.2
Resolving codeload.github.com (codeload.github.com)... 140.82.121.10
Connecting to codeload.github.com (codeload.github.com)|140.82.121.10|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: unspecified [application/x-gzip]
Saving to: ‘v0.0.2.tar.gz’
[ <=> ] 101,303 --.-K/s in 0.01s
2025-07-31 15:25:05 (6.57 MB/s) - ‘v0.0.2.tar.gz’ saved [101303]
>tar xvf v0.0.2.tar.gz
baysplinepy-0.0.2/
baysplinepy-0.0.2/.gitignore
baysplinepy-0.0.2/.travis.yml
baysplinepy-0.0.2/LICENSE
baysplinepy-0.0.2/README.rst
baysplinepy-0.0.2/bayspline/
baysplinepy-0.0.2/bayspline/__init__.py
baysplinepy-0.0.2/bayspline/example_data/
baysplinepy-0.0.2/bayspline/example_data/tierney2016-p178-15p.csv
baysplinepy-0.0.2/bayspline/modelparams/
baysplinepy-0.0.2/bayspline/modelparams/__init__.py
baysplinepy-0.0.2/bayspline/modelparams/bayes_posterior.mat
baysplinepy-0.0.2/bayspline/modelparams/core.py
baysplinepy-0.0.2/bayspline/plot.py
baysplinepy-0.0.2/bayspline/predict.py
baysplinepy-0.0.2/bayspline/tests/
baysplinepy-0.0.2/bayspline/tests/__init__.py
baysplinepy-0.0.2/bayspline/tests/test_predict_sst.py
baysplinepy-0.0.2/bayspline/tests/test_predict_uk.py
baysplinepy-0.0.2/bayspline/tests/test_utils.py
baysplinepy-0.0.2/bayspline/utils.py
baysplinepy-0.0.2/ci/
baysplinepy-0.0.2/ci/requirements-py35.yml
baysplinepy-0.0.2/ci/requirements-py36.yml
baysplinepy-0.0.2/setup.py
baysplinepy-0.0.2/whats-new.rst
>cd baysplinepy-0.0.2/
>ls
bayspline/ ci/ LICENSE README.rst setup.py whats-new.rst
(base) >conda activate my_very_complete_env
(my_very_complete_env) >python
Python 3.12.4 | packaged by conda-forge | (main, Jun 17 2024, 10:23:07) [GCC 12.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> import bayspline as bsl
>>> example_file = bsl.get_example_data('tierney2016-p178-15p.csv')
>>> d = np.genfromtxt(example_file, delimiter=',', names=True)
>>>
>>> prediction = bsl.predict_sst(d['uk37'], prior_std=10)
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:33<00:00, 14.87it/s]
>>> type(prediction)
<class 'bayspline.predict.SSTPrediction'>
>>> prediction
SSTPrediction(ensemble=array([[43.00995563, 32.83456583, 29.41568629, ..., 56.05279752,
32.5673014 , 37.69329088],
[25.5316321 , 34.83117254, 34.56163057, ..., 32.62638468,
27.94681856, 29.08531471],
[32.07855444, 25.59368864, 26.73683853, ..., 40.68898904,
26.97243237, 37.7751331 ],
...,
[22.12087532, 28.13367503, 22.64527099, ..., 26.5950704 ,
26.22114106, 25.42657283],
[23.44125776, 25.53569734, 25.79566057, ..., 25.4587341 ,
24.11952543, 23.62833184],
[23.28643255, 28.16401372, 29.39495386, ..., 26.28692475,
28.17450948, 28.1976014 ]], shape=(97, 125000)), prior_mean=array([27.85294118, 27.29411765, 27.23529412, 27.32352941, 27.32352941,
27.44117647, 27.26470588, 27.52941176, 27.44117647, 27.47058824,
27.52941176, 27.44117647, 27.26470588, 27.32352941, 26.97058824,
27.23529412, 27.08823529, 27.32352941, 27.11764706, 27.08823529,
27.08823529, 27.17647059, 27.17647059, 27.08823529, 27.02941176,
26.97058824, 27.32352941, 27.14705882, 27.29411765, 27.20588235,
27.17647059, 27.41176471, 27.35294118, 26.91176471, 27.26470588,
27.29411765, 27.17647059, 26.79411765, 26.47058824, 26.76470588,
27.02941176, 26.79411765, 26.73529412, 26.73529412, 26.79411765,
26.85294118, 26.73529412, 26.73529412, 26.67647059, 26.55882353,
26.47058824, 26.41176471, 26.5 , 26.38235294, 26.38235294,
26.32352941, 26.41176471, 26.38235294, 26.32352941, 26.32352941,
26.29411765, 26.29411765, 26.32352941, 26.08823529, 26.08823529,
25.82352941, 25.5 , 25.32352941, 25.11764706, 25.58823529,
25.5 , 25.38235294, 25.64705882, 25.55882353, 25.23529412,
25.35294118, 25.97058824, 25.67647059, 25.97058824, 25.67647059,
25.85294118, 25.61764706, 25.76470588, 26.08823529, 26. ,
25.55882353, 26. , 25.97058824, 26. , 25.58823529,
25.52941176, 25.11764706, 25.38235294, 25.55882353, 25.61764706,
25.35294118, 25.11764706]), prior_std=10, jump_distance=np.float64(6.350899999999999), acceptance=np.float64(0.46950119587628864), rhat=array([1.14268629]))
>>>
>>>
>>> sst = np.arange(1, 25)
>>> prediction_2 = bsl.predict_uk(sst)
>>> prediction_2
UKPrediction(ensemble=array([[0.10494627, 0.04294787, 0.15532562, ..., 0.0587097 , 0.20169074,
0.09581955],
[0.19066846, 0.04635925, 0.15683951, ..., 0.1004465 , 0.18069335,
0.15126002],
[0.204884 , 0.09502602, 0.19157386, ..., 0.05443234, 0.20863643,
0.15645332],
...,
[0.76992931, 0.70046949, 0.85805503, ..., 0.78276341, 0.79814979,
0.78590304],
[0.80936849, 0.87841609, 0.70769468, ..., 0.81879373, 0.76117749,
0.79661735],
[0.85334466, 0.82227373, 0.86390017, ..., 0.88562306, 0.82070975,
0.89398335]], shape=(24, 1500)), prior_mean=None, prior_std=None)
I have provided below the listing of my environment, but looking at what you import, your dependencies seem to be very standard ones, mostly: numpy, scipy, tqdm and matplotlib
(my_very_complete_env) >conda list
# packages in environment at /home/share/unix_files/cdat/miniconda3_2024-03/envs/my_very_complete_env:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
_r-mutex 1.0.1 anacondar_1 conda-forge
_sysroot_linux-64_curr_repodata_hack 4 h5bd9786_17 conda-forge
anyio 4.9.0 pyh29332c3_0 conda-forge
aom 3.9.1 hac33072_0 conda-forge
argon2-cffi 25.1.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py312h66e93f0_5 conda-forge
arrow 1.3.0 pyhd8ed1ab_1 conda-forge
asttokens 3.0.0 pyhd8ed1ab_1 conda-forge
async-lru 2.0.5 pyh29332c3_0 conda-forge
attrs 25.3.0 pyh71513ae_0 conda-forge
aws-c-auth 0.9.0 h0fbd49f_19 conda-forge
aws-c-cal 0.9.2 he7b75e1_1 conda-forge
aws-c-common 0.12.4 hb03c661_0 conda-forge
aws-c-compression 0.3.1 h92c474e_6 conda-forge
aws-c-event-stream 0.5.5 h149bd38_3 conda-forge
aws-c-http 0.10.4 h37a7233_0 conda-forge
aws-c-io 0.21.2 h6252d9a_1 conda-forge
aws-c-mqtt 0.13.3 h19deb91_3 conda-forge
aws-c-s3 0.8.6 h800fcd2_2 conda-forge
aws-c-sdkutils 0.2.4 h92c474e_1 conda-forge
aws-checksums 0.2.7 h92c474e_2 conda-forge
aws-crt-cpp 0.33.1 hb4fd278_2 conda-forge
aws-sdk-cpp 1.11.606 h31ade35_1 conda-forge
azure-core-cpp 1.16.0 h3a458e0_0 conda-forge
azure-identity-cpp 1.12.0 ha729027_0 conda-forge
azure-storage-blobs-cpp 12.14.0 hb1c9500_1 conda-forge
azure-storage-common-cpp 12.10.0 hebae86a_2 conda-forge
azure-storage-files-datalake-cpp 12.12.0 h8b27e44_3 conda-forge
babel 2.17.0 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.13.4 pyha770c72_0 conda-forge
binutils 2.44 h4852527_1 conda-forge
binutils_impl_linux-64 2.44 h4bf12b8_1 conda-forge
binutils_linux-64 2.44 h4852527_1 conda-forge
bleach 6.2.0 pyh29332c3_4 conda-forge
bleach-with-css 6.2.0 h82add2a_4 conda-forge
blosc 1.21.6 he440d0b_1 conda-forge
bokeh 3.7.3 pyhd8ed1ab_0 conda-forge
bottleneck 1.5.0 py312hc0a28a1_0 conda-forge
brotli 1.1.0 hb9d3cd8_3 conda-forge
brotli-bin 1.1.0 hb9d3cd8_3 conda-forge
brotli-python 1.1.0 py312h2ec8cdc_3 conda-forge
bwidget 1.10.1 ha770c72_1 conda-forge
bzip2 1.0.8 h4bc722e_7 conda-forge
c-ares 1.34.5 hb9d3cd8_0 conda-forge
c-compiler 1.11.0 h4d9bdce_0 conda-forge
ca-certificates 2025.7.14 hbd8a1cb_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
cairo 1.18.4 h3394656_0 conda-forge
cartopy 0.24.0 py312hf9745cd_0 conda-forge
cdo 2.5.0 hc8165f4_0 conda-forge
cdsapi 0.7.6 pyhd8ed1ab_0 conda-forge
certifi 2025.7.14 pyhd8ed1ab_0 conda-forge
cf_xarray 0.10.6 pyhd8ed1ab_0 conda-forge
cffi 1.17.1 py312h06ac9bb_0 conda-forge
cftime 1.6.4 py312hc0a28a1_1 conda-forge
charset-normalizer 3.4.2 pyhd8ed1ab_0 conda-forge
click 8.2.1 pyh707e725_0 conda-forge
cloudpickle 3.1.1 pyhd8ed1ab_0 conda-forge
cmake 4.0.3 h74e3db0_0 conda-forge
cmocean 4.0.3 pyhd8ed1ab_1 conda-forge
colorama 0.4.6 pyhd8ed1ab_1 conda-forge
colorspacious 1.1.2 pyhecae5ae_1 conda-forge
comm 0.2.3 pyhe01879c_0 conda-forge
conda-gcc-specs 14.3.0 hb991d5c_3 conda-forge
contourpy 1.3.3 py312hd9148b4_0 conda-forge
crc32c 2.7.1 py312h66e93f0_1 conda-forge
cuda-cudart 12.9.79 h5888daf_0 conda-forge
cuda-cudart_linux-64 12.9.79 h3f2d84a_0 conda-forge
cuda-version 12.9 h4f385c5_3 conda-forge
curl 8.14.1 h332b0f4_0 conda-forge
cxx-compiler 1.11.0 hfcd1e18_0 conda-forge
cycler 0.12.1 pyhd8ed1ab_1 conda-forge
cytoolz 1.0.1 py312h66e93f0_0 conda-forge
dask 2025.7.0 pyhe01879c_0 conda-forge
dask-core 2025.7.0 pyhe01879c_1 conda-forge
dav1d 1.2.1 hd590300_0 conda-forge
dcw-gmt 2.2.0 ha770c72_0 conda-forge
debugpy 1.8.15 py312h8285ef7_0 conda-forge
decorator 5.2.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
deprecated 1.2.18 pyhd8ed1ab_0 conda-forge
distributed 2025.7.0 pyhe01879c_0 conda-forge
donfig 0.8.1.post1 pyhd8ed1ab_1 conda-forge
eccodes 2.41.0 h8bb6dbc_0 conda-forge
ecmwf-datastores-client 0.2.0 pyhd8ed1ab_0 conda-forge
eigen 3.4.0 h00ab1b0_0 conda-forge
esmf 8.8.1 nompi_h4441c20_0 conda-forge
esmpy 8.8.1 pyhecae5ae_0 conda-forge
exceptiongroup 1.3.0 pyhd8ed1ab_0 conda-forge
executing 2.2.0 pyhd8ed1ab_0 conda-forge
expat 2.7.1 hecca717_0 conda-forge
fftw 3.3.10 nompi_hf1063bd_110 conda-forge
findlibs 0.0.5 pyhd8ed1ab_0 conda-forge
flake8 7.3.0 pyhd8ed1ab_0 conda-forge
flexcache 0.3 pyhd8ed1ab_1 conda-forge
flexparser 0.4 pyhd8ed1ab_1 conda-forge
flox 0.10.4 pyhd8ed1ab_0 conda-forge
font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge
font-ttf-inconsolata 3.000 h77eed37_0 conda-forge
font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge
font-ttf-ubuntu 0.83 h77eed37_3 conda-forge
fontconfig 2.15.0 h7e30c49_1 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
fonttools 4.59.0 py312h8a5da7c_0 conda-forge
fqdn 1.5.1 pyhd8ed1ab_1 conda-forge
freeglut 3.2.2 ha6d2627_3 conda-forge
freetype 2.13.3 ha770c72_1 conda-forge
freexl 2.0.0 h9dce30a_2 conda-forge
fribidi 1.0.10 h36c2ea0_0 conda-forge
fsspec 2025.7.0 pyhd8ed1ab_0 conda-forge
future 1.0.0 pyhd8ed1ab_2 conda-forge
gcc 14.3.0 he448592_3 conda-forge
gcc_impl_linux-64 14.3.0 hd9e9e21_3 conda-forge
gcc_linux-64 14.3.0 h1382650_11 conda-forge
geos 3.13.1 h97f6797_0 conda-forge
geotiff 1.7.4 h3551947_0 conda-forge
gflags 2.2.2 h5888daf_1005 conda-forge
gfortran_impl_linux-64 14.3.0 h7db7018_3 conda-forge
ghostscript 10.04.0 h5888daf_0 conda-forge
giflib 5.2.2 hd590300_0 conda-forge
glog 0.7.1 hbabe93e_0 conda-forge
gmt 6.5.0 h8300b2c_8 conda-forge
graphite2 1.3.14 h5888daf_0 conda-forge
gshhg-gmt 2.3.7 ha770c72_1003 conda-forge
gsl 2.7 he838d99_0 conda-forge
gxx 14.3.0 he448592_3 conda-forge
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