TypeError when running periodic demos with dolfinx/dolfinx_mpc v0.8.0

[bnherrerac]

Hello, I am unable to run the periodic demos using dolfinx 0.8.0 and dolfinx_mpc 0.8.0, with Python 3.12.6. The demos I can't run are the following:

• https://github.com/jorgensd/dolfinx_mpc/blob/v0.8.0/python/demos/demo_periodic_geometrical.py
• https://github.com/jorgensd/dolfinx_mpc/blob/v0.8.0/python/demos/demo_periodic3d_topological.py

In both cases I get a similar error, here's the error for demo_periodic_geometrical.py:

  File "/home/bnherrerac/p2/demos/demo_periodic_geometrical.py", line 81, in <module>
    mpc.create_periodic_constraint_geometrical(V, periodic_boundary, periodic_relation, bcs)
  File "/home/bnherrerac/anaconda3/envs/fenicsx-env/lib/python3.12/site-packages/dolfinx_mpc/multipointconstraint.py", line 286, in create_periodic_constraint_geometrical
    mpc_data = dolfinx_mpc.cpp.mpc.create_periodic_constraint_geometrical(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: create_periodic_constraint_geometrical(): incompatible function arguments. The following argument types are supported:
    1. create_periodic_constraint_geometrical(V: dolfinx::fem::FunctionSpace<float>, indicator: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], ndarray[dtype=bool, shape=(*), order='C']], relation: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float32, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<float, float>], scale: float, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_float
    2. create_periodic_constraint_geometrical(V: dolfinx::fem::FunctionSpace<float>, indicator: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], ndarray[dtype=bool, shape=(*), order='C']], relation: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float32, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<std::complex<float>, float>], scale: complex, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_complex_float
    3. create_periodic_constraint_geometrical(V: dolfinx::fem::FunctionSpace<double>, indicator: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], ndarray[dtype=bool, shape=(*), order='C']], relation: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float64, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<double, double>], scale: float, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_double
    4. create_periodic_constraint_geometrical(V: dolfinx::fem::FunctionSpace<double>, indicator: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], ndarray[dtype=bool, shape=(*), order='C']], relation: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float64, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<std::complex<double>, double>], scale: complex, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_complex_double

Invoked with types: dolfinx.cpp.fem.FunctionSpace_float64, function, function, list, float, bool 

And the error for demo_periodic3d_topological.py:

Traceback (most recent call last):
  File "/home/bnherrerac/p2/demos/demo_periodic3d_topological.py", line 187, in <module>
    demo_periodic3D(celltype)
  File "/home/bnherrerac/p2/demos/demo_periodic3d_topological.py", line 97, in demo_periodic3D
    mpc.create_periodic_constraint_topological(V.sub(0), mt, 2, periodic_relation, bcs, default_scalar_type(1))
  File "/home/bnherrerac/anaconda3/envs/fenicsx-env/lib/python3.12/site-packages/dolfinx_mpc/multipointconstraint.py", line 254, in create_periodic_constraint_topological
    mpc_data = dolfinx_mpc.cpp.mpc.create_periodic_constraint_topological(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: create_periodic_constraint_topological(): incompatible function arguments. The following argument types are supported:
    1. create_periodic_constraint_topological(V: dolfinx::fem::FunctionSpace<float>, meshtags: dolfinx::mesh::MeshTags<int>, dim: int, relation: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float32, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<float, float>], scale: float, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_float
    2. create_periodic_constraint_topological(V: dolfinx::fem::FunctionSpace<float>, meshtags: dolfinx::mesh::MeshTags<int>, dim: int, relation: Callable[[numpy.ndarray[dtype=float32, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float32, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<std::complex<float>, float>], scale: complex, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_complex_float
    3. create_periodic_constraint_topological(V: dolfinx::fem::FunctionSpace<double>, meshtags: dolfinx::mesh::MeshTags<int>, dim: int, relation: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float64, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<double, double>], scale: float, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_double
    4. create_periodic_constraint_topological(V: dolfinx::fem::FunctionSpace<double>, meshtags: dolfinx::mesh::MeshTags<int>, dim: int, relation: Callable[[numpy.ndarray[dtype=float64, writable=False, shape=(*, *), ]], numpy.ndarray[dtype=float64, shape=(*, *), ]], bcs: list[dolfinx::fem::DirichletBC<std::complex<double>, double>], scale: complex, collapse: bool) -> dolfinx_mpc.cpp.mpc.mpc_data_complex_double

Invoked with types: dolfinx.cpp.fem.FunctionSpace_float64, dolfinx.cpp.mesh.MeshTags_int32, int, function, list, float, bool

I installed dolfinx and dolfinx_mpc via conda install, and made sure that both versions are 0.8.0. I am trying to run a similar code, where I impose periodic boundary conditions in opposite faces of an unit cell, but I get stuck when calling create_periodic_constraint_geometrical, as in the demo. If you have any idea how I could get around this, it would be very helpful. Thanks in advance!

[jorgensd]

Could you try with 0.8.1: https://github.com/jorgensd/dolfinx_mpc/tree/v0.8.1
and also give me the conda commands you ran to create your environment ?

[bnherrerac]

Tried with 0.8.1 keeping dolfinx 0.8.0, the same error happened. I rerun these conda commands to create the env and install all the dependencies:

conda create -n fenicsx-env
conda activate fenicsx-env
conda install -c conda-forge fenics-dolfinx mpich pyvista
conda install conda-forge::dolfinx_mpc
conda install conda-forge::pytest
conda install scipy

which leaves me with dolfinx 0.8.0 and dolfinx-mpc 0.8.1. Here is a MWE that reproduces the error after this installation:

import numpy as np
from mpi4py import MPI
from dolfinx import fem, mesh
from dolfinx.common import Timer
from dolfinx_mpc import MultiPointConstraint

dolfinx_mesh = mesh.create_unit_cube(MPI.COMM_WORLD, 10, 10, 10)
V = fem.functionspace(dolfinx_mesh, ("Lagrange", 1, (dolfinx_mesh.geometry.dim, )))

def x_periodic_boundary(x):
    return np.isclose(x[0], 1.0, atol=1e-8)

def x_periodic_relation(x):
    out_x = np.zeros_like(x)
    out_x[0] = 1 - x[0]
    out_x[1] = x[1]
    out_x[2] = x[2]
    return out_x

with Timer("~PERIODIC: Initialize MPC"):
    mpc = MultiPointConstraint(V)
    mpc.create_periodic_constraint_geometrical(V, x_periodic_boundary, x_periodic_relation, bcs=[])
    mpc.finalize()

Thank you for your help!

[jorgensd]

I can reproduce this. I think this is an issue with an incompatibility with nanobind versions.
I will ask @minrk for guidance as he is a wizard at this!

[minrk]

This is almost certainly an incompatibility in nanobind (likely a compiler version mismatch) that should be pinned but apparently isn't. Can you share the output of conda env export?

[minrk]

Yup, it's the same nanobind abi pinning issue that I believe I've fixed in dolfinx itself, but didn't realize it extended to mpc as well. The quickest workaround is to add gxx=12 to your list of packages, and it should pick the right compatible version of everything.

When this PR is merged, the latest builds of everything should work together again.

[bnherrerac]

Thank you both for looking into this. The command conda install gxx=12 worked well as a workaround. I am having a similar issue in scifem too, the exact same as here.

This is the output of conda env export:

channels:
  - conda-forge
  - defaults
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=2_gnu
  - aiohappyeyeballs=2.4.2=pyhd8ed1ab_0
  - aiohttp=3.10.6=py312h66e93f0_0
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  - alsa-lib=1.2.12=h4ab18f5_0
  - aom=3.9.1=hac33072_0
  - attrs=24.2.0=pyh71513ae_0
  - binutils_impl_linux-64=2.43=h4bf12b8_1
  - binutils_linux-64=2.43=h4852527_1
  - blosc=1.21.6=hef167b5_0
  - brotli=1.1.0=hb9d3cd8_2
  - brotli-bin=1.1.0=hb9d3cd8_2
  - brotli-python=1.1.0=py312h2ec8cdc_2
  - bzip2=1.0.8=h4bc722e_7
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  - cairo=1.18.0=hebfffa5_3
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  - dav1d=1.2.1=hd590300_0
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  - dolfinx_mpc=0.8.1=py312h369e91a_0
  - double-conversion=3.3.0=h59595ed_0
  - eigen=3.4.0=h00ab1b0_0
  - exceptiongroup=1.2.2=pyhd8ed1ab_0
  - expat=2.6.3=h5888daf_0
  - fenics-basix=0.8.0=py312h2492b07_1
  - fenics-dolfinx=0.8.0=py312h66e9945_105
  - fenics-ffcx=0.8.0=pyh4af843d_0
  - fenics-libbasix=0.8.0=h9187eef_1
  - fenics-libdolfinx=0.8.0=h17dcdb5_105
  - fenics-ufcx=0.8.0=h22f594c_0
  - fenics-ufl=2024.1.0=pyhd8ed1ab_0
  - ffmpeg=6.1.2=gpl_h8657690_705
  - fftw=3.3.10=mpi_mpich_hbcf76dd_10
  - fltk=1.3.9=h9305793_1
  - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
  - font-ttf-inconsolata=3.000=h77eed37_0
  - font-ttf-source-code-pro=2.038=h77eed37_0
  - font-ttf-ubuntu=0.83=h77eed37_3
  - fontconfig=2.14.2=h14ed4e7_0
  - fonts-conda-ecosystem=1=0
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  - freeimage=3.18.0=h4bd6248_21
  - freetype=2.12.1=h267a509_2
  - fribidi=1.0.10=h36c2ea0_0
  - frozenlist=1.4.1=py312h66e93f0_1
  - gcc=12.4.0=h236703b_1
  - gcc_impl_linux-64=12.4.0=hb2e57f8_1
  - gcc_linux-64=12.4.0=h6b7512a_4
  - gl2ps=1.4.2=hae5d5c5_1
  - glew=2.1.0=h9c3ff4c_2
  - gmp=6.3.0=hac33072_2
  - gmsh=4.12.2=h6b98cf8_0
  - graphite2=1.3.13=h59595ed_1003
  - gxx=12.4.0=h236703b_1
  - gxx_impl_linux-64=12.4.0=h613a52c_1
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  - importlib_resources=6.4.5=pyhd8ed1ab_0
  - iniconfig=2.0.0=pyhd8ed1ab_0
  - jsoncpp=1.9.6=h84d6215_0
  - jxrlib=1.1=hd590300_3
  - kahip=3.16=h2fbc463_4
  - kahip-python=3.16=py312ha7be871_4
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  - libadios2=2.10.1=mpi_mpich_hb885cfe_3
  - libaec=1.1.3=h59595ed_0
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  - libdolfinx_mpc=0.8.1=h641d226_0
  - libdrm=2.4.123=hb9d3cd8_0
  - libedit=3.1.20191231=he28a2e2_2
  - libegl=1.7.0=ha4b6fd6_0
  - libev=4.33=hd590300_2
  - libexpat=2.6.3=h5888daf_0
  - libffi=3.4.2=h7f98852_5
  - libgcc=14.1.0=h77fa898_1
  - libgcc-devel_linux-64=12.4.0=ha4f9413_101
  - libgcc-ng=14.1.0=h69a702a_1
  - libgfortran=14.1.0=h69a702a_1
  - libgfortran-ng=14.1.0=h69a702a_1
  - libgfortran5=14.1.0=hc5f4f2c_1
  - libgl=1.7.0=ha4b6fd6_0
  - libglib=2.82.1=h2ff4ddf_0
  - libglu=9.0.0=ha6d2627_1004
  - libglvnd=1.7.0=ha4b6fd6_0
  - libglx=1.7.0=ha4b6fd6_0
  - libgomp=14.1.0=h77fa898_1
  - libhwloc=2.11.1=default_hecaa2ac_1000
  - libiconv=1.17=hd590300_2
  - libjpeg-turbo=3.0.0=hd590300_1
  - liblapack=3.9.0=24_linux64_openblas
  - libllvm19=19.1.0=ha7bfdaf_0
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  - libnghttp2=1.58.0=h47da74e_1
  - libnsl=2.0.1=hd590300_0
  - libogg=1.3.5=h4ab18f5_0
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  - libopenvino=2024.4.0=hac27bb2_0
  - libopenvino-auto-batch-plugin=2024.4.0=h4d9b6c2_0
  - libopenvino-auto-plugin=2024.4.0=h4d9b6c2_0
  - libopenvino-hetero-plugin=2024.4.0=h3f63f65_0
  - libopenvino-intel-cpu-plugin=2024.4.0=hac27bb2_0
  - libopenvino-intel-gpu-plugin=2024.4.0=hac27bb2_0
  - libopenvino-intel-npu-plugin=2024.4.0=hac27bb2_0
  - libopenvino-ir-frontend=2024.4.0=h3f63f65_0
  - libopenvino-onnx-frontend=2024.4.0=h56242b0_0
  - libopenvino-paddle-frontend=2024.4.0=h56242b0_0
  - libopenvino-pytorch-frontend=2024.4.0=h5888daf_0
  - libopenvino-tensorflow-frontend=2024.4.0=h358ae18_0
  - libopenvino-tensorflow-lite-frontend=2024.4.0=h5888daf_0
  - libopus=1.3.1=h7f98852_1
  - libpciaccess=0.18=hd590300_0
  - libpng=1.6.44=hadc24fc_0
  - libpq=16.4=h2d7952a_1
  - libprotobuf=4.25.3=hd5b35b9_1
  - libptscotch=7.0.4=h2376d02_5
  - libraw=0.21.3=hca62329_0
  - libsanitizer=12.4.0=h46f95d5_1
  - libscotch=7.0.4=h3055ed5_5
  - libsodium=1.0.20=h4ab18f5_0
  - libsqlite=3.46.1=hadc24fc_0
  - libssh2=1.11.0=h0841786_0
  - libstdcxx=14.1.0=hc0a3c3a_1
  - libstdcxx-devel_linux-64=12.4.0=ha4f9413_101
  - libstdcxx-ng=14.1.0=h4852527_1
  - libtheora=1.1.1=h4ab18f5_1006
  - libtiff=4.7.0=h6565414_0
  - libuuid=2.38.1=h0b41bf4_0
  - libva=2.22.0=h8a09558_1
  - libvorbis=1.3.7=h9c3ff4c_0
  - libvpx=1.14.1=hac33072_0
  - libwebp-base=1.4.0=hd590300_0
  - libxcb=1.17.0=h8a09558_0
  - libxcrypt=4.4.36=hd590300_1
  - libxkbcommon=1.7.0=h2c5496b_1
  - libxml2=2.12.7=he7c6b58_4
  - libzip=1.11.1=hf83b1b0_0
  - libzlib=1.3.1=h4ab18f5_1
  - loguru=0.7.2=py312h7900ff3_2
  - lz4-c=1.9.4=hcb278e6_0
  - matplotlib-base=3.9.2=py312hd3ec401_1
  - metis=5.1.0=h59595ed_1007
  - mpfr=4.2.1=h90cbb55_3
  - mpi=1.0=mpich
  - mpi4py=4.0.0=py312h0068001_3
  - mpich=4.2.2=h670b19f_101
  - msgpack-python=1.1.0=py312h68727a3_0
  - multidict=6.1.0=py312h66e93f0_0
  - mumps-include=5.7.3=ha770c72_0
  - mumps-mpi=5.7.3=hd6ed86c_0
  - munkres=1.1.4=pyh9f0ad1d_0
  - mysql-common=9.0.1=h266115a_1
  - mysql-libs=9.0.1=he0572af_1
  - ncurses=6.5=he02047a_1
  - nlohmann_json=3.11.3=he02047a_1
  - numpy=2.1.1=py312h58c1407_0
  - occt=7.7.2=novtk_h130ccc2_101
  - ocl-icd=2.3.2=hd590300_1
  - openexr=3.2.2=h04e0de5_2
  - openh264=2.4.1=h59595ed_0
  - openjpeg=2.5.2=h488ebb8_0
  - openssl=3.3.2=hb9d3cd8_0
  - packaging=24.1=pyhd8ed1ab_0
  - parmetis=4.0.3=h583469f_1006
  - pathspec=0.12.1=pyhd8ed1ab_0
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  - pillow=10.4.0=py312h56024de_1
  - pip=24.2=pyh8b19718_1
  - pixman=0.43.2=h59595ed_0
  - pkg-config=0.29.2=h4bc722e_1009
  - platformdirs=4.3.6=pyhd8ed1ab_0
  - pluggy=1.5.0=pyhd8ed1ab_0
  - pooch=1.8.2=pyhd8ed1ab_0
  - proj=9.5.0=h12925eb_0
  - pthread-stubs=0.4=hb9d3cd8_1002
  - pugixml=1.14=h59595ed_0
  - pycparser=2.22=pyhd8ed1ab_0
  - pyparsing=3.1.4=pyhd8ed1ab_0
  - pysocks=1.7.1=pyha2e5f31_6
  - pytest=8.3.3=pyhd8ed1ab_0
  - python=3.12.6=hc5c86c4_1_cpython
  - python-dateutil=2.9.0=pyhd8ed1ab_0
  - python-gmsh=4.12.2=h57928b3_0
  - python_abi=3.12=5_cp312
  - pyvista=0.44.1=pyhd8ed1ab_0
  - qhull=2020.2=h434a139_5
  - qt6-main=6.7.3=h20baabe_0
  - rapidjson=1.1.0.post20240409=hac33072_1
  - readline=8.2=h8228510_1
  - requests=2.32.3=pyhd8ed1ab_0
  - scalapack=2.2.0=h417d24c_2
  - scikit-build=0.18.1=pyh4afc917_0
  - scikit-build-core=0.10.7=pyh4afc917_0
  - scipy=1.14.1=py312h7d485d2_0
  - scooby=0.10.0=pyhd8ed1ab_0
  - setuptools=75.1.0=pyhd8ed1ab_0
  - six=1.16.0=pyh6c4a22f_0
  - slepc=3.21.1=real_h97ad6bc_302
  - slepc4py=3.21.1=py312hf817a4c_104
  - snappy=1.2.1=ha2e4443_0
  - sqlite=3.46.1=h9eae976_0
  - suitesparse=7.8.2=hb42a789_0
  - superlu=5.2.2=h00795ac_0
  - superlu_dist=9.0.0=h3feb4ed_1
  - svt-av1=2.2.1=h5888daf_0
  - sysroot_linux-64=2.17=h4a8ded7_17
  - tbb=2021.13.0=h84d6215_0
  - tbb-devel=2021.13.0=h94b29a5_0
  - tk=8.6.13=noxft_h4845f30_101
  - tomli=2.0.1=pyhd8ed1ab_0
  - typing-extensions=4.12.2=hd8ed1ab_0
  - typing_extensions=4.12.2=pyha770c72_0
  - tzdata=2024a=h8827d51_1
  - urllib3=2.2.3=pyhd8ed1ab_0
  - utfcpp=4.0.5=ha770c72_0
  - vtk=9.3.1=qt_py312he5e186c_208
  - vtk-base=9.3.1=qt_py312h2768b8c_208
  - vtk-io-ffmpeg=9.3.1=qt_py312hc8241c7_208
  - wayland=1.23.1=h3e06ad9_0
  - wayland-protocols=1.37=hd8ed1ab_0
  - wheel=0.44.0=pyhd8ed1ab_0
  - wslink=2.2.1=pyhd8ed1ab_0
  - x264=1!164.3095=h166bdaf_2
  - x265=3.5=h924138e_3
  - xcb-util=0.4.1=hb711507_2
  - xcb-util-cursor=0.1.5=hb9d3cd8_0
  - xcb-util-image=0.4.0=hb711507_2
  - xcb-util-keysyms=0.4.1=hb711507_0
  - xcb-util-renderutil=0.3.10=hb711507_0
  - xcb-util-wm=0.4.2=hb711507_0
  - xkeyboard-config=2.42=h4ab18f5_0
  - xorg-inputproto=2.3.2=hb9d3cd8_1003
  - xorg-kbproto=1.0.7=hb9d3cd8_1003
  - xorg-libice=1.1.1=hb9d3cd8_1
  - xorg-libsm=1.2.4=h7391055_0
  - xorg-libx11=1.8.10=h4f16b4b_0
  - xorg-libxau=1.0.11=hb9d3cd8_1
  - xorg-libxdmcp=1.1.3=hb9d3cd8_1
  - xorg-libxext=1.3.4=hb9d3cd8_3
  - xorg-libxfixes=5.0.3=hb9d3cd8_1005
  - xorg-libxi=1.7.10=h4bc722e_1
  - xorg-libxmu=1.1.3=h4ab18f5_1
  - xorg-libxrender=0.9.11=hb9d3cd8_1
  - xorg-libxt=1.3.0=hd590300_1
  - xorg-libxtst=1.2.5=h4bc722e_0
  - xorg-libxxf86vm=1.1.5=hb9d3cd8_2
  - xorg-recordproto=1.14.2=hb9d3cd8_1003
  - xorg-xextproto=7.3.0=hb9d3cd8_1004
  - xorg-xorgproto=2024.1=hb9d3cd8_1
  - xorg-xproto=7.0.31=hb9d3cd8_1008
  - xz=5.2.6=h166bdaf_0
  - yaml=0.2.5=h7f98852_2
  - yarl=1.13.1=py312h66e93f0_0
  - zeromq=4.3.5=ha4adb4c_5
  - zfp=0.5.5=h9c3ff4c_8
  - zipp=3.20.2=pyhd8ed1ab_0
  - zlib=1.3.1=h4ab18f5_1
  - zlib-ng=2.2.2=h5888daf_0
  - zstandard=0.23.0=py312hef9b889_1
  - zstd=1.5.6=ha6fb4c9_0
  - pip:
      - nanobind==2.1.0
      - scifem==0.2.5
prefix: /home/bnherrerac/anaconda3/envs/fenicsx-env```

</details>