General usage ¶Īll the functions and classes in the package are available in the main module. Some compilers like LLVM or Clang do not support OpenMP. Support for the parts of the OpenMP 4.0+.
they are included by default if installing torch from pip. The simplest way to get the new repo is to rerun the installation instructions below. sudo apt-get install python3-dev libopenblas-dev pip install cmake scikit-build torch pybind11 OSX. This will unfortunately also destroy references in issues. If you need anything from the previous repo, see ompy_Archive_Sept2019.
Unfortunetely, this has the sideeffect that the history had to be rewritten: Previous commits now have a different SHA1 (git version keys). We cleaned the repository from old comits clogging the repo (big data files that should never have been there). NB: Read this (only) if you have cloned the repo before October 2019: Type export ompy_OpenMP=False in the terminal before the setup above. If you don’t have OpenMP / have problems installing it (see above), you can install without OpenMP. If your standard python and pip link to python 2, you may have to use python3 and pip3. This is useful as most package managers will not be able to remove manually installed packages and so in order to delete this package completely one needs to manually remove all the files.Note that we require python 3.7 or higher. When installing the package manually, if you add the flag –record install.txt, the location of all the installed files will be output to the file install.txt. Note that some of the compiled extensions require Openmp 2.0 or above. For OS-X and Linux the standard compilers should be fine for building the package. A good resource which can help with this can be found here. On Windows machines one needs the correct version of the Microsoft Visual Studios compiler for the given python version one is building the package for. More functionality is available when soft dependencies are installed. For the manual installation you must have all the prerequisite python packages installed:īoost, installation must include header files for boost. For the easiest install with just numpy, pip can generally install trimesh cleanly on Windows, Linux, and OSX: pip install trimesh The minimal install can load many supported formats (STL, PLY, GLTF/GLB) into numpy arrays. For a lighter installation (preferred for computing clusters), one can use miniconda. We recommend the use of the free package manager Anaconda which installs Python and manages its packages. QuSpin is currently being supported for Python 3 which are a prerequisite.
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