I installed Intel MKL and other libraries for a customized numpy. Here is my `~/.numpy-site.cfg`:
[DEFAULT] library_dirs = /usr/lib:/usr/local/lib include_dirs = /usr/include:/usr/local/include [mkl] library_dirs = /opt/intel/mkl/lib/intel64/ include_dirs = /opt/intel/mkl/include/ mkl_libs = mkl_intel_ilp64, mkl_intel_thread, mkl_core, mkl_rt lapack_libs = [amd] amd_libs = amd [umfpack] umfpack_libs = umfpack [djbfft] include_dirs = /usr/local/djbfft/include library_dirs = /usr/local/djbfft/lib
This configuration file seems OK during the installation of numpy. But when I was installing scipy via `pip3 install scipy`, it reported that
numpy.distutils.system_info.BlasNotFoundError: Blas (http://www.netlib.org/blas/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [blas]) or by setting the BLAS environment variable.
In my mind MKL is an implementation of Blas so just mentioning MKL should be fine. I've tried
1. `export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64:$LD_LIBRARY_PATH`
2. `export BLAS=/opt/intel/mkl/lib/intel64`
3. Copy the content in the `[mkl]` section and paste into the `[blas]` section in the file `~/.numpy-site.cfg`
But none of these works. So what is going wrong? Does scipy respect `~/.numpy-site.cfg`? Thank you.