I'm using M1pro and have successfully installed Numpy with Accelerate following, and it really speedup my programs. I also ran np.test() to check the correctness and every test passed. However, I can't install Scipy with Accelerate, since the official document said Accelerate has a LAPACK of too old version. I can't even find a scipy that can pass scipy.test(). I tried the codes below: conda install numpy 'libblas=*=*accelerate' conda install scipy np.test() as fails, sp.test() can't even finish conda install numpy 'libblas=*=*openblas' conda install scipy Both np.test() and sp.test() can finish, but with many failures. I believe the bugs are due to Conda. pip install --no-binary :all: --no-use-pep517 numpy pip install scipy np.test() has no failure and went fast, sp.test() uses OpenBLAS and has 3 failures. This is the best version I have found. So my question is: can we find a reliable version of scipy on M1? Considering the popularity of scipy, I think it's not a high-living expectation. And a question for Apple: is there really a plan to upgrade the LAPACK in Accelerate?

Hi there I'm writing some audio plug-ins that use biquad filtering of incoming audio. The audio is supplied to me as vectors of doubles. I am using the Accelerate callbacks of vDSP_biquad_CreateSetupD, vDSP_biquad_DestroySetupD and vDSP_biquadD on a vDSP_biquad_SetupD struct. When the user changes the filter parameters, I want to update the coefficients of the biquad filter. I assumed that I would be able to use the new vDSP_biquad_SetCoefficientsDouble callback, but that requires a vDSP_biquad_Setup rater than a vDSP_biquad_SetupD — i.e. a single-precision vector, rather than the double-precision vector that I would have thought it would require. Is that an error? How do I update the coefficients of a double-precision object? Thanks in advance, Michael