Numpy longdouble arithmetic does not seem to be in long double with conversion

Question

I have been playing C99\'s quad precision long double. It is my understanding that (platform specific) numpy supports long double and 128bit floats.

I have run acro

Answer 1

NumPy does not provide quad precision on x86 machines. It does provide access to the C long double type (as provided by the compilation environment; with MSVC this may be 64 bits, with GCC it is normally 80 bits) as np.longdouble. The types np.float96 and np.float128 are simply long doubles padded to 96 or 128 bits (for aligned memory access). See the numpy docs. To get quad precision in numpy you need to use a hardware platform and compiler where long double is actual quad precision.

While it would be possible for numpy to support quad precision using compiler support (GCC's float128) or external libraries, this has not been implemented. It would also be possible to write a third-party importable module that made one of these available, but that has not been done either.

Note too that even when using np.longdouble, it is easy to lose precision: for example, the % operator forces numpy to pass its numbers through python floats, throwing away any extra precision.