diff options
Diffstat (limited to 'numpy/doc/basics.py')
| -rw-r--r-- | numpy/doc/basics.py | 16 |
1 files changed, 9 insertions, 7 deletions
diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py index 3d473da8f..745bff15a 100644 --- a/numpy/doc/basics.py +++ b/numpy/doc/basics.py @@ -151,10 +151,11 @@ useful to use floating-point numbers with more precision. Whether this is possible in numpy depends on the hardware and on the development environment: specifically, x86 machines provide hardware floating-point with 80-bit precision, and while most C compilers provide this as their -``long double`` type, MSVC makes ``long double`` identical to ``double`` -(64 bits). Numpy makes the compiler's ``long double`` available as -``np.longdouble`` (and ``np.clongdouble`` for the complex numbers). -You can find out what your numpy provides with``np.finfo(np.longdouble)``. +``long double`` type, MSVC (standard for Windows builds) makes +``long double`` identical to ``double`` (64 bits). Numpy makes the +compiler's ``long double`` available as ``np.longdouble`` (and +``np.clongdouble`` for the complex numbers). You can find out what your +numpy provides with``np.finfo(np.longdouble)``. Numpy does not provide a dtype with more precision than C ``long double``s; in particular, the 128-bit IEEE quad precision @@ -166,9 +167,10 @@ depends on hardware and development environment; typically on 32-bit systems they are padded to 96 bits, while on 64-bit systems they are typically padded to 128 bits. ``np.longdouble`` is padded to the system default; ``np.float96`` and ``np.float128`` are provided for users who -want specific padding (for space or compatibility reasons). In spite -of the names, these provide only as much precision as ``np.longdouble``, -that is, 64 or 80 bits on x86 machines. +want specific padding. In spite of the names, ``np.float96`` and +``np.float128`` provide only as much precision as ``np.longdouble``, +that is, 80 bits on most x86 machines and 64 bits in standard +Windows builds. Be warned that even if ``np.longdouble`` offers more precision than python ``float``, it is easy to lose that extra precision, since |