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author | Dillon Niederhut <dniederhut@enthought.com> | 2017-08-11 18:29:37 -0500 |
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committer | Dillon Niederhut <dniederhut@enthought.com> | 2017-08-11 18:29:37 -0500 |
commit | 01d5886a5ad760e7a27f2f7d715177fafb3777cd (patch) | |
tree | 12e6351b404a3df9f660c8658edf5844398c0275 /numpy/doc/basics.py | |
parent | 3d58387717eeb5d8aebe1d712ddbbd04adef2cb2 (diff) | |
download | numpy-01d5886a5ad760e7a27f2f7d715177fafb3777cd.tar.gz |
DOC: reverts some escapes [ci-skip]
Diffstat (limited to 'numpy/doc/basics.py')
-rw-r--r-- | numpy/doc/basics.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py index b79fb2a86..76d455cd0 100644 --- a/numpy/doc/basics.py +++ b/numpy/doc/basics.py @@ -155,10 +155,10 @@ with 80-bit precision, and while most C compilers provide this as their ``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 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 +``long double``s; in particular, the 128-bit IEEE quad precision data type (FORTRAN's ``REAL*16``\) is not available. For efficient memory alignment, ``np.longdouble`` is usually stored |