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| author | Dillon Niederhut <dniederhut@enthought.com> | 2017-07-27 00:03:08 -0600 |
|---|---|---|
| committer | Dillon Niederhut <dniederhut@enthought.com> | 2017-07-27 00:03:08 -0600 |
| commit | 3d58387717eeb5d8aebe1d712ddbbd04adef2cb2 (patch) | |
| tree | df00020b6b15e773337a80c37232f23db18e4bc8 /numpy/doc/basics.py | |
| parent | ec3710f9b5f9957e57cf11cadac34a8c3e69cc79 (diff) | |
| download | numpy-3d58387717eeb5d8aebe1d712ddbbd04adef2cb2.tar.gz | |
DOC: removes extraneous whitespace with escapes
[ci-skip]
Diffstat (limited to 'numpy/doc/basics.py')
| -rw-r--r-- | numpy/doc/basics.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py index 40fb0501e..b79fb2a86 100644 --- a/numpy/doc/basics.py +++ b/numpy/doc/basics.py @@ -155,11 +155,11 @@ 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 -data type (FORTRAN's ``REAL*16`` ) is not available. +``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 padded with zero bits, either to 96 or 128 bits. Which is more efficient |