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authorDillon Niederhut <dniederhut@enthought.com>2017-08-11 18:29:37 -0500
committerDillon Niederhut <dniederhut@enthought.com>2017-08-11 18:29:37 -0500
commit01d5886a5ad760e7a27f2f7d715177fafb3777cd (patch)
tree12e6351b404a3df9f660c8658edf5844398c0275 /numpy/doc/basics.py
parent3d58387717eeb5d8aebe1d712ddbbd04adef2cb2 (diff)
downloadnumpy-01d5886a5ad760e7a27f2f7d715177fafb3777cd.tar.gz
DOC: reverts some escapes [ci-skip]
Diffstat (limited to 'numpy/doc/basics.py')
-rw-r--r--numpy/doc/basics.py4
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