diff options
Diffstat (limited to 'numpy/lib/nanfunctions.py')
| -rw-r--r-- | numpy/lib/nanfunctions.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index 7f7aea9bc..ab88c6a37 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -204,7 +204,7 @@ def nanmin(a, axis=None, out=None, keepdims=np._NoValue): Notes ----- - Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic + NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. @@ -311,7 +311,7 @@ def nanmax(a, axis=None, out=None, keepdims=np._NoValue): Notes ----- - Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic + NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. @@ -453,7 +453,7 @@ def nansum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero. - In Numpy versions <= 1.8 Nan is returned for slices that are all-NaN or + In NumPy versions <= 1.8 Nan is returned for slices that are all-NaN or empty. In later versions zero is returned. Parameters |