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| author | Mark Wiebe <mwwiebe@gmail.com> | 2010-11-10 17:08:45 -0800 |
|---|---|---|
| committer | Charles Harris <charlesr.harris@gmail.com> | 2010-12-01 20:02:15 -0700 |
| commit | 9b72aa96cec9d182062f378fca869aaa303f1ca9 (patch) | |
| tree | 15a2a98c221552c2306bbc4edf2aacdd9533c6f1 /doc/source/reference/arrays.scalars.rst | |
| parent | 632ba9b0cfc07ef7ca49fedc698ebfd3a9031be2 (diff) | |
| download | numpy-9b72aa96cec9d182062f378fca869aaa303f1ca9.tar.gz | |
DOC: core: Update docs for half/float16 type
Diffstat (limited to 'doc/source/reference/arrays.scalars.rst')
| -rw-r--r-- | doc/source/reference/arrays.scalars.rst | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/doc/source/reference/arrays.scalars.rst b/doc/source/reference/arrays.scalars.rst index 62e22146a..001227af4 100644 --- a/doc/source/reference/arrays.scalars.rst +++ b/doc/source/reference/arrays.scalars.rst @@ -12,7 +12,7 @@ convenient in applications that don't need to be concerned with all the ways data can be represented in a computer. For scientific computing, however, more control is often needed. -In NumPy, there are 21 new fundamental Python types to describe +In NumPy, there are 24 new fundamental Python types to describe different types of scalars. These type descriptors are mostly based on the types available in the C language that CPython is written in, with several additional types compatible with Python's types. @@ -138,10 +138,12 @@ Unsigned integers: Floating-point numbers: =================== ============================= =============== +:class:`half` ``'j'`` :class:`single` compatible: C float ``'f'`` :class:`double` compatible: C double :class:`float_` compatible: Python float ``'d'`` :class:`longfloat` compatible: C long float ``'g'`` +:class:`float16` 16 bits :class:`float32` 32 bits :class:`float64` 64 bits :class:`float96` 96 bits, platform? |