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doc: fix table formatting problem, add 'string constant' as supported compiler type

This commit is contained in:
Sebastien Bourdeauducq 2017-01-16 13:58:09 -06:00
parent 043780d603
commit b4f3be7e1b
1 changed files with 24 additions and 23 deletions
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25
doc/manual/compiler.rst
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@ -13,6 +13,7 @@ A number of Python features can be used inside a kernel for compilation and exec
* 64-bit signed integers (use ``numpy.int64`` to convert)
* Double-precision floating point numbers
* Lists of any supported types
* String constants
* User-defined classes, with attributes of any supported types (attributes that are not used anywhere in the kernel are ignored)
For a demonstration of some of these features, see the ``mandelbrot.py`` example.
@ -29,29 +30,29 @@ Kernel code can call host functions without any additional ceremony. However, su
The Python types correspond to ARTIQ type annotations as follows:
+-------------+-------------------------+
+---------------+-------------------------+
| Python | ARTIQ |
+=============+=========================+
+===============+=========================+
| NoneType | TNone |
+-------------+-------------------------+
+-------------+---------------------------+
| bool | TBool |
+-------------+-------------------------+
+-------------+---------------------------+
| int | TInt32 or TInt64 |
+-------------+-------------------------+
+-------------+---------------------------+
| float | TFloat |
+-------------+-------------------------+
+-------------+---------------------------+
| str | TStr |
+-------------+-------------------------+
+-------------+---------------------------+
| list of T | TList(T) |
+-------------+-------------------------+
+-------------+---------------------------+
| range | TRange32, TRange64 |
+-------------+-------------------------+
+-------------+---------------------------+
| numpy.int32 | TInt32 |
+-------------+-------------------------+
+-------------+---------------------------+
| numpy.int64 | TInt64 |
+-------------+-------------------------+
+-------------+---------------------------+
| numpy.float64 | TFloat |
+-------------+-------------------------+
+-------------+---------------------------+
Pitfalls
--------