I still need to do some cleanups and add tests, but I finally have this
working and thought I'd share. I'm really happy with this:
In [1]: from sympy import *
In [2]: a, b, c = symbols('a, b, c')
In [3]: expr = (sin(a) + sqrt(b)*c**2)/2
In [4]: from sympy.utilities.autowrap import ufuncify
In [5]: func = ufuncify((a, b, c), expr)
In [6]: func(1, 2, 3)
Out[6]: 6.7846965230828769
In [7]: func([1, 2, 3, 4, 5], [6, 7, 8, 9, 10], 3)
Out[7]: array([ 11.44343933, 12.36052961, 12.79848207, 13.12159875,
13.75078733])
In [8]: from numpy import arange
In [9]: a = arange(10).reshape((2, 5))
In [10]: c = arange(10, 20).reshape((2, 5))
In [11]: b = 25
In [12]: func(a, b, c)
Out[12]:
array([[ 250. , 302.92073549, 360.45464871, 422.57056 ,
489.62159875],
[ 562.02053786, 639.86029225, 722.8284933 , 810.49467912,
902.70605924]])
In [13]: type(func)
Out[13]: numpy.ufunc
This now does everything a numpy `ufunc` does normally, as it *is* a ufunc.
Codegen is hooked up to numpy api. Type conversion and broadcasting are
done automagically.
Caveats: only functions with a single output are accepted (this could be
changed to accept multi-output without much effort though). Also, as with
all unfuncs, input/outputs must all be scalars (no matrix/Indexed
operations allowed).
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