Numpy Support in numba

One objective of numba is having a seamless integration with NumPy. NumPy arrays provide an efficient storage method for homogeneous sets if data. NumPy dtypes provide type information useful when compiling, and the regular, structured storage of potentially large amounts of data in memory provides an ideal memory layout for code generation. numba excels at generating code that executes on top of NumPy arrays.

NumPy support in Numba comes in many forms: * numba understands NumPy ufuncs and is able to generate equivalent native code for many of them. * NumPy arrays are directly supported in numba. Access to Numpy arrays is very efficient, as indexing is lowered to memory accessing when possible. * numba is able to generate ufuncs/gufuncs. This means that it is possible to implement ufuncs/gufuncs within Python, getting speeds comparable to that of ufuncs/gufuncs implemented in C extension modules using the NumPy C API.

Supported ufuncs

One objective on numba is having all the standard ufuncs in NumPy understood by numba. When a supported ufunc is found when compiling a function, numba maps the ufunc to equivalent native code. This allows the use of those ufuncs in numba code that gets compiled in no-python mode.

Limitations

Right now support for ufuncs is quite limited in no-python mode. Meaning that only a selection of the ufuncs work in no-python mode.

Also, in its current implementation ufuncs working on arrays will only compile in no-python mode if the output is explicit (the output array is passed as second argument). Note that this limitation does not apply when applied to scalars

Following is a list of the different NumPy ufuncs that numba is aware of, sorted in the same way as in the NumPy documentation.

Math operations

UFUNC	MODE
name	python-mode	no-python
add	Yes	Yes
subtract	Yes	Yes
multiply	Yes	Yes
divide	Yes	Yes
logaddexp	Yes	Yes
logaddexp2	Yes	Yes
true_divide	Yes	Yes
floor_divide	Yes	Yes
negative	Yes	Yes
power	Yes	Yes
remainder	Yes	No
mod	Yes	No
fmod	Yes	No
abs	Yes	Yes
absolute	Yes	Yes
fabs	Yes	Yes
rint	Yes	Yes
sign	Yes	Yes
conj	Yes	No
exp	Yes	Yes
exp2	Yes	Yes
log	Yes	Yes
log2	Yes	Yes
log10	Yes	Yes
expm1	Yes	Yes
log1p	Yes	Yes
sqrt	Yes	Yes
square	Yes	No
reciprocal	Yes	No
conjugate	Yes	No

Trigonometric functions

UFUNC	MODE
name	python-mode	no-python
sin	Yes	Yes
cos	Yes	Yes
tan	Yes	Yes
arcsin	Yes	Yes
arccos	Yes	Yes
arctan	Yes	Yes
arctan2	Yes	Yes
hypot	Yes	Yes
sinh	Yes	Yes
cosh	Yes	Yes
tanh	Yes	Yes
arcsinh	Yes	Yes
arccosh	Yes	Yes
arctanh	Yes	Yes
deg2rad	Yes	Yes
rad2deg	Yes	Yes
degrees	Yes	Yes
radians	Yes	Yes

Bit-twiddling functions

UFUNC	MODE
name	python-mode	no-python
bitwise_and	Yes	No
bitwise_or	Yes	No
bitwise_xor	Yes	No
bitwise_not	Yes	No
invert	Yes	No
left_shift	Yes	No
right_shift	Yes	No

Comparison functions

UFUNC	MODE
name	python-mode	no-python
greater	Yes	No
greater_equal	Yes	No
less	Yes	No
less_equal	Yes	No
not_equal	Yes	No
equal	Yes	No
logical_and	Yes	No
logical_or	Yes	No
logical_xor	Yes	No
logical_not	Yes	No
maximum	Yes	No
minimum	Yes	No
fmax	Yes	No
fmin	Yes	No

Floating functions

UFUNC	MODE
name	python-mode	no-python
isfinite	Yes	No
isinf	Yes	No
isnan	Yes	No
signbit	Yes	No
copysign	Yes	Yes
nextafter	Yes	No
modf	Yes	No
ldexp	Yes*	No
frexp	Yes	No
floor	Yes	Yes
ceil	Yes	Yes
trunc	Yes	Yes
spacing	Yes	No

* not supported on windows 32 bit