I have a one dimensional NumPy array:
a = numpy.array([2,3,3])
I would like to have the product of all elements, 18 in this case.
The only way I could find to do this would be:
b = reduce(lambda x,y: x*y, a)
Which looks pretty, but is not very fast (I need to do this a lot).
Is there a numpy method that does this? If not, what is the most efficient way of doing this? My real world arrays have 39 float elements.
In NumPy you can try:
numpy.prod(a)
For a larger array numpy.arange(1,40) / 10.
:
array([ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. , 1.1,
1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. , 2.1, 2.2,
2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2, 3.3,
3.4, 3.5, 3.6, 3.7, 3.8, 3.9])
your reduce(lambda x,y: x*y, a)
needs 24.2µs,
numpy.prod(a)
needs 3.9µs.
EDIT: a.prod()
needs 2.67µs. Thanks to J.F. Sebastian!
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