Feb 13, 2021 · Isn't the answer to How to use np.vectorize? usually "Don't. It just pretends to be a vectorized function but is just a loop with a different name"?

Using Numpy Vectorize on Functions that Return Vectors Asked 15 years, 4 months ago Modified 2 years, 11 months ago Viewed 125k times

Oct 4, 2009 · Is it a good idea to vectorize the code? What are good practices in terms of when to do it? What happens underneath?

Aug 11, 2021 · Many CPUs have "vector" or "SIMD" instruction sets which apply the same operation simultaneously to two, four, or more pieces of data. Modern x86 chips have the SSE instructions, …

Oct 6, 2018 · np.vectorize, list comprehension + zip and map methods, i.e. the top 3, all have roughly the same performance. This is because they use tuple and bypass some Pandas overhead from …

Mar 10, 2016 · I have noticed that the gcc flag -ftree-vectorize is very useful for optimizing code. I am trying to understand better how it works, but the doc is fairly concise: Perform vectorization on trees...

Feb 5, 2016 · What is the most efficient way to map a function over a numpy array? I am currently doing: import numpy as np x = np.array ( [1, 2, 3, 4, 5]) # Obtain array of square ...

Sep 13, 2017 · As the title, I'd like to know how to define a vectorized function in R. Is it just by using a loop in the function? Is this method efficient? And what's the best practice ?

Jan 3, 2009 · The v4 series of the gcc compiler can automatically vectorize loops using the SIMD processor on some modern CPUs, such as the AMD Athlon or Intel Pentium/Core chips. How is this …

Jul 9, 2014 · def f(x, y): np.where(y == 0, 0, x/y) which doesn't work for scalars. Is there a better way to write a function which contains an if statement? It should work with both scalars and arrays.