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"?

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?

The purpose of np.vectorize is to transform functions which are not numpy-aware (e.g. take floats as input and return floats as output) into functions that can operate on (and return) numpy arrays.

Jul 19, 2024 · I am trying to Import and vectorize data from Azure Blob Storage to Azure AI Search. I have two embedding models deployed in Azure AI Studio - text-embedding-3-small …

Jul 9, 2014 · Let's say we have the following function: def f(x, y): if y == 0: return 0 return x/y This works fine with scalar values. Unfortunately when I try to use numpy arrays for x and y the

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 ?

Sep 14, 2009 · 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 …

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 …

Oct 3, 2013 · Bear in mind that np.vectorize doesn't really give any performance benefit over a plain list comprehension - you'll still end up looping in Python rather than C

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 ...