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"?

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.

Dec 15, 2021 · How can I convert an image to a vectorised form? Normal image: Vectorised Image: I implemented image segmentation using the SLIC method. The result is close to the desired outcome …

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 instructions, …

Oct 6, 2018 · I am using Pandas dataframes and want to create a new column as a function of existing columns. I have not seen a good discussion of the speed difference between df.apply() and …

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 …

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 ...

Nov 6, 2015 · With the GCC compiler, the -ftree-vectorize option turns on auto-vectorization, and this flag is automatically set when using -O3. To what level does it vectorize?

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 ?

Mar 6, 2015 · vectorize conditional assignment in pandas dataframe Asked 10 years, 10 months ago Modified 2 years, 11 months ago Viewed 58k times