simd - What is "vectorization"? - Stack Overflow
WEBSep 14, 2009 · Vectorization is the term for converting a scalar program to a vector program. Vectorized programs can run multiple operations from a single instruction, whereas scalar can only operate on pairs of operands at once. From wikipedia: Scalar approach: for (i = 0; i < 1024; i++) {. C[i] = A[i]*B[i];
c++ - What does vectorization mean? - Stack Overflow
WEBOct 4, 2009 · 1. The constraints like dependency (between different iterations of the loop) needs to be checked before vectorizing the loop. 2. Function calls needs to be prevented. 3. Pointer access can create aliasing and it needs to be prevented.
python - Vectorizing a function in pandas - Stack Overflow
WEBDec 20, 2014 · Vectorizing a function in pandas. Ask Question Asked 9 years, 9 months ago. Modified 9 years, 9 months ago.
numpy - Python vectorizing nested for loops - Stack Overflow
WEBimport numexpr as ne. mask = ne.evaluate('X**2 + Y**2 + Z**2 < radius**2') Approach #2. We can also gradually build the three ranges corresponding to the shape parameters and perform the subtraction against the three elements of roi on the fly without actually creating the meshes as done earlier with np.mgrid.
numpy - Vectorizing a function (Python) - Stack Overflow
WEBOct 3, 2013 · You should name your function h_scalar () 1.) Your exponential should be -.50 * x ** 2.00. 2.) You cannot broadcast an operation like **2.00 across a standard python array. To do this, convert x to a np.array. 3.) If you don't want to use numpy, consider using a for loop to compute the formula for each element in x.
python - Vectorizing or Speeding up Fuzzywuzzy String Matching …
WEBOct 3, 2018 · 4. This solution leverages apply() and should demonstrate reasonable performance improvements. Feel free to play around with the scorer and change the threshold to meet your needs: import pandas as pd, numpy as np. from fuzzywuzzy import process, fuzz. df = pd.DataFrame([['cliftonlarsonallen llp minneapolis MN'],
Why is vectorization, faster in general, than loops?
WEBJan 30, 2016 · 125. Vectorization (as the term is normally used) refers to SIMD (single instruction, multiple data) operation. That means, in essence, that one instruction carries out the same operation on a number of operands in parallel. For example, to multiply a vector of size N by a scalar, let's call M the number of operands that size that it can ...
Why does vectorized code run faster than for loops in MATLAB?
WEBDec 10, 2013 · MATLAB is designed to perform vector operations really quickly. MATLAB is an interpreted language, which is why loops are so slow in it. MATLAB sidesteps this issue by providing extremely fast (usually written in C, and optimized for the specific architecture) and well tested functions to operate on vectors. There is really no magic here, it is ...
Vectorizing a Pandas dataframe for Scikit-Learn
WEBAug 1, 2016 · Since scikit-learn 0.13.0 (Jan 3, 2014) there is a new parameter 'records' for the to_dict() method available, so now you can simple use this method without additional manipulations:
python - How to vectorize a data frame with several text columns …
WEBJun 19, 2015 · I have several pandas data series, and want to train this data to map to an output, df["output"]. So far I have merged the series into one, and separated each by commas. df = pd.read_csv("sourced...