Given a NumPy array A, what is the fastest/most effic开发者_运维知识库ient way to apply the same function, f, to every cell?
I need to calculate the euclidean distance between 2 matrices in matlab. Currently I am using bsxfun and calculating the distance as below( i am attaching a snippet of the code ):
Here\'s another one: ValidFirings = ((DwellTimes > 30/(24*60*60)) | (GroupCount > 1)); for i = length(ValidFirings):-1:2
As a toy example, suppose that we have a function called \'my_func\' (the code is below) that takes two parameters \'n\' and \'p\'. Our function, \'my_func\', will generate a random matrix \'x\' with
I was programming something in MATLAB and, as recommended, I am always trying to use vectorization. But in the end the program was quite slow. So I found out that in one place the code is significantl
One particular hot spot when I profile a code I am working on, is the following loop: for(int loc = start; loc<end; ++loc)
i am just interested in how these things work and am after a library or paper that describes the approach that most of these take. At a guess they pro开发者_开发百科bably support a few basic construct
I was just playing around with the Altivec extension on a power6 cluster we have.I noticed that when I compiled the code below without any optimizations, my speedup was 4 as I was expecting.However, w
[EDIT:I sort of brush this example up so I didn\'t clean up my code very well. My question is more on, how do I pass a subarray into a numpy.vectorize-d function, not specifically about this example.]
I\'ve got a data frame containing a vector of x values, a vector of y values, and a vector of IDs: x <- rep(0:3, 3)
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