R - vectorizing a which operation
Date : March 29 2020, 07:55 AM
hop of those help? Hi I have a function in R that I'm trying to optimize for performance. I need to vectorize a for loop. My problem is the slightly convoluted data structure and the way I need to perform lookups using the 'which' command. , You could write your function like this: foo <- function(AA, BB, CC) {
pa <- AA*CC
x <- outer(pa, pa)
diag(x) <- 0
res <- colSums(x)*BB
return(res)
}
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Vectorizing this non-unique-key operation
Tag : python , By : Sigtryggur
Date : March 29 2020, 07:55 AM
may help you . Here's a vectorized approach based upon searchsorted - # Get sorted index positions
idx = np.searchsorted(rows, test)
# Set out-of-bounds(invalid ones) to some dummy index, say 0
idx[idx==len(rows)] = 0
# Get invalid mask array found out by indexing data array
# with those indices and looking for matches
invalid_mask = rows[idx] != test
# Get data indexed array as output and set invalid places with 0s
out = data[idx]
out[invalid_mask] = 0
out = data[idx] * (rows[idx] == test) # skips using `invalid_mask`
out = np.where(invalid_mask, 0, data[idx])
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Vectorizing a for-loop operation
Tag : matlab , By : Alecsandru Soare
Date : March 29 2020, 07:55 AM
it should still fix some issue That's pretty simple, especially since j is only used for row indexing here: X(:,1)= random1;
for i = 1:length(Time)
X(:,i+1) = X(:,i) - mu*X(:,i)*TimeStep + Sigma*sqrt(2*mu)*sqrt(TimeStep)*random2(i);
end
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Vectorizing list of lists operation in R
Tag : r , By : Cube_Zombie
Date : March 29 2020, 07:55 AM
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Vectorizing operation in NumPy
Date : March 29 2020, 07:55 AM
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