In Python, if I were to make a function which would return a list whose length varies depending on the input, if I couldn’t fit the code into a list comprehension, I’d usually use a yield statement to yield each array element I want in the output. Is there a recommended pattern for doing this in Julia?
One could always create an empty list and then append each wanted entry to that list but I wonder if there’s a better way to do that? Speed is a very crucial factor here as this function will need to be applied to every element in a very large matrix.
In case anyone needs an example of what I actually mean, I’m trying to convert something similar to this function from Python to Julia:
def hop(x, n): for i in range(n-1): mask = 3 << i if x & mask != 0 and x & mask != mask: yield x ^ mask mask = (1 << (n-1)) | 1 if x & mask != 0 and x & mask != mask: yield x ^ mask
What’s going on here is that you give this function two integers
n, where you care about the binary pattern of x mod n. Ie. if I am concerned with the binary pattern
x should be
10 in base
n should be
4 because I’m treating
x as a
4 bit integer.
The function is making a mask, initially 3, ie.
0011 in base
2 and its checking checking if
x shares exactly one
1 bit with
mask and if so, will yield an integer whose binary pattern is the same those of
x in the spots where
mask has zeros and will yield the complement of
x's digits in the positions where
1s. Finally, it does the same thing with a
mask that has
1s at both ends of the digit and
0s everywhere else.
From the amount of control structure here, I don’t think this is a good candidate for list comprehensions but I also suspect that creating an empty list and appending to it isn’t ideal.