I am using accumarray() to create a 3D array from a list of xyz coordinates PointCoors and their respective values PointValues like this:
Stack=accumarray([PointCoors(:,1),PointCoors(:,2),PointCoors(:,3)],PointValues,...
StackSize,#max,uint16(0));
However I found out that accumarray() does not multithread (don't see why it shouldn't) and as a result of this the computation of this step takes too long.
Is there an alternative to accumarray() that can take advantage of multiple cores?
Thank you
Related
I was looking for something similar to lower_bound() function for sets in
python, as we have in C++.
Task is to have a ds, which inserts element in sorted manner, storing only single instance of each distinct value, and returns the left neighbor of a given value, both operations in O(logn) worst time in python.
python: something similar to bisect module for lists, with efficient insertion may work.
sets are unordered, and the standard lib does not offer tree structures.
Maybe you could look at sorted containers (3rd party lib): http://www.grantjenks.com/docs/sortedcontainers/ it might offer a good approach to your problem.
I am using the Neo library for linear algebra in Nim, and I would like to extract arbitrary rows from a matrix.
I can explicitly select a continuous sequence of rows as per the examples in the README, but can't select a disjoint subset of rows.
import neo
let x = randomMatrix(10, 4)
let some_rows = #[1,3,5]
echo x[2..4, All] # works fine
echo x[some_rows, All] ## error
The first echo works because you are creating a Slice object, which neo has defined a proc for. The second echo uses a sequence of integers, and that kind of access is not defined in the neo library. Unfortunately Slices define contiguous closed ranges, you can't even specify steps to iterate in bigger increments than one, so there is no way to accomplish what you want.
Looking at the structure of a Matrix, it seems that it is highly optimised to avoid copying data. Matrix transformation operations seem to reuse the data of the previous matrix and change the access/dimensions. As such, a matrix transformation with arbitrary random would not be possible, the indexes in your example specifically access non contiguos data and this would need to be encoded somehow in the new structure. Plus if you wrote #[1,5,3] that would defeat any kind of normal iterative looping.
An alternative of course is to write a proc which accepts a sequence instead of a slice and then builds a new matrix copying data from the old one. This implies a performance penalty, but if you think this is a good addition to the library please request it in the issue tracker of the project. If it is not accepted, then you will need to write yourself such a proc for personal use in your programs.
In Ruby Programming language myList.shuffle.first is slower than myList.sample since it completely shuffle the list and pick the first element. If something similar (shuffle and take first) is done in Haskell, will that be as fast as the later (sampling the array)? I am assuming that the list will be shuffled lazily so picking the first element or taking the sample will be virtually same.
It can be written to behave that way, using the decorate-sort-undecorate pattern: first label each element in your list with a random number; sort by the labels; throw away the labels; and take the first element. The standard implementation of sort will make this an O(n) operation, just like sampling would be. Not sure if there are any packages that offer this out of the box, and of course the manually written version of the algorithm may have better constants.
I am doing a project where I would like to vectorize (if possible), these lines of code in Matlab:
for j=1:length(image_feature(i,:))
string1b=strcat(num2str(j),':',num2str(image_feature(i,j)));
write_file1b=[write_file1b string1b ' '];
end
Basically, what I want to get is an output string in the following way:
1:Value1 2:Value2 3:Value3 ....
Note that ValueX is a number so a real example would be an output like this:
1:23.2 2:34.3 3:110.8
Is this possible? I was thinking about doing something like creating another vector with values from 1 to j, and another j-long vector with only ":", and a num2str(image_feature(i,:)), and then hopefully there is a function f (like a vectorized strcat) that if I do:
f(num2str(1:j),colon_vector,num2str(image_feature(i,:)))
will give me the output I mention above.
Im not sure I understood your question but perhaps this might help
val=[23.2 34.3 110.8]
output = [1:length(val); val]
sprintf('%i: %f ',output)
As output I get
1: 23.200000 2: 34.300000 3: 110.800000
You can vectorize all your array operations to create an array or matrix of numbers very efficiently, but by the very nature of strings in MATLAB, you cannot vectorize the creation of your output string. Theoretically, if you have a fixed length string like in C++, you could concurrently write to different memory locations within the string, but that is not something that is supported by MATLAB. Even if it were, it looks like you have variable-length numbers, so even that would be difficult (unless you were to allocate a specific amount of space per number pair, leading to variable-length spaces between number pairs. It doesn't look like you want to do that, since your examples have exactly one space between all number pairs).
If you'd be interested in efficiently creating a vector, the answer provided by twerdster would accomplish that, but even in that code, the sprintf statement is not concurrent. His code does get rid of the for-loop, which improves efficiency, so I prefer his code to yours.
I think the best way to form this question is with an example...so, the actual reason I decided to ask about this is because of because of Problem 55 on Project Euler. In the problem, it asks to find the number of Lychrel numbers below 10,000. In an imperative language, I would get the list of numbers leading up to the final palindrome, and push those numbers to a list outside of my function. I would then check each incoming number to see if it was a part of that list, and if so, simply stop the test and conclude that the number is NOT a Lychrel number. I would do the same thing with non-lychrel numbers and their preceding numbers.
I've done this before and it has worked out nicely. However, it seems like a big hassle to actually implement this in Haskell without adding a bunch of extra arguments to my functions to hold the predecessors, and an absolute parent function to hold all of the numbers that I need to store.
I'm just wondering if there is some kind of tool that I'm missing here, or if there are any standards as a way to do this? I've read that Haskell kind of "naturally caches" (for example, if I wanted to define odd numbers as odds = filter odd [1..], I could refer to that whenever I wanted to, but it seems to get complicated when I need to dynamically add elements to a list.
Any suggestions on how to tackle this?
Thanks.
PS: I'm not asking for an answer to the Project Euler problem, I just want to get to know Haskell a bit better!
I believe you're looking for memoizing. There are a number of ways to do this. One fairly simple way is with the MemoTrie package. Alternatively if you know your input domain is a bounded set of numbers (e.g. [0,10000)) you can create an Array where the values are the results of your computation, and then you can just index into the array with your input. The Array approach won't work for you though because, even though your input numbers are below 10,000, subsequent iterations can trivially grow larger than 10,000.
That said, when I solved Problem 55 in Haskell, I didn't bother doing any memoization whatsoever. It turned out to just be fast enough to run (up to) 50 iterations on all input numbers. In fact, running that right now takes 0.2s to complete on my machine.