Using Accumarray with @maxk instead of @max?
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Ayman Al-Sukhon
on 16 Dec 2019
Commented: Ayman Al-Sukhon
on 17 Dec 2019
Hi,
Say you have three vectors:
a = [1;2;3;4;5;1;3;1;4];
b = [100;200;300;400;500;400;300;200;100];
c = [123;456;221;111;800;1000;10;25;150];
And you use accumarray so that:
maxval = sparse(accumarray(a(:,1),max(b,c),[],@max))
You get:
maxval =
(1,1) 1000
(2,1) 456
(3,1) 300
(4,1) 400
(5,1) 800
Now lets, say I have a whole lot of variables for each subs (something like 2000 each), and I want the average of the top 3 values using the same method. How can I accomplish this? For example, in the same problem, I want my output to be:
The top three values with subs 1 are: 100,400 and 200, so their average is 233.33 and the first row in my sparse matrix is:
maxval =
(1,1) 1000
and so on.
Is it maybe possible to use maxk as a function handle?
0 Comments
Accepted Answer
Walter Roberson
on 16 Dec 2019
accumarray(a(:,1), max(b,c), [], @(v) mean(maxk(v,3)), 0, true) %final parameter is sparse flag
3 Comments
dpb
on 17 Dec 2019
@() is the preamble to define an anonymous function. The v is the dummy argument variable name Walter chose; you'll see it reflected in the argument to maxk().
All the details about anonymous functions is in the documentation under the general subject of functions.
More Answers (1)
dpb
on 16 Dec 2019
Edited: dpb
on 16 Dec 2019
Don't see anyway around with accumarray because the VAL parameter must be 1:1 with rows of SUBS; use findgroups/splitapply or varfun (altho latter must be table or timetable).
g=findgroups(a);
mnk=splitapply(@(x) mean(maxk(x,3)),b,g);
yields
>> mnk =
233.3333
200.0000
300.0000
250.0000
500.0000
>>
7 Comments
dpb
on 16 Dec 2019
What it looked like to me, too, Walter.
Your's works for the specific instance (or anywhere sum is the needed intemediary); however in the followup here I was thinking of the more general cases where the function needs the elements rather than a single result.
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