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Always!
29%
It depends
14%
Never!
21%
I didn't know that was possible
36%
1810 个投票
Base case:
Suppose you need to do a computation many times. We are going to assume that this computation cannot be vectorized. The simplest case is to use a for loop:
number_of_elements = 1e6;
test_fcn = @(x) sqrt(x) / x;
tic
for i = 1:number_of_elements
x(i) = test_fcn(i);
end
t_forward = toc;
disp(t_forward + " seconds")
Preallocation:
This can easily be sped up by preallocating the variable that houses results:
tic
x = zeros(number_of_elements, 1);
for i = 1:number_of_elements
x(i) = test_fcn(i);
end
t_forward_prealloc = toc;
disp(t_forward_prealloc + " seconds")
In this example, preallocation speeds up the loop by a factor of about three to four (running in R2024a). Comment below if you get dramatically different results.
disp(sprintf("%.1f", t_forward / t_forward_prealloc))
Run it in reverse:
Is there a way to skip the explicit preallocation and still be fast? Indeed, there is.
clear x
tic
for i = number_of_elements:-1:1
x(i) = test_fcn(i);
end
t_backward = toc;
disp(t_backward + " seconds")
By running the loop backwards, the preallocation is implicitly performed during the first iteration and the loop runs in about the same time (within statistical noise):
disp(sprintf("%.2f", t_forward_prealloc / t_backward))
Do you get similar results when running this code? Let us know your thoughts in the comments below.
Beneficial side effect:
Have you ever had to use a for loop to delete elements from a vector? If so, keeping track of index offsets can be tricky, as deleting any element shifts all those that come after. By running the for loop in reverse, you don't need to worry about index offsets while deleting elements.
quick / easy
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themed / in a group
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challenge (e.g., banned functions)
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puzzle / game
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educational
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other (comment below)
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117 个投票
isstring
11%
ischar
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iscellstr
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isletter
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isspace
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ispunctuation
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2455 个投票
Don't use / What are Projects?
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1–10
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11–20
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21–30
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31–50
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51+ (comment below)
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4070 个投票
2
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3
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4
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6
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8
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Other (comment below)
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6419 个投票
numel(v)
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length(v)
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width(v)
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nnz(v)
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size(v, 1)
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sum(v > 0)
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2537 个投票
ismissing( { [ ] } )
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ismissing( NaN )
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ismissing( NaT )
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ismissing( missing )
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ismissing( categorical(missing) )
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ismissing( { '' } ) % 2 apostrophes
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896 个投票
isempty( [ ] )
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isempty( { } )
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isempty( '' ) % 2 single quotes
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isempty( "" ) % 2 double quotes
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c = categorical( [ ] ); isempty(c)
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s = struct("a", [ ] ); isempty(s.a)
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1324 个投票
sort(v)
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unique(v)
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union(v, [ ])
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intersect(v, v)
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setdiff(v, [ ])
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All return sorted output
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1193 个投票
s = ['M','A','T','L','A','B']
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char([77,65,84,76,65,66])
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"MAT" + "LAB"
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upper(char('matlab' - '0' + 48))
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fliplr("BALTAM")
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rot90(rot90('BALTAM'))
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2929 个投票
eye(3) - diag(ones(1,3))
11%
0 ./ ones(3)
9%
cos(repmat(pi/2, [3,3]))
16%
zeros(3)
20%
A(3, 3) = 0
32%
mtimes([1;1;0], [0,0,0])
12%
3009 个投票
Have you ever learned that something you were doing manually in MATLAB was already possible using a built-in feature? Have you ever written a function only to later realize (or be told) that a built-in function already did what you needed?
Two such moments come to mind for me.
1. Did you realize that you can set conditional breakpoints? Neither did I, until someone showed me that feature. To do that, open or create a file in the editor, right click on a line number for any line that contains code, and select Set Conditional Breakpoint... This will bring up a dialog wherein you can type any logical condition for which execution should be paused. Before I learned about this, I would manually insert if-statements during debugging. Then, after fixing each bug, I would have to delete those statements. This built-in feature is so much better.
2. Have you ever needed to plot horizontal or vertical lines in a plot? For the longest time, I would manually code such lines. Then, I learned about xline() and yline(). Not only is less code required, these lines automatically span the entire axes while zooming, panning, or adjusting axis limits!
Share your own Aha! moments below. This will help everyone learn about MATLAB functionality that may not be obvious or front and center.
(Note: While File Exchange contains many great contributions, the intent of this thread is to focus on built-in MATLAB functionality.)
1
33%
2
34%
3
18%
4
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5
3%
6+
6%
1643 个投票
<= 6 GB
10%
7–12 GB
26%
13–22 GB
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23–46 GB
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47–90 GB
6%
>= 91 GB
6%
15925 个投票
Yes, the available tools are great
12%
Yes, the available tools need help
6%
No, but I would like to
14%
No, it is not important to me
7%
What is test-driven development?
61%
1955 个投票
Always
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Sometimes
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In the past, but not now
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Never
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What is Simulink Project?
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2443 个投票
Always
8%
Sometimes
9%
In the past, but not now
2%
Never
23%
What is MATLAB Project?
58%
4533 个投票
A bunch of quick, simple problems
16%
A structured, educational set
15%
Brain-teasers
16%
Random miscellany
3%
Something else
2%
What are Problem Groups?
49%
1777 个投票
Cody has a wealth of problem groups that allow users of various skill levels to improve programming skills vis-à-vis MATLAB in an engaging way.
I would like to highlight the Draw Letters group, composed of problems created by Majid Farzaneh.
If you haven't yet visited Cody or solved that problem group, I would recommend that you head over there now. What are you waiting for?