A simple Octave tip


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Matlab and Octave are both great for quickly trying out numeric code, especially using linear algebra. Many times code can be written to use the built in matrix operators instead of using loops. This makes the code clearer and faster. The following examples all use Octave.

First, consider this formula

\begin{equation*} S = \sum_{i=1}^n x_i y_i \end{equation*}

x and y are one dimensional vectors in Octave, so we can find \(S\) with this code:

S = 0;
N = length(x);
for i = 1:N
  S += x(i) * y(i);
end

That code is straight forward. Octave can do more, though. The =.*= operator does an element by element multiplication over matrices, and =sum= adds up the elements in a matrix. Since our matrices are one-dimensional, we can compose these functions to get our result, at the cost of creating a temporary matrix.

S = sum(x .* y)

Finally, Octave already has a function that does what we want. The formula we are looking at is the dot product of two vectors, so in Octave, we can do

S = dot(x, y)

The first attempt is the clearest when you do not know what .*, sum, and dot do. But, once you know what sum and dot do, they are much clearer. Also, they are much faster in Octave than the naive loop.

The next listing shows a test driver to compare the three methods.

fprintf("\n||||\n| method | size| result | time |\n")
fmt = "| %s | %d | %f | %f |\n";

for SIZE = [100, 1000,10000,100000,1000000]
    x = rand(SIZE, 1);
    y = rand(SIZE, 1);

    fprintf("|---\n")
    tic
    S = 0;
    for i = 1:SIZE
      S += x(i) * y(i);
    end
    t1 = toc;
    fprintf(fmt, "for", SIZE, S, t1);

    tic
    S = sum(x .* y);
    t1 = toc;
    fprintf(fmt, "sum", SIZE, S, t1);

    tic
    S = dot(x, y);
    t1 = toc;
    fprintf(fmt, "dot", SIZE, S, t1);
  end

Running this code gives us the following results.

method size result time
for 100 24.266291 0.000744
sum 100 24.266291 0.000055
dot 100 24.266291 0.000018
for 1000 247.065638 0.007198
sum 1000 247.065638 0.000016
dot 1000 247.065638 0.000017
for 10000 2507.387623 0.074163
sum 10000 2507.387623 0.000083
dot 10000 2507.387623 0.000029
for 100000 25090.247927 0.736105
sum 100000 25090.247927 0.000656
dot 100000 25090.247927 0.000095
for 1000000 249863.296971 7.334975
sum 1000000 249863.296971 0.006773
dot 1000000 249863.296971 0.001246

As a general rule, we should always try to use the language and tools, instead of doing things ourselves. Often, this is mostly a matter of learning what is available.

Sometimes, though we want to learn how something works. Then, of course, it makes sense to do it ourselves instead of just making a call to existing code.