Tips and tricks

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Tiny helper functions

This is a list of tiny helper functions (the equivalent of e.g., shell aliases), the kind one would have on its .octaverc file.

replace help with man

If you use octave too much, you'll find yourself trying to use help instead of man on bash. This function will fix that so you can use man in your octave instance (you can also do the opposite, create a help alias in bash but man has less characters).

Code: alias to help
 function man (name)
   help (char (name))


Real matrix operations

This is a table of matrix operations commonly performed in Octave and their equivalents in C++ when using the octave libraries.

matrix multiplicationA*BA*B
element multiplicationA.*Bproduct(A,B)
element divisionA./Bquotient(A,B)
select element m,n of A**A(m,n)A(m-1,n-1)
select row N of A**A(N,:)A.row(N-1)
select column N of A**A(:,N)A.column(N-1)
extract submatrix of AA(a:b,c:d)A.extract(a-1,c-1,b-1,d-1)
absolute value of Aabs(A)A.abs()
comparison to scalar***A>2mx_el_gt(A,2)
matrix of zerosA=zeros(m,n)A.fill(0.0)
matrix of onesA=ones(m,n)A.fill(1.0)
identity matrixeye(N)identity_matrix(N,N)
inverse of Ainv(A)A.inverse()
pseudoinverse of Apinv(A)A.pseudo_inverse()
diagonal elements of Adiag(A)A.diag()
column vectorA(:)ColumnVector(A.reshape (dim_vector(A.length())))
row vectorA(:)'RowVector(A.reshape (dim_vector(A.length())))
check for Inf or NaNany(~isfinite(A))A.any_element_is_inf_or_nan()
stack two matrices verticallyA=[B;C]B.stack(C)
uniform random matrixrand(a,b)octave_rand::distribution("uniform"); octave_rand::matrix(a,b)
normal random matrixrandn(a,b)octave_rand::distribution("normal"); octave_rand::matrix(a,b)
sum squares of columnssumsq(A)A.sumsq()
sum along columnssum(A,1)A.sum(0)
sum along rowssum(A,2)A.sum(1)
product along columnsprod(A,1)
product along rowsprod(A,2)
cumsum along columnscumsum(A,1)A.cumsum(0)
cumsum along rowscumsum(A,2)A.cumsum(1)
cumproduct along columnscumprod(A,1)A.cumprod(0)
cumproduct along rowscumprod(A,2)A.cumprod(1)
number of rowssize(A,1)A.rows()
number of columnssize(A,2)A.cols()


  • Transpose, addition, and multiplication operations also apply to RowVector, ComplexRowVector, ColumnVector, and ComplexColumnVector data types when the dimensions are in agreement.
  • The difference is due to the fact that arrays are zero-based in C++, but one-based in Octave.
  • The names of Octave internal functions, such as mx_el_gt, are not documented and are subject to change. Functions such as mx_el_gt may eventually be available at both the scripting level and in C++ under more common names such as gt.

Complex Matrix Operations

conjugate tranposeA'A.hermitian()


Vectorizing Tricks

You can easily fill a vector with an index:

   for i=1:n, x(i) = i; end
   x = 1:n;

This works for expressions on the index by wrapping the index in an expression:

   for i=1:n, x(i) = sin(2*pi*i*f/r); end
   x = sin(2*pi*(1:n)*f/r);

You can also work with other vectors this way:

   for i=1:n, x(i) = sin(2*pi*y(i)*f/r); end
   x = sin(2*pi*y*f/r);

Conditionals in the for loop are a little bit tricky. We need to create an index vector for the true condition, and another for the false condition, then calculate the two independently.

   for i=1:n, if y(i)<1, x(i)=y(i); else x(i) = 2*y(i); endif
   idx = y < 1;
   x(idx) = y(idx);
   x(!idx) = 2*y(!idx);

FIXME: add the following

  • examples from matrices
  • tricks with sort and cumsum (e.g., hist, lookup)
  • counter-examples such as a tridiagonal solver
  • sparse matrix tricks
  • tricks relying on fortran indexing

Other references