Initialize Multiple Numpy Arrays (Multiple Assignment) - Like MATLAB deal()

Question

I was unable to find anything describing how to do this, which leads to be believe I\'m not doing this in the proper idiomatic Python way. Advice on the \'proper\' Python w

Answer 1

Nothing wrong or un-Pythonic with

dData = np.zeros(n)
gData = np.zeros(n)
etc.

You could put them on one line, but there's no particular reason to do so.

dData, gData = np.zeros(n), np.zeros(n)

Don't try dData = gData = np.zeros(n), because a change to dData changes gData (they point to the same object). For the same reason you usually don't want to use x = y = [].

The deal in MATLAB is a convenience, but isn't magical. Here's how Octave implements it

function [varargout] = deal (varargin)
  if (nargin == 0)
    print_usage ();
  elseif (nargin == 1 || nargin == nargout)
    varargout(1:nargout) = varargin;
  else
    error ("deal: nargin > 1 and nargin != nargout");
  endif

endfunction

In contrast to Python, in Octave (and presumably MATLAB)

one=two=three=zeros(1,3)

assigns different objects to the 3 variables.

Notice also how MATLAB talks about deal as a way of assigning contents of cells and structure arrays. http://www.mathworks.com/company/newsletters/articles/whats-the-big-deal.html