[Matplotlib-users] load function

[Humufr <hu...@ya...>]

         Hi John,

I did some change in the load function, it's help for me so perhaps some 
other people will appreciate it. I add the possibility to choose which 
columns inside a file you want use.

ex: I have a file like:

1 2 3
1 2 3
1 2 3

and I want use only the columns 2 and 3:

so I can do this with the new load function:

load('toto.dat',columns=[2,3])

Perhaps you can arrange this to have something a little bit cleaner (I'm 
a beginner with python).

I add the change to have the matrix transpose too to correct the problem 
I hab before to recuperate the columns and not the lines when you are doing:

x,y,z = load('toto.dat')

Thanks,

         Nicolas

ps: I add something inside the doc but you had to correct this too for a 
correct english or/and more understandable text if you include these 
changes.

------------------------------------------------------------

def load(fname,comments='%',columns=None):
   """
   Load ASCII data from fname into an array and return the array.

   The data must be regular, same number of values in every row

   fname can be a filename or a file handle.

   A character for to delimit the comments can be use (optional),

   the default is the matlab character '%'.

   An second optional argument can be add, to tell which columns you
      want use in the file. This arguments is a list who contains the
      number of columns beggining by 1.

   matfile data is not currently supported, but see
   Nigel Wade's matfile ftp://ion.le.ac.uk/matfile/matfile.tar.gz

   Example usage:

   x,y = load('test.dat')  # data in two columns

   X = load('test.dat')    # a matrix of data

   x = load('test.dat')    # a single column of data

   x = load('test.dat,'#') # the character use like a comment delimiter 
is '#'

   """

   if is_string_like(fname):
       fh = file(fname)
   elif hasattr(fname, 'seek'):
       fh = fname
   else:
       raise ValueError('fname must be a string or file handle')
      X = []
   numCols = None
   for line in fh:
       line = line[:line.find(comments)].strip()
       if not len(line): continue
       row = [float(val) for val in line.split()]
       thisLen = len(row)
       if numCols is not None and thisLen != numCols:
           raise ValueError('All rows must have the same number of 
columns')
       if columns is not None:
           row = [row[i] for i in (array(columns)-1)]
       X.append(row)

   X = array(X)
   r,c = X.shape
   if r==1 or c==1:
       X.shape = max([r,c]),
   return transpose(X)