Gaz wrote: > Hi guys. I've been lookig for this in the numpy pdf manual, in this > group and on google, but i could not get an answer...
You will probably want to look or ask on the numpy list, too. https://lists.sourceforge.net/lists/listinfo/numpy-discussion > Is there a way to create a custom data type (eg: Name: string(30), Age: > int(2), married: boolean, etc) and then use that custom data in a > matrix? Actually, this is a two question question :P Yes. Use record arrays. They are discussed in section 8.5 of the _The Guide to NumPy_ if you have the book. There is another example of using record arrays on the SciPy wiki (although it is less focused on combining different data types than it is named column access): http://www.scipy.org/RecordArrays Here is an example: In [18]: from numpy import * In [19]: rec.fromrecords([['Robert', 25, False], ['Thomas', 53, True]], names='name,age,married', formats=['S30', int, bool]) Out[19]: recarray([('Robert', 25, False), ('Thomas', 53, True)], dtype=[('name', '|S30'), ('age', '>i4'), ('married', '|b1')]) In [21]: Out[19].name Out[21]: chararray([Robert, Thomas], dtype='|S30') In [22]: Out[19].age Out[22]: array([25, 53]) In [23]: Out[19].married Out[23]: array([False, True], dtype=bool) You can also use object arrays if you need to implement classes and not just dumb, basic types: In [33]: class Hex(dict): ....: def __init__(self, **kwds): ....: dict.__init__(self, **kwds) ....: self.__dict__ = self ....: ....: In [34]: field = array([Hex(color=(0,0,0), owner='Player1', x=10, y=20, etc='Black hex owned by Player1'), ....: Hex(color=(1,1,1), owner='Player2', x=10, y=21, etc='White hex owned by Player2')], dtype=object) In [35]: In [35]: field Out[35]: array([{'y': 20, 'etc': 'Black hex owned by Player1', 'color': (0, 0, 0), 'owner': 'Player1', 'x': 10}, {'y': 21, 'etc': 'White hex owned by Player2', 'color': (1, 1, 1), 'owner': 'Player2', 'x': 10}], dtype=object) -- Robert Kern [EMAIL PROTECTED] "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco -- http://mail.python.org/mailman/listinfo/python-list
