Marlin Rowley wrote:
All:
Say I have an array:
a = (['rrrrggggbbbbaaaa'],['rrrrggggbbbbaaaa'])
How do I make it so that I now have:
starting with first element (a[0])
new_arr[0] = 'r'
new_arr[1] = 'g'
new_arr[2] = 'b'
new_arr[3] = 'a'
new_arr[4] = 'r'
.....
continuing "through" a[1] with the same new_arr
new_arr[N] = 'r'
new_arr[N+1] = 'g'
....
-M
Numpy can do this for you. First, do you really mean the array to
contain lists of one string each? If so:
>>> import numpy
>>> a = (['rrrrggggbbbbaaaa'],['rrrrggggbbbbaaaa'])
>>> b = numpy.frombuffer(''.join(sum(a,[])),dtype='S1') # Kind of a
kludge here
>>> b
array(['r', 'r', 'r', 'r', 'g', 'g', 'g', 'g', 'b', 'b', 'b', 'b', 'a',
'a', 'a', 'a', 'r', 'r', 'r', 'r', 'g', 'g', 'g', 'g', 'b', 'b',
'b', 'b', 'a', 'a', 'a', 'a'],
dtype='|S1')
>>> b.shape=(2,4,4)
>>> b
array([[['r', 'r', 'r', 'r'],
['g', 'g', 'g', 'g'],
['b', 'b', 'b', 'b'],
['a', 'a', 'a', 'a']],
[['r', 'r', 'r', 'r'],
['g', 'g', 'g', 'g'],
['b', 'b', 'b', 'b'],
['a', 'a', 'a', 'a']]],
dtype='|S1')
>>> c = b.transpose((2,0,1))
>>> c
array([[['r', 'g', 'b', 'a'],
['r', 'g', 'b', 'a']],
[['r', 'g', 'b', 'a'],
['r', 'g', 'b', 'a']],
[['r', 'g', 'b', 'a'],
['r', 'g', 'b', 'a']],
[['r', 'g', 'b', 'a'],
['r', 'g', 'b', 'a']]],
dtype='|S1')
>>> d=c.copy() # To make it contiguous
>>> d.shape = (32,)
>>> d
array(['r', 'g', 'b', 'a', 'r', 'g', 'b', 'a', 'r', 'g', 'b', 'a', 'r',
'g', 'b', 'a', 'r', 'g', 'b', 'a', 'r', 'g', 'b', 'a', 'r', 'g',
'b', 'a', 'r', 'g', 'b', 'a'],
dtype='|S1')
Done. Cool no?
Gary Herron
------------------------------------------------------------------------
From: [EMAIL PROTECTED]
To: [EMAIL PROTECTED]; python-list@python.org
Subject: RE: numpy.frombuffer != unpack() ??
Date: Fri, 16 May 2008 17:31:30 -0500
Thank you! That solved it!
-M
------------------------------------------------------------------------
> To: python-list@python.org
> From: [EMAIL PROTECTED]
> Subject: Re: numpy.frombuffer != unpack() ??
> Date: Fri, 16 May 2008 17:25:00 -0500
>
> Marlin Rowley wrote:
> > All:
> >
> > I'm getting different floating point values when I use numpy
vs. unpack().
> >
> > frgba = numpy.frombuffer(<string of bytes>, dtype=float32)
> > buffer = unpack("!f", byte)
> >
> > frgba[0] != buffer[0]
> >
> > why? This is forcing me use the unpack() function since it's
giving me
> > the correct values. What am I doing wrong?
>
> Endianness, perhaps? '!' specifies big-endian data (an alias for
'>'). Most
> likely, you are on a little-endian platform. All of the dtypes
in numpy default
> to the native-endianness unless specified. If you want to read
big-endian data
> using numpy, do this:
>
> frgba = numpy.frombuffer(<string of bytes>, dtype='>f')
>
> If you have any more problems with numpy, please join us on the
numpy mailing
> list. When reporting problems, please try to provide a small but
complete
> snippet of self-contained code, the output that you got, and
explain the output
> that you expected to get. Thank you.
>
> http://www.scipy.org/Mailing_Lists
>
> --
> Robert Kern
>
> "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
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