On Tue, Aug 2, 2011 at 9:44 AM, Jeremy Conlin <jlcon...@gmail.com> wrote:
> I am trying to create a numpy array from some text I'm reading from a
> file. Ideally, I'd like to create a structured array with the first
> element as an int and the remaining as floats. I'm currently
> unsuccessful in my attempts. I've copied a simple script below that
> shows what I've done and the wrong output. Can someone please show me
> what is happening?
>
> I'm using numpy version 1.5.1 under Python 2.7.1 on a Mac running Snow
> Leopard.
>
> Thanks,
> Jeremy
I'd use numpy.loadtxt:
In [1]: import numpy, StringIO
In [2]: l = ' 32000 7.89131E-01 8.05999E-03 3.88222E+03'
In [3]: tfc_dtype = numpy.dtype([('nps', 'u8'), ('t', 'f8'), ('e',
'f8'), ('fom', 'f8')])
In [4]: input = StringIO.StringIO(l)
In [5]: numpy.loadtxt(input, dtype=tfc_dtype)
Out[5]:
array((32000L, 0.78913100000000003, 0.0080599899999999995, 3882.2199999999998),
dtype=[('nps', '<u8'), ('t', '<f8'), ('e', '<f8'), ('fom', '<f8')])
In [6]: input.close()
In [7]: input = StringIO.StringIO(l)
In [8]: numpy.loadtxt(input)
Out[8]:
array([ 3.20000000e+04, 7.89131000e-01, 8.05999000e-03,
3.88222000e+03])
In [9]: input.close()
If you're reading from a file you can replace the StringIO objects
with file objects.
~Brett
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