[Numpy-discussion] How to start at line # x when using numpy.memmap
Brent Pedersen
bpederse@gmail....
Fri Aug 19 10:18:12 CDT 2011
On Fri, Aug 19, 2011 at 9:09 AM, Jeremy Conlin <jlconlin@gmail.com> wrote:
> On Fri, Aug 19, 2011 at 8:01 AM, Brent Pedersen <bpederse@gmail.com> wrote:
>> On Fri, Aug 19, 2011 at 7:29 AM, Jeremy Conlin <jlconlin@gmail.com> wrote:
>>> On Fri, Aug 19, 2011 at 7:19 AM, Pauli Virtanen <pav@iki.fi> wrote:
>>>> Fri, 19 Aug 2011 07:00:31 -0600, Jeremy Conlin wrote:
>>>>> I would like to use numpy's memmap on some data files I have. The first
>>>>> 12 or so lines of the files contain text (header information) and the
>>>>> remainder has the numerical data. Is there a way I can tell memmap to
>>>>> skip a specified number of lines instead of a number of bytes?
>>>>
>>>> First use standard Python I/O functions to determine the number of
>>>> bytes to skip at the beginning and the number of data items. Then pass
>>>> in `offset` and `shape` parameters to numpy.memmap.
>>>
>>> Thanks for that suggestion. However, I'm unfamiliar with the I/O
>>> functions you are referring to. Can you point me to do the
>>> documentation?
>>>
>>> Thanks again,
>>> Jeremy
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion@scipy.org
>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>
>> this might get you started:
>>
>>
>> import numpy as np
>>
>> # make some fake data with 12 header lines.
>> with open('test.mm', 'w') as fhw:
>> print >> fhw, "\n".join('header' for i in range(12))
>> np.arange(100, dtype=np.uint).tofile(fhw)
>>
>> # use normal python io to determine of offset after 12 lines.
>> with open('test.mm') as fhr:
>> for i in range(12): fhr.readline()
>> offset = fhr.tell()
>>
>> # use the offset in your call to np.memmap.
>> a = np.memmap('test.mm', mode='r', dtype=np.uint, offset=offset)
>
> Thanks, that looks good. I tried it, but it doesn't get the correct
> data. I really don't understand what is going on. A simple code and
> sample data is attached if anyone has a chance to look at it.
>
> Thanks,
> Jeremy
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
in that case, i would use:
np.loadtxt('tmp.dat', skiprows=12)
More information about the NumPy-Discussion
mailing list